Enviromics in breeding: applications and perspectives on envirotypic-assisted selection
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ORIGINAL ARTICLE
Enviromics in breeding: applications and perspectives on envirotypic‑assisted selection Rafael T. Resende1 · Hans‑Peter Piepho2 · Guilherme J. M. Rosa3 · Orzenil B. Silva‑Junior4 · Fabyano F. e Silva5 · Marcos Deon V. de Resende6,7 · Dario Grattapaglia4,8 Received: 25 June 2019 / Accepted: 10 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
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.
Introduction One of the greatest challenges of modern agriculture is dealing with an accelerated growth of the human population worldwide, together with limited prospects of significantly
expanding farmed land. Tailoring highly adapted genetic material to the available environments becomes a key element to increase agricultural yields without the conversion of additional land and losses due to adverse environmental impact (Garnett et al. 2013). The differential response of genotypes across variable environments, known as genotype
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