IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i7p667-d594625.html
   My bibliography  Save this article

Multi-Allelic Haplotype-Based Association Analysis Identifies Genomic Regions Controlling Domestication Traits in Intermediate Wheatgrass

Author

Listed:
  • Prabin Bajgain

    (Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA)

  • James A. Anderson

    (Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA)

Abstract

Intermediate wheatgrass (IWG) is a perennial forage grass undergoing a rigorous domestication as a grain crop. As a young grain crop, several agronomic and domestication traits need improvement for IWG to be relevant in current agricultural landscapes. This study genetically maps six domestication traits in the fourth cycle IWG breeding population at the University of Minnesota: height, seed length, seed width, shattering, threshability, and seed mass. A weak population structure was observed and linkage disequilibrium ( r 2 ) declined rapidly: 0.23 mega base pairs at conventional r 2 value of 0.2. Broad-sense heritabilities were overall high and ranged from 0.71–0.92. Association analysis was carried out using 25,909 single SNP markers and 5379 haplotype blocks. Thirty-one SNP markers and 17 haplotype blocks were significantly associated with the domestication traits. These associations were of moderate effect as they explained 4–6% of the observed phenotypic variation. Ten SNP markers were also detected by the haplotype association analysis. One SNP marker on Chromosome 8, also discovered in haplotype block analysis, was common between seed length and seed mass. Increasing the frequency of favorable alleles in IWG populations via marker-assisted selection and genomic selection is an effective approach to improve IWG’s domestication traits.

Suggested Citation

  • Prabin Bajgain & James A. Anderson, 2021. "Multi-Allelic Haplotype-Based Association Analysis Identifies Genomic Regions Controlling Domestication Traits in Intermediate Wheatgrass," Agriculture, MDPI, vol. 11(7), pages 1-15, July.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:667-:d:594625
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/7/667/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/7/667/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael D. Purugganan & Dorian Q. Fuller, 2009. "The nature of selection during plant domestication," Nature, Nature, vol. 457(7231), pages 843-848, February.
    2. Xiaolei Liu & Meng Huang & Bin Fan & Edward S Buckler & Zhiwu Zhang, 2016. "Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies," PLOS Genetics, Public Library of Science, vol. 12(2), pages 1-24, February.
    3. Jennifer Spindel & Hasina Begum & Deniz Akdemir & Parminder Virk & Bertrand Collard & Edilberto Redoña & Gary Atlin & Jean-Luc Jannink & Susan R McCouch, 2015. "Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic," PLOS Genetics, Public Library of Science, vol. 11(2), pages 1-25, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Siyu Zhang & Zhe Ji & Wu Jiao & Chengbo Shen & Yaojun Qin & Yunzhi Huang & Menghan Huang & Shuming Kang & Xuan Liu & Shunqi Li & Zulong Mo & Ying Yu & Bingyu Jiang & Yanan Tian & Longfei Wang & Qingxi, 2025. "Natural variation of OsWRKY23 drives difference in nitrate use efficiency between indica and japonica rice," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    2. repec:idb:brikps:64718 is not listed on IDEAS
    3. Guangbao Guo & Guoqi Qian & Lu Lin & Wei Shao, 2021. "Parallel inference for big data with the group Bayesian method," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(2), pages 225-243, February.
    4. Charles‐Elie Rabier & Simona Grusea, 2021. "Prediction in high‐dimensional linear models and application to genomic selection under imperfect linkage disequilibrium," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1001-1026, August.
    5. Matranga, Andrea, 2017. "The Ant and the Grasshopper: Seasonality and the Invention of Agriculture," MPRA Paper 76626, University Library of Munich, Germany.
    6. Eva Johansson & Faraz Muneer & Thomas Prade, 2023. "Plant Breeding to Mitigate Climate Change—Present Status and Opportunities with an Assessment of Winter Wheat Cultivation in Northern Europe as an Example," Sustainability, MDPI, vol. 15(16), pages 1-14, August.
    7. repec:plo:pone00:0243666 is not listed on IDEAS
    8. Brandon Schlautman & Spencer Barriball & Claudia Ciotir & Sterling Herron & Allison J. Miller, 2018. "Perennial Grain Legume Domestication Phase I: Criteria for Candidate Species Selection," Sustainability, MDPI, vol. 10(3), pages 1-23, March.
    9. Muhabbat Turdieva & Agnès Bernis-Fonteneau & Maira Esenalieva & Abdihalil Kayimov & Ashirmuhammed Saparmyradov & Khursandi Safaraliev & Kairkul Shalpykov & Paolo Colangelo & Devra I. Jarvis, 2024. "A Regional Perspective of Socio-Ecological Predictors for Fruit and Nut Tree Varietal Diversity Maintained by Farmer Communities in Central Asia," World, MDPI, vol. 5(1), pages 1-14, January.
    10. Serge Svizzero, 2017. "How the Neolithic Revolution Has Unfolded: Invention and Adoption or Change and Adaptation? Addressing the Diffusion Controversy about Initial Domestication," Working Papers hal-02145476, HAL.
    11. Ganwen Zhang & Jianini Zhao & Jieru Wang & Guo Lin & Lin Li & Fengfei Ban & Meiting Zhu & Yangjun Wen & Jin Zhang, 2024. "An Improved Expectation–Maximization Bayesian Algorithm for GWAS," Mathematics, MDPI, vol. 12(13), pages 1-14, June.
    12. Zhuangzhuang Hong & Zhankui Zeng & Jiaojiao Li & Xuefang Yan & Junqiao Song & Qunxiang Yan & Qiong Li & Yue Zhao & Chang Liu & Xueyan Jing & Chunping Wang, 2025. "Gene Mining and Genetic Effect Analysis Reveal Novel Loci, TaZn-2DS Associated with Zinc Content in Wheat Grain," Agriculture, MDPI, vol. 15(2), pages 1-16, January.
    13. Xubin Lu & Hui Jiang & Abdelaziz Adam Idriss Arbab & Bo Wang & Dingding Liu & Ismail Mohamed Abdalla & Tianle Xu & Yujia Sun & Zongping Liu & Zhangping Yang, 2023. "Investigating Genetic Characteristics of Chinese Holstein Cow’s Milk Somatic Cell Score by Genetic Parameter Estimation and Genome-Wide Association," Agriculture, MDPI, vol. 13(2), pages 1-17, January.
    14. Zhaoxuan Che & Jiakun Qiao & Fangjun Xu & Xinyun Li & Yunxia Zhao & Mengjin Zhu, 2024. "Integrated Analysis Reveals Genetic Basis of Growth Curve Parameters in an F 2 Designed Pig Population Based on Genome and Transcriptome Data," Agriculture, MDPI, vol. 14(10), pages 1-18, September.
    15. Muriel Gros-Balthazard & Claire Newton & Sarah Ivorra & Marie-Hélène Pierre & Jean-Christophe Pintaud & Jean-Frédéric Terral, 2016. "The Domestication Syndrome in Phoenix dactylifera Seeds: Toward the Identification of Wild Date Palm Populations," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-21, March.
    16. Md. S. Islam & Per McCord & Quentin D. Read & Lifang Qin & Alexander E. Lipka & Sushma Sood & James Todd & Marcus Olatoye, 2022. "Accuracy of Genomic Prediction of Yield and Sugar Traits in Saccharum spp. Hybrids," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
    17. Muhammad Junaid Zaghum & Kashir Ali & Sheng Teng, 2022. "Integrated Genetic and Omics Approaches for the Regulation of Nutritional Activities in Rice ( Oryza sativa L.)," Agriculture, MDPI, vol. 12(11), pages 1-17, October.
    18. Julien Frouin & Axel Labeyrie & Arnaud Boisnard & Gian Attilio Sacchi & Nourollah Ahmadi, 2019. "Genomic prediction offers the most effective marker assisted breeding approach for ability to prevent arsenic accumulation in rice grains," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-22, June.
    19. Alemayehu Teressa Negawo & Meki Shehabu Muktar & Ricardo Alonso Sánchez Gutiérrez & Ermias Habte & Alice Muchugi & Chris S. Jones, 2024. "A Genome-Wide Association Study of Biomass Yield and Feed Quality in Buffel Grass ( Cenchrus ciliaris L.)," Agriculture, MDPI, vol. 14(2), pages 1-27, February.
    20. Yusuke Toda & Hitomi Wakatsuki & Toru Aoike & Hiromi Kajiya-Kanegae & Masanori Yamasaki & Takuma Yoshioka & Kaworu Ebana & Takeshi Hayashi & Hiroshi Nakagawa & Toshihiro Hasegawa & Hiroyoshi Iwata, 2020. "Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.
    21. Thomas Kaczmarek & Philippe Cubry & Louis Champion & Sandrine Causse & Marie Couderc & Julie Orjuela & Edak A. Uyoh & Happiness O. Oselebe & Stephen N. Dachi & Charlotte O. A. Adje & Emmanuel Sekloka , 2025. "Independent domestication and cultivation histories of two West African indigenous fonio millet crops," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
    22. Lanzhi Li & Xingfei Zheng & Jiabo Wang & Xueli Zhang & Xiaogang He & Liwen Xiong & Shufeng Song & Jing Su & Ying Diao & Zheming Yuan & Zhiwu Zhang & Zhongli Hu, 2023. "Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:667-:d:594625. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.