Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

doi:10.1186/s12870-022-03677-8

CORC > 植物研究所 > 中国科学院植物研究所 > 中科院植物分子生理学重点实验室

	Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat
	Wei, Jun ; Fang, Yu ; Jiang, Hao ; Wu, Xing-ting ; Zuo, Jing-hong ; Xia, Xian-chun ; Li, Jin-quan ; Stich, Benjamin 2; Cao, Hong ; Liu, Yong-xiu
刊名	BMC PLANT BIOLOGY
	2022
卷号	22 期号:1
关键词	Grain size Pre-harvest sprouting Seed dormancy Seed vigor Spike length WGCNA Wheat
ISSN号	1471-2229
DOI	10.1186/s12870-022-03677-8
文献子类	Article
英文摘要	Background Wheat (Triticum aestivum L.) is an important cereal crop. Increasing grain yield for wheat is always a priority. Due to the complex genome of hexaploid wheat with 21 chromosomes, it is difficult to identify underlying genes by traditional genetic approach. The combination of genetics and omics analysis has displayed the powerful capability to identify candidate genes for major quantitative trait loci (QTLs), but such studies have rarely been carried out in wheat. In this study, candidate genes related to yield were predicted by a combined use of linkage mapping and weighted gene co-expression network analysis (WGCNA) in a recombinant inbred line population. Results QTL mapping was performed for plant height (PH), spike length (SL) and seed traits. A total of 68 QTLs were identified for them, among which, 12 QTLs were stably identified across different environments. Using RNA sequencing, we scanned the 99,168 genes expression patterns of the whole spike for the recombinant inbred line population. By the combined use of QTL mapping and WGCNA, 29, 47, 20, 26, 54, 46 and 22 candidate genes were predicted for PH, SL, kernel length (KL), kernel width, thousand kernel weight, seed dormancy, and seed vigor, respectively. Candidate genes for different traits had distinct preferences. The known PH regulation genes Rht-B and Rht-D, and the known seed dormancy regulation genes TaMFT can be selected as candidate gene. Moreover, further experiment revealed that there was a SL regulatory QTL located in an interval of about 7 Mbp on chromosome 7A, named TaSL1, which also involved in the regulation of KL. Conclusions A combination of QTL mapping and WGCNA was applied to predicted wheat candidate genes for PH, SL and seed traits. This strategy will facilitate the identification of candidate genes for related QTLs in wheat. In addition, the QTL TaSL1 that had multi-effect regulation of KL and SL was identified, which can be used for wheat improvement. These results provided valuable molecular marker and gene information for fine mapping and cloning of the yield-related trait loci in the future.
学科主题	Plant Sciences
出版地	LONDON
WOS关键词	GRAIN-SIZE ; RICE ; ASSOCIATION ; GENOMICS ; REVEALS
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
语种	英语
出版者	BMC
WOS记录号	WOS:000810684100002
资助机构	Strategic Priority Research Program of the Chinese Academy of Sciences [XDA24010104, XDA08010303] ; National Natural Science Foundation of China [U20A2033]
内容类型	期刊论文
源URL	[http://ir.ibcas.ac.cn/handle/2S10CLM1/28733]
专题	中科院植物分子生理学重点实验室
作者单位	1.Chinese Acad Agr Sci, Natl Wheat Improvement Ctr, Inst Crop Sci, Beijing, Peoples R China 2.Strube Res GmbH & Co KG, D-38387 Sollingen, Germany 3.Heinrich Heine Univ, Inst Quantitat Genet & Genom Plants, Dusseldorf, Germany 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Bot, Key Lab Plant Mol Physiol, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Wei, Jun,Fang, Yu,Jiang, Hao,et al. Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat[J]. BMC PLANT BIOLOGY,2022,22(1).
APA	Wei, Jun.,Fang, Yu.,Jiang, Hao.,Wu, Xing-ting.,Zuo, Jing-hong.,...&Liu, Yong-xiu.(2022).Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat.BMC PLANT BIOLOGY,22(1).
MLA	Wei, Jun,et al."Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat".BMC PLANT BIOLOGY 22.1(2022).