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Background: Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR) is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV) and TCSR. Results: A classifier for differentiating CD4+ T cell-specific genes from housekeeping genes using HMV data was built. We found HMV in both promoter and gene body regions to be predictive of genes which are targets of TCSR. For example, the histone modification types H3K4me3 and H3K27ac were identified as the most predictive for CpG-related promoters, whereas H3K4me3 and H3K79me3 were the most predictive for nonCpG-related promoters. However, genes targeted by TCSR can be predicted using other type of HMVs as well. Such redundancy implies that multiple type of underlying regulatory elements, such as enhancers or intragenic alternative promoters, which can regulate gene expression in a tissue/cell-type specific fashion, may be marked by the HMVs. Finally, we show that the predictive power of HMV for TCSR is not limited to protein-coding genes in CD4+ T cells, as we successfully predicted TCSR targeted genes in muscle cells, as well as microRNA genes with expression specific to CD4+ T cells, by the same classifier which was trained on HMV data of protein-coding genes in CD4+ T cells. Conclusion: We have begun to understand the HMV patterns that guide gene expression in both tissue/cell-type specific and ubiquitous manner. [ABSTRACT FROM AUTHOR]

Background: Adaptative immune repertoire diversity in vertebrate species is generated by recombination of variable (V), diversity (D) and joining (J) genes in the immunoglobulin (IG) loci of B lymphocytes and in the T cell receptor (TR) loci of T lymphocytes. These V-J and V-D-J gene rearrangements at the DNA level involve recombination signal sequences (RSS). Whereas many data exist, they are scattered in non specialized resources with different nomenclatures (eg. flat files) and are difficult to extract. Description: IMGT/GeneInfo is an online information system that provides, through a user-friendly interface, exhaustive information resulting from the complex mechanisms of T cell receptor V-J and V-DJ recombinations. T cells comprise two populations which express the αβand γδ TR, respectively. The first version of the system dealt with the Homo sapiens and Mus musculus TRA and TRB loci whose gene rearrangements allow the synthesis of the αβ TR chains. In this paper, we present the second version of IMGT/GeneInfo where we complete the database for the Homo sapiens and Mus musculus TRG and TRD loci along with the introduction of a quality control procedure for existing and new data. We also include new functionalities to the four loci analysis, giving, to date, a very informative tool which allows to work on V(D)J genes of all TR loci in both human and mouse species. IMGT/GeneInfo provides more than 59,000 rearrangement combinations with a full gene description which is freely available at http://imgt.cines.fr/ GeneInfo. Conclusion: IMGT/GeneInfo allows all TR information sequences to be in the same spot, and are now available within two computer-mouse clicks. This is useful for biologists and bioinformaticians for the study of T lymphocyte V(D)J gene rearrangements and their applications in immune response analysis. [ABSTRACT FROM AUTHOR]

A conference paper on inferring gene regulatory networks from classified microarray data is presented. The network inference method is based on the optimal network search algorithm proposed by Ott. ROC analysis of networks recovered from synthetic data provides a measure of the performance of the method. The method shows that distinct sub-networks associated with AML and with T-cell responses emerge.