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: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 M-bM-^@M-^Xhotspots,M-bM-^@M-^Y 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 M-bM-^@M-^XfertileM-bM-^@M-^Y 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. Gene expression was measured in whole testis in males aged 70(M-BM-15) days. Samples include 294 WSB/EiJ x PWD/PhJ F2s, 11 PWD/PhJ x WSB/EiJ F2s, 8 WSB/EiJ, 8 PWD/PhJ, 6 PWD/PhJ x WSB/EiJ F1s and 4 WSB/EiJ x PWD/PhJ F1s.
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes.
Project description:Natural variation in protein expression is common in all organisms and contribute to phenotypic differences among individuals. While variation in gene expression at the transcript level has been extensively investigated, the genetic mechanisms underlying variation in protein expression have lagged considerably behind. Here we investigate genetic architecture of protein expression by profiling a deep mouse brain proteome of two inbred strains, C57BL/6J (B6) and DBA/2J (D2), and their reciprocal F1 hybrids using two-dimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) technology. By comparing protein expression levels in the four mouse strains, we observed 329 statistically significant differentially expressed proteins between the two parental strains and identified four common inheritance patterns, including dominant, additive, over- and under-dominant expression. We further applied the proteogenomic approach to detect variant peptides and define protein allele-specific expression (pASE).