IDEAS home Printed from https://ideas.repec.org/a/caa/jnlcjg/v54y2018i3id98-2017-cjgpb.html
   My bibliography  Save this article

Detection of QTLs for cold tolerance at the booting stage in near-isogenic lines derived from rice landrace Lijiangxintuanheigu

Author

Listed:
  • Shu Ming YANG

    (Biotechnology and Genetic Resources Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, P.R. China)

  • Su Hua ZHANG

    (Biotechnology and Genetic Resources Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, P.R. China
    Agricultural Biotechnology Key Laboratory of Yunnan Province, Kunming, Yunnan, P.R. China)

  • Tao YANG

    (Biotechnology and Genetic Resources Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, P.R. China)

  • Li WANG

    (College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, Yunnan, P.R. China)

Abstract

Chilling damage significantly reduces grain yield in rice, while exploring major quantitative trait loci (QTLs) has the potential to improve rice production. Mapping of QTLs for 5 cold tolerance-related traits at the booting stage was conducted with SSR markers and inclusive composite interval mapping (ICIM) approach, based on 105 near-isogenic lines derived from a backcross between Lijiangxintuanheigu (LTH, cold-tolerant landrace) and Towada (cold-sensitive cultivar). Phenotype values were investigated under five cold-stress environments and analysed by the best linear unbiased prediction (BLUP). Twenty-one QTLs were identified on chromosomes 1, 2, 3, 4, 6, 7, 10 and 11, and the amount of variation (R2) explained by each QTL ranged from 7.71 to 29.66%, with five co-located QTL regions. Eight novel major loci (qSF-2, qSF-6a, qSF-7, qGW-6, qDGWP-4, qDSWPP-4, qDWPP-1 and qDWPP-4b) were detected in several environments and BLUP, and their alleles were contributed by LTH with R2 variance from 12.24 to 29.66%. These favourable QTLs would facilitate elucidation of the genetic mechanism of cold tolerance and provide strategies for breeding high-productive rice.

Suggested Citation

  • Shu Ming YANG & Su Hua ZHANG & Tao YANG & Li WANG, 2018. "Detection of QTLs for cold tolerance at the booting stage in near-isogenic lines derived from rice landrace Lijiangxintuanheigu," Czech Journal of Genetics and Plant Breeding, Czech Academy of Agricultural Sciences, vol. 54(3), pages 93-100.
    • Handle: RePEc:caa:jnlcjg:v:54:y:2018:i:3:id:98-2017-cjgpb
    DOI: 10.17221/98/2017-CJGPB
    as

    Download full text from publisher

    File URL: http://cjgpb.agriculturejournals.cz/doi/10.17221/98/2017-CJGPB.html
    Download Restriction: free of charge
    File URL: http://cjgpb.agriculturejournals.cz/doi/10.17221/98/2017-CJGPB.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.17221/98/2017-CJGPB?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Xu-Qing & Rong, Jian-Ying & Liu, Xiu-Ying, 2008. "Best linear unbiased prediction for linear combinations in general mixed linear models," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1503-1517, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shu Ming Yang & Fei Fei Zhang & Su Hua Zhang & Gui Yong Li & Li Qiong Zeng & Guan Suo Liu & Xiao Fen Yu & Xue Li Qiu, 2019. "QTL mapping of physiological traits at the booting stage in rice under low temperature combined with nitrogen fertilization," Czech Journal of Genetics and Plant Breeding, Czech Academy of Agricultural Sciences, vol. 55(4), pages 146-155.

    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. M. Revan Özkale & Funda Can, 2017. "An evaluation of ridge estimator in linear mixed models: an example from kidney failure data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2251-2269, September.
    2. Nesrin Güler & Melek Eriş Büyükkaya & Melike Yiğit, 2022. "Comparison of Covariance Matrices of Predictors in Seemingly Unrelated Regression Models," Indian Journal of Pure and Applied Mathematics, Springer, vol. 53(3), pages 801-809, September.
    3. S. J. Haslett & X. Q. Liu & A. Markiewicz & S. Puntanen, 2020. "Some properties of linear sufficiency and the BLUPs in the linear mixed model," Statistical Papers, Springer, vol. 61(1), pages 385-401, February.
    4. Yongge Tian, 2015. "A new derivation of BLUPs under random-effects model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(8), pages 905-918, November.
    5. Laura M. Grajeda & Lisa M. Thompson & William Arriaga & Eduardo Canuz & Saad B. Omer & Michael Sage & Eduardo Azziz-Baumgartner & Joe P. Bryan & John P. McCracken, 2020. "Effectiveness of Gas and Chimney Biomass Stoves for Reducing Household Air Pollution Pregnancy Exposure in Guatemala: Sociodemographic Effect Modifiers," IJERPH, MDPI, vol. 17(21), pages 1-14, October.
    6. Xiaojun Shi & Hiroshi Tsuji & Shunming Zhang, 2012. "Introducing Heterogeneity of Managers' Attitude into Behavioral Risk Scoring for Software Offshoring," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(3), pages 299-316, May.
    7. Liu, Xin & Wang, Qing-Wen, 2013. "Equality of the BLUPs under the mixed linear model when random components and errors are correlated," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 297-309.
    8. Liu, Xu-Qing & Wang, Dong-Dong & Rong, Jian-Ying, 2009. "Quadratic prediction and quadratic sufficiency in finite populations," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1979-1988, October.
    9. Dermoune, Azzouz & Rahmania, Nadji & Wei, Tianwen, 2012. "General linear mixed model and signal extraction problem with constraint," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 311-321.

    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:caa:jnlcjg:v:54:y:2018:i:3:id:98-2017-cjgpb. 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: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    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.