Three‐dimension genetic networks among seed oil‐related traits, metabolites and genes reveal the genetic foundations of oil synthesis in soybeanLiu, J.‐Y., Li, P., Zhang, Y.‐W., Zuo, J.‐F., Li, G., Han, X., Dunwell, J. M. ORCID: https://orcid.org/0000-0003-2147-665X and Zhang, Y.‐M. (2020) Three‐dimension genetic networks among seed oil‐related traits, metabolites and genes reveal the genetic foundations of oil synthesis in soybean. The Plant Journal, 103 (3). pp. 1103-1124. ISSN 0960-7412
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1111/tpj.14788 Abstract/SummaryAlthough the biochemical and genetic basis of lipid metabolism is clear in Arabidopsis, there is limited information concerning the relevant genes in soybean. To address this issue, here we constructed three-dimension genetic networks using six seed oil-related traits, fifty-two lipid-metabolism-related metabolites and 54,294 SNPs in at most 286 soybean accessions. As a result, 284 and 279 candidate genes were found by phenotypic and metabolic genome-wide association studies and multi-omics analyses, respectively, to be significantly associated with seed oil-related traits and metabolites; six seed oil-related traits were found by MCP and SCAD analyses to be significantly related to thirty-one metabolites. Among the above candidate genes, 36 genes were found to be associated with oil synthesis (27), amino acid synthesis (4) and TCA cycle (5), and four genes GmFATB1a, GmPDAT, GmPLDα1 and GmDAGAT1 are known oil-synthesis-related genes. Using the above information, 133 three-dimension genetic networks were constructed, in which 24 are known, e.g., pyruvate-GmPDAT-GmFATA2-oil content. Using these networks, GmPDAT, GmAGT and GmACP4 reveal the genetic relationships between pyruvate and the three major nutrients, and GmPDAT, GmZF351 and GmPgs1 reveal the genetic relationships between amino acids and seed oil content. In addition, GmCds1, along with average temperature in July and rainfall, influence seed oil content across years. This study provides a new approach for three-dimension network construction and new information for soybean seed oil improvement and gene function identification.
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