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作物学报 ›› 2021, Vol. 47 ›› Issue (11): 2121-2133.doi: 10.3724/SP.J.1006.2021.04249

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

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*()   

  1. 南京农业大学大豆研究所 / 国家大豆改良中心 / 农业农村部大豆生物学与遗传育种重点实验室(综合) / 作物遗传与种质创新国家重点实验室/江苏省现代作物生产协同创新中心, 江苏南京 210095
  • 收稿日期:2020-11-20 接受日期:2021-03-19 出版日期:2021-11-12 网络出版日期:2021-04-01
  • 通讯作者: 邢光南
  • 作者简介:E-mail: 2019101129@njau.edu.cn
  • 基金资助:
    国家重点研发计划项目(2016YFD0100201);国家自然科学基金项目(31571694);中央高校基本科研业务费专项资金(KYT201801);长江学者和创新团队发展计划(PCSIRT_17R55);高等学校学科创新引智基地项目111(B08025);国家现代农业产业技术体系(大豆)建设专项(CARS-04);江苏省优势学科建设工程专项和江苏省JCIC-MCP项目

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*()   

  1. Soybean Research Institute, Nanjing Agricultural University / National Center for Soybean Improvement / Key Laboratory for Biology and Genetic Improvement of Soybean (General), Ministry of Agriculture and Rural Affairs / National Key Laboratory for Crop Genetic and Germplasm Enhancement / Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, Jiangsu, China
  • Received:2020-11-20 Accepted:2021-03-19 Published:2021-11-12 Published online:2021-04-01
  • Contact: XING Guang-Nan
  • Supported by:
    National Key Research and Development Program of China(2016YFD0100201);National Natural Science Foundation of China(31571694);Fundamental Research Funds for Central Universities(KYT201801);MOE Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT_17R55);Project of Intellectual Base for Discipline Innovation in Colleges and Universities(B08025);China Agriculture Research System(CARS-04);iangsu Higher Education PAPD Program, and the Jiangsu JCIC-MCP Program

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摘要：

百粒重是影响大豆产量的重要农艺性状, 揭示其分子基础发掘关键候选基因对大豆改良具有重要意义。本研究通过对12个大豆品种籽粒发育3个时期共36个样本的转录组数据进行加权基因共表达网络分析(weighted gene co-expression network analysis, WGCNA), 得到20个基因共表达模块, 与百粒重及4个粒形性状关联后发现green模块与表型最为相关, 之后根据Gene Significance (GS)值和Eigengene Connectivity (kME)值筛选出13个green模块内的核心基因(hub gene); 然后对2组百粒重存在极显著差异的大豆品种的籽粒发育3个时期分别进行基因差异表达分析发现大豆在籽粒发育前中期可能通过MAPK信号通路调节百粒重大小; 之后对其进行SNPs/InDels挖掘并根据Gene Ontology (GO)注释发现green模块内的Glyma.14G043900和Glyma.15G217400由于SNP变异造成同义以及非同义突变, 且存在调控基因表达相关的GO Terms以及锌指结构域, 表明它们可能通过调控hub基因和差异表达基因调控大豆百粒重及粒形性状。Glyma.15G217400位于已报道的4个百粒重QTL中, 而Glyma.14G043900位于已报道的一个籽粒蛋白含量及一个油脂含量QTL中。通过比对大豆公共数据库发现这2个基因的百粒重增效等位变异受到人工选择, 其频率从野生大豆到地方品种再到育成品种的过程中逐渐升高。这些结果为进一步发掘大豆百粒重候选基因及其表达调控机制提供了新思路。

关键词: 大豆, 百粒重, 转录组学, WGCNA, 候选基因

Abstract:

100-seed weight of soybean is an important agronomic trait that affects yield, and it is of great significance to reveal its molecular basis and discover key candidate genes for soybean improvement breeding. In this study, weighted gene co-expression network analysis (WGCNA) was performed on the transcriptome data of 36 samples from 12 soybean varieties at three stages of seed development, and 20 gene co-expression modules were obtained. After correlating with 100-seed weight and four-seed shape traits, the green module was found to be most correlated with the phenotypes. Then 13 hub genes of green module were screened based on the Gene Significance (GS) and Eigengene Connectivity (kME) value. Gene differential expression of two groups of soybean varieties with extremely significant differences in 100-seed weight showed that the MAPK signaling pathway in the early and mid-term of seed development might regulate the 100-seed weight in soybean. According to SNPs/InDels calling and Gene Ontology (GO) annotation, Glyma.14G043900 and Glyma.15G217400 in the green module caused synonymous and non-synonymous coding mutations due to SNP mutations, and there were GO Terms and zinc finger domains related to gene expression regulation. These results suggested that they might regulate the 100-seed weight and seed shape of soybeans by regulating the hub gene and differentially expressed genes. Furthermore, Glyma.15G217400 was located in four reported QTLs of 100-seed weight, while Glyma.14G043900 was located in a reported seed protein content QTL and an oil content QTL. Compared with soybean public database, the increasing 100-seed weight alleles of the two genes were artificially selected and their frequency was gradually increased from wild accessions to landraces, resulting in the improved cultivars. These results provide new ideas for further discovering 100-seed weight candidate gene in soybean and its expression regulation mechanism.

Key words: soybean, 100-seed weight, transcriptomics, WGCNA, candidate gene

图1

软阈值β的确定 A图纵坐标是无尺度网络模型指数, 红线代表R2=0.85。B图纵坐标每一个软阈值对应的平均连接度。图A和图B的横坐标均代表软阈值β。"

表1

SNPs/InDels过滤标准"

SNPs过滤标准
SNPs filter standards		 InDels过滤标准
InDels filter standards
QualByDepth (QD) > 2.0 QualByDepth (QD) > 2.0
RMSMappingQuality (MQ) > 40.0 —
FisherStrand (FS) < 60.0 FisherStrand (FS) < 200.0
StrandOddsRatio (SOR) < 3.0 StrandOddsRatio (SOR) < 10.0
MappingQualityRankSumTest (MQRankSum) > -12.5 MappingQualityRankSumTest (MQRankSum) > -12.5
ReadPosRankSumTest (ReadPosRankSum) > -8.0 ReadPosRankSumTest (ReadPosRankSum) > -8.0

图2

12个大豆品种百粒重的箱型图 横坐标代表12个大豆品种, 纵坐标表示百粒重。一个点代表一次观察值。品种间不同大写字母说明百粒重基于Duncan氏新复极差法在P = 0.01水平的差异显著性。"

图3

模块内基因数目柱状图 横轴代表模块, 纵轴代表模块内基因数目。"

图4

模块与性状关联热图(A)及green模块内2904个基因的表达量热图(B) A图中横轴表示百粒重及粒形性状, 纵轴表示每一个模块的特征向量; 红色的格子代表性状与模块具有正相关性, 蓝色的格子代表性状与模块具有负相关性。B: green模块内2904个基因在12个大豆品种3个时期表达量行标准化后绘制。G、H和I分别为籽粒发育前期、中期和后期。"

图5

green模块内2904个基因的GO富集 横坐标(每列)代表富集基因占输入基因比例, 纵坐标(每行)代表GO Terms。点的大小代表富集的基因个数, 点的颜色代表经费舍尔精确测验矫正后的Padjust值。"

图6

百粒重存在极显著差异的2组大豆品种籽粒发育不同时期基因的表达差异(A)及小粒品种下调基因的MAPK信号通路富集图(B) G、H和I分别代表籽粒发育前期、中期和后期。Down-regulated genes代表小粒品种中下调的基因, Up-regulated genes代表小粒品种中上调的基因。"

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。"

图8

SNPs/InDels及DEGs在大豆染色体的分布图 A: SNPs密度; B: InDels密度; C: log2 (Fold Change) of DEGs, 内圈为在小粒品种组中显著上调基因, 外圈为下调基因。"

表2

SNPs/InDels分布区域"

变异位置
Variation region		 SNPs InDels
数目
Count		 比例
Percentage (%)		 数目
Count		 比例
Percentage (%)
DOWNSTREAM 41,636 23.67 5788 26.22
EXON 72,950 41.48 3028 13.72
INTERGENIC 2100 1.19 424 1.92
INTRON 8576 4.88 1625 7.36
SPLICE_SITE_ACCEPTOR 31 0.02 11 0.05
SPLICE_SITE_DONOR 31 0.02 12 0.05
SPLICE_SITE_REGION 334 0.19 69 0.31
TRANSCRIPT — — 1 0.01
UPSTREAM 29,780 16.93 4128 18.70
UTR_3_PRIME 14,683 8.35 4400 19.94
UTR_5_PRIME 5749 3.27 2586 11.72

表3

Green模块内在大粒和小粒品种组间存在非同义SNP突变的10个基因"

基因
Gene		 染色体
Chromosome		 位置
Position		 小粒品种组等位变异
Allele of small 100-SW		 大粒品种组等位变异
Allele of large 100-SW
Glyma.02G139500 Gm02 14480344 G A
Glyma.02G140100 Gm02 14531600 T C
Glyma.06G179600 Gm06 15246959 A G
Glyma.07G018200 Gm07 1456246 A G
Glyma.12G057100 Gm12 4156207 T C
Glyma.14G043900 Gm14 3335050 T C
Glyma.15G217400 Gm15 35930038 A T
Glyma.17G071400 Gm17 5580413 A G
Glyma.17G076400 Gm17 5974992 C T
Glyma.18G237000 Gm18 52573168 T C

表4

候选基因Glyma.14G043900和Glyma.15G217400的GO注释"

基因
Gene		 GO编号
GO ID		 GO类型
GO type		 注释描述
Annotation description
Glyma.14G043900 GO:0006355 生物过程
Biological process		 以DNA为模板的转录调控
Regulation of transcription, DNA-templated
GO:0008270 分子功能
Molecular function		 锌离子结合
Zinc ion binding
Glyma.15G217400 GO:0061158 生物过程
Biological process		 3'端非翻译区介导的mRNA失稳
3'-UTR-mediated mRNA destabilization
GO:0005829 细胞组分
Cellular component		 胞质溶胶
Cytosol
GO:0003730 分子功能
Molecular function		 mRNA 3'端非翻译区结合
mRNA 3'-UTR binding
GO:0046872 分子功能
Molecular function		 金属离子结合
Metal ion binding

图9

green模块内候选基因、hub基因以及差异表达基因的共表达网络 红色点代表候选基因, 黄色点代表hub基因, 绿色点代表DEGs, 蓝色点代表既是DEGs同时又是hub基因。线的颜色深浅代表基因间的weight值大小。黑色的线代表基因间的weight大于0.1, 灰色线代表基因间的weight小于0.1但大于0.01。"

图10

不同大豆类型中Glyma.14G043900和Glyma.15G217400非同义SNP突变等位变异的频率变化 圆点代表百粒重的增效等位变异, 而三角形代表百粒重的减效等位变异。"

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