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Registro Completo |
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Biblioteca(s): |
Embrapa Trigo. |
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Data corrente: |
20/12/2017 |
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Data da última atualização: |
27/12/2017 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
BRUM, L. E. G.; MACHADO, A. P.; BRAMMER, S. P.; NASCIMENTO JUNIOR, A. do. |
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Afiliação: |
LUIZA ELODI GREINER BRUM, Engenharia Ambiental - UPF; ANA PAULA MACHADO, Biomedicina – Ulbra; SANDRA PATUSSI BRAMMER, CNPT; ALFREDO DO NASCIMENTO JUNIOR, CNPT. |
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Título: |
Variabilidade genética entre cultivares de aveias forrageiras por meio de marcadores microssatélites: estudos preliminares. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
In: MOSTRA DE INICIAÇÃO CIENTÍFICA, 12.; MOSTRA DE PÓS-GRADUAÇÃO DA EMBRAPA TRIGO, 9., 2017, Passo Fundo. Resumos... Passo Fundo: Embrapa Trigo, 2017. |
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Páginas: |
p. 28. |
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Idioma: |
Português |
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Thesagro: |
Aveia forrageira; Marcador genético; Variação genética. |
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Thesaurus Nal: |
Genetic markers; Genetic variation; Oats. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/169460/1/2017MICp28.pdf
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Marc: |
LEADER 00808nam a2200217 a 4500
001 2083132
005 2017-12-27
008 2017 bl uuuu u00u1 u #d
100 1 $aBRUM, L. E. G.
245 $aVariabilidade genética entre cultivares de aveias forrageiras por meio de marcadores microssatélites$bestudos preliminares.$h[electronic resource]
260 $aIn: MOSTRA DE INICIAÇÃO CIENTÍFICA, 12.; MOSTRA DE PÓS-GRADUAÇÃO DA EMBRAPA TRIGO, 9., 2017, Passo Fundo. Resumos... Passo Fundo: Embrapa Trigo$c2017
300 $ap. 28.
650 $aGenetic markers
650 $aGenetic variation
650 $aOats
650 $aAveia forrageira
650 $aMarcador genético
650 $aVariação genética
700 1 $aMACHADO, A. P.
700 1 $aBRAMMER, S. P.
700 1 $aNASCIMENTO JUNIOR, A. do
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Registro original: |
Embrapa Trigo (CNPT) |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
30/12/2019 |
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Data da última atualização: |
30/12/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
LARA, L. A. de C.; SANTOS, M. F.; JANK, L.; CHIARI, L.; VILELA, M. de M.; AMADEU, R. R.; SANTOS, J. P. R. dos; SILVA, F. G. da; ZENG, Z.-B.; GARCIA, A. A. F. |
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Afiliação: |
Letícia A. de C. Lara, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; MATEUS FIGUEIREDO SANTOS, CNPGC; LIANA JANK, CNPGC; LUCIMARA CHIARI, CNPGC; MARIANE DE MENDONCA VILELA, CNPGC; Rodrigo R. Amadeu, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; Jhonathan P. R. dos Santos, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; FRANCISCO GUILHERME DA SILVA, CNPGL; Zhao-Bang Zeng, North Carolina State University - NCSU; Antonio Augusto F. Garcia, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ. |
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Título: |
Genomic Selection with Allele Dosage in Panicum maximum Jacq. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
G3: Genes|Genomes|Genetics, v. 9, p. 2463-2475, August 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We ,also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotypingby- sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum. MenosGenomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We ,also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotypingby- sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformati... Mostrar Tudo |
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Thesaurus NAL: |
Genomics; Genotyping; Guinea; Plant breeding; Polyploidy; Prediction. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/207993/1/Genomic-Selection-with-Allele-Dosage.pdf
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Marc: |
LEADER 02472naa a2200301 a 4500
001 2117941
005 2019-12-30
008 2019 bl uuuu u00u1 u #d
100 1 $aLARA, L. A. de C.
245 $aGenomic Selection with Allele Dosage in Panicum maximum Jacq.$h[electronic resource]
260 $c2019
520 $aGenomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We ,also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotypingby- sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum.
650 $aGenomics
650 $aGenotyping
650 $aGuinea
650 $aPlant breeding
650 $aPolyploidy
650 $aPrediction
700 1 $aSANTOS, M. F.
700 1 $aJANK, L.
700 1 $aCHIARI, L.
700 1 $aVILELA, M. de M.
700 1 $aAMADEU, R. R.
700 1 $aSANTOS, J. P. R. dos
700 1 $aSILVA, F. G. da
700 1 $aZENG, Z.-B.
700 1 $aGARCIA, A. A. F.
773 $tG3: Genes|Genomes|Genetics$gv. 9, p. 2463-2475, August 2019.
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