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Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat

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Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered.

Abstract

Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (31671695 and 31501307) and the China 111 Project of the Ministry of Education of China (B12007).

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  1. Yang Yang and Aduragbemi Amo have contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China

    Yang Yang,  Aduragbemi Amo , Di Wei, Yongmao Chai, Jie Zheng, Pengfang Qiao, Chunge Cui, Shan Lu, Liang Chen & Yin-Gang Hu

  2. Institute of Water Saving Agriculture in Arid Regions of China, Northwest A&F University, Yangling, Shaanxi, China

    Yin-Gang Hu

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  1. Yang Yang
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Contributions

Y.G.H. and L.C. designed the experiment, Y.Y. and A.A. performed the experiment and wrote the paper, D.W., Y.C. and J.Z. collected the previous studies, P.Q., C.C. and S.L. analyzed the data, Y.G.H. and L.C. reviewed the paper. All authors read and approved the article.

Corresponding authors

Correspondence to Liang Chen or Yin-Gang Hu.

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All authors declare that they have no conflicts of interests.

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We declare that these experiments complied with the ethical standards in China.

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Communicated by Susanne Dreisigacker.

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Yang, Y., Amo , ., Wei, D. et al. Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. Theor Appl Genet 134, 3083–3109 (2021). https://doi.org/10.1007/s00122-021-03881-4

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