利用动态转录组学挖掘大豆百粒重候选基因

曾健, 徐先超, 徐昱斐, 王秀成, 于海燕, 冯贝贝, 邢光南

Utilization of dynamic transcriptomics analysis for candidate gene mining of 100-seed weight in soybean

ZENG Jian, XU Xian-Chao, XU Yu-Fei, WANG Xiu-Cheng, YU Hai-Yan, FENG Bei-Bei, XING Guang-Nan

图7 green模块内hub基因GS值和kME值的柱形图(A)及不同百粒重大豆品种组间差异表达基因的表达量聚类热图(B) 100-SW: 百粒重; SA: 籽粒面积; SL: 籽粒长度; SP: 籽粒周长; SW: 籽粒宽度。G、H和I分别代表籽粒发育前期、中期和后期。Large和Small分别代表P = 0.01差异极显著的大粒大豆和小粒大豆品种组。图B中加粗的基因代表第1种表达模式的基因。

Fig. 7 Histogram of GS and kME value of hub gene in green module (A) and cluster heat map of differentially expressed genes among soybean varieties with different 100-seed weight (B) 100-SW: 100-seed weight; SA: seed area; SL: seed length; SP: seed perimeter; SW: seed width. G, H, and I represent the early stage, the middle stage, and the later stage of seed development, respectively. Large and Small represent large soybean varieties and small soybean varieties panel at P = 0.01, respectively. Gene in bold represents the first expression pattern in figure B.