Metabotyping as a stopover in Genome-to-phenome Mapping

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Predicting phenotypic expression from genomic and environmental information is arguably the greatest challenge in today’s biology. Being able to survey genomic content, e.g., as single-nucleotide polymorphism data, within a diverse population and predict the phenotypes of external traits, represents the holy grail across genome-informed disciplines, from personal medicine and nutrition to plant breeding. In the present study, we propose a two-step procedure in bridging the genome to phenome gap where external phenotypes are viewed as emergent properties of internal phenotypes, such as molecular profiles, in interaction with the environment. Using biomass accumulation and shoot-root allometry as external traits in diverse genotypes of the model grass Brachypodium distachyon, we established correlative models between genotypes and metabolite profiles (metabotypes) as internal phenotypes, and between metabotypes and external phenotypes under two contrasting watering regimes. Our results demonstrate the potential for employing metabotypes as an integrator in predicting external phenotypes from genomic information.

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The Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) database was generated to mechanistically understand how feedbacks across scales, from molecular to plant to plant populations and communities to ecosystems, govern the resilience of system functions to elevated CO2...
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