05146nas a2200745 4500008004100000022001400041245013000055210006900185260001200254300001200266490000800278520304400286653001503330653001003345653001103355653001203366653002503378653002003403653001003423653002103433653002603454653003803480653002503518653003403543653001103577653001603588653001303604653003103617653002303648653001103671653001103682653002003693653000903713653001603722653001303738653002503751653003103776653002503807653001203832653000903844653002603853653001603879100002203895700001303917700001303930700002303943700001503966700001903981700002404000700001604024700001604040700002904056700001404085700001504099700002704114700002404141700001404165700001204179700001604191700001504207700001504222700001404237700001504251856013404266 2019 eng d a1365-213300aFibroblast activation and abnormal extracellular matrix remodelling as common hallmarks in three cancer-prone genodermatoses.0 aFibroblast activation and abnormal extracellular matrix remodell c2019 09 a512-5220 v1813 a
BACKGROUND: Recessive dystrophic epidermolysis bullosa (RDEB), Kindler syndrome (KS) and xeroderma pigmentosum complementation group C (XPC) are three cancer-prone genodermatoses whose causal genetic mutations cannot fully explain, on their own, the array of associated phenotypic manifestations. Recent evidence highlights the role of the stromal microenvironment in the pathology of these disorders.
OBJECTIVES: To investigate, by means of comparative gene expression analysis, the role played by dermal fibroblasts in the pathogenesis of RDEB, KS and XPC.
METHODS: We conducted RNA-Seq analysis, which included a thorough examination of the differentially expressed genes, a functional enrichment analysis and a description of affected signalling circuits. Transcriptomic data were validated at the protein level in cell cultures, serum samples and skin biopsies.
RESULTS: Interdisease comparisons against control fibroblasts revealed a unifying signature of 186 differentially expressed genes and four signalling pathways in the three genodermatoses. Remarkably, some of the uncovered expression changes suggest a synthetic fibroblast phenotype characterized by the aberrant expression of extracellular matrix (ECM) proteins. Western blot and immunofluorescence in situ analyses validated the RNA-Seq data. In addition, enzyme-linked immunosorbent assay revealed increased circulating levels of periostin in patients with RDEB.
CONCLUSIONS: Our results suggest that the different causal genetic defects converge into common changes in gene expression, possibly due to injury-sensitive events. These, in turn, trigger a cascade of reactions involving abnormal ECM deposition and underexpression of antioxidant enzymes. The elucidated expression signature provides new potential biomarkers and common therapeutic targets in RDEB, XPC and KS. What's already known about this topic? Recessive dystrophic epidermolysis bullosa (RDEB), Kindler syndrome (KS) and xeroderma pigmentosum complementation group C (XPC) are three genodermatoses with high predisposition to cancer development. Although their causal genetic mutations mainly affect epithelia, the dermal microenvironment likely contributes to the physiopathology of these disorders. What does this study add? We disclose a large overlapping transcription profile between XPC, KS and RDEB fibroblasts that points towards an activated phenotype with high matrix-synthetic capacity. This common signature seems to be independent of the primary causal deficiency, but reflects an underlying derangement of the extracellular matrix via transforming growth factor-β signalling activation and oxidative state imbalance. What is the translational message? This study broadens the current knowledge about the pathology of these diseases and highlights new targets and biomarkers for effective therapeutic intervention. It is suggested that high levels of circulating periostin could represent a potential biomarker in RDEB.
10aAdolescent10aAdult10aBiopsy10aBlister10aCase-Control Studies10aCells, Cultured10aChild10aChild, Preschool10aEpidermolysis Bullosa10aEpidermolysis Bullosa Dystrophica10aExtracellular Matrix10aExtracellular Matrix Proteins10aFemale10aFibroblasts10aFibrosis10aGene Expression Regulation10aHealthy Volunteers10aHumans10aInfant10aInfant, Newborn10aMale10aMiddle Aged10amutation10aPeriodontal Diseases10aPhotosensitivity Disorders10aPrimary Cell Culture10aRNA-seq10aSkin10aXeroderma Pigmentosum10aYoung Adult1 aChacón-Solano, E1 aLeón, C1 aDíaz, F1 aGarcía-García, F1 aGarcía, M1 aEscámez, M, J1 aGuerrero-Aspizua, S1 aConti, C, J1 aMencía, Á1 aMartínez-Santamaría, L1 aLlames, S1 aPévida, M1 aCarbonell-Caballero, J1 aPuig-Butillé, J, A1 aMaseda, R1 aPuig, S1 ade Lucas, R1 aBaselga, E1 aLarcher, F1 aDopazo, J1 aDel Rio, M uhttps://www.clinbioinfosspa.es/content/fibroblast-activation-and-abnormal-extracellular-matrix-remodelling-common-hallmarks-three02787nas a2200349 4500008004100000022001400041245008700055210006900142260001200211490000600223520171300229653001201942653003001954653001101984653002201995653001302017653001102030653000902041653001002050653002702060100003302087700002902120700002002149700003002169700002102199700001902220700002002239700001902259700001902278700002202297856011802319 2018 eng d a2057-585800aThe first complete genomic structure of Butyrivibrio fibrisolvens and its chromid.0 afirst complete genomic structure of Butyrivibrio fibrisolvens an c2018 100 v43 aButyrivibrio fibrisolvens forms part of the gastrointestinal microbiome of ruminants and other mammals, including humans. Indeed, it is one of the most common bacteria found in the rumen and plays an important role in ruminal fermentation of polysaccharides, yet, to date, there is no closed reference genome published for this species in any ruminant animal. We successfully assembled the nearly complete genome sequence of B. fibrisolvens strain INBov1 isolated from cow rumen using Illumina paired-end reads, 454 Roche single-end and mate pair sequencing technology. Additionally, we constructed an optical restriction map of this strain to aid in scaffold ordering and positioning, and completed the first genomic structure of this species. Moreover, we identified and assembled the first chromid of this species (pINBov266). The INBov1 genome encodes a large set of genes involved in the cellulolytic process but lacks key genes. This seems to indicate that B. fibrisolvens plays an important role in ruminal cellulolytic processes, but does not have autonomous cellulolytic capacity. When searching for genes involved in the biohydrogenation of unsaturated fatty acids, no linoleate isomerase gene was found in this strain. INBov1 does encode oleate hydratase genes known to participate in the hydrogenation of oleic acids. Furthermore, INBov1 contains an enolase gene, which has been recently determined to participate in the synthesis of conjugated linoleic acids. This work confirms the presence of a novel chromid in B. fibrisolvens and provides a new potential reference genome sequence for this species, providing new insight into its role in biohydrogenation and carbohydrate degradation.
10aAnimals10aButyrivibrio fibrisolvens10aCattle10aGenome, Bacterial10aGenomics10aHumans10aMilk10aRumen10aSequence Analysis, DNA1 aHernáez, Javier, Rodríguez1 aCucchi, Maria, Esperanza1 aCravero, Silvio1 aMartinez, Maria, Carolina1 aGonzalez, Sergio1 aPuebla, Andrea1 aDopazo, Joaquin1 aFarber, Marisa1 aPaniego, Norma1 aRivarola, Máximo uhttps://www.clinbioinfosspa.es/content/first-complete-genomic-structure-butyrivibrio-fibrisolvens-and-its-chromid02225nas a2200265 4500008004100000022001400041245012800055210006900183260001300252300001200265490000800277520128900285100002301574700002801597700002501625700002001650700002001670700001901690700002501709700002301734700002501757700002501782700002101807856013101828 2015 eng d a1600-072200aFamily-based genome-wide association study in Patagonia confirms the association of the DMD locus and cleft lip and palate.0 aFamilybased genomewide association study in Patagonia confirms t c2015 Oct a381-3840 v1233 aThe etiology of cleft lip with or without cleft palate (CL±P) is complex and heterogeneous, and multiple genetic and environmental factors are involved. Some candidate genes reported to be associated with oral clefts are located on the X chromosome. At least three genes causing X-linked syndromes [midline 1 (MID1), oral-facial-digital syndrome 1 (OFD1), and dystrophin (DMD)] were previously found to be associated with isolated CL±P. We attempted to confirm the role of X-linked genes in the etiology of isolated CL±P in a South American population through a family-based genome-wide scan. We studied 27 affected children and their mothers, from 26 families, in a Patagonian population with a high prevalence of CL±P. We conducted an exploratory analysis of the X chromosome to identify candidate regions associated with CL±P. Four genomic segments were identified, two of which showed a statistically significant association with CL±P. One is an 11-kb region of Xp21.1 containing the DMD gene, and the other is an intergenic region (8.7 kb; Xp11.4). Our results are consistent with recent data on the involvement of the DMD gene in the etiology of CL±P. The MID1 and OFD1 genes were not included in the four potential CL±P-associated X-chromosome genomic segments.
1 aFonseca, Renata, F1 ade Carvalho, Flávia, M1 aPoletta, Fernando, A1 aMontaner, David1 aDopazo, Joaquin1 aMereb, Juan, C1 aMoreira, Miguel, A M1 aSeuanez, Hector, N1 aVieira, Alexandre, R1 aCastilla, Eduardo, E1 aOrioli, Iêda, M uhttps://www.clinbioinfosspa.es/content/family-based-genome-wide-association-study-patagonia-confirms-association-dmd-locus-and02556nas a2200301 4500008004100000022001400041245008500055210006900140260001600209300000700225490000700232520160800239653001501847653001801862653001301880653004201893653001101935653002301946653002701969653001301996100002002009700002002029700002302049700002002072700002002092700002202112856012002134 2015 eng d a1471-210500aFast inexact mapping using advanced tree exploration on backward search methods.0 aFast inexact mapping using advanced tree exploration on backward c2015 Jan 28 a180 v163 aBACKGROUND: Short sequence mapping methods for Next Generation Sequencing consist on a combination of seeding techniques followed by local alignment based on dynamic programming approaches. Most seeding algorithms are based on backward search alignment, using the Burrows Wheeler Transform, the Ferragina and Manzini Index or Suffix Arrays. All these backward search algorithms have excellent performance, but their computational cost highly increases when allowing errors. In this paper, we discuss an inexact mapping algorithm based on pruning strategies for search tree exploration over genomic data.
RESULTS: The proposed algorithm achieves a 13x speed-up over similar algorithms when allowing 6 base errors, including insertions, deletions and mismatches. This algorithm can deal with 400 bps reads with up to 9 errors in a high quality Illumina dataset. In this example, the algorithm works as a preprocessor that reduces by 55% the number of reads to be aligned. Depending on the aligner the overall execution time is reduced between 20-40%.
CONCLUSIONS: Although not intended as a complete sequence mapping tool, the proposed algorithm could be used as a preprocessing step to modern sequence mappers. This step significantly reduces the number reads to be aligned, accelerating overall alignment time. Furthermore, this algorithm could be used for accelerating the seeding step of already available sequence mappers. In addition, an out-of-core index has been implemented for working with large genomes on systems without expensive memory configurations.
10aAlgorithms10aGenome, Human10aGenomics10aHigh-Throughput Nucleotide Sequencing10aHumans10aSequence Alignment10aSequence Analysis, DNA10aSoftware1 aSalavert, José1 aTomás, Andrés1 aTárraga, Joaquín1 aMedina, Ignacio1 aDopazo, Joaquin1 aBlanquer, Ignacio uhttps://www.clinbioinfosspa.es/content/fast-inexact-mapping-using-advanced-tree-exploration-backward-search-methods02193nas 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/abstract02491nas 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-000694nas a2200193 4500008004100000022001400041245010000055210006900155260000900224300000800233490000700241520001400248100002100262700002600283700001600309700002000325700002100345856013400366 2011 eng d a1471-222900aFortunella margarita Transcriptional Reprogramming Triggered by Xanthomonas citri subsp. citri.0 aFortunella margarita Transcriptional Reprogramming Triggered by c2011 a1590 v113 aABSTRACT:1 aKhalaf, Abeer, A1 aGmitter, Frederick, G1 aConesa, Ana1 aDopazo, Joaquin1 aMoore, Gloria, A uhttps://www.clinbioinfosspa.es/content/fortunella-margarita-transcriptional-reprogramming-triggered-xanthomonas-citri-subsp-citri03102nas a2200325 4500008004100000245012300041210006900164260001600233520197300249100001902222700001902241700002402260700002102284700001702305700003102322700002002353700003002373700002502403700002402428700001902452700001902471700002102490700002602511700002402537700002902561700001802590700002002608700001902628856012902647 2010 eng d00aFine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains.0 aFinescale evolution genomic phenotypic and ecological differenti c2010 Feb 183 aGenomic and metagenomic data indicate a high degree of genomic variation within microbial populations, although the ecological and evolutive meaning of this microdiversity remains unknown. Microevolution analyses, including genomic and experimental approaches, are so far very scarce for non-pathogenic bacteria. In this study, we compare the genomes, metabolomes and selected ecological traits of the strains M8 and M31 of the hyperhalophilic bacterium Salinibacter ruber that contain ribosomal RNA (rRNA) gene and intergenic regions that are identical in sequence and were simultaneously isolated from a Mediterranean solar saltern. Comparative analyses indicate that S. ruber genomes present a mosaic structure with conserved and hypervariable regions (HVRs). The HVRs or genomic islands, are enriched in transposases, genes related to surface properties, strain-specific genes and highly divergent orthologous. However, the many indels outside the HVRs indicate that genome plasticity extends beyond them. Overall, 10% of the genes encoded in the M8 genome are absent from M31 and could stem from recent acquisitions. S. ruber genomes also harbor 34 genes located outside HVRs that are transcribed during standard growth and probably derive from lateral gene transfers with Archaea preceding the M8/M31 divergence. Metabolomic analyses, phage susceptibility and competition experiments indicate that these genomic differences cannot be considered neutral from an ecological perspective. The results point to the avoidance of competition by micro-niche adaptation and response to viral predation as putative major forces that drive microevolution within these Salinibacter strains. In addition, this work highlights the extent of bacterial functional diversity and environmental adaptation, beyond the resolution of the 16S rRNA and internal transcribed spacers regions.The ISME Journal advance online publication, 18 February 2010; doi:10.1038/ismej.2010.6.
1 aPeña, Arantxa1 aTeeling, Hanno1 aHuerta-Cepas, Jaime1 aSantos, Fernando1 aYarza, Pablo1 aBrito-Echeverría, Jocelyn1 aLucio, Marianna1 aSchmitt-Kopplin, Philippe1 aMeseguer, Inmaculada1 aSchenowitz, Chantal1 aDossat, Carole1 aBarbe, Valerie1 aDopazo, Joaquín1 aRosselló-Mora, Ramon1 aSchüler, Margarete1 aGlöckner, Frank, Oliver1 aAmann, Rudolf1 aGabaldón, Toni1 aAntón, Josefa uhttps://www.clinbioinfosspa.es/content/fine-scale-evolution-genomic-phenotypic-and-ecological-differentiation-two-coexisting02604nas a2200229 4500008004100000245010300041210006900144260001500213300001200228490000800240520175600248100002902004700003802033700002802071700002902099700001802128700002002146700002002166700002302186700003002209856013502239 2010 eng d00aFM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status.0 aFM19G11 a new hypoxiainducible factor HIF modulator affects stem c2010 Jan 8 a1333-420 v2853 aThe biology of the alpha subunits of hypoxia-inducible factors (HIFalpha) has expanded from their role in angiogenesis to their current position in the self-renewal and differentiation of stem cells. The results reported in this article show the discovery of FM19G11, a novel chemical entity that inhibits HIFalpha proteins that repress target genes of the two alpha subunits, in various tumor cell lines as well as in adult and embryonic stem cell models from rodents and humans, respectively. FM19G11 inhibits at nanomolar range the transcriptional and protein expression of Oct4, Sox2, Nanog, and Tgf-alpha undifferentiating factors, in adult rat and human embryonic stem cells, FM19G11 activity occurs in ependymal progenitor stem cells from rats (epSPC), a cell model reported for spinal cord regeneration, which allows the progression of oligodendrocyte cell differentiation in a hypoxic environment, has created interest in its characterization for pharmacological research. Experiments using small interfering RNA showed a significant depletion in Sox2 protein only in the case of HIF2alpha silencing, but not in HIF1alpha-mediated ablation. Moreover, chromatin immunoprecipitation data, together with the significant presence of functional hypoxia response element consensus sequences in the promoter region of Sox2, strongly validated that this factor behaves as a target gene of HIF2alpha in epSPCs. FM19G11 causes a reduction of overall histone acetylation with significant repression of p300, a histone acetyltransferase required as a co-factor for HIF-transcription activation. Arrays carried out in the presence and absence of the inhibitor showed the predominant involvement of epigenetic-associated events mediated by the drug.
1 aMoreno-Manzano, Victoria1 aRodríguez-Jiménez, Francisco, J1 aAceña-Bonilla, Jose, L1 aFustero-Lardíes, Santos1 aErceg, Slaven1 aDopazo, Joaquin1 aMontaner, David1 aStojkovic, Miodrag1 aSánchez-Puelles, Jose, M uhttps://www.clinbioinfosspa.es/content/fm19g11-new-hypoxia-inducible-factor-hif-modulator-affects-stem-cell-differentiation-status03020nas 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-algorithms01719nas a2200229 4500008004100000022001400041245009600055210006900151260001300220300001000233490000600243520095200249653003101201653002901232653001301261653002001274653001301294653002001307100001901327700002001346856012301366 2010 eng d a1744-838700aFunctional genomics and networks: new approaches in the extraction of complex gene modules.0 aFunctional genomics and networks new approaches in the extractio c2010 Feb a55-630 v73 aThe engine that makes the cell work is made of an intricate network of molecular interactions. Nowadays, the elements and relationships of this complex network can be studied with several types of high-throughput techniques. The dream of having a global picture of the cell from different perspectives that can jointly explain cell behavior is, at least technically, feasible. However, this task can only be accomplished by filling the gap between data and information. The availability of methods capable of accurately managing, integrating and analyzing the results from these experiments is crucial for this purpose. Here, we review the new challenges raised by the availability of different genomic data, as well as the new proposals presented to cope with the increasing data complexity. Special emphasis is given to approaches that explore the transcriptome trying to describe the modules of genes that account for the traits studied.
10aGene Expression Regulation10aGene Regulatory Networks10aGenomics10aProtein Binding10aProteins10aSystems biology1 aMinguez, Pablo1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/functional-genomics-and-networks-new-approaches-extraction-complex-gene-modules02389nas a2200301 4500008004100000022001400041245010100055210006900156260001600225300001100241490000600252520140600258653001601664653002301680653003001703653001301733653001101746653004401757100001801801700002001819700001801839700002001857700001901877700002401896700002001920700001801940856012901958 2010 eng d a1932-620300aFunctional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis.0 aFunctional genomics of 5 to 8cell stage human embryos by blastom c2010 Oct 26 ae136150 v53 aBlastomere fate and embryonic genome activation (EGA) during human embryonic development are unsolved areas of high scientific and clinical interest. Forty-nine blastomeres from 5- to 8-cell human embryos have been investigated following an efficient single-cell cDNA amplification protocol to provide a template for high-density microarray analysis. The previously described markers, characteristic of Inner Cell Mass (ICM) (n = 120), stemness (n = 190) and Trophectoderm (TE) (n = 45), were analyzed, and a housekeeping pattern of 46 genes was established. All the human blastomeres from the 5- to 8-cell stage embryo displayed a common gene expression pattern corresponding to ICM markers (e.g., DDX3, FOXD3, LEFTY1, MYC, NANOG, POU5F1), stemness (e.g., POU5F1, DNMT3B, GABRB3, SOX2, ZFP42, TERT), and TE markers (e.g., GATA6, EOMES, CDX2, LHCGR). The EGA profile was also investigated between the 5-6- and 8-cell stage embryos, and compared to the blastocyst stage. Known genes (n = 92) such as depleted maternal transcripts (e.g., CCNA1, CCNB1, DPPA2) and embryo-specific activation (e.g., POU5F1, CDH1, DPPA4), as well as novel genes, were confirmed. In summary, the global single-cell cDNA amplification microarray analysis of the 5- to 8-cell stage human embryos reveals that blastomere fate is not committed to ICM or TE. Finally, new EGA features in human embryogenesis are presented.
10aBlastomeres10aDNA, Complementary10aGene Expression Profiling10aGenomics10aHumans10aOligonucleotide Array Sequence Analysis1 aGalan, Amparo1 aMontaner, David1 aPóo, Eugenia1 aValbuena, Diana1 aRuiz, Veronica1 aAguilar, Cristóbal1 aDopazo, Joaquin1 aSimon, Carlos uhttps://www.clinbioinfosspa.es/content/functional-genomics-5-8-cell-stage-human-embryos-blastomere-single-cell-cdna-analysis01411nas a2200157 4500008004100000245004400041210004300085260000900128300001100137490000800148520095000156100002101106700002301127700002401150856007901174 2010 eng d00aFunctional profiling methods in cancer.0 aFunctional profiling methods in cancer c2010 a363-740 v5763 aThe introduction of new high-throughput methodologies such as DNA microarrays constitutes a major breakthrough in cancer research. The unprecedented amount of data produced by such technologies has opened new avenues for interrogating living systems although, at the same time, it has demanded of the development of new data analytical methods as well as new strategies for testing hypotheses. A history of early successful applications in cancer boosted the use of microarrays and fostered further applications in other fields. Keeping the pace with these technologies, bioinformatics offers new solutions for data analysis and, what is more important, permits the formulation of a new class of hypotheses inspired in systems biology, more oriented to pathways or, in general, to modules of functionally related genes. Although these analytical methodologies are new, some options are already available and are discussed in this chapter.
1 aDopazo, Joaquín1 aGrützmann, Robert1 aPilarsky, Christian uhttps://www.clinbioinfosspa.es/content/functional-profiling-methods-cancer01773nas a2200205 4500008004100000022001400041245006300055210006200118260001700180300001100197490000700208520113100215653002501346653002601371653001301397653001301410653002401423100002001447856010001467 2009 eng d a1873-286000aFormulating and testing hypotheses in functional genomics.0 aFormulating and testing hypotheses in functional genomics c2009 Feb-Mar a97-1070 v453 aOBJECTIVE: The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the results, relating the available genomic information to the hypotheses that originated the experiment.
METHODS AND RESULTS: Initially, this interpretation has been made on a pre-selection of relevant genes, based on the experimental values, followed by the study of the enrichment in some functional properties. Nevertheless, functional enrichment methods, demonstrated to have a flaw: the first step of gene selection was too stringent given that the cooperation among genes was ignored. The assumption that modules of genes related by relevant biological properties (functionality, co-regulation, chromosomal location, etc.) are the real actors of the cell biology lead to the development of new procedures, inspired in systems biology criteria, generically known as gene-set methods. These methods have been successfully used to analyze transcriptomic and large-scale genotyping experiments as well as to test other different genome-scale hypothesis in other fields such as phylogenomics.
10aBiological Evolution10aComputational Biology10aGenomics10aGenotype10aModels, Theoretical1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/formulating-and-testing-hypotheses-functional-genomics-001598nas a2200145 4500008004100000245006200041210006200103300001100165490000700176520111100183653001501294653002201309100001501331856010601346 2009 eng d00aFormulating and testing hypotheses in functional genomics0 aFormulating and testing hypotheses in functional genomics a97-1070 v453 aOBJECTIVE: The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the results, relating the available genomic information to the hypotheses that originated the experiment. METHODS AND RESULTS: Initially, this interpretation has been made on a pre-selection of relevant genes, based on the experimental values, followed by the study of the enrichment in some functional properties. Nevertheless, functional enrichment methods, demonstrated to have a flaw: the first step of gene selection was too stringent given that the cooperation among genes was ignored. The assumption that modules of genes related by relevant biological properties (functionality, co-regulation, chromosomal location, etc.) are the real actors of the cell biology lead to the development of new procedures, inspired in systems biology criteria, generically known as gene-set methods. These methods have been successfully used to analyze transcriptomic and large-scale genotyping experiments as well as to test other different genome-scale hypothesis in other fields such as phylogenomics.
10ababelomics10agene set analysis1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1878965902718nas 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-data02422nas a2200469 4500008004100000022001400041245007800055210006900133260001300202300001300215490000700228520094000235653001001175653002101185653003001206653004101236653002601277653001101303653002101314653002201335653004401357653001901401653001801420653002701438100002001465700003001485700002701515700002501542700002101567700002401588700002801612700002601640700002701666700002401693700002201717700002101739700001501760700002001775700002301795700002101818856011301839 2009 eng d a1029-240300aFunctional signatures identified in B-cell non-Hodgkin lymphoma profiles.0 aFunctional signatures identified in Bcell nonHodgkin lymphoma pr c2009 Oct a1699-7080 v503 aGene-expression profiling in B-cell lymphomas has provided crucial data on specific lymphoma types, which can contribute to the identification of essential lymphoma survival genes and pathways. In this study, the gene-expression profiling data of all major B-cell lymphoma types were analyzed by unsupervised clustering. The transcriptome classification so obtained, was explored using gene set enrichment analysis generating a heatmap for B-cell lymphoma that identifies common lymphoma survival mechanisms and potential therapeutic targets, recognizing sets of coregulated genes and functional pathways expressed in different lymphoma types. Some of the most relevant signatures (stroma, cell cycle, B-cell receptor (BCR)) are shared by multiple lymphoma types or subclasses. A specific attention was paid to the analysis of BCR and coregulated pathways, defining molecular heterogeneity within multiple B-cell lymphoma types.
10aAdult10aCluster Analysis10aGene Expression Profiling10aGene Expression Regulation, Leukemic10aGenetic Heterogeneity10aHumans10aLymphoma, B-Cell10aNeoplasm Proteins10aOligonucleotide Array Sequence Analysis10aRNA, Messenger10aRNA, Neoplasm10aTranscription, Genetic1 aAggarwal, Mohit1 aSánchez-Beato, Margarita1 aGómez-López, Gonzalo1 aAl-Shahrour, Fátima1 aMartínez, Nerea1 aRodríguez, Antonia1 aRuiz-Ballesteros, Elena1 aCamacho, Francisca, I1 aPérez-Rosado, Alberto1 ade la Cueva, Paloma1 aArtiga, María, J1 aPisano, David, G1 aKimby, Eva1 aDopazo, Joaquin1 aVilluendas, Raquel1 aPiris, Miguel, A uhttps://www.clinbioinfosspa.es/content/functional-signatures-identified-b-cell-non-hodgkin-lymphoma-profiles00524nas a2200121 4500008004100000245007600041210006900117260004900186100001600235700002300251700001500274856011300289 2007 eng d00af single nucleotide polymorphism arrays: Design, tools and applications0 af single nucleotide polymorphism arrays Design tools and applica aNew York, USAbTaylor & Francis, F. Falciani1 aRobledo, M.1 aGonzález-Neira, A1 aDopazo, J. uhttps://www.clinbioinfosspa.es/content/f-single-nucleotide-polymorphism-arrays-design-tools-and-applications02196nas a2200217 4500008004100000245016500041210006900206300001000275490000700285520140700292653001501699653003501714100002401749700001601773700001601789700002001805700001501825700001701840700001501857856010601872 2007 eng d00aFatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments0 aFatiGO a functional profiling tool for genomic data Integration aW91-60 v353 aThe ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.
10ababelomics10afunctional enrichment analysys1 aAl-Shahrour, Fatima1 aMinguez, P.1 aTarraga, J.1 aMedina, Ignacio1 aAlloza, E.1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1747850402680nas a2200385 4500008004100000022001400041245016600055210006900221260001300290300001000303490000700313520140700320653002201727653001201749653001801761653002601779653003001805653001001835653001301845653001101858653001301869653004401882653002601926653001301952653002401965653002601989100002502015700001902040700002302059700002002082700001602102700002002118700002002138856013602158 2007 eng d a1362-496200aFatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.0 aFatiGO a functional profiling tool for genomic data Integration c2007 Jul aW91-60 v353 aThe ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.
10aAmino Acid Motifs10aAnimals10aBinding Sites10aComputational Biology10aGene Expression Profiling10aGenes10aGenomics10aHumans10aInternet10aOligonucleotide Array Sequence Analysis10aProgramming Languages10aSoftware10aSystems Integration10aTranscription Factors1 aAl-Shahrour, Fátima1 aMinguez, Pablo1 aTárraga, Joaquín1 aMedina, Ignacio1 aAlloza, Eva1 aMontaner, David1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/fatigo-functional-profiling-tool-genomic-data-integration-functional-annotation-regulatory-002090nas a2200169 4500008004100000245011600041210006900157300000900226490000600235520123000241653007701471653008501548653014401633100001801777700001901795856010601814 2007 eng d00aFrom endosymbiont to host-controlled organelle: the hijacking of mitochondrial protein synthesis and metabolism0 aFrom endosymbiont to hostcontrolled organelle the hijacking of m ae2190 v33 aMitochondria are eukaryotic organelles that originated from the endosymbiosis of an alpha-proteobacterium. To gain insight into the evolution of the mitochondrial proteome as it proceeded through the transition from a free-living cell to a specialized organelle, we compared a reconstructed ancestral proteome of the mitochondrion with the proteomes of alpha-proteobacteria as well as with the mitochondrial proteomes in yeast and man. Overall, there has been a large turnover of the mitochondrial proteome during the evolution of mitochondria. Early in the evolution of the mitochondrion, proteins involved in cell envelope synthesis have virtually disappeared, whereas proteins involved in replication, transcription, cell division, transport, regulation, and signal transduction have been replaced by eukaryotic proteins. More than half of what remains from the mitochondrial ancestor in modern mitochondria corresponds to translation, including post-translational modifications, and to metabolic pathways that are directly, or indirectly, involved in energy conversion. Altogether, the results indicate that the eukaryotic host has hijacked the proto-mitochondrion, taking control of its protein synthesis and metabolism.10aComputer Simulation DNA Mutational Analysis/methods Evolution *Evolution10aGenetic Organelles/physiology Protein Biosynthesis/*genetics Symbiosis/*genetics10aMolecular Fungal Proteins/*physiology Genetic Variation/genetics Humans Mitochondria/*physiology Mitochondrial Proteins/*physiology *Models1 aGabaldón, T.1 aHuynen, M., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1798326502367nas a2200229 4500008004100000245007200041210006900113300000800182490000600190520145600196653010501652653001501757653013601772100002401908700001501932700001501947700002101962700001601983700001701999700001502016856010602031 2007 eng d00aFrom genes to functional classes in the study of biological systems0 aFrom genes to functional classes in the study of biological syst a1140 v83 aBACKGROUND: With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed. RESULTS: Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics. CONCLUSION: Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.
10aAlgorithms Chromosome Mapping/*methods Computer Simulation Gene Expression Profiling/methods *Models10ababelomics10aBiological Multigene Family/*physiology Signal Transduction/*physiology *Software Systems Biology/*methods *User-Computer Interface1 aAl-Shahrour, Fatima1 aArbiza, L.1 aDopazo, H.1 aHuerta-Cepas, J.1 aMinguez, P.1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1740759602519nas a2200337 4500008004100000022001400041245007300055210006900128260001600197300000800213490000600221520148900227653001501716653002301731653002401754653003001778653002301808653002101831653002401852653001301876653002001889653002801909100002501937700002101962700002001983700002402003700001902027700002002046700002002066856009502086 2007 eng d a1471-210500aFrom genes to functional classes in the study of biological systems.0 aFrom genes to functional classes in the study of biological syst c2007 Apr 03 a1140 v83 aBACKGROUND: With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed.
RESULTS: Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics.
CONCLUSION: Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.
10aAlgorithms10aChromosome Mapping10aComputer Simulation10aGene Expression Profiling10aModels, Biological10aMultigene Family10aSignal Transduction10aSoftware10aSystems biology10aUser-Computer Interface1 aAl-Shahrour, Fátima1 aArbiza, Leonardo1 aDopazo, Hernán1 aHuerta-Cepas, Jaime1 aMinguez, Pablo1 aMontaner, David1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/genes-functional-classes-study-biological-systems-000431nas a2200109 4500008004100000245005200041210005200093260004900145100001500194700002400209856008800233 2007 eng d00aFunctional annotation of microarray experiments0 aFunctional annotation of microarray experiments aNew York, USAbTaylor & Francis, F. Falciani1 aDopazo, J.1 aAl-Shahrour, Fatima uhttps://www.clinbioinfosspa.es/content/functional-annotation-microarray-experiments01771nas a2200205 4500008004100000022001400041245009400055210006900149260001600218300001000234490000600244520105200250100001701302700002001319700002701339700002301366700002501389700002001414856013101434 2007 eng d a0973-206300aFunctional profiling and gene expression analysis of chromosomal copy number alterations.0 aFunctional profiling and gene expression analysis of chromosomal c2007 Apr 10 a432-50 v13 aContrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.
1 aConde, Lucia1 aMontaner, David1 aBurguet-Castell, Jordi1 aTárraga, Joaquín1 aAl-Shahrour, Fátima1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/functional-profiling-and-gene-expression-analysis-chromosomal-copy-number-alterations-001696nas a2200193 4500008004100000245009300041210006900134300001000203490000600213520105200219653001501271100001401286700001701300700002401317700001601341700002401357700001501381856010601396 2007 eng d00aFunctional profiling and gene expression analysis of chromosomal copy number alterations0 aFunctional profiling and gene expression analysis of chromosomal a432-50 v13 aContrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.
10ababelomics1 aConde, L.1 aMontaner, D.1 aBurguet-Castell, J.1 aTarraga, J.1 aAl-Shahrour, Fatima1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1759793501723nas a2200277 4500008004100000022001400041245009000055210006900145260001600214300001100230490000700241520077800248653002801026653002301054653003001077653003801107653003201145653001301177653002001190653002401210100001901234700002501253700002001278700002001298856012701318 2007 eng d a1367-481100aFunctional profiling of microarray experiments using text-mining derived bioentities.0 aFunctional profiling of microarray experiments using textmining c2007 Nov 15 a3098-90 v233 aMOTIVATION: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.
10aArtificial Intelligence10aDatabases, Protein10aGene Expression Profiling10aInformation Storage and Retrieval10aNatural Language Processing10aProteins10aResearch Design10aSystems Integration1 aMinguez, Pablo1 aAl-Shahrour, Fátima1 aMontaner, David1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/functional-profiling-microarray-experiments-using-text-mining-derived-bioentities-001608nas a2200193 4500008004100000245008900041210006900130300001100199490000700210520077100217653003900988653001501027653019401042100001601236700002401252700001701276700001501293856010601308 2007 eng d00aFunctional profiling of microarray experiments using text-mining derived bioentities0 aFunctional profiling of microarray experiments using textmining a3098-90 v233 aMOTIVATION: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.
10aArtificial Intelligence *Databases10ababelomics10aProtein Gene Expression Profiling/*methods Information Storage and Retrieval/*methods *Natural Language Processing Proteins/*classification/*metabolism Research/*methods Systems Integration1 aMinguez, P.1 aAl-Shahrour, Fatima1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1785541501588nas a2200157 4500008004100000245005600041210005600097300001200153490000700165520107100172653001501243653002201258653002901280100001501309856010601324 2006 eng d00aFunctional interpretation of microarray experiments0 aFunctional interpretation of microarray experiments a398-4100 v103 aOver the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.
10ababelomics10aDiabetes Mellitus10amicroarray data analysis1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1706951602404nas a2200157 4500008004100000245009100041210006900132300001000201490000700211520184000218653001502058100001602073700002402089700001502113856011802128 2006 eng d00aA function-centric approach to the biological interpretation of microarray time-series0 afunctioncentric approach to the biological interpretation of mic a57-660 v173 aThe interpretation of microarray experiments is commonly addressed by means a two-step approach in which the relevant genes are firstly selected uniquely on the basis of their experimental values (ignoring their coordinate behaviors) and in a second step their functional properties are studied to hypothesize about the biological roles they are fulfilling in the cell. Recently, different methods (e.g. GSEA or FatiScan) have been proposed to study the coordinate behavior of blocks of functionally-related genes. These methods study the distribution of functional information across lists of genes ranked according their different experimental values in a static situation, such as the comparison between two classes (e.g. healthy controls versus diseased cases). Nevertheless there is no an equivalent way of studying a dynamic situation from a functional point of view. We present a method for the functional analysis of microarrays series in which the experiments display autocorrelation between successive points (e.g. time series, dose-response experiments, etc.) The method allows to recover the dynamics of the molecular roles fulfilled by the genes along the series which provides a novel approach to functional interpretation of such experiments. The method finds blocks of functionally-related genes which are significantly and coordinately over-expressed at different points of the series. This method draws inspiration from systems biology given that the analysis does not focus on individual properties of genes but on collective behaving blocks of functionally-related genes. The FatiScan algorithm used in the method proposed is available at: http://fatiscan.bioinfo.cipf.es, or within the Babelomics suite: http://www.babelomics.org. Additional material is available at: http://bioinfo.cipf.es/data/plasmodium.
10ababelomics1 aMinguez, P.1 aAl-Shahrour, Fatima1 aDopazo, J. uhttps://www.clinbioinfosspa.es/content/function-centric-approach-biological-interpretation-microarray-time-series01450nas a2200193 4500008004100000245010400041210006900145300001100214490000700225520063300232653005000865653001500915653002700930653016800957100002401125700002101149700001501170856007101185 2004 eng d00aFatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes0 aFatiGO a web tool for finding significant associations of Gene O a578-800 v203 aWe present a simple but powerful procedure to extract Gene Ontology (GO) terms that are significantly over- or under-represented in sets of genes within the context of a genome-scale experiment (DNA microarray, proteomics, etc.). Said procedure has been implemented as a web application, FatiGO, allowing for easy and interactive querying. FatiGO, which takes the multiple-testing nature of statistical contrast into account, currently includes GO associations for diverse organisms (human, mouse, fly, worm and yeast) and the TrEMBL/Swissprot GOAnnotations@EBI correspondences from the European Bioinformatics Institute.
10a*Algorithms Artificial Intelligence Databases10ababelomics10aDNA/*methods *Software10aGenetic Gene Expression Profiling/*methods *Hypermedia Information Storage and Retrieval/*methods *Internet *Phylogeny Sequence Alignment/methods Sequence Analysis1 aAl-Shahrour, Fatima1 aDiaz-Uriarte, R.1 aDopazo, J. uhttp://bioinformatics.oxfordjournals.org/content/20/4/578.abstract01632nas a2200193 4500008004100000245007600041210006900117300001000186490000700196520078800203653023600991100001701227700001901244700001501263700001501278700001601293700002301309856010601332 2002 eng d00aFilamentous fungi as cell factories for heterologous protein production0 aFilamentous fungi as cell factories for heterologous protein pro a200-60 v203 aFilamentous fungi have been used as sources of metabolites and enzymes for centuries. For about two decades, molecular genetic tools have enabled us to use these organisms to express extra copies of both endogenous and exogenous genes. This review of current practice reveals that molecular tools have enabled several new developments. But it has been process development that has driven the final breakthrough to achieving commercially relevant quantities of protein. Recent research into gene expression in filamentous fungi has explored their wealth of genetic diversity with a view to exploiting them as expression hosts and as a source of new genes. Inevitably, the progress in the ’genomics’ technology will further develop high-throughput technologies for these organisms.10aFermentation/genetics/physiology Fungi/*genetics/*metabolism Humans Interleukin-6/analysis/*biosynthesis/genetics Peroxidases/analysis/*biosynthesis/genetics Protein Conformation Recombinant Proteins/analysis/*biosynthesis/genetics1 aPunt, P., J.1 avan Biezen, N.1 aConesa, A.1 aAlbers, A.1 aMangnus, J.1 avan den Hondel, C. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1194337501436nas a2200157 4500008004100000245005900041210005800100300001100158490000700169520072900176653020800905100001501113700001701128700002701145856010601172 2002 eng d00aFungal peroxidases: molecular aspects and applications0 aFungal peroxidases molecular aspects and applications a143-580 v933 aPeroxidases are oxidoreductases that utilize hydrogen peroxide to catalyze oxidative reactions. A large number of peroxidases have been identified in fungal species and are being characterized at the molecular level. In this manuscript we review the current knowledge on the molecular aspects of this type of enzymes. We present an overview of the research efforts undertaken in deciphering the structural basis of the catalytic properties of fungal peroxidases and discuss molecular genetics and protein homology aspects of this enzyme class. Finally, we summarize the potential biotechnological applications of these enzymes and evaluate recent advances on their expression in heterologous systems for production purposes.10aAmino Acid Sequence Binding Sites Biotechnology Catalysis Fungi/*enzymology Molecular Sequence Data Peroxidases/chemistry/*genetics/metabolism Recombinant Proteins Sequence Homology Substrate Specificity1 aConesa, A.1 aPunt, P., J.1 avan den Hondel, C., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11738721