Project description:STAT3 is a transcription factor playing a crucial role in inflammation, immunity and oncogenesis, able to induce distinct subsets of target genes in different cell types or under different conditions. Identification of direct transcriptional targets however has only defined a relatively limited set of genes, not sufficient to explain its variegated functions. In order to improve our understanding of the STAT3 transcriptional network we decided to develop a computational approach for the discovery of STAT3 functional binding sites. Upon generating a Positional Weight Matrix to define STAT3 binding sites, we applied a loglikelihood ratio scoring function and were able to assign affinity scores with very high specificity (93.5%) as measured by EMSA. STAT3 binding sites scoring above a stringent threshold have been identified genome-wide in Homo sapiens and Mus musculus and selected for phylogenetic conservation by genomic sequence alignment using eight vertebrate species. Validation was carried out on a subset of predicted; sites within genes previously identified as STAT3-responsive by microarray analysis. The high percentage of sites able to bind STAT3 in vivo, as assessed by Chromatin Immunoprecipitation (ChIP) analysis, revealed the high predictive power of our method. Experiment Overall Design: Three prototypic situation were investigated using two replications for each experimental point: STAT3+/+ versus STAT3-/- MEFs , STAT3+/+ versus STAT3+/+ treated with OSM and STAT3-/- versus STAT3-/- treated with OSM.
Project description:To characterize the genetic basis of hybrid male sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven ‘hotspots,’ seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL - but not cis eQTL - were substantially lower when mapping was restricted to a ‘fertile’ subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility.
Project description:STAT3 is a transcription factor playing a crucial role in inflammation, immunity and oncogenesis, able to induce distinct subsets of target genes in different cell types or under different conditions. Identification of direct transcriptional targets however has only defined a relatively limited set of genes, not sufficient to explain its variegated functions. In order to improve our understanding of the STAT3 transcriptional network we decided to develop a computational approach for the discovery of STAT3 functional binding sites. Upon generating a Positional Weight Matrix to define STAT3 binding sites, we applied a loglikelihood ratio scoring function and were able to assign affinity scores with very high specificity (93.5%) as measured by EMSA. STAT3 binding sites scoring above a stringent threshold have been identified genome-wide in Homo sapiens and Mus musculus and selected for phylogenetic conservation by genomic sequence alignment using eight vertebrate species. Validation was carried out on a subset of predicted sites within genes previously identified as STAT3-responsive by microarray analysis. The high percentage of sites able to bind STAT3 in vivo, as assessed by Chromatin Immunoprecipitation (ChIP) analysis, revealed the high predictive power of our method.