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

Authors: LI, HUI - Huazhong Agricultural University; THRASH, ADAM - Mississippi State University; TANG, JULIET - Forest Service (FS); HE, LINLIN - Huazhong Agricultural University; YAN, JIANBING - Huazhong Agricultural University; Warburton, Marilyn

Submitted to: Plant Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/4/2019
Publication Date: 2/9/2019
Citation: Li, H., Thrash, A., Tang, J., He, L., Yan, J., Warburton, M.L. 2019. Leveraging GWAS data to identify metabolic pathways and pathway networks involved in maize lipid biosynthesis. Plant Journal. 98(5):853-863. https://doi.org/10.1111/tpj.14282.
DOI: https://doi.org/10.1111/tpj.14282

Interpretive Summary: Maize oil is a valuable resource for human food, animal feed, and bio-energy. Molecular genetic mapping using new tools and techniques can identify which genes cause differences in oil level and composition, but some important genes may be missed. A complementary analysis, pathways analysis, identifies potentially overlooked genes by looking at how all the genes work together to create oil in the cells. Our pathway analysis of oil synthesis in corn found several different important ways that oil levels and composition is changed in a corn kernel, and these genes and synthesis pathways provide a real opportunity to efficiently manipulate high-oil maize genetic improvement.

Technical Abstract: Maize oil contains rich polyunsaturated fatty acids (FAs) and high energy, making maize oil a valuable resource for human food, animal feed, and bio-energy. Conventional genome-wide association study (GWAS), which is based on single nucleotide polymorphism (SNP)-trait associations, may miss 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 levels set for the false discovery rate and by insufficient numbers of high-frequency polymorphisms found in most panels. As a complementary analysis, pathways analysis emphasizes cumulative aspects of SNP-trait associations rather than just significance of single SNPs and was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. Our pathway analysis indicated that acyl-lipid pathways, including wax esters biosynthesis, sphingolipid biosynthesis, phospholipid biosynthesis and flavonoid biosynthesis were as important as FA and triacylglycerol (TAG) biosynthesis for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways that start with FAs and carbon partitioning pathways, were critical for decreasing FA content, changing FA ratios, and ultimately, to decreasing oil content. The newly identified pathways and pathway networks found in this study, and especially the acyl-lipid associated pathways, provide a real opportunity to efficiently manipulate high-oil maize genetic improvement. Keywords: Maize, Lipid metabolism, Pathway analysis, Genome-wide association study