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A quantitative genomics map of rice provides genetic insights and guides breeding

Nature Genetics volume 53, pages 243–253 (2021)Cite this article

Abstract

Extensive allelic variation in agronomically important genes serves as the basis of rice breeding. Here, we present a comprehensive map of rice quantitative trait nucleotides (QTNs) and inferred QTN effects based on eight genome-wide association study cohorts. Population genetic analyses revealed that domestication, local adaptation and heterosis are all associated with QTN allele frequency changes. A genome navigation system, RiceNavi, was developed for QTN pyramiding and breeding route optimization, and implemented in the improvement of a widely cultivated indica variety. This work presents an efficient platform that bridges ever-increasing genomic knowledge and diverse improvement needs in rice.

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Fig. 1: Genotype matrix of 225 QTGs for a collection of 404 rice accessions.
Fig. 2: GWAS loci associated with important agronomic traits summarized from eight GWAS cohorts.
Fig. 3: Genomic distribution and linkage drag for QTGs in rice genome.
Fig. 4: Genetic investigation of the QTNs.
Fig. 5: Benchmarking for different backcrossing breeding designs.
Fig. 6: A schematic diagram for RiceNavi implementation and user operation.
Fig. 7: Improvement of the Huanghuazhan cultivar by implementation of RiceNavi.

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Data availability

The raw DNA sequencing data of the QTN library are deposited with GenBank under the bioproject accession no. PRJNA623686. A web-based version of RiceNavi is available from the website http://www.xhhuanglab.cn/tool/RiceNavi.html (supporting most browsers including Chrome, Firefox and Safari, but not Internet Explorer). In this web-based application, all functions in RiceNavi (QTNmap, QTNpick, Simulation and SampleSelect) can be accessed with user-friendly graphical interfaces.

Code availability

The source code of RiceNavi is available from both our laboratory website (http://www.xhhuanglab.cn/tool/RiceNavi.html) and the GitHub repository (https://github.com/xhhuanglab/RiceNavi). The other codes for the QTN-related analyses are also provided in the GitHub repository (https://github.com/xhhuanglab/QTN_scripts).

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Acknowledgements

We are grateful to the China National Rice Research Institute, Institute of Crop Sciences of Chinese Academy of Agricultural Sciences, Institute of Plant Protection of Chinese Academy of Agricultural Sciences, Chinese Academy of Sciences Center for Excellence of Molecular Plant Sciences and Huazhong Agricultural University for providing valuable rice varieties (see Supplementary Dataset 2 for details). We thank P. Xu and J. Murray for their advice and assistance in the paper writing. This work was funded by the National Natural Science Foundation of China (grant nos. 91935301 and 31825015), Innovation Program of Shanghai Municipal Education Commission (grant no. 2017-01-07-00-02-E00039) and Program of Shanghai Academic Research Leader (grant no. 18XD1402900) to X.H. and the US National Science Foundation (Plant Genome Research Program, IOS-1947609) to K.M.O.

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Author notes

  1. These authors contributed equally: Xin Wei, Jie Qiu.

Authors and Affiliations

  1. Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China

    Xin Wei, Jie Qiu, Kaicheng Yong, Jiongjiong Fan, Qi Zhang, Hua Hua, Jie Liu, Qin Wang & Xuehui Huang

  2. Department of Biology, Washington University in St Louis, St Louis, MO, USA

    Kenneth M. Olsen

  3. National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China

    Bin Han

Authors
  1. Xin Wei
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Contributions

X.H. designed these studies and contributed to the original concept of the project. X.W., K.Y., J.F., Q.Z. and H.H. contributed to the collection, planting and phenotyping of the QTN library. Q.W. and J.L. performed the genome sequencing of the QTN library and breeding populations. J.Q., X.W. and X.H. performed QTN analysis, developed the RiceNavi system and implemented RiceNavi in practical breeding. X.H., J.Q., X.W., K.M.O. and B.H. analyzed the data and wrote the paper.

Corresponding author

Correspondence to Xuehui Huang.

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Competing interests

A patent on the QTN-based breeding selection method has been filed by Shanghai Normal University with X.H., X.W. and J.Q. as inventors. The remaining authors declare no competing interests.

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Peer review information Nature Genetics thanks Makoto Matsuoka and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Wei, X., Qiu, J., Yong, K. et al. A quantitative genomics map of rice provides genetic insights and guides breeding. Nat Genet 53, 243–253 (2021). https://doi.org/10.1038/s41588-020-00769-9

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