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Genome‐wide association study and genomic prediction for intramuscular fat content in Suhuai pigs using imputed whole‐genome sequencing data.

Authors :
Wang, Binbin
Li, Pinghua
Hou, Liming
Zhou, Wuduo
Tao, Wei
Liu, Chenxi
Liu, Kaiyue
Niu, Peipei
Zhang, Zongping
Li, Qiang
Su, Guosheng
Huang, Ruihua
Source :
Evolutionary Applications; Dec2022, Vol. 15 Issue 12, p2054-2066, 13p
Publication Year :
2022

Abstract

Integrating the single‐nucleotide polymorphisms (SNPs) significantly affecting target traits from imputed whole‐genome sequencing (iWGS) data into the genomic prediction (GP) model is an economic, efficient, and feasible strategy to improve prediction accuracy. The objective was to dissect the genetic architecture of intramuscular fat content (IFC) by genome wide association studies (GWAS) and to investigate the accuracy of GP based on pedigree‐based BLUP (PBLUP) model, genomic best linear unbiased prediction (GBLUP) models and Bayesian mixture (BayesMix) models under different strategies. A total of 482 Suhuai pigs were genotyped using an 80 K SNP chip. Furthermore, 30 key samples were selected for resequencing and were used as a reference panel to impute the 80 K chip data to the WGS dataset. The 80 K data and iWGS data were used to perform GWAS and test GP accuracies under different scenarios. GWAS results revealed that there were four major regions affecting IFC. Two important functional candidate genes were found in the two most significant regions, including protein kinase C epsilon (PRKCE) and myosin light chain 2 (MYL2). The results of the predictions showed that the PBLUP model had the lowest reliability (0.096 ± 0.032). The reliability (0.229 ± 0.035) was improved by replacing pedigree information with 80 K chip data. Compared with using 80 K SNPs alone, pruning iWGS SNPs with the R‐squared cutoff of linkage disequilibrium (0.55) led to a slight improvement (0.006), adding significant iWGS SNPs led to an improvement of reliability by 0.050 when using a one‐component GBLUP, a further increase of 0.033 when using a two‐component GBLUP model. For BayesMix models, compared with using 80 K SNPs alone, adding additional significant iWGS SNPs into one‐ or two‐component BayesMix models led to improvements of reliabilities for IFC by 0.040 and 0.089, respectively. Our results may facilitate further identification of causal genes for IFC and may be beneficial for the improvement of IFC in pig breeding programs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17524563
Volume :
15
Issue :
12
Database :
Complementary Index
Journal :
Evolutionary Applications
Publication Type :
Academic Journal
Accession number :
160812659
Full Text :
https://doi.org/10.1111/eva.13496