Dataset Information

Multiomic Profiling of the Liver Across Diets and Age in a Diverse Mouse Population

ABSTRACT: We profiled the liver transcriptome, proteome, and metabolome from 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wildtype and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into segregating edges. Candidate hits were cross-examined in an independent Diversity Outbred mouse liver dataset segregating for similar diets, with ~80-90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.

ORGANISM(S): Mus musculus

PROVIDER: GSE310411 | GEO | 2025/11/22

REPOSITORIES: GEO

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Project description:Obesity is in large part a brain disease that is caused by genetics, the environment (e.g., diet) and their interactions. Identifying genes in the brain that interact with diet to influence obesity is not possible in humans. The goal of this study was to use outbred heterogeneous stock (HS) rats to identify genetic loci for diet-induced obesity followed by RNAseq in the ventromedial hypothalamus (VMH) to identify candidate causal genes. We measured multiple metabolic traits (including fat and lean mass, fasting glucose, insulin, and lipids, glucose tolerance, food intake and activity levels) after long-term consumption of a low-fat (LFD) or high-fat diet (HFD) in 2000 HS rats, split equally be sex and diet. Rats were genotyped using low-coverage whole genome sequencing. RNAseq was run in the VMH of a sub-set of 400 HS rats split equally by sex and diet. We used linear mixed models to detect physiological and expression quantitative trait loci (pQTLs and eQTLs, respectively) in the full dataset and separately by diet and sex. Genes with cis-eQTLs that overlapped pQTLs were assessed as candidate causal genes through mediation analysis. We also identified VMH genes differentially expressed by diet in both sexes, followed by pathway analysis. We identified 47 pQTLs where seven mapped multiple traits, 11 were diet-specific and 13 were sex-specific. We identified nine candidate causal genes, including Pcare, Rbks, Mpv17 and Gpn1 within a pleiotropic pQTL for multiple adiposity traits on rat chr. 6 and Tnsfs9 within a pQTL for fat pad weight on rat chr. 9. We also identified Ccdc77 as a candidate gene within a LFD-specific pQTL for activity levels and Rtel1 and Polr3k within a male-specific pQTL for fatty liver. Genes involved in extracellular matrix and inflammation were dysregulated by diet, particularly in females, while males on HFD showed upregulation of several addiction pathways. This work demonstrates the importance of accounting for diet and sex in genetic studies for obesity and identifies novel candidate genes as neural regulators of diet-induced obesity and related traits.

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Multiomic Profiling of the Liver Across Diets and Age in a Diverse Mouse Population

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