Zhang, Junjie and Zhang, Yifeng and Gong, Huanfa and Cui, Leilei and Ma, Junwu and Chen, Congying and Ai, Huashui and Xiao, Shijun and Huang, Lusheng and Yang, Bin (2019) Landscape of Loci and Candidate Genes for Muscle Fatty Acid Composition in Pigs Revealed by Multiple Population Association Analysis. Frontiers in Genetics, 10. ISSN 1664-8021
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Abstract
Genome wide association analyses in diverse populations can identify complex trait loci that are specifically present in one population or shared across multiple populations, which help to better understand the genetic architecture of complex traits in a broader genetic context. In this study, we conducted genome-wide association studies and meta-analysis for 38 fatty acid composition traits with 12–19 million imputed genome sequence SNPs in 2446 pigs from six populations, encompassing White Duroc × Erhualian F2, Sutai, Duroc-Landrace-Yorkshire (DLY) three-way cross, Laiwu, Erhualian, and Bamaxiang pigs that were originally genotyped with 60 K or 1.4 million single nucleotide polymorphism (SNP) chips. The analyses uncovered 285 lead SNPs (P < 5 × 10-8), among which 78 locate more than 1 Mb to the lead chip SNPs were considered as novel, largely augmented the landscape of loci for porcine muscle fatty acid composition. Meta-analysis enhanced the association significance at loci near FADS2, ABCD2, ELOVL5, ELOVL6, ELOVL7, SCD, and THRSP genes, suggesting possible existence of population shared mutations underlying these loci. Further haplotype analysis at SCD loci identified a shared 3.7 kb haplotype in F2, Sutai and DLY pigs showing consistent effects of decreasing C18:0 contents in the three populations. In contrast, at FASN loci, we found an Erhualian specific haplotype explaining the population specific association signals in Erhualian pigs. This study refines our understanding on landscape of loci and candidate genes for fatty acid composition traits of pigs.
Item Type: | Article |
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Subjects: | STM Open Press > Medical Science |
Depositing User: | Unnamed user with email support@stmopenpress.com |
Date Deposited: | 31 Jan 2023 07:43 |
Last Modified: | 17 Jun 2024 06:34 |
URI: | http://journal.submissionpages.com/id/eprint/224 |