Abstract
Selective breeding in agriculture increases the genetic potential of plants and animals to show high performance for phenotypic traits by selecting the best selection candidates genetically as parents of the next generation. This genetic gain is a direct result of the accuracy by which we can predict the breeding values of selection candidates in each generation. The more accurate the breeding values, the higher the probability that we will select the best candidates, and the higher the genetic gain. Unfortunately, the accuracies of breeding values for malt quality in barley are somewhat lower than theoretically possible. They range between 30-50% for most traits, which highlights that we are only realizing a
small proportion of the potential for genetic gain. The main reason is that the information currently used to predict breeding values – phenotypic, pedigree, and genomic data – does not tell us enough about the genetic potential of individuals. Other sources of information are clearly needed. Therefore, if we are to realize more genetic gain in barley, we need to uncover new sources of information that enable us to generate more accurate breeding values. An exciting new source of information is nuclear magnetic resonance metabolomics or NMR metabolomics. NMR metabolomics measures the abundance of all metabolites in a sample from an individual. These metabolite abundances (whole-metabolomic data) are
associated with the level of physiological activity in biological pathways that are initiated at the DNA and culminate in trait expression. The level of physiological activity is regulated by the genes that an individual has inherited from its parents and by cues from its environment. This link between metabolite abundances and inherited genes means that individuals with high performance for individual traits should display similar patterns of metabolite abundances across the metabolome with these patterns reflecting common genes and environmental cues. In this study, which included more than 2500 malt samples from more than 500 individual spring barley lines from the Nordic Seed breeding population, we show that whole-metabolomic data could be used to accurately predict malt quality phenotypes of individual lines and plots in spring barley. Correlations between predicted and observed phenotype were 0.78 for filtering speed, 0.51 for extraction yield, 0.85 for wort color, 0.82 for beta glucan, and 0.80 for viscosity. This demonstrated that patterns of metabolite abundances did reflect common genes and environmental cues.
small proportion of the potential for genetic gain. The main reason is that the information currently used to predict breeding values – phenotypic, pedigree, and genomic data – does not tell us enough about the genetic potential of individuals. Other sources of information are clearly needed. Therefore, if we are to realize more genetic gain in barley, we need to uncover new sources of information that enable us to generate more accurate breeding values. An exciting new source of information is nuclear magnetic resonance metabolomics or NMR metabolomics. NMR metabolomics measures the abundance of all metabolites in a sample from an individual. These metabolite abundances (whole-metabolomic data) are
associated with the level of physiological activity in biological pathways that are initiated at the DNA and culminate in trait expression. The level of physiological activity is regulated by the genes that an individual has inherited from its parents and by cues from its environment. This link between metabolite abundances and inherited genes means that individuals with high performance for individual traits should display similar patterns of metabolite abundances across the metabolome with these patterns reflecting common genes and environmental cues. In this study, which included more than 2500 malt samples from more than 500 individual spring barley lines from the Nordic Seed breeding population, we show that whole-metabolomic data could be used to accurately predict malt quality phenotypes of individual lines and plots in spring barley. Correlations between predicted and observed phenotype were 0.78 for filtering speed, 0.51 for extraction yield, 0.85 for wort color, 0.82 for beta glucan, and 0.80 for viscosity. This demonstrated that patterns of metabolite abundances did reflect common genes and environmental cues.
Originalsprog | Engelsk |
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Publikationsdato | 2020 |
Status | Udgivet - 2020 |
Begivenhed | International Symposium of the Society for Plant Breeding (GPZ): Digital Breeding - Tulln, Østrig Varighed: 11 feb. 2020 → 13 feb. 2020 https://gpz2020.boku.ac.at/ |
Konference
Konference | International Symposium of the Society for Plant Breeding (GPZ) |
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Land/Område | Østrig |
By | Tulln |
Periode | 11/02/2020 → 13/02/2020 |
Internetadresse |