Dataset Information

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley.

ABSTRACT: Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype states, for genotype-by-environment (G×E) modelling. Sub-populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G×E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock-related genes, associated with the environmentally adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G×E effect directions, and the importance of latitudinally based genic context in the expression of large-effect alleles. Our analysis supports a gene-level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses.

SUBMITTER: Bustos-Korts D

PROVIDER: S-EPMC6851764 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley.

Bustos-Korts Daniela D Dawson Ian K IK Russell Joanne J Tondelli Alessandro A Guerra Davide D Ferrandi Chiara C Strozzi Francesco F Nicolazzi Ezequiel L EL Molnar-Lang Marta M Ozkan Hakan H Megyeri Maria M Miko Peter P Çakır Esra E Yakışır Enes E Trabanco Noemi N Delbono Stefano S Kyriakidis Stylianos S Booth Allan A Cammarano Davide D Mascher Martin M Werner Peter P Cattivelli Luigi L Rossini Laura L Stein Nils N Kilian Benjamin B Waugh Robbie R van Eeuwijk Fred A FA

The Plant journal : for cell and molecular biology 20190627 6

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype state ...[more]

PMID: 31108005

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Project description:Key messageSimulations demonstrated that estimates of realized genetic gain from linear mixed models using regional trials are biased to some degree. Thus, we recommend multiple selected models to obtain a range of reasonable estimates. Genetic improvements of discrete characteristics are obvious and easy to demonstrate, while quantitative traits require reliable and accurate methods to disentangle the confounding genetic and non-genetic components. Stochastic simulations of soybean [Glycine max (L.) Merr.] breeding programs were performed to evaluate linear mixed models to estimate the realized genetic gain (RGG) from annual multi-environment trials (MET). True breeding values were simulated under an infinitesimal model to represent the genetic contributions to soybean seed yield under various MET conditions. Estimators were evaluated using objective criteria of bias and linearity. Covariance modeling and direct versus indirect estimation-based models resulted in a substantial range of estimated values, all of which were biased to some degree. Although no models produced unbiased estimates, the three best-performing models resulted in an average bias of [Formula: see text] kg/ha[Formula: see text]/yr[Formula: see text] ([Formula: see text] bu/ac[Formula: see text]/yr[Formula: see text]). Rather than relying on a single model to estimate RGG, we recommend the application of several models with minimal and directional bias. Further, based on the parameters used in the simulations, we do not think it is appropriate to use any single model to compare breeding programs or quantify the efficiency of proposed new breeding strategies. Lastly, for public soybean programs breeding for maturity groups II and III in North America, the estimated RGG values ranged from 18.16 to 39.68 kg/ha[Formula: see text]/yr[Formula: see text] (0.27-0.59 bu/ac[Formula: see text]/yr[Formula: see text]) from 1989 to 2019. These results provide strong evidence that public breeders have significantly improved soybean germplasm for seed yield in the primary production areas of North America.

Dataset Information

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley.

Publications

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley.

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