Skip to main content
SpringerLink
Log in

Mapping QTL main and interaction influences on milling quality in elite US rice germplasm

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

Abstract

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 2005–2007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTL × environment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of genetic × environment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating year–location combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.

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
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

QTL:

Quantitative-trait locus

GEI:

Genetic × environment interaction

QEI:

QTL × environment interaction

QQI:

QTL × QTL interaction

QQEI:

QQI × environment interaction

HR:

Head-rice yield

RIL:

Recombinant inbred line

MET:

Multi-environment trial

MIM:

Multiple-interval mapping

References

  • Aluko G, Martinez C, Tohme J, Castano C, Bergman C, Oard JH (2004) QTL mapping of grain quality traits from the interspecific cross Oryza sativa x O. glaberrima. Theor Appl Genet 109:630–639

    Article  CAS  PubMed  Google Scholar 

  • Bauer A, Hoti F, von Korff M, Pillen K, Léon J, Sillanpää M (2009) Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials. Theor Appl Genet 119:105–123

    Article  CAS  PubMed  Google Scholar 

  • Boer MP, Wright D, Feng L, Podlich DW, Luo L, Cooper M, van Eeuwijk FA (2007) A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. Genetics 177:1801–1813

    Article  PubMed  Google Scholar 

  • Carlborg Ö, Kerje S, Schütz K, Jacobsson L, Jensen P, Andersson L (2003) A global search reveals epistatic interaction between QTL for early growth in the chicken. Genome Res 13:413–421

    Article  CAS  PubMed  Google Scholar 

  • Childs N (2006) Rice situation and outlook yearbook. United States Department of Agriculture, Economic Research Service

  • Cooper NTW, Siebenmorgen TJ, Counce PA (2008) Effects of nighttime temperature during kernel development on rice physicochemical properties. Cereal Chem 85:276–282

    Article  CAS  Google Scholar 

  • Counce PA, Bryant RJ, Bergman CJ, Bautista RC, Wang YJ, Siebenmorgen TJ, Moldenhauer KAK, Meullenet JFC (2005) Rice milling quality, grain dimensions, and starch branching as affected by high night temperatures. Cereal Chem 82:645–648

    Article  CAS  Google Scholar 

  • de Givry S, Bouchez M, Chabrier P, Milan D, Schiex T (2005) CarthaGene: multipopulation integrated genetic and radiation hybrid mapping. Bioinformatics 21:1703–1704

    Article  PubMed  Google Scholar 

  • Dong YJ, Tsuzuki E, Lin DZ, Kamiunten H, Terao H, Matsuo M, Cheng SH (2004) Molecular genetic mapping of quantitative trait loci for milling quality in rice (Oryza sativa L.). J Cereal Sci 40:109–114

    Article  CAS  Google Scholar 

  • Dudley JW, Johnson GR (2009) Epistatic models improve prediction of performance in corn. Crop Sci 49:763–770

    Article  CAS  Google Scholar 

  • Fan CH, Xing YZ, Mao HL, Lu TT, Han B, Xu CG, Li XH, Zhang QF (2006) GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet 112:1164–1171

    Article  CAS  PubMed  Google Scholar 

  • Fjellstrom RG, Chen M, Bergman CJ, McClung AM (2004) Single nucleotide polymorphism markers at the rice alk locus controlling alkali spreading value. In: Rice Technical Working Group Meeting. Rice Technical Working Group, New Orleans, LA, p 66

  • Fukuta Y, Sasahara H, Tamura K, Fukuyama T (2000) RFLP linkage map included the information of segregation distortion in a wide-cross population between indica and japonica rice (Oryza sativa L.). Breed Sci 50:65–72

    CAS  Google Scholar 

  • Hao W, Zhu M-Z, Gao J-P, Sun S-Y, Lin H-X (2009) Identification of quantitative trait loci for rice quality in a population of chromosome segment substitution lines. J Integr Plant Biol 51:500–512

    Article  CAS  PubMed  Google Scholar 

  • Harushima Y, Yano M, Shomura A, Sato M, Shimano T, Kuboki Y, Yamamoto T, Lin SY, Antonio BA, Parco A, Kajiya H, Huang N, Yamamoto K, Nagamura Y, Kurata N, Khush GS, Sasaki T (1998) A high-density rice genetic linkage map with 2275 markers using a single F2 population. Genetics 148:479–494

    CAS  PubMed  Google Scholar 

  • Jiang C, Zeng Z-B (1997) Mapping quantitative trait loci with dominant and missing markers in various crosses from two inbred lines. Genetica 101:47–58

    Article  CAS  PubMed  Google Scholar 

  • Jiang GH, Hong XY, Xu CG, Li XH, He YQ (2005) Identification of quantitative trait loci for grain appearance and milling quality using a doubled-haploid rice population. J Integr Plant Biol 47:1391–1403

    Article  Google Scholar 

  • Joehanes R, Nelson JC (2008) QGene 4.0, an extensible Java QTL-analysis platform. Bioinformatics 24:2788–2789

    Article  CAS  PubMed  Google Scholar 

  • Juliano BO, Bechtel DB (1985) The rice grain and its gross composition. In: Juliano BO (ed) Rice: chemistry and technology, 2nd edn. The American Association of Cereal Chemists, St. Paul, pp 17–58

    Google Scholar 

  • Kao C-H, Zeng Z-B, Teasdale RD (1999) Multiple interval mapping for quantitative trait loci. Genetics 152:1203–1216

    CAS  PubMed  Google Scholar 

  • Kepiro JL, McClung AM, Chen MH, Yeater KM, Fjellstrom RG (2007) Mapping QTLs for milling yield and grain characteristics in a tropical japonica long grain cross. J Cereal Sci 48:477–485

    Article  Google Scholar 

  • Kunze OR, Calderwood DL (1985) Rough rice drying. In: Juliano BO (ed) Rice: Chemistry and Technology, 2nd edn. The American Association of Cereal Chemists, St. Paul, pp 233–264

    Google Scholar 

  • Li ZF, Wan JM, Xia JF, Zhai HQ (2003a) Mapping quantitative trait loci underlying appearance quality of rice grains (Oryza sativa L.). Acta Genet Sin 30:251–259

    PubMed  Google Scholar 

  • Li ZK, Yu SB, Lafitte HR, Huang N, Courtois B, Hittalmani S, Vijayakumar CHM, Liu GF, Wang GC, Shashidhar HE, Zhuang JY, Zheng KL, Singh VP, Sidhu JS, Srivantaneeyakul S, Khush GS (2003b) QTL × environment interactions in rice. I. Heading date and plant height. Theor Appl Genet 108:141–153

    Article  CAS  PubMed  Google Scholar 

  • Li JM, Xiao JH, Grandillo S, Jiang LY, Wan YZ, Deng QY, Yuan LP, McCouch SR (2004) QTL detection for rice grain quality traits using an interspecific backcross population derived from cultivated Asian (O. sativa L.) and African (O. glaberrima S.) rice. Genome 47:697–704

    Article  CAS  PubMed  Google Scholar 

  • Lin SY, Ikehashi H, Yanagihara S, Kawashima A (1992) Segregation distortion via male gametes in hybrids between indica and japonica or wide-compatibility varieties of rice (Oryza sativa L). Theor Appl Genet 84:812–818

    Article  Google Scholar 

  • Lin HX, Yamamoto T, Sasaki T, Yano M (2000) Characterization and detection of epistatic interactions of 3 QTLs, Hd1, Hd2, and Hd3, controlling heading date in rice using nearly isogenic lines. Theor Appl Genet 101:1021–1028

    Article  CAS  Google Scholar 

  • Lou J, Chen L, Yue G, Lou Q, Mei H, Xiong L, Luo L (2009) QTL mapping of grain quality traits in rice. J Cereal Sci 50:145–151

    Article  CAS  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  Google Scholar 

  • Malosetti M, Voltas J, Romagosa I, Ullrich SE, van Eeuwijk FA (2004) Mixed models including environmental covariables for studying QTL by environment interaction. Euphytica 137:139–145

    Article  CAS  Google Scholar 

  • McCouch SR, Teytelman L, Xu YB, Lobos KB, Clare K, Walton M, Fu BY, Maghirang R, Li ZK, Xing YZ, Zhang QF, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L (2002) Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res 9:199–207

    Article  CAS  PubMed  Google Scholar 

  • Mei H, Luo L, Guo L, Wang Y, Yu X, Ying C, Li Z (2002) Molecular mapping of QTLs for rice milling yield traits. Acta Genet Sin 29:791–797

    CAS  PubMed  Google Scholar 

  • Moldenhauer KAK, Gibbons JH, McKenzie KS (2004) Rice varieties. In: Champagne ET (ed) Rice: chemistry and technology, 3rd edn. The American Association of Cereal Chemists, St. Paul, pp 49–75

    Google Scholar 

  • Pérez CM, Juliano BO (1978) Modification of the simplified amylose test for milled rice. Starch 30:424–426

    Article  Google Scholar 

  • Piepho H-P (2000) A mixed-model approach to mapping quantitative trait loci in barley on the basis of multiple environment data. Genetics 156:2043–2050

    CAS  PubMed  Google Scholar 

  • SAS Institute (2004) SAS 9.1.3 help and documentation. SAS Institute, Inc, Cary

    Google Scholar 

  • Septiningsih EM, Trijatmiko KR, Moeljopawiro S, McCouch SR (2003) Identification of quantitative trait loci for grain quality in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon. Theor Appl Genet 107:1433–1441

    Article  CAS  PubMed  Google Scholar 

  • Shimomura K, Low-Zeddies SS, King DP, Steeves TDL, Whiteley A, Kushla J, Zemenides PD, Lin A, Vitaterna MH, Churchill GA, Takahashi JS (2001) Genome-wide epistatic interaction analysis reveals complex genetic determinants of circadian behavior in mice. Genome Res 11:959–980

    Article  CAS  PubMed  Google Scholar 

  • Siebenmorgen TJ, Meullenet JF (2004) Impact of drying, storage, and milling of rice quality and functionality. In: Champagne ET (ed) Rice: chemistry and technology, 3rd edn. The American Association of Cereal Chemists, St. Paul, pp 301–328

    Google Scholar 

  • Stylianou I, Korstanje R, Li R, Sheehan S, Paigen B, Churchill G (2006) Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci. Mamm Genome 17:22–36

    Article  PubMed  Google Scholar 

  • Tan YF, Xing YZ, Li JX, Yu SB, Xu CG, Zhang QF (2000) Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid. Theor Appl Genet 101:823–829

    Article  CAS  Google Scholar 

  • Tan YF, Sun M, Xing YZ, Hua JP, Sun XL, Zhang QF, Corke H (2001) Mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid. Theor Appl Genet 103:1037–1045

    Article  CAS  Google Scholar 

  • van Ruiten HTL (1985) Rice milling: an overview. In: Juliano BO (ed) Rice: chemistry and technology, 2nd edn. The American Association of Cereal Chemists, St. Paul, pp 349–388

    Google Scholar 

  • von Korff M, Grando S, Del Greco A, This D, Baum M, Ceccarelli S (2008) Quantitative trait loci associated with adaptation to Mediterranean dryland conditions in barley. Theor Appl Genet 117:653–669

    Article  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Wan XY, Wan JM, Weng JF, Jiang L, Bi JC, Wang CM, Zhai HQ (2005) Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments. Theor Appl Genet 110:1334–1346

    Article  CAS  PubMed  Google Scholar 

  • Wang GL, Mackill DJ, Bonman JM, McCouch SR, Champoux MC, Nelson RJ (1994) RFLP mapping of genes conferring complete and partial resistance to blast in a durably resistant rice cultivar. Genetics 136:1421–1434

    CAS  PubMed  Google Scholar 

  • Wang CM, Yasui H, Yoshimura A, Wan JM, Zhai HQ (2002) Identification of quantitative trait loci controlling F2 sterility and heading date in rice. Acta Genet Sin 29:339–342

    CAS  PubMed  Google Scholar 

  • Ware DH, Jaiswal PJ, Ni JJ, Yap I, Pan XK, Clark KY, Teytelman L, Schmidt SC, Zhao W, Chang K, Cartinhour S, Stein LD, McCouch SR (2002) Gramene, a tool for grass genomics. Plant Physiol 130:1606–1613

    Article  CAS  PubMed  Google Scholar 

  • Webb BD (1985) Criteria of rice quality in the United States. In: Juliano BO (ed) Rice: Chemistry and Technology, 2nd edn. The American Association of Cereal Chemists, St. Paul, pp 403–442

    Google Scholar 

  • Wei WH, Knott S, Haley CS, de Koning DJ (2010) Controlling false positives in the mapping of epistatic QTL. Heredity 104:401–409

    Article  PubMed  Google Scholar 

  • Xing YZ, Xu CG, Hua JP, Tan YF, Sun XL (2001) Mapping and isolation of quantitative trait loci controlling plant height and heading date in rice. Acta Bot Sin 43:721–726

    CAS  Google Scholar 

  • Xing YZ, Tan YF, Hua JP, Sun XL, Xu CG, Zhang Q (2002) Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor Appl Genet 105:248–257

    Article  CAS  PubMed  Google Scholar 

  • Xu S, Jia Z (2007) Genomewide analysis of epistatic effects for quantitative traits in barley. Genetics 175:1955–1963

    Article  CAS  PubMed  Google Scholar 

  • Yamamoto T, Taguchi-Shiobara F, Ukai Y, Sasaki T, Yano M (2001) Mapping quantitative trait loci for days-to-heading, and culm, panicle and internode lengths in a BC1F3 population using an elite rice variety, Koshihikari, as the recurrent parent. Breed Sci 51:63–71

    Article  CAS  Google Scholar 

  • Yamamoto T, Yonemaru J, Yano M (2009) Towards the understanding of complex traits in rice: substantially or superficially? DNA Res 16:141–154

    Article  CAS  PubMed  Google Scholar 

  • Yang J, Zhu J, Williams RW (2007) Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics 23:1527–1536

    Article  CAS  PubMed  Google Scholar 

  • Yano M, Harushima Y, Nagamura Y, Kurata N, Minobe Y, Sasaki T (1997) Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map. Theor Appl Genet 95:1025–1032

    Article  CAS  Google Scholar 

  • Yoshida S, Ikegami M, Kuze J, Sawada K, Hashimoto Z, Ishii T, Nakamura C, Kamijima O (2002) QTL analysis for plant and grain characters of sake-brewing rice using a doubled haploid population. Breed Sci 52:309–317

    Article  CAS  Google Scholar 

  • Zhang Y-M, Gai J (2009) Methodologies for segregation analysis and QTL mapping in plants. Genetica 136:311–318

    Article  PubMed  Google Scholar 

  • Zhao K, Wright M, Kimball J, Eizenga G, McClung A, Kovach M, Tyagi W, Ali ML, Tung CW, Reynolds A, Bustamante CD, McCouch SRP (2010) Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome. PLoS One (in press)

  • Zheng TQ, Xu JL, Li ZK, Zhai HQ, Wan JM (2007) Genomic regions associated with milling quality and grain shape identified in a set of random introgression lines of rice (Oryza sativa L.). Plant Breed 126:158–163

    Article  CAS  Google Scholar 

  • Zhou L, Chen L, Jiang L, Zhang W, Liu L, Liu X, Zhao Z, Liu S, Zhang L, Wang J, Wan J (2009) Fine mapping of the grain chalkiness QTL qPGWC-7 in rice (Oryza sativa L.). Theor Appl Genet 118:581–590

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We thank J. Delgado for all image analysis measurements; J. Cammack, K. Landry, C. Henry, P. Roberts, J. Bonnette, H. Hoffpauir, C. Conner, and J. Vawter for all milling determinations; N. Gipson for amylose content determinations; L. Murray for consultation on linear models; E. Christensen and S. Simpson for genotypic analysis; I. Roughton for fissuring determinations; and F.-M. Xie for providing the MY1 mapping population. Support for this work has been provided in part by US Department of Agriculture Cooperative State Research, Education and Extension Service—National Research Initiative—Applied Plant Genomics Program grant 2004-35317-14867 entitled “RiceCAP: A coordinated research, education, and extension project for the application of genomic discoveries to improve rice in the United States.” This is contribution 09-002-J from the Kansas Agriculture Experiment Station.

Author information

Authors and Affiliations

  1. Department of Plant Pathology, 4024 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS, 66506, USA

    J. C. Nelson

  2. US Department of Agriculture, Agricultural Research Service, Rice Research Unit, 1509 Aggie Dr., Beaumont, TX, 77713, USA

    A. M. McClung & R. G. Fjellstrom

  3. Division of Agriculture Rice Research and Extension Center, University of Arkansas, 2900 Hwy 130 E., Stuttgart, AR, 72160, USA

    K. A. K. Moldenhauer & E. Boza

  4. California Cooperative Rice Research Foundation, P. O. Box 306, Biggs, CA, 95917, USA

    F. Jodari

  5. School of Plant, Environmental, and Soil Sciences, Louisiana State University, 104 Sturgis Hall, Baton Rouge, LA, 70803, USA

    J. H. Oard

  6. Rice Research Station, Louisiana State University AgCenter, 1373 Caffey Road, Rayne, LA, 70578, USA

    S. Linscombe

  7. US Department of Agriculture, Agricultural Research Service, Genomics and Bioinformatics Research Unit, Stoneville, MS, 38776–0038, USA

    B. E. Scheffler

  8. US Department of Agriculture, Agricultural Research Service, 1001 Holleman Drive East, College Station, TX, 77840, USA

    K. M. Yeater

Authors
  1. J. C. Nelson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. M. McClung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. G. Fjellstrom
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. K. A. K. Moldenhauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. E. Boza
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. F. Jodari
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. J. H. Oard
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. S. Linscombe
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. B. E. Scheffler
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. K. M. Yeater
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. C. Nelson.

Additional information

Communicated by Q. Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nelson, J.C., McClung, A.M., Fjellstrom, R.G. et al. Mapping QTL main and interaction influences on milling quality in elite US rice germplasm. Theor Appl Genet 122, 291–309 (2011). https://doi.org/10.1007/s00122-010-1445-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-010-1445-z

Keywords

Search

Navigation