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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
24/10/2012 |
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Data da última atualização: |
16/02/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; AGUIAR, A. M.; ABAD, J. M.; TAKAHASHI, E. K.; ROSADO, A. M.; FARIA, D. A.; PAPPAS JUNIOR, G. J.; KILIAN, A.; GRATTAPAGLIA, D. |
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Afiliação: |
MARCOS DEON VILELA DE RESENDE, CNPF; MÁRCIO F. R. RESENDE, UFV; CAROLINA P. SANSALONI, UnB; CESAR D. PETROLI, UnB; Alexandre A. Missiaggia, 5 FIBRIA Celulose; Aurelio M. Aguiar, FIBRIA Celulose; JUPITER M. ABAD, FIBRIA CELULOSE S. A.; ELIZABETE K. TAKAHASHI, CENIBRA CELULOSE NIPO BRASILEIRA S. A.; ANTONIO M. ROSADO, CENIBRA CELULOSE NIPO BRASILEIRA S. A.; DANIELLE A. FARIA, CENARGEN; GEORGIOS JOANNIS PAPPAS JUNIOR, CENARGEN; ANDRZEJ KILIAN, DIVERSITY ARRAYS TECHNOLOGY; DARIO GRATTAPAGLIA, CENARGEN. |
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Título: |
Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
New Phytologist, v. 194, p. 116-128, 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the ?missing heritability? of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (Ne = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74?97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype environment interaction. GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population- specific predictive models will likely drive the initial applications of GS in forest tree breeding. MenosGenomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the ?missing heritability? of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (Ne = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74?97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype environment interaction. GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population- specific predictive models will likely drive the initial applications of G... Mostrar Tudo |
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Palavras-Chave: |
Qualidade da madeira. |
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Thesagro: |
Eucalipto; Seleção Genética. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02465naa a2200301 a 4500
001 1937744
005 2018-02-16
008 2012 bl uuuu u00u1 u #d
100 1 $aRESENDE, M. D. V. de
245 $aGenomic selection for growth and wood quality in Eucalyptus$bcapturing the missing heritability and accelerating breeding for complex traits in forest trees.$h[electronic resource]
260 $c2012
520 $aGenomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the ?missing heritability? of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (Ne = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74?97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype environment interaction. GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population- specific predictive models will likely drive the initial applications of GS in forest tree breeding.
650 $aEucalipto
650 $aSeleção Genética
653 $aQualidade da madeira
700 1 $aRESENDE JUNIOR, M. F. R.
700 1 $aSANSALONI, C. P.
700 1 $aPETROLI, C. D.
700 1 $aMISSIAGGIA, A. A.
700 1 $aAGUIAR, A. M.
700 1 $aABAD, J. M.
700 1 $aTAKAHASHI, E. K.
700 1 $aROSADO, A. M.
700 1 $aFARIA, D. A.
700 1 $aPAPPAS JUNIOR, G. J.
700 1 $aKILIAN, A.
700 1 $aGRATTAPAGLIA, D.
773 $tNew Phytologist$gv. 194, p. 116-128, 2012.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
16/02/2009 |
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Data da última atualização: |
07/03/2017 |
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Tipo da produção científica: |
Comunicado Técnico/Recomendações Técnicas |
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Autoria: |
AIDAR, H.; THUNG, M. D.; DEL PELOSO, M. J.; FARIA, L. C. de; MELO, L. C.; COSTA, J. G. C. da; RAVA, C. A.; PEREIRA, H. S.; CABRERA DIAZ, J. L.; SILVA, H. T. da; SARTORATO, A.; FARIA, J. C. de; BASSINELLO, P. Z.; WENDLAND, A. |
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Afiliação: |
HOMERO AIDAR, CNPAF; MICHAEL DIJIE THUNG, CNPAF; MARIA JOSE DEL PELOSO, CNPAF; LUIS CLAUDIO DE FARIA, CNPAF; LEONARDO CUNHA MELO, CNPAF; JOAQUIM GERALDO CAPRIO DA COSTA, CNPAF; CARLOS AGUSTIN RAVA, CNPAF; HELTON SANTOS PEREIRA, CNPAF; JOSE LUIS CABRERA DIAZ, CNPAF; HELOISA TORRES DA SILVA, CNPAF; ALOISIO SARTORATO, CNPAF; JOSIAS CORREA DE FARIA, CNPAF; PRISCILA ZACZUK BASSINELLO, CNPAF; ADRIANE WENDLAND FERREIRA, CNPAF. |
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Título: |
BRS Executivo: feijão comum com tipo de grão cranberry para o mercado internacional. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2008. |
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Páginas: |
2 p. |
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Série: |
(Embrapa Arroz e Feijão. Comunicado técnico, 157). |
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Idioma: |
Português |
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Conteúdo: |
O Programa de Melhoramento Genético do Feijoeiro Comum da Embrapa Arroz e Feijão, atento às novas tendências do mercado, está focado na busca de cultivares para atender as novas demandas, possibilitando ao agricultor ofertar um produto de maior valor e auferir melhores rendimentos com a cultura. É com esta filosofia que está sendo indicada a cultivar de feijoeiro comum BRS Executivo, com tipo de grão comercial Rajado (Cranberry), para o plantio na época de "Inverno", no Estado de Goiás. |
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Palavras-Chave: |
BRS Executivo; Cranberry; Grão rajado. |
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Thesagro: |
Feijão; Melhoramento Genético Vegetal; Phaseolus Vulgaris. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/CNPAF-2009-09/27949/1/comt_157.pdf
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Marc: |
LEADER 01555nam a2200361 a 4500
001 1216226
005 2017-03-07
008 2008 bl uuuu u0uu1 u #d
100 1 $aAIDAR, H.
245 $aBRS Executivo$bfeijão comum com tipo de grão cranberry para o mercado internacional.$h[electronic resource]
260 $aSanto Antônio de Goiás: Embrapa Arroz e Feijão$c2008
300 $a2 p.
490 $a(Embrapa Arroz e Feijão. Comunicado técnico, 157).
520 $aO Programa de Melhoramento Genético do Feijoeiro Comum da Embrapa Arroz e Feijão, atento às novas tendências do mercado, está focado na busca de cultivares para atender as novas demandas, possibilitando ao agricultor ofertar um produto de maior valor e auferir melhores rendimentos com a cultura. É com esta filosofia que está sendo indicada a cultivar de feijoeiro comum BRS Executivo, com tipo de grão comercial Rajado (Cranberry), para o plantio na época de "Inverno", no Estado de Goiás.
650 $aFeijão
650 $aMelhoramento Genético Vegetal
650 $aPhaseolus Vulgaris
653 $aBRS Executivo
653 $aCranberry
653 $aGrão rajado
700 1 $aTHUNG, M. D.
700 1 $aDEL PELOSO, M. J.
700 1 $aFARIA, L. C. de
700 1 $aMELO, L. C.
700 1 $aCOSTA, J. G. C. da
700 1 $aRAVA, C. A.
700 1 $aPEREIRA, H. S.
700 1 $aCABRERA DIAZ, J. L.
700 1 $aSILVA, H. T. da
700 1 $aSARTORATO, A.
700 1 $aFARIA, J. C. de
700 1 $aBASSINELLO, P. Z.
700 1 $aWENDLAND, A.
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Embrapa Arroz e Feijão (CNPAF) |
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