Dataset Information

Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons.

ABSTRACT: Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWASs), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using non-human primate models.

SUBMITTER: Lin W

PROVIDER: S-EPMC10943580 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons.

Lin Wenhe W Wall Jeffrey D JD Li Ge G Newman Deborah D Yang Yunqi Y Abney Mark M VandeBerg John L JL Olivier Michael M Gilad Yoav Y Cox Laura A LA

Cell genomics 20240301 3

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWASs), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic locali ...[more]

PMID: 38430910

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Project description:BackgroundDysregulation of microRNA (miRNA) expression has been implicated in molecular genetic events leading to the progression and development of atherosclerosis. We hypothesized that miRNA expression profiles differ between baboons with low and high serum low-density lipoprotein cholesterol (LDL-C) concentrations in response to diet, and that a subset of these miRNAs regulate genes relevant to dyslipidemia and risk of atherosclerosis.ResultsUsing Next Generation Illumina sequencing methods, we sequenced hepatic small RNA libraries from baboons differing in their LDL-C response to a high-cholesterol, high-fat (HCHF) challenge diet (low LDL-C, n?=?3; high LDL-C, n?=?3), resulting in 517 baboon miRNAs: 490 were identical to human miRNAs and 27 were novel. We compared miRNA expression profiles from liver biopsies collected before and after the challenge diet and observed that HCHF diet elicited expression of more miRNAs compared to baseline (chow) diet for both low and high LDL-C baboons. Eighteen miRNAs exhibited differential expression in response to HCHF diet in high LDL-C baboons compared to 10 miRNAs in low LDL-C baboons. We used TargetScan/Base tools to predict putative miRNA targets; miRNAs expressed in high LDL-C baboons had significantly more gene targets than miRNAs expressed in low LDL-C responders. Further, we identified miRNA isomers and other non-coding RNAs that were differentially expressed in response to the challenge diet in both high LDL-C and low LDL-C baboons.ConclusionsWe sequenced and annotated baboon liver miRNAs from low LDL-C and high LDL-C responders using high coverage Next Gen sequencing methods, determined expression changes in response to a HCHF diet challenge, and predicted target genes regulated by the differentially expressed miRNAs. The identified miRNAs will enrich the database for non-coding small RNAs including the extent of variation in these sequences. Further, we identified other small non-coding RNAs differentially expressed in response to diet. Our discovery of differentially expressed baboon miRNAs in response to a HCHF diet challenge that differ by LDL-C phenotype is a fundamental step in understating the role of non-coding RNAs in dyslipidemia.

Project description:This dataset contains proteomic data from mice with high or low weight gain in response to a high fat diet. Both host and microbial proteins are present. In the supplemental, there are also tables and supplementary files that can be used for replicating the bioinformatic analysis. Abstract: Consumption of refined high-fat, low-fiber diets promotes development of obesity and its associated consequences. While genetics play an important role in dictating susceptibility to such obesogenic diets, mice with nearly uniform genetics exhibit marked heterogeneity in their extent of obesity in response to such diets. This suggests non-genetic determinants play a role in diet-induced obesity. Hence, we sought to identify parameters that predict, and/or correlate with, development of obesity in response to an obesogenic diet. We assayed behavior, metabolic parameters, inflammatory markers/cytokines, microbiota composition, and the fecal metaproteome, in a cohort of mice (n=50) prior to, and the 8 weeks following, administration of an obesogenic high-fat low-fiber diet. Neither behavioral testing nor quantitation of inflammatory markers broadly predicted severity of diet-induced obesity. Although, the small subset of mice that exhibited basal elevations in serum IL-6 (n=5) were among the more obese mice in the cohort. While fecal microbiota composition changed markedly in response to the obesogenic diet, it lacked the ability to predict which mice were relative prone or resistant to obesity. In contrast, fecal metaproteome analysis revealed functional and taxonomic differences among the proteins associated with proneness to obesity. Targeted interrogation of microbiota composition data successfully validated the taxonomic differences seen in the metaproteome. While future work will be needed to determine the breadth of applicability of these associations to other cohorts of animals and humans, this study nonetheless highlights the potential power of gut microbial proteins to predict and perhaps impact development of obesity.

Dataset Information

Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons.

Publications

Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons.

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