Wu Ziyi, Dou Tengfei, Bai Liyao, Han Jinyi, Yang Feng, Wang Kejun, Han Xuelei, Qiao Ruimin, Li Xiu-Ling, Li Xin-Jian
College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, Henan, China.
Sanya Institute, Hainan Academy of Agricultural Science, Sanya, Hainan, China.
J Anim Breed Genet. 2024 Mar;141(2):124-137. doi: 10.1111/jbg.12830. Epub 2023 Oct 12.
Body composition traits are complex traits controlled by minor genes and, in hybrid populations, are impacted by additive and nonadditive effects. We aimed to identify candidate genes and increase the accuracy of genomic prediction of body composition traits in crossbred pigs by including dominance genetic effects. Genomic selection (GS) and genome-wide association studies were performed on seven body composition traits in 807 Yunong-black pigs using additive genomic models (AM) and additive-dominance genomic models (ADM) with an imputed high-density single nucleotide polymorphism (SNP) array and the Illumina Porcine SNP50 BeadChip. The results revealed that the additive heritabilities estimated for AM and ADM using the 50 K SNP data ranged from 0.20 to 0.34 and 0.11 to 0.30, respectively. However, the ranges of additive heritability for AM and ADM in the imputed data ranged from 0.20 to 0.36 and 0.12 to 0.30, respectively. The dominance variance accounted for 23% and 27% of the total variance for the 50 K and imputed data, respectively. The accuracy of genomic prediction improved by 5% on average for 50 K and imputed data when dominance effect were considered. Without the dominance effect, the accuracies for 50 K and imputed data were 0.35 and 0.38, respectively, and 0.41 and 0.43, respectively, upon considering it. A total of 12 significant SNP and 16 genomic regions were identified in the AM, and 14 significant SNP and 21 genomic regions were identified in the ADM for both the 50 K and imputed data. There were five overlapping SNP in the 50 K and imputed data. In the AM, a significant SNP (CNC10041568) was found in both body length and backfat thickness traits, which was in the PLAG1 gene strongly and significantly associated with body length and backfat thickness in pigs. Moreover, a significant SNP (CNC10031356) with a heterozygous dominant genotype was present in the ADM. Furthermore, several functionally related genes were associated with body composition traits, including MOS, RPS20, LYN, TGS1, TMEM68, XKR4, SEMA4D and ARNT2. These findings provide insights into molecular markers and GS breeding for the Yunong-black pigs.
体组成性状是由微效基因控制的复杂性状,在杂交群体中,受加性和非加性效应影响。我们旨在通过纳入显性遗传效应来鉴定候选基因,并提高杂交猪体组成性状基因组预测的准确性。利用插补的高密度单核苷酸多态性(SNP)阵列和Illumina猪SNP50芯片,采用加性基因组模型(AM)和加性-显性基因组模型(ADM),对807头豫农黑猪的7种体组成性状进行了基因组选择(GS)和全基因组关联研究。结果显示,使用50K SNP数据,AM和ADM估计的加性遗传力分别为0.20至0.34和0.11至0.30。然而,在插补数据中,AM和ADM的加性遗传力范围分别为0.20至0.36和0.12至0.30。显性方差分别占50K和插补数据总方差的23%和27%。考虑显性效应时,50K和插补数据的基因组预测准确性平均提高了5%。不考虑显性效应时,50K和插补数据的准确性分别为0.35和0.38,考虑显性效应后分别为0.41和0.43。在50K和插补数据的AM中,共鉴定出12个显著SNP和16个基因组区域,在ADM中鉴定出14个显著SNP和21个基因组区域。50K和插补数据中有5个重叠SNP。在AM中,在体长和背膘厚性状中均发现一个显著SNP(CNC10041568),其位于PLAG1基因中,与猪的体长和背膘厚密切相关。此外,在ADM中存在一个具有杂合显性基因型的显著SNP(CNC10031356)。此外,几个功能相关基因与体组成性状相关,包括MOS、RPS20、LYN、TGS1、TMEM68、XKR4、SEMA4D和ARNT2。这些发现为豫农黑猪的分子标记和GS育种提供了见解。