Project description:<p>While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis- association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell- specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (<a href="http://dice-database.org">http://dice-database.org</a>). </p>
Project description:We developed a novel approach combining next generation sequencing, bioinformatics and mass spectrometry to assess the impact of non-MHC polymorphisms on the repertoire of MHC I-associated peptides (MIPs). We compared the genomic landscape of MIPs eluted from B lymphoblasts of two MHC-identical siblings and determined that MIPs mirror the genomic frequency of non-synonymous polymorphisms but they behave as recessive traits at the surface level. Moreover, we showed that 11.7% of the MIP coding exome is polymorphic at the population level. Our method provides fundamental insights into the relation between the genomic self and the immune self and accelerates the discovery of polymorphic MIPs (also known as minor histocompatibility antigens), which play a major role in allo-immune responses. RNA-seq of human B lymphoblasts derived from peripheral blood mononuclear cells from 2 HLA-identical female siblings.
Project description:We developed a novel approach combining next generation sequencing, bioinformatics and mass spectrometry to assess the impact of non-MHC polymorphisms on the repertoire of MHC I-associated peptides (MIPs). We compared the genomic landscape of MIPs eluted from B lymphoblasts of two MHC-identical siblings and determined that MIPs mirror the genomic frequency of non-synonymous polymorphisms but they behave as recessive traits at the surface level. Moreover, we showed that 11.7% of the MIP coding exome is polymorphic at the population level. Our method provides fundamental insights into the relation between the genomic self and the immune self and accelerates the discovery of polymorphic MIPs (also known as minor histocompatibility antigens), which play a major role in allo-immune responses.
Project description:While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org).
Project description:Stable ethnic variations in DNA methylation are associated with genetic polymorphisms. This experiment was updated on 21st July 2012. The normalized data file was updated.
Project description:Identification of genetic polymorphisms associated with inter-individual variation in immune response to Mycobacterium tuberculosis infection.
Project description:Identification of genetic polymorphisms associated with inter-individual variation in immune response to Mycobacterium tuberculosis infection.