Dataset Information

BXD Mouse Liver Gene Expression

ABSTRACT: The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 41 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.

ORGANISM(S): Mus musculus

PROVIDER: GSE17522 | GEO | 2009/08/06

SECONDARY ACCESSION(S): PRJNA118801

REPOSITORIES: GEO

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Project description:Individual genetic variation affects gene expression and cell phenotype by acting within complex molecular circuits, but this relationship is still largely unknown. Here, we combine genomic and meso-scale profiling with novel computational methods to detect genetic variants that affect the responsiveness of gene expression to stimulus (responsiveness QTLs) and position them in circuit diagrams. We apply this approach to study individual variation in transcriptional responsiveness to three different pathogen components in the model response of primary bone marrow dendritic cells (DCs) from recombinant inbred mice strains. We show that reQTLs are common both in cis (affecting a single target gene) and in trans (pleiotropically affecting co-regulated gene modules) and are specific to some stimuli but not others. Leveraging the stimulus-specific activity of reQTLs and the differential responsiveness of their associated targets, we show how to position reQTLs within the context of known pathways in this regulatory circuit. For example, we find that a pleiotropic trans-acting genetic factor in chr1:129-165Mb affects the responsiveness of 35 anti-viral genes only during an anti-viral like stimulus. Using RNAi we uncover RGS16 the likely causal gene in this interval, and an activator of the antiviral response. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in other complex circuits in primary mammalian cells. The transcriptional response of DCs to pathogen components in the context of the mouse BXD recombinant inbred lines. We isolated DCs from individual age-synchronized female mice of different BXD and parental strains. We measured 30 global transcription profiles in resting and stimulated DCs from two parental strains (B6 and D2) and six BXD strains. We used bone marrow derived primary DCs from a panel of recombinant inbred (RI) BXD mice derived from a cross of the parental C57BL/6J (B6) and DBA/2J (D2) strains. We measured transcriptional responses in DCs from each of two parental strains and 6 BXD strains stimulated by three ligands of Toll-like receptors: LPS (TLR4 ligand), Pam3CSK ('PAM', TLR2 ligand) and poly IC (TLR3/RIG-I ligand).

Project description:We used 8 strains the BXD mouse genetic reference population, including parents C57BL/6J and DBA/2J, to study the proteome of the heart, whole brain, liver, quadriceps, and brown adipose tissue (BAT) across 8 different genotypes. For each sample, we examined the proteome of the mitochondria, as well as the whole cell fraction (including mitochondria). Later, we supplemented this study with an additional 19 strains of BXD mouse, with one strain overlapping, in the BAT for both whole cell and mitochondrial extract to examine tissue-specific hypotheses generated from the original set of 8 strains. All together, these data allowed us to (1) examine proteome expression of the mitochondria, (2) examine differences in proteome expression across tissue, (3) examine differences in proteome expression across strain, and (4) examine all three of the preceding factors simultaneously against one-another. This allowed us to uncover several proteins which are expressed in the mitochondria but are not reported as such in the literature, of which we validated a few by traditional staining techniques. Furthermore, we compare our proteome data against transcriptome data gathered in the same individual mice. We observe (1) that differences in expression of genes involved in oxidative phosphorylation are far more tissue-dependent at the protein level than the transcript level, and (2) and we observe that the phenotypic relationship between BAT and thermogenesis is far more evident at the protein expression data than it is from the transcript expression. Together, these data provide two conclusions: (1) next-gen mass spectrometry proteomics techniques can identify organelle localizations that were not evident from other techniques (perhaps particularly those proteins which are expressed both inside and outside the mitochondria); and (2) proteome and transcriptome data are complimentary, and proteome data may help us find and test new hypotheses even for physiological pathways which have been well studied at the genetic and transcriptomic levels.

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BXD Mouse Liver Gene Expression

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