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Unraveling yield-related traits with QTL analysis and dissection of QTL × environment interaction using a high-density bin map in rapeseed (Brassica napus. L)

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Abstract

According to the temperature and duration of the vernalization stage, three types of varieties adapted to different environments were bred in rapeseed breeding: spring, semi-winter, and winter type. Usually in a particular rapeseed producing area, only one type (spring or winter) is cultivated and almost none of the rapeseed varieties can adapt to both environments, which is mainly caused by the strong G × E, but how G × E affected yield-related traits is still unclear in rapeseed. In the present study, we tried to perform QTL mapping and dissect G × E into QTL × environments interactions (QTL × E) for seven yield traits in a DH population derived from No.2127 (a spring DH line) × ZY821 (a semi-winter cultivar) using a high-density SNP bin map. We described the impact of QTL × E on the genetic control of yield traits. Firstly, for the same trait of the same DH line, significant phenotypic difference for all the seven traits were observed when grown in the spring and semi-winter environment, respectively. Secondly, for five out of seven traits, the broad-sense heritability in the spring (adaptive) environment was higher over the semi-winter (stress) environment. Thirdly, total 74 non-redundant QTL including 26 consensus QTL and 48 trial-specific ones were detected, the positive additive effects of QTL were dispersed in both parents for all the seven traits. Among the 26 consensus QTL, eleven were specific to the spring or semi-winter environment, and the other 15 were common between the two environments, including four for flowering time (FT), and four for silique length (SL), 3 for thousand seed weight (TSW), each of them explained 6.4–26.1% of the phenotypic variation. Our results revealed that QTL × E for the seven yield-related traits mainly reflected by the environment-specific QTL, partly reflected by the same QTL with different expressions. These findings provided a better understanding of the genetic basis of QTL × E affected yield-related traits in rapeseed.

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Acknowledgements

This research was funded by the National Key Research and Development Program of China (2017YFD0101700), the National Natural Science Foundation of China (31301361, 31171589).

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Authors and Affiliations

  1. College of Agriculture, Yangtze University, Jingzhou, 434000, China

    Yanping Xie, Jinsong Xu & Xuekun Zhang

  2. Engineering Research Center of Ecology and Agricultural Use of Waterland, Ministry of Education, Yangtze University, Jingzhou, 434000, China

    Jinsong Xu & Xuekun Zhang

  3. College of Life Science, Yangtze University, Jingzhou, 434000, China

    Gang Tian, Lingli Xie & Benbo Xu

  4. National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China

    Kede Liu

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  1. Yanping Xie
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Contributions

YX, JX drafted manuscript and conducted experiment, XZ revised the manuscript, YX, JX, GT LX carried out analysis, BX provide reagents for experiments, YX GT collected phenotypic data, KL supervised the study.

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Correspondence to Jinsong Xu.

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Electronic supplementary material

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10681_2020_2708_MOESM1_ESM.xls

Supplemental table 1 (a): ANOVA for six yield-related traits in the spring environment. (b) ANOVA for seven yield-related traits in the semi-winter environment. (XLSX 20 kb)

10681_2020_2708_MOESM2_ESM.xls

Supplemental table 2 (a): Phenotypic correlation coefficients among traits for DH population in the two trials in the spring environment. (b) Phenotypic correlation coefficients among traits for DH population in the two trials in the semi-winter environment. (XLSX 19 kb)

10681_2020_2708_MOESM3_ESM.xls

Supplemental table 3 (a): The list of 108 original QTL identified in the four individual trials. (b) The list of the 57 unique-QTL obtained after meta-analysis of the 74 non-redundant QTL. (XLSX 73 kb)

10681_2020_2708_MOESM4_ESM.ppt

Supplemental figure 1: The main climate factors in the rapeseed growing period in 4 trails. (A1-A4) The changes of climatic factors, calculated monthly, in the two semi-winter microenvironments. Fine lines with different colors represent the different microenvironments. (B1-B4) The changes of climatic factors, calculated monthly, in the two spring microenvironments. Fine lines with different colors represent the different microenvironments. (PPT 270 kb)

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Xie, Y., Xu, J., Tian, G. et al. Unraveling yield-related traits with QTL analysis and dissection of QTL × environment interaction using a high-density bin map in rapeseed (Brassica napus. L). Euphytica 216, 171 (2020). https://doi.org/10.1007/s10681-020-02708-5

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