@article {513, title = {Diversification of the expanded teleost-specific toll-like receptor family in Atlantic cod, Gadus morhua.}, journal = {BMC Evol Biol}, volume = {12}, year = {2012}, month = {2012 Dec 29}, pages = {256}, abstract = {

BACKGROUND: Toll-like receptors (Tlrs) are major molecular pattern recognition receptors of the innate immune system. Atlantic cod (Gadus morhua) is the first vertebrate known to have lost most of the mammalian Tlr orthologues, particularly all bacterial recognising and other cell surface Tlrs. On the other hand, its genome encodes a unique repertoire of teleost-specific Tlrs. The aim of this study was to investigate if these duplicate Tlrs have been retained through adaptive evolution to compensate for the lack of other cell surface Tlrs in the cod genome.

RESULTS: In this study, one tlr21, 12 tlr22 and two tlr23 genes representing the teleost-specific Tlr family have been cloned and characterised in cod. Phylogenetic analysis grouped all tlr22 genes under a single clade, indicating that the multiple cod paralogues have arisen through lineage-specific duplications. All tlrs examined were transcribed in immune-related tissues as well as in stomach, gut and gonads of adult cod and were differentially expressed during early development. These tlrs were also differentially regulated following immune challenge by immersion with Vibrio anguillarum, indicating their role in the immune response. An increase in water temperature from 4 to 12{\textdegree}C was associated with a 5.5-fold down-regulation of tlr22d transcript levels in spleen. Maximum likelihood analysis with different evolution models revealed that tlr22 genes are under positive selection. A total of 24 codons were found to be positively selected, of which 19 are in the ligand binding region of ectodomain.

CONCLUSION: Positive selection pressure coupled with experimental evidence of differential expression strongly support the hypothesis that teleost-specific tlr paralogues in cod are undergoing neofunctionalisation and can recognise bacterial pathogen-associated molecular patterns to compensate for the lack of other cell surface Tlrs.

}, keywords = {Amino Acid Sequence, Animals, Binding Sites, Evolution, Molecular, Fish Diseases, Fish Proteins, Gadus morhua, Gene Expression Profiling, Genetic Variation, Gills, Head Kidney, Host-Pathogen Interactions, Models, Molecular, Molecular Sequence Data, Multigene Family, Phylogeny, Protein Structure, Tertiary, Reverse Transcriptase Polymerase Chain Reaction, Selection, Genetic, Sequence Analysis, DNA, Sequence Homology, Amino Acid, Temperature, Toll-Like Receptors, Vibrio}, issn = {1471-2148}, doi = {10.1186/1471-2148-12-256}, author = {Sundaram, Arvind Y M and Kiron, Viswanath and Dopazo, Joaquin and Fernandes, Jorge M O} } @article {517, title = {Inferring the regulatory network behind a gene expression experiment.}, journal = {Nucleic Acids Res}, volume = {40}, year = {2012}, month = {2012 Jul}, pages = {W168-72}, abstract = {

Transcription factors (TFs) and miRNAs are the most important dynamic regulators in the control of gene expression in multicellular organisms. These regulatory elements play crucial roles in development, cell cycling and cell signaling, and they have also been associated with many diseases. The Regulatory Network Analysis Tool (RENATO) web server makes the exploration of regulatory networks easy, enabling a better understanding of functional modularity and network integrity under specific perturbations. RENATO is suitable for the analysis of the result of expression profiling experiments. The program analyses lists of genes and search for the regulators compatible with its activation or deactivation. Tests of single enrichment or gene set enrichment allow the selection of the subset of TFs or miRNAs significantly involved in the regulation of the query genes. RENATO also offers an interactive advanced graphical interface that allows exploring the regulatory network found.RENATO is available at: http://renato.bioinfo.cipf.es/.

}, keywords = {Binding Sites, Databases, Genetic, Fanconi Anemia, Gene Regulatory Networks, Internet, MicroRNAs, Software, Transcription Factors, Transcriptome}, issn = {1362-4962}, doi = {10.1093/nar/gks573}, author = {Bleda, Marta and Medina, Ignacio and Alonso, Roberto and De Maria, Alejandro and Salavert, Francisco and Dopazo, Joaquin} } @article {605, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W91-6}, abstract = {

The 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.

}, keywords = {Amino Acid Motifs, Animals, Binding Sites, Computational Biology, Gene Expression Profiling, Genes, Genomics, Humans, Internet, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, Transcription Factors}, issn = {1362-4962}, doi = {10.1093/nar/gkm260}, author = {Al-Shahrour, F{\'a}tima and Minguez, Pablo and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Alloza, Eva and Montaner, David and Dopazo, Joaquin} }