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Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

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Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes.

Abstract

Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3–8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2–6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

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Acknowledgements

The authors would also like to express appreciation to Klaus Strenzke, Joseph Moss, Izabela Ciechnowska, Fabiana Dias, Katherine Chabot, Tom Keady, and Russel Puk for their technical support with phenotypic data collection in both conventional and organic management.

Funding

This study was supported by grants to the University of Alberta wheat breeding program from the Alberta Crop Industry Development Fund (ACIDF), Alberta Wheat Commission (AWC), Saskatchewan Wheat Development Commission (Sask Wheat), Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery and Collaborative Grant, Agriculture, and Agri-Food Canada (AAFC), Western Grains Research Foundation Endowment Fund (WGRF), and Core Program Check-off funds to DS.

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Authors and Affiliations

  1. Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada

    Kassa Semagn, Muhammad Iqbal, Hua Chen, Enid Perez-Lara, Darcy H. Bemister, Rongrong Xiang, Jun Zou, Muhammad Asif, Atif Kamran & Dean Spaner

  2. Department of Agronomy, School of Life Science and Engineering, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang, 621010, Sichuan, China

    Hua Chen

  3. Department of Agronomy, 2004 Throckmorton Plant Science Center, Kansas State University, Manhattan, KS, 66506, USA

    Muhammad Asif

  4. Heartland Plant Innovations, Kansas Wheat Innovation Center, 1990 Kimball Avenue, Manhattan, KS, 66502, USA

    Muhammad Asif

  5. Department of Botany, Seed Centre, The University of Punjab, New Campus, Lahore, 54590, Pakistan

    Atif Kamran

  6. Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada

    Amidou N’Diaye & Curtis Pozniak

  7. Agriculture, and Agri-Food Canada, 5403-1st Avenue South, Lethbridge, AB, T1J 4B1, Canada

    Harpinder Randhawa & Brian L. Beres

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  1. Kassa Semagn
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  2. Muhammad Iqbal
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  3. Hua Chen
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  10. Amidou N’Diaye
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  13. Curtis Pozniak
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  14. Dean Spaner
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Contributions

KS conceptualize the work, curated and analyzed the data, and wrote the paper. MI supervised the field data collection, contributed on data curation and analyses, and edited the paper. HC, EP, DHB, JZ, RX, MA, AK, HR, BLB, AN, and CP were involved in data generation and edited the paper. DS conceptualize the project, acquired funding, supervised the project, and edited the paper.

Corresponding author

Correspondence to Dean Spaner.

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The authors declare no competing interest.

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Communicated by Aimin Zhang.

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Semagn, K., Iqbal, M., Chen, H. et al. Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems. Theor Appl Genet 134, 3699–3719 (2021). https://doi.org/10.1007/s00122-021-03923-x

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