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Genetic analysis of the metabolome exemplified using a rice population.

ABSTRACT: Plant metabolites are crucial for both plant life and human nutrition. Despite recent advance in metabolomics, the genetic control of plant metabolome remains largely unknown. Here, we performed a genetic analysis of the rice metabolome that provided over 2,800 highly resolved metabolic quantitative trait loci for 900 metabolites. Distinct and overlapping accumulation patterns of metabolites were observed and complex genetic regulation of metabolism was revealed in two different tissues. We associated 24 candidate genes to various metabolic quantitative trait loci by data mining, including ones regulating important morphological traits and biological processes. The corresponding pathways were reconstructed by updating in vivo functions of previously identified and newly assigned genes. This study demonstrated a powerful tool and provided a vast amount of high-quality data for understanding the plasticity of plant metabolome, which may help bridge the gap between the genome and phenome.

SUBMITTER: Gong L

PROVIDER: S-EPMC3864304 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Genetic analysis of the metabolome exemplified using a rice population.

Gong Liang L Chen Wei W Gao Yanqiang Y Liu Xianqing X Zhang Hongyan H Xu Caiguo C Yu Sibin S Zhang Qifa Q Luo Jie J

Proceedings of the National Academy of Sciences of the United States of America 20131120 50

Plant metabolites are crucial for both plant life and human nutrition. Despite recent advance in metabolomics, the genetic control of plant metabolome remains largely unknown. Here, we performed a genetic analysis of the rice metabolome that provided over 2,800 highly resolved metabolic quantitative trait loci for 900 metabolites. Distinct and overlapping accumulation patterns of metabolites were observed and complex genetic regulation of metabolism was revealed in two different tissues. We asso ...[more]

PMID: 24259710

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Project description:BackgroundWith an increasing world population and a gradual decline in the amount of arable land, food security remains a global challenge. Continued increases in rice yield will be required to break through the barriers to grain output. In order to transition from hybrid rice to super-hybrid rice, breeding demands cannot be addressed through traditional heterosis. Therefore, it is necessary to incorporate high yield loci from other rice genetic groups and to scientifically utilize intersubspecific heterosis in breeding lines. In this study, 781 lines from a segregating F2 population constructed by crossing the indica variety, "Giant Spike Rice" R1128 as trait donor with the japonica cultivar 'Nipponbare', were re-sequenced using high-throughout multiplexed shotgun genotyping (MSG) technology. In combination with high-density single nucleotide polymorphisms, quantitative trait locus (QTL) mapping and genetic effect analysis were performed for five yield factors (spikelet number per panicle, primary branches per panicle, secondary branches per panicle, plant height, and panicle length) to explore the genetic mechanisms underlying the formation of the giant panicle of R1128. Also, they were preformed to locate new high-yielding rice genetic intervals, providing data for super-high-yielding rice breeding.ResultsQTL mapping and genetic effect analysis for five yield factors in the population gave the following results: 49 QTLs for the five yield factors were distributed on 11 of 12 chromosomes. The super-hybrid line R1128 carries multiple major genes for good traits, including Sd1 for plant height, Hd1 and Ehd1 for heading date, Gn1a for spikelet number and IPA1 for ideal plant shape. These genes accounted for 44.3%, 21.9%, 6.2%, 12.9% and 10.6% of the phenotypic variation in the individual traits. Six novel QTLs, qph1-2, qph9-1, qpl12-1, qgn3-1, qgn11-1and qsbn11-1 are reported here for the first time.ConclusionsHigh-throughout sequencing technology makes it convenient to study rice genomics and makes the QTL/gene mapping direct, efficient, and more reliable. The genetic regions discovered in this study will be valuable for breeding in rice varieties because of the diverse genetic backgrounds of the rice.

Dataset Information

Genetic analysis of the metabolome exemplified using a rice population.

Publications

Genetic analysis of the metabolome exemplified using a rice population.

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