Enviromics - Schlüssel für standortoptimierte Züchtungen?  [28.09.20]

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Originalpublikation

Rafael T. Resende 1*, Hans-Peter Piepho 2, Orzenil B. Silva-Junior 3,4, Fabyano F. e Silva 5, Marcos Deon V. de Resende 6,7 and Dario Grattapaglia 3,4*, (2020) Enviromics in breeding: applications and perspectives on envirotypic-assisted selection. In: TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik. 22 September 2020; DOI: 10.1007/s00122-020-03684-z. bioRxiv August 6, 2019

Affiliations:

1. Universidade Federal de Goiás (UFG), School of Agronomy/ Forestry Sector, 74.690-900, Goiânia, GO, Brazil
2. Biostatistics Unit, University of Hohenheim, 70593 Stuttgart, Germany
3. EMBRAPA Genetic Resources and Biotechnology – EPqB, Brasília, DF, 70770-910, Brazil
4. Genomic Sciences and Biotechnology Program, SGAN, Catholic University of Brasília, 916 modulo B, Brasília, DF, 70790-160, Brazil
5. Department of Animal Science, Universidade Federal de Viçosa, 36.570-900, Viçosa, Minas Gerais, Brazil
6. Department of Statistics, Universidade Federal de Viçosa, 36.570-900, Viçosa, Minas Gerais, Brazil
7. EMBRAPA Forestry Research, 83411-000, Colombo, Paraná, Brazil

*Corresponding authors: Rafael T. Resende: rafael.tassinari@gmail.com; Dario Grattapaglia: dario.grattapaglia@embrapa.br.

Abstract

Key message: We propose the application of enviromics to breeding practice, by which the similarity among sites assessed on an “omics” scale of environmental attributes drives the prediction of unobserved genotype performances. Abstract: 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. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Mehr Informationen zur Forschung von Prof. Dr. Hans-Peter Piepho Fg. Biostatistik [Leitung] Institut für Kulturpflanzenwissenschaften https://www.uni-hohenheim.de/en/organization/einrichtung/fg-biostatistik

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