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Three‐dimensional genetic networks among seed oil‐related traits, metabolites and genes reveal the genetic foundations of oil synthesis in soybean
Author(s) -
Liu JinYang,
Li Pei,
Zhang YaWen,
Zuo JianFang,
Li Guo,
Han Xu,
Dunwell Jim M.,
Zhang YuanMing
Publication year - 2020
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.14788
Subject(s) - gene , biology , candidate gene , genetic variation , genetic association , genetics , amino acid , single nucleotide polymorphism , genotype
SUMMARY Although the biochemical and genetic basis of lipid metabolism is clear in Arabidopsis, there is limited information concerning the relevant genes in Glycine max (soybean). To address this issue, we constructed three‐dimensional genetic networks using six seed oil‐related traits, 52 lipid metabolism‐related metabolites and 54 294 SNPs in 286 soybean accessions in total. As a result, 284 and 279 candidate genes were found to be significantly associated with seed oil‐related traits and metabolites by phenotypic and metabolic genome‐wide association studies and multi‐omics analyses, respectively. Using minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) analyses, six seed oil‐related traits were found to be significantly related to 31 metabolites. Among the above candidate genes, 36 genes were found to be associated with oil synthesis (27 genes), amino acid synthesis (four genes) and the tricarboxylic acid (TCA) cycle (five genes), and four genes ( GmFATB1a , GmPDAT , GmPLDα1 and GmDAGAT1 ) are already known to be related to oil synthesis. Using this information, 133 three‐dimensional genetic networks were constructed, 24 of which 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 the rainfall from June to September, influence seed oil content across years. This study provides a new approach for the construction of three‐dimensional genetic networks and reveals new information for soybean seed oil improvement and the identification of gene function.