Genomic selection in dairy cattle simulated populations

Detalhes bibliográficos
Autor(a) principal: De Oliveira Seno, Leonardo
Data de Publicação: 2018
Outros Autores: Guidolin, Diego Gomes Freire, Aspilcueta-Borquis, Rusbel Raul, Do Nascimento, Guilherme Batista [UNESP], Da Silva, Thiago Bruno Ribeiro, De Oliveira, Henrique Nunes [UNESP], Munari, Danísio Prado [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1017/S0022029918000304
http://hdl.handle.net/11449/189810
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 17 000 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 16 000 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 17 000 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 16 000 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 Federal University (UFGD)Universidade Anhanguera (Uniderp)Universidade Estadual Paulista (UNESP)Mato Grosso Federal University (UFMT)Universidade Estadual Paulista (UNESP)CAPES: 23038.000928/2010-42Grande Dourados Federal University (UFGD)Universidade Anhanguera (Uniderp)Universidade Estadual Paulista (Unesp)Mato Grosso Federal University (UFMT)De Oliveira Seno, LeonardoGuidolin, Diego Gomes FreireAspilcueta-Borquis, Rusbel RaulDo Nascimento, Guilherme Batista [UNESP]Da Silva, Thiago Bruno RibeiroDe Oliveira, Henrique Nunes [UNESP]Munari, Danísio Prado [UNESP]2019-10-06T16:52:54Z2019-10-06T16:52:54Z2018-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article125-132http://dx.doi.org/10.1017/S0022029918000304Journal of Dairy Research, v. 85, n. 2, p. 125-132, 2018.1469-76290022-0299http://hdl.handle.net/11449/18981010.1017/S00220299180003042-s2.0-85055002160Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Dairy Researchinfo:eu-repo/semantics/openAccess2024-06-06T13:42:35Zoai:repositorio.unesp.br:11449/189810Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:43:37.860847Repositório 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
De Oliveira Seno, Leonardo
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 De Oliveira Seno, Leonardo
author_facet De Oliveira Seno, Leonardo
Guidolin, Diego Gomes Freire
Aspilcueta-Borquis, Rusbel Raul
Do Nascimento, Guilherme Batista [UNESP]
Da Silva, Thiago Bruno Ribeiro
De Oliveira, Henrique Nunes [UNESP]
Munari, Danísio Prado [UNESP]
author_role author
author2 Guidolin, Diego Gomes Freire
Aspilcueta-Borquis, Rusbel Raul
Do Nascimento, Guilherme Batista [UNESP]
Da Silva, Thiago Bruno Ribeiro
De Oliveira, Henrique Nunes [UNESP]
Munari, Danísio Prado [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Grande Dourados Federal University (UFGD)
Universidade Anhanguera (Uniderp)
Universidade Estadual Paulista (Unesp)
Mato Grosso Federal University (UFMT)
dc.contributor.author.fl_str_mv De Oliveira Seno, Leonardo
Guidolin, Diego Gomes Freire
Aspilcueta-Borquis, Rusbel Raul
Do Nascimento, Guilherme Batista [UNESP]
Da Silva, Thiago Bruno Ribeiro
De Oliveira, Henrique Nunes [UNESP]
Munari, Danísio 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 17 000 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 16 000 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 2018-05-01
2019-10-06T16:52:54Z
2019-10-06T16:52:54Z
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/S0022029918000304
Journal of Dairy Research, v. 85, n. 2, p. 125-132, 2018.
1469-7629
0022-0299
http://hdl.handle.net/11449/189810
10.1017/S0022029918000304
2-s2.0-85055002160
url http://dx.doi.org/10.1017/S0022029918000304
http://hdl.handle.net/11449/189810
identifier_str_mv Journal of Dairy Research, v. 85, n. 2, p. 125-132, 2018.
1469-7629
0022-0299
10.1017/S0022029918000304
2-s2.0-85055002160
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
dc.source.none.fl_str_mv Scopus
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)
repository.mail.fl_str_mv
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