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A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.)

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Abstract

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This study identified 333 genomic regions associated to 28 traits related to nitrogen use efficiency in European winter wheat using genome-wide association in a 214-varieties panel experimented in eight environments.

Abstract

Improving nitrogen use efficiency is a key factor to sustainably ensure global production increase. However, while high-throughput screening methods remain at a developmental stage, genetic progress may be mainly driven by marker-assisted selection. The objective of this study was to identify chromosomal regions associated with nitrogen use efficiency-related traits in bread wheat (Triticum aestivum L.) using a genome-wide association approach. Two hundred and fourteen European elite varieties were characterised for 28 traits related to nitrogen use efficiency in eight environments in which two different nitrogen fertilisation levels were tested. The genome-wide association study was carried out using 23,603 SNP with a mixed model for taking into account parentage relationships among varieties. We identified 1,010 significantly associated SNP which defined 333 chromosomal regions associated with at least one trait and found colocalisations for 39 % of these chromosomal regions. A method based on linkage disequilibrium to define the associated region was suggested and discussed with reference to false positive rate. Through a network approach, colocalisations were analysed and highlighted the impact of genomic regions controlling nitrogen status at flowering, precocity, and nitrogen utilisation on global agronomic performance. We were able to explain 40 ± 10 % of the total genetic variation. Numerous colocalisations with previously published genomic regions were observed with such candidate genes as Ppd-D1, Rht-D1, NADH-Gogat, and GSe. We highlighted selection pressure on yield and nitrogen utilisation discussing allele frequencies in associated regions.

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Abbreviations

ADM_S:

Straw dry matter at maturity

DArT:

Diversity array technology

LD:

Linkage disequilibrium

FLO:

Flowering date

G:

Genotype

G × E:

Genotype × environment

GNY:

Grain nitrogen yield

GPC:

Grain protein content

GPD:

Grain protein deviation

GY:

Grain dry matter yield

HI:

Harvest index

KS:

Kernel per spike

N:

Nitrogen

%N_S:

Straw nitrogen content at maturity

NHI:

Nitrogen harvest index

NSA:

Straw nitrogen per area

NTA:

Total nitrogen in plant at maturity

NUE:

Nitrogen use efficiency

NUE_Prot:

Nitrogen use to protein efficiency

NupE:

Nitrogen uptake

NutE:

Nitrogen utilisation efficiency

NutE_Prot:

Nitrogen utilisation to protein efficiency

P :

P value

PH:

Plant height

QTL:

Quantitative trait locus

QTN:

Quantitative trait nucleotide

SA:

Spike per area

SNP:

Small nucleotide polymorphism

SSR:

Single sequence repeat

TKW:

Thousand kernel weight

References

  • An D, Su J, Liu Q, Zhu Y, Tong Y, Li J, Jing R, Li B, Li Z (2006) Mapping QTLs for nitrogen uptake in relation to the early growth of wheat (Triticum aestivum L.). Plant Soil 284:73–84

    Article  CAS  Google Scholar 

  • Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J (2004) BioMercator: integrating genetic maps and QTN towards discovery of candidate genes. Bioinform 20:2324–2326

    Article  CAS  Google Scholar 

  • Avni R, Zhao R, Pearce S, Jun Y, Uauy C, Tabbita F, Fahima T, Slade A, Dubcovsky J, Distelfeld A (2013) Functional characterization of GPC-1 genes in hexaploid wheat. Planta 239:313–324

    Article  PubMed  Google Scholar 

  • Barraclough PB, Howarth JR, Jones J, Lopez-Bellido R, Parmar S, Shepherd CE, Hawkesford MJ (2010) Nitrogen efficiency of wheat: genotypic and environmental variation and prospects for improvement. Eur J Agron 33:1–11

    Article  CAS  Google Scholar 

  • Bayer M, Milne I, Stephen G, Shaw P, Cardle L, Wright F, Marshall D (2011) Comparative visualization of genetic and physical maps with Strudel. Bioinformatics 27:1307–1308

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Bordes J, Ravel C, Jaubertie JP, Duperrier B, Gardet O, Heumez E, Pissavy AL, Charmet G, Le Gouis J, Balfourrier F (2013) Genomic regions associated with the nitrogen limitation response revealed in a global wheat core collection. Theor Appl Genet 126:805–822

    Article  CAS  PubMed  Google Scholar 

  • Breseghello F, Sorrells M (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177

    Article  PubMed Central  PubMed  Google Scholar 

  • Butler DG, Cullis BR, Gilmour AR, Gogel BJ (2009) ASReml-R reference manual. Technical report, Queensland Department of Primary Industries. http://www.vsni.co.uk/software/asreml/

  • Cadalen T, Boeuf C, Bernard S, Bernard M (1997) An intervarietal molecular marker map in Triticum aestivum L. Em. Thell. and comparison with a map from a wide cross. Theor Appl Genet 94:367–377

    Article  CAS  Google Scholar 

  • Conti V, Roncallo PF, Beaufort V, Cervigni GL, Miranda R, Jensen CA, Echenique VC (2011) Mapping of main and epistatic effect QTL associated to grain protein and gluten strength using a RIL population of durum wheat. J Appl Genet 52:287–298

    Article  CAS  PubMed  Google Scholar 

  • Cormier F, Faure S, Dubreuil P, Heumez E, Beauchêne K, Lafarge S, Praud S, Le Gouis J (2013) A multi-environmental study of recent breeding progress on nitrogen use efficiency in wheat (Triticum aestivum L.). Theor Appl Genet 126:3035–3048

    Article  PubMed  Google Scholar 

  • Crossa J, Burgueno J, Dreisigacker S, Vargas M, Herrera-Foessel SA, Lillemo M, Singh RP, Trethowan R, Warburton M, Franco J, Reynolds M, Crouch JH, Ortiz R (2007) Association analysis of historical bread wheat germplasm using additive covariance of relatives and population structure. Genetics 177:1889–1913

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Cullis BR, Smith AB, Coombes NE (2006) On the design of early generation variety trials with correlated data. J Agric Biol Envir S 11:381–393

    Article  Google Scholar 

  • Distelfeld A, Avni R, Fischer AM (2014) Senescence, nutrient remobilization, and yield in wheat and barley. J Exp Bot 65:3783–3798

    Article  PubMed  Google Scholar 

  • Dumur J, Jahier J, Bancel E, Laurière M, Bernard M, Branlard G (2004) Proteomic analysis of aneuploidy lines in the homeologous group 1 of the hexaploid wheat cultivar Courtot. Proteomics 4:2685–2695

    Article  CAS  PubMed  Google Scholar 

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Longmans Green, Harlow

    Google Scholar 

  • FAO (2011) Current world fertilizer trends and outlook to 2015. ftp://ftp.fao.org/ag/agp/docs/cwfto15.pdf

  • FAO (2012) World agriculture towards 203/2050, the 2012 revision. http://www.fao.org/docrep/016/ap106e/ap106e.pdf

  • Fontaine JX, 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 119:645–662

    Article  CAS  PubMed  Google Scholar 

  • Foulkes M, Hawkesford M, Barraclough P, Holdsworth M, Kerr S, Kightley S, Shewry P (2009) Identifying traits to improve the nitrogen economy of wheat: recent advances and future prospects. Field Crop Res 114:329–342

    Article  Google Scholar 

  • Gaju O, Allard V, Martre P, Snape JW, Heumez E, Le Gouis J, Moreau D, Bogard M, Griffiths S, Orford S, Hubbart S, Foulkes MJ (2011) Identification of traits to improve the nitrogen-use efficiency of wheat genotypes. Field Crop Res 123:139–152

    Article  Google Scholar 

  • Gregersen PL, Holm PB, Krupinska K (2008) Leaf senescence and nutrient remobilisation in barley and wheat. Plant Biol 10:37–49

    Article  CAS  PubMed  Google Scholar 

  • Guarda G, Padovan S, Delogu G (2004) Grain yield, nitrogen-use efficiency and baking quality of old and modern Italian bread wheat cultivars grown at different nitrogen levels. Eur J Agron 21:181–192

    Article  CAS  Google Scholar 

  • Guo Y, Kong FM, Xu YF, Zhao Y, Liang X, Wang YY, An DG, Li SS (2012) QTL mapping for seedling traits in wheat grown under varying concentrations of N, P and K nutrients. Theor Appl Genet 124:851–865

    Article  CAS  PubMed  Google Scholar 

  • Habash DZ, Bernard S, Schondelmaier J, Weyen J, Quarrie SA (2007) The genetics of nitrogen use in hexaploid wheat : N utilisation, development and yield. Theor Appl Genet 114:403–419

    Article  CAS  PubMed  Google Scholar 

  • Hill WG, Robertson A (1968) Linkage disequilibrium in finite populations. Theo Appl Genet 38:226–231

    Article  CAS  Google Scholar 

  • Hill WG, Weir BS (1998) Variances and covariances of squared linkage disequilibria in finite populations. Theor Popul Biol 33:54–78

    Article  Google Scholar 

  • Hirel B, Le Gouis J, Ney B, Gallais A (2007) The challenge of improving nitrogen use efficiency in crop plants: toward a more central role for genetic variability and quantitative genetics within integrated approaches. J Exp Bot 58:2369–2387

    Article  CAS  PubMed  Google Scholar 

  • Hörtensteiner S, Feller U (2002) Nitrogen metabolism and remobilisation during senescence. J Exp Bot 53:927–937

    Article  PubMed  Google Scholar 

  • Huang A, Xu S, Cai X (2014) Whole-genome quantitative trait locus mapping reveals major role of epistasis on yield of rice. PLoS One 9(1):e87330. doi:10.1371/journal.pone.008733

    Article  PubMed Central  PubMed  Google Scholar 

  • Justes E, Mary B, Meynard JM, Machet JM, Thelier-Huche L (1994) Determination of a critical nitrogen dilution curve for winter crops. Ann Bot Lond 74:397–407

    Article  CAS  Google Scholar 

  • Kamran A, Iqbal M, Spaner D (2014) Flowering time wheat (Triticum aestivum L.): a key factor for global adaptability. Euphytica 197:1–26

    Article  CAS  Google Scholar 

  • Kant S, Bi YM, Rothstein S (2011) Understanding plant response to nitrogen limitation for the improvement of crop nitrogen use efficiency. J Exp Bot 62:1499–1509

    Article  CAS  PubMed  Google Scholar 

  • Knyazikhin Y, Schull M, Stenberg P, Mõttus M, Rautiainen M, Yang Y, Marshak A, Latorre Carmona P, Kaufmann R, Lewis P, Disney M, Vanderbilt V, Davis A, Baret F, Jacquemoud S, Lyapustin A, Myneni R (2013) Hyperspectral remote sensing of foliar nitrogen content. PNAS 110:185–192

    Article  Google Scholar 

  • Korte A, Farlow A (2013) The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9:29

    Article  CAS  PubMed Central  PubMed  Google Scholar 

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

    CAS  PubMed Central  PubMed  Google Scholar 

  • Laperche A, Devienne-Barret F, Maury O, Le Gouis J, Ney B (2006) A simplified conceptual model of carbon/nitrogen functioning for QTL analysis of wheat adaptation to nitrogen deficiency. Theor Appl Genet 113:1131–1146

    Article  CAS  PubMed  Google Scholar 

  • 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 115:399–415

    Article  CAS  PubMed  Google Scholar 

  • Larsen R, Marx M (1985) An introduction to probability and its applications. Prentice-Hall Inc, Englewood Cliffs

    Google Scholar 

  • Le Gouis J, Beghin B, Heumez E, Pluchard P (2000) Genetic differences for nitrogen uptake and nitrogen utilisation efficiencies in winter wheat. Eur J Agron 12:163–173

    Article  Google Scholar 

  • Le Gouis J, Bordes J, Ravel C, Heumez E, Faure S, Praud S, Galic N, Remoué C, Balfourier F, Allard V, Rousset M (2012) Genome-wide association analysis to identify chromosomal regions determining components of earliness in wheat. Theor Appl Genet 124:597–611

    Article  PubMed  Google Scholar 

  • Lorenz AJ, Hamblin MT, Jannink JL (2010) Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS One 5(11):e14079. doi:10.1371/journal.pone.0014079

    Article  PubMed Central  PubMed  Google Scholar 

  • Mackay T (2014) Epistasis and quantitative traits: using model organisms to study gene–gene interactions. Nature Rev Genet 15:22–33

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Mangin B, Goffinet B, Rebai A (1994) Constructing confidence intervals for QTL location. Genetics 138:1301–1308

    CAS  PubMed Central  PubMed  Google Scholar 

  • Manske GGB, Ortiz-Monasterio IJ, Vlek PLG (2001) Techniques for measuring genetic diversity in roots. In: Application of physiology in wheat breeding. CIMMYT, Mexico, pp 208–218

  • McCarthy MI, Hirschhorn JN (2008) Genome-wide association studies: potential next steps on a genetic journey. Hum Mol Genet 17:156–165

    Article  Google Scholar 

  • Muurinen S, Slafer GA, Peltonen-Sainio P (2006) Breeding effects on nitrogen use efficiency of spring cereals under northern conditions. Crop Sci 46:561–568

    Article  CAS  Google Scholar 

  • Neumann K, Kobiljski B, Dencic S, Varshney RK, Börner A (2011) Genome-wide association mapping: a case study in bread wheat (Triticum aestivum L.). Mol Breed 27:37–58

    Article  Google Scholar 

  • Novoselovic D, Baric M, Drezner G, Gunjaca J, Lalic A (2004) Quantitative inheritance of some wheat plant traits. Genet Mol Biol 27:92–98

    Article  Google Scholar 

  • Opsahl T, Agneessens F, Skvoretz J (2010) Node centrality in weighted networks: generalizing degree and shortest paths. Soc Netw 32:245–251

    Article  Google Scholar 

  • Ortiz-Monasterio I, Sayre KD, Rajaram S, McMahon M (1997) Genetic progress in wheat yield and nitrogen use efficiency under four N rates. Crop Sci 37:898–904

    Article  Google Scholar 

  • Pathak RR, Lochab S, Raghuram N (2011) Plant systems | improving plant nitrogen-use efficiency. In: Comprehensive biotechnology, 2nd edn. Elsevier, Amsterdam, pp 209–218

  • Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. Plos Genet 2:e190

    Article  PubMed Central  PubMed  Google Scholar 

  • Payne P (1987) Genetics of wheat storage proteins and the effect of allelic variation on bread-making quality. Am Rev Plant Physiol 38:141–153

    Article  CAS  Google Scholar 

  • Philipps PC (2008) Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet 9:855–867

    Article  Google Scholar 

  • Plessis A, Ravel C, Bordes J, Balfourier F, Martre P (2013) Association study of wheat grain protein composition reveals that gliadin and glutenin composition are trans-regulated by different chromosome regions. J Exp Bot 64:3627–3644

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Quarrie SA, Steed A, Calestani C, Semikhodskii A, Lebreton C, Chinoy C, Steele N, Pljevljakusic D, Waterman E, Weyen J, Schondelmaier J, Habash DZ, Farmer P, Saker L, Clarkson DT, Abugalieva A, Yessimbekova M, Turuspekov Y, Abugalieva S, Tuberosa R, Sanguineti M-C, Hollington PA, Aragues R, Royo A, Dodig D (2005) A high density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTL for grain yield across a range of environments. Theor Appl Genet 110:865–880

    Article  CAS  PubMed  Google Scholar 

  • Quraishi UM, Abrouk M, Murat F (2011) Cross-genome map based dissection of a nitrogen use efficiency ortho-meta QTL in bread wheat unravels concerted cereal genome evolution. Plant J 65:745–756

    Article  CAS  PubMed  Google Scholar 

  • Reynolds M, Manes Y, Izanloo A, Langridge P (2009) Phenotyping approaches for physiological breeding and gene discovery in wheat. An Appl Biol 155:309–320

    Article  Google Scholar 

  • Rincent R, Moreau L, Monod H, Kuhn E, Melchinger AE, Malvar RA, Moreno-Gonzalez J, Nicolas S, Madur D, Combes V, Dumas F, Altmann T, Brunel D, Ouzunova M, Flament P, Dubreuil P, Charcosset A, Mary-Huard T (2014) Recovering power in association mapping panels with variable levels of linkage disequilibrium. Genet 197:375–387

    Article  Google Scholar 

  • Rogers JS (1972) Measures of genetic similarity and genetic distances. Studies in Genetics. University of Texas Publication 7213, pp 145–153

  • Rothstein S (2007) Returning to our roots: making plant biology research relevant to future challenges in agriculture. Plant Cell 19:2695–2699

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Somers D, Isaac P, Edwards K (2004) A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet 109:1105–1114

    Article  CAS  PubMed  Google Scholar 

  • Sourdille P, Gandon B, Chiquet V, Nicot N, Somers D, Murigneux A, Bernard M (2004) Wheat génoplante SSR mapping data release: a new set of markers and comprehensive genetic and physical mapping data. Funct Integr Genomics 4:12–25

    Article  CAS  PubMed  Google Scholar 

  • Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Sci 327:818–822

    Article  CAS  Google Scholar 

  • Tian F, Bradbury PJ, Briwn PJ, Hung H, Sun Q, Flint-Garcia S, Rocheford TR, Mcmullen MD, Holland JB, Buckler ES (2011) Genome-wide association study of maize identifies genes affecting leaf architecture. Nat Genet 43:159–162

    Article  CAS  PubMed  Google Scholar 

  • Uauy C, Distelfeld A, Fahima T, Blechl A, Dubcovsky J (2006) A NAC gene regulating senescence improves grain protein, zinc and irons content in wheat. Science 314:1298–1300

    Article  CAS  PubMed  Google Scholar 

  • Visscher PM, Thompson R, Haley CS (1996) Confidence intervals in QTL mapping by bootstrapping. Genetics 143:1013–1020

    CAS  PubMed Central  PubMed  Google Scholar 

  • Wang S, Debbie W, Forrest K, Allen A et al (2014) Characterization of polyploidy wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotech J. doi:10.1111/pbi.12183

    Google Scholar 

  • Wu X, Wang Z, Chang X, Jing R (2010) Genetic dissection of the developmental behaviours of plant height in wheat under diverse water regimes. J Exp Bot 61:2923–2937

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Würschum T, Langer S, Longin CFH, Korzun V, Akhunov E, Ebmeyer E, Schachschneider R, Kazman E, Schacht J, Reif JC (2013) Population structure, genetic diversity and linkage disequilibrium in elite winter wheat assessed with SNP and SSR markers. Theor Appl Genet 126:1477–1486

    Article  PubMed  Google Scholar 

  • Xu Y, Wang R, Tong Y, Zhao H, Xie Q, Liu D, Zhang A, Li B, Xu H, An D (2013) Mapping QTL for yield and nitrogen-related traits in wheat: influence of nitrogen and phosphorus fertilization on QTL expression. Theor Appl Genet 127:59–72

    Article  CAS  PubMed  Google Scholar 

  • Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    Article  CAS  PubMed  Google Scholar 

  • Zhang K, Tian J, Zhao L, Wang S (2008) Mapping QTL with epistatic effects and QTL × environment interactions for plant height using a doubled haploid population in cultivated wheat. J Genet Genomics 35:119–127

    Article  CAS  PubMed  Google Scholar 

  • Zhang LY, Liu DC, Guo XL, Yang WL, Sun JZ, Wang DW, Zhang A (2010) Genomic distribution of quantitative trait loci for yield and yield-related traits in common wheat. J Integr Plant Biol 52:996–1007

    Article  PubMed  Google Scholar 

  • Zhao K, Tung CW, Eizenga GC, Wright MH, Ali ML et al (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Comm 2:467–477

    Article  Google Scholar 

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Acknowledgments

These analyses were a part of a PhD thesis (129/2012) supported by the ANRT (Association Nationale de la Recherche et de la Technologie). Data were obtained thanks to the support of the ANR ProtNBle project (06 GPLA016). The authors are also grateful to experimental units staff at Estrées-Mons experimental unit (INRA) and at Villiers-le-Bâclea and Vraux (Arvalis), and to Quang Hien Le for English style proofing. Sincere thanks to Ian Mackay for his involvement in the reviewing process.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

The authors declare that the experiments comply with the current laws of the country in which they were performed.

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Authors and Affiliations

  1. Centre de recherche de Chappes, Biogemma, Route d’Ennezat CS90126, 63720, Chappes, France

    Fabien Cormier, Pierre Dubreuil, Stéphane Lafarge & Sébastien Praud

  2. Diversité et Ecophysiologie des Céréales, INRA, UMR 1095 Génétique, 5 chemin de Beaulieu, 63 039, Clermont-Ferrand, France

    Jacques Le Gouis

  3. Diversité et Ecophysiologie des Céréales, Université Blaise Pascal, UMR 1095 Génétique, 63 177, Aubière Cedex, France

    Jacques Le Gouis

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  1. Fabien Cormier
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  2. Jacques Le Gouis
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  3. Pierre Dubreuil
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  4. Stéphane Lafarge
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  5. Sébastien Praud
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Correspondence to Sébastien Praud.

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Communicated by Ian Mackay.

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Cormier, F., Le Gouis, J., Dubreuil, P. et al. A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.). Theor Appl Genet 127, 2679–2693 (2014). https://doi.org/10.1007/s00122-014-2407-7

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