Shen, Yu and Wang, Haiyan and Xie, Jiahao and Wang, Zixuan and Ma, Yunlong (2021) Trait-specific Selection Signature Detection Reveals Novel Loci of Meat Quality in Large White Pigs. Frontiers in Genetics, 12. ISSN 1664-8021
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Abstract
In past decades, meat quality traits have been shaped by human-driven selection in the process of genetic improvement programs. Exploring the potential genetic basis of artificial selection and mapping functional candidate genes for economic traits are of great significance in genetic improvement of pigs. In this study, we focus on investigating the genetic basis of five meat quality traits, including intramuscular fat content (IMF), drip loss, water binding capacity, pH at 45 min (pH45min), and ultimate pH (pH24h). Through making phenotypic gradient differential population pairs, Wright’s fixation index (FST) and the cross-population extended haplotype homozogysity (XPEHH) were applied to detect selection signatures for these five traits. Finally, a total of 427 and 307 trait-specific selection signatures were revealed by FST and XPEHH, respectively. Further bioinformatics analysis indicates that some genes, such as USF1, NDUFS2, PIGM, IGSF8, CASQ1, and ACBD6, overlapping with the trait-specific selection signatures are responsible for the phenotypes including fat metabolism and muscle development. Among them, a series of promising trait-specific selection signatures that were detected in the high IMF subpopulation are located in the region of 93544042-95179724bp on SSC4, and the genes harboring in this region are all related to lipids and muscle development. Overall, these candidate genes of meat quality traits identified in this analysis may provide some fundamental information for further exploring the genetic basis of this complex trait.
Item Type: | Article |
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Subjects: | Bengali Archive > Medical Science |
Depositing User: | Unnamed user with email support@bengaliarchive.com |
Date Deposited: | 06 Feb 2023 07:31 |
Last Modified: | 29 Jun 2024 12:36 |
URI: | http://science.archiveopenbook.com/id/eprint/93 |