04625nas a2201141 4500008004100000022001400041245011000055210006900165260000900234300001200243490000700255520126600262653002401528653001301552653002301565653001101588653001501599653002001614100001901634700002301653700002201676700002101698700002001719700002301739700002101762700002601783700001901809700002001828700001901848700002201867700002301889700002401912700001701936700002101953700001701974700001601991700002402007700002502031700002502056700002302081700002302104700002702127700002402154700001602178700002102194700002602215700002502241700002102266700002102287700001902308700003202327700002102359700002202380700002002402700001902422700002602441700001802467700001802485700002302503700002102526700001902547700001902566700002202585700001802607700001902625700001802644700002302662700001802685700002002703700001902723700003302742700002602775700002702801700002502828700002302853700001802876700002302894700001702917700002402934700001802958700002202976700002502998700002003023700002303043700002003066700002603086700002003112700001903132700002203151700002203173700002003195700002303215700002103238700001803259700002403277710003503301856014703336 2024 eng d a1664-322400aDrug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.0 aDrugtarget identification in COVID19 disease mechanisms using co c2023 a12828590 v143 a
INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.
METHODS: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.
RESULTS: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.
DISCUSSION: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.
10aComputer Simulation10aCOVID-1910adrug repositioning10aHumans10aSARS-CoV-210aSystems biology1 aNiarakis, Anna1 aOstaszewski, Marek1 aMazein, Alexander1 aKuperstein, Inna1 aKutmon, Martina1 aGillespie, Marc, E1 aFunahashi, Akira1 aAcencio, Marcio, Luis1 aHemedan, Ahmed1 aAichem, Michael1 aKlein, Karsten1 aCzauderna, Tobias1 aBurtscher, Felicia1 aYamada, Takahiro, G1 aHiki, Yusuke1 aHiroi, Noriko, F1 aHu, Finterly1 aPham, Nhung1 aEhrhart, Friederike1 aWillighagen, Egon, L1 aValdeolivas, Alberto1 aDugourd, Aurélien1 aMessina, Francesco1 aEsteban-Medina, Marina1 aPeña-Chilet, Maria1 aRian, Kinza1 aSoliman, Sylvain1 aAghamiri, Sara, Sadat1 aPuniya, Bhanwar, Lal1 aNaldi, Aurélien1 aHelikar, Tomáš1 aSingh, Vidisha1 aFernández, Marco, Fariñas1 aBermudez, Viviam1 aTsirvouli, Eirini1 aMontagud, Arnau1 aNoël, Vincent1 aPonce-de-Leon, Miguel1 aMaier, Dieter1 aBauch, Angela1 aGyori, Benjamin, M1 aBachman, John, A1 aLuna, Augustin1 aPiñero, Janet1 aFurlong, Laura, I1 aBalaur, Irina1 aRougny, Adrien1 aJarosz, Yohan1 aOverall, Rupert, W1 aPhair, Robert1 aPerfetto, Livia1 aMatthews, Lisa1 aRex, Devasahayam, Arokia Bal1 aOrlic-Milacic, Marija1 aGomez, Luis, Cristobal1 aDe Meulder, Bertrand1 aRavel, Jean, Marie1 aJassal, Bijay1 aSatagopam, Venkata1 aWu, Guanming1 aGolebiewski, Martin1 aGawron, Piotr1 aCalzone, Laurence1 aBeckmann, Jacques, S1 aEvelo, Chris, T1 aD'Eustachio, Peter1 aSchreiber, Falk1 aSaez-Rodriguez, Julio1 aDopazo, Joaquin1 aKuiper, Martin1 aValencia, Alfonso1 aWolkenhauer, Olaf1 aKitano, Hiroaki1 aBarillot, Emmanuel1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard1 aCOVID-19 Disease Map Community uhttps://www.clinbioinfosspa.es/content/drug-target-identification-covid-19-disease-mechanisms-using-computational-systems-biology-approaches-000729nam a2200205 4500008004100000020002200041022001400063245010000077210006900177260003800246300001200284490001000296100002000306700002500326700003000351700003600381700002000417700002000437856006600457 2023 eng d a978-3-031-42696-4 a0302-974300aCell-Level Pathway Scoring Comparison with a Biologically Constrained Variational Autoencoder0 aCellLevel Pathway Scoring Comparison with a Biologically Constra aChambSpringer Nature Switzerland a62 - 770 v141371 aGundogdu, Pelin1 aPayá-Milans, Miriam1 aAlamo-Alvarez, Inmaculada1 aNepomuceno-Chamorro, Isabel, A.1 aDopazo, Joaquin1 aLoucera, Carlos uhttps://link.springer.com/chapter/10.1007/978-3-031-42697-1_502250nas a2200253 4500008004100000022001400041245013700055210006900192260001600261490000700277520134400284100002701628700002001655700002401675700002601699700001801725700001801743700002101761700001901782700002801801700002001829700002601849856012101875 2023 eng d a1999-492300aA Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact.0 aComprehensive Analysis of 21 Actionable Pharmacogenes in the Spa c2023 Apr 190 v153 aThe implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.
1 aNúñez-Torres, Rocío1 aPita, Guillermo1 aPeña-Chilet, Maria1 aLópez-López, Daniel1 aZamora, Jorge1 aRoldán, Gema1 aHerráez, Belén1 aAlvarez, Nuria1 aAlonso, María, Rosario1 aDopazo, Joaquin1 aGonzález-Neira, Anna uhttps://www.clinbioinfosspa.es/content/comprehensive-analysis-21-actionable-pharmacogenes-spanish-population-genetic02668nas a2200301 4500008004100000022001400041245008600055210006900141260001600210300000700226490000700233520168700240100002601927700001801953700002901971700002302000700002102023700002102044700002602065700002202091700002002113700002702133700002602160700002402186700002002210710002902230856010702259 2023 eng d a1479-736400aA crowdsourcing database for the copy-number variation of the Spanish population.0 acrowdsourcing database for the copynumber variation of the Spani c2023 Mar 09 a200 v173 aBACKGROUND: Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.
RESULTS: Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ .
CONCLUSION: SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.
1 aLópez-López, Daniel1 aRoldán, Gema1 aFernandez-Rueda, Jose, L1 aBostelmann, Gerrit1 aCarmona, Rosario1 aAquino, Virginia1 aPerez-Florido, Javier1 aOrtuno, Francisco1 aPita, Guillermo1 aNúñez-Torres, Rocío1 aGonzález-Neira, Anna1 aPeña-Chilet, Maria1 aDopazo, Joaquin1 aCSVS Crowdsourcing Group uhttps://www.clinbioinfosspa.es/content/crowdsourcing-database-copy-number-variation-spanish-population02234nas a2200325 4500008004100000022001400041245014800055210006900203260001600272300001100288490000700299520106600306100002701372700003201399700002401431700001701455700002601472700001901498700002101517700001801538700002201556700001701578700001901595700002901614700002001643700002301663700002301686700002401709856017501733 2023 eng d a2211-124700aDefective extracellular matrix remodeling in brown adipose tissue is associated with fibro-inflammation and reduced diet-induced thermogenesis.0 aDefective extracellular matrix remodeling in brown adipose tissu c2023 Jun 13 a1126400 v423 aThe relevance of extracellular matrix (ECM) remodeling is reported in white adipose tissue (AT) and obesity-related dysfunctions, but little is known about the importance of ECM remodeling in brown AT (BAT) function. Here, we show that a time course of high-fat diet (HFD) feeding progressively impairs diet-induced thermogenesis concomitantly with the development of fibro-inflammation in BAT. Higher markers of fibro-inflammation are associated with lower cold-induced BAT activity in humans. Similarly, when mice are housed at thermoneutrality, inactivated BAT features fibro-inflammation. We validate the pathophysiological relevance of BAT ECM remodeling in response to temperature challenges and HFD using a model of a primary defect in the collagen turnover mediated by partial ablation of the Pepd prolidase. Pepd-heterozygous mice display exacerbated dysfunction and BAT fibro-inflammation at thermoneutrality and in HFD. Our findings show the relevance of ECM remodeling in BAT activation and provide a mechanism for BAT dysfunction in obesity.
1 aPellegrinelli, Vanessa1 aFigueroa-Juárez, Elizabeth1 aSamuelson, Isabella1 aU-Din, Mueez1 aRodriguez-Fdez, Sonia1 aVirtue, Samuel1 aLeggat, Jennifer1 aCubuk, Cankut1 aPeirce, Vivian, J1 aNiemi, Tarja1 aCampbell, Mark1 aRodriguez-Cuenca, Sergio1 aDopazo, Joaquin1 aCarobbio, Stefania1 aVirtanen, Kirsi, A1 aVidal-Puig, Antonio uhttps://www.clinbioinfosspa.es/content/defective-extracellular-matrix-remodeling-brown-adipose-tissue-associated-fibro-inflammation-and-reduced-diet-induced-thermogenesis02653nas a2200409 4500008004100000022001400041245014400055210006900199260001600268300000800284490000600292520117700298100002801475700003601503700002001539700001801559700003301577700002901610700003801639700003601677700002601713700003401739700003701773700002701810700002901837700001701866700001901883700002601902700002501928700002001953700001901973700002401992700002902016700003002045700003202075856013602107 2023 eng d a2399-364200aMetabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging.0 aMetabolic reprogramming by Acly inhibition using SB204990 alters c2023 Mar 08 a2500 v63 aATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.
1 aSola-García, Alejandro1 aCáliz-Molina, María, Ángeles1 aEspadas, Isabel1 aPetr, Michael1 aPanadero-Morón, Concepción1 aGonzález-Morán, Daniel1 aMartín-Vázquez, María, Eugenia1 aNarbona-Pérez, Álvaro, Jesús1 aLópez-Noriega, Livia1 aMartínez-Corrales, Guillermo1 aLópez-Fernández-Sobrino, Raúl1 aCarmona-Marin, Lina, M1 aMartínez-Force, Enrique1 aYanes, Oscar1 aVinaixa, Maria1 aLópez-López, Daniel1 aReyes, José, Carlos1 aDopazo, Joaquin1 aMartín, Franz1 aGauthier, Benoit, R1 aScheibye-Knudsen, Morten1 aCapilla-González, Vivian1 aMartín-Montalvo, Alejandro uhttps://www.clinbioinfosspa.es/content/metabolic-reprogramming-acly-inhibition-using-sb-204990-alters-glucoregulation-and-modulates02202nas a2200181 4500008004100000022001400041245011200055210006900167260001600236490000700252520151000259100002001769700002201789700003501811700002001846700002001866856013401886 2023 eng d a2079-773700aSigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types.0 aSigPrimedNet A SignalingInformed Neural Network for scRNAseq Ann c2023 Apr 100 v123 aSingle-cell RNA sequencing is increasing our understanding of the behavior of complex tissues or organs, by providing unprecedented details on the complex cell type landscape at the level of individual cells. Cell type definition and functional annotation are key steps to understanding the molecular processes behind the underlying cellular communication machinery. However, the exponential growth of scRNA-seq data has made the task of manually annotating cells unfeasible, due not only to an unparalleled resolution of the technology but to an ever-increasing heterogeneity of the data. Many supervised and unsupervised methods have been proposed to automatically annotate cells. Supervised approaches for cell-type annotation outperform unsupervised methods except when new (unknown) cell types are present. Here, we introduce SigPrimedNet an artificial neural network approach that leverages (i) efficient training by means of a sparsity-inducing signaling circuits-informed layer, (ii) feature representation learning through supervised training, and (iii) unknown cell-type identification by fitting an anomaly detection method on the learned representation. We show that SigPrimedNet can efficiently annotate known cell types while keeping a low false-positive rate for unseen cells across a set of publicly available datasets. In addition, the learned representation acts as a proxy for signaling circuit activity measurements, which provide useful estimations of the cell functionalities.
1 aGundogdu, Pelin1 aAlamo, Inmaculada1 aNepomuceno-Chamorro, Isabel, A1 aDopazo, Joaquin1 aLoucera, Carlos uhttps://www.clinbioinfosspa.es/content/sigprimednet-signaling-informed-neural-network-scrna-seq-annotation-known-and-unknown-cell02575nas a2200457 4500008004100000022001400041245008300055210006900138260001600207490000700223520116500230653001301395653001801408653001101426653001301437653001401450653001401464653001501478100002001493700002601513700003301539700002501572700002101597700002301618700003201641700003101673700002101704700002901725700002601754700002001780700002501800700002701825700002801852700002301880700002301903700002001926700001801946700002201964700002001986856011102006 2022 eng d a1999-491500aAssessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival.0 aAssessing the Impact of SARSCoV2 Lineages and Mutations on Patie c2022 Aug 270 v143 aOBJECTIVES: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.
METHODS: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.
RESULTS: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.
CONCLUSIONS: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.
10aCOVID-1910aGenome, Viral10aHumans10amutation10aPandemics10aPhylogeny10aSARS-CoV-21 aLoucera, Carlos1 aPerez-Florido, Javier1 aCasimiro-Soriguer, Carlos, S1 aOrtuno, Francisco, M1 aCarmona, Rosario1 aBostelmann, Gerrit1 aMartínez-González, Javier1 aMuñoyerro-Muñiz, Dolores1 aVillegas, Román1 aRodríguez-Baño, Jesús1 aRomero-Gómez, Manuel1 aLorusso, Nicola1 aGarcia-León, Javier1 aNavarro-Marí, Jose, M1 aCamacho-Martinez, Pedro1 aMerino-Diaz, Laura1 ade Salazar, Adolfo1 aViñuela, Laura1 aLepe, Jose, A1 aGarcía, Federico1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/assessing-impact-sars-cov-2-lineages-and-mutations-patient-survival03523nas a2200553 4500008004100000022001400041245007400055210006900129260001300198300001000211490000700221520170300228100002701931700002001958700003101978700002802009700003002037700002502067700001702092700002702109700003202136700002602168700002602194700003502220700003102255700001702286700003102303700003002334700003302364700003302397700003502430700003302465700002502498700003102523700002602554700002502580700002002605700002302625700002302648700002102671700002902692700003102721700002002752700002002772700002102792700002702813710002202840856010702862 2022 eng d a1579-212900aIncidence and Prevalence of Children's Diffuse Lung Disease in Spain.0 aIncidence and Prevalence of Childrens Diffuse Lung Disease in Sp c2022 Jan a22-290 v583 aBACKGROUND: Children's diffuse lung disease, also known as children's Interstitial Lung Diseases (chILD), are a heterogeneous group of rare diseases with relevant morbidity and mortality, which diagnosis and classification are very complex. Epidemiological data are scarce. The aim of this study was to analyse incidence and prevalence of chILD in Spain.
METHODS: Multicentre observational prospective study in patients from 0 to 18 years of age with chILD to analyse its incidence and prevalence in Spain, based on data reported in 2018 and 2019.
RESULTS: A total of 381 cases with chILD were notified from 51 paediatric pulmonology units all over Spain, covering the 91.7% of the paediatric population. The average incidence of chILD was 8.18 (CI 95% 6.28-10.48) new cases/million of children per year. The average prevalence of chILD was 46.53 (CI 95% 41.81-51.62) cases/million of children. The age group with the highest prevalence were children under 1 year of age. Different types of disorders were seen in children 2-18 years of age compared with children 0-2 years of age. Most frequent cases were: primary pulmonary interstitial glycogenosis in neonates (17/65), neuroendocrine cell hyperplasia of infancy in infants from 1 to 12 months (44/144), idiopathic pulmonary haemosiderosis in children from 1 to 5 years old (13/74), hypersensitivity pneumonitis in children from 5 to 10 years old (9/51), and scleroderma in older than 10 years old (8/47).
CONCLUSIONS: We found a higher incidence and prevalence of chILD than previously described probably due to greater understanding and increased clinician awareness of these rare diseases.
1 aTorrent-Vernetta, Alba1 aGaboli, Mirella1 aCastillo-Corullón, Silvia1 aMondéjar-López, Pedro1 aSantiago, Verónica, Sanz1 aCosta-Colomer, Jordi1 aOsona, Borja1 aTorres-Borrego, Javier1 ade la Serna-Blázquez, Olga1 aAlonso, Sara, Bellón1 aAguilera, Pilar, Caro1 ade Atauri, Álvaro, Gimeno-Dí1 aSoria, Alfredo, Valenzuela1 aAyats, Roser1 ade Vicente, Carlos, Martin1 aGonzález, Valle, Velasco1 aGonzález, José, Domingo Mo1 aCalderín, Elisa, María Can1 aPastor-Vivero, María, Dolores1 aÁlvarez, María, Ángeles V1 aRovira-Amigo, Sandra1 aSerrano, Ignacio, Iglesias1 aIzquierdo, Ana, Díez1 aMessa, Inés, de Mir1 aGartner, Silvia1 aNavarro, Alexandra1 aBaz-Redón, Noelia1 aCarmona, Rosario1 aCamats-Tarruella, Núria1 aFernández-Cancio, Mónica1 aRapp, Christina1 aDopazo, Joaquin1 aGriese, Matthias1 aMoreno-Galdó, Antonio1 aChILD-Spain Group uhttps://www.clinbioinfosspa.es/content/incidence-and-prevalence-childrens-diffuse-lung-disease-spain-003236nas a2200193 4500008004100000022001400041245011800055210006900173260001600242300000600258490000700264520252200271100002002793700002002813700003002833700002002863700002302883856013602906 2022 eng d a1756-038100aIntegrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data.0 aIntegrating pathway knowledge with deep neural networks to reduc c2022 Jan 03 a10 v153 aBACKGROUND: Single-cell RNA sequencing (scRNA-seq) data provide valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applications of scRNA-seq data analysis is the identification of new cell types and cell states. Deep neural networks (DNNs) are among the best methods to address this problem. However, this performance comes with the trade-off for a lack of interpretability in the results. In this work we propose an intelligible pathway-driven neural network to correctly solve cell-type related problems at single-cell resolution while providing a biologically meaningful representation of the data.
RESULTS: In this study, we explored the deep neural networks constrained by several types of prior biological information, e.g. signaling pathway information, as a way to reduce the dimensionality of the scRNA-seq data. We have tested the proposed biologically-based architectures on thousands of cells of human and mouse origin across a collection of public datasets in order to check the performance of the model. Specifically, we tested the architecture across different validation scenarios that try to mimic how unknown cell types are clustered by the DNN and how it correctly annotates cell types by querying a database in a retrieval problem. Moreover, our approach demonstrated to be comparable to other less interpretable DNN approaches constrained by using protein-protein interactions gene regulation data. Finally, we show how the latent structure learned by the network could be used to visualize and to interpret the composition of human single cell datasets.
CONCLUSIONS: Here we demonstrate how the integration of pathways, which convey fundamental information on functional relationships between genes, with DNNs, that provide an excellent classification framework, results in an excellent alternative to learn a biologically meaningful representation of scRNA-seq data. In addition, the introduction of prior biological knowledge in the DNN reduces the size of the network architecture. Comparative results demonstrate a superior performance of this approach with respect to other similar approaches. As an additional advantage, the use of pathways within the DNN structure enables easy interpretability of the results by connecting features to cell functionalities by means of the pathway nodes, as demonstrated with an example with human melanoma tumor cells.
1 aGundogdu, Pelin1 aLoucera, Carlos1 aAlamo-Alvarez, Inmaculada1 aDopazo, Joaquin1 aNepomuceno, Isabel uhttps://www.clinbioinfosspa.es/content/integrating-pathway-knowledge-deep-neural-networks-reduce-dimensionality-single-cell-rna-seq08213nas a2202125 4500008004100000022001400041245005800055210005600113260001600169520175300185100001701938700002901955700002801984700002002012700002702032700002002059700003002079700003402109700002902143700002702172700003102199700002002230700002502250700002002275700002802295700002302323700002102346700001902367700002902386700002302415700001802438700002202456700002402478700002902502700002902531700002902560700002102589700002502610700002302635700001802658700002002676700002002696700002602716700002402742700001802766700002202784700002402806700003102830700002802861700001802889700002102907700003202928700002502960700003102985700003003016700002403046700001903070700003303089700002903122700002903151700003403180700002803214700002503242700002503267700003303292700003203325700002903357700003303386700002703419700003003446700002903476700002803505700002503533700002903558700002003587700002803607700002103635700002603656700002603682700003303708700002703741700002303768700003103791700001903822700002703841700002403868700002603892700002203918700002003940700002203960700002103982700002804003700002004031700002504051700002004076700002904096700002604125700003004151700001804181700002604199700002104225700002704246700002804273700003304301700003104334700002804365700002704393700001604420700002504436700002404461700002004485700002704505700003704532700002104569700002504590700002004615700002504635700002104660700001704681700002204698700002004720700002304740700003004763700002404793700001804817700002204835700001904857700002204876700002804898700001904926700001904945700001704964700002004981700002605001700001905027700002005046700002205066700001905088700003105107700002205138700002205160700002105182700001805203700002105221700002605242700002605268700003005294700002105324700002305345700002405368700002005392700002305412700001605435700002005451700003205471700002005503700001805523700002005541700001805561700001705579700002005596700001805616700001805634700001805652700001905670700002205689700002305711700003005734700001805764700002605782700002205808700002805830700001905858700002105877700002205898710002505920710002505945710002405970856009305994 2022 eng d a1460-208300aNovel genes and sex differences in COVID-19 severity.0 aNovel genes and sex differences in COVID19 severity c2022 Jun 163 aHere we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p < 5x10-8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10-22 and p = 8.1x10-12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10-8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10-8) and ARHGAP33 (p = 1.3x10-8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10-8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.
1 aCruz, Raquel1 ade Almeida, Silvia, Diz-1 aHeredia, Miguel, López1 aQuintela, Inés1 aCeballos, Francisco, C1 aPita, Guillermo1 aLorenzo-Salazar, José, M1 aGonzález-Montelongo, Rafaela1 aGago-Domínguez, Manuela1 aPorras, Marta, Sevilla1 aCastaño, Jair, Antonio Te1 aNevado, Julián1 aAguado, Jose, María1 aAguilar, Carlos1 aAguilera-Albesa, Sergio1 aAlmadana, Virginia1 aAlmoguera, Berta1 aAlvarez, Nuria1 aAndreu-Bernabeu, Álvaro1 aArana-Arri, Eunate1 aArango, Celso1 aArranz, María, J1 aArtiga, Maria-Jesus1 aBaptista-Rosas, Raúl, C1 aBarreda-Sánchez, María1 aBelhassen-Garcia, Moncef1 aBezerra, Joao, F1 aBezerra, Marcos, A C1 aBoix-Palop, Lucía1 aBrión, Maria1 aBrugada, Ramón1 aBustos, Matilde1 aCalderón, Enrique, J1 aCarbonell, Cristina1 aCastano, Luis1 aCastelao, Jose, E1 aConde-Vicente, Rosa1 aCordero-Lorenzana, Lourdes1 aCortes-Sanchez, Jose, L1 aCorton, Marta1 aDarnaude, Teresa1 aDe Martino-Rodríguez, Alba1 aCampo-Pérez, Victor1 aBustamante, Aranzazu, Diaz1 aDomínguez-Garrido, Elena1 aLuchessi, André, D1 aEirós, Rocío1 aSanabria, Gladys, Mercedes E1 aFariñas, María, Carmen1 aFernández-Robelo, Uxía1 aFernández-Rodríguez, Amanda1 aFernández-Villa, Tania1 aGil-Fournier, Belén1 aGómez-Arrue, Javier1 aÁlvarez, Beatriz, González1 aQuirós, Fernan, Gonzalez B1 aGonzález-Peñas, Javier1 aGutiérrez-Bautista, Juan, F1 aHerrero, María, José1 aHerrero-Gonzalez, Antonio1 aJimenez-Sousa, María, A1 aLattig, María, Claudia1 aBorja, Anabel, Liger1 aLopez-Rodriguez, Rosario1 aMancebo, Esther1 aMartín-López, Caridad1 aMartín, Vicente1 aMartinez-Nieto, Oscar1 aMartinez-Lopez, Iciar1 aMartinez-Resendez, Michel, F1 aMartinez-Perez, Ángel1 aMazzeu, Juliana, A1 aMacías, Eleuterio, Merayo1 aMinguez, Pablo1 aCuerda, Victor, Moreno1 aSilbiger, Vivian, N1 aOliveira, Silviene, F1 aOrtega-Paino, Eva1 aParellada, Mara1 aPaz-Artal, Estela1 aSantos, Ney, P C1 aPérez-Matute, Patricia1 aPerez, Patricia1 aPérez-Tomás, Elena1 aPerucho, Teresa1 aPinsach-Abuin, Mel, Lina1 aPompa-Mera, Ericka, N1 aPorras-Hurtado, Gloria, L1 aPujol, Aurora1 aLeón, Soraya, Ramiro1 aResino, Salvador1 aFernandes, Marianne, R1 aRodríguez-Ruiz, Emilio1 aRodriguez-Artalejo, Fernando1 aRodriguez-Garcia, José, A1 aRuiz-Cabello, Francisco1 aRuiz-Hornillos, Javier1 aRyan, Pablo1 aSoria, José, Manuel1 aSouto, Juan, Carlos1 aTamayo, Eduardo1 aTamayo-Velasco, Alvaro1 aTaracido-Fernandez, Juan, Carlos1 aTeper, Alejandro1 aTorres-Tobar, Lilian1 aUrioste, Miguel1 aValencia-Ramos, Juan1 aYáñez, Zuleima1 aZarate, Ruth1 aNakanishi, Tomoko1 aPigazzini, Sara1 aDegenhardt, Frauke1 aButler-Laporte, Guillaume1 aMaya-Miles, Douglas1 aBujanda, Luis1 aBouysran, Youssef1 aPalom, Adriana1 aEllinghaus, David1 aMartínez-Bueno, Manuel1 aRolker, Selina1 aAmitrano, Sara1 aRoade, Luisa1 aFava, Francesca1 aSpinner, Christoph, D1 aPrati, Daniele1 aBernardo, David1 aGarcía, Federico1 aDarcis, Gilles1 aFernández-Cadenas, Israel1 aHolter, Jan, Cato1 aBanales, Jesus, M1 aFrithiof, Robert1 aDuga, Stefano1 aAsselta, Rosanna1 aPereira, Alexandre, C1 aRomero-Gómez, Manuel1 aNafría-Jiménez, Beatriz1 aHov, Johannes, R1 aMigeotte, Isabelle1 aRenieri, Alessandra1 aPlanas, Anna, M1 aLudwig, Kerstin, U1 aButi, Maria1 aRahmouni, Souad1 aAlarcón-Riquelme, Marta, E1 aSchulte, Eva, C1 aFranke, Andre1 aKarlsen, Tom, H1 aValenti, Luca1 aZeberg, Hugo1 aRichards, Brent1 aGanna, Andrea1 aBoada, Mercè1 aRojas, Itziar1 aRuiz, Agustín1 aSánchez, Pascual1 aReal, Luis, Miguel1 aGuillén-Navarro, Encarna1 aAyuso, Carmen1 aGonzález-Neira, Anna1 aRiancho, José, A1 aRojas-Martinez, Augusto1 aFlores, Carlos1 aLapunzina, Pablo1 aCarracedo, Ángel1 aSCOURGE Cohort Group1 aHOSTAGE Cohort Group1 aGRA@CE Cohort Group uhttps://www.clinbioinfosspa.es/content/novel-genes-and-sex-differences-covid-19-severity07193nas a2202077 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2021 eng d a1744-429200aCOVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.0 aCOVID19 Disease Map a computational knowledge repository of viru c2021 10 ae103870 v173 aWe need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
10aAntiviral Agents10aComputational Biology10aComputer Graphics10aCOVID-1910aCytokines10aData Mining10aDatabases, Factual10aGene Expression Regulation10aHost Microbial Interactions10aHumans10aImmunity, Cellular10aImmunity, Humoral10aImmunity, Innate10aLymphocytes10aMetabolic Networks and Pathways10aMyeloid Cells10aProtein Interaction Mapping10aSARS-CoV-210aSignal Transduction10aSoftware10aTranscription Factors10aViral Proteins1 aOstaszewski, Marek1 aNiarakis, Anna1 aMazein, Alexander1 aKuperstein, Inna1 aPhair, Robert1 aOrta-Resendiz, Aurelio1 aSingh, Vidisha1 aAghamiri, Sara, Sadat1 aAcencio, Marcio, Luis1 aGlaab, Enrico1 aRuepp, Andreas1 aFobo, Gisela1 aMontrone, Corinna1 aBrauner, Barbara1 aFrishman, Goar1 aGómez, Luis, Cristóbal1 aSomers, Julia1 aHoch, Matti1 aGupta, Shailendra, Kumar1 aScheel, Julia1 aBorlinghaus, Hanna1 aCzauderna, Tobias1 aSchreiber, Falk1 aMontagud, Arnau1 ade Leon, Miguel, Ponce1 aFunahashi, Akira1 aHiki, Yusuke1 aHiroi, Noriko1 aYamada, Takahiro, G1 aDräger, Andreas1 aRenz, Alina1 aNaveez, Muhammad1 aBocskei, Zsolt1 aMessina, Francesco1 aBörnigen, Daniela1 aFergusson, Liam1 aConti, Marta1 aRameil, Marius1 aNakonecnij, Vanessa1 aVanhoefer, Jakob1 aSchmiester, Leonard1 aWang, Muying1 aAckerman, Emily, E1 aShoemaker, Jason, E1 aZucker, Jeremy1 aOxford, Kristie1 aTeuton, Jeremy1 aKocakaya, Ebru1 aSummak, Gökçe, Yağmur1 aHanspers, Kristina1 aKutmon, Martina1 aCoort, Susan1 aEijssen, Lars1 aEhrhart, Friederike1 aRex, Devasahayam, Arokia Bal1 aSlenter, Denise1 aMartens, Marvin1 aPham, Nhung1 aHaw, Robin1 aJassal, Bijay1 aMatthews, Lisa1 aOrlic-Milacic, Marija1 aRibeiro, Andrea, Senff1 aRothfels, Karen1 aShamovsky, Veronica1 aStephan, Ralf1 aSevilla, Cristoffer1 aVarusai, Thawfeek1 aRavel, Jean-Marie1 aFraser, Rupsha1 aOrtseifen, Vera1 aMarchesi, Silvia1 aGawron, Piotr1 aSmula, Ewa1 aHeirendt, Laurent1 aSatagopam, Venkata1 aWu, Guanming1 aRiutta, Anders1 aGolebiewski, Martin1 aOwen, Stuart1 aGoble, Carole1 aHu, Xiaoming1 aOverall, Rupert, W1 aMaier, Dieter1 aBauch, Angela1 aGyori, Benjamin, M1 aBachman, John, A1 aVega, Carlos1 aGrouès, Valentin1 aVazquez, Miguel1 aPorras, Pablo1 aLicata, Luana1 aIannuccelli, Marta1 aSacco, Francesca1 aNesterova, Anastasia1 aYuryev, Anton1 ade Waard, Anita1 aTurei, Denes1 aLuna, Augustin1 aBabur, Ozgun1 aSoliman, Sylvain1 aValdeolivas, Alberto1 aEsteban-Medina, Marina1 aPeña-Chilet, Maria1 aRian, Kinza1 aHelikar, Tomáš1 aPuniya, Bhanwar, Lal1 aModos, Dezso1 aTreveil, Agatha1 aOlbei, Marton1 aDe Meulder, Bertrand1 aBallereau, Stephane1 aDugourd, Aurélien1 aNaldi, Aurélien1 aNoël, Vincent1 aCalzone, Laurence1 aSander, Chris1 aDemir, Emek1 aKorcsmaros, Tamas1 aFreeman, Tom, C1 aAugé, Franck1 aBeckmann, Jacques, S1 aHasenauer, Jan1 aWolkenhauer, Olaf1 aWilighagen, Egon, L1 aPico, Alexander, R1 aEvelo, Chris, T1 aGillespie, Marc, E1 aStein, Lincoln, D1 aHermjakob, Henning1 aD'Eustachio, Peter1 aSaez-Rodriguez, Julio1 aDopazo, Joaquin1 aValencia, Alfonso1 aKitano, Hiroaki1 aBarillot, Emmanuel1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard1 aCOVID-19 Disease Map Community uhttps://www.clinbioinfosspa.es/content/covid19-disease-map-computational-knowledge-repository-virus-host-interaction-mechanisms03508nas a2200709 4500008004100000022001400041245008200055210006900137260001500206300001600221490000700237520139500244653001201639653002301651653001801674653002301692653001001715653001901725653002201744653002501766653001801791653001301809653001101822653001301833653002301846653001301869653001001882100002401892700001801916700002601934700002501960700002101985700002102006700002602027700002002053700002902073700002302102700002902125700002602154700002002180700002702200700002702227700001802254700001902272700003002291700001802321700003402339700001902373700002902392700002702421700001902448700002502467700001702492700002802509700002802537700001902565700002202584700001902606700002002625710004302645856011002688 2021 eng d a1362-496200aCSVS, a crowdsourcing database of the Spanish population genetic variability.0 aCSVS a crowdsourcing database of the Spanish population genetic c2021 01 08 aD1130-D11370 v493 aThe knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.
10aAlleles10aChromosome Mapping10aCrowdsourcing10aDatabases, Genetic10aExome10aGene Frequency10aGenetic Variation10aGenetics, Population10aGenome, Human10aGenomics10aHumans10aInternet10aPrecision Medicine10aSoftware10aSpain1 aPeña-Chilet, Maria1 aRoldán, Gema1 aPerez-Florido, Javier1 aOrtuno, Francisco, M1 aCarmona, Rosario1 aAquino, Virginia1 aLópez-López, Daniel1 aLoucera, Carlos1 aFernandez-Rueda, Jose, L1 aGallego, Asunción1 aGarcia-Garcia, Francisco1 aGonzález-Neira, Anna1 aPita, Guillermo1 aNúñez-Torres, Rocío1 aSantoyo-López, Javier1 aAyuso, Carmen1 aMinguez, Pablo1 aAvila-Fernandez, Almudena1 aCorton, Marta1 aMoreno-Pelayo, Miguel, Ángel1 aMorin, Matías1 aGallego-Martinez, Alvaro1 aLopez-Escamez, Jose, A1 aBorrego, Salud1 aAntiňolo, Guillermo1 aAmigo, Jorge1 aSalgado-Garrido, Josefa1 aPasalodos-Sanchez, Sara1 aMorte, Beatriz1 aCarracedo, Ángel1 aAlonso, Ángel1 aDopazo, Joaquin1 aSpanish Exome Crowdsourcing Consortium uhttps://www.clinbioinfosspa.es/content/csvs-crowdsourcing-database-spanish-population-genetic-variability01938nas a2200277 4500008004100000022001400041245011400055210006900169260001600238490000700254520095600261100002701217700002401244700002601268700003001294700001901324700001901343700003401362700003601396700002001432700002001452700001801472700001701490700002001507856013301527 2021 eng d a2072-669400aMutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development.0 aMutational Characterization of Cutaneous Melanoma Supports Diver c2021 Oct 180 v133 aAccording to the divergent pathway model, cutaneous melanoma comprises a nevogenic group with a propensity to melanocyte proliferation and another one associated with cumulative solar damage (CSD). While characterized clinically and epidemiologically, the differences in the molecular profiles between the groups have remained primarily uninvestigated. This study has used a custom gene panel and bioinformatics tools to investigate the potential molecular differences in a thoroughly characterized cohort of 119 melanoma patients belonging to nevogenic and CSD groups. We found that the nevogenic melanomas had a restricted set of mutations, with the prominently mutated gene being . The CSD melanomas, in contrast, showed mutations in a diverse group of genes that included , , , and . We thus provide evidence that nevogenic and CSD melanomas constitute different biological entities and highlight the need to explore new targeted therapies.
1 aMillán-Esteban, David1 aPeña-Chilet, Maria1 aGarcía-Casado, Zaida1 aManrique-Silva, Esperanza1 aRequena, Celia1 aBañuls, José1 aLopez-Guerrero, Jose, Antonio1 aRodríguez-Hernández, Aranzazu1 aTraves, Víctor1 aDopazo, Joaquin1 aVirós, Amaya1 aKumar, Rajiv1 aNagore, Eduardo uhttps://www.clinbioinfosspa.es/content/mutational-characterization-cutaneous-melanoma-supports-divergent-pathways-model-melanoma03248nas a2201189 4500008004100000022001400041245003300055210002900088260001600117100002300133700002200156700001900178700001500197700002500212700001700237700001900254700001700273700002900290700001800319700001600337700002200353700001300375700001700388700002000405700001800425700002500443700002500468700002800493700001800521700001900539700001900558700002300577700002600600700002400626700002500650700002600675700001700701700001400718700002400732700001600756700002100772700002100793700001500814700001900829700002100848700002100869700002400890700001700914700002600931700001900957700001700976700002100993700002501014700002301039700001601062700002301078700001901101700002101120700001901141700002401160700002701184700002001211700002101231700002101252700002201273700002001295700002101315700002001336700001901356700001801375700001901393700002501412700002201437700002401459700001901483700002101502700001901523700001901542700001701561700002601578700002401604700001601628700001801644700002201662700001701684700001801701700001401719700002501733700001701758700002301775700001701798700001801815700002401833700002801857700001801885700001801903700001901921700001701940700002201957700002501979856005402004 2021 eng d a1061-403600aThe NCI Genomic Data Commons0 aNCI Genomic Data Commons cOct-02-20221 aHeath, Allison, P.1 aFerretti, Vincent1 aAgrawal, Stuti1 aAn, Maksim1 aAngelakos, James, C.1 aArya, Renuka1 aBajari, Rosita1 aBaqar, Bilal1 aBarnowski, Justin, H. B.1 aBurt, Jeffrey1 aCatton, Ann1 aChan, Brandon, F.1 aChu, Fay1 aCullion, Kim1 aDavidsen, Tanja1 aDo, Phuong-My1 aDompierre, Christian1 aFerguson, Martin, L.1 aFitzsimons, Michael, S.1 aFord, Michael1 aFukuma, Miyuki1 aGaheen, Sharon1 aGanji, Gajanan, L.1 aGarcia, Tzintzuni, I.1 aGeorge, Sameera, S.1 aGerhard, Daniela, S.1 aGerthoffert, Francois1 aGomez, Fauzi1 aHan, Kang1 aHernandez, Kyle, M.1 aIssac, Biju1 aJackson, Richard1 aJensen, Mark, A.1 aJoshi, Sid1 aKadam, Ajinkya1 aKhurana, Aishmit1 aKim, Kyle, M. J.1 aKraft, Victoria, E.1 aLi, Shenglai1 aLichtenberg, Tara, M.1 aLodato, Janice1 aLolla, Laxmi1 aMartinov, Plamen1 aMazzone, Jeffrey, A.1 aMiller, Daniel, P.1 aMiller, Ian1 aMiller, Joshua, S.1 aMiyauchi, Koji1 aMurphy, Mark, W.1 aNullet, Thomas1 aOgwara, Rowland, O.1 aOrtuño, Francisco, M.1 aPedrosa, Jesús1 aPham, Phuong, L.1 aPopov, Maxim, Y.1 aPorter, James, J.1 aPowell, Raymond1 aRademacher, Karl1 aReid, Colin, P.1 aRich, Samantha1 aRogel, Bessie1 aSahni, Himanso1 aSavage, Jeremiah, H.1 aSchmitt, Kyle, A.1 aSimmons, Trevar, J.1 aSislow, Joseph1 aSpring, Jonathan1 aStein, Lincoln1 aSullivan, Sean1 aTang, Yajing1 aThiagarajan, Mathangi1 aTroyer, Heather, D.1 aWang, Chang1 aWang, Zhining1 aWest, Bedford, L.1 aWilmer, Alex1 aWilson, Shane1 aWu, Kaman1 aWysocki, William, P.1 aXiang, Linda1 aYamada, Joseph, T.1 aYang, Liming1 aYu, Christine1 aYung, Christina, K.1 aZenklusen, Jean, Claude1 aZhang, Junjun1 aZhang, Zhenyu1 aZhao, Yuanheng1 aZubair, Ariz1 aStaudt, Louis, M.1 aGrossman, Robert, L. uhttp://www.nature.com/articles/s41588-021-00791-502217nas a2200349 4500008004100000022001400041245009500055210006900150260001500219300000900234490000700243520109300250100002301343700001801366700001901384700002201403700002301425700001601448700002701464700001901491700001501510700001601525700001801541700001901559700001301578700001501591700001801606700001701624700002601641710007101667856012901738 2021 eng d a2041-172300aOrchestrating and sharing large multimodal data for transparent and reproducible research.0 aOrchestrating and sharing large multimodal data for transparent c2021 10 04 a57970 v123 aReproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.
1 aMammoliti, Anthony1 aSmirnov, Petr1 aNakano, Minoru1 aSafikhani, Zhaleh1 aEeles, Christopher1 aSeo, Heewon1 aNair, Sisira, Kadambat1 aMer, Arvind, S1 aSmith, Ian1 aHo, Chantal1 aBeri, Gangesh1 aKusko, Rebecca1 aLin, Eva1 aYu, Yihong1 aMartin, Scott1 aHafner, Marc1 aHaibe-Kains, Benjamin1 aMassive Analysis Quality Control (MAQC) Society Board of Directors uhttps://www.clinbioinfosspa.es/content/orchestrating-and-sharing-large-multimodal-data-transparent-and-reproducible-research00782nas a2200229 4500008004100000245009000041210006900131260001600200300000800216490000700224100003400231700002600265700003000291700002600321700002700347700002000374700003600394700002800430700002000458700002900478856004500507 2021 eng d00aPhylogenetic Analysis of the 2020 West Nile Virus (WNV) Outbreak in Andalusia (Spain)0 aPhylogenetic Analysis of the 2020 West Nile Virus WNV Outbreak i cJan-05-2021 a8360 v131 aCasimiro-Soriguer, Carlos, S.1 aPerez-Florido, Javier1 aFernandez-Rueda, Jose, L.1 aPedrosa-Corral, Irene1 aGuillot-Sulay, Vicente1 aLorusso, Nicola1 aMartinez-Gonzalez, Luis, Javier1 aNavarro-Marí, Jose, M.1 aDopazo, Joaquin1 aSanbonmatsu-Gámez, Sara uhttps://www.mdpi.com/1999-4915/13/5/836 05409nas a2201477 4500008004100000022001400041245007800055210006900133260001200202300001400214490000700228520122900235653002601464653001401490653001101504653001501515653003501530653002001565653003801585100001901623700001901642700001801661700002301679700002401702700002301726700002101749700002801770700001801798700002501816700002401841700002701865700001801892700002301910700002001933700001501953700002201968700002001990700002702010700002102037700002202058700001802080700001902098700002702117700002002144700001902164700002002183700002102203700001702224700002102241700002302262700002002285700002202305700002002327700001802347700002302365700001802388700002102406700002602427700001902453700001702472700001802489700002402507700001902531700001602550700001702566700001602583700002102599700002102620700002102641700002102662700002202683700002202705700002102727700001602748700001702764700001502781700002102796700001702817700002402834700002202858700002002880700002402900700001802924700001602942700002302958700002102981700002403002700001703026700002603043700002403069700002503093700002403118700002203142700002103164700001703185700001903202700001803221700001803239700001303257700001703270700001603287700001903303700002703322700002003349700001703369700002203386700001903408700001903427700002603446700001903472700002903491700002103520700001603541700002203557700001603579700002003595700002403615700001903639700002403658700002203682700002003704700001803724710003303742710004903775856010703824 2021 eng d a1546-170X00aReporting guidelines for human microbiome research: the STORMS checklist.0 aReporting guidelines for human microbiome research the STORMS ch c2021 11 a1885-18920 v273 aThe particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.
10aComputational Biology10aDysbiosis10aHumans10aMicrobiota10aObservational Studies as Topic10aResearch Design10aTranslational Science, Biomedical1 aMirzayi, Chloe1 aRenson, Audrey1 aZohra, Fatima1 aElsafoury, Shaimaa1 aGeistlinger, Ludwig1 aKasselman, Lora, J1 aEckenrode, Kelly1 avan de Wijgert, Janneke1 aLoughman, Amy1 aMarques, Francine, Z1 aMacIntyre, David, A1 aArumugam, Manimozhiyan1 aAzhar, Rimsha1 aBeghini, Francesco1 aBergstrom, Kirk1 aBhatt, Ami1 aBisanz, Jordan, E1 aBraun, Jonathan1 aBravo, Hector, Corrada1 aBuck, Gregory, A1 aBushman, Frederic1 aCasero, David1 aClarke, Gerard1 aCollado, Maria, Carmen1 aCotter, Paul, D1 aCryan, John, F1 aDemmer, Ryan, T1 aDevkota, Suzanne1 aElinav, Eran1 aEscobar, Juan, S1 aFettweis, Jennifer1 aFinn, Robert, D1 aFodor, Anthony, A1 aForslund, Sofia1 aFranke, Andre1 aFurlanello, Cesare1 aGilbert, Jack1 aGrice, Elizabeth1 aHaibe-Kains, Benjamin1 aHandley, Scott1 aHerd, Pamela1 aHolmes, Susan1 aJacobs, Jonathan, P1 aKarstens, Lisa1 aKnight, Rob1 aKnights, Dan1 aKoren, Omry1 aKwon, Douglas, S1 aLangille, Morgan1 aLindsay, Brianna1 aMcGovern, Dermot1 aMcHardy, Alice, C1 aMcWeeney, Shannon1 aMueller, Noel, T1 aNezi, Luigi1 aOlm, Matthew1 aPalm, Noah1 aPasolli, Edoardo1 aRaes, Jeroen1 aRedinbo, Matthew, R1 aRühlemann, Malte1 aSartor, Balfour1 aSchloss, Patrick, D1 aSchriml, Lynn1 aSegal, Eran1 aShardell, Michelle1 aSharpton, Thomas1 aSmirnova, Ekaterina1 aSokol, Harry1 aSonnenburg, Justin, L1 aSrinivasan, Sujatha1 aThingholm, Louise, B1 aTurnbaugh, Peter, J1 aUpadhyay, Vaibhav1 aWalls, Ramona, L1 aWilmes, Paul1 aYamada, Takuji1 aZeller, Georg1 aZhang, Mingyu1 aZhao, Ni1 aZhao, Liping1 aBao, Wenjun1 aCulhane, Aedin1 aDevanarayan, Viswanath1 aDopazo, Joaquin1 aFan, Xiaohui1 aFischer, Matthias1 aJones, Wendell1 aKusko, Rebecca1 aMason, Christopher, E1 aMercer, Tim, R1 aSansone, Susanna-Assunta1 aScherer, Andreas1 aShi, Leming1 aThakkar, Shraddha1 aTong, Weida1 aWolfinger, Russ1 aHunter, Christopher1 aSegata, Nicola1 aHuttenhower, Curtis1 aDowd, Jennifer, B1 aJones, Heidi, E1 aWaldron, Levi1 aGenomic Standards Consortium1 aMassive Analysis and Quality Control Society uhttps://www.clinbioinfosspa.es/content/reporting-guidelines-human-microbiome-research-storms-checklist01585nas a2200505 4500008004100000245010600041210007100147260001600218300000800234490000700242100002700249700001900276700002000295700002800315700002900343700002700372700002800399700002500427700002000452700001700472700001900489700001900508700002000527700002100547700002900568700002600597700002700623700002200650700002700672700001800699700002200717700001500739700001800754700002100772700001900793700002100812700001800833700001800851700002400869700002200893700002100915710003200936710002400968856008700992 2021 eng d00aSchuurs–Hoeijmakers Syndrome (PACS1 Neurodevelopmental Disorder): Seven Novel Patients and a Review0 aSchuurs–Hoeijmakers Syndrome PACS1 Neurodevelopmental Disorder S cJan-05-2021 a7380 v121 aTenorio-Castaño, Jair1 aMorte, Beatriz1 aNevado, Julián1 aMartínez-Glez, Víctor1 aSantos-Simarro, Fernando1 aGarcía-Miñaur, Sixto1 aPalomares-Bralo, María1 aPacio-Míguez, Marta1 aGómez, Beatriz1 aArias, Pedro1 aAlcochea, Alba1 aCarrión, Juan1 aArias, Patricia1 aAlmoguera, Berta1 aLópez-Grondona, Fermina1 aLorda-Sanchez, Isabel1 aGalán-Gómez, Enrique1 aValenzuela, Irene1 aPerez, María, Méndez1 aCuscó, Ivón1 aBarros, Francisco1 aPié, Juan1 aRamos, Sergio1 aRamos, Feliciano1 aKuechler, Alma1 aTizzano, Eduardo1 aAyuso, Carmen1 aKaiser, Frank1 aPérez-Jurado, Luis1 aCarracedo, Ángel1 aLapunzina, Pablo1 aThe ENoD-CIBERER Consortium1 aThe SIDE Consortium uhttps://www.mdpi.com/2073-4425/12/5/738https://www.mdpi.com/2073-4425/12/5/738/pdf02937nas a2200613 4500008004100000022001400041245012600055210006900181260001500250300001500265490000700280520120500287653001801492653001101510653001301521653001101534653002101545653000901566653001401575653002001589653001301609653001501622653001801637100001301655700002401668700001201692700001701704700001601721700001701737700001601754700001601770700001201786700001401798700001601812700001501828700002101843700002101864700002201885700001501907700002301922700002101945700002101966700001601987700001602003700002102019700002502040700001902065700001702084700001402101700001802115700002602133710003102159856013302190 2020 eng d a2405-472000aCommunity Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.0 aCommunity Assessment of the Predictability of Cancer Protein and c2020 08 26 a186-195.e90 v113 aCancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper's transparent peer review process is included in the Supplemental Information.
10aCrowdsourcing10aFemale10aGenomics10aHumans10aMachine Learning10aMale10aNeoplasms10aPhosphoproteins10aProteins10aProteomics10aTranscriptome1 aYang, Mi1 aPetralia, Francesca1 aLi, Zhi1 aLi, Hongyang1 aMa, Weiping1 aSong, Xiaoyu1 aKim, Sunkyu1 aLee, Heewon1 aYu, Han1 aLee, Bora1 aBae, Seohui1 aHeo, Eunji1 aKaczmarczyk, Jan1 aStępniak, Piotr1 aWarchoł, Michał1 aYu, Thomas1 aCalinawan, Anna, P1 aBoutros, Paul, C1 aPayne, Samuel, H1 aReva, Boris1 aBoja, Emily1 aRodriguez, Henry1 aStolovitzky, Gustavo1 aGuan, Yuanfang1 aKang, Jaewoo1 aWang, Pei1 aFenyö, David1 aSaez-Rodriguez, Julio1 aNCI-CPTAC-DREAM Consortium uhttps://www.clinbioinfosspa.es/content/community-assessment-predictability-cancer-protein-and-phosphoprotein-levels-genomics-and01798nas a2200577 4500008004100000022001400041245011100055210006900166260001500235300000800250490000600258653002000264653002600284653002700310653001300337653002300350653003200373653003100405653001100436653003000447653002300477653001400500653002100514653001500535100002300550700002200573700002300595700002100618700001900639700002300658700002300681700002500704700002000729700001900749700002000768700002100788700001600809700002200825700002200847700002300869700002000892700002700912700002300939700002200962700002100984700002001005700002101025700001801046700002401064856013201088 2020 eng d a2052-446300aCOVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms.0 aCOVID19 Disease Map building a computational repository of SARSC c2020 05 05 a1360 v710aBetacoronavirus10aComputational Biology10aCoronavirus Infections10aCOVID-1910aDatabases, Factual10aHost Microbial Interactions10aHost-Pathogen Interactions10aHumans10aInternational Cooperation10aModels, Biological10aPandemics10aPneumonia, Viral10aSARS-CoV-21 aOstaszewski, Marek1 aMazein, Alexander1 aGillespie, Marc, E1 aKuperstein, Inna1 aNiarakis, Anna1 aHermjakob, Henning1 aPico, Alexander, R1 aWillighagen, Egon, L1 aEvelo, Chris, T1 aHasenauer, Jan1 aSchreiber, Falk1 aDräger, Andreas1 aDemir, Emek1 aWolkenhauer, Olaf1 aFurlong, Laura, I1 aBarillot, Emmanuel1 aDopazo, Joaquin1 aOrta-Resendiz, Aurelio1 aMessina, Francesco1 aValencia, Alfonso1 aFunahashi, Akira1 aKitano, Hiroaki1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard uhttps://www.clinbioinfosspa.es/content/covid-19-disease-map-building-computational-repository-sars-cov-2-virus-host-interaction05180nas a2201117 4500008004100000022001400041245011300055210006900168260001200237300001200249490000700261520174900268653001402017653003102031653001502062653002502077653001902102653005102121653001102172653002902183653003802212653001102250653000902261653002302270653003602293653002702329100002202356700001702378700002402395700002802419700003302447700002702480700001502507700002402522700002902546700002602575700002802601700001702629700002002646700002102666700001902687700002702706700001902733700002002752700002402772700003002796700001902826700002602845700002902871700001802900700002102918700002202939700003202961700002002993700002603013700002903039700002103068700002203089700002103111700001903132700002703151700002403178700002903202700003203231700002003263700001803283700003103301700002803332700001603360700002503376700003103401700003303432700002903465700002203494700002103516700002403537700001903561700002503580700001703605700001703622700001803639700002303657700002003680700001603700700002203716700002503738700001803763700002303781700002003804700002003824700002103844700003303865700001703898700002103915856012603936 2020 eng d a1468-624400aOptimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.0 aOptimised molecular genetic diagnostics of Fanconi anaemia by wh c2020 04 a258-2680 v573 aPURPOSE: Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.
METHODS: 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.
RESULTS: We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.
10aCell Line10aDNA Copy Number Variations10aDNA Repair10aDNA-Binding Proteins10aFanconi Anemia10aFanconi Anemia Complementation Group A Protein10aFemale10aGene Knockout Techniques10aGenetic Predisposition to Disease10aHumans10aMale10aMutation, Missense10aPolymorphism, Single Nucleotide10awhole exome sequencing1 aBogliolo, Massimo1 aPujol, Roser1 aAza-Carmona, Miriam1 aMuñoz-Subirana, Núria1 aRodriguez-Santiago, Benjamin1 aCasado, José, Antonio1 aRio, Paula1 aBauser, Christopher1 aReina-Castillón, Judith1 aLopez-Sanchez, Marcos1 aGonzalez-Quereda, Lidia1 aGallano, Pia1 aCatalá, Albert1 aRuiz-Llobet, Ana1 aBadell, Isabel1 aDiaz-Heredia, Cristina1 aHladun, Raquel1 aSenent, Leonort1 aArgiles, Bienvenida1 aBurgues, Juan, Miguel Ber1 aBañez, Fatima1 aArrizabalaga, Beatriz1 aAlmaraz, Ricardo, López1 aLopez, Monica1 aFiguera, Ángela1 aMolinés, Antonio1 ade Soto, Inmaculada, Pérez1 aHernando, Inés1 aMuñoz, Juan, Antonio1 aMarin, Maria, Del Rosari1 aBalmaña, Judith1 aStjepanovic, Neda1 aCarrasco, Estela1 aCuesta, Isabel1 aCosuelo, José, Miguel1 aRegueiro, Alexandra1 aJimenez, José, Moraleda1 aGalera-Miñarro, Ana, Maria1 aRosiñol, Laura1 aCarrió, Anna1 aBeléndez-Bieler, Cristina1 aSoto, Antonio, Escudero1 aCela, Elena1 ade la Mata, Gregorio1 aFernández-Delgado, Rafael1 aGarcia-Pardos, Maria, Carmen1 aSáez-Villaverde, Raquel1 aBarragaño, Marta1 aPortugal, Raquel1 aLendinez, Francisco1 aHernadez, Ines1 aVagace, José, Manue1 aTapia, Maria1 aNieto, José1 aGarcia, Marta1 aGonzalez, Macarena1 aVicho, Cristina1 aGalvez, Eva1 aValiente, Alberto1 aAntelo, Maria, Luisa1 aAncliff, Phil1 aGarcía, Francisco1 aDopazo, Joaquin1 aSevilla, Julian1 aPaprotka, Tobias1 aPérez-Jurado, Luis, Alberto1 aBueren, Juan1 aSurralles, Jordi uhttps://www.clinbioinfosspa.es/content/optimised-molecular-genetic-diagnostics-fanconi-anaemia-whole-exome-sequencing-and03269nas a2200685 4500008004100000022001400041245011800055210006900173260001500242300000900257490000700266520115400273653001901427653005101446653001701497653002201514653002101536653002601557653002201583653002001605653003001625653001901655653001301674653001101687653003101698653001301729653001401742653002101756653003501777653004101812653002201853100002301875700001701898700001901915700001801934700002301952700001901975700001501994700001702009700001602026700002002042700001602062700002402078700001902102700001802121700002402139700001802163700002502181700001702206700001902223700002302242700002702265700002002292700002502312700002002337700002102357700002602378710005702404856012202461 2019 eng d a2041-172300aCommunity assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.0 aCommunity assessment to advance computational prediction of canc c2019 06 17 a26740 v103 aThe effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
10aADAM17 Protein10aAntineoplastic Combined Chemotherapy Protocols10aBenchmarking10aBiomarkers, Tumor10aCell Line, Tumor10aComputational Biology10aDatasets as Topic10aDrug Antagonism10aDrug Resistance, Neoplasm10aDrug Synergism10aGenomics10aHumans10aMolecular Targeted Therapy10amutation10aNeoplasms10apharmacogenetics10aPhosphatidylinositol 3-Kinases10aPhosphoinositide-3 Kinase Inhibitors10aTreatment Outcome1 aMenden, Michael, P1 aWang, Dennis1 aMason, Mike, J1 aSzalai, Bence1 aBulusu, Krishna, C1 aGuan, Yuanfang1 aYu, Thomas1 aKang, Jaewoo1 aJeon, Minji1 aWolfinger, Russ1 aNguyen, Tin1 aZaslavskiy, Mikhail1 aJang, In, Sock1 aGhazoui, Zara1 aAhsen, Mehmet, Eren1 aVogel, Robert1 aNeto, Elias, Chaibub1 aNorman, Thea1 aK Y Tang, Eric1 aGarnett, Mathew, J1 aDi Veroli, Giovanni, Y1 aFawell, Stephen1 aStolovitzky, Gustavo1 aGuinney, Justin1 aDry, Jonathan, R1 aSaez-Rodriguez, Julio1 aAstraZeneca-Sanger Drug Combination DREAM Consortium uhttps://www.clinbioinfosspa.es/content/community-assessment-advance-computational-prediction-cancer-drug-combinations01484nas a2200421 4500008004100000245011900041210006900160260001600229490000600245110005300251700001800304700001800322700002300340700002500363700001600388700001900404700001500423700001800438700001900456700002400475700001900499700002200518700001600540700003100556700001800587700001800605700001800623700001900641700002200660700002300682700002700705700002700732700001900759700002400778700002500802700002600827856020900853 2018 eng d00aA crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection0 acrowdsourced analysis to identify ab initio molecular signatures cJan-12-20180 v91 aThe Respiratory Viral DREAM Challenge Consortium1 aFourati, Slim1 aTalla, Aarthi1 aMahmoudian, Mehrad1 aBurkhart, Joshua, G.1 aKlén, Riku1 aHenao, Ricardo1 aYu, Thomas1 aAydın, Zafer1 aYeung, Ka, Yee1 aAhsen, Mehmet, Eren1 aAlmugbel, Reem1 aJahandideh, Samad1 aLiang, Xiao1 aNordling, Torbjörn, E. M.1 aShiga, Motoki1 aStanescu, Ana1 aVogel, Robert1 aPandey, Gaurav1 aChiu, Christopher1 aMcClain, Micah, T.1 aWoods, Christopher, W.1 aGinsburg, Geoffrey, S.1 aElo, Laura, L.1 aTsalik, Ephraim, L.1 aMangravite, Lara, M.1 aSieberts, Solveig, K. uhttp://www.nature.com/articles/s41467-018-06735-8http://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-802577nas a2200529 4500008004100000022001400041245008700055210006900142260001500211300000800226490000600234520103000240653001001270653001801280653001001298653001101308653002001319653001101339653002301350653002301373653001901396653002501415653001801440100002301458700002701481700002101508700002501529700001601554700001901570700001701589700002201606700002401628700003101652700002101683700002401704700001901728700002401747700001801771700001801789700002101807700002001828700002001848700002101868700002301889700002001912856011501932 2018 eng d a2041-172300aThe effects of death and post-mortem cold ischemia on human tissue transcriptomes.0 aeffects of death and postmortem cold ischemia on human tissue tr c2018 02 13 a4900 v93 aPost-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.
10aBlood10aCold Ischemia10aDeath10aFemale10agene expression10aHumans10aModels, Biological10aPostmortem Changes10aRNA, Messenger10aStochastic Processes10aTranscriptome1 aFerreira, Pedro, G1 aMuñoz-Aguirre, Manuel1 aReverter, Ferran1 aGodinho, Caio, P Sá1 aSousa, Abel1 aAmadoz, Alicia1 aSodaei, Reza1 aHidalgo, Marta, R1 aPervouchine, Dmitri1 aCarbonell-Caballero, José1 aNurtdinov, Ramil1 aBreschi, Alessandra1 aAmador, Raziel1 aOliveira, Patrícia1 aCubuk, Cankut1 aCurado, João1 aAguet, François1 aOliveira, Carla1 aDopazo, Joaquin1 aSammeth, Michael1 aArdlie, Kristin, G1 aGuigó, Roderic uhttps://www.clinbioinfosspa.es/content/effects-death-and-post-mortem-cold-ischemia-human-tissue-transcriptomes02954nas a2200541 4500008004100000022001400041245008900055210006900144260000900213300001300222490000700235520138200242653001001624653000901634653001801643653001101661653002901672653003201701653002601733653001101759653001401770653002901784653000901813653001601822653001301838653002201851653001801873653001401891653002701905100002101932700003101953700002001984700002402004700002402028700002602052700001602078700001902094700001902113700002502132700002002157700001902177700002002196700002002216700002402236700002002260700001902280856011302299 2018 eng d a1932-620300aThe modular network structure of the mutational landscape of Acute Myeloid Leukemia.0 amodular network structure of the mutational landscape of Acute M c2018 ae02029260 v133 aAcute myeloid leukemia (AML) is associated with the sequential accumulation of acquired genetic alterations. Although at diagnosis cytogenetic alterations are frequent in AML, roughly 50% of patients present an apparently normal karyotype (NK), leading to a highly heterogeneous prognosis. Due to this significant heterogeneity, it has been suggested that different molecular mechanisms may trigger the disease with diverse prognostic implications. We performed whole-exome sequencing (WES) of tumor-normal matched samples of de novo AML-NK patients lacking mutations in NPM1, CEBPA or FLT3-ITD to identify new gene mutations with potential prognostic and therapeutic relevance to patients with AML. Novel candidate-genes, together with others previously described, were targeted resequenced in an independent cohort of 100 de novo AML patients classified in the cytogenetic intermediate-risk (IR) category. A mean of 4.89 mutations per sample were detected in 73 genes, 35 of which were mutated in more than one patient. After a network enrichment analysis, we defined a single in silico model and established a set of seed-genes that may trigger leukemogenesis in patients with normal karyotype. The high heterogeneity of gene mutations observed in AML patients suggested that a specific alteration could not be as essential as the interaction of deregulated pathways.
10aAdult10aAged10aCytodiagnosis10aFemale10aGene Regulatory Networks10aGenetic Association Studies10aGenetic Heterogeneity10aHumans10aKaryotype10aLeukemia, Myeloid, Acute10aMale10aMiddle Aged10amutation10aNeoplasm Proteins10aNucleophosmin10aPrognosis10awhole exome sequencing1 aIbáñez, Mariam1 aCarbonell-Caballero, José1 aSuch, Esperanza1 aGarcía-Alonso, Luz1 aLiquori, Alessandro1 aLópez-Pavía, María1 aLLop, Marta1 aAlonso, Carmen1 aBarragán, Eva1 aGómez-Seguí, Inés1 aNeef, Alexander1 aHervás, David1 aMontesinos, Pau1 aSanz, Guillermo1 aSanz, Miguel, Angel1 aDopazo, Joaquin1 aCervera, José uhttps://www.clinbioinfosspa.es/content/modular-network-structure-mutational-landscape-acute-myeloid-leukemia02800nas a2200445 4500008004100000022001400041245015700055210006900212260001600281300001600297490000600313520134500319653001001664653002501674653002601699653002001725653003801745653001301783653001501796653001101811653001801822653001601840653001601856653001401872653003501886100003001921700002401951700002201975700002601997700002902023700002202052700002602074700002502100700002402125700002102149700002002170700001802190700001702208856012902225 2017 eng d a1949-255300aGenomic expression differences between cutaneous cells from red hair color individuals and black hair color individuals based on bioinformatic analysis.0 aGenomic expression differences between cutaneous cells from red c2017 Feb 14 a11589-115990 v83 aThe MC1R gene plays a crucial role in pigmentation synthesis. Loss-of-function MC1R variants, which impair protein function, are associated with red hair color (RHC) phenotype and increased skin cancer risk. Cultured cutaneous cells bearing loss-of-function MC1R variants show a distinct gene expression profile compared to wild-type MC1R cultured cutaneous cells. We analysed the gene signature associated with RHC co-cultured melanocytes and keratinocytes by Protein-Protein interaction (PPI) network analysis to identify genes related with non-functional MC1R variants. From two detected networks, we selected 23 nodes as hub genes based on topological parameters. Differential expression of hub genes was then evaluated in healthy skin biopsies from RHC and black hair color (BHC) individuals. We also compared gene expression in melanoma tumors from individuals with RHC versus BHC. Gene expression in normal skin from RHC cutaneous cells showed dysregulation in 8 out of 23 hub genes (CLN3, ATG10, WIPI2, SNX2, GABARAPL2, YWHA, PCNA and GBAS). Hub genes did not differ between melanoma tumors in RHC versus BHC individuals. The study suggests that healthy skin cells from RHC individuals present a constitutive genomic deregulation associated with the red hair phenotype and identify novel genes involved in melanocyte biology.
10aAdult10aCoculture Techniques10aComputational Biology10agene expression10aGenetic Predisposition to Disease10aGenomics10aHair Color10aHumans10aKeratinocytes10aMelanocytes10aMiddle Aged10aPhenotype10aReceptor, Melanocortin, Type 11 aPuig-Butille, Joan, Anton1 aGimenez-Xavier, Pol1 aVisconti, Alessia1 aNsengimana, Jérémie1 aGarcia-Garcia, Francisco1 aTell-Marti, Gemma1 aEscamez, Maria, José1 aNewton-Bishop, Julia1 aBataille, Veronique1 aDel Rio, Marcela1 aDopazo, Joaquin1 aFalchi, Mario1 aPuig, Susana uhttp://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=14140&path%5B%5D=4509401430nas a2200481 4500008004100000022001400041245007200055210006900127260001500196300001400211490000800225653000900233653002400242653003700266653003400303653001900337653001000356653002900366653001100395653002200406653002800428653001100456653001600467653001300483100002100496700002100517700002800538700002700566700002600593700002000619700002000639700002000659700002900679700002000708700002600728700002800754700002200782700002400804700002000828700002100848700002500869856005400894 2017 eng d a1533-440600aGGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.0 aGGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonat c2017 05 04 a1794-17950 v37610aAged10aAmino Acid Sequence10aBone Density Conservation Agents10aDimethylallyltranstransferase10aDiphosphonates10aExome10aFarnesyltranstransferase10aFemale10aFemoral Fractures10aGeranyltranstransferase10aHumans10aMiddle Aged10amutation1 aRoca-Ayats, Neus1 aBalcells, Susana1 aGarcia-Giralt, Natàlia1 aFalcó-Mascaró, Maite1 aMartínez-Gil, Núria1 aAbril, Josep, F1 aUrreizti, Roser1 aDopazo, Joaquin1 aQuesada-Gómez, José, M1 aNogués, Xavier1 aMellibovsky, Leonardo1 aPrieto-Alhambra, Daniel1 aDunford, James, E1 aJavaid, Muhammad, K1 aRussell, Graham1 aGrinberg, Daniel1 aDíez-Pérez, Adolfo uhttp://www.nejm.org/doi/full/10.1056/NEJMc161280403542nas a2200649 4500008004100000022001400041245010900055210006900164260001600233300000700249490000700256520162800263653001601891653001701907653000801924100001901932700002001951700002201971700002501993700002502018700002202043700001702065700002102082700002502103700001902128700002202147700002002169700002102189700001902210700001802229700001802247700002202265700002302287700001802310700002002328700001602348700002602364700001702390700002202407700001702429700002202446700002102468700003202489700002802521700002302549700002902572700002502601700001802626700001902644700002502663700002602688700002302714700001902737700003402756700002402790856007802814 2017 eng d a1474-760X00aWhole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes.0 aWhole exome sequencing coupled with unbiased functional analysis c2017 Mar 08 a480 v183 aBACKGROUND: Hirschsprung disease (HSCR), which is congenital obstruction of the bowel, results from a failure of enteric nervous system (ENS) progenitors to migrate, proliferate, differentiate, or survive within the distal intestine. Previous studies that have searched for genes underlying HSCR have focused on ENS-related pathways and genes not fitting the current knowledge have thus often been ignored. We identify and validate novel HSCR genes using whole exome sequencing (WES), burden tests, in silico prediction, unbiased in vivo analyses of the mutated genes in zebrafish, and expression analyses in zebrafish, mouse, and human. RESULTS: We performed de novo mutation (DNM) screening on 24 HSCR trios. We identify 28 DNMs in 21 different genes. Eight of the DNMs we identified occur in RET, the main HSCR gene, and the remaining 20 DNMs reside in genes not reported in the ENS. Knockdown of all 12 genes with missense or loss-of-function DNMs showed that the orthologs of four genes (DENND3, NCLN, NUP98, and TBATA) are indispensable for ENS development in zebrafish, and these results were confirmed by CRISPR knockout. These genes are also expressed in human and mouse gut and/or ENS progenitors. Importantly, the encoded proteins are linked to neuronal processes shared by the central nervous system and the ENS. CONCLUSIONS: Our data open new fields of investigation into HSCR pathology and provide novel insights into the development of the ENS. Moreover, the study demonstrates that functional analyses of genes carrying DNMs are warranted to delineate the full genetic architecture of rare complex diseases.10aHirschprung10aRare Disease10aWES1 aGui, Hongsheng1 aSchriemer, Duco1 aCheng, William, W1 aChauhan, Rajendra, K1 aAntiňolo, Guillermo1 aBerrios, Courtney1 aBleda, Marta1 aBrooks, Alice, S1 aBrouwer, Rutger, W W1 aBurns, Alan, J1 aCherny, Stacey, S1 aDopazo, Joaquin1 aEggen, Bart, J L1 aGriseri, Paola1 aJalloh, Binta1 aLe, Thuy-Linh1 aLui, Vincent, C H1 aLuzón-Toro, Berta1 aMatera, Ivana1 aNgan, Elly, S W1 aPelet, Anna1 aRuiz-Ferrer, Macarena1 aSham, Pak, C1 aShepherd, Iain, T1 aSo, Man-Ting1 aSribudiani, Yunia1 aTang, Clara, S M1 avan den Hout, Mirjam, C G N1 avan der Linde, Herma, C1 avan Ham, Tjakko, J1 avan IJcken, Wilfred, F J1 aVerheij, Joke, B G M1 aAmiel, Jeanne1 aBorrego, Salud1 aCeccherini, Isabella1 aChakravarti, Aravinda1 aLyonnet, Stanislas1 aTam, Paul, K H1 aGarcia-Barceló, Maria-Mercè1 aHofstra, Robert, Mw uhttp://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1174-601877nas a2200577 4500008004100000245010800041210006900149260001600218490000700234100001900241700002000260700002300280700002600303700002500329700002200354700001700376700002200393700002700415700002000442700002300462700002000485700002300505700001900528700001800547700001800565700002400583700002300607700001800630700002200648700001600670700002600686700001800712700002300730700001700753700002200770700002300792700003500815700002900850700002400879700003100903700002800934700001800962700001900980700002500999700002601024700002301050700002101073700003401094700002701128856014401155 2017 eng d00aWhole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes0 aWhole exome sequencing coupled with unbiased functional analysis cJan-12-20170 v181 aGui, Hongsheng1 aSchriemer, Duco1 aCheng, William, W.1 aChauhan, Rajendra, K.1 aAntiňolo, Guillermo1 aBerrios, Courtney1 aBleda, Marta1 aBrooks, Alice, S.1 aBrouwer, Rutger, W. W.1 aBurns, Alan, J.1 aCherny, Stacey, S.1 aDopazo, Joaquin1 aEggen, Bart, J. L.1 aGriseri, Paola1 aJalloh, Binta1 aLe, Thuy-Linh1 aLui, Vincent, C. H.1 aLuzón-Toro, Berta1 aMatera, Ivana1 aNgan, Elly, S. W.1 aPelet, Anna1 aRuiz-Ferrer, Macarena1 aSham, Pak, C.1 aShepherd, Iain, T.1 aSo, Man-Ting1 aSribudiani, Yunia1 aTang, Clara, S. M.1 avan den Hout, Mirjam, C. G. N.1 avan der Linde, Herma, C.1 avan Ham, Tjakko, J.1 avan IJcken, Wilfred, F. J.1 aVerheij, Joke, B. G. M.1 aAmiel, Jeanne1 aBorrego, Salud1 aCeccherini, Isabella1 aChakravarti, Aravinda1 aLyonnet, Stanislas1 aTam, Paul, K. H.1 aGarcia-Barceló, Maria-Mercè1 aHofstra, Robert, M. W. uhttp://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1174-6http://link.springer.com/content/pdf/10.1186/s13059-017-1174-6.pdf03274nas a2200469 4500008004100000022001400041245010000055210006900155260001600224520184400240653001202084653000802096653001802104653002402122653001902146653000802165100002102173700001902194700001702213700002402230700002302254700002902277700002302306700002302329700002102352700001902373700002202392700003302414700002302447700001602470700002602486700002802512700002002540700002002560700002702580700002002607700002702627700001902654700002702673700002502700856007902725 2016 eng d a1537-171900a267 Spanish exomes reveal population-specific differences in disease-related genetic variation.0 a267 Spanish exomes reveal populationspecific differences in dise c2016 Jan 133 aRecent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalogue of local variability motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including about 10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies in order to distinguish real disease associations from population-specific polymorphisms.10adisease10aNGS10apolymorphisms10aPopulation genomics10aprioritization10aSNP1 aDopazo, Joaquín1 aAmadoz, Alicia1 aBleda, Marta1 aGarcía-Alonso, Luz1 aAlemán, Alejandro1 aGarcia-Garcia, Francisco1 aRodriguez, Juan, A1 aDaub, Josephine, T1 aMuntané, Gerard1 aRueda, Antonio1 aVela-Boza, Alicia1 aLópez-Domingo, Francisco, J1 aFlorido, Javier, P1 aArce, Pablo1 aRuiz-Ferrer, Macarena1 aMéndez-Vidal, Cristina1 aArnold, Todd, E1 aSpleiss, Olivia1 aAlvarez-Tejado, Miguel1 aNavarro, Arcadi1 aBhattacharya, Shomi, S1 aBorrego, Salud1 aSantoyo-López, Javier1 aAntiňolo, Guillermo uhttps://mbe.oxfordjournals.org/content/early/2016/02/17/molbev.msw005.full02961nas a2200505 4500008004100000022001400041245008800055210006900143260001300212300001000225490000900235520151700244653001501761653001701776653001001793653002101803653002101824653001001845653001101855653004201866653001101908653001101919653002801930653000901958653001301967653001301980653001401993653001402007653002302021100002002044700002102064700001902085700002902104700002302133700002202156700002202178700001902200700001902219700002002238700001702258700002302275700002102298700002102319856011502340 2016 eng d a1552-483300aScreening of CD96 and ASXL1 in 11 patients with Opitz C or Bohring-Opitz syndromes.0 aScreening of CD96 and ASXL1 in 11 patients with Opitz C or Bohri c2016 Jan a24-310 v170A3 aOpitz C trigonocephaly (or Opitz C syndrome, OTCS) and Bohring-Opitz syndrome (BOS or C-like syndrome) are two rare genetic disorders with phenotypic overlap. The genetic causes of these diseases are not understood. However, two genes have been associated with OTCS or BOS with dominantly inherited de novo mutations. Whereas CD96 has been related to OTCS (one case) and to BOS (one case), ASXL1 has been related to BOS only (several cases). In this study we analyze CD96 and ASXL1 in a group of 11 affected individuals, including 2 sibs, 10 of them were diagnosed with OTCS, and one had a BOS phenotype. Exome sequences were available on six patients with OTCS and three parent pairs. Thus, we could analyze the CD96 and ASXL1 sequences in these patients bioinformatically. Sanger sequencing of all exons of CD96 and ASXL1 was carried out in the remaining patients. Detailed scrutiny of the sequences and assessment of variants allowed us to exclude putative pathogenic and private mutations in all but one of the patients. In this patient (with BOS) we identified a de novo mutation in ASXL1 (c.2100dupT). By nature and location within the gene, this mutation resembles those previously described in other BOS patients and we conclude that it may be responsible for the condition. Our results indicate that in 10 of 11, the disease (OTCS or BOS) cannot be explained by small changes in CD96 or ASXL1. However, the cohort is too small to make generalizations about the genetic etiology of these diseases.
10aAdolescent10aAntigens, CD10aChild10aChild, Preschool10aCraniosynostoses10aExome10aFemale10aHigh-Throughput Nucleotide Sequencing10aHumans10aInfant10aIntellectual Disability10aMale10amutation10aPedigree10aPhenotype10aPrognosis10aRepressor Proteins1 aUrreizti, Roser1 aRoca-Ayats, Neus1 aTrepat, Judith1 aGarcia-Garcia, Francisco1 aAlemán, Alejandro1 aOrteschi, Daniela1 aMarangi, Giuseppe1 aNeri, Giovanni1 aOpitz, John, M1 aDopazo, Joaquin1 aCormand, Bru1 aVilageliu, Lluïsa1 aBalcells, Susana1 aGrinberg, Daniel uhttps://www.clinbioinfosspa.es/content/screening-cd96-and-asxl1-11-patients-opitz-c-or-bohring-opitz-syndromes03376nas a2200793 4500008004100000022001400041245011500055210006900170260001600239520112300255653001101378653000801389653002001397100001901417700002601436700001201462700001801474700002201492700002701514700002201541700002201563700001901585700002901604700002301633700002001656700002001676700002301696700002501719700002201744700002201766700002101788700004001809700001201849700001701861700001201878700001601890700001901906700001801925700002101943700001601964700002001980700002402000700002002024700001802044700001302062700001702075700001802092700002102110700002402131700002002155700002102175700001702196700002102213700002502234700002102259700001902280700001902299700002102318700001602339700001402355700001702369700001502386700001302401700003102414700002102445700002102466700002002487856007502507 2015 eng d a1548-710500aCombining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.0 aCombining tumor genome simulation with crowdsourcing to benchmar c2015 May 183 aThe detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.10acancer10aNGS10avariant calling1 aEwing, Adam, D1 aHoulahan, Kathleen, E1 aHu, Yin1 aEllrott, Kyle1 aCaloian, Cristian1 aYamaguchi, Takafumi, N1 aBare, Christopher1 aP’ng, Christine1 aWaggott, Daryl1 aSabelnykova, Veronica, Y1 aKellen, Michael, R1 aNorman, Thea, C1 aHaussler, David1 aFriend, Stephen, H1 aStolovitzky, Gustavo1 aMargolin, Adam, A1 aStuart, Joshua, M1 aBoutros, Paul, C1 aparticipants, ICGC-TCGA, DREAM Soma1 aXi, Liu1 aDewal, Ninad1 aFan, Yu1 aWang, Wenyi1 aWheeler, David1 aWilm, Andreas1 aTing, Grace, Hui1 aLi, Chenhao1 aBertrand, Denis1 aNagarajan, Niranjan1 aChen, Qing-Rong1 aHsu, Chih-Hao1 aHu, Ying1 aYan, Chunhua1 aKibbe, Warren1 aMeerzaman, Daoud1 aCibulskis, Kristian1 aRosenberg, Mara1 aBergelson, Louis1 aKiezun, Adam1 aRadenbaugh, Amie1 aSertier, Anne-Sophie1 aFerrari, Anthony1 aTonton, Laurie1 aBhutani, Kunal1 aHansen, Nancy, F1 aWang, Difei1 aSong, Lei1 aLai, Zhongwu1 aLiao, Yang1 aShi, Wei1 aCarbonell-Caballero, José1 aDopazo, Joaquín1 aLau, Cheryl, C K1 aGuinney, Justin uhttp://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3407.html02351nas a2200229 4500008004100000022001400041245014200055210006900197260001600266520153800282100001701820700002401837700001401861700001401875700001501889700002301904700001401927700001801941700001501959700001501974856013201989 2015 eng d a1523-174700aDifferential Features Between Chronic Skin Inflammatory Diseases Revealed in Skin-Humanized Psoriasis and Atopic Dermatitis Mouse Models.0 aDifferential Features Between Chronic Skin Inflammatory Diseases c2015 Sep 233 aPsoriasis (PS) and atopic dermatitis (AD) are chronic and relapsing inflammatory diseases of the skin affecting a large number of patients worldwide. Psoriasis is characterized by a Th1/Th17 immunological response whereas acute AD lesions exhibit Th2-dominant inflammation. Current single gene and signaling pathways-based models of inflammatory skin diseases are incomplete. Previous work allowed us to model psoriasis in skin-humanized mice through proper combinations of inflammatory cell components and disruption of barrier function. Herein we describe and characterize an animal model for AD using similar bioengineered-based approaches, by intradermal injection of human Th2 lymphocytes in regenerated human skin after partial removal of stratum corneum. In the present work we have extensively compared this model with the previous and an improved version of the PS model, in which Th17/Th1 lymphocytes replace exogenous cytokines. Comparative expression analyses revealed marked differences in specific epidermal proliferation and differentiation markers and immune-related molecules including antimicrobial peptides. Likewise, the composition of the dermal inflammatory infiltrate presented important differences. Availability of accurate and reliable animal models for these diseases will contribute to the understanding of the pathogenesis and provide valuable tools for drug development and testing.Journal of Investigative Dermatology accepted article preview online, 23 September 2015. doi:10.1038/jid.2015.362.
1 aCarretero, M1 aGuerrero-Aspizua, S1 aIllera, N1 aGalvez, V1 aNavarro, M1 aGarcía-García, F1 aDopazo, J1 aJorcano, J, L1 aLarcher, F1 aDel Rio, M uhttps://www.clinbioinfosspa.es/content/differential-features-between-chronic-skin-inflammatory-diseases-revealed-skin-humanized02478nas a2200325 4500008004100000022001400041245015000055210006900205260000900274300000700283490000600290520144200296653001401738653000901752653001901761100002301780700001701803700001901820700002401839700002601863700002001889700002801909700002601937700002601963700002001989700002502009700002002034700001902054856007902073 2015 eng d a1755-879400aIdentification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas.0 aIdentification of epistatic interactions through genomewide asso c2015 a830 v83 aBACKGROUND: The molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk. METHODS: We carried out the first screening for epistasis by Multifactor-Dimensionality Reduction (MDR) in genome-wide association study (GWAS) on sMTC and juvenile PTC, to identify the potential simultaneous involvement of pairs of variants in the disease. RESULTS: We have identified two significant epistatic gene interactions in sMTC (CHFR-AC016582.2 and C8orf37-RNU1-55P) and three in juvenile PTC (RP11-648k4.2-DIO1, RP11-648k4.2-DMGDH and RP11-648k4.2-LOXL1). Interestingly, each interacting gene pair included a non-coding RNA, providing thus support to the relevance that these elements are increasingly gaining to explain carcinoma development and progression. CONCLUSIONS: Overall, this study contributes to the understanding of the genetic basis of thyroid carcinoma susceptibility in two different case scenarios such as sMTC and juvenile PTC.10aepistasis10aGWAS10aThyroid cancer1 aLuzón-Toro, Berta1 aBleda, Marta1 aNavarro, Elena1 aGarcía-Alonso, Luz1 aRuiz-Ferrer, Macarena1 aMedina, Ignacio1 aMartín-Sánchez, Marta1 aGonzalez, Cristina, Y1 aFernández, Raquel, M1 aTorroglosa, Ana1 aAntiňolo, Guillermo1 aDopazo, Joaquin1 aBorrego, Salud uhttp://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-015-0160-701498nas a2200289 4500008004100000022001400041245014900055210006900204260000800273300000700281490000600288520057300294100002300867700001700890700001900907700002400926700002600950700002000976700002800996700002701024700002701051700002001078700002501098700002001123700001901143856004601162 2015 eng d a1755-879400aIdentification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas0 aIdentification of epistatic interactions through genomewide asso cDec a830 v83 aThe molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk.1 aLuzón-Toro, Berta1 aBleda, Marta1 aNavarro, Elena1 aGarcía-Alonso, Luz1 aRuiz-Ferrer, Macarena1 aMedina, Ignacio1 aMartín-Sánchez, Marta1 aGonzalez, Cristina, Y.1 aFernández, Raquel, M.1 aTorroglosa, Ana1 aAntiňolo, Guillermo1 aDopazo, Joaquin1 aBorrego, Salud uhttps://doi.org/10.1186/s12920-015-0160-702147nas a2200301 4500008004100000022001400041245009600055210006900151260001600220520124900236100002101485700002401506700001401530700001401544700002201558700001701580700001701597700001701614700002301631700001701654700001801671700001501689700001901704700001801723700001501741700001801756856007101774 2015 eng d a1546-169600aPrediction of human population responses to toxic compounds by a collaborative competition.0 aPrediction of human population responses to toxic compounds by a c2015 Aug 103 aThe ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson’s r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.1 aEduati, Federica1 aMangravite, Lara, M1 aWang, Tao1 aTang, Hao1 aBare, Christopher1 aHuang, Ruili1 aNorman, Thea1 aKellen, Mike1 aMenden, Michael, P1 aYang, Jichen1 aZhan, Xiaowei1 aZhong, Rui1 aXiao, Guanghua1 aXia, Menghang1 aAbdo, Nour1 aKosyk, Oksana uhttp://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3299.html02492nas a2200577 4500008004100000022001400041245006100055210005800116260001500174300001600189490000700205520082400212653000801036653001901044653001701063100001801080700002101098700002101119700002801140700002301168700001701191700002201208700002201230700003001252700001601282700002001298700002601318700002901344700002201373700002201395700002001417700002901437700002701466700002101493700001701514700002201531700002101553700002401574700002201598700002901620700002701649700002001676700002001696700002501716700002101741700002001762700001601782700002801798700002101826856006701847 2014 eng d a1098-100400aA New Overgrowth Syndrome is Due to Mutations in RNF125.0 aNew Overgrowth Syndrome is Due to Mutations in RNF125 c2014 Sep 5 a1436–14410 v353 aOvergrowth syndromes (OGS) are a group of disorders in which all parameters of growth and physical development are above the mean for age and sex. We evaluated a series of 270 families from the Spanish Overgrowth Syndrome Registry with no known overgrowth syndrome. We identified one de novo deletion and three missense mutations in RNF125 in six patients from 4 families with overgrowth, macrocephaly, intellectual disability, mild hydrocephaly, hypoglycaemia and inflammatory diseases resembling Sjögren syndrome. RNF125 encodes an E3 ubiquitin ligase and is a novel gene of OGS. Our studies of the RNF125 pathway point to upregulation of RIG-I-IPS1-MDA5 and/or disruption of the PI3K-AKT and interferon signaling pathways as the putative final effectors. This article is protected by copyright. All rights reserved.10aNGS10aprioritization10aRare Disease1 aTenorio, Jair1 aMansilla, Alicia1 aValencia, María1 aMartínez-Glez, Víctor1 aRomanelli, Valeria1 aArias, Pedro1 aCastrejón, Nerea1 aPoletta, Fernando1 aGuillén-Navarro, Encarna1 aGordo, Gema1 aMansilla, Elena1 aGarcía-Santiago, Fé1 aGonzález-Casado, Isabel1 aVallespín, Elena1 aPalomares, María1 aMori, María, A1 aSantos-Simarro, Fernando1 aGarcía-Miñaur, Sixto1 aFernández, Luis1 aMena, Rocío1 aBenito-Sanz, Sara1 aDel Pozo, Angela1 aSilla, Juan, Carlos1 aIbañez, Kristina1 aLópez-Granados, Eduardo1 aMartín-Trujillo, Alex1 aMontaner, David1 aHeath, Karen, E1 aCampos-Barros, Angel1 aDopazo, Joaquín1 aNevado, Julián1 aMonk, David1 aRuiz-Pérez, Víctor, L1 aLapunzina, Pablo uhttp://onlinelibrary.wiley.com/doi/10.1002/humu.22689/abstract03075nas a2200385 4500008004100000022001400041245005700055210005600112260000900168300000700177490001400184520197500198653002202173653001502195653002002210653003002230653002902260653002002289653001502309653003002324653001602354653001202370653002902382653002002411653001402431100002102445700001802466700002002484700001802504700002002522700002102542700002002563700001602583856009002599 2014 eng d a1752-050900aPathway network inference from gene expression data.0 aPathway network inference from gene expression data c2014 aS70 v8 Suppl 23 aBACKGROUND: The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules.
RESULTS: We present a novel computational methodology to study the functional interconnections among the molecular elements of a biological system. The PANA approach uses high-throughput genomics measurements and a functional annotation scheme to extract an activity profile from each functional block -or pathway- followed by machine-learning methods to infer the relationships between these functional profiles. The result is a global, interconnected network of pathways that represents the functional cross-talk within the molecular system. We have applied this approach to describe the functional transcriptional connections during the yeast cell cycle and to identify pathways that change their connectivity in a disease condition using an Alzheimer example.
CONCLUSIONS: PANA is a useful tool to deepen in our understanding of the functional interdependences that operate within complex biological systems. We show the approach is algorithmically consistent and the inferred network is well supported by the available functional data. The method allows the dissection of the molecular basis of the functional connections and we describe the different regulatory mechanisms that explain the network's topology obtained for the yeast cell cycle data.
10aAlzheimer Disease10aCell Cycle10aDNA Replication10aGene Expression Profiling10aGene Regulatory Networks10aGluconeogenesis10aGlycolysis10aOxidative Phosphorylation10aProteolysis10aPurines10aSaccharomyces cerevisiae10aSystems biology10aUbiquitin1 aPonzoni, Ignacio1 aNueda, María1 aTarazona, Sonia1 aGötz, Stefan1 aMontaner, David1 aDussaut, Julieta1 aDopazo, Joaquin1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/pathway-network-inference-gene-expression-data02925nas a2200409 4500008004100000022001400041245011400055210006900169260001300238300001000251490000700261520165700268653001201925653001501937653001101952653003901963653001802002653001902020653001202039653003102051653001302082653000902095653001402104653001602118653002702134653002402161653001802185100002102203700002502224700003102249700001602280700002002296700001802316700002502334700003202359856012402391 2014 eng d a1096-093700aSequencing and functional analysis of the genome of a nematode egg-parasitic fungus, Pochonia chlamydosporia.0 aSequencing and functional analysis of the genome of a nematode e c2014 Apr a69-800 v653 aPochonia chlamydosporia is a worldwide-distributed soil fungus with a great capacity to infect and destroy the eggs and kill females of plant-parasitic nematodes. Additionally, it has the ability to colonize endophytically roots of economically-important crop plants, thereby promoting their growth and eliciting plant defenses. This multitrophic behavior makes P. chlamydosporia a potentially useful tool for sustainable agriculture approaches. We sequenced and assembled ∼41 Mb of P. chlamydosporia genomic DNA and predicted 12,122 gene models, of which many were homologous to genes of fungal pathogens of invertebrates and fungal plant pathogens. Predicted genes (65%) were functionally annotated according to Gene Ontology, and 16% of them found to share homology with genes in the Pathogen Host Interactions (PHI) database. The genome of this fungus is highly enriched in genes encoding hydrolytic enzymes, such as proteases, glycoside hydrolases and carbohydrate esterases. We used RNA-Seq technology in order to identify the genes expressed during endophytic behavior of P. chlamydosporia when colonizing barley roots. Functional annotation of these genes showed that hydrolytic enzymes and transporters are expressed during endophytism. This structural and functional analysis of the P. chlamydosporia genome provides a starting point for understanding the molecular mechanisms involved in the multitrophic lifestyle of this fungus. The genomic information provided here should also prove useful for enhancing the capabilities of this fungus as a biocontrol agent of plant-parasitic nematodes and as a plant growth-promoting organism.
10aAnimals10aAscomycota10aFemale10aGene Expression Regulation, Fungal10aGene ontology10aGenome, Fungal10aHordeum10aHost-Pathogen Interactions10aNematoda10aOvum10aPhylogeny10aPlant Roots10aSequence Analysis, DNA10aSignal Transduction10aTranscriptome1 aLarriba, Eduardo1 aJaime, María, D L A1 aCarbonell-Caballero, José1 aConesa, Ana1 aDopazo, Joaquin1 aNislow, Corey1 aMartín-Nieto, José1 aLopez-Llorca, Luis, Vicente uhttps://www.clinbioinfosspa.es/content/sequencing-and-functional-analysis-genome-nematode-egg-parasitic-fungus-pochonia03200nas a2200517 4500008004100000022001400041245017300055210006900228260001300297300001000310490000700320520152000327653003201847653003101879653001601910653001101926653000901937653002301946653002801969653001501997653002002012100002802032700002302060700001602083700002402099700002502123700002102148700001902169700002202188700002102210700002002231700002002251700002202271700001902293700002102312700002802333700002202361700002002383700001702403700002702420700002602447700002102473700002402494700002802518856013602546 2014 eng d a1098-100400aTwo novel mutations in the BCKDK (branched-chain keto-acid dehydrogenase kinase) gene are responsible for a neurobehavioral deficit in two pediatric unrelated patients.0 aTwo novel mutations in the BCKDK branchedchain ketoacid dehydrog c2014 Apr a470-70 v353 aInactivating mutations in the BCKDK gene, which codes for the kinase responsible for the negative regulation of the branched-chain α-keto acid dehydrogenase complex (BCKD), have recently been associated with a form of autism in three families. In this work, two novel exonic BCKDK mutations, c.520C>G/p.R174G and c.1166T>C/p.L389P, were identified at the homozygous state in two unrelated children with persistently reduced body fluid levels of branched-chain amino acids (BCAAs), developmental delay, microcephaly, and neurobehavioral abnormalities. Functional analysis of the mutations confirmed the missense character of the c.1166T>C change and showed a splicing defect r.[520c>g;521_543del]/p.R174Gfs1*, for c.520C>G due to the presence of a new donor splice site. Mutation p.L389P showed total loss of kinase activity. Moreover, patient-derived fibroblasts showed undetectable (p.R174Gfs1*) or barely detectable (p.L389P) levels of BCKDK protein and its phosphorylated substrate (phospho-E1α), resulting in increased BCKD activity and the very rapid BCAA catabolism manifested by the patients' clinical phenotype. Based on these results, a protein-rich diet plus oral BCAA supplementation was implemented in the patient homozygous for p.R174Gfs1*. This treatment normalized plasma BCAA levels and improved growth, developmental and behavioral variables. Our results demonstrate that BCKDK mutations can result in neurobehavioral deficits in humans and support the rationale for dietary intervention.
10aAmino Acids, Branched-Chain10aDevelopmental Disabilities10aFibroblasts10aHumans10aMale10aMutation, Missense10aNervous System Diseases10aPediatrics10aProtein Kinases1 aGarcía-Cazorla, Angels1 aOyarzabal, Alfonso1 aFort, Joana1 aRobles, Concepción1 aCastejón, Esperanza1 aRuiz-Sala, Pedro1 aBodoy, Susanna1 aMerinero, Begoña1 aLopez-Sala, Anna1 aDopazo, Joaquin1 aNunes, Virginia1 aUgarte, Magdalena1 aArtuch, Rafael1 aPalacín, Manuel1 aRodríguez-Pombo, Pilar1 aAlcaide, Patricia1 aNavarrete, Rosa1 aSanz, Paloma1 aFont-Llitjós, Mariona1 aVilaseca, Ma, Antonia1 aOrmaizabal, Aida1 aPristoupilova, Anna1 aAgulló, Sergi, Beltran uhttps://www.clinbioinfosspa.es/content/two-novel-mutations-bckdk-branched-chain-keto-acid-dehydrogenase-kinase-gene-are-responsible02611nas a2200313 4500008004100000022001400041245017200055210006900227260001600296300001000312490000700322520157100329100002801900700002301928700001601951700002401967700002501991700002102016700001902037700002202056700002102078700002102099700002002120700002202140700001902162700002102181700002802202856006702230 2014 eng d a1098-100400aTwo Novel Mutations in the BCKDK Gene (Branched-Chain Keto-Acid Dehydrogenase Kinase) are Responsible of a Neurobehavioral Deficit in two Pediatric Unrelated Patients.0 aTwo Novel Mutations in the BCKDK Gene BranchedChain KetoAcid Deh c2014 Jan 21 a470-70 v353 aInactivating mutations in the BCKDK gene, which codes for the kinase responsible for the negative regulation of the branched-chain keto-acid dehydrogenase complex (BCKD), have recently been associated with a form of autism in three families. In this work, two novel exonic BCKDK mutations, c.520C>G/p.R174G and c.1166T>C/p.L389P, were identified at the homozygous state in two unrelated children with persistently reduced body fluid levels of branched-chain amino acids (BCAAs), developmental delay, microcephaly and neurobehavioral abnormalities. Functional analysis of the mutations confirmed the missense character of the c.1166T>C change and showed a splicing defect r.[520c>g;521_543del]/p.R174Gfs1*, for c.520C>G due to the presence of a new donor splice site. Mutation p.L389P showed total loss of kinase activity. Moreover, patient-derived fibroblasts showed undetectable (p.R174Gfs1*) or barely detectable (p.L389P) levels of BCKDK protein and its phosphorylated substrate (phospho-E1α), resulting in increased BCKD activity and the very rapid BCAA catabolism manifested by the patients’ clinical phenotype. Based on these results, a protein-rich diet plus oral BCAA supplementation was implemented in the patient homozygous for p.R174Gfs1*. This treatment normalized plasma BCAA levels and improved growth, developmental and behavioral variables. Our results demonstrate that BCKDK mutations can result in neurobehavioral deficits in humans and support the rationale for dietary intervention. This article is protected by copyright. All rights reserved.1 aGarcía-Cazorla, Angels1 aOyarzabal, Alfonso1 aFort, Joana1 aRobles, Concepción1 aCastejón, Esperanza1 aRuiz-Sala, Pedro1 aBodoy, Susanna1 aMerinero, Begoña1 aLopez-Sala, Anna1 aDopazo, Joaquín1 aNunes, Virginia1 aUgarte, Magdalena1 aArtuch, Rafael1 aPalacín, Manuel1 aRodríguez-Pombo, Pilar uhttp://onlinelibrary.wiley.com/doi/10.1002/humu.22513/abstract02660nas a2200421 4500008004100000022001400041245010400055210006900159260001700228300000900245490000800254520136600262653001501628653001001643653003201653653001001685653001001695653001101705653004201716653001101758653001101769653000901780653003001789653001301819100001901832700003401851700002701885700002601912700002801938700002301966700001901989700002902008700002002037700001702057700001802074700001902092856012702111 2013 eng d a1096-720600aExome sequencing identifies a new mutation in SERAC1 in a patient with 3-methylglutaconic aciduria.0 aExome sequencing identifies a new mutation in SERAC1 in a patien c2013 Sep-Oct a73-70 v1103 a3-Methylglutaconic aciduria (3-MGA-uria) is a heterogeneous group of syndromes characterized by an increased excretion of 3-methylglutaconic and 3-methylglutaric acids. Five types of 3-MGA-uria (I to V) with different clinical presentations have been described. Causative mutations in TAZ, OPA3, DNAJC19, ATP12, ATP5E, and TMEM70 have been identified. After excluding the known genetic causes of 3-MGA-uria we used exome sequencing to investigate a patient with Leigh syndrome and 3-MGA-uria. We identified a homozygous variant in SERAC1 (c.202C>T; p.Arg68*), that generates a premature stop codon at position 68 of SERAC1 protein. Western blot analysis in patient's fibroblasts showed a complete absence of SERAC1 that was consistent with the prediction of a truncated protein and supports the pathogenic role of the mutation. During the course of this project a parallel study identified mutations in SERAC1 as the genetic cause of the disease in 15 patients with MEGDEL syndrome, which was compatible with the clinical and biochemical phenotypes of the patient described here. In addition, our patient developed microcephaly and optic atrophy, two features not previously reported in MEGDEL syndrome. We highlight the usefulness of exome sequencing to reveal the genetic bases of human rare diseases even if only one affected individual is available.
10aAdolescent10aAdult10aCarboxylic Ester Hydrolases10aChild10aExome10aFemale10aHigh-Throughput Nucleotide Sequencing10aHumans10aInfant10aMale10aMetabolism, Inborn Errors10amutation1 aTort, Frederic1 aGarcía-Silva, María, Teresa1 aFerrer-Cortès, Xènia1 aNavarro-Sastre, Aleix1 aGarcia-Villoria, Judith1 aColl, Maria, Josep1 aVidal, Enrique1 aJiménez-Almazán, Jorge1 aDopazo, Joaquin1 aBriones, Paz1 aElpeleg, Orly1 aRibes, Antonia uhttps://www.clinbioinfosspa.es/content/exome-sequencing-identifies-new-mutation-serac1-patient-3-methylglutaconic-aciduria02491nas a2200373 4500008004100000022001400041245014600055210006900201260001600270300000800286490000600294520125600300653001101556653003801567653003401605653001301639653002501652653001101677653000901688100002701697700001701724700002701741700002001768700002301788700002401811700002001835700002001855700002801875700002001903700002501923700002001948700001901968856013001987 2012 eng d a1750-117200aFour new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease.0 aFour new loci associations discovered by pathwaybased and networ c2012 Dec 28 a1030 v73 aFinding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung's disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.
10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHirschsprung Disease10aHumans10aMale1 aFernández, Raquel, Ma1 aBleda, Marta1 aNúñez-Torres, Rocío1 aMedina, Ignacio1 aLuzón-Toro, Berta1 aGarcía-Alonso, Luz1 aTorroglosa, Ana1 aMarbà, Martina1 aEnguix-Riego, Ma, Valle1 aMontaner, David1 aAntiňolo, Guillermo1 aDopazo, Joaquin1 aBorrego, Salud uhttps://www.clinbioinfosspa.es/content/four-new-loci-associations-discovered-pathway-based-and-network-analyses-genome-wide-002193nas a2200289 4500008004100000022001400041245014800055210006900203260001600272300000800288490000600296520126100302100002701563700001701590700002701607700002001634700002301654700002401677700002001701700002001721700002801741700002001769700002501789700002101814700001901835856004901854 2012 eng d a1750-117200aFour new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung’s disease.0 aFour new loci associations discovered by pathwaybased and networ c2012 Dec 28 a1030 v73 aABSTRACT: Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung’s disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.1 aFernández, Raquel, Ma1 aBleda, Marta1 aNúñez-Torres, Rocío1 aMedina, Ignacio1 aLuzón-Toro, Berta1 aGarcía-Alonso, Luz1 aTorroglosa, Ana1 aMarbà, Martina1 aEnguix-Riego, Ma, Valle1 aMontaner, David1 aAntiňolo, Guillermo1 aDopazo, Joaquín1 aBorrego, Salud uhttp://www.ojrd.com/content/7/1/103/abstract03423nas a2200253 4500008004100000022001400041245011200055210006900167260000900236300000800245490000700253520257000260100002502830700003202855700001602887700001702903700002102920700002502941700002202966700001802988700002203006700001803028856012303046 2012 eng d a1471-216400aIdentification of yeast genes that confer resistance to chitosan oligosaccharide (COS) using chemogenomics.0 aIdentification of yeast genes that confer resistance to chitosan c2012 a2670 v133 aBACKGROUND: Chitosan oligosaccharide (COS), a deacetylated derivative of chitin, is an abundant, and renewable natural polymer. COS has higher antimicrobial properties than chitosan and is presumed to act by disrupting/permeabilizing the cell membranes of bacteria, yeast and fungi. COS is relatively non-toxic to mammals. By identifying the molecular and genetic targets of COS, we hope to gain a better understanding of the antifungal mode of action of COS. RESULTS: Three different chemogenomic fitness assays, haploinsufficiency (HIP), homozygous deletion (HOP), and multicopy suppression (MSP) profiling were combined with a transcriptomic analysis to gain insight in to the mode of action and mechanisms of resistance to chitosan oligosaccharides. The fitness assays identified 39 yeast deletion strains sensitive to COS and 21 suppressors of COS sensitivity. The genes identified are involved in processes such as RNA biology (transcription, translation and regulatory mechanisms), membrane functions (e.g. signalling, transport and targeting), membrane structural components, cell division, and proteasome processes. The transcriptomes of control wild type and 5 suppressor strains overexpressing ARL1, BCK2, ERG24, MSG5, or RBA50, were analyzed in the presence and absence of COS. Some of the up-regulated transcripts in the suppressor overexpressing strains exposed to COS included genes involved in transcription, cell cycle, stress response and the Ras signal transduction pathway. Down-regulated transcripts included those encoding protein folding components and respiratory chain proteins. The COS-induced transcriptional response is distinct from previously described environmental stress responses (i.e. thermal, salt, osmotic and oxidative stress) and pre-treatment with these well characterized environmental stressors provided little or any resistance to COS. CONCLUSIONS: Overexpression of the ARL1 gene, a member of the Ras superfamily that regulates membrane trafficking, provides protection against COS-induced cell membrane permeability and damage. We found that the ARL1 COS-resistant over-expression strain was as sensitive to Amphotericin B, Fluconazole and Terbinafine as the wild type cells and that when COS and Fluconazole are used in combination they act in a synergistic fashion. The gene targets of COS identified in this study indicate that COS’s mechanism of action is different from other commonly studied fungicides that target membranes, suggesting that COS may be an effective fungicide for drug-resistant fungal pathogens.1 aJaime, María, D L A1 aLopez-Llorca, Luis, Vicente1 aConesa, Ana1 aLee, Anna, Y1 aProctor, Michael1 aHeisler, Lawrence, E1 aGebbia, Marinella1 aGiaever, Guri1 aWestwood, Timothy1 aNislow, Corey uhttps://www.clinbioinfosspa.es/content/identification-yeast-genes-confer-resistance-chitosan-oligosaccharide-cos-using01738nas a2200193 4500008004100000022001400041245017100055210006900226260001600295520097200311100001801283700001601301700001801317700002101335700001801356700002201374700001801396856013001414 2012 eng d a1364-370300aMicroarray analysis of Etrog citron (Citrus medica L.) reveals changes in chloroplast, cell wall, peroxidase and symporter activities in response to viroid infection.0 aMicroarray analysis of Etrog citron Citrus medica L reveals chan c2012 Mar 153 aViroids are small (246-401 nucleotides), single-stranded, circular RNA molecules that infect several crop plants and can cause diseases of economic importance. Citrus are the hosts in which the largest number of viroids have been identified. Citrus exocortis viroid (CEVd), the causal agent of citrus exocortis disease, induces considerable losses in citrus crops. Changes in the gene expression profile during the early (pre-symptomatic) and late (post-symptomatic) stages of Etrog citron infected with CEVd were investigated using a citrus cDNA microarray. MaSigPro analysis was performed and, on the basis of gene expression profiles as a function of the time after infection, the differentially expressed genes were classified into five clusters. FatiScan analysis revealed significant enrichment of functional categories for each cluster, indicating that viroid infection triggers important changes in chloroplast, cell wall, peroxidase and symporter activities.1 aRizza, Serena1 aConesa, Ana1 aJuarez, José1 aCatara, Antonino1 aNavarro, Luis1 aDuran-Vila, Nuria1 aAncillo, Gema uhttps://www.clinbioinfosspa.es/content/microarray-analysis-etrog-citron-citrus-medica-l-reveals-changes-chloroplast-cell-wall01878nas a2200289 4500008004100000022001400041245008700055210006900142260000900211300001100220490000600231520100600237100002701243700002001270700002801290700001901318700002701337700002201364700001801386700002001404700002001424700001801444700002101462700002101483700002001504856006401524 2012 eng d a1748-567300aSelect your SNPs (SYSNPs): a web tool for automatic and massive selection of SNPs.0 aSelect your SNPs SYSNPs a web tool for automatic and massive sel c2012 a324-340 v63 aAssociation studies are the choice approach in the discovery of the genomic basis of complex traits. To carry out such analysis, researchers frequently need to (1) select optimally informative sets of Single Nucleotide Polymorphisms (SNPs) in candidate regions and (2) annotate the results of associations found by means of genome-wide SNP arrays. These are complex tasks, since many criteria have to be considered, including the SNPs’ functional properties, technological information and haplotype frequencies in given populations. SYSNPs implements algorithms that allow for efficient and simultaneous consideration of all the relevant criteria to obtain sets of SNPs that properly cover arbitrarily large lists of genes or genomic regions. Complementarily, SYSNPs allows for comprehensive functional annotation of SNPs linked to any given marker SNP. SYSNPs dramatically reduces the effort needed for SNP selection from days of searching various databases to a few minutes using a simple browser.1 aLorente-Galdos, Belén1 aMedina, Ignacio1 aMorcillo-Suarez, Carlos1 aHeredia, Txema1 aCarreño-Torres, Angel1 aSangrós, Ricardo1 aAlegre, Josep1 aPita, Guillermo1 aVellalta, Gemma1 aMalats, Nuria1 aPisano, David, G1 aDopazo, Joaquín1 aNavarro, Arcadi uhttp://inderscience.metapress.com/content/f76740x8071u513n/03140nas a2200145 4500008004100000022001400041245012900055210006900184260001600253520254200269100002002811700002002831700001602851856012702867 2011 eng d a1468-435700aARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments.0 aARSyN a method for the identification and removal of systematic c2011 Nov 143 aTranscriptomic profiling experiments that aim to the identification of responsive genes in specific biological conditions are commonly set up under defined experimental designs that try to assess the effects of factors and their interactions on gene expression. Data from these controlled experiments, however, may also contain sources of unwanted noise that can distort the signal under study, affect the residuals of applied statistical models, and hamper data analysis. Commonly, normalization methods are applied to transcriptomics data to remove technical artifacts, but these are normally based on general assumptions of transcript distribution and greatly ignore both the characteristics of the experiment under consideration and the coordinative nature of gene expression. In this paper, we propose a novel methodology, ARSyN, for the preprocessing of microarray data that takes into account these 2 last aspects. By combining analysis of variance (ANOVA) modeling of gene expression values and multivariate analysis of estimated effects, the method identifies the nonstructured part of the signal associated to the experimental factors (the noise within the signal) and the structured variation of the ANOVA errors (the signal of the noise). By removing these noise fractions from the original data, we create a filtered data set that is rich in the information of interest and includes only the random noise required for inferential analysis. In this work, we focus on multifactorial time course microarray (MTCM) experiments with 2 factors: one quantitative such as time or dosage and the other qualitative, as tissue, strain, or treatment. However, the method can be used in other situations such as experiments with only one factor or more complex designs with more than 2 factors. The filtered data obtained after applying ARSyN can be further analyzed with the appropriate statistical technique to obtain the biological information required. To evaluate the performance of the filtering strategy, we have applied different statistical approaches for MTCM analysis to several real and simulated data sets, studying also the efficiency of these techniques. By comparing the results obtained with the original and ARSyN filtered data and also with other filtering techniques, we can conclude that the proposed method increases the statistical power to detect biological signals, especially in cases where there are high levels of structural noise. Software for ARSyN is freely available at http://www.ua.es/personal/mj.nueda.1 aNueda, Maria, J1 aFerrer, Alberto1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/arsyn-method-identification-and-removal-systematic-noise-multifactorial-time-course02878nas a2200301 4500008004100000245015000041210006900191260001600260300001200276490000700288520183800295100001902133700002202152700002502174700002102199700002002220700002002240700001702260700002102277700002202298700002502320700002102345700002002366700001802386700002102404700002402425856012702449 2011 eng d00aDifferential Lipid Partitioning Between Adipocytes and Tissue Macrophages Modulates Macrophage Lipotoxicity and M2/M1 Polarization in Obese Mice.0 aDifferential Lipid Partitioning Between Adipocytes and Tissue Ma c2011 Jan 24 a797-8090 v603 aOBJECTIVE Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. RESEARCH DESIGN AND METHODS We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. RESULTS We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell-like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. CONCLUSIONS Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization.
1 aPrieur, Xavier1 aMok, Crystal, Y L1 aVelagapudi, Vidya, R1 aNúñez, Vanessa1 aFuentes, Lucía1 aMontaner, David1 aIshikawa, Ko1 aCamacho, Alberto1 aBarbarroja, Nuria1 aO’Rahilly, Stephen1 aSethi, Jaswinder1 aDopazo, Joaquin1 aOresic, Matej1 aRicote, Mercedes1 aVidal-Puig, Antonio uhttps://www.clinbioinfosspa.es/content/differential-lipid-partitioning-between-adipocytes-and-tissue-macrophages-modulates01382nas a2200313 4500008004100000245005700041210005500098260001300153300001300166490000600179520044900185100001700634700002200651700002700673700002200700700002000722700002200742700001800764700001900782700001700801700003300818700002800851700002000879700002600899700002500925700001600950700002100966856008100987 2011 eng d00aDiscovery of an ebolavirus-like filovirus in europe.0 aDiscovery of an ebolaviruslike filovirus in europe c2011 Oct ae10023040 v73 aFiloviruses, amongst the most lethal of primate pathogens, have only been reported as natural infections in sub-Saharan Africa and the Philippines. Infections of bats with the ebolaviruses and marburgviruses do not appear to be associated with disease. Here we report identification in dead insectivorous bats of a genetically distinct filovirus, provisionally named Lloviu virus, after the site of detection, Cueva del Lloviu, in Spain.
1 aNegredo, Ana1 aPalacios, Gustavo1 aVázquez-Morón, Sonia1 aGonzález, Félix1 aDopazo, Hernán1 aMolero, Francisca1 aJuste, Javier1 aQuetglas, Juan1 aSavji, Nazir1 aMartínez, Maria, de la Cruz1 aHerrera, Jesus, Enrique1 aPizarro, Manuel1 aHutchison, Stephen, K1 aEchevarría, Juan, E1 aLipkin, Ian1 aTenorio, Antonio uhttps://www.clinbioinfosspa.es/content/discovery-ebolavirus-filovirus-europe02924nas a2200433 4500008004100000022001400041245013300055210006900188260000900257300001100266490000600277520154700283653001201830653002801842653001001870653002201880653001101902653002301913653001101936653001201947653001301959653001301972653002301985653004402008653003002052653003102082653002502113653001802138100003302156700001902189700002202208700002002230700002002250700002002270700002002290700002002310700002502330856013502355 2011 eng d a1932-620300aMutation screening of multiple genes in Spanish patients with autosomal recessive retinitis pigmentosa by targeted resequencing.0 aMutation screening of multiple genes in Spanish patients with au c2011 ae278940 v63 aRetinitis Pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. RP is the leading cause of visual loss in individuals younger than 60 years, with a prevalence of about 1 in 4000. The molecular genetic diagnosis of autosomal recessive RP (arRP) is challenging due to the large genetic and clinical heterogeneity. Traditional methods for sequencing arRP genes are often laborious and not easily available and a screening technique that enables the rapid detection of the genetic cause would be very helpful in the clinical practice. The goal of this study was to develop and apply microarray-based resequencing technology capable of detecting both known and novel mutations on a single high-throughput platform. Hence, the coding regions and exon/intron boundaries of 16 arRP genes were resequenced using microarrays in 102 Spanish patients with clinical diagnosis of arRP. All the detected variations were confirmed by direct sequencing and potential pathogenicity was assessed by functional predictions and frequency in controls. For validation purposes 4 positive controls for variants consisting of previously identified changes were hybridized on the array. As a result of the screening, we detected 44 variants, of which 15 are very likely pathogenic detected in 14 arRP families (14%). Finally, the design of this array can easily be transformed in an equivalent diagnostic system based on targeted enrichment followed by next generation sequencing.
10aAlleles10aDNA Mutational Analysis10aExons10aGenetic Variation10aGenome10aHispanic or Latino10aHumans10aIntrons10aLanguage10amutation10aMutation, Missense10aOligonucleotide Array Sequence Analysis10aPolymerase Chain Reaction10aReproducibility of Results10aRetinitis pigmentosa10aUnited States1 adel Pozo, María, González-1 aBorrego, Salud1 aBarragán, Isabel1 aPieras, Juan, I1 aSantoyo, Javier1 aMatamala, Nerea1 aNaranjo, Belén1 aDopazo, Joaquin1 aAntiňolo, Guillermo uhttps://www.clinbioinfosspa.es/content/mutation-screening-multiple-genes-spanish-patients-autosomal-recessive-retinitis-pigmentosa01461nas a2200253 4500008004100000245009300041210006900134260000900203300000700212490000700219520063100226100002300857700001500880700001900895700002300914700002800937700001500965700001700980700002100997700002401018700002001042700002001062856012501082 2011 eng d00aRecent human evolution has shaped geographical differences in susceptibility to disease.0 aRecent human evolution has shaped geographical differences in su c2011 a550 v123 aSearching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.
1 aMarigorta, Urko, M1 aLao, Oscar1 aCasals, Ferran1 aCalafell, Francesc1 aMorcillo-Suarez, Carlos1 aFaria, Rui1 aBosch, Elena1 aSerra, François1 aBertranpetit, Jaume1 aDopazo, Hernán1 aNavarro, Arcadi uhttps://www.clinbioinfosspa.es/content/recent-human-evolution-has-shaped-geographical-differences-susceptibility-disease02554nas a2200361 4500008004100000245014100041210006900182260001600251300003100267490000700298520145100305653001501756653002001771653001501791653001001806653000801816653000901824100002001833700002101853700001701874700002101891700001801912700001601930700002301946700002901969700002701998700002002025700002302045700002002068700002002088700002102108856006302129 2010 eng d00aBabelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.0 aBabelomics an integrative platform for the analysis of transcrip c2010 May 16 aW210-W213. Featured in NAR0 v383 aBabelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein-protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org.
10ababelomics10agene expression10agenotyping10agepas10aGSA10aGWAS1 aMedina, Ignacio1 aCarbonell, José1 aPulido, Luis1 aMadeira, Sara, C1 aGoetz, Stefan1 aConesa, Ana1 aTárraga, Joaquín1 aPascual-Montano, Alberto1 aNogales-Cadenas, Ruben1 aSantoyo, Javier1 aGarcía, Francisco1 aMarbà, Martina1 aMontaner, David1 aDopazo, Joaquín uhttp://nar.oxfordjournals.org/content/38/suppl_2/W210.full03760nas a2200625 4500008004100000022001400041245009800055210006900153260001600222300001100238490000600249520178700255653001002042653004902052653001102101653002102112653004902133653002502182653002902207653002402236653002802260653001102288653001902299653003802318653003402356653001302390653002302403653001102426653001502437653001102452653003602463653003702499653002902536653003802565653002002603653002002623653002002643653001702663100002102680700002002701700002402721700002702745700002102772700002202793700002202815700002502837700001702862700002002879700002102899700001902920700001902939700002102958700002602979856012903005 2010 eng d a1932-620300aExploring the link between germline and somatic genetic alterations in breast carcinogenesis.0 aExploring the link between germline and somatic genetic alterati c2010 Nov 22 ae140780 v53 aRecent genome-wide association studies (GWASs) have identified candidate genes contributing to cancer risk through low-penetrance mutations. Many of these genes were unexpected and, intriguingly, included well-known players in carcinogenesis at the somatic level. To assess the hypothesis of a germline-somatic link in carcinogenesis, we evaluated the distribution of somatic gene labels within the ordered results of a breast cancer risk GWAS. This analysis suggested frequent influence on risk of genetic variation in loci encoding for "driver kinases" (i.e., kinases encoded by genes that showed higher somatic mutation rates than expected by chance and, therefore, whose deregulation may contribute to cancer development and/or progression). Assessment of these predictions using a population-based case-control study in Poland replicated the association for rs3732568 in EPHB1 (odds ratio (OR) = 0.79; 95% confidence interval (CI): 0.63-0.98; P(trend) = 0.031). Analyses by early age at diagnosis and by estrogen receptor α (ERα) tumor status indicated potential associations for rs6852678 in CDKL2 (OR = 0.32, 95% CI: 0.10-1.00; P(recessive) = 0.044) and rs10878640 in DYRK2 (OR = 2.39, 95% CI: 1.32-4.30; P(dominant) = 0.003), and for rs12765929, rs9836340, rs4707795 in BMPR1A, EPHA3 and EPHA7, respectively (ERα tumor status P(interaction)<0.05). The identification of three novel candidates as EPH receptor genes might indicate a link between perturbed compartmentalization of early neoplastic lesions and breast cancer risk and progression. Together, these data may lay the foundations for replication in additional populations and could potentially increase our knowledge of the underlying molecular mechanisms of breast carcinogenesis.
10aAdult10aBone Morphogenetic Protein Receptors, Type I10aBreast10aBreast Neoplasms10aCalcium-Calmodulin-Dependent Protein Kinases10aCase-Control Studies10aCyclin-Dependent Kinases10aDisease Progression10aEstrogen Receptor alpha10aFemale10aGene Frequency10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aGerm-Line Mutation10aHumans10aOdds Ratio10aPoland10aPolymorphism, Single Nucleotide10aProtein Serine-Threonine Kinases10aProtein-Tyrosine Kinases10aReceptor Protein-Tyrosine Kinases10aReceptor, EphA310aReceptor, EphA710aReceptor, EphB110aRisk Factors1 aBonifaci, Núria1 aGórski, Bohdan1 aMasojć, Bartlomiej1 aWokołorczyk, Dominika1 aJakubowska, Anna1 aDębniak, Tadeusz1 aBerenguer, Antoni1 aMusach, Jordi, Serra1 aBrunet, Joan1 aDopazo, Joaquin1 aNarod, Steven, A1 aLubiński, Jan1 aLázaro, Conxi1 aCybulski, Cezary1 aPujana, Miguel, Angel uhttps://www.clinbioinfosspa.es/content/exploring-link-between-germline-and-somatic-genetic-alterations-breast-carcinogenesis03020nas a2200541 4500008004100000022001400041245013100055210006900186260001300255300001100268490000700279520146000286653001501746653002301761653002701784653003001811653001301841653001101854653003001865653004401895653001401939653003001953653001301983653002001996100001102016700001902027700001802046700001302064700001802077700001802095700002102113700001402134700001602148700001802164700001202182700001402194700001202208700001202220700001102232700001402243700001802257700001702275700001702292700001202309700001102321700001602332856013002348 2010 eng d a1473-115000aFunctional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes.0 aFunctional analysis of multiple genomic signatures demonstrates c2010 Aug a310-230 v103 aGene expression signatures of toxicity and clinical response benefit both safety assessment and clinical practice; however, difficulties in connecting signature genes with the predicted end points have limited their application. The Microarray Quality Control Consortium II (MAQCII) project generated 262 signatures for ten clinical and three toxicological end points from six gene expression data sets, an unprecedented collection of diverse signatures that has permitted a wide-ranging analysis on the nature of such predictive models. A comprehensive analysis of the genes of these signatures and their nonredundant unions using ontology enrichment, biological network building and interactome connectivity analyses demonstrated the link between gene signatures and the biological basis of their predictive power. Different signatures for a given end point were more similar at the level of biological properties and transcriptional control than at the gene level. Signatures tended to be enriched in function and pathway in an end point and model-specific manner, and showed a topological bias for incoming interactions. Importantly, the level of biological similarity between different signatures for a given end point correlated positively with the accuracy of the signature predictions. These findings will aid the understanding, and application of predictive genomic signatures, and support their broader application in predictive medicine.
10aAlgorithms10aDatabases, Genetic10aEndpoint Determination10aGene Expression Profiling10aGenomics10aHumans10aNeural Networks, Computer10aOligonucleotide Array Sequence Analysis10aPhenotype10aPredictive Value of Tests10aProteins10aQuality Control1 aShi, W1 aBessarabova, M1 aDosymbekov, D1 aDezso, Z1 aNikolskaya, T1 aDudoladova, M1 aSerebryiskaya, T1 aBugrim, A1 aGuryanov, A1 aBrennan, R, J1 aShah, R1 aDopazo, J1 aChen, M1 aDeng, Y1 aShi, T1 aJurman, G1 aFurlanello, C1 aThomas, R, S1 aCorton, J, C1 aTong, W1 aShi, L1 aNikolsky, Y uhttps://www.clinbioinfosspa.es/content/functional-analysis-multiple-genomic-signatures-demonstrates-classification-algorithms01700nas a2200265 4500008004100000245004500041210004400086260000900130300001300139490000600152520096600158653000801124653001401132100002001146700001601166700002701182700002001209700002001229700002301249700001901272700001901291700002001310700002001330856008401350 2010 eng d00aInitial genomics of the human nucleolus.0 aInitial genomics of the human nucleolus c2010 ae10008890 v63 aWe report for the first time the genomics of a nuclear compartment of the eukaryotic cell. 454 sequencing and microarray analysis revealed the pattern of nucleolus-associated chromatin domains (NADs) in the linear human genome and identified different gene families and certain satellite repeats as the major building blocks of NADs, which constitute about 4% of the genome. Bioinformatic evaluation showed that NAD-localized genes take part in specific biological processes, like the response to other organisms, odor perception, and tissue development. 3D FISH and immunofluorescence experiments illustrated the spatial distribution of NAD-specific chromatin within interphase nuclei and its alteration upon transcriptional changes. Altogether, our findings describe the nature of DNA sequences associated with the human nucleolus and provide insights into the function of the nucleolus in genome organization and establishment of nuclear architecture.
10aNGS10anucleolus1 aNémeth, Attila1 aConesa, Ana1 aSantoyo-López, Javier1 aMedina, Ignacio1 aMontaner, David1 aPéterfia, Bálint1 aSolovei, Irina1 aCremer, Thomas1 aDopazo, Joaquin1 aLängst, Gernot uhttp://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.100088907842nas a2202545 4500008004100000245014500041210006900186260001300255300001100268490000700279520110300286100001601389700002201405700002201427700002101449700001701470700002301487700001801510700001801528700002601546700001901572700002501591700002201616700002301638700002301661700001801684700001901702700001701721700001201738700002201750700002301772700002301795700001401818700002401832700002001856700001701876700001601893700001701909700002001926700002201946700001701968700001701985700001502002700001602017700001502033700002402048700002102072700001802093700002702111700001802138700002002156700002002176700001902196700001802215700001602233700001702249700001502266700002002281700002102301700001802322700001402340700002402354700002002378700002202398700002002420700002702440700001102467700001402478700001302492700001802505700001702523700002602540700001302566700001302579700002302592700001902615700002202634700002202656700001802678700001902696700002102715700001502736700002102751700001602772700001602788700001702804700002702821700002302848700002102871700001702892700002702909700002002936700001702956700001502973700001402988700002203002700001703024700001903041700001703060700001703077700001503094700002203109700001603131700002703147700002003174700002403194700002003218700002603238700001703264700001503281700001603296700001403312700001703326700002603343700001603369700002203385700001703407700001503424700002103439700003003460700002103490700001903511700001603530700002603546700001203572700002303584700001403607700002303621700002103644700001803665700002003683700002403703700001503727700002403742700002103766700002003787700002103807700001903828700001703847700001103864700001703875700001803892700001303910700001703923700001303940700001403953700001703967700001303984700001903997700003204016700002004048700001904068700001904087700002404106700002004130700002104150700002404171700002104195700002404216700001804240700001904258700001704277700002004294700001704314700002104331700001804352700001704370700001204387700002504399700001904424700002404443700002604467700002504493700001504518700002004533700001704553700001904570700002304589700001604612700002104628700001904649700002004668700001704688700001604705700001504721700001804736700001704754700002204771700001804793700002004811700002504831700002304856700001804879700001504897700001704912700001404929700002204943700002104965700001904986700001605005700001905021700001505040700001205055700001405067700001505081700001705096700001405113700001505127700001505142700001705157700001605174700001605190700002605206856006405232 2010 eng d00aThe MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.0 aMicroArray Quality Control MAQCII study of common practices for c2010 Aug a827-380 v283 aGene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
1 aShi, Leming1 aCampbell, Gregory1 aJones, Wendell, D1 aCampagne, Fabien1 aWen, Zhining1 aWalker, Stephen, J1 aSu, Zhenqiang1 aChu, Tzu-Ming1 aGoodsaid, Federico, M1 aPusztai, Lajos1 aShaughnessy, John, D1 aOberthuer, André1 aThomas, Russell, S1 aPaules, Richard, S1 aFielden, Mark1 aBarlogie, Bart1 aChen, Weijie1 aDu, Pan1 aFischer, Matthias1 aFurlanello, Cesare1 aGallas, Brandon, D1 aGe, Xijin1 aMegherbi, Dalila, B1 aSymmans, Fraser1 aWang, May, D1 aZhang, John1 aBitter, Hans1 aBrors, Benedikt1 aBushel, Pierre, R1 aBylesjo, Max1 aChen, Minjun1 aCheng, Jie1 aCheng, Jing1 aChou, Jeff1 aDavison, Timothy, S1 aDelorenzi, Mauro1 aDeng, Youping1 aDevanarayan, Viswanath1 aDix, David, J1 aDopazo, Joaquin1 aDorff, Kevin, C1 aElloumi, Fathi1 aFan, Jianqing1 aFan, Shicai1 aFan, Xiaohui1 aFang, Hong1 aGonzaludo, Nina1 aHess, Kenneth, R1 aHong, Huixiao1 aHuan, Jun1 aIrizarry, Rafael, A1 aJudson, Richard1 aJuraeva, Dilafruz1 aLababidi, Samir1 aLambert, Christophe, G1 aLi, Li1 aLi, Yanen1 aLi, Zhen1 aLin, Simon, M1 aLiu, Guozhen1 aLobenhofer, Edward, K1 aLuo, Jun1 aLuo, Wen1 aMcCall, Matthew, N1 aNikolsky, Yuri1 aPennello, Gene, A1 aPerkins, Roger, G1 aPhilip, Reena1 aPopovici, Vlad1 aPrice, Nathan, D1 aQian, Feng1 aScherer, Andreas1 aShi, Tieliu1 aShi, Weiwei1 aSung, Jaeyun1 aThierry-Mieg, Danielle1 aThierry-Mieg, Jean1 aThodima, Venkata1 aTrygg, Johan1 aVishnuvajjala, Lakshmi1 aWang, Sue, Jane1 aWu, Jianping1 aWu, Yichao1 aXie, Qian1 aYousef, Waleed, A1 aZhang, Liang1 aZhang, Xuegong1 aZhong, Sheng1 aZhou, Yiming1 aZhu, Sheng1 aArasappan, Dhivya1 aBao, Wenjun1 aLucas, Anne, Bergstrom1 aBerthold, Frank1 aBrennan, Richard, J1 aBuness, Andreas1 aCatalano, Jennifer, G1 aChang, Chang1 aChen, Rong1 aCheng, Yiyu1 aCui, Jian1 aCzika, Wendy1 aDemichelis, Francesca1 aDeng, Xutao1 aDosymbekov, Damir1 aEils, Roland1 aFeng, Yang1 aFostel, Jennifer1 aFulmer-Smentek, Stephanie1 aFuscoe, James, C1 aGatto, Laurent1 aGe, Weigong1 aGoldstein, Darlene, R1 aGuo, Li1 aHalbert, Donald, N1 aHan, Jing1 aHarris, Stephen, C1 aHatzis, Christos1 aHerman, Damir1 aHuang, Jianping1 aJensen, Roderick, V1 aJiang, Rui1 aJohnson, Charles, D1 aJurman, Giuseppe1 aKahlert, Yvonne1 aKhuder, Sadik, A1 aKohl, Matthias1 aLi, Jianying1 aLi, Li1 aLi, Menglong1 aLi, Quan-Zhen1 aLi, Shao1 aLi, Zhiguang1 aLiu, Jie1 aLiu, Ying1 aLiu, Zhichao1 aMeng, Lu1 aMadera, Manuel1 aMartinez-Murillo, Francisco1 aMedina, Ignacio1 aMeehan, Joseph1 aMiclaus, Kelci1 aMoffitt, Richard, A1 aMontaner, David1 aMukherjee, Piali1 aMulligan, George, J1 aNeville, Padraic1 aNikolskaya, Tatiana1 aNing, Baitang1 aPage, Grier, P1 aParker, Joel1 aParry, Mitchell1 aPeng, Xuejun1 aPeterson, Ron, L1 aPhan, John, H1 aQuanz, Brian1 aRen, Yi1 aRiccadonna, Samantha1 aRoter, Alan, H1 aSamuelson, Frank, W1 aSchumacher, Martin, M1 aShambaugh, Joseph, D1 aShi, Qiang1 aShippy, Richard1 aSi, Shengzhu1 aSmalter, Aaron1 aSotiriou, Christos1 aSoukup, Mat1 aStaedtler, Frank1 aSteiner, Guido1 aStokes, Todd, H1 aSun, Qinglan1 aTan, Pei-Yi1 aTang, Rong1 aTezak, Zivana1 aThorn, Brett1 aTsyganova, Marina1 aTurpaz, Yaron1 aVega, Silvia, C1 aVisintainer, Roberto1 avon Frese, Juergen1 aWang, Charles1 aWang, Eric1 aWang, Junwei1 aWang, Wei1 aWestermann, Frank1 aWilley, James, C1 aWoods, Matthew1 aWu, Shujian1 aXiao, Nianqing1 aXu, Joshua1 aXu, Lei1 aYang, Lun1 aZeng, Xiao1 aZhang, Jialu1 aZhang, Li1 aZhang, Min1 aZhao, Chen1 aPuri, Raj, K1 aScherf, Uwe1 aTong, Weida1 aWolfinger, Russell, D uhttp://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html00608nas a2200169 4500008004100000245010100041210006900142300001300211490000600224100002500230700001900255700002700274700001900301700002000320700002000340856007800360 2010 eng d00aSelection upon Genome Architecture: Conservation of Functional Neighborhoods with Changing Genes0 aSelection upon Genome Architecture Conservation of Functional Ne ae10009530 v61 aAl-Shahrour, Fátima1 aMinguez, Pablo1 aMarqués-Bonet, Tomás1 aGazave, Elodie1 aNavarro, Arcadi1 aDopazo, Joaquin uhttp://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.100095301786nas a2200277 4500008004100000022001400041245009200055210006900147260001300216300001200229490000700241520089700248653001501145653003001160653001301190653001301203653001801216653004401234653001301278100002401291700002101315700002001336700002001356700001601376856011601392 2010 eng d a1362-496200aSerial Expression Analysis: a web tool for the analysis of serial gene expression data.0 aSerial Expression Analysis a web tool for the analysis of serial c2010 Jul aW239-450 v383 aSerial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es.
10aAlgorithms10aGene Expression Profiling10aInternet10aKinetics10aLinear Models10aOligonucleotide Array Sequence Analysis10aSoftware1 aNueda, Maria, José1 aCarbonell, José1 aMedina, Ignacio1 aDopazo, Joaquin1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/serial-expression-analysis-web-tool-analysis-serial-gene-expression-data02297nam a2200145 4500008004100000022002200041245007500063210007300138260003500211300000800246520173700254100001501991700001602006856012902022 2009 eng d a978-84-92910-06-900aEvolución y Adaptación.150 años después del Origen de las Especies0 aEvolución y Adaptación150 años después del Origen de las Especie aValencia. EspañabObrapropia. a5103 aEvolución y Adaptación: 150 años después del Origen de las Especies es un homenaje a la figura de Charles Darwin al cumplirse 200 años de su nacimiento y 150 años de la publicación que lo hiciese mundialmente famoso. En esta edición 101 autores convocados por la Sociedad Española de Biología Evolutiva han resumido su trabajo de investigación en 51 artículos. Estos se han agrupado en temáticas que abarcan los problemas de la evolución molecular, el cambio morfológico, la evolución del desarrollo, el origen de las especies y su interacción, la diversidad biológica, la evolución del comportamiento, la paleobiología, la evolución experimental, la evolución cultural y la evolución en la filosofía y la docencia. Muchos de estos trabajos representan décadas de constante investigación en el laboratorio y en el campo. El común denominador de los artículos que contiene este libro es el esfuerzo por transmitir a un público no necesariamente experto la actualidad de las investigaciones que en el campo de la adaptación y la evolución se desarrolla en diferentes laboratorios. Esta obra resume por lo tanto, gran parte de las investigaciones que en materia de evolución biológica se realiza en España. Esta edición deja constancia entonces del "Hecho de la Evolución", y de la actualidad de teoría evolutiva moderna como cuerpo explicativo del mundo biológico 150 años después del origen de las especies.
1 aDopazo, H.1 aNavarro, A. uhttps://www.clinbioinfosspa.es/content/evoluci%C3%B3n-y-adaptaci%C3%B3n150-a%C3%B1os-despu%C3%A9s-del-origen-de-las-especies03290nas a2200205 4500008004100000245014400041210006900185300001100254490000800265520221900273653002002492653002302512653017902535653018702714100001802901700002402919700001502943700002002958856010602978 2009 eng d00aExploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli0 aExploring the antimicrobial action of a carbon monoxidereleasing a813-240 v1553 aWe recently reported that carbon monoxide (CO) has bactericidal activity. To understand its mode of action we analysed the gene expression changes occurring when Escherichia coli, grown aerobically and anaerobically, is treated with the CO-releasing molecule CORM-2 (tricarbonyldichlororuthenium(II) dimer). Microarray analysis shows that the E. coli CORM-2 response is multifaceted, with a high number of differentially regulated genes spread through several functional categories, namely genes involved in inorganic ion transport and metabolism, regulators, and genes implicated in post-translational modification, such as chaperones. CORM-2 has a higher impact in E. coli cells grown anaerobically, as judged by the repression of genes belonging to eight functional classes which are not seen in the response of aerobically CORM-2-treated cells. The biological relevance of the variations caused by CORM-2 was substantiated by studying the CORM-2 sensitivity of selected E. coli mutants. The results show that the deletion of redox-sensing regulators SoxS and OxyR increased the sensitivity to CORM-2 and suggest that while SoxS plays an important role in protection against CORM-2 under both growth conditions, OxyR seems to participate only in the aerobic CORM-2 response. Under anaerobic conditions, we found that the heat-shock proteins IbpA and IbpB contribute to CORM-2 defence since the deletion of these genes increases the sensitivity of the strain. The induction of several met genes and the hypersensitivity to CORM-2 of the DeltametR, DeltametI and DeltametN mutant strains suggest that CO has effects on the methionine metabolism of E. coli. CORM-2 also affects the transcription of several E. coli biofilm-related genes and increases biofilm formation in E. coli. In particular, the absence of tqsA or bhsA increases the resistance of E. coli to CORM-2, and deletion of tsqA leads to a strain that has lost its capacity to form biofilm upon treatment with CORM-2. In spite of the relatively stable nature of the CO molecule, our results show that CO is able to trigger a significant alteration in the transcriptome of E. coli which necessarily has effects in several key metabolic pathways.
10aBacterial Genes10aBacterial/genetics10aBiofilms Carbon Monoxide/*metabolism Escherichia coli/*genetics/metabolism Escherichia coli Proteins/genetics/metabolism *Gene Expression Profiling Gene Expression Regulation10aRegulator Genetic Complementation Test Methionine/metabolism Microbial Viability Mutation Oligonucleotide Array Sequence Analysis Organometallic Compounds/*pharmacology Phenotype RNA1 aNobre, L., S.1 aAl-Shahrour, Fatima1 aDopazo, J.1 aSaraiva, L., M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1924675203505nas a2200373 4500008004100000022001400041245014500055210006900200260001300269300001200282490000800294520221900302653001302521653002002534653002102554653003002575653003002605653004202635653002102677653002102698653003302719653001502752653002402767653001302791653004402804653002902848653001402877653001902891100002102910700002502931700002002956700002302976856013202999 2009 eng d a1350-087200aExploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli.0 aExploring the antimicrobial action of a carbon monoxidereleasing c2009 Mar a813-8240 v1553 aWe recently reported that carbon monoxide (CO) has bactericidal activity. To understand its mode of action we analysed the gene expression changes occurring when Escherichia coli, grown aerobically and anaerobically, is treated with the CO-releasing molecule CORM-2 (tricarbonyldichlororuthenium(II) dimer). Microarray analysis shows that the E. coli CORM-2 response is multifaceted, with a high number of differentially regulated genes spread through several functional categories, namely genes involved in inorganic ion transport and metabolism, regulators, and genes implicated in post-translational modification, such as chaperones. CORM-2 has a higher impact in E. coli cells grown anaerobically, as judged by the repression of genes belonging to eight functional classes which are not seen in the response of aerobically CORM-2-treated cells. The biological relevance of the variations caused by CORM-2 was substantiated by studying the CORM-2 sensitivity of selected E. coli mutants. The results show that the deletion of redox-sensing regulators SoxS and OxyR increased the sensitivity to CORM-2 and suggest that while SoxS plays an important role in protection against CORM-2 under both growth conditions, OxyR seems to participate only in the aerobic CORM-2 response. Under anaerobic conditions, we found that the heat-shock proteins IbpA and IbpB contribute to CORM-2 defence since the deletion of these genes increases the sensitivity of the strain. The induction of several met genes and the hypersensitivity to CORM-2 of the DeltametR, DeltametI and DeltametN mutant strains suggest that CO has effects on the methionine metabolism of E. coli. CORM-2 also affects the transcription of several E. coli biofilm-related genes and increases biofilm formation in E. coli. In particular, the absence of tqsA or bhsA increases the resistance of E. coli to CORM-2, and deletion of tsqA leads to a strain that has lost its capacity to form biofilm upon treatment with CORM-2. In spite of the relatively stable nature of the CO molecule, our results show that CO is able to trigger a significant alteration in the transcriptome of E. coli which necessarily has effects in several key metabolic pathways.
10aBiofilms10aCarbon Monoxide10aEscherichia coli10aEscherichia coli Proteins10aGene Expression Profiling10aGene Expression Regulation, Bacterial10aGenes, Bacterial10aGenes, Regulator10aGenetic Complementation Test10aMethionine10aMicrobial Viability10amutation10aOligonucleotide Array Sequence Analysis10aOrganometallic Compounds10aPhenotype10aRNA, Bacterial1 aNobre, Lígia, S1 aAl-Shahrour, Fátima1 aDopazo, Joaquin1 aSaraiva, Lígia, M uhttps://www.clinbioinfosspa.es/content/exploring-antimicrobial-action-carbon-monoxide-releasing-compound-through-whole-genome-002718nas a2200265 4500008004100000022001400041245005800055210005700113260001600170300000700186490001500193520188200208653002402090653003002114653004402144653001702188100002402205700002502229700002002254700002902274700002002303700002002323700001602343856009302359 2009 eng d a1471-210500aFunctional assessment of time course microarray data.0 aFunctional assessment of time course microarray data c2009 Jun 16 aS90 v10 Suppl 63 aMOTIVATION: Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated.
METHODS: We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies.
RESULTS: Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study.
10aComputer Simulation10aGene Expression Profiling10aOligonucleotide Array Sequence Analysis10aTime Factors1 aNueda, Maria, José1 aSebastián, Patricia1 aTarazona, Sonia1 aGarcia-Garcia, Francisco1 aDopazo, Joaquin1 aFerrer, Alberto1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/functional-assessment-time-course-microarray-data01750nas a2200181 4500008004100000022002200041245009600063210007100159260002600230300001000256520107600266100002101342700001501363700001501378700001501393700001601408856014401424 2009 eng d a978-84-92910-06-900aGenómica Comparativa y Selección Natural. Aplicaciones en el Genoma Humano. Capítulo 1.60 aGenómica Comparativa y Selección Natural Aplicaciones en el Geno aValenciabObrapropia. a51-593 aLa búsqueda de los eventos adaptativos a nivel molecular que ha diferenciado el genoma humano del de nuestro pariente vivo más cercano, el chimpancé, ha sido una de las áreas de mayor investigación en genómica comparativa. Paralelamente, la predicción funcional de variantes genéticas en nuestra especie ha sido un área de intenso desarrollo en bioinformática. En este trabajo discutiremos resultados previos y otros más recientes que dan cuenta de estos desarrollos. Veremos que en todos los casos la estimación de las presiones selectivas a nivel de los genes individuales o de los residuos de las proteínas son el denominador común para discutir ambos aspectos. Finalmente mostraremos cómo el análisis de estas presiones selectivas por grupos funcionales de genes resulta una alternativa viable y con suficiente poder estadístico para el análisis de la adaptación y de las restricciones evolutivas a nivel genómico.
1 aSerra, François1 aArbiza, L.1 aDopazo, H.1 aDopazo, H.1 aNavarro, A. uhttps://www.clinbioinfosspa.es/content/gen%C3%B3mica-comparativa-y-selecci%C3%B3n-natural-aplicaciones-en-el-genoma-humano-cap%C3%ADtulo-1600912nas a2200265 4500008004100000245010100041210006900142260000700211100002100218700002100239700002000260700002200280700001800302700002200320700002200342700002000364700002000384700001400404700001900418700001900437700001800456700002400474700001800498856013000516 2009 eng d00aPeripheral blood cells transcriptome to study new biomarkers for myocardial infarction follow up0 aPeripheral blood cells transcriptome to study new biomarkers for c061 aSilbiger, Vivian1 aLuchessi, André1 aHirata, Rosario1 aCarracedo, Ángel1 aBrión, Maria1 aNeto, Lidio, Lima1 aPastorelli, C, P.1 aDopazo, Joaquin1 aMontaner, David1 aGarcia, F1 aSampaio, M, P.1 aPereira, M, P.1 aSantos, E, S.1 aArmaganijan, Dikran1 aHirata, Mario uhttps://www.clinbioinfosspa.es/content/peripheral-blood-cells-transcriptome-study-new-biomarkers-myocardial-infarction-follow00491nas a2200157 4500008004100000022002900041245004900070210004900119260003900168300001200207100001600219700001500235700001600250700001800266856004900284 2009 eng d a1605663980, 97816056639800aProtein Interactions for Functional Genomics0 aProtein Interactions for Functional Genomics aHershey, USAbIdea Group Inc (IGI) a223-2381 aMinguez, P.1 aDopazo, J.1 aLi, Xiao-Li1 aNg, See-Kiong uhttp://books.google.es/books?id=pNyCy5GsqtkC02722nas a2200385 4500008004100000022001400041245008300055210006900138260001300207300001200220490000700232520153300239653001201772653002601784653002201810653002301832653002801855653001001883653001301893653002701906653003101933653001301964653002701977100001802004700003302022700001802055700002102073700002902094700002402123700002302147700001802170700002002188700001602208856011202224 2008 eng d a1362-496200aHigh-throughput functional annotation and data mining with the Blast2GO suite.0 aHighthroughput functional annotation and data mining with the Bl c2008 Jun a3420-350 v363 aFunctional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.
10aAnimals10aComputational Biology10aComputer Graphics10aDatabases, Genetic10aExpressed Sequence Tags10aGenes10aGenomics10aSequence Analysis, DNA10aSequence Analysis, Protein10aSoftware10aVocabulary, Controlled1 aGötz, Stefan1 aGarcía-Gómez, Juan, Miguel1 aTerol, Javier1 aWilliams, Tim, D1 aNagaraj, Shivashankar, H1 aNueda, Maria, José1 aRobles, Montserrat1 aTalon, Manuel1 aDopazo, Joaquin1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/high-throughput-functional-annotation-and-data-mining-blast2go-suite03690nas a2200937 4500008004100000022001400041245007800055210006900133260001300202300001100215490000600226520100100232653002601233653003201259653002301291653003801314653001301352653002601365653002401391110002301415700002301438700001901461700001801480700002501498700001801523700001901541700002101560700001601581700001601597700002901613700001701642700001901659700002201678700002501700700003101725700002501756700001601781700001901797700001601816700002001832700002601852700002501878700001901903700001901922700001801941700001901959700001401978700001901992700002002011700002002031700001702051700002002068700002102088700002402109700002102133700002102154700002102175700002202196700001802218700002002236700002302256700002402279700002502303700002002328700002002348700002002368700002002388700002202408700002002430700002302450700001702473700001602490700002702506700001802533700001802551700001902569700002002588700001802608700002302626856010302649 2008 eng d a1477-405400aInteroperability with Moby 1.0--it's better than sharing your toothbrush!0 aInteroperability with Moby 10its better than sharing your toothb c2008 May a220-310 v93 aThe BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.
10aComputational Biology10aDatabase Management Systems10aDatabases, Factual10aInformation Storage and Retrieval10aInternet10aProgramming Languages10aSystems Integration1 aBioMoby Consortium1 aWilkinson, Mark, D1 aSenger, Martin1 aKawas, Edward1 aBruskiewich, Richard1 aGouzy, Jerome1 aNoirot, Celine1 aBardou, Philippe1 aNg, Ambrose1 aHaase, Dirk1 aSaiz, Enrique, de Andres1 aWang, Dennis1 aGibbons, Frank1 aGordon, Paul, M K1 aSensen, Christoph, W1 aCarrasco, Jose, Manuel Rod1 aFernández, José, M1 aShen, Lixin1 aLinks, Matthew1 aNg, Michael1 aOpushneva, Nina1 aNeerincx, Pieter, B T1 aLeunissen, Jack, A M1 aErnst, Rebecca1 aTwigger, Simon1 aUsadel, Bjorn1 aGood, Benjamin1 aWong, Yan1 aStein, Lincoln1 aCrosby, William1 aKarlsson, Johan1 aRoyo, Romina1 aPárraga, Iván1 aRamírez, Sergio1 aGelpi, Josep, Lluis1 aTrelles, Oswaldo1 aPisano, David, G1 aJimenez, Natalia1 aKerhornou, Arnaud1 aRosset, Roman1 aZamacola, Leire1 aTárraga, Joaquín1 aHuerta-Cepas, Jaime1 aCarazo, Jose, María1 aDopazo, Joaquin1 aGuigó, Roderic1 aNavarro, Arcadi1 aOrozco, Modesto1 aValencia, Alfonso1 aClaros, Gonzalo1 aPérez, Antonio, J1 aAldana, Jose1 aRojano, Mar1 aCruz, Raul, Fernandez-1 aNavas, Ismael1 aSchiltz, Gary1 aFarmer, Andrew1 aGessler, Damian1 aSchoof, Heiko1 aGroscurth, Andreas uhttps://www.clinbioinfosspa.es/content/interoperability-moby-10-its-better-sharing-your-toothbrush03310nas a2200841 4500008004100000245008100041210007100122300001100193490000600204520100100210653007501211653010801286100002201394700001501416700001401431700002001445700001401465700001501479700001501494700001101509700001401520700001401534700001301548700001601561700001901577700001901596700002101615700002201636700001301658700001401671700001101685700001801696700002101714700002201735700001401757700001601771700001501787700001301802700001301815700001401828700001501842700001701857700001301874700001601887700001601903700001801919700001601937700001901953700001601972700001801988700001502006700001702021700001602038700002102054700001902075700001502094700001402109700001602123700001502139700001702154700001902171700001802190700001502208700001902223700002602242700001402268700001602282700001502298700001602313700001502329700001802344856010602362 2008 eng d00aInteroperability with Moby 1.0–it’s better than sharing your toothbrush!0 aInteroperability with Moby 10–it s better than sharing your toot a220-310 v93 aThe BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.
10aComputational Biology/*methods *Database Management Systems *Databases10aFactual Information Storage and Retrieval/*methods *Internet *Programming Languages Systems Integration1 aWilkinson, M., D.1 aSenger, M.1 aKawas, E.1 aBruskiewich, R.1 aGouzy, J.1 aNoirot, C.1 aBardou, P.1 aNg, A.1 aHaase, D.1 aEde, Saiz1 aWang, D.1 aGibbons, F.1 aGordon, P., M.1 aSensen, C., W.1 aCarrasco, J., M.1 aFernandez, J., M.1 aShen, L.1 aLinks, M.1 aNg, M.1 aOpushneva, N.1 aNeerincx, P., B.1 aLeunissen, J., A.1 aErnst, R.1 aTwigger, S.1 aUsadel, B.1 aGood, B.1 aWong, Y.1 aStein, L.1 aCrosby, W.1 aKarlsson, J.1 aRoyo, R.1 aParraga, I.1 aRamirez, S.1 aGelpi, J., L.1 aTrelles, O.1 aPisano, D., G.1 aJimenez, N.1 aKerhornou, A.1 aRosset, R.1 aZamacola, L.1 aTarraga, J.1 aHuerta-Cepas, J.1 aCarazo, J., M.1 aDopazo, J.1 aGuigo, R.1 aNavarro, A.1 aOrozco, M.1 aValencia, A.1 aClaros, M., G.1 aPerez, A., J.1 aAldana, J.1 aRojano, M., M.1 aCruz, Fernandez-Santa1 aNavas, I.1 aSchiltz, G.1 aFarmer, A.1 aGessler, D.1 aSchoof, H.1 aGroscurth, A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1823880402714nas a2200253 4500008004100000245009200041210006900133300001300202490000700215520168800222653010801910653001202018653001902030653005802049653012102107100001802228700001502246700002302261700002202284700001902306700001402325700001502339856010602354 2007 eng d00aDiscovering gene expression patterns in time course microarray experiments by ANOVA-SCA0 aDiscovering gene expression patterns in time course microarray e a1792-8000 v233 aMOTIVATION: Designed microarray experiments are used to investigate the effects that controlled experimental factors have on gene expression and learn about the transcriptional responses associated with external variables. In these datasets, signals of interest coexist with varying sources of unwanted noise in a framework of (co)relation among the measured variables and with the different levels of the studied factors. Discovering experimentally relevant transcriptional changes require methodologies that take all these elements into account. RESULTS: In this work, we develop the application of the Analysis of variance-simultaneous component analysis (ANOVA-SCA) Smilde et al. Bioinformatics, (2005) to the analysis of multiple series time course microarray data as an example of multifactorial gene expression profiling experiments. We denoted this implementation as ASCA-genes. We show how the combination of ANOVA-modeling and a dimension reduction technique is effective in extracting targeted signals from data by-passing structural noise. The methodology is valuable for identifying main and secondary responses associated with the experimental factors and spotting relevant experimental conditions. We additionally propose a novel approach for gene selection in the context of the relation of individual transcriptional patterns to global gene expression signals. We demonstrate the methodology on both real and synthetic datasets. AVAILABILITY: ASCA-genes has been implemented in the statistical language R and is available at http://www.ivia.es/centrodegenomica/bioinformatics.htm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.10aAlgorithms *Analysis of Variance Computational Biology/*methods Computer Simulation Data Interpretation10aGenetic10aGenetic Models10aStatistical Gene Expression Profiling/*methods Models10aStatistical Oligonucleotide Array Sequence Analysis/*methods Principal Component Analysis Time Factors Transcription1 aNueda, M., J.1 aConesa, A.1 aWesterhuis, J., A.1 aHoefsloot, H., C.1 aSmilde, A., K.1 aTalon, M.1 aFerrer, A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1751925002830nas a2200277 4500008004100000245011000041210006900151300001100220490000700231520162300238653016301861653002002024653018602044653004602230100001802276700001402294700002302308700001802331700001402349700001702363700001502380700001902395700001602414700001602430856010602446 2006 eng d00aERCC4 associated with breast cancer risk: a two-stage case-control study using high-throughput genotyping0 aERCC4 associated with breast cancer risk a twostage casecontrol a9420-70 v663 aThe failure of linkage studies to identify further high-penetrance susceptibility genes for breast cancer points to a polygenic model, with more common variants having modest effects on risk, as the most likely candidate. We have carried out a two-stage case-control study in two European populations to identify low-penetrance genes for breast cancer using high-throughput genotyping. Single-nucleotide polymorphisms (SNPs) were selected across preselected cancer-related genes, choosing tagSNPs and functional variants where possible. In stage 1, genotype frequencies for 640 SNPs in 111 genes were compared between 864 breast cancer cases and 845 controls from the Spanish population. In stage 2, candidate SNPs identified in stage 1 (nominal P < 0.01) were tested in a Finnish series of 884 cases and 1,104 controls. Of the 10 candidate SNPs in seven genes identified in stage 1, one (rs744154) on intron 1 of ERCC4, a gene belonging to the nucleotide excision repair pathway, was associated with recessive protection from breast cancer after adjustment for multiple testing in stage 2 (odds ratio, 0.57; Bonferroni-adjusted P = 0.04). After considering potential functional SNPs in the region of high linkage disequilibrium that extends across the entire gene and upstream into the promoter region, we concluded that rs744154 itself could be causal. Although intronic, it is located on the first intron, in a region that is highly conserved across species, and could therefore be functionally important. This study suggests that common intronic variation in ERCC4 is associated with protection from breast cancer.10a80 and over Breast Neoplasms/epidemiology/*genetics/pathology Case-Control Studies DNA-Binding Proteins/genetics/*physiology Female Finland/epidemiology Genes10aAdult Aged Aged10aRecessive Genetic Predisposition to Disease Genotype Humans Introns/genetics Linkage Disequilibrium Middle Aged Neoplasm Proteins/genetics/*physiology Neoplasm Staging *Polymorphism10aSingle Nucleotide Risk Spain/epidemiology1 aMilne, R., L.1 aRibas, G.1 aGonzalez-Neira, A.1 aFagerholm, R.1 aSalas, A.1 aGonzalez, E.1 aDopazo, J.1 aNevanlinna, H.1 aRobledo, M.1 aBenitez, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1701859601934nas a2200193 4500008004100000245012000041210006900161300001300230490000700243520110800250653010701358653001901465653008801484100001501572700001801587700001501605700001401620856010601634 2006 eng d00amaSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments0 amaSigPro a method to identify significantly differential express a1096-1020 v223 aMOTIVATION: Multi-series time-course microarray experiments are useful approaches for exploring biological processes. In this type of experiments, the researcher is frequently interested in studying gene expression changes along time and in evaluating trend differences between the various experimental groups. The large amount of data, multiplicity of experimental conditions and the dynamic nature of the experiments poses great challenges to data analysis. RESULTS: In this work, we propose a statistical procedure to identify genes that show different gene expression profiles across analytical groups in time-course experiments. The method is a two-regression step approach where the experimental groups are identified by dummy variables. The procedure first adjusts a global regression model with all the defined variables to identify differentially expressed genes, and in second a variable selection strategy is applied to study differences between groups and to find statistically significant different profiles. The methodology is illustrated on both a real and a simulated microarray dataset.10a*Algorithms Computer Simulation Gene Expression/*physiology Gene Expression Profiling/*methods *Models10aGenetic Models10aStatistical Oligonucleotide Array Sequence Analysis/*methods *Software Time Factors1 aConesa, A.1 aNueda, M., J.1 aFerrer, A.1 aTalon, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1648133302167nas a2200301 4500008004100000245008600041210006900127300001100196490000700207520100200214653012701216653002601343653013701369653003901506653001801545100002001563700001901583700001901602700001901621700001401640700002401654700001701678700001801695700001301713700001901726700001401745856010601759 2005 eng d00aThe C-type lectin fold as an evolutionary solution for massive sequence variation0 aCtype lectin fold as an evolutionary solution for massive sequen a886-920 v123 aOnly few instances are known of protein folds that tolerate massive sequence variation for the sake of binding diversity. The most extensively characterized is the immunoglobulin fold. We now add to this the C-type lectin (CLec) fold, as found in the major tropism determinant (Mtd), a retroelement-encoded receptor-binding protein of Bordetella bacteriophage. Variation in Mtd, with its approximately 10(13) possible sequences, enables phage adaptation to Bordetella spp. Mtd is an intertwined, pyramid-shaped trimer, with variable residues organized by its CLec fold into discrete receptor-binding sites. The CLec fold provides a highly static scaffold for combinatorial display of variable residues, probably reflecting a different evolutionary solution for balancing diversity against stability from that in the immunoglobulin fold. Mtd variants are biased toward the receptor pertactin, and there is evidence that the CLec fold is used broadly for sequence variation by related retroelements.10aAmino Acid Sequence Bacterial Outer Membrane Proteins/*chemistry Bacteriophages/*metabolism Bordetella/*virology Evolution10aBordetella/*chemistry10aC-Type/*chemistry Molecular Sequence Data Protein Conformation Protein Folding Viral Proteins/*chemistry/*genetics Virulence Factors10aMolecular Genetic Variation Genome10aViral Lectins1 aMcMahon, S., A.1 aMiller, J., L.1 aLawton, J., A.1 aKerkow, D., E.1 aHodes, A.1 aMarti-Renom, M., A.1 aDoulatov, S.1 aNarayanan, E.1 aSali, A.1 aMiller, J., F.1 aGhosh, P. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1617032403705nas a2200805 4500008004100000245010800041210006900149300001100218490000700229520133100236653002501567653010901592653000801701653010501709653007501814100001601889700001401905700001501919700001701934700001501951700001501966700001301981700001501994700001602009700002002025700001502045700002102060700001502081700001802096700001502114700002902129700001502158700001702173700001502190700002802205700001502233700001602248700001402264700002602278700001602304700001502320700002102335700001602356700001902372700002002391700001702411700002702428700001702455700001502472700001602487700001502503700002502518700002002543700001302563700001602576700002202592700001302614700001602627700001402643700001402657700001402671700001402685700001502699700001502714700001602729700001402745700001702759700001702776856010602793 2005 eng d00aDevelopment of a citrus genome-wide EST collection and cDNA microarray as resources for genomic studies0 aDevelopment of a citrus genomewide EST collection and cDNA micro a375-910 v573 aA functional genomics project has been initiated to approach the molecular characterization of the main biological and agronomical traits of citrus. As a key part of this project, a citrus EST collection has been generated from 25 cDNA libraries covering different tissues, developmental stages and stress conditions. The collection includes a total of 22,635 high-quality ESTs, grouped in 11,836 putative unigenes, which represent at least one third of the estimated number of genes in the citrus genome. Functional annotation of unigenes which have Arabidopsis orthologues (68% of all unigenes) revealed gene representation in every major functional category, suggesting that a genome-wide EST collection was obtained. A Citrus clementina Hort. ex Tan. cv. Clemenules genomic library, that will contribute to further characterization of relevant genes, has also been constructed. To initiate the analysis of citrus transcriptome, we have developed a cDNA microarray containing 12,672 probes corresponding to 6875 putative unigenes of the collection. Technical characterization of the microarray showed high intra- and inter-array reproducibility, as well as a good range of sensitivity. We have also validated gene expression data achieved with this microarray through an independent technique such as RNA gel blot analysis.10aCitrus/*genetics DNA10aComplementary/chemistry/genetics *Expressed Sequence Tags Gene Expression Profiling Gene Library *Genome10aDNA10aPlant Genomics/*methods Molecular Sequence Data Oligonucleotide Array Sequence Analysis/*methods RNA10aPlant/genetics/metabolism Reproducibility of Results Sequence Analysis1 aForment, J.1 aGadea, J.1 aHuerta, L.1 aAbizanda, L.1 aAgusti, J.1 aAlamar, S.1 aAlos, E.1 aAndres, F.1 aArribas, R.1 aBeltran, J., P.1 aBerbel, A.1 aBlazquez, M., A.1 aBrumos, J.1 aCanas, L., A.1 aCercos, M.1 aColmenero-Flores, J., M.1 aConesa, A.1 aEstables, B.1 aGandia, M.1 aGarcia-Martinez, J., L.1 aGimeno, J.1 aGisbert, A.1 aGomez, G.1 aGonzalez-Candelas, L.1 aGranell, A.1 aGuerri, J.1 aLafuente, M., T.1 aMadueno, F.1 aMarcos, J., F.1 aMarques, M., C.1 aMartinez, F.1 aMartinez-Godoy, M., A.1 aMiralles, S.1 aMoreno, P.1 aNavarro, L.1 aPallas, V.1 aPerez-Amador, M., A.1 aPerez-Valle, J.1 aPons, C.1 aRodrigo, I.1 aRodriguez, P., L.1 aRoyo, C.1 aSerrano, R.1 aSoler, G.1 aTadeo, F.1 aTalon, M.1 aTerol, J.1 aTrenor, M.1 aVaello, L.1 aVicente, O.1 aVidal, Ch1 aZacarias, L.1 aConejero, V. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1583012802532nas a2200229 4500008004100000245015400041210006900195300001000264490000700274520149500281653013001776653009301906653007401999100001802073700001902091700002002110700001702130700001802147700001502165700001602180856010602196 2001 eng d00aIdentification of optimal regions for phylogenetic studies on VP1 gene of foot-and-mouth disease virus: analysis of types A and O Argentinean viruses0 aIdentification of optimal regions for phylogenetic studies on VP a31-450 v323 aAn analysis of the informative content of sequence stretches on the foot-and-mouth disease virus (FMDV) VPI gene was applied to two important viral serotypes: A and O. Several sequence regions were identified to allow the reconstruction of phylogenetic trees equivalent to those derived from the whole VPI gene. The optimal informative regions for sequence windows of 150 to 250 nt were predicted between positions 250 and 550 of the gene. The sequences spanning the 250 nt of the 3’ end (positions 400 to 650), extensively used for FMDV phylogenetic analyses, showed a lower informative content. In spite of this, the use of sequences from this region allowed the derivation of phylogenetic trees for type A and type O FMDVs which showed topologies similar to those previously reported for the whole VP1 gene. When the sequences determined for viruses isolated in Argentina, between 1990 and 1993, were included in these analyses, the results obtained revealed features of the circulation of type A and type O viruses in the field, in the months that preceded the eradication of the disease in this country. Type A viruses were closely related to an Argentinean vaccine strain, and defined an independent cluster within this serotype. Among the type O viruses analysed, two groups were distinguished; one was closely related to the South American vaccine strains, while the other was grouped with viruses of the O3 subtype. In addition, a detailed phylogeny for type A FMDV is presented.10aAmino Acid Sequence Animals Aphthovirus/classification/*genetics Base Sequence Capsid/chemistry/*genetics Capsid Proteins DNA10aComplementary/chemistry Molecular Sequence Data *Phylogeny Polymerase Chain Reaction RNA10aViral/chemistry/genetics Serotyping Viral Proteins/analysis/*genetics1 aNunez, J., I.1 aMartin, M., J.1 aPiccone, M., E.1 aCarrillo, E.1 aPalma, E., L.1 aDopazo, J.1 aSobrino, F. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11254175