02262nas a2200193 4500008004100000245016300041210006900204520151300273100001501786700002901801700001501830700001801845700001601863700002101879700002601900700002201926700001401948856010601962 2009 eng d00aMembrane transporters and carbon metabolism implicated in chloride homeostasis differentiate salt stress responses in tolerant and sensitive Citrus rootstocks0 aMembrane transporters and carbon metabolism implicated in chlori3 a

Salinity tolerance in Citrus is strongly related to leaf chloride accumulation. Both chloride homeostasis and specific genetic responses to Cl(-) toxicity are issues scarcely investigated in plants. To discriminate the transcriptomic network related to Cl(-) toxicity and salinity tolerance, we have used two Cl(-) salt treatments (NaCl and KCl) to perform a comparative microarray approach on two Citrus genotypes, the salt-sensitive Carrizo citrange, a poor Cl(-) excluder, and the tolerant Cleopatra mandarin, an efficient Cl(-) excluder. The data indicated that Cl(-) toxicity, rather than Na(+) toxicity and/or the concomitant osmotic perturbation, is the primary factor involved in the molecular responses of citrus plant leaves to salinity. A number of uncharacterized membrane transporter genes, like NRT1-2, were differentially regulated in the tolerant and the sensitive genotypes, suggesting its potential implication in Cl(-) homeostasis. Analyses of enriched functional categories showed that the tolerant rootstock induced wider stress responses in gene expression while repressing central metabolic processes such as photosynthesis and carbon utilization. These features were in agreement with phenotypic changes in the patterns of photosynthesis, transpiration, and stomatal conductance and support the concept that regulation of transpiration and its associated metabolic adjustments configure an adaptive response to salinity that reduces Cl(-) accumulation in the tolerant genotype.

1 aBrumos, J.1 aColmenero-Flores, J., M.1 aConesa, A.1 aIzquierdo, P.1 aSanchez, G.1 aIglesias, D., J.1 aLopez-Climent, M., F.1 aGomez-Cadenas, A.1 aTalon, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1919094403856nas a2200385 4500008004100000245011000041210006900151300000700220490000600227520253000233653016602763653002902929653009302958100001403051700001503065700002203080700001503102700001403117700001503131700001303146700001503159700001403174700001503188700002103203700001303224700001403237700001503251700001703266700001903283700001503302700001603317700001703333700001403350856010603364 2007 eng d00aAnalysis of 13000 unique Citrus clusters associated with fruit quality, production and salinity tolerance0 aAnalysis of 13000 unique Citrus clusters associated with fruit q a310 v83 aBACKGROUND: Improvement of Citrus, the most economically important fruit crop in the world, is extremely slow and inherently costly because of the long-term nature of tree breeding and an unusual combination of reproductive characteristics. Aside from disease resistance, major commercial traits in Citrus are improved fruit quality, higher yield and tolerance to environmental stresses, especially salinity. RESULTS: A normalized full length and 9 standard cDNA libraries were generated, representing particular treatments and tissues from selected varieties (Citrus clementina and C. sinensis) and rootstocks (C. reshni, and C. sinenis x Poncirus trifoliata) differing in fruit quality, resistance to abscission, and tolerance to salinity. The goal of this work was to provide a large expressed sequence tag (EST) collection enriched with transcripts related to these well appreciated agronomical traits. Towards this end, more than 54000 ESTs derived from these libraries were analyzed and annotated. Assembly of 52626 useful sequences generated 15664 putative transcription units distributed in 7120 contigs, and 8544 singletons. BLAST annotation produced significant hits for more than 80% of the hypothetical transcription units and suggested that 647 of these might be Citrus specific unigenes. The unigene set, composed of 13000 putative different transcripts, including more than 5000 novel Citrus genes, was assigned with putative functions based on similarity, GO annotations and protein domains CONCLUSION: Comparative genomics with Arabidopsis revealed the presence of putative conserved orthologs and single copy genes in Citrus and also the occurrence of both gene duplication events and increased number of genes for specific pathways. In addition, phylogenetic analysis performed on the ammonium transporter family and glycosyl transferase family 20 suggested the existence of Citrus paralogs. Analysis of the Citrus gene space showed that the most important metabolic pathways known to affect fruit quality were represented in the unigene set. Overall, the similarity analyses indicated that the sequences of the genes belonging to these varieties and rootstocks were essentially identical, suggesting that the differential behaviour of these species cannot be attributed to major sequence divergences. This Citrus EST assembly contributes both crucial information to discover genes of agronomical interest and tools for genetic and genomic analyses, such as the development of new markers and microarrays.10aAcclimatization/*genetics Amino Acid Motifs Citrus/*genetics Cluster Analysis Expressed Sequence Tags Fruit/genetics Gene Duplication *Gene Expression Regulation10aPlant Gene Library Genes10aPlant Genomics Molecular Sequence Data Multigene Family Phylogeny *Salts/adverse effects1 aTerol, J.1 aConesa, A.1 aColmenero, J., M.1 aCercos, M.1 aTadeo, F.1 aAgusti, J.1 aAlos, E.1 aAndres, F.1 aSoler, G.1 aBrumos, J.1 aIglesias, D., J.1 aGotz, S.1 aLegaz, F.1 aArgout, X.1 aCourtois, B.1 aOllitrault, P.1 aDossat, C.1 aWincker, P.1 aMorillon, R.1 aTalon, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1725432702714nas 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=1751925002657nas a2200277 4500008004100000245007600041210006900117300001200186490000600198520157700204653011001781653008001891653001701971653001801988653005402006653006902060100001802129700002102147700001502168700001802183700001402201700001802215700002102233700001902254856010602273 2007 eng d00aSpatial differentiation in the vegetative mycelium of Aspergillus niger0 aSpatial differentiation in the vegetative mycelium of Aspergillu a2311-220 v63 aFungal mycelia are exposed to heterogenic substrates. The substrate in the central part of the colony has been (partly) degraded, whereas it is still unexplored at the periphery of the mycelium. We here assessed whether substrate heterogeneity is a main determinant of spatial gene expression in colonies of Aspergillus niger. This question was addressed by analyzing whole-genome gene expression in five concentric zones of 7-day-old maltose- and xylose-grown colonies. Expression profiles at the periphery and the center were clearly different. More than 25% of the active genes showed twofold differences in expression between the inner and outermost zones of the colony. Moreover, 9% of the genes were expressed in only one of the five concentric zones, showing that a considerable part of the genome is active in a restricted part of the colony only. Statistical analysis of expression profiles of colonies that had either been or not been transferred to fresh xylose-containing medium showed that differential expression in a colony is due to the heterogeneity of the medium (e.g., genes involved in secretion, genes encoding proteases, and genes involved in xylose metabolism) as well as to medium-independent mechanisms (e.g., genes involved in nitrate metabolism and genes involved in cell wall synthesis and modification). Thus, we conclude that the mycelia of 7-day-old colonies of A. niger are highly differentiated. This conclusion is also indicated by the fact that distinct zones of the colony grow and secrete proteins, even after transfer to fresh medium.10aAspergillus niger/*metabolism Cell Wall/metabolism Fungal Proteins/metabolism *Gene Expression Regulation10aBiological Mycelium/*metabolism Oligonucleotide Array Sequence Analysis RNA10aFungal Genes10aFungal Genome10aFungal Glucans/chemistry Maltose/chemistry Models10aFungal Time Factors Trans-Activators/metabolism Xylose/chemistry1 aLevin, A., M.1 ade Vries, R., P.1 aConesa, A.1 ade Bekker, C.1 aTalon, M.1 aMenke, H., H.1 avan Peij, N., N.1 aWosten, H., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1795151302376nas a2200229 4500008004100000245009300041210006900134300001200203490000800215520165600223653001501879100001701894700001301911700001501924700001801939700001701957700001901974700001801993700001502011700001402026856010602040 2006 eng d00aBlast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis0 aBlast2GO goes grid developing a gridenabled prototype for functi a194-2040 v1203 a

The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.

10ababelomics1 aAparicio, G.1 aGotz, S.1 aConesa, A.1 aSegrelles, D.1 aBlanquer, I.1 aGarcia, J., M.1 aHernandez, V.1 aRobles, M.1 aTalon, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1682313801934nas 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=1648133301401nas a2200193 4500008004100000245010600041210006900147300001100216490000700227520075600234653001500990100001501005700001301020700002501033700001401058700001401072700001501086856010601101 2005 eng d00aBlast2GO: a universal tool for annotation, visualization and analysis in functional genomics research0 aBlast2GO a universal tool for annotation visualization and analy a3674-60 v213 a

SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. AVAILABILITY: Blast2GO is freely available via Java Web Start at http://www.blast2go.de. SUPPLEMENTARY MATERIAL: http://www.blast2go.de -> Evaluation.

10ababelomics1 aConesa, A.1 aGotz, S.1 aGarcia-Gomez, J., M.1 aTerol, J.1 aTalon, M.1 aRobles, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1608147403705nas 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=15830128