A Large-Scale Genome-Wide Association Study in US Holstein Cattle

被引:158
|
作者
Jiang, Jicai [1 ]
Ma, Li [1 ]
Prakapenka, Dzianis [2 ]
VanRaden, Paul M. [3 ]
Cole, John B. [3 ]
Da, Yang [2 ]
机构
[1] Univ Maryland, Dept Anim & Avian Sci, College Pk, MD 20742 USA
[2] Univ Minnesota, Dept Anim Sci, St Paul, MN 55108 USA
[3] USDA ARS, Anim Genom & Improvement Lab, Beltsville, MD USA
基金
美国食品与农业研究所;
关键词
GWAS; dairy cattle; milk production; fertility; somatic cell score; AFFECTING MILK-YIELD; DAIRY-CATTLE; MISSENSE MUTATION; DGAT1; GENE; IDENTIFICATION; TRAITS; MODEL; QTL; VARIANTS; SAMPLE;
D O I
10.3389/fgene.2019.00412
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Genome-wide association study (GWAS) is a powerful approach to identify genomic regions and genetic variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. We conducted a large-scale GWAS using 294,079 first-lactation Holstein cows and identified new additive and dominance effects on five production traits, three fertility traits, and somatic cell score. Four chromosomes had the most significant SNP effects on the five production traits, a Chr14 region containing DGAT1 mostly had positive effects on fat yield and negative effects on milk and protein yields, the 88.07-89.60 Mb region of Chr06 with SLC4A4, GC, NPFFR2, and ADAMTS3 for milk and protein yields, the 30.03-36.67 Mb region of Chr20 with C6 and GHR for milk yield, and the 88.19-88.88 Mb region with ABCC9 as well as the 91.13-94.62 Mb region of Chr05 with PLEKHA5, MGST1 , SLC15A5, and EPS8 for fat yield. For fertility traits, the SNP in GC of Chr06, and the SNPs in the 65.02-69.43 Mb region of Chr01 with COX17, ILDR1, and KALRN had the most significant effects for daughter pregnancy rate and cow conception rate, whereas SNPs in AFF1 of Chr06, the 47.54-52.79 Mb region of Chr07, TSPAN4 of Chr29, and NPAS1 of Chr18 had the most significant effects for heifer conception rate. For somatic cell score, GC of Chr06 and PRLR of Chr20 had the most significant effects. A small number of dominance effects were detected for the production traits with far lower statistical significance than the additive effects and for fertility traits with similar statistical significance as the additive effects. Analysis of allelic effects revealed the presence of uni-allelic, asymmetric, and symmetric SNP effects and found the previously reported DGAT1 antagonism was an extreme antagonistic pleiotropy between fat yield and milk and protein yields among all SNPs in this study.
引用
收藏
页数:21
相关论文
共 50 条
  • [21] Large-scale genome-wide association study of coronary artery disease in genetically diverse populations
    Tcheandjieu, Catherine
    Zhu, Xiang
    Hilliard, Austin T.
    Clarke, Shoa L.
    Napolioni, Valerio
    Ma, Shining
    Lee, Kyung Min
    Fang, Huaying
    Chen, Fei
    Lu, Yingchang
    Tsao, Noah L.
    Raghavan, Sridharan
    Koyama, Satoshi
    Gorman, Bryan R.
    Vujkovic, Marijana
    Klarin, Derek
    Levin, Michael G.
    Sinnott-Armstrong, Nasa
    Wojcik, Genevieve L.
    Plomondon, Mary E.
    Maddox, Thomas M.
    Waldo, Stephen W.
    Bick, Alexander G.
    Pyarajan, Saiju
    Huang, Jie
    Song, Rebecca
    Ho, Yuk-Lam
    Buyske, Steven
    Kooperberg, Charles
    Haessler, Jeffrey
    Loos, Ruth J. F.
    Do, Ron
    Verbanck, Marie
    Chaudhary, Kumardeep
    North, Kari E.
    Avery, Christy L.
    Graff, Mariaelisa
    Haiman, Christopher A.
    Le Marchand, Loic
    Wilkens, Lynne R.
    Bis, Joshua C.
    Leonard, Hampton
    Shen, Botong
    Lange, Leslie A.
    Giri, Ayush
    Dikilitas, Ozan
    Kullo, Iftikhar J.
    Stanaway, Ian B.
    Jarvik, Gail P.
    Gordon, Adam S.
    NATURE MEDICINE, 2022, 28 (08) : 1679 - +
  • [22] Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
    de Vries, Paul S.
    Sabater-Lleal, Maria
    Chasman, Daniel I.
    Trompet, Stella
    Ahluwalia, Tarunveer S.
    Teumer, Alexander
    Kleber, Marcus E.
    Chen, Ming-Huei
    Wang, Jie Jin
    Attia, John R.
    Marioni, Riccardo E.
    Steri, Maristella
    Weng, Lu-Chen
    Pool, Rene
    Grossmann, Vera
    Brody, Jennifer A.
    Venturini, Cristina
    Tanaka, Toshiko
    Rose, Lynda M.
    Oldmeadow, Christopher
    Mazur, Johanna
    Basu, Saonli
    Franberg, Mattias
    Yang, Qiong
    Ligthart, Symen
    Hottenga, Jouke J.
    Rumley, Ann
    Mulas, Antonella
    de Craen, Anton J. M.
    Grotevendt, Anne
    Taylor, Kent D.
    Delgado, Graciela E.
    Kifley, Annette
    Lopez, Lorna M.
    Berentzen, Tina L.
    Mangino, Massimo
    Bandinelli, Stefania
    Morrison, Alanna C.
    Hamsten, Anders
    Tofler, Geoffrey
    de Maat, Moniek P. M.
    Draisma, Harmen H. M.
    Lowe, Gordon D.
    Zoledziewska, Magdalena
    Sattar, Naveed
    Lackner, Karl J.
    Voelker, Uwe
    McKnight, Barbara
    Huang, Jie
    Holliday, Elizabeth G.
    PLOS ONE, 2017, 12 (01):
  • [23] Large-scale genome-wide association study of coronary artery disease in genetically diverse populations
    Catherine Tcheandjieu
    Xiang Zhu
    Austin T. Hilliard
    Shoa L. Clarke
    Valerio Napolioni
    Shining Ma
    Kyung Min Lee
    Huaying Fang
    Fei Chen
    Yingchang Lu
    Noah L. Tsao
    Sridharan Raghavan
    Satoshi Koyama
    Bryan R. Gorman
    Marijana Vujkovic
    Derek Klarin
    Michael G. Levin
    Nasa Sinnott-Armstrong
    Genevieve L. Wojcik
    Mary E. Plomondon
    Thomas M. Maddox
    Stephen W. Waldo
    Alexander G. Bick
    Saiju Pyarajan
    Jie Huang
    Rebecca Song
    Yuk-Lam Ho
    Steven Buyske
    Charles Kooperberg
    Jeffrey Haessler
    Ruth J. F. Loos
    Ron Do
    Marie Verbanck
    Kumardeep Chaudhary
    Kari E. North
    Christy L. Avery
    Mariaelisa Graff
    Christopher A. Haiman
    Loïc Le Marchand
    Lynne R. Wilkens
    Joshua C. Bis
    Hampton Leonard
    Botong Shen
    Leslie A. Lange
    Ayush Giri
    Ozan Dikilitas
    Iftikhar J. Kullo
    Ian B. Stanaway
    Gail P. Jarvik
    Adam S. Gordon
    Nature Medicine, 2022, 28 : 1679 - 1692
  • [24] Research Guidelines in the Era of Large-scale Collaborations: An Analysis of Genome-wide Association Study Consortia
    Austin, Melissa A.
    Hair, Marilyn S.
    Fullerton, Stephanie M.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2012, 175 (09) : 962 - 969
  • [25] Approximate generalized least squares method for large-scale genome-wide association study.
    Ma, L.
    Jiang, J.
    Prakapenka, D.
    Cole, J.
    Da, Y.
    JOURNAL OF DAIRY SCIENCE, 2019, 102 : 30 - 30
  • [26] A large-scale genome-wide association study meta-analysis of cannabis use disorder
    Johnson, Emma C.
    Demontis, Ditte
    Thorgeirsson, Thorgeir E.
    Walters, Raymond K.
    Polimanti, Renato
    Hatoum, Alexander S.
    Sanchez-Roige, Sandra
    Paul, Sarah E.
    Wendt, Frank R.
    Clarke, Toni-Kim
    Lai, Dongbing
    Reginsson, Gunnar W.
    Zhou, Hang
    He, June
    Baranger, David A. A.
    Gudbjartsson, Daniel F.
    Wedow, Robbee
    Adkins, Daniel E.
    Adkins, Amy E.
    Alexander, Jeffry
    Bacanu, Silviu-Alin
    Bigdeli, Tim B.
    Boden, Joseph
    Brown, Sandra A.
    Bucholz, Kathleen K.
    Bybjerg-Grauholm, Jonas
    Corley, Robin P.
    Degenhardt, Louisa
    Dick, Danielle M.
    Domingue, Benjamin W.
    Fox, Louis
    Goate, Alison M.
    Gordon, Scott D.
    Hack, Laura M.
    Hancock, Dana B.
    Hartz, Sarah M.
    Hickie, Ian B.
    Hougaard, David M.
    Krauter, Kenneth
    Lind, Penelope A.
    McClintick, Jeanette N.
    McQueen, Matthew B.
    Meyers, Jacquelyn L.
    Montgomery, Grant W.
    Mors, Ole
    Mortensen, Preben B.
    Nordentoft, Merete
    Pearson, John F.
    Peterson, Roseann E.
    Reynolds, Maureen D.
    LANCET PSYCHIATRY, 2020, 7 (12): : 1032 - 1045
  • [27] Large-Scale Genome-Wide Association Studies Consortia Blessing, Burden, or Necessity?
    Ingelsson, Erik
    CIRCULATION-CARDIOVASCULAR GENETICS, 2010, 3 (05) : 396 - 398
  • [28] Secure large-scale genome-wide association studies using homomorphic encryption
    Blatt, Marcelo
    Gusev, Alexander
    Polyakov, Yuriy
    Goldwasser, Shafi
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (21) : 11608 - 11613
  • [29] Bayesian hierarchical hypothesis testing in large-scale genome-wide association analysis
    Samaddar, Anirban
    Maiti, Tapabrata
    de los Campos, Gustavo
    GENETICS, 2024, 228 (04)
  • [30] Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies
    Huang, Jim C.
    Meek, Christopher
    Kadie, Carl
    Heckerman, David
    PLOS ONE, 2011, 6 (07):