Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

被引:38
|
作者
Duan, Xinghai [1 ,2 ]
An, Bingxing [1 ]
Du, Lili [1 ]
Chang, Tianpeng [1 ]
Liang, Mang [1 ]
Yang, Bai-Gao [2 ]
Xu, Lingyang [1 ]
Zhang, Lupei [1 ]
Li, Junya [1 ]
Guangxin, E. [2 ]
Gao, Huijiang [1 ]
机构
[1] Chinese Acad Agr Sci, Inst Anim Sci, Beijing 100193, Peoples R China
[2] Southwest Univ, Coll Anim Sci & Technol, Chongqing 400715, Peoples R China
来源
ANIMALS | 2021年 / 11卷 / 01期
关键词
longitudinal data; growth curve model; single-trait GWAS; multi-trait GWAS; Chinese Simmental beef cattle;
D O I
10.3390/ani11010192
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Simple Summary Complex traits that require observations over multiple time points for the same individual are called longitudinal traits. Understanding the genetic architecture of beef cattle growth cannot be limited simply to a genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the longitudinal weight-age using a growth curve approach. We compared three nonlinear models that described the body weight data of Chinese Simmental beef cattle. The parameters of the suitable model were treated as phenotypes of single-trait GWAS and multi-trait GWAS. We identified 87 significant single nucleotide polymorphisms (SNPs) associated with body weight. Many candidate genes associated with body weight were identified which may be useful for exploring the full genetic architecture underlying growth and development traits in livestock. The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight-age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R-2 = 0.954). The parameters' mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.
引用
收藏
页码:1 / 15
页数:15
相关论文
共 50 条
  • [21] Genome-Wide Assessment of Runs of Homozygosity in Chinese Wagyu Beef Cattle
    Zhao, Guoyao
    Zhang, Tianliu
    Liu, Yuqiang
    Wang, Zezhao
    Xu, Lei
    Zhu, Bo
    Gao, Xue
    Zhang, Lupei
    Gao, Huijiang
    Liu, George E.
    Li, Junya
    Xu, Lingyang
    ANIMALS, 2020, 10 (08): : 1 - 13
  • [22] Genome-Wide association study and possibilities for genomic selection of Simmental cattle breed in Russia
    Ignatieva, Larisa P.
    Sermyagin, Alexander A.
    Nikitin, Sergey
    Conte, Alexander
    Naryshkina, Elena
    Zinovieva, Natalia A.
    JOURNAL OF ANIMAL SCIENCE, 2021, 99 : 246 - 246
  • [23] Genome-Wide Association Study Reveals the PLAG1 Gene for Knuckle, Biceps and Shank Weight in Simmental Beef Cattle
    Song, Yuxin
    Xu, Lingyang
    Chen, Yan
    Zhang, Lupei
    Gao, Huijiang
    Zhu, Bo
    Niu, Hong
    Zhang, Wengang
    Xia, Jiangwei
    Gao, Xue
    Li, Junya
    PLOS ONE, 2016, 11 (12):
  • [24] Genome-wide association analysis of body conformation traits in Chinese Holstein Cattle
    Li, Shuangshuang
    Ge, Fei
    Chen, Lili
    Liu, Yuxin
    Chen, Yan
    Ma, Yi
    BMC GENOMICS, 2024, 25 (01):
  • [25] Genome-wide association analyses for carcass quality in crossbred beef cattle
    Lu, Duc
    Sargolzaei, Mehdi
    Kelly, Matthew
    Vander Voort, Gordon
    Wang, Zhiquan
    Mandell, Ira
    Moore, Stephen
    Plastow, Graham
    Miller, Stephen Paul
    BMC GENETICS, 2013, 14
  • [26] Genome-wide association analyses for carcass quality in crossbred beef cattle
    Duc Lu
    Mehdi Sargolzaei
    Matthew Kelly
    Gordon Vander Voort
    Zhiquan Wang
    Ira Mandell
    Stephen Moore
    Graham Plastow
    Stephen Paul Miller
    BMC Genetics, 14
  • [27] Genomic prediction and genome-wide association analysis of female longevity in a composite beef cattle breed
    Hay, E. Hamidi
    Roberts, A.
    JOURNAL OF ANIMAL SCIENCE, 2017, 95 (04) : 1467 - 1471
  • [28] Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle
    Christopher M. Seabury
    David L. Oldeschulte
    Mahdi Saatchi
    Jonathan E. Beever
    Jared E. Decker
    Yvette A. Halley
    Eric K. Bhattarai
    Maral Molaei
    Harvey C. Freetly
    Stephanie L. Hansen
    Helen Yampara-Iquise
    Kristen A. Johnson
    Monty S. Kerley
    JaeWoo Kim
    Daniel D. Loy
    Elisa Marques
    Holly L. Neibergs
    Robert D. Schnabel
    Daniel W. Shike
    Matthew L. Spangler
    Robert L. Weaber
    Dorian J. Garrick
    Jeremy F. Taylor
    BMC Genomics, 18
  • [29] Identifying novel genes for carcass traits by testing G x E interaction through genome-wide meta-analysis in Chinese Simmental beef cattle
    Wang, Xiaoqiao
    Miao, Jian
    Xia, Jiangwei
    Chang, Tianpeng
    Guangxin, E.
    Bao, Jinshan
    Jin, Shengyun
    Xu, Lingyang
    Zhang, Lupei
    Zhu, Bo
    Gao, Xue
    Chen, Yan
    Li, Junya
    Gao, Huijiang
    LIVESTOCK SCIENCE, 2018, 212 : 75 - 82
  • [30] Genome-wide association studies of female reproduction in tropically adapted beef cattle
    Hawken, R. J.
    Zhang, Y. D.
    Fortes, M. R. S.
    Collis, E.
    Barris, W. C.
    Corbet, N. J.
    Williams, P. J.
    Fordyce, G.
    Holroyd, R. G.
    Walkley, J. R. W.
    Barendse, W.
    Johnston, D. J.
    Prayaga, K. C.
    Tier, B.
    Reverter, A.
    Lehnert, S. A.
    JOURNAL OF ANIMAL SCIENCE, 2012, 90 (05) : 1398 - 1410