使用50对身体组成性状的加性和显性效应进行基因组预测和全基因组关联研究 K和估算的云南黑猪高密度SNP基因型。

IF 1.9 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE Journal of Animal Breeding and Genetics Pub Date : 2023-10-12 DOI:10.1111/jbg.12830
Ziyi Wu, Tengfei Dou, Liyao Bai, Jinyi Han, Feng Yang, Kejun Wang, Xuelei Han, Ruimin Qiao, Xiu-Ling Li, Xin-Jian Li
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引用次数: 0

摘要

身体组成性状是由小基因控制的复杂性状,在杂交群体中,受到加性和非加性效应的影响。我们的目的是通过包括显性遗传效应来识别候选基因,并提高杂交猪身体组成性状基因组预测的准确性。使用具有高密度单核苷酸多态性(SNP)阵列的加性基因组模型(AM)和加性显性基因组模型(ADM)和Illumina Porcine SNP50珠芯片,对807头云南黑猪的7个身体组成性状进行了基因组选择(GS)和全基因组关联研究。结果表明,使用50 K SNP数据的范围分别为0.20至0.34和0.11至0.30。然而,估算数据中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。优势方差分别占50 K和估算数据。50年来,基因组预测的准确性平均提高了5% K和考虑显性效应时的估算数据。在没有优势效应的情况下,50 K和估算数据分别为0.35和0.38,0.41和0.43 K和估算数据。50个SNP中有5个重叠 K和估算数据。在AM中,在体长和背厚性状中都发现了一个显著的SNP(CNC10041568),该SNP在PLAG1基因中与猪的体长和背面厚度强烈且显著相关。此外,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身体组成性状相关,包括MOS、RPS20、LYN、TGS1、TMEM68、XKR4、SEMA4D和ARNT2。这些发现为云南黑猪的分子标记和GS育种提供了见解。
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Genomic prediction and genome-wide association studies for additive and dominance effects for body composition traits using 50 K and imputed high-density SNP genotypes in Yunong-black pigs

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.

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来源期刊
Journal of Animal Breeding and Genetics
Journal of Animal Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
5.20
自引率
3.80%
发文量
58
审稿时长
12-24 weeks
期刊介绍: The Journal of Animal Breeding and Genetics publishes original articles by international scientists on genomic selection, and any other topic related to breeding programmes, selection, quantitative genetic, genomics, diversity and evolution of domestic animals. Researchers, teachers, and the animal breeding industry will find the reports of interest. Book reviews appear in many issues.
期刊最新文献
Genomic Diversity of U.S. Katahdin Hair Sheep. The Effect of Preselection on the Level of Bias and Accuracy in a Broiler Breeder Population, a Simulation Study. Genomic Prediction Using Imputed Whole-Genome Sequence Data in Australian Angus Cattle. Genetic Characterisation of Feeding Patterns in Lactating Holstein Cows and Their Association With Feed Efficiency Traits. Methods of Calculating Prediction Error Variance and Prediction Accuracy for Restricted Best Linear Unbiased Prediction of Breeding Values.
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