Detection of Genomic Imprinting for Carcass Traits in Cattle Using Imputed High-Density Genotype Data

被引:3
|
作者
Kenny, David [1 ,2 ]
Sleator, Roy D. [2 ]
Murphy, Craig P. [2 ]
Evans, Ross D. [3 ]
Berry, Donagh P. [1 ]
机构
[1] Anim & Grassland Res & Innovat Ctr, Teagasc,Moorepk, Cork, Ireland
[2] Munster Technol Univ, Dept Biol Sci, Bishopstown Campus, Cork, Ireland
[3] Irish Cattle Breeding Federat, Highfield House, Bandon, Cork, Ireland
基金
爱尔兰科学基金会;
关键词
genomic imprinting; carcass traits; epigenetics; association analysis; non-additive; GENETIC-PARAMETERS; ASSOCIATION; GROWTH; DAIRY;
D O I
10.3389/fgene.2022.951087
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Genomic imprinting is an epigenetic phenomenon defined as the silencing of an allele, at least partially, at a given locus based on the sex of the transmitting parent. The objective of the present study was to detect the presence of SNP-phenotype imprinting associations for carcass weight (CW), carcass conformation (CC) and carcass fat (CF) in cattle. The data used comprised carcass data, along with imputed, high-density genotype data on 618,837 single nucleotide polymorphisms (SNPs) from 23,687 cattle; all animal genotypes were phased with respect to parent of origin. Based on the phased genotypes and a series of single-locus linear models, 24, 339, and 316 SNPs demonstrated imprinting associations with CW, CC, and CF, respectively. Regardless of the trait in question, no known imprinted gene was located within 0.5 Mb of the SNPs demonstrating imprinting associations in the present study. Since all imprinting associations detected herein were at novel loci, further investigation of these regions may be warranted. Nonetheless, knowledge of these associations might be useful for improving the accuracy of genomic evaluations for these traits, as well as mate allocations systems to exploit the effects of genomic imprinting.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Genomic Prediction Using Imputed Whole-Genome Sequence Data in Australian Angus Cattle
    Kamprasert, Nantapong
    Aliloo, Hassan
    van Der Werf, Julius H. J.
    Duff, Christian J.
    Clark, Samuel A.
    JOURNAL OF ANIMAL BREEDING AND GENETICS, 2024,
  • [32] Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes
    Piccoli, Mario L.
    Brito, Luiz F.
    Braccini, Jose
    Cardoso, Fernando F.
    Sargolzaei, Mehdi
    Schenkel, Flavio S.
    BMC GENETICS, 2017, 18
  • [33] Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes
    Mario L. Piccoli
    Luiz F. Brito
    José Braccini
    Fernando F. Cardoso
    Mehdi Sargolzaei
    Flávio S. Schenkel
    BMC Genetics, 18
  • [34] Identification of linked regions using high-density SNP genotype data in linkage analysis
    Lin, Guohui
    Wang, Zhanyong
    Wang, Lusheng
    Lau, Yu-Lung
    Yang, Wanling
    BIOINFORMATICS, 2008, 24 (01) : 86 - 93
  • [35] Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle
    Li, Hongwei
    Wang, Zezhao
    Xu, Lei
    Li, Qian
    Gao, Han
    Ma, Haoran
    Cai, Wentao
    Chen, Yan
    Gao, Xue
    Zhang, Lupei
    Gao, Huijiang
    Zhu, Bo
    Xu, Lingyang
    Li, Junya
    EVOLUTIONARY APPLICATIONS, 2022, 15 (12): : 2028 - 2042
  • [36] Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers
    Gunia, M.
    Saintilan, R.
    Venot, E.
    Hoze, C.
    Fouilloux, M. N.
    Phocas, F.
    JOURNAL OF ANIMAL SCIENCE, 2014, 92 (08) : 3258 - 3269
  • [37] Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
    Martinez-Castillero, Maria
    Then, Carlos
    Altarriba, Juan
    Srihi, Houssemeddine
    Lopez-Carbonell, David
    Diaz, Clara
    Martinez, Paulino
    Hermida, Miguel
    Varona, Luis
    ANIMALS, 2021, 11 (06):
  • [38] Implications of using genomic prediction within a high-density SNP dataset to predict DUS traits in barley
    Huw Jones
    Ian Mackay
    Theoretical and Applied Genetics, 2015, 128 : 2461 - 2470
  • [39] Implications of using genomic prediction within a high-density SNP dataset to predict DUS traits in barley
    Jones, Huw
    Mackay, Ian
    THEORETICAL AND APPLIED GENETICS, 2015, 128 (12) : 2461 - 2470
  • [40] Genomic prediction for feed efficiency traits based on 50K and imputed high density SNP genotypes in multiple breed populations of Canadian beef cattle
    Li, C.
    Chen, L.
    Vinsky, M.
    Crowley, J.
    Miller, S. P.
    Plastow, G.
    Basarab, J.
    Stothard, P.
    JOURNAL OF ANIMAL SCIENCE, 2016, 94 : 154 - 155