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Metabolome Analysis of Multi-Connected Biparental Chromosome Segment Substitution Line Populations1

Jie Chen,Jilin Wang,Wenqiang Sun,Meng Peng,Zhiyang Yuan,S. Shen,K. Xie,Cheng Jin,Yangyang Sun,Xianqing Liu,A. Fernie,Sibin Yu,Jie Luo

Published 2018 in Plant Physiology

ABSTRACT

Multi-biparental populations generate a large set of metabolite QTL (mQTL), and consolidation of a metabolic pathway may confer plant disease resistance activity. Metabolomic analysis coupled with advanced genetic populations represents a powerful tool with which to investigate the plant metabolome. However, genetic analyses of the rice (Oryza sativa) metabolome have been conducted mainly using natural accessions or a single biparental population. Here, the flag leaves from three interconnected chromosome segment substitution line populations with a common recurrent genetic background were used to dissect rice metabolic diversity. We effectively used multiple interconnected biparental populations, constructed by introducing genomic segments into Zhenshan 97 from ACC10 (A/Z), Minghui 63 (M/Z), and Nipponbare (N/Z), to map metabolic quantitative trait loci (mQTL). A total of 1,587 mQTL were generated, of which 684, 479, and 722 were obtained from the A/Z, M/Z, and N/Z chromosome segment substitution line populations, respectively, and we designated 99 candidate genes for 367 mQTL. In addition, 1,001 mQTL were generated specifically from joint linkage analysis with 25 candidate genes assigned. Several of these candidates were validated, such as LOC_Os07g01020 for the in vivo content of pyridoxine and its derivative and LOC_Os04g25980 for cis-zeatin glucosyltransferase activity. We propose a novel biosynthetic pathway for O-methylapigenin C-pentoside and demonstrated that LOC_Os04g11970 encodes a component of this pathway through fine-mapping. We postulate that the methylated apigenin may confer plant disease resistance. This study demonstrates the power of using multiple interconnected populations to generate a large number of veritable mQTL. The combined results are discussed in the context of functional metabolomics and the possible features of assigned candidates underlying respective metabolites.

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