Enviromicsin breeding: applications and perspectives on envirotypic-assisted selection

Abstract

AbstractGenotype by Environment interaction (G × E) studies 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 understanding and dealing with G × E. 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 under an envirotypic-assisted breeding framework and propose the GIS-GE method, i.e. a geospatial tool to maximize genetic gains by predicting the phenotypic performance of unobserved genotypes using “enviromic markers”. In summary, a particular site represents a set of envirotypes, each one representing a set of environmental factors that interact with the genetic background of genotypes, thus resulting in informative re-rankings to make decisions over different environments. Based on a simulated case study, we show that GIS-GE allows accurate (i) matching of genotypes to their most appropriate sites; (ii) definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (iii) indication of the best sites to carry out experiments for further analysis based on environments that maximize heritability. Envirotyping techniques provide a new class of markers for genetic studies, which are inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of the Enviromics approach into breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity. Environmental scenarios can also be improved using information from strategic plans for biodiversity and genetic resources management, especially in the current perspective of dynamic climate change.Key messageWe propose the application ofEnviromicsto breeding practice, by which the similarity among sites assessed on an “omics” scale of environmental attributes drives the prediction of unobserved genotypes.