Genomic selection in dairy cattle simulated populations

Detalhes bibliográficos
Autor(a) principal: Seno, Leonardo de Oliveira
Data de Publicação: 2018
Outros Autores: Freire Guidolin, Diego Gomes, Aspilcueta-Borquis, Rusbel Raul, Nascimento, Guilherme Batista do [UNESP], Ribeiro da Silva, Thiago Bruno, Oliveira, Henrique Nunes de [UNESP], Munari, Danisio Prado [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1017/S002202991000304
http://hdl.handle.net/11449/166258
Resumo: Genomic selection is arguably the most promising tool for improving genetic gain in domestic animals to emerge in the last few decades, but is an expensive process. The aim of this study was to evaluate the economic impact related to the implementation of genomic selection in a simulated dairy cattle population. The software QMSim was used to simulate genomic and phenotypic data. The simulated genome contained 30 chromosomes with 100 cm each, 1666 SNPs markers equally spread and 266 QTLs randomly designated for each chromosome. The numbers of markers and QTLs were designated according to information available from Animal QTL (http://www.animalgenome.org/QTLdb) and Bovine QTL (http://bovineqtl.tamu.edu/). The allelic frequency changes were assigned in a gamma distribution with alpha parameters equal to 0.4. Recurrent mutation rates of 1.0e(-4) were assumed to apply to markers and QTLs. A historic population of 1000 individuals was generated and the total number of animals was reduced gradually along 850 generations until we obtained a number of 200 animals in the last generation, characterizing a bottleneck effect. Progenies were created along generations from random mating of the male and female gametes, assuming the same proportion of both genders. Than the population was extended for another 150 generations until we obtained 17000 animals, with only 320 male individuals in the last generation. After this period a 25 year of selection was simulated taking into account a trait limited by sex with heritability of 0.30 (i.e. milk yield), one progeny/cow/year and variance equal to 1.0. Annually, 320 bulls were mated with 16000 dams, assuming a replacement rate of 60 and 40% for males and females, respectively. Selection and discard criteria were based in four strategies to obtain the EBVs assuming as breeding objective to maximize milk yield. The progeny replaced the discarded animals creating an overlapping generation structure. The selection strategies were: RS is selection based on random values; PS is selection based on phenotypic values; Blup is selection based on EBVs estimated by BLUP; and GEBV is selection based on genomic estimated breeding values in one step, using high (GBlup) and low (GBlupi) density panels. Results indicated that the genetic evaluation using the aid of genomic information could provide better genetic gain rates in dairy cattle breeding programs as well as reduce the average inbreeding coefficient in the population. The economic viability indicators showed that only Blup and GBlup/GBlupi strategies, the ones that used milk control and genetic evaluation were economic viable, considering a discount rate of 6.32% per year.
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spelling Genomic selection in dairy cattle simulated populationsCost-benefit analysisgenetic parameterssingle nucleotide polymorphismsGenomic selection is arguably the most promising tool for improving genetic gain in domestic animals to emerge in the last few decades, but is an expensive process. The aim of this study was to evaluate the economic impact related to the implementation of genomic selection in a simulated dairy cattle population. The software QMSim was used to simulate genomic and phenotypic data. The simulated genome contained 30 chromosomes with 100 cm each, 1666 SNPs markers equally spread and 266 QTLs randomly designated for each chromosome. The numbers of markers and QTLs were designated according to information available from Animal QTL (http://www.animalgenome.org/QTLdb) and Bovine QTL (http://bovineqtl.tamu.edu/). The allelic frequency changes were assigned in a gamma distribution with alpha parameters equal to 0.4. Recurrent mutation rates of 1.0e(-4) were assumed to apply to markers and QTLs. A historic population of 1000 individuals was generated and the total number of animals was reduced gradually along 850 generations until we obtained a number of 200 animals in the last generation, characterizing a bottleneck effect. Progenies were created along generations from random mating of the male and female gametes, assuming the same proportion of both genders. Than the population was extended for another 150 generations until we obtained 17000 animals, with only 320 male individuals in the last generation. After this period a 25 year of selection was simulated taking into account a trait limited by sex with heritability of 0.30 (i.e. milk yield), one progeny/cow/year and variance equal to 1.0. Annually, 320 bulls were mated with 16000 dams, assuming a replacement rate of 60 and 40% for males and females, respectively. Selection and discard criteria were based in four strategies to obtain the EBVs assuming as breeding objective to maximize milk yield. The progeny replaced the discarded animals creating an overlapping generation structure. The selection strategies were: RS is selection based on random values; PS is selection based on phenotypic values; Blup is selection based on EBVs estimated by BLUP; and GEBV is selection based on genomic estimated breeding values in one step, using high (GBlup) and low (GBlupi) density panels. Results indicated that the genetic evaluation using the aid of genomic information could provide better genetic gain rates in dairy cattle breeding programs as well as reduce the average inbreeding coefficient in the population. The economic viability indicators showed that only Blup and GBlup/GBlupi strategies, the ones that used milk control and genetic evaluation were economic viable, considering a discount rate of 6.32% per year.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Grande Dourados Fed Univ UFGD, Dourados, MS, BrazilUniv Anhanguera Uniderp, Campo Grande, MS, BrazilUniv Estadual Paulista UNESP, Jaboticabal, SP, BrazilMato Grosso Fed Univ UFMT, Rondonopolis, MT, BrazilUniv Estadual Paulista UNESP, Jaboticabal, SP, BrazilCAPES: 23038.000928/2010-42Cambridge Univ PressGrande Dourados Fed Univ UFGDUniv Anhanguera UniderpUniversidade Estadual Paulista (Unesp)Universidade Federal de Mato Grosso do Sul (UFMS)Seno, Leonardo de OliveiraFreire Guidolin, Diego GomesAspilcueta-Borquis, Rusbel RaulNascimento, Guilherme Batista do [UNESP]Ribeiro da Silva, Thiago BrunoOliveira, Henrique Nunes de [UNESP]Munari, Danisio Prado [UNESP]2018-11-29T23:05:23Z2018-11-29T23:05:23Z2018-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article125-132application/pdfhttp://dx.doi.org/10.1017/S002202991000304Journal Of Dairy Research. New York: Cambridge Univ Press, v. 85, n. 2, p. 125-132, 2018.0022-0299http://hdl.handle.net/11449/16625810.1017/S002202991000304WOS:000440010700002WOS000440010700002Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Dairy Researchinfo:eu-repo/semantics/openAccess2023-12-12T06:23:11Zoai:repositorio.unesp.br:11449/166258Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-12-12T06:23:11Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Genomic selection in dairy cattle simulated populations
title Genomic selection in dairy cattle simulated populations
spellingShingle Genomic selection in dairy cattle simulated populations
Seno, Leonardo de Oliveira
Cost-benefit analysis
genetic parameters
single nucleotide polymorphisms
title_short Genomic selection in dairy cattle simulated populations
title_full Genomic selection in dairy cattle simulated populations
title_fullStr Genomic selection in dairy cattle simulated populations
title_full_unstemmed Genomic selection in dairy cattle simulated populations
title_sort Genomic selection in dairy cattle simulated populations
author Seno, Leonardo de Oliveira
author_facet Seno, Leonardo de Oliveira
Freire Guidolin, Diego Gomes
Aspilcueta-Borquis, Rusbel Raul
Nascimento, Guilherme Batista do [UNESP]
Ribeiro da Silva, Thiago Bruno
Oliveira, Henrique Nunes de [UNESP]
Munari, Danisio Prado [UNESP]
author_role author
author2 Freire Guidolin, Diego Gomes
Aspilcueta-Borquis, Rusbel Raul
Nascimento, Guilherme Batista do [UNESP]
Ribeiro da Silva, Thiago Bruno
Oliveira, Henrique Nunes de [UNESP]
Munari, Danisio Prado [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Grande Dourados Fed Univ UFGD
Univ Anhanguera Uniderp
Universidade Estadual Paulista (Unesp)
Universidade Federal de Mato Grosso do Sul (UFMS)
dc.contributor.author.fl_str_mv Seno, Leonardo de Oliveira
Freire Guidolin, Diego Gomes
Aspilcueta-Borquis, Rusbel Raul
Nascimento, Guilherme Batista do [UNESP]
Ribeiro da Silva, Thiago Bruno
Oliveira, Henrique Nunes de [UNESP]
Munari, Danisio Prado [UNESP]
dc.subject.por.fl_str_mv Cost-benefit analysis
genetic parameters
single nucleotide polymorphisms
topic Cost-benefit analysis
genetic parameters
single nucleotide polymorphisms
description Genomic selection is arguably the most promising tool for improving genetic gain in domestic animals to emerge in the last few decades, but is an expensive process. The aim of this study was to evaluate the economic impact related to the implementation of genomic selection in a simulated dairy cattle population. The software QMSim was used to simulate genomic and phenotypic data. The simulated genome contained 30 chromosomes with 100 cm each, 1666 SNPs markers equally spread and 266 QTLs randomly designated for each chromosome. The numbers of markers and QTLs were designated according to information available from Animal QTL (http://www.animalgenome.org/QTLdb) and Bovine QTL (http://bovineqtl.tamu.edu/). The allelic frequency changes were assigned in a gamma distribution with alpha parameters equal to 0.4. Recurrent mutation rates of 1.0e(-4) were assumed to apply to markers and QTLs. A historic population of 1000 individuals was generated and the total number of animals was reduced gradually along 850 generations until we obtained a number of 200 animals in the last generation, characterizing a bottleneck effect. Progenies were created along generations from random mating of the male and female gametes, assuming the same proportion of both genders. Than the population was extended for another 150 generations until we obtained 17000 animals, with only 320 male individuals in the last generation. After this period a 25 year of selection was simulated taking into account a trait limited by sex with heritability of 0.30 (i.e. milk yield), one progeny/cow/year and variance equal to 1.0. Annually, 320 bulls were mated with 16000 dams, assuming a replacement rate of 60 and 40% for males and females, respectively. Selection and discard criteria were based in four strategies to obtain the EBVs assuming as breeding objective to maximize milk yield. The progeny replaced the discarded animals creating an overlapping generation structure. The selection strategies were: RS is selection based on random values; PS is selection based on phenotypic values; Blup is selection based on EBVs estimated by BLUP; and GEBV is selection based on genomic estimated breeding values in one step, using high (GBlup) and low (GBlupi) density panels. Results indicated that the genetic evaluation using the aid of genomic information could provide better genetic gain rates in dairy cattle breeding programs as well as reduce the average inbreeding coefficient in the population. The economic viability indicators showed that only Blup and GBlup/GBlupi strategies, the ones that used milk control and genetic evaluation were economic viable, considering a discount rate of 6.32% per year.
publishDate 2018
dc.date.none.fl_str_mv 2018-11-29T23:05:23Z
2018-11-29T23:05:23Z
2018-05-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1017/S002202991000304
Journal Of Dairy Research. New York: Cambridge Univ Press, v. 85, n. 2, p. 125-132, 2018.
0022-0299
http://hdl.handle.net/11449/166258
10.1017/S002202991000304
WOS:000440010700002
WOS000440010700002
url http://dx.doi.org/10.1017/S002202991000304
http://hdl.handle.net/11449/166258
identifier_str_mv Journal Of Dairy Research. New York: Cambridge Univ Press, v. 85, n. 2, p. 125-132, 2018.
0022-0299
10.1017/S002202991000304
WOS:000440010700002
WOS000440010700002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal Of Dairy Research
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 125-132
application/pdf
dc.publisher.none.fl_str_mv Cambridge Univ Press
publisher.none.fl_str_mv Cambridge Univ Press
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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