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Genetic control and phenotypic characterization of panicle architecture and grain yield-related traits in foxtail millet (Setaria italica)

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Multi-environment QTL mapping identified 23 stable loci and 34 co-located QTL clusters for panicle architecture and grain yield-related traits, which provide a genetic basis for foxtail millet yield improvement.

Abstract

Panicle architecture and grain weight, both of which are influenced by genetic and environmental factors, have significant effects on grain yield potential. Here, we used a recombinant inbred line (RIL) population of 333 lines of foxtail millet, which were grown in 13 trials with varying environmental conditions, to identify quantitative trait loci (QTL) controlling nine agronomic traits related to panicle architecture and grain yield. We found that panicle weight, grain weight per panicle, panicle length, panicle diameter, and panicle exsertion length varied across different geographical locations. QTL mapping revealed 159 QTL for nine traits. Of the 159 QTL, 34 were identified in 2 to 12 environments, suggesting that the genetic control of panicle architecture in foxtail millet is sensitive to photoperiod and/or other environmental factors. Eighty-eight QTL controlling different traits formed 34 co-located QTL clusters, including the triple QTL cluster qPD9.2/qPL9.5/qPEL9.3, which was detected 23 times in 13 environments. Several candidate genes, including Seita.2G388700, Seita.3G136000, Seita.4G185300, Seita.5G241500, Seita.5G243100, Seita.9G281300, and Seita.9G342700, were identified in the genomic intervals of multi-environmental QTL or co-located QTL clusters. Using available phenotypic and genotype data, we conducted haplotype analysis for Seita.2G002300 and Seita.9G064000,which showed high correlations with panicle weight and panicle exsertion length, respectively. These results not only provided a basis for further fine mapping, functional studies and marker-assisted selection of traits related to panicle architecture in foxtail millet, but also provide information for comparative genomics analyses of cereal crops.

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Acknowledgements

We thank Dr. Jin Gao helped in data analysis. This work was supported by National Key R&D Program of China (grant nos. 2019YFD1000700, and 2019YFD1000701), China Agricultural Research System (CARS06-13.5), National Natural Science foundation of China (31871630), China Postdoctoral Science Foundation (2018M641553), the Agricultural Science and Technology Innovation Program of CAAS (ICS2020YJ08BX-2), and the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences.

Funding

This work was supported by National Key R&D Program of China (grant nos. 2019YFD1000700, and 2019YFD1000701), China Agricultural Research System (CARS06-13.5), National Natural Science foundation of China (31871630), China Postdoctoral Science Foundation (2018M641553), the Agricultural Science and Technology Innovation Program of CAAS (ICS2020YJ08BX-2), and the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences.

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  1. Hui Zhi and Qiang He have contributed equally to this work.

Authors and Affiliations

  1. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian, Beijing, 100081, China

    Hui Zhi, Qiang He, Sha Tang, Junjun Yang, Wei Zhang, Huifang Liu, Yanchao Jia, Guanqing Jia, Jun Liu & Xianmin Diao

  2. Institute of Millet Crops, Shanxi Agricultural University, Changzhi, 046000, Shanxi, China

    Aiying Zhang, Yuhui Li & Erhu Guo

  3. Institute of Crop Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, Jilin, China

    Ming Gao & Shujie Li

  4. Cereal Crops Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China

    Junxia Li, Na Qin, Cancan Zhu & Chunye Ma

  5. Institute of Dry-Land Agriculture and Forestry, Liaoning Academy of Agricultural Sciences, Chaoyang, 122000, Liaoning, China

    Haijin Zhang, Guoqiu Chen & Wenfei Zhang

  6. Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, 030031, Shanxi, China

    Haigang Wang & Zhijun Qiao

  7. Institute of Millet Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, 050035, China

    Shunguo Li & Ruhong Cheng

  8. Anyang Academy of Agricultural Sciences, Anyang, 455000, Henan, China

    Lu Xing, Suying Wang & Jinrong Liu

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  1. Hui Zhi
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Contributions

HZ and QH did data analysis and drafted the manuscript. XD and HZ designed the experiment, developed the RIL population, and revised the manuscript. JL helped in the data analysis and discussion. ST, JY, WZ, HL, YJ, GJ, AZ, YL, EG, MG, SL, JL, NQ, CZ, CM, HZ, GC, WZ, HW, ZQ, SL, RC, LX, SW, and JL collected the phenotype. All authors have read and approved the final manuscript.

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Correspondence to Xianmin Diao.

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Zhi, H., He, Q., Tang, S. et al. Genetic control and phenotypic characterization of panicle architecture and grain yield-related traits in foxtail millet (Setaria italica). Theor Appl Genet 134, 3023–3036 (2021). https://doi.org/10.1007/s00122-021-03875-2

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