Genetic Variation for Seed Metabolite Levels in Brachypodium distachyon.

Yoshihiko Onda,Keiichi Mochida,Kotaro Takahagi,Yukiko Uehara-Yamaguchi,David F Garvin,Minami Shimizu,Yuji Sawada,Komaki Inoue,Masami Y Hirai

doi:10.3390/ijms20092348

Abstract

Metabolite composition and concentrations in seed grains are important traits of cereals. To identify the variation in the seed metabolotypes of a model grass, namely Brachypodium distachyon, we applied a widely targeted metabolome analysis to forty inbred lines of B. distachyon and examined the accumulation patterns of 183 compounds in the seeds. By comparing the metabolotypes with the population structure of these lines, we found signature metabolites that represent different accumulation patterns for each of the three B. distachyon subpopulations. Moreover, we found that thirty-seven metabolites exhibited significant differences in their accumulation between the lines Bd21 and Bd3-1. Using a recombinant inbred line (RIL) population from a cross between Bd3-1 and Bd21, we identified the quantitative trait loci (QTLs) linked with this variation in the accumulation of thirteen metabolites. Our metabolite QTL analysis illustrated that different genetic factors may presumably regulate the accumulation of 4-pyridoxate and pyridoxamine in vitamin B6 metabolism. Moreover, we found two QTLs on chromosomes 1 and 4 that affect the accumulation of an anthocyanin, chrysanthemin. These QTLs genetically interacted to regulate the accumulation of this compound. This study demonstrates the potential for metabolite QTL mapping in B. distachyon and provides new insights into the genetic dissection of metabolomic traits in temperate grasses.

Highlights

Cereal grains provide important nutrients in the human diet [1,2]
When we compared the accumulation patterns of 183 metabolites (Table S2) from these lines through partial least squares regression discriminant analysis (PLS-DA) analysis with the metabolotype datasets from our widely-targeted metabolome analysis, we found that the forty lines were again classified into two major groups, one of which could be further separated into two groups based on their metabolotypes
To identify metabolites whose accumulation patterns were related to the population groups, we examined the variable importance of projection (VIP) scores based on the results of PLS-DA and identified thirty-six metabolites with VIP scores of >1.5 for at least one of the three components (Figure 1C)

Summary

Introduction

Cereal grains provide important nutrients in the human diet [1,2]. grain quality is an agronomically important trait influenced by genetic factors, which are related to the metabolism of various phytochemicals in seeds [3]. Metabolite quantitative trait locus (mQTL) analysis and metabolite-based genome-wide association studies (mGWAS) have enabled us to identify relationships between genetic and metabolic variation [6,7] and have led to advances in the discovery of genes involved in metabolic pathways and their regulatory networks [8,9,10]. In plants, these genetic approaches combined with high-throughput metabolomics have allowed researchers to discover genes associated with an abundance of metabolites in model plants, such as Arabidopsis thaliana, and in various crop species (such as Beta vulgaris, Brassica napus, Brassica oleracea, Capsicum annuum, Cucumis melo or yza sativa, Prunus persica, Solanum lycopersicum, Solanum tuberosum, Triticum aestivum and Zea mays) [7,11]. To our knowledge, this variation in metabolite abundance has not been exploited to identify the genetic factors associated with metabolite abundance in temperate grasses

Methods

Results

Conclusion