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Beyond pathways: Accelerated flavonoids candidate identification and novel exploration of enzymatic properties using combined mapping populations of wheat.

Authors :
Chen, Jie
Zhang, Yueqi
Wei, Jiaqi
Hu, Xin
Yin, Huanran
Liu, Wei
Li, Dongqin
Tian, Wenfei
Hao, Yuanfeng
He, Zhonghu
Fernie, Alisdair R.
Chen, Wei
Source :
Plant Biotechnology Journal. Jul2024, Vol. 22 Issue 7, p2033-2050. 18p.
Publication Year :
2024

Abstract

Summary: Although forward‐genetics‐metabolomics methods such as mGWAS and mQTL have proven effective in providing myriad loci affecting metabolite contents, they are somehow constrained by their respective constitutional flaws such as the hidden population structure for GWAS and insufficient recombinant rate for QTL. Here, the combination of mGWAS and mQTL was performed, conveying an improved statistical power to investigate the flavonoid pathways in common wheat. A total of 941 and 289 loci were, respectively, generated from mGWAS and mQTL, within which 13 of them were co‐mapped using both approaches. Subsequently, the mGWAS or mQTL outputs alone and their combination were, respectively, utilized to delineate the metabolic routes. Using this approach, we identified two MYB transcription factor encoding genes and five structural genes, and the flavonoid pathway in wheat was accordingly updated. Moreover, we have discovered some rare‐activity‐exhibiting flavonoid glycosyl‐ and methyl‐transferases, which may possess unique biological significance, and harnessing these novel catalytic capabilities provides potentially new breeding directions. Collectively, we propose our survey illustrates that the forward‐genetics‐metabolomics approaches including multiple populations with high density markers could be more frequently applied for delineating metabolic pathways in common wheat, which will ultimately contribute to metabolomics‐assisted wheat crop improvement. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14677644
Volume :
22
Issue :
7
Database :
Academic Search Index
Journal :
Plant Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
177929411
Full Text :
https://doi.org/10.1111/pbi.14323