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  1. Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis

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    Author(s): Hui Li; Adam Thrash; Juliet D. Tang; Linlin He; Jianbing Yan; Marilyn L. Warburton
    Date: 2019
    Source: The Plant Journal. 38: 1-11.
    Publication Series: Scientific Journal (JRNL)
    Station: Forest Products Laboratory
    DOI: https://doi.org/10.1111/tpj.14282
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    Description

    Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio-energy. Although this trait has been studied via conventional genome-wide association study (GWAS), the single nucleotide polymorphism (SNP)-trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP-trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl-lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl-lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high-oil maize genetic improvement.

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    Citation

    Li, Hui; Thrash, Adam; Tang, Juliet D.; He, Linlin; Yan, Jianbing; Warburton, Marilyn L. 2019. Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis . The Plant Journal. 38: 1-11.

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    Keywords

    Maize, lipid metabolism, pathway analysis, genome-wide association study

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