Unraveling genetic sensitivity of beef cattle to environmental variation under tropical conditions

被引:46
作者
Carvalheiro, Roberto [1 ,2 ]
Costilla, Roy [3 ,4 ]
Neves, Haroldo H. R. [5 ]
Albuquerque, Lucia G. [1 ,2 ]
Moore, Stephen [4 ]
Hayes, Ben J. [4 ]
机构
[1] Sao Paulo State Univ UNESP, Sch Agr & Veterinarian Sci, BR-14884900 Jaboticabal, SP, Brazil
[2] Natl Council Sci & Technol Dev CNPq, BR-71605001 Brasilia, DF, Brazil
[3] Univ Queensland, IMB, St Lucia, Qld 4072, Australia
[4] Univ Queensland, Ctr Anim Sci, QAAFI, St Lucia, Qld 4072, Australia
[5] GenSys Associated Consultants, BR-90680000 Porto Alegre, RS, Brazil
基金
巴西圣保罗研究基金会;
关键词
GENOME-WIDE ASSOCIATION; REACTION NORM MODEL; GENOTYPE IMPUTATION; HEAT TOLERANCE; IMMUNE-SYSTEM; DAIRY-CATTLE; EXPRESSION; SELECTION; INFORMATION; HOLSTEIN;
D O I
10.1186/s12711-019-0470-x
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
BackgroundSelection of cattle that are less sensitive to environmental variation in unfavorable environments and more adapted to harsh conditions is of primary importance for tropical beef cattle production systems. Understanding the genetic background of sensitivity to environmental variation is necessary for developing strategies and tools to increase efficiency and sustainability of beef production. We evaluated the degree of sensitivity of beef cattle performance to environmental variation, at the animal and molecular marker levels (412K single nucleotide polymorphisms), by fitting and comparing the results of different reaction norm models (RNM), using a comprehensive dataset of Nellore cattle raised under diverse environmental conditions.ResultsHeteroscedastic RNM (with different residual variances for environmental level) provided better fit than homoscedastic RNM. In addition, spline and quadratic RNM outperformed linear RNM, which suggests the existence of a nonlinear genetic component affecting the performance of Nellore cattle. This nonlinearity indicates that within-animal sensitivity depends on the environmental gradient (EG) level and that animals may present different patterns of sensitivity according to the range of environmental variations. The spline RNM showed that sensitivity to environmental variation from harsh to average EG is lowly correlated with sensitivity from average to good EG, at both the animal and molecular marker levels. Although the genomic regions that affect sensitivity in harsher environments were not the same as those associated with less challenging environments, the candidate genes within those regions participate in common biological processes such as those related to inflammatory and immune response. Some plausible candidate genes were identified.ConclusionsSensitivity of tropical beef cattle to environmental variation is not continuous along the environmental gradient, which implies that animals that are less sensitive to harsher conditions are not necessarily less responsive to variations in better environmental conditions, and vice versa. The same pattern was observed at the molecular marker level, i.e. genomic regions and, consequently, candidate genes associated with sensitivity to harsh conditions were not the same as those associated with sensitivity to less challenging conditions.
引用
收藏
页数:14
相关论文
共 69 条
[1]   Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score [J].
Aguilar, I. ;
Misztal, I. ;
Johnson, D. L. ;
Legarra, A. ;
Tsuruta, S. ;
Lawlor, T. J. .
JOURNAL OF DAIRY SCIENCE, 2010, 93 (02) :743-752
[2]   NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].
AKAIKE, H .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) :716-723
[3]  
[Anonymous], 2003, ROBUST REGRESSION OU
[4]  
[Anonymous], 1984, Applications of Linear Models in Animal Breeding
[5]   The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans [J].
Ardlie, Kristin G. ;
DeLuca, David S. ;
Segre, Ayellet V. ;
Sullivan, Timothy J. ;
Young, Taylor R. ;
Gelfand, Ellen T. ;
Trowbridge, Casandra A. ;
Maller, Julian B. ;
Tukiainen, Taru ;
Lek, Monkol ;
Ward, Lucas D. ;
Kheradpour, Pouya ;
Iriarte, Benjamin ;
Meng, Yan ;
Palmer, Cameron D. ;
Esko, Tonu ;
Winckler, Wendy ;
Hirschhorn, Joel N. ;
Kellis, Manolis ;
MacArthur, Daniel G. ;
Getz, Gad ;
Shabalin, Andrey A. ;
Li, Gen ;
Zhou, Yi-Hui ;
Nobel, Andrew B. ;
Rusyn, Ivan ;
Wright, Fred A. ;
Lappalainen, Tuuli ;
Ferreira, Pedro G. ;
Ongen, Halit ;
Rivas, Manuel A. ;
Battle, Alexis ;
Mostafavi, Sara ;
Monlong, Jean ;
Sammeth, Michael ;
Mele, Marta ;
Reverter, Ferran ;
Goldmann, Jakob M. ;
Koller, Daphne ;
Guigo, Roderic ;
McCarthy, Mark I. ;
Dermitzakis, Emmanouil T. ;
Gamazon, Eric R. ;
Im, Hae Kyung ;
Konkashbaev, Anuar ;
Nicolae, Dan L. ;
Cox, Nancy J. ;
Flutre, Timothee ;
Wen, Xiaoquan ;
Stephens, Matthew .
SCIENCE, 2015, 348 (6235) :648-660
[6]  
Bahbahani Hussain, 2017, Front Genet, V8, P68, DOI 10.3389/fgene.2017.00068
[7]   Diabetes Risk Gene and Wnt Effector Tcf7l2/TCF4 Controls Hepatic Response to Perinatal and Adult Metabolic Demand [J].
Boj, Sylvia F. ;
van Es, Johan H. ;
Huch, Meritxell ;
Li, Vivian S. W. ;
Jose, Anabel ;
Hatzis, Pantelis ;
Mokry, Michal ;
Haegebarth, Andrea ;
van den Born, Maaike ;
Chambon, Pierre ;
Voshol, Peter ;
Dor, Yuval ;
Cuppen, Edwin ;
Fillat, Cristina ;
Clevers, Hans .
CELL, 2012, 151 (07) :1595-1607
[8]   Genetic evaluations for growth heat tolerance in Angus cattle [J].
Bradford, H. L. ;
Fragomeni, B. O. ;
Bertrand, J. K. ;
Lourenco, D. A. L. ;
Misztal, I. .
JOURNAL OF ANIMAL SCIENCE, 2016, 94 (10) :4143-4150
[9]   The cattle interleukin-13 gene: genomic organization, chromosomal location, and evolution of the promoter [J].
Buitkamp, J ;
Jann, O ;
Fries, R .
IMMUNOGENETICS, 1999, 49 (10) :872-878
[10]   Importance of adaptation and genotype X environment interactions in tropical beef breeding systems [J].
Burrow, H. M. .
ANIMAL, 2012, 6 (05) :729-740