Project description:By comparing mouse fibroblasts from two parental strains (Bl6 and Spretus) with fibroblasts from their first generation offspring (F1) we can detect allele specific expression of proteins. The Bl6 and Spretus lines are evolutionary distant and harbour many SNPs in their genomes which when synonomous we can detect on the protein level using mass spectrometry. By mixing SILAC labeled Bl6, Spretus and F1 offspring cell lines we can detect peptides shared between all three cell lines and also SNP peptides that are only expressed in the F1 cells and either Bl6 or Spretus cells. By comparing the abundance of the shared peptides and the SNP peptides we can quantify how much of a protein in the F1 cells that comes from the paternal or maternal allele. This data were then further compared to polysome profiling data. Azidohomoalanine labeling was used to enrich newly synthesized proteins from the three cell lines.
Project description:This set of data was used to identify cis-regulatory SNPs by measuring allelic gene expression. From analyzing cis-regulatory SNPs from different tissues, cis-regulatory SNPs common across tissues or the cell-type specific were cataloged.
Project description:The contribution to genetic diversity of genomic segmental copy number variations (CNVs) is less well understood than that of single-nucleotide polymorphisms (SNPs). While less frequent than SNPs, CNVs have greater potential to affect phenotype. In this study, we have performed the most comprehensive survey to date of CNVs in mice, analyzing the genomes of 42 Mouse Phenome Consortium priority strains. This microarray comparative genomic hybridization (CGH)-based analysis has identified 2094 putative CNVs, with an average of 10 Mb of DNA in 51 CNVs when individual mouse strains were compared to the reference strain C57BL/6J. This amount of variation results in gene content that can differ by hundreds of genes between strains. These genes include members of large families such as the major histocompatibility and pheromone receptor genes, but there are also many singleton genes including genes with expected phenotypic consequences from their deletion or amplification. Using a whole-genome association analysis, we demonstrate that complex multigenic phenotypes, such as food intake, can be associated with specific copy number changes. Keywords: comparative genomic hybridization
Project description:The specific genes influencing the quantitative variation in macronutrient preference and food intake are virtually unknown. We refined a previously identified mouse chromosome 17 (MMU17) region harboring quantitative trait loci (QTL) with large effects on preferential macronutrient intake-carbohydrate (Mnic1), total kilcalories (Kcal2), and total food volume (Tfv1) using interval-specific congenic strains. These loci were isolated in the [C57BL/6J.CAST/EiJ-17.1-(D17Mit19-D17Mit50); B6.CAST-17.1] strain, developed by introgressing a ~40.1 Mb CAST MMU17 region into recipient B6 genome. In a diet selection paradigm (carbohydrate/protein vs. fat/protein), these B6.CAST-17.1 sub-congenic mice eat 30% more calories from the carbohydrate-rich diet, ~10% more total calories, and ~9% more total food volume per body weight. In the current study, this carbohydrate-preferring B6.CAST-17.1 subcongenic strain was crossed with the fat-preferring inbred B6 strain to generate a subcongenic-derived F2 mapping population; genotypes were determined using a high-density, custom SNP panel. The main outcome of this study is that genetic linkage analysis greatly reduced the 95% confidence interval (CI) for Mnic1 (encompassing Kcal2 and Tfv1) from 40.1 to 29.5 Mb and more precisely established the QTL boundaries. Specifically, the genetic architecture for Mnic1 (preferential carbohydrate intake) does not follow the same pattern as that for co-localized Kcal2/Tfv1 (total kcal and food volume, respectively), suggesting the presence of separate quantitative trait genes for these food intake traits. No genetic linkage for self-selected fat intake was detected, underscoring the carbohydrate-specific effects of this MMU17 locus. The Mnic1/Kcal2/Tfv1 QTL was further de-limited to a ~19.1 Mb interval, based on the absence of macronutrient diet selection phenotypes in subcongenic HQ17IIa mice that possess CAST MMU17 donor segment on a C57BL/6Jhg/hg background. A second key finding is the separation of two energy balance QTLs: Mnic1/Kcal2/Tfv1 for food intake and a newly discovered locus regulating short term body weight gain. The genes Decr2, Ppard and Agapt1 in the critical QTL interval were identified and prioritized using a combination of genome sequence analysis, and tag-based transcriptome sequencing to measure hypothalamic gene expression in non-recombinant F2 controls, possessing cast/cast and b6/b6 genotypes across the sub-congenic segment.