Dataset Information

Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism.

ABSTRACT: Identifying the causal gene(s) that connects genetic variation to a phenotype is a challenging problem in genome-wide association studies (GWASs). Here, we develop a systematic approach that integrates mouse liver co-expression networks with human lipid GWAS data to identify regulators of cholesterol and lipid metabolism. Through our approach, we identified 48 genes showing replication in mice and associated with plasma lipid traits in humans and six genes on the X chromosome. Among these 54 genes, 25 have no previously identified role in lipid metabolism. Based on functional studies and integration with additional human lipid GWAS datasets, we pinpoint Sestrin1 as a causal gene associated with plasma cholesterol levels in humans. Our validation studies demonstrate that Sestrin1 influences plasma cholesterol in multiple mouse models and regulates cholesterol biosynthesis. Our results highlight the power of combining mouse and human datasets for prioritization of human lipid GWAS loci and discovery of lipid genes.

SUBMITTER: Li Z

PROVIDER: S-EPMC7184639 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism.

Li Zhonggang Z Votava James A JA Zajac Gregory J M GJM Nguyen Jenny N JN Leyva Jaimes Fernanda B FB Ly Sophia M SM Brinkman Jacqueline A JA De Giorgi Marco M Kaul Sushma S Green Cara L CL St Clair Samantha L SL Belisle Sabrina L SL Rios Julia M JM Nelson David W DW Sorci-Thomas Mary G MG Lagor William R WR Lamming Dudley W DW Eric Yen Chi-Liang CL Parks Brian W BW

Cell metabolism 20200319 4

Identifying the causal gene(s) that connects genetic variation to a phenotype is a challenging problem in genome-wide association studies (GWASs). Here, we develop a systematic approach that integrates mouse liver co-expression networks with human lipid GWAS data to identify regulators of cholesterol and lipid metabolism. Through our approach, we identified 48 genes showing replication in mice and associated with plasma lipid traits in humans and six genes on the X chromosome. Among these 54 gen ...[more]

PMID: 32197071

Similar Datasets

Project description:Broilers are a globally significant resource for food production, and their relative growth rate (RGR) has attracted increasing attention for improving broiler monitoring, feed management and feed conversion. The main objectives of this study were to identify key candidate genes affecting the RGR in white-feathered broiler by integrating genomic and transcriptomic datasets. This study reports a meta-analysis of genome-wide association studies (GWAS) using 3 purebred lines (n = 3,727) and 5,841,467 input SNPs to understand the genetic control of the RGR. A total of 101 associated SNPs located on 6 chromosomes were identified, 16 of which were common in the GWAS and meta cohorts. Fine mapping of a significant peak with 7 linked SNP (r2 > 0.94) located within the coding region of RAP2C revealed that chr4:3474286 (C > G) among these SNPs was a highly putative causal variant (PIP = 19%) and explained 2.26% of the RGR variation. Further analyses indicated that the surface expression level of the RAP2C gene in the blood, macrophage, lung tissue, and cecum tissue of commercial broiler breed (Ross) was higher than in the corresponding tissues of other egg-laying hens and local breeds. In addition, there was a significant difference in the expression of the RAP2C gene between the high (H, n = 5) and low (L, n = 4) RGR groups. A total of 301 differentially expressed genes (DEGs) related to the RGR in white-feathered broiler were identified by transcriptome differential analysis between the H and L populations, among which NFKBIA, CSF1R and TLR2A were important hub genes. Furthermore, the candidate genes identified based on GWASs, meta-analysis and DEGs analysis were significantly enriched for gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in the growth cone, integrated-mediated signaling pathway, and MAPK signaling pathway. Overall, the RAP2C, NFKBIA, CSF1R and TLR2A genes are considered the most important candidate genes influencing RGR trait in white-feathered broiler. These findings provide valuable insights into the complex system that regulates broiler growth.

Dataset Information

Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism.

Publications

Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets