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

Author:

Chen Jie123,Zhang Yueqi12,Wei Jiaqi124,Hu Xin12,Yin Huanran12,Liu Wei12,Li Dongqin1,Tian Wenfei5,Hao Yuanfeng5,He Zhonghu5,Fernie Alisdair R.6ORCID,Chen Wei12ORCID

Affiliation:

1. National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan) Huazhong Agricultural University Wuhan China

2. Hubei Hongshan Laboratory Wuhan China

3. Yazhouwan National Laboratory Sanya China

4. Wuhan Academy of Agricultural Sciences Wuhan China

5. National Wheat Improvement Center, Institute of Crop Sciences Chinese Academy of Agricultural Sciences Beijing China

6. Max‐Planck‐Institute of Molecular Plant Physiology Potsdam‐Golm Germany

Abstract

SummaryAlthough 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.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Wiley

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