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| Registros recuperados : 20 | |
| 4. |  | BISON, O.; AGUIAR, A. M.; RESENDE, G. D. S. P.; RAMALHO, M. A. P. Inbreeding depression in Eucalyptus clones. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 4, n. 4, p. 459-464, Dec. 2004.| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 5. | | BELTRAME, R.; LAZAROTTO, M.; HASELEIN, C. R.; SANTINI, E. J.; SCHNEIDER, P. R.; AGUIAR, A. M. Determinação das deformações residuais longitudinais decorrentes das tensões de crescimento em Eucalyptus spp. Ciência Florestal, Santa Maria, RS, v. 22, n. 2, p. 343-351, jul./set. 2012.| Biblioteca(s): Embrapa Florestas. |
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| 6. | | AGUIAR, M. S. de; FERREIRA, D. F.; AGUIAR, A. M.; BISON, O.; REZENDE, G. D. S. P.; GRATTAPAGLIA, D. Potencial de híbridos entre clones-elite de eucalipto por meio de marcadores microssatélites. Pesquisa Agropecuaria Brasileira, Brasília, DF, v. 42, n. 7, p. 1007-1012, jul. 2007.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Unidades Centrais. |
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| 7. | | MÔRO, G. V.; SANTOS, M. F.; BENTO, D. A. V.; AGUIAR, A. M.; SOUZA JUNIOR, C. L. de. Genetic analysis of kernel oil content in tropical maize with design III and QTL mapping. Euphytica, Wageningen, v. 185, n. 3, p. 419-428, 2012.| Biblioteca(s): Embrapa Hortaliças. |
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| 9. | | BISON, O.; RAMALHO, M. A. P.; REZENDE, G. D. S. P.; AGUIAR, A. M.; RESENDE, M. D. V. de. Dialelo parcial entre clones de Eucalyptus camaldulensis e clones de E. urophylla, E. grandis e E. saligna. Revista Árvore, Viçosa, v. 33, n. 3, p. 395-402, 2009.| Biblioteca(s): Embrapa Florestas. |
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| 11. | | BELICUAS, P. R.; AGUIAR, A. M.; BENTO, D. A. V.; CAMARA, T. M. M.; SOUZA JUNIOR, C. L. de. Inheritance of the stay-green trait in tropical maize. Euphytica, Wageningen, Holanda, v. 196, n. 3,2014.| Biblioteca(s): Embrapa Tabuleiros Costeiros. |
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| 14. | | RESENDE, M. D. V. de; BARBOSA, M. H. P.; REZENDE, G. D. S. P.; AGUIAR, A. M.; DIAS, L. A. dos S.; STURION, J. A. Métodos e estratégias de melhoramento de espécies perenes: estado da arte e perspectivas. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 3., 2005, Gramado. Anais. Passo Fundo: Embrapa Trigo; [S.l.]: Sociedade Brasileira de Melhoramento de Plantas, 2005. Palestra.| Biblioteca(s): Embrapa Florestas. |
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| 15. | | AZEVEDO, C. F.; ABAD, J. I. M.; MISSIAGGIA, A. A.; AGUIAR, A. M.; RESENDE, M. D. V. de; SILVA, F. F. e.; PEREIRA, C. S. Parametrizações em marcadores dominantes DarTs para características de crescimento de eucalipto. Revista Matemática e Estatística em foco, v. 1, n. 2, 2013. Edição especial dos anais do Encontro Mineiro de Estatística, 12., 2013, Uberlândia. Resumo.| Biblioteca(s): Embrapa Florestas. |
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| 16. | | RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; AGUIAR, A. M.; ABAD, J. I. M.; MISSIAGGIA, A. A.; SANSALONI, C. P.; PETROLI, C. D.; GRATTAPAGLIA, D. Computação da Seleção Genômica Ampla (GWS). Colombo: Embrapa Florestas, 2010. CD-ROM. (Embrapa Florestas. Documentos, 210).| Biblioteca(s): Embrapa Florestas. |
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| 17. | | TEIXEIRA, J. E. de C.; BONINE, C. A. V.; DIAS, D. da C.; SCARPINATI, E. A.; AGUIAR, A. M.; TOLEDO, F. H. R. B.; TAMBARUSSI, E. V.; VENCOVSKY, R. Cruzamentos dialélicos entre clones elite de Eucalyptus grandis e Eucalyptus urophylla. Scientia Forestalis, Piracicaba, v. 41, n. 100, p. 497-505, dez. 2013.| Biblioteca(s): Embrapa Florestas. |
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| 18. | | MULLER, B. S. F.; ALMEIDA FILHO, J. E. de; LIMA, B. M.; GARCIA, C. C.; MISSIAGGIA, A.; AGUIAR, A. M.; TAKAHASHI, E.; KIRST, M.; GEZAN, S. A.; SILVA JUNIOR, O. B. da; NEVES, L. G.; GRATTAPAGLIA, D. Independent and Joint-GWAS for growth traits in Eucalyptus by assembling genome-wide data for 3373 individuals across four breeding populations. The New phytologist, v. 221, n. 2, p. 818-833, 2019. Na publicação: Orzenil B. Silva-Junior.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 19. | | MULLER, B. S. F.; NEVES, L. G.; LIMA, B. M.; GARCIA, C. C.; MISSIAGGIA, A.; AGUIAR, A. M.; TAKAHASHI, E. K.; SILVA JUNIOR, O. B. da; KIRST, M.; GRATTAPAGLIA, D. Joint GWAS analysis for growth traits across four Eucalyptus breeding populations. In: PLANT AND ANIMAL GENOME CONFERENCE, 25., 2017, San Diego. [Abstracts...]. San Diego, CA: [s.n.], 2017. W338.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 20. | | 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. Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. New Phytologist, v. 194, p. 116-128, 2012.| Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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| Registros recuperados : 20 | |
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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. |
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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Circulação/Nível: |
A - 1 |
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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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