Molecular Breeding

, Volume 31, Issue 3, pp 587–599 | Cite as

Identifying wheat genomic regions for improving grain protein concentration independently of grain yield using multiple inter-related populations

  • Matthieu Bogard
  • Vincent Allard
  • Pierre Martre
  • Emmanuel Heumez
  • John W. Snape
  • Simon Orford
  • Simon Griffiths
  • Oorbessy Gaju
  • John Foulkes
  • Jacques Le Gouis


Grain yield (GY) and grain protein concentration (GPC) are two major traits contributing to the economic value of the wheat crop. These are, consequently, major targets in wheat breeding programs, but their simultaneous improvement is hampered by the negative correlation between GPC and GY. Identifying the genetic determinants of GPC and GY through quantitative trait loci (QTL) analysis would be one way to identify chromosomal regions, allowing improvement of GPC without reducing GY using marker-assisted selection. Therefore, QTL detection was carried out for GY and GPC using three inter-connected doubled haploid populations grown in a large multi-environment trial network. Chromosomes 2A, 2D, 3B, 7B and 7D showed co-location of QTL for GPC and GY with antagonistic effects, thus contributing to the negative GPC–GY relationship. Nonetheless, genomic regions determining GPC independently of GY across experiments were found on chromosomes 3A and 5D and could help breeders to move the GPC–GY relationship in a desirable direction.


Grain protein concentration Grain yield QTL MCQTL Triticum aestivum



Grain protein concentration


Grain yield


Quantitative trait loci



This work was supported by the “NUE traits” project [IN-BB-06] (; funded by the Institut National de la Recherche Agronomique (INRA) and the UK Biotechnology and Biological Sciences Research Council (BBSRC). Authors gratefully acknowledge the experimental work carried out by Joëlle Messaoud, Séverine Rougeol, Jean-Louis Joseph and Pascal Lemaire (INRA, Clermont-Ferrand), Dominique Brasseur (INRA, Estrées-Mons), Rob Perdue (University of Nottingham, Sutton Bonington), and Lesley Fish (John Innes Centre, Norwich).

Supplementary material

11032_2012_9817_MOESM1_ESM.doc (458 kb)
The online version of this article contains supplementary material (Table S1 and Figure S1). Results of QTL detection are publicly available at (DOC 458 kb)


  1. Akbari M, Wenzl P, Caig V, Carling J, Xia L, Yang S, Uszynski G, Mohler V, Lehmensiek A, Kuchel H, Hayden M, Howes N, Sharp P, Vaughan P, Rathmell B, Huttner E, Kilian A (2006) Diversity arrays technology (DArT®) for high-throughput profiling of the hexaploid wheat genome. Theor Appl Genet 113:1409–1420PubMedCrossRefGoogle Scholar
  2. Akhunov E, Nicolet C, Dvorak J (2009) Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay. Theor Appl Genet 119:507–517PubMedCrossRefGoogle Scholar
  3. Balfourier F, Roussel V, Strelchenko P, Exbrayat-Vinson F, Sourdille P, Boutet G, Koenig J, Ravel C, Mitrofanova O, Beckert M (2007) A worldwide bread wheat core collection arrayed in a 384-well plate. Theor Appl Genet 114:1265–1275PubMedCrossRefGoogle Scholar
  4. Barbottin A, Lecomte C, Bouchard C, Jeuffroy M (2005) Nitrogen remobilization during grain filling in wheat: genotypic and environmental effects. Crop Sci 45:1141–1150CrossRefGoogle Scholar
  5. Beales J, Turner A, Griffiths S, Snape J, Laurie D (2007) A pseudo-response regulator is misexpressed in the photoperiod insensitive Ppd-D1a mutant of wheat (Triticum aestivum L.). Theor Appl Genet 115:721–733PubMedCrossRefGoogle Scholar
  6. Billotte N, Jourjon MF, Marseillac N, Berger A, Flori A, Asmady H, Adon B, Singh R, Nouy B, Potier F, Cheah SC, Rohde W, Ritter E, Courtois B, Charrier A, Mangin B (2010) QTL detection by multi-parent linkage mapping in oil palm (Elaeis guineensis Jacq.). Theor Appl Genet 120:1673–1687PubMedCrossRefGoogle Scholar
  7. Blanc G, Charcosset A, Mangin B, Gallais A, Moreau L (2006) Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize. Theor Appl Genet 113:206–224PubMedCrossRefGoogle Scholar
  8. Blanco A, Pasqualone A, Troccoli A, Di Fonzo N, Simeone R (2002) Detection of grain protein content QTLs across environments in tetraploid wheats. Plant Mol Biol 48:615–623PubMedCrossRefGoogle Scholar
  9. Blanco A, Simeone R, Gadaleta A (2006) Detection of QTLs for grain protein content in durum wheat. Theor Appl Genet 112:1195–1204PubMedCrossRefGoogle Scholar
  10. Blanco A, Mangini G, Giancaspro A, Giove S, Colasuonno P, Simeone R, Signorile A, De Vita P, Mastrangelo AM, Cattivelli L, Gadaleta A (2012) Relationship between grain protein content and grain yield components through quantitative trait locus analyses in a recombinant inbred line population derived from two elite durum wheat cultivars. Mol Breed 30:79–92CrossRefGoogle Scholar
  11. Bogard M, Allard V, Brancourt-Hulmel M, Heumez E, Machet J, Jeuffroy M, Gate P, Martre P, Le Gouis J (2010) Deviation from the grain protein concentration–grain yield negative relationship is highly correlated to post-anthesis N uptake in winter wheat. J Exp Bot 61:4303–4312PubMedCrossRefGoogle Scholar
  12. Bogard M, Jourdan M, Allard V, Martre P, Perretant MR, Ravel C, Heumez E, Orford S, Snape J, Giffiths S, Oorbessy G, Foulkes J, Le Gouis J (2011) Anthesis date mainly explained correlations between post-anthesis leaf senescence, grain yield and grain protein concentration in a winter wheat population segregating for flowering time QTLs. J Exp Bot 62:3621–3636PubMedCrossRefGoogle Scholar
  13. Bonnin I, Rousset M, Madur D, Sourdille P, Dupuits C, Brunel D, Goldringer I (2008) FT genome A and D polymorphisms are associated with the variation of earliness components in hexaploid wheat. Theor Appl Genet 116:383–394PubMedCrossRefGoogle Scholar
  14. Bordes J, Ravel C, Le Gouis J, Lapierre A, Charmet G, Balfourier F (2010) Use of a global wheat core collection for association analysis of flour and dough quality traits. J Cereal Sci 54:137–147CrossRefGoogle Scholar
  15. Charmet G, Robert N, Branlard G, Linossier L, Martre P, Triboï E (2005) Genetic analysis of dry matter and nitrogen accumulation and protein composition in wheat kernels. Theor Appl Genet 111:540–550PubMedCrossRefGoogle Scholar
  16. Chee P, Elias E, Anderson J, Kianian S (2001) Evaluation of a high grain protein QTL from Triticum turgidum L. var. dicoccoides in an adapted durum wheat background. Crop Sci 41:295–301CrossRefGoogle Scholar
  17. Crossa J, Burgueno J, Dreisigacker S, Vargas M, Herrera-Foessel SA, Lillemo M, Singh RP, Trethowan R, Warburton M, Franco J, Reynolds M, Crouch J, Ortiz R (2007) Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure. Genetics 177:1889–1913PubMedCrossRefGoogle Scholar
  18. De Givry S, Bouchez M, Chabrier P, Milan D, Schiex T (2005) CarhtaGene: multipopulation integrated genetic and radiation hybrid mapping. Bioinformatics 21:1703–1704PubMedCrossRefGoogle Scholar
  19. Dubcovsky J (2004) Marker-assisted selection in public breeding programs: the wheat experience. Crop Sci 44:1895–1898CrossRefGoogle Scholar
  20. Fontaine J, Ravel C, Pageau K, Heumez E, Dubois F, Hirel B, Le Gouis J (2009) A quantitative genetic study for elucidating the contribution of glutamine synthetase, glutamate dehydrogenase and other nitrogen-related physiological traits to the agronomic performance of common wheat. Theor Appl Genet 119:645–662PubMedCrossRefGoogle Scholar
  21. Francki M, Walker E, Crawford A, Broughton S, Ohm H, Barclay I, Wilson R, McLean R (2009) Comparison of genetic and cytogenetic maps of hexaploid wheat (Triticum aestivum L.) using SSR and DArT markers. Mol Genet Genomics 281:181–191PubMedCrossRefGoogle Scholar
  22. Gaju O, Allard V, Martre P, Snape JW, Heumez E, Le Gouis J, Moreau D, Bogard M, Griffiths S, Orford S, Hubbart S, Foulkes J (2011) Identification of traits to improve the nitrogen use efficiency of wheat genotypes. Field Crops Res 123:139–152CrossRefGoogle Scholar
  23. Gegas VC, Nazari A, Griffiths S, Simmonds J, Fish L, Orford S, Sayers L, Doonan JH, Snape JW (2010) A genetic framework for grain size and shape variation in wheat. Plant Cell 22:1046–1056PubMedCrossRefGoogle Scholar
  24. Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155:463–473PubMedGoogle Scholar
  25. Gregersen PL, Holm PB, Krupinska K (2008) Leaf senescence and nutrient remobilisation in barley and wheat. Plant Biol 10:37–49PubMedCrossRefGoogle Scholar
  26. Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Alibert L, Orford S, Wingen L, Herry L, Faure S, Laurie D, Bilham L, Snape J (2009) Meta-QTL analysis of the genetic control of ear emergence in elite European winter wheat germplasm. Theor Appl Genet 119:383–395PubMedCrossRefGoogle Scholar
  27. Groos C, Bervas E, Charmet G (2004) Genetic analysis of grain protein content, grain hardness and dough rheology in a hard×hard bread wheat progeny. J Cereal Sci 40:93–100Google Scholar
  28. Groos C, Robert N, Bervas E, Charmet G (2003) Genetic analysis of grain protein content, grain yield and thousand-kernel weight in bread wheat. Theor Appl Genet 106:1032–1040PubMedGoogle Scholar
  29. Groos C, Bervas E, Chanliaud E, Charmet G (2007) Genetic analysis of bread-making quality scores in bread wheat using a recombinant inbred line population. Theor Appl Genet 115:313–323PubMedCrossRefGoogle Scholar
  30. Gupta PK, Varshney RK, Sharma PC, Ramesh B (1999) Molecular markers and their applications in wheat breeding. Plant Breed 118:369–390CrossRefGoogle Scholar
  31. Hanocq E, Laperche A, Jaminon O, Lainé A, Le Gouis J (2007) Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysis. Theor Appl Genet 114:569–584PubMedCrossRefGoogle Scholar
  32. Holland JB (2007) Genetic architecture of complex traits in plants. Curr Opin Plant Biol 10:156–161PubMedCrossRefGoogle Scholar
  33. Jourjon M, Durel C, Goffinet B, Laurens F (2000) An example of application for MCQTL software: fine characterisation of a QTL for apple scab resistance. Plant and Animal Genome Conference VIII, San Diego, USAGoogle Scholar
  34. Jourjon M, Jasson S, Marcel J, Ngom B, Mangin B (2005) MCQTL: multi-allelic QTL mapping in multi-cross design. Bioinformatics 21:128–130PubMedCrossRefGoogle Scholar
  35. Kerfal S, Giraldo P, Rodriguez-Quijano M, Vazquez JF, Adams K, Lukow OM, Roder MS, Somers DJ, Carrillo JM (2010) Mapping quantitative trait loci (QTLs) associated with dough quality in a soft × hard bread wheat progeny. J Cereal Sci 52:46–52CrossRefGoogle Scholar
  36. Kichey T, Hirel B, Heumez E, Dubois F, Le Gouis J (2007) In winter wheat (Triticum aestivum L.), post-anthesis nitrogen uptake and remobilisation to the grain correlates with agronomic traits and nitrogen physiological markers. Field Crops Res 102:22–32CrossRefGoogle Scholar
  37. Kuchel H, Williams KJ, Langridge P, Eagles HA, Jefferies SP (2007) Genetic dissection of grain yield in bread wheat. I. QTL analysis. Theor Appl Genet 115:1029–1041PubMedCrossRefGoogle Scholar
  38. Laperche A, Brancourt-Hulmel M, Heumez E, Gardet O, Hanocq E, Devienne-Barret F, Le Gouis J (2007) Using genotype × nitrogen interaction variables to evaluate the QTL involved in wheat tolerance to nitrogen constraints. Theor Appl Genet 115:399–415PubMedCrossRefGoogle Scholar
  39. Li X, Zhao X, He X, Zhao G, Li B, Liu D, Zhang A, Zhang X, Tong Y, Li Z (2011) Haplotype analysis of the genes encoding glutamine synthetase plastic isoforms and their association with nitrogen-use- and yield-related traits in bread wheat. New Phytol 189:449–458PubMedCrossRefGoogle Scholar
  40. Marza F, Bai GH, Carver BF, Zhou WC (2006) Quantitative trait loci for yield and related traits in the wheat population Ning7840 × Clark. Theor Appl Genet 112:688–698PubMedCrossRefGoogle Scholar
  41. McNeal F, Berg C (1978) Recurrent selection for grain protein content in spring wheat. Crop Sci 18:779–782CrossRefGoogle Scholar
  42. Miezan K, Heyne EG, Finney KF (1977) Genetic and environmental effects on the grain protein content in wheat. Crop Sci 17:591–593CrossRefGoogle Scholar
  43. Muranty H (1996) Power of tests for quantitative trait loci detection using full-sib families in different schemes. Heredity 76:156–165CrossRefGoogle Scholar
  44. Oliphant A, Barker DL, Stuelpnagel JR, Chee MS (2002) BeadArray technology: enabling an accurate, cost-effective approach to high-throughput genotyping. BioTechniques Suppl 56–58:60–61Google Scholar
  45. Oury F, Bérard P, Brancourt-Hulmel M, Depatureaux C, Doussineaux G, Galic N, Giraud A, Heumez E, Lecomte C, Pluchard P, Rousset M, Trottet M (2003) Yield and grain protein concentration in bread wheat: a review and a study of multi-annual data from a French breeding program. J Genet Breed 57:59–68Google Scholar
  46. Oury F, Chiron H, Faye A, Gardet O, Giraud A, Heumez E, Rolland B, Rousset M, Trottet M, Charmet G, Branlard G (2010) The prediction of bread wheat quality: joint use of the phenotypic information brought by technological tests and the genetic information brought by HMW and LMW glutenin subunits. Euphytica 171:87–109CrossRefGoogle Scholar
  47. Pepe J, Heiner JF, Robert E (1975) Plant height, protein percentage, and yield relationships in spring wheat. Crop Sci 15:793–797CrossRefGoogle Scholar
  48. Perretant M, Cadalen T, Charmet G, Sourdille P, Nicolas P, Boeuf C, Tixier M, Branlard G, Bernard S (2000) QTL analysis of bread-making quality in wheat using a doubled haploid population. Theor Appl Genet 100:1167–1175CrossRefGoogle Scholar
  49. Pierre J, Huguet T, Barre P, Huyghe C, Julier B (2008) Detection of QTLs for flowering date in three mapping populations of the model legume species Medicago truncatula. Theor Appl Genet 117:609–620PubMedCrossRefGoogle Scholar
  50. Prasad M, Kumar N, Kulwal P, Röder M, Balyan H, Dhaliwal H, Gupta P (2003) QTL analysis for grain protein content using SSR markers and validation studies using NILs in bread wheat. Theor Appl Genet 106:659–667PubMedGoogle Scholar
  51. Pushpendra KG, Harindra SB, Pawan LK, Neeraj K, Ajay K, Reyazul RM, Amita M, Jitendra K (2007) QTL analysis for some quantitative traits in bread wheat. J Zhejiang Univ Sci B 8:807–814PubMedCrossRefGoogle Scholar
  52. Rebaï A, Goffinet B (1993) Power of tests for QTL detection using replicated progenies derived from a diallel cross. Theor Appl Genet 86:1014–1022CrossRefGoogle Scholar
  53. Rebaï A, Blanchard P, Perret D, Vincourt P (1997) Mapping quantitative trait loci controlling silking date in a diallel cross among four lines of maize. Theor Appl Genet 95:451–459CrossRefGoogle Scholar
  54. Reif JC, Gowda M, Maurer HP, Longin CFH, Korzun V, Ebmeyer E, Bothe R, Pietsch C, Wurschum T (2010) Association mapping for quality traits in soft winter wheat. Theor Appl Genet 122:961–970PubMedCrossRefGoogle Scholar
  55. Sanford DA, MacKown CT (1986) Variation in nitrogen use efficiency among soft red winter wheat genotypes. Theor Appl Genet 72:158–163CrossRefGoogle Scholar
  56. Sherman JD, Lanning SP, Clark D, Talbert LE (2008) Registration of near-isogenic hard-textured wheat lines differing for presence of a high grain protein gene. J Plant Regist 2:162–164CrossRefGoogle Scholar
  57. Shewry PR (2009) Wheat. J Exp Bot 60:1537–1553PubMedCrossRefGoogle Scholar
  58. Slafer GA, Andrade FH, Feingold SE (1990) Genetic improvement of bread wheat (Triticum aestivum L.) in Argentina: relationships between nitrogen and dry matter. Euphytica 50:63–71CrossRefGoogle Scholar
  59. Sourdille P, Singh S, Cadalen T, Brown-Guedira GL, Gay G, Qi L, Gill BS, Dufour P, Murigneux A, Bernard M (2004) Microsattelite-based deletion bin system for the establishment of genetic-physical map relationships in wheat (Triticum aestivum L.). Funct Integr Genomics 4:12–25PubMedCrossRefGoogle Scholar
  60. Sun X, Marza F, Ma H, Carver BF, Bai G (2010) Mapping quantitative trait loci for quality factors in an inter-class cross of US and Chinese wheat. Theor Appl Genet 120:1041–1051PubMedCrossRefGoogle Scholar
  61. Triboi E, Martre P, Girousse C, Ravel C, Triboi-Blondel A (2006) Unravelling environmental and genetic relationships between grain yield and nitrogen concentration for wheat. Eur J Agron 25:108–118CrossRefGoogle Scholar
  62. Uauy C, Brevis JC, Dubcovsky J (2006) The high grain protein content gene Gpc-B1 accelerates senescence and has pleiotropic effects on protein content in wheat. J Exp Bot 57:2785–2794PubMedCrossRefGoogle Scholar
  63. Varshney RK, Dubey A (2009) Novel genomic tools and modern genetic and breeding approaches for crop improvement. J Plant Biochem Biotechnol 18:127–138CrossRefGoogle Scholar
  64. Verhoeven KJF, Jannink J, McIntyre LM (2005) Using mating designs to uncover QTL and the genetic architecture of complex traits. Heredity 96:139–149CrossRefGoogle Scholar
  65. Veyrieras JB, Goffinet B, Charcosset A (2007) MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinfo 8:49Google Scholar
  66. Wang RX, Hai L, Zhang XY, You GX, Yan CS, Xiao SH (2009) QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679. Theor Appl Genet 118:313–325PubMedCrossRefGoogle Scholar
  67. Yan L, Fu D, Li C, Blechl A, Tranquilli G, Bonafede M, Sanchez A, Valarik M, Yasuda S, Dubcovsky J (2006) The wheat and barley vernalization gene VRN3 is an orthologue of FT. Proc Natl Acad Sci USA 51:19581–19586CrossRefGoogle Scholar
  68. Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421CrossRefGoogle Scholar
  69. Zhao L, Zhang KP, Liu B, Deng Z, Qu HL, Tian JC (2010) A comparison of grain protein content QTLs and flour protein content QTLs across environments in cultivated wheat. Euphytica 174:325–335CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Matthieu Bogard
    • 1
    • 2
  • Vincent Allard
    • 1
    • 2
  • Pierre Martre
    • 1
    • 2
  • Emmanuel Heumez
    • 3
  • John W. Snape
    • 4
  • Simon Orford
    • 4
  • Simon Griffiths
    • 4
  • Oorbessy Gaju
    • 5
  • John Foulkes
    • 5
  • Jacques Le Gouis
    • 1
    • 2
  1. 1.INRA, UMR 1095 Génétique, Diversité et Ecophysiologie des CéréalesClermont-FerrandFrance
  2. 2.UMR 1095 Génétique, Diversité et Ecophysiologie des CéréalesUniversité Blaise PascalAubière CedexFrance
  3. 3.INRA, UMR 1281 Stress Abiotiques et Différenciation des Végétaux Cultivés, Estrées-MonsPéronneFrance
  4. 4.Crop Genetics DepartmentJohn Innes CentreNorwichUK
  5. 5.Division of Agricultural SciencesUniversity of NottinghamLeicestershireUK

Personalised recommendations