Skip to main content

Advertisement

SpringerLink
Log in

Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis

  • Original Paper
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

An F4:5 population of 490 recombinant inbred lines (RILs) from the cross Apo/2*Swarna was used to detect quantitative trait loci (QTL) with large effects on grain yield under drought stress using bulk-segregant analysis (BSA). Swarna is an important rainfed lowland rice variety grown on millions of hectares in Asia, but is highly susceptible to drought and aerobic soil conditions. Apo is an aerobic-adapted variety with moderate tolerance to drought. Two rice microsatellite (RM) markers, RM324, and RM416, located on chromosomes 2 and 3, respectively, were shown via BSA to be strongly associated with yield under lowland drought stress. The effects of these QTL were tested in a total of eight hydrological environments over a period of 3 years. The QTL linked to RM416 (DTY 3.1) had a large effect on grain yield under severe lowland drought stress, explaining about 31% of genetic variance for the trait (P < 0.0001). It also explained considerable variance for yield under mild stress in lowland conditions and aerobic environments. To our knowledge this is the first reported QTL that has a large effect on yield in both lowland drought and aerobic environments. The QTL linked to RM324 (DTY 2.1) had a highly significant effect on grain yield in lowland drought stress (R 2 = 13–16%) and in two aerobic trials. The effect of these QTL on grain yield was verified to be not mainly due to phenology differences. Effects of DTY 3.1 on yield under stress have been observed in several other rice mapping populations studied at IRRI. Results of this study indicate that BSA is an effective method of identifying QTL alleles with large effects on rice yield under severe drought stress. The Apo alleles for these large-effect QTL for grain yield under drought and aerobic conditions may be immediately exploited in marker-assisted-breeding to improve the drought tolerance of Swarna.

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
Fig. 2

Similar content being viewed by others

References

  • Babu RC, Nguyen BD, Chamarerk V, Shanmugasundaram P, Chezhian P, Jeyaprakash P, Ganesh SK, Palchamy A, Sadasivam S, Sarkarung S, Wade LJ, Nguyen HT (2003) Genetic analysis of drought resistance in rice by molecular markers: association between secondary traits and field performance. Crop Sci 43:1457–1469

    Article  CAS  Google Scholar 

  • Bernier J, Kumar A, Venuprasad R, Spaner D, Atlin GN (2007) A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Sci 47:507–516

    Article  Google Scholar 

  • Bernier J, Atlin GN, Serraj R, Kumar A, Spaner D (2008) Breeding upland rice for drought resistance. J Sci Food Agric 88:927–939

    Article  CAS  Google Scholar 

  • Courtois B, Mclaren G, Sinha PK, Prasad K, Yadav R, Shen L (2000) Mapping QTLs associated with drought avoidance in upland rice. Mol Breed 6:55–66

    Article  CAS  Google Scholar 

  • George T, Magbanua R, Garrity DP, Tubana BS, Quinton J (2002) Rapid yield loss of rice cropped successively in aerobic soil. Agron J 94:981–989

    Article  Google Scholar 

  • Hemamalini GS, Shashidar HE, Hittalmani S (2000) Molecular marker-assisted tagging of morphological and physiological traits under two contrasting moisture regimes at peak vegetative stage in rice. Euphytica 112:69–78

    Article  CAS  Google Scholar 

  • Huke RE, Huke EH (1997) Rice area by type of culture: south, southeast, and east Asia. IRRI, Los Baños, Philippines

    Google Scholar 

  • IRGSP (2005) The map-based sequence of the rice genome. Nature 436:793–800

    Article  Google Scholar 

  • Kamoshita A, Zhang J, Siopongco J, Sarkarung S, Nguyen HT, Wade LJ (2002) Effects of phenotyping environment on identification of quantitative trait loci for rice root morphology under anaerobic conditions. Crop Sci 42:255–265

    Article  CAS  PubMed  Google Scholar 

  • Kim HJ, Hyun Y, Park JY, Park MJ, Park MK, Kim MD, Kim HJ, Lee MH, Moon J, Lee I, Kim J (2004) A genetic link between cold responses and flowering time through FVE in Arabidopsis thaliana. Nat Genet 36:167–171

    Article  CAS  PubMed  Google Scholar 

  • Kumar R, Venuprasad R, Atlin GN (2007) Genetic analysis of rainfed lowland rice drought tolerance under naturally-occurring stress in eastern India: heritability and QTL effects. Field Crops Res 103:42–52

    Article  Google Scholar 

  • Kumar A, Bernier J, Verulkar S, Lafitte HR, Atlin GN (2008) Breeding for drought tolerance: direct selection for yield, response to selection and use of drought-tolerant donors in upland and lowland-adapted populations. Field Crops Res 107:221–231

    Article  Google Scholar 

  • Lanceras JC, Pantuwan G, Jongdee B, Toojinda T (2004) Quantitative trait loci associated with drought tolerance at reproductive stage in rice. Plant Physiol 135:384–399

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lander E, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Maccaferri M, Sanguineti MC, Corneti S, Ortega JLA, Salem MB, Bort J, DeAmbrogio E, del Moral LFG, Demontis A, El-Ahmed A, Maalouf F, Machlab H, Martos V, Moragues M, Motawaj J, Nachit M, Nserallah N, Ouabbou H, Royo C, Slama A, Tuberosa R (2008) Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 178:489–511

    Article  PubMed  PubMed Central  Google Scholar 

  • Mackill DJ (2003) What molecular tools are available for selection for drought tolerance? In: Fischer KS, Lafitte R, Fukai S, Atlin GN, Hardy B (eds) Breeding rice for drought-prone environments. IRRI, Los Baños, Philippines, pp 55–57

    Google Scholar 

  • Masle J, Gilmore SR, Farquhar D (2005) The ERECTA gene regulates plant transpiration in Arabidopsis. Nature 436:866–870

    Article  CAS  PubMed  Google Scholar 

  • Michelmoore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci USA 88:9828–9832

    Article  Google Scholar 

  • Navabi A, Mather DE, Bernier J, Spaner DM, Atlin GN (2009) QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses. Theor Appl Genet 118:347–358

    Article  PubMed  Google Scholar 

  • Ouk M, Basnayake J, Tsubo M, Fukai S, Fischer KS, Cooper M, Nesbitt H (2006) Use of drought response index for identification of drought tolerant genotypes in rainfed lowland rice. Field Crops Res 99:48–58

    Article  Google Scholar 

  • Pandey S, Bhandari HN, Hardy B (2007) Economic costs of drought and rice farmers’ coping mechanisms. IRRI, Los Baños, Philippines

    Google Scholar 

  • Pantuwan G, Fukai S, Cooper M, Rajatasereekul S, O’Toole JC (2002) Yield response of rice (Oryza sativa L.) genotypes to drought under rainfed lowlands: 2. Selection of drought resistant genotypes. Field Crops Res 73:169–180

    Article  Google Scholar 

  • Price AH, Courtois B (1999) Mapping QTLs associated with drought resistance in rice: progress, problems and prospects. Plant Growth Regul 29:123–133

    Article  CAS  Google Scholar 

  • Price AH, Cairns JE, Horton P, Jones RGW, Griffiths H (2002) Linking drought-resistance mechanisms to drought avoidance in upland rice during a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses. J Exp Bot 53:989–1004

    Article  CAS  PubMed  Google Scholar 

  • Quarrie S, Lazic-jancic V, Kovacevic D, Steed A, Pekic S (1999) Bulk segregant analysis with molecular markers and its use for improving drought resistance in maize. J Exp Bot 50:1299–1306

    Article  CAS  Google Scholar 

  • Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: a laboratory manual, 2nd edn. Cold Spring Harbour, New York

    Google Scholar 

  • SAS Institute Inc (2004) SAS OnlineDoc® 9.1.3. SAS Institute Inc, Cary, NC, USA

    Google Scholar 

  • Shashidhar HE, Vinod MS, Sudhir Naveen, Sharma GV, Krishnamurthy K (2005) Markers linked to grain yield using bulked segregant analysis approach in rice (Oryza sativa L.). Rice Genet Newsl 22:69–71

    Google Scholar 

  • Shen X, Zhou M, Lu W, Ohm H (2003) Detection of Fusarium head blight resistance QTL in a wheat population using bulked segregant analysis. Theor Appl Genet 106:1041–1047

    Article  CAS  PubMed  Google Scholar 

  • Temnykh S, Declerck G, Lukashova A, Lipovich L, Cartinhour S, McCouch S (2001) Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, and genetic marker potential. Genome Res 11:1441–1452

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tripathy JN, Zhang J, Robin S, Nguyen TT, Nguyen HT (2000) QTLs for cell-membrane stability mapped in rice (Oryza sativa L.) under drought stress. Theor Appl Genet 100:1197–1202

    Article  CAS  Google Scholar 

  • Venuprasad R, Lafitte HR, Atlin GN (2007) Response to direct selection for grain yield under drought stress in rice. Crop Sci 47:285–293

    Article  Google Scholar 

  • Venuprasad R, Sta Cruz MT, Amante M, Magbanua R, Kumar A, Atlin GN (2008) Response to two cycles of divergent selection for grain yield under drought stress in four rice breeding populations. Field Crops Res 107:232–244

    Article  Google Scholar 

  • Venuprasad R, Bool ME, Dalid CO, Bernier J, Kumar A, Atlin GN (2009) Genetic loci responding to two cycles of divergent selection for grain yield under drought stress in a rice breeding population. Euphytica 167:261–269

    Article  CAS  Google Scholar 

  • Yadav R, Courtois B, Huang N, Mclaren G (1997) Mapping genes controlling root morphology and root distribution in a double-haploid population of rice. Theor Appl Genet 94:619–632

    Article  CAS  Google Scholar 

  • Yang J, Zhu J, Williams RW (2007) Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics 23:527–1536

    Article  Google Scholar 

  • Yang J, Hu CC, Hu H, Yu R, Xia Z, Ye X, Zhu J (2008) QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics 24:721–723

    Article  PubMed  Google Scholar 

  • Yano M, Kojima S, Takahashi Y, Lin H, Sasaki T (2001) Genetic control of flowering time in rice, a short-day plant. Plant Physiol 127:1425–1429

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yue B, Xue W, Xiong L, Yu X, Luo L, Cui K, Jin D, Xing Y, Zhang Q (2006) Genetic basis of drought resistance at reproductive stage in rice: separation of drought tolerance from drought avoidance. Genetics 172:1213–1228

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhang J, Zheng HG, Aarti A, Pantuwan G, Nguyen TT, Tripathy JN, Sarial AK, Robin S, Babu RC, Nguyen BD, Sarkarung S, Blum A, Nguyen HT (2001) Locating genomic regions associated with components of drought resistance in rice: comparative mapping within and across species. Theor Appl Genet 103:19–29

    Article  CAS  Google Scholar 

  • Zheng HG, Babu RC, Pathan MS, Ali L, Huang N, Courtois B, Nguyen HT (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 

  • Zou GH, Liu HY, Mei HW, Liu GL, Yu XQ, Li MS, Wu JH, Chen L, Luo LJ (2008) Screening for drought resistance of rice recombinant inbred populations in the field. J Integr Plant Biol 49:1508–1516

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported partly by funds from the Rockefeller Foundation, the Generation Challenge Program and the Bill & Melinda Gates Foundation. We thank Roger Magbanua for the help provided to conduct the field experiments.

Author information

Authors and Affiliations

  1. Plant Breeding Genetics and Biotechnology Division, International Rice Research Institute (IRRI), DAPO Box 7777, Manila, Philippines

    Ramaiah Venuprasad, C. O. Dalid, M. Del Valle, D. Zhao, M. Espiritu, M. T. Sta Cruz, M. Amante & A. Kumar

  2. International Maize and Wheat Improvement Centre (CIMMYT), Apdo. Postal 6-641, 06600, Mexico DF, Mexico

    G. N. Atlin

Authors
  1. Ramaiah Venuprasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. O. Dalid
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Del Valle
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Espiritu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. T. Sta Cruz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. Amante
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. A. Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. G. N. Atlin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Kumar.

Additional information

Communicated by Q. Zhang.

Electronic supplementary material

This material is unfortunately not in the Publisher's archive anymore:

Supplementary Fig. 1: Weekly average rainfall, evaporation, ground water depth, and soil water potential (tensiometer reading at 20 cm depth) at the lowland drought experimental site during flowering period: IRRI DS 2008. (TIFF 63 kb)

Supplementary Fig. 2: Gel photos of markers selected based on bulk-segregant analysis. Marker name and lane names are indicated at the top the respective gel photo. Tails composited on basis of grain yield in DS 2006 lowland stress trial. RM324 and RM416 are located on chromosomes 2 (66 cM) and 3 (191.6 cM) respectively (Source: Temnykh et al. 2001). (TIFF 117 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Venuprasad, R., Dalid, C.O., Del Valle, M. et al. Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis. Theor Appl Genet 120, 177–190 (2009). https://doi.org/10.1007/s00122-009-1168-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-009-1168-1

Keywords

Search

Navigation