Skip to main content
SpringerLink
Log in

Pooled Mapping of Quantitative Trait Loci Conferring Heat Tolerance at Seedling Stage in Rice (Oryza sativa L.)

  • Published:
Cytology and Genetics Aims and scope Submit manuscript

Abstract

Global warming threatens human life on many aspects, including heat stress on crop production. Breeding heat-tolerant varieties is a fundamental way to meet the challenge. To study the genetic basis of seedling tolerance to heat stress in rice (Oryza sativa L.), we performed QTL mapping based on a large F2 population consisting of 4450 individuals derived from a cross between a japonica rice variety Huaidao 5 (HD5) and an indica rice variety 1892S using the method of bulked segregant analysis coupled with whole-genome sequencing (BSA-seq). HD5 was more tolerant to high temperature than 1892S at the seedling stage. By analyzing a pair of opposite DNA pools made from 124 extremely-sensitive seedlings and 178 extremely-tolerant seedlings from the F2 population using the block regression mapping (BRM) method, we mapped a QTL on chromosome 12, of which the additive effect was estimated to explain 3.75% of the phenotypic variance. We named the QTL qSLHT12.1, which must be a novel QTL, because no QTLs for rice seedling tolerance to heat stress have been mapped on chromosome 12 before. The information obtained in this study will facilitate marker-assisted breeding of heat-resistant lines and positional cloning of the gene conferring heat tolerance in rice.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.

Similar content being viewed by others

Notes

  1. The author contributed equally to this work.

REFERENCES

  1. Akhter, D., Qin, R., Nath, U.K., et al., A rice gene, OsPL, encoding a MYB family transcription factor confers anthocyanin synthesis, heat stress response and hormonal signaling, Gene, 2019, vol. 699, pp. 62–72. https://doi.org/10.1016/j.gene.2019.03.013

    Article  CAS  PubMed  Google Scholar 

  2. Asako, K., Bao, G., Ye, S., et al., Detection of quantitative trait loci for white-back and basal-white kernels under high temperature stress in Japonica rice varieties, Breed. Sci., 2007, vol. 57, pp. 107–116.

    Article  Google Scholar 

  3. Baliuag, N.A., Redona, E.D., Hernandez, J.E., et al., Genetic analysis for heat tolerance and early morning flowering traits at flowering stage in rice (Oryza sativa L.), Philipp. J. Crop Sci., 2015, vol. 40, pp. 62–72.

    Google Scholar 

  4. Cao, L., Zhu, J., Zhao, S., et al., Mapping QTLs for heat tolerance in a DH population from indica-japonica cross of rice (Oryza sativa L.), J. Agr. Sci.-Cambridge, 2002, vol. 10, pp. 210–214.

  5. Cao, Z., Tang, X., Xiao, W., et al., Identification and genetic effect analysis of QTL (qHTH10) for heat tolerance at heading and flowering stage of rice, MPB, 2019, vol. 17, pp. 2223–2230.

    Google Scholar 

  6. Cao, Z., Li, Y., Tang, H., et al., Fine mapping of the qHTB1-1QTL, which confers heat tolerance at the booting stage, using an Oryza rufipogon Griff. introgression line, Theor. Appl. Genet., 2020, vol. 133, pp. 1161–1175. https://doi.org/10.1007/s00122-020-03539-7

    Article  CAS  PubMed  Google Scholar 

  7. Chen, Q., Yu, S., Li, C., et al., Identification of QTLs for heat tolerance at flowering stage in rice, Sci. Agric. Sin., 2008, vol. 41, pp. 315–321. https://doi.org/10.3864/j.issn.0578-1752.2008.02.001

    Article  CAS  Google Scholar 

  8. Chen, L., Wang, Q., Tang, M., et al., QTL mapping and identification of candidate genes for heat tolerance at the flowering stage in rice, Front. Genet., 2021, vol. 11, p. 621871. https://doi.org/10.13271/j.mpb.017.002223

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cheng, L., Wang, J., Uzokwe, V., et al., Genetic analysis of cold tolerance at seedling stage and heat tolerance at anthesis in rice (Oryza sativa L.), J. Integr. Agr., 2012, vol. 11, pp. 359–367. https://doi.org/10.1016/S2095-3119(12)60020-3

    Article  Google Scholar 

  10. Cingolani, P., Platts, A., Wang, L.L., et al., A program for annotating and predicting the effects of single nucleotide polymorphisms, Snp Eff: SNPs in the genome of Drosophila melanogaster strain w 1118; iso-2; iso-3, Fly, 2012, vol. 6, pp. 80–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Doyle, J. and Doyle, J., A rapid procedure for DNA purification from small quantities of fresh leaf tissue, Phytochem. Bull., 1987, vol. 19, pp. 11–15.

    Google Scholar 

  12. Driedonks, N., Rieu, I., and Vriezen, W.H., Breeding for plant heat tolerance at vegetative and reproductive stages, Plant Reprod., 2016, vol. 29, pp. 67–79. https://doi.org/10.1007/s00497-016-0275-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Garrison, E. and Marth, G., Haplotype-based variant detection from short-read sequencing, Quant. Biol., 2012.

  14. Hatfield, J.L. and Prueger, J.H., Temperature extremes: effect on plant growth and development, Weather Clim. Extremes, 2015, vol. 10, pp. 4–10. https://doi.org/10.1016/j.wace.2015.08.001

    Article  Google Scholar 

  15. Hirabayashi, H., Sasaki, K., Kambe, T., et al., qEMF3, a novel QTL for the early-morning flowering trait from wild rice, Oryza officinalis, to mitigate heat stress damage at flowering in rice, O. sativa, J. Exp. Bot., 2015, vol. 66, pp. 1227–1236. https://doi.org/10.1093/jxb/eru474

    Article  CAS  PubMed  Google Scholar 

  16. Huang, L., Tang, W., Bu, S., et al., BRM: a statistical method for QTL mapping based on bulked segregant analysis by deep sequencing, Bioinformatics, 2020, vol. 36, pp. 2150–2156. https://doi.org/10.1093/bioinformatics/btz861

    Article  CAS  PubMed  Google Scholar 

  17. Jagadish, S.V.K., Craufurd, P.P.Q., and Wheeler, T.R., Phenotyping parents of mapping populations of rice for heat tolerance during anthesis, Crop Sci., 2008, vol. 48, pp. 1140–1146. https://doi.org/10.2135/cropsci2007.10.0559

    Article  Google Scholar 

  18. Jagadish, S.V.K., Cairns, J., Lafitte, R., et al., Genetic analysis of heat tolerance at anthesis in rice, Crop Sci., 2010, vol. 50, pp. 1633–1641. https://doi.org/10.2135/cropsci2009.09.0516

    Article  CAS  Google Scholar 

  19. Jagadish, S.V.K., Septiningsih, E.M., Kohli, A., et al., Genetic advances in adapting rice to a rapidly changing climate, J. Agro CropSci., 2012, vol. 198, pp. 360–373. https://doi.org/10.1111/j.1439-037X.2012.00525.x

    Article  Google Scholar 

  20. Kawahara, Y., Bastide, M., Hamilton, J.P., et al., Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data, Rice, 2013, vol. 6, p. 4. https://doi.org/10.1186/1939-8433-6-4

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kilasi, N.L., Singh, J., Vallejos, C.E., et al., Heat stress tolerance in rice (Oryza sativa L.): identification of quantitative trait loci and candidate genes for seedling growth under heat stress, Front. Plant Sci., 2018, vol. 9, p. 1578. https://doi.org/10.3389/fpls.2018.01578

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kobayashi, A., Bao, G., Ye, S., et al., Detection of quantitative trait loci for white-back and basal-white kernels under high temperature stress in Japonica rice varieties, Breed. Sci., 2007, vol. 57, pp. 107–116. https://doi.org/10.1270/jsbbs.57.107

    Article  Google Scholar 

  23. Li, H. and Durbin, R., Fast and accurate short read alignment with burrows-wheeler transform, Bioinformatics, 2009, vol. 25, pp. 1754–1760. https://doi.org/10.1093/bioinformatics/btp324

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Li, H., Handsaker, B., Wysoker, A., et al., The sequence alignment/map format and SAM tools, Bioinformatics, 2009, vol. 25, pp. 2078–2079. https://doi.org/10.1093/bioinformatics/btp352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li, M.M., Li, X., Yu, L.Q., et al., Identification of QTLs associated with heat tolerance at the heading and flowering stage in rice (Oryza Sativa L.), Euphytica, 2018, vol. 214, pp. 1–11. https://doi.org/10.1007/s10681-018-2136-0

    Article  Google Scholar 

  26. Liang, T., Chi, W., Huang, L., et al., Bulked segregant analysis coupled with whole-genome sequencing (BSA-seq) mapping identifies a novel pi21 haplotype conferring basal resistance to rice blast disease, Int. J. Mol. Sci., 2020, vol. 21, p. 2162. https://doi.org/10.3390/ijms21062162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liu, Q., Yang, T., Yu, T., et al., Integrating small RNA sequencing with QTL mapping for identification of miRNAs and their target genes associated with heat tolerance at the flowering stage in rice, Front. Plant Sci., 2017, vol. 8, p. 43. https://doi.org/10.3389/fpls.2017.00043

    Article  PubMed  PubMed Central  Google Scholar 

  28. Magwene, P.M., Willis, J.H., and Kelly, J.K., The statistics of bulk segregant analysis using next generation sequencing, PLoS Comput. Biol., 2011, vol. 7, p. e1002255. https://doi.org/10.1371/journal.pcbi.1002255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Miyahara, K., Wada, T., Sonoda, J.Y., et al., Detection and validation of QTLs for milky-white grains caused by high temperature during the ripening period in japonica rice, Breed. Sci., 2017, vol. 67, pp. 333–339. https://doi.org/10.1270/jsbbs.16203

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Murata, K., Iyama, Y., Yamaguchi, T., et al., Identification of a novel gene (Apq1) from the indica rice cultivar ‘Habataki’ that improves the quality of grains produced under high temperature stress, Breed. Sci., 2014, vol. 64, pp. 273–281. https://doi.org/10.1270/jsbbs.64.273

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Nishida, S., Dissanayaka, D.M.S.B., Honda, S., et al., Identification of genomic regions associated with low phosphorus tolerance in japonica rice (Oryza sativa L.) by QTL-Seq, J. Soil Sci. Plant Nutr., 2018, vol. 64, pp. 278–281. https://doi.org/10.1080/00380768.2017.1412238

    Article  CAS  Google Scholar 

  32. Nubankoh, P., Wanchana, S., Saensuk, C., et al., QTL-seq reveals genomic regions associated with spikelet fertility in response to a high temperature in rice (Oryza sativa L.), Plant Cell Rep., 2020, vol. 39, pp. 149–162. https://doi.org/10.1007/s00299-019-02477-z

    Article  CAS  PubMed  Google Scholar 

  33. Pan, Y., Liang, H., Gao, L., et al., Transcriptomic profiling of germinating seeds under cold stress and characterization of the cold-tolerant gene LTG5 in rice, BMC Biol., 2020, vol. 20, p. 371. https://doi.org/10.1186/s12870-020-02569-z

    Article  CAS  Google Scholar 

  34. Park, J.R., Yang, W.T., Kim, D.H., et al., Identification of a novel gene, Osbht, in response to high temperature tolerance at booting stage in rice, Int. J. Mol. Sci., 2020, vol. 21, p. 5862. https://doi.org/10.3390/ijms21165862

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ps, S., Sv, A.M., Prakash, C., et al., High resolution mapping of QTLs for heat tolerance in rice using a 5K SNP array, Rice, 2017, vol. 10, p. 28. https://doi.org/10.1186/s12284-017-0167-0

    Article  PubMed  PubMed Central  Google Scholar 

  36. Solomon, S., Qin, D., Manning, M., et al., Summary for Policymakers, in Climate Change 2007: The Physical Science Basis; Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), 2007.

  37. Tabata, M., Hirabayashi, H., Takeuchi, Y., et al., Mapping of quantitative trait loci for the occurrence of White-Back kernels associated with high temperatures during the ripening period of rice (Oryza sativa L.), Breed. Sci., 2007, vol. 57, pp. 47–52. https://doi.org/10.1270/jsbbs.57.47

    Article  Google Scholar 

  38. Takagi, H., Abe, A., Yoshida, K., et al., QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations, Plant J., 2013, vol. 74, pp. 174–183. https://doi.org/10.1111/tpj.12105

    Article  CAS  PubMed  Google Scholar 

  39. Tang, W., Huang, L., Bu, S., et al., Estimation of QTL heritability based on pooled sequencing data, Bioinformatics, 2018, vol. 34, pp. 978–984. https://doi.org/10.1093/bioinformatics/btx703

    Article  CAS  PubMed  Google Scholar 

  40. Tazib, T., Kobayashi, Y., Koyama, H., et al., QTL analyses for anther length and dehiscence at flowering as traits for the tolerance of extreme temperatures in rice (Oryza sativa L.), Euphytica, 2015, vol. 203, pp. 629–642. https://doi.org/10.1007/s10681-014-1291-1

    Article  Google Scholar 

  41. Thanh, P.T., Phan, P.D.T., Ishikawa, R., et al., QTL analysis for flowering time using backcross population between Oryza sativa Nipponbare and O. rufipogon, Genes Genet. Syst., 2010, vol. 85, pp. 273–279. https://doi.org/10.1266/ggs.85.273

    Article  PubMed  Google Scholar 

  42. Wada, T., Miyahara, K., Sonoda, J.Y., et al., Detection of QTLs for white-back and basal-white grains caused by high temperature during ripening period in japonica rice, Breed. Sci., 2015, vol. 65, pp. 216–225. https://doi.org/10.1270/jsbbs.65.216

    Article  PubMed  PubMed Central  Google Scholar 

  43. Waghmare, S.G., Sindhumole, P., Mathew, D., et al., Identification of QTL linked to heat tolerance in rice (Oryza Sativa L.) using SSR markers through bulked segregant analysis, Electron. J. Plant Breed., 2021, vol. 12, pp. 46–53. https://doi.org/10.37992/2021.1201.007

    Article  Google Scholar 

  44. Wei, H., Liu, J., Wang, Y., et al., A dominant major locus in chromosome 9 of rice (Oryza sativa L.) confers tolerance to 48 °C high temperature at seedling stage, J. Hered., 2013, vol. 104, pp. 287–294. https://doi.org/10.1093/jhered/ess103

    Article  CAS  PubMed  Google Scholar 

  45. Welch, J.R., Vincent, J.R., Auffhammer, M., et al., Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures, Proc. Natl. Acad. Sci. U. S. A., 2010, vol. 107, pp. 14562–14567. https://doi.org/10.1073/pnas.1001222107

    Article  PubMed  PubMed Central  Google Scholar 

  46. Xiao, Y., Pan, Y., Luo, L., et al., Quantitative trait loci associated with seed set under high temperature stress at the flowering stage in rice, Euphytica, 2011, vol. 178, pp. 331–338. https://doi.org/10.1007/s10681-010-0300-2

    Article  Google Scholar 

  47. Yan, C., Zhan, G., Hong, X., et al., Identification and fine mapping of a major QTL, TT1-2, that plays significant roles in regulating heat tolerance in rice, Plant Mol. Biol. Rep., 2020, vol. 39, pp. 376–385. https://doi.org/10.1007/s11105-020-01256-5

    Article  CAS  Google Scholar 

  48. Yang, Z., Huang, D., Tang, W., et al., Mapping of quantitative trait loci underlying cold tolerance in rice seedlings via high-throughput sequencing of pooled extremes, PloS One, 2013, vol. 8, p. e68433. https://doi.org/10.1371/journal.pone.0068433

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Yang, X., Xia, X., Zhang, Z., et al., QTL mapping by whole genome re-sequencing and analysis of candidate genes for nitrogen use efficiency in rice, Front. Plant Sci., 2017, vol. 8, p. 1634. https://doi.org/10.3389/fpls.2017.01634

    Article  PubMed  PubMed Central  Google Scholar 

  50. Ye, C., Argayoso, M.A., Redoña, E.D., et al., Mapping QTL for heat tolerance at flowering stage in rice using SNP markers, Plant Breed., 2012, vol. 131, pp. 33–41. https://doi.org/10.1111/j.1439-0523.2011.01924.x

    Article  CAS  Google Scholar 

  51. Ye, C., Tenorio, F.A., Argayoso, M.A., et al., Identifying and confirming quantitative trait loci associated with heat tolerance at flowering stage in different rice populations, BMC Genet., 2015a, vol. 16, pp. 41–50. https://doi.org/10.1186/s12863-015-0199-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ye, C., Tenorio, F.A., Redoña, E.D., et al., Fine-mapping and validating qHTSF4.1 to increase spikelet fertility under heat stress at flowering in rice, Theor. Appl. Genet., 2015b, vol. 128, pp. 1507–1517. https://doi.org/10.1007/s00122-015-2526-9

    Article  CAS  PubMed  Google Scholar 

  53. Yoshida, S., Forno, D.A., Cock, J.H., et al., Laboratory manual for physiological studies of rice, Int. Rice Res. Inst. Philipp., 1976, pp. 61–66.

  54. Zhang, C., Chen, F., Hong, R., et al., Mapping QTLs for heat tolerance in rice (Oryza sativa L.) at heading stage using chromosome segment substitution lines, Agric. Biotechnol., 2017, vol. 6, pp. 15–18. https://doi.org/10.19759/j.cnki.2164-4993.2017.02.004

    Article  CAS  Google Scholar 

  55. Zhao, L., Lei, J., Huang, Y., et al., Mapping quantitative trait loci for heat tolerance at anthesis in rice using chromosomal segment substitution lines, Breed. Sci., 2016, vol. 66, pp. 358–366. https://doi.org/10.1270/jsbbs.15084

    Article  PubMed  PubMed Central  Google Scholar 

  56. Zheng, J., Li, X., Su, H., et al., Construction of a genetic linkage map and QTL location for heat tolerance in japonica rice resources Rejing35, J. Nuclear Agric. Sci., 2017, vol. 31, pp. 844–851. https://doi.org/10.11869/j.issn.100-8551.2017.05.0844

    Article  Google Scholar 

  57. Zhu, C., Jiang, L., Zhang, W., et al., Identifying QTLs for thermo-tolerance of amylose content and gel consistency in rice, Chin. J. Rice Sci., 2006, vol. 20, pp. 248–252.

    CAS  Google Scholar 

  58. Zhu, S., Huang, R., Wai, H.P., et al., Mapping quantitative trait loci for heat tolerance at the booting stage using chromosomal segment substitution lines in rice, Physi-ol. Mol. Biol. Plants, 2017, vol. 23, pp. 817–825. https://doi.org/10.1007/s12298-017-0465-4

    Article  CAS  Google Scholar 

Download references

ACKNOWLEDGMENTS

We really thank funding bodies:

(1) The grants GJJ180879 funded by the Science and Technology Project of the Education Department of Jiangxi Province.

(2) The grants 2018FJCBD01 funded by the Open Project of the Key Laboratory of Crop Design and Breeding of Fujian Province.

Author information

Authors and Affiliations

  1. College of Life Sciences, Shangrao Normal University, Shangrao, 334001, Jiangxi, China

    Y. Wu, G. Zhang, C. Zhang, S. Hong & J. Deng

  2. College of Advanced Agricultural Sciences, Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang, China

    H. Wu

  3. Marine and Agricultural Biotechnology Laboratory, Fuzhou Institute of Oceanography Minjiang University, Fuzhou, 350108, Fujian, China

    W. Tang

  4. Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, 350108, Fujian, China

    W. Wu

Authors
  1. Y. Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. W. Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. S. Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. J. Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. W. Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Y. Wu or W. Wu.

Ethics declarations

The authors declare that they have no conflicts of interest. This article does not contain any studies involving animals or human participants performed by any of the authors.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, Y., Wu, H., Zhang, G. et al. Pooled Mapping of Quantitative Trait Loci Conferring Heat Tolerance at Seedling Stage in Rice (Oryza sativa L.). Cytol. Genet. 57, 367–373 (2023). https://doi.org/10.3103/S0095452723040126

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0095452723040126

Search

Navigation