A Highly Specific Genome-Wide Association Study Integrated with Transcriptome Data Reveals the Contribution of Copy Number Variations to Specialized Metabolites in Arabidopsis thaliana Accessions
Author(s) -
Kazumasa Shirai,
Fumio Matsuda,
Ryo Nakabayashi,
Masanori Okamoto,
Maho Tanaka,
Akihiro Fujimoto,
Minami Shimizu,
Kazuo Shinozaki,
Motoaki Seki,
Kazuki Saito,
Kousuke Hanada
Publication year - 2017
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/msx234
Subject(s) - biology , metabolome , gene duplication , arabidopsis thaliana , genome , genetics , gene , copy number variation , transcriptome , quantitative trait locus , genome wide association study , metabolite , computational biology , evolutionary biology , metabolomics , single nucleotide polymorphism , gene expression , bioinformatics , genotype , mutant , biochemistry
Lineage-specific gene duplications contribute to a large variation in specialized metabolites among different plant species. There is also considerable variability in the specialized metabolites within a single plant species. However, it is unclear whether copy number variations (CNVs) derived from gene duplication events contribute to the diversity of specialized metabolites within species. We identified metabolome quantitative trait genes (mQTGs) associated with quantitative metabolite variations and examined the relationship between mQTGs and CNVs. We obtained 1,335 specialized metabolite signals from 53 worldwide A. thaliana accessions using liquid chromatography-quadrupole time-of-flight mass spectrometry. In this study, genes associated with specialized metabolites were inferred by either a generally authorized genome-wide association study (GWAS) approach or a novel analysis of the association between gene expression and metabolite accumulation. Genes qualified by both analyses are defined to be mQTGs. The integrated method enabled us to detect mQTGs with a low false positive rate (=5.71 × 10-4). We also identified 5,654 genes associated with 1,335 specialized metabolites. Of these genes, 4.4% were affected by CNVs, which was more than expected (χ2 test: P < 0.01). This result suggests that CNVs contribute to variations in specialized metabolites within a species. To assess the contribution of CNVs to adaptive evolution in A. thaliana, we examined the selective sweeps around the mQTGs. We observed that the mQTGs with CNVs tended to undergo selective sweeps. These observations imply that variations in specialized metabolites caused by CNVs contribute to the adaptive evolution of A. thaliana.
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