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| 4. |  | GRATTAPAGLIA, D. Genômica de Eucalyptus: oportunidades e desafios. In: MARIATH, J. E. de A.; SANTOS, R. P. dos. (Org.). Os avanços da Botânica no início do século XXI: Morfologia, Fisiologia, Taxonomia, Ecologia e Genética. Bento Gonçalves: Sociedade Botânica do Brasil, 2006. Conferências plenárias e Simpósios do: CONGRESSO NACIONAL DE BOTÂNICA, 57.; ENCONTRO ESTADUAL DE BOTÂNICOS, 13.; ENCONTRO ESTADUAL DE HERBÁRIOS, 5., 2006, Gramado, RS. p. 150-156.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Recursos Genéticos e Biotecnologia. Para informações adicionais entre em contato com cenargen.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Café; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
10/12/2020 |
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Data da última atualização: |
17/12/2021 |
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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, R. T.; PIEPHO,H.-P.; ROSA, G. J. M.; SILVA JUNIOR, O. B. da; SILVA, F. F. e; RESENDE, M. D. V. de; GRATTAPAGLIA, D. |
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Afiliação: |
RAFAEL T. RESENDE, UFG; HANS-PETER PIEPHO, UNIVERSITY OF HOHENHEIM, GERMANY; GUILHERME J. M. ROSA, UNIVERSITY OF WISCONSIN-MADISON, USA; ORZENIL BONFIM DA SILVA JUNIOR, Cenargen; FABYANO F. E SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; DARIO GRATTAPAGLIA, Cenargen. |
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Título: |
Enviromics in breeding: applications and perspectives on envirotypic-assisted selection. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Theoretical and Applied Genetics, v. 134, n. 1, 2021. p. 95-112. |
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DOI: |
https://doi.org/10.1007/s00122-020-03684-z |
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Idioma: |
Inglês |
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Conteúdo: |
Genotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change. Envirotyping provides a new class of markers for genetic studies, which are fairly inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of enviromics approaches into plant breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity. MenosGenotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change... Mostrar Tudo |
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Thesagro: |
Interação Genética; Melhoramento Genético Vegetal; Sistema de Informação Geográfica. |
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Thesaurus NAL: |
Breeding; Genotype-environment interaction; Geographic information systems; Plant breeding. |
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Categoria do assunto: |
-- |
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Marc: |
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024 7 $ahttps://doi.org/10.1007/s00122-020-03684-z$2DOI
100 1 $aRESENDE, R. T.
245 $aEnviromics in breeding$bapplications and perspectives on envirotypic-assisted selection.$h[electronic resource]
260 $c2021
520 $aGenotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change. Envirotyping provides a new class of markers for genetic studies, which are fairly inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of enviromics approaches into plant breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity.
650 $aBreeding
650 $aGenotype-environment interaction
650 $aGeographic information systems
650 $aPlant breeding
650 $aInteração Genética
650 $aMelhoramento Genético Vegetal
650 $aSistema de Informação Geográfica
700 1 $aPIEPHO,H.-P.
700 1 $aROSA, G. J. M.
700 1 $aSILVA JUNIOR, O. B. da
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aGRATTAPAGLIA, D.
773 $tTheoretical and Applied Genetics$gv. 134, n. 1, 2021. p. 95-112.
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