Skip to main content

Advertisement

Log in

QTL analysis of drought tolerance traits in rice during the vegetative growth period

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

Drought affects the growth and development of rice from direct seeding or transplanting to maturity in northern China. It is important to carry out QTL mapping for drought tolerance to improve rice breeding. In this study, a rice RIL population consisting of 253 families was constructed by crossing Miyang 23 with Jileng 1. The leaf rolling index (LRI), leaf withering degree (LWD) and leaf chlorophyll content (LCC) were measured over three years, and QTLs for these traits were mapped. The results showed that LRI, LWD and LCC were all quantitative traits controlled by multiple genes. A total of 28 QTLs related to three drought-resistant indices were detected; four QTLs controlling LRI and LWD were detected on Chromosome 1. qLRI1-1 and qLWD1-4 were located in the interval of AH01001843-RM302, explaining 10.30% and 4.90% of the phenotypic variation, respectively; qLWD1-2B and qLRI-1JC were both located in RM315-S01167A, and qLWD1-2B was explained 11.15% of the phenotypic variation, while qLRI-1JC explained 7.96% of the phenotypic variation. The two QTLs located on Chromosome 5, qLWD5-1B and qLRI5, were located in CMB0526.3486-RM87. qLWD5-1B explained 6.93% of the phenotypic variation, while qLRI5 explained 8.79%-9.13% of the phenotypic variation. The two QTLs detected on Chromosome 12, qLWD12 and qLRI12, were located in the S12099-CMB1226.0 interval and explained 4.59%-7.25% of the phenotypic variation. The above QTLs, including qLWD1-2B, qLRI1-1JC, qLWD5-1B and qLRI5, have been detected many times. Future work should involve implementing in-depth fine mapping of these QTLs and using the identified markers in the drought resistance molecular marker selection breeding of rice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

All data included in this study are available upon request. Please contact with the corresponding author.

References

  • Ali M, Pathan M, Zhang J, Bai G, Sarkarung S, Nguyen H (2000) Mapping QTLs for root traits in a recombinant inbred population from two indica ecotypes in rice. Theor Appl Genet 101:756–766

    Article  CAS  Google Scholar 

  • Babu RC, Nguyen BD, Chamarerk V et al (2003) Genetic analysis of drought resistance in rice by molecular markers: association between secondary traits and field performance. Crop Sci 43(4):1457–1469

    Article  CAS  Google Scholar 

  • Bing H, Wang J, Li YF, Ma XD et al (2018) Identification of quantitative trait loci associated with drought tolerance traits in rice (Oryza sativa L.)under PEG and field drought stress. Euphytica 214:74

    Article  Google Scholar 

  • Champoux MC, Wang G, Sarkarung S et al (1995) Locating genes associated with root morphology and drought avoidance in rice via linkage to molecular markers. Theor Appl Genet 90:969–981

    Article  CAS  PubMed  Google Scholar 

  • Courtois B, McLaren G, Sinha PK et al (2000) Mapping QTLs associated with drought avoidance in upland rice. Mol Breed 6:55–66

    Article  CAS  Google Scholar 

  • Dixit S, Huang BE, Sta Cruz MT, Maturan PT, Ontoy JC, Kumar A (2014) QTLs for tolerance of drought and breeding for tolerance of abiotic and biotic stress: an integrated approach. PLoS ONE 9(10):e109574

    Article  PubMed  PubMed Central  Google Scholar 

  • Han B, Wang J, Liu YF et al (2018) Identification of quantitative trait loci associated with drought tolerance traits in rice (OryzasativaL.) under PEG and field drought stress. Euphytica 214:74. https://doi.org/10.1007/s10681-018-2138-y

  • Hemamalini G, Shashidhar H, Hittalmani S (2000) Molecular marker assisted tagging of morphological and physiological traits under two contrasting moisture regimes at peak vegetative stage in rice(Oryza sativa L.). Euphytica 112:69–78

    Article  CAS  Google Scholar 

  • Jiang X, Ma XS, Luo LJ, Liu HY (2016) QTL mapping of phenotypic traits under drought stress simulated by PEG-6000 in Rice Seed lings. Crops 5:31–37. https://doi.org/10.16035/j.issn.1001-7283.2016.05.006

  • John ME (1992) An effificient method for isolation of RNA and DNA from plants containing polyphenolics. Nucleic Acid Res 20(9):2381

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kadioglu A, Terzi R (2007) A dehydration avoidance mechanism: leaf rolling. Bot Rev 73:290–302

    Article  Google Scholar 

  • Kadioglu A, Terzi R, Saruhan N, Saglam A (2012) Current advances in the investigation of leaf rolling caused by biotic and abiotic stress factors. Plant Sci 182:42–48

    Article  CAS  PubMed  Google Scholar 

  • Kuang Y Xia ST (2007) Effects of drought on growth and development and approachs to promoting drought resistance of rice. Beijing Agric 36:8–14

  • Li ZC, Mu P, Li CP, Zhang HL, Li ZK, Gao YM, Wang XK (2005) QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments. Theor Appl Genet 110:1244–1252

    Article  CAS  PubMed  Google Scholar 

  • Li HH, Ye GY, Wang JK (2007) A modified algorithm for the improvement of composite interval mapping. Genetics 175:361–374. https://doi.org/10.1534/genetics.106.066811

    Article  PubMed  PubMed Central  Google Scholar 

  • Li HH, Zhang LY, Wang JK (2010) Analysis and answers to frequently asked questions in quantitative trait locus mapping. Acta Agron Sin 36(6):918–931

    Article  Google Scholar 

  • Li C, Zou X, Zhang C, Shao Q, Liu J, Liu B et al (2016) OsLBD3–7 over expression induced adaxially rolled leaves in rice. PLoS ONE 11(6):e0156413

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu YQ, Zhao HW, Wang JG, Liu HL, Wang J, Jia Y (2013) QTL mapping for rice seed ling morphological traits under simulated drought stress conditions. Crops. https://doi.org/10.16035/j.issn.1001-7283.2013.02.035

  • Luo JJ Huang W, Zhu DL Lin HX (2005) QTLmapping of drought-resistance of cultivated rice. Plant Physiol 41(2):260–268

  • MaCouch SR, Cho YG, Yang M et al (1997) Report on QTL nomenclature. Rice Gene Newslett 14:11–13

    Google Scholar 

  • Nie YY, Cai YH, Fu H et al (2011) QTL mapping of drought-resistant traits of cultivated rice and research advance in molecular breeding. Acta Agric Jiangxi 23(7):89–92

    Google Scholar 

  • Ooijen JV, Ooijen JV, Verlaat JV, Ooijen J, Tol JV, Dalen J, Buren J, Meer JVD, Krieken JV, Ooijen J, Kessel JV, Van O, Voorrips R, Heuvel LVD (2006) JoinMap®4, Software for the calculation of genetic linkage maps in experimental populations. In: Kyazma BV (ed) Wageningen. Netherlands

  • Price AH, Townend J, Jones MP et al (2002) Mapping QTLs associated with drought avoidance in upland rice grown in the Philippines and West Africa. Plant Mol Biol. https://doi.org/10.1023/A:1014805625790

    Article  PubMed  Google Scholar 

  • Ray JD, Yu L, McCouch SR et al (1996) Mapping quantitative trait loci associated with root penetration ability in rice(Oryza sativa L.). Theor Appl Genet 92:627–636

    Article  CAS  PubMed  Google Scholar 

  • Richards RA, Rebetzke GJ, Condon AG, van Herwaarden AF (2002) Breeding opportunities for increasing the efficiency of water use and crop yield in temperate cereals. Crop Sci 42:111–121

    Article  PubMed  Google Scholar 

  • Robin S, Pathan MS, Courtois B et al (2003) Mapping osmotic adjustment in an advanced backcross inbred population of rice. Theor Appl Genet 107(7):1288–1296

    Article  CAS  PubMed  Google Scholar 

  • Singh R, Singh Y, Xalaxo S, Verulkar S, Yadav N, Singh S et al (2016) From QTL to variety-harnessing the benefits of QTLs for drought, flood and salt tolerance in mega rice varieties of India through a multi-institutional network. Plant Sci 242:278–287

    Article  CAS  PubMed  Google Scholar 

  • Song PH, Zheng GW, Ling Z et al (2017) Correlation analysis and gene identification for chlorophyll content and photosynthetic rate in rice leaves under drought stress. Chin J Biochem Mol Biol 11:926–932. https://doi.org/10.13865/j.cnki.cjbmb.2007.11.013

  • Spitzer M, Wildenhain J, Rappsilber J, Tyers M (2014) Box Plot R: a web tool for generation of box plots. Nat Methods 11(2):121–122

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Turner NC (1997) Further progress in crop water relations. Adv Agron 58:293–339

    Article  Google Scholar 

  • Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93(1):77–78

    Article  CAS  PubMed  Google Scholar 

  • Wang H, Cao LY, Guo YH et al (2008) Correlation analysis and QTL mapping of some physiological traits related to drought resistance in rice. Chin J Rice Sci 22(5):477–484

    CAS  Google Scholar 

  • Xiao YL, Yu CY, Lei JG et al (2012) Screening of rice germplasm accessions for vegetative drought tolerance. Acta Agri Univ Jiang Xiensis 34(3):0428–0433

    Google Scholar 

  • Xu JC, Zhou LX (2002) Identification of molecular markers associated with root traits expression in rice by correlation analysis. Acta Genet Sin 3(1):245–249

    Google Scholar 

  • Xu JL, Lafitte HR, Gao YM, FuB Y, Torres R, Li ZK (2005) QTLs for drought avoidance and tolerance identified in a set of random introgression lines of rice. Theor Appl Genet 111(8):1642–1650

    Article  CAS  PubMed  Google Scholar 

  • Yang SQ, Li WQ, Miao H, Gan PF, Qiao L, Chang YL, Shi CH, Chen KM (2016) RFL2, a gene encoding an unknown function protein which contains DUF630 and DUF632 domains controls leaf rolling in rice. Rice 9(1):37

    Article  PubMed  PubMed Central  Google Scholar 

  • Rao YC, Dai ZJ, Zhu YT et al (2020) Advances in research of drought resistance in rice. J Zhejiang Normal Univ Nat Sci 43(4)417

  • Yue B, Xiong LZ, Xue WY, Xing YZ, Luo LJ, Xu CG (2005) Genetic analysis for drought resistance of rice at reproductive stage in field with different types of soil. Theor Appl Genet 111:1127–1136

    Article  PubMed  Google Scholar 

  • Zhang J, Zheng HG, Aarti A et al (2001) Locating genomic regions associated with components of drought resistance in rice: comparative mapping within and across species. Theor Appl Genet 103(1):19–29

    Article  CAS  Google Scholar 

  • Zhang JJ, Wu SY, Jiang L, Wang JL, Zhang X, Guo XP et al (2015) A detailed analysis of the leaf rolling mutant Sll2 reveals complex nature in regulation of bulliform cell development in rice (Oryza sativa L.). Plant Biol 17(2):437–448

    Article  CAS  PubMed  Google Scholar 

  • Zheng HG, Babu RC, Pathan MS et al (2000) Quantitative trait loci for root-penetration ability and root thickness in rice: comparison of genetic backgrounds. Genome 43:53–61

    Article  CAS  PubMed  Google Scholar 

  • Zheng B, Yang L, Zhang W, Mao C, Wu Y, Yi K, Liu F, Wu P (2003) Mapping QTLs and candidate genes for rice root traits under different water-supply conditions and comparative analysis across three populations. Theor Appl Genet 107(1505–1515):113

    Google Scholar 

  • Zheng BS, Yang L, Mao CZ et al (2006) QTLs and candidate genes for rice root growth under flooding and upland conditions. Acta Genet Sin 33(2):141–151

    Article  PubMed  Google Scholar 

  • Zhu Q, Xu JC (2010) Research advance on molecular mechanism of drought resistance in plant. J Anhui Agri Sci 38(26):14198–14202

    CAS  Google Scholar 

  • Zou DT, Wang J, Wang JG, Liu HL, Liu YQ, Jia Y (2014) QTL analysis of flag leaf characteristics and ears weight in rice. J North East Agric Univ 45(1):23–28

Download references

Acknowledgements

This work was supported by the Special Fund for Rice Breeding of Ningxia Hui Autonomous Region (2018NYYZ0302) and the Natural Sciences Foundation of Ningxia Hui Autonomous Region (2022AAC03459).

Funding

This work was supported by the Special Fund for Rice Breeding of Ningxia Hui Autonomous Region (2018NYYZ0302) and the Natural Sciences Foundation of Ningxia Hui Autonomous Region (2022AAC03459).

Author information

Authors and Affiliations

Authors

Contributions

LC conducted field work, generated the phenotypic data, performed the data analysis and wrote the manuscript; JM generated the phenotypic and genotypic data; XM performed the genotyping of the mapping population; DC assisted with field work; BH assisted with field work; JS designed the research and implemented manuscript revisions; and LH designed the experiment and guided the experiments and manuscript revisions. All authors read and approved the final version of the manuscript.

Corresponding authors

Correspondence to JianChang Sun or LongZhi Han.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, L., Ma, J., Ma, X. et al. QTL analysis of drought tolerance traits in rice during the vegetative growth period. Euphytica 219, 33 (2023). https://doi.org/10.1007/s10681-022-03151-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10681-022-03151-4

Keywords

Navigation