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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Gado de Leite; Embrapa Pecuária Sudeste. |
Data corrente: |
15/04/2014 |
Data da última atualização: |
05/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
BUZANSKAS, M. E.; GROSSI, D. A.; VENTURA, R. V.; SCHENKEL, F. S.; SARGOLZAEI, M.; MEIRELLES, S. L. C. O; MOKRY, F. B.; HIGA, R. H.; MUDADU, M. de A.; SILVA, M. V. G. B.; NICIURA, S. C. M.; TORRES JUNIOR, R. A. de A.; ALENCAR, M. M. de; REGITANO, L. C. de A.; MUNARI, D. P. |
Afiliação: |
MARCOS VINICIUS GUALBERTO B SILVA, CNPGL. |
Título: |
Genome-wide association for growth traits in Canchim beef cattle. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Plos One, v. 9, n. 4, e94802 2014. |
Idioma: |
Inglês |
Conteúdo: |
Abstract. Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and 1/2 Canchim + 1/2 Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle. MenosAbstract. Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and 1/2 Canchim + 1/2 Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate r... Mostrar Tudo |
Palavras-Chave: |
Genome-wide; Growth trait; Raça Canchim; Race Canchim. |
Thesagro: |
Gado de corte. |
Thesaurus Nal: |
Beef cattle; genome-wide association study. |
Categoria do assunto: |
-- G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/105444/1/Artigo-MVinicius-journal.plosone.0094802.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/114268/1/Buzanskas2014-Genome.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/101136/1/PROCI-2014.00012.pdf
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Marc: |
LEADER 02995naa a2200373 a 4500 001 1986150 005 2024-02-05 008 2014 bl uuuu u00u1 u #d 100 1 $aBUZANSKAS, M. E. 245 $aGenome-wide association for growth traits in Canchim beef cattle.$h[electronic resource] 260 $c2014 520 $aAbstract. Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and 1/2 Canchim + 1/2 Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle. 650 $aBeef cattle 650 $agenome-wide association study 650 $aGado de corte 653 $aGenome-wide 653 $aGrowth trait 653 $aRaça Canchim 653 $aRace Canchim 700 1 $aGROSSI, D. A. 700 1 $aVENTURA, R. V. 700 1 $aSCHENKEL, F. S. 700 1 $aSARGOLZAEI, M. 700 1 $aMEIRELLES, S. L. C. O 700 1 $aMOKRY, F. B. 700 1 $aHIGA, R. H. 700 1 $aMUDADU, M. de A. 700 1 $aSILVA, M. V. G. B. 700 1 $aNICIURA, S. C. M. 700 1 $aTORRES JUNIOR, R. A. de A. 700 1 $aALENCAR, M. M. de 700 1 $aREGITANO, L. C. de A. 700 1 $aMUNARI, D. P. 773 $tPlos One$gv. 9, n. 4, e94802 2014.
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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Registro Completo
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
20/08/2020 |
Data da última atualização: |
20/12/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
KRAUSE, M. D.; DIAS, K. O. das G.; SANTOS, J. P. R. dos; OLIVEIRA, A. A. de; GUIMARAES, L. J. M.; PASTINA, M. M.; MARGARIDO, G. R. A.; GARCIA, A. A. F. |
Afiliação: |
Matheus Dalsente Krause, Iowa State University; Kaio Olímpio das Graças Dias, Escola Superior de Agricultura "Luiz de Queiroz"; Jhonathan Pedroso Rigal dos Santos, Escola Superior de Agricultura "Luiz de Queiroz"; Amanda Avelar de Oliveira, Escola Superior de Agricultura "Luiz de Queiroz"; LAURO JOSE MOREIRA GUIMARAES, CNPMS; MARIA MARTA PASTINA, CNPMS; Gabriel Rodrigues Alves Margarido, Escola Superior de Agricultura "Luiz de Queiroz"; Antonio Augusto Franco Garcia, Escola Superior de Agricultura "Luiz de Queiroz". |
Título: |
Boosting predictive ability of tropical maize hybrids via genotype-by-environment interaction under multivariate GBLUP models. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Crop Science, v. 60, n. 6, p. 3049-3065, 2020. |
DOI: |
10.1002/csc2.20253 |
Idioma: |
Inglês |
Conteúdo: |
Genomic selection has been implemented in several plant and animal breeding programs and it has proven to improve efficiency and maximize genetic gains. Phenotypic data of grain yield was measured in 147 maize (Zea mays L.) singlecross hybrids at 12 environments. Single-cross hybrids genotypes were inferred based on their parents (inbred lines) via single nucleotide polymorphism (SNP) markers obtained from genotyping-by-sequencing (GBS). Factor analytic multiplicative genomic best linear unbiased prediction (GBLUP) models, in the framework of multienvironment trials, were used to predict grain yield performance of unobserved tropical maize single-cross hybrids. Predictions were performed for two situations: untested hybrids (CV1), and hybrids evaluated in some environments but missing in others (CV2). Models that borrowed information across individuals through genomic relationships and within individuals across environments presented higher predictive accuracy than those models that ignored it. For these models, predictive accuracies were up to 0.4 until eight environments were considered as missing for the validation set, which represents 67% of missing data for a given hybrid. These results highlight the importance of including genotype-by-environment interactions and genomic relationship information for boosting predictions of tropical maize single-cross hybrids for grain yield. |
Thesagro: |
Genótipo; Melhoramento Genético Vegetal; Milho. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/219490/1/Boosting-predictive.pdf
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Marc: |
LEADER 02201naa a2200253 a 4500 001 2124456 005 2020-12-20 008 2020 bl uuuu u00u1 u #d 024 7 $a10.1002/csc2.20253$2DOI 100 1 $aKRAUSE, M. D. 245 $aBoosting predictive ability of tropical maize hybrids via genotype-by-environment interaction under multivariate GBLUP models.$h[electronic resource] 260 $c2020 520 $aGenomic selection has been implemented in several plant and animal breeding programs and it has proven to improve efficiency and maximize genetic gains. Phenotypic data of grain yield was measured in 147 maize (Zea mays L.) singlecross hybrids at 12 environments. Single-cross hybrids genotypes were inferred based on their parents (inbred lines) via single nucleotide polymorphism (SNP) markers obtained from genotyping-by-sequencing (GBS). Factor analytic multiplicative genomic best linear unbiased prediction (GBLUP) models, in the framework of multienvironment trials, were used to predict grain yield performance of unobserved tropical maize single-cross hybrids. Predictions were performed for two situations: untested hybrids (CV1), and hybrids evaluated in some environments but missing in others (CV2). Models that borrowed information across individuals through genomic relationships and within individuals across environments presented higher predictive accuracy than those models that ignored it. For these models, predictive accuracies were up to 0.4 until eight environments were considered as missing for the validation set, which represents 67% of missing data for a given hybrid. These results highlight the importance of including genotype-by-environment interactions and genomic relationship information for boosting predictions of tropical maize single-cross hybrids for grain yield. 650 $aGenótipo 650 $aMelhoramento Genético Vegetal 650 $aMilho 700 1 $aDIAS, K. O. das G. 700 1 $aSANTOS, J. P. R. dos 700 1 $aOLIVEIRA, A. A. de 700 1 $aGUIMARAES, L. J. M. 700 1 $aPASTINA, M. M. 700 1 $aMARGARIDO, G. R. A. 700 1 $aGARCIA, A. A. F. 773 $tCrop Science$gv. 60, n. 6, p. 3049-3065, 2020.
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