State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China.
Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.
Plant J. 2020 Aug;103(3):1103-1124. doi: 10.1111/tpj.14788. Epub 2020 May 29.
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.
尽管拟南芥中脂质代谢的生化和遗传基础已经很清楚，但关于大豆（Glycine max）中相关基因的信息却很有限。为了解决这个问题，我们使用 286 个大豆品系的 6 个种子油相关性状、52 种脂质代谢相关代谢物和 54294 个 SNP，构建了三维遗传网络。结果，通过表型和代谢全基因组关联研究以及多组学分析，分别发现了 284 个和 279 个候选基因与种子油相关性状和代谢物显著相关。使用极小极大凹惩罚（MCP）和光滑截断绝对偏差（SCAD）分析，发现 6 个种子油相关性状与 31 种代谢物显著相关。在上述候选基因中，有 36 个基因与油合成（27 个基因）、氨基酸合成（4 个基因）和三羧酸（TCA）循环（5 个基因）有关，其中 4 个基因（GmFATB1a、GmPDAT、GmPLDα1 和 GmDAGAT1）已经与油合成有关。利用这些信息，构建了 133 个三维遗传网络，其中 24 个是已知的，例如丙酮酸-GmPDAT-GmFATA2-油含量。利用这些网络，GmPDAT、GmAGT 和 GmACP4 揭示了丙酮酸与三大营养素之间的遗传关系，GmPDAT、GmZF351 和 GmPgs1 揭示了氨基酸与种子油含量之间的遗传关系。此外，GmCds1 与 7 月平均气温和 6 月至 9 月的降雨量一起，影响多年来的种子油含量。本研究为构建三维遗传网络提供了一种新方法，并为大豆种子油改良和基因功能鉴定提供了新信息。
