数量性状位点
全基因组关联研究
生物
优先次序
特质
遗传建筑学
遗传学
注释
计算生物学
表达数量性状基因座
进化生物学
单核苷酸多态性
基因型
计算机科学
基因
管理科学
经济
程序设计语言
作者
Yuwei Gou,Yunhan Jing,Yifei Wang,Xingyu Li,Jing Yang,Kai Wang,Hengdong He,Yuansheng Yang,Young Tang,Chen Wang,Jun Xu,Fan Yang,Mingzhou Li,Qianzi Tang
标识
DOI:10.1016/j.jbc.2025.108267
摘要
Genome-wide association study (GWAS) and quantitative trait locus (QTL) mapping methods provide valuable insights and opportunities for identifying functional gene underlying phenotype formation. However, the majority of GWAS risk loci and QTLs located in non-coding regions, posing significant challenges in pinpointing the protein-coding genes associated with specific traits. Moreover, growing evidence suggests not all GWAS risk loci and QTLs are functional, emphasizing the critical need for prioritizing causal sites-a task of paramount importance for biologists. The accumulation of publicly available multi-omics data provides an unprecedented opportunity to annotate and prioritize GWAS risk loci and QTLs.Therefore, we developed a comprehensive multi-omics database encompassing four major agricultural species-pig, sheep, cattle, and chicken. This database integrates publicly accessible datasets, including 140 GWAS studies (covering 471 traits), 2,625 QTL datasets (spanning 1,235 traits), 86 Hi-C datasets (from 8 cell/tissue types), 95 epigenomic datasets (from 4 cell/tissue types), and 769 transcription factor motifs. The database aims to link GWAS/QTL loci located in the non-coding regions to the target genes they regulate, and prioritize functional and causal regulatory elements. Ultimately, it provides a valuable resource and potential validation targets for elucidating the genes and molecular pathways underlying economically important traits in agricultural animals.
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