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Updated: Sep 11, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Comprehensive Multi-omics Analysis of Regulatory Variants for Body Weight in Cattle
Qunhao Niu1, Jiayuan Wu1, Tianyi Wu1
1State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
Abstract:
Body weight is a polygenic trait with intricate inheritance patterns. Functional genomics enriched with multi-layer annotations offers essential resources for exploring the genetic architecture of complex traits. In this study, we conducted an extensive characterization of regulatory variants associated with body weight-related traits in cattle using multi-omics analysis. First, we identified seven candidate genes by integrating selective sweep analysis and multiple genome-wide association study (GWAS) strategies using imputed whole-genome sequencing data from a population of 1577 individuals. Subsequently, we uncovered 3340 eGenes (genes whose expression levels are associated with genetic variants) across 227 muscle samples. Transcriptome-wide association studies (TWASs) further revealed a total of 532 distinct candidate genes associated with body weight-related traits. Colocalization analyses unveiled 44 genes shared between expression quantitative trait loci (eQTLs) and GWAS signals. Moreover, a comprehensive analysis by integrating GWAS, selective sweep, eQTL, TWAS, epigenomic profiling, and molecular validation highlighted a positively selected genomic region on Bos taurus autosome 6 (BTA6). This locus harbors pleiotropic genes (LAP3, MED28, and NCAPG) and a prioritized functional variant involved in the complex regulation of body weight. Additionally, convergent evolution analysis and phenome-wide association studies underscored the conservation of this locus across species. Our study provides a comprehensive understanding of the genetic regulation of body weight through multi-omics analysis in cattle. Our findings contribute to unraveling the genetic mechanisms governing weight-related traits and shed valuable light on the genetic improvement of farm animals.
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