1. Unraveling genetic sensitivity of beef cattle to environmental variation under tropical conditions
- Author
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Roberto Carvalheiro, Lucia Galvão de Albuquerque, Ben J. Hayes, Roy Costilla, Haroldo H. R. Neves, Stephen S. Moore, Universidade Estadual Paulista (Unesp), National Council for Scientific and Technological Development (CNPq), University of Queensland, and GenSys Assoc. Consultants
- Subjects
Male ,Candidate gene ,lcsh:QH426-470 ,[SDV]Life Sciences [q-bio] ,Single-nucleotide polymorphism ,Beef cattle ,Biology ,Weight Gain ,Polymorphism, Single Nucleotide ,chemistry.chemical_compound ,Molecular marker ,Genetics ,Environmental level ,Animals ,Gene–environment interaction ,Ecology, Evolution, Behavior and Systematics ,Environmental gradient ,lcsh:SF1-1100 ,2. Zero hunger ,Tropical Climate ,0402 animal and dairy science ,04 agricultural and veterinary sciences ,General Medicine ,040201 dairy & animal science ,Environmental variation ,lcsh:Genetics ,chemistry ,Evolutionary biology ,Cattle ,Female ,Gene-Environment Interaction ,Animal Science and Zoology ,lcsh:Animal culture ,Research Article ,Genome-Wide Association Study - Abstract
Made available in DSpace on 2019-10-06T17:12:38Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-06-20 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Background: Selection 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 (412 K 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. Results: Heteroscedastic 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. Conclusions: Sensitivity 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. School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP) National Council for Scientific and Technological Development (CNPq) Institute for Molecular Bioscience (IMB) University of Queensland Queensland Alliance for Agriculture and Food Innovation (QAAFI) Centre for Animal Science University of Queensland GenSys Assoc. Consultants School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP)
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- 2019