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Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg

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A repertoire of the genomic regions involved in quantitative resistance to Leptosphaeria maculans in winter oilseed rape was established from combined linkage-based QTL and genome-wide association (GWA) mapping.

Abstract

Linkage-based mapping of quantitative trait loci (QTL) and genome-wide association studies are complementary approaches for deciphering the genomic architecture of complex agronomical traits. In oilseed rape, quantitative resistance to blackleg disease, caused by L. maculans, is highly polygenic and is greatly influenced by the environment. In this study, we took advantage of multi-year data available on three segregating populations derived from the resistant cv Darmor and multi-year data available on oilseed rape panels to obtain a wide overview of the genomic regions involved in quantitative resistance to this pathogen in oilseed rape. Sixteen QTL regions were common to at least two biparental populations, of which nine were the same as previously detected regions in a multi-parental design derived from different resistant parents. Eight regions were significantly associated with quantitative resistance, of which five on A06, A08, A09, C01 and C04 were located within QTL support intervals. Homoeologous Brassica napus genes were found in eight homoeologous QTL regions, which corresponded to 657 pairs of homoeologous genes. Potential candidate genes underlying this quantitative resistance were identified. Genomic predictions and breeding are also discussed, taking into account the highly polygenic nature of this resistance.

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References

  • Alamery S, Tirnaz S, Bayer P, Tollenaere R, Chaloub B, Edwards D, Batley J (2017) Genome-wide identification and comparative analysis of NBS-LRR resistance genes in Brassica napus. Crop Pasture Sci 69:72–93

    Article  CAS  Google Scholar 

  • Allard A, Bink MCAM, Martinez S, Kelner J, Legave J, Guardo M, Di Pierro EA, Laurens F, Van De Weg EW, Costes E (2016) Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population. J Exp Bot 67:2875–2888

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Aubertot JN, Schott JJ, Penaud A, Brun H, Doré T (2004) Methods for sampling and assessment in relation to the spatial pattern of phoma stem canker (Leptosphaeria maculans) in oilseed rape. Eur J Plant Pathol 110:183–192

    Article  Google Scholar 

  • Avia K, Coelho SM, Montecinos GJ, Cormier A, Lerck F, Mauger S, Faugeron S, Valero M, Cock JM, Boudry P (2017) High-density genetic map and identification of QTLs for responses to temperature and salinity stresses in the model brown alga. Ectocarpus Sci Rep 7:43241

    Article  PubMed  Google Scholar 

  • Balesdent MH, Fudal I, Ollivier B, Bally P, Grandaubert J, Eber F, Chèvre AM, Leflon M, Rouxel T (2013) The dispensable chromosome of Leptosphaeria maculans shelters an effector gene conferring avirulence towards Brassica rapa. New Phytol 198:887–898

    Article  PubMed  CAS  Google Scholar 

  • Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Soft 67:1–48

    Article  Google Scholar 

  • Becker MG, Zhang X, Walker PL, Wan JC, Millar JL, Khan D et al (2017) Transcriptome analysis of the Brassica napus-Leptosphaeria maculans pathosystem identifies receptor, signalling and structural genes underlying plant resistance. Plant J 90:573–586

    Article  PubMed  CAS  Google Scholar 

  • Bian Y, Holland JB (2017) Data from: enhancing genomic prediction with genome-wide association studies in multiparental maize populations. Dryad Digit Repos. https://doi.org/10.5061/dryad.cd3hv

    Article  Google Scholar 

  • Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889–890

    Article  PubMed  CAS  Google Scholar 

  • Brun H, Levivier S, Somda I, Ruer D, Renard M, Chevre AM (2000) A field method for evaluating the potential durability of new resistance sources: application to the Leptosphaeria maculans-Brassica napus pathosystem. Phytopathol 90:961–966

    Article  CAS  Google Scholar 

  • Brun H, Chèvre AM, Fitt BD, Powers S, Besnard AL, Ermel M, Huteau V, Marquer B, Eber F, Renard M, Andrivon D (2010) Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus. New Phytol 185:285–299

    Article  PubMed  Google Scholar 

  • Chalhoub B, Denoeud F, Liu S, Parkin IAP, Tang H, Wang X et al (2014) Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science 345:950–953

    Article  PubMed  CAS  Google Scholar 

  • Clarke WE, Higgins EE, Plieske J, Wieseke R, Sidebottom C et al (2016) A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of singlelocus markers in the allotetraploid genome. Theor Appl Genet 129:1887–1899

    Article  PubMed  PubMed Central  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  CAS  Google Scholar 

  • Delourme R, Pilet-Nayel ML, Archipiano M, Horvais R, Tanguy X, Rouxel T, Brun H, Renard M, Balesdent MH (2004) A cluster of major specific resistance genes to Leptosphaeria maculans in Brassica napus. Phytopathol 94:578–583

    Article  CAS  Google Scholar 

  • Delourme R, Chevre AM, Brun H, Rouxel T, Balesdent MH, Dias JS et al (2006) Major gene and polygenic resistance to Leptosphaeria maculans in oilseed rape (Brassica napus). Eur J Plant Pathol 114:41–52

    Article  Google Scholar 

  • Delourme R, Falentin C, Fomeju BF, Boillot M, Lassalle G et al (2013) High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L. BMC Genomics 14:120

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Delourme R, Bousset L, Ermel E, Duffé P, Besnard AL, Marquer B, Fudal I, Linglin J, Chadoeuf J, Brun H (2014) Quantitative resistance affects the speed of frequency increase but not the diversity of the virulence alleles overcoming a major resistance gene to Leptosphaeria maculans in oilseed rape. Infect Genet Evol 27:490–499

    Article  PubMed  CAS  Google Scholar 

  • Endelman JB (2011) Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4:250–255

    Article  Google Scholar 

  • Evans N, Baierl A, Semenov MA, Gladders P, Fitt BDL (2008) Range and severity of a plant disease increased by global warming. J R Soc Interface 5:525–531

    Article  PubMed  Google Scholar 

  • Fitt BDL, Brun H, Barbetti MJ, Rimmer SR (2006) World-wide importance of phoma stem canker (Leptosphaeria maculans and L. biglobosa) on oilseed rape (Brassica napus). Eur J Plant Pathol 114:3–15

    Article  Google Scholar 

  • Foisset N, Delourme R, Barret P, Renard M (1995) Localization of agronomic traits on a B. napus map. In: Proceedings of 9th international Rapeseed congress, vol 4. Cambridge, UK, pp 1199–1201

  • Foisset N, Delourme R, Barret P, Hubert N, Landry BS, Renard M (1996) Molecular mapping analysis in Brassica napus using isozyme, RAPD and RFLP markers on a doubled haploid progeny. Theor Appl Genet 93:1017–1025

    Article  PubMed  CAS  Google Scholar 

  • Fopa Fomeju B, Falentin C, Lassalle G, Manzanares-Dauleux M, Delourme R (2014) Homologous duplicated regions are involved in quantitative resistance of Brassica napus to stem canker. BMC Genomics 15:498

    Article  PubMed  PubMed Central  Google Scholar 

  • Fopa Fomeju B, Falentin C, Lassalle G, Manzanares-Dauleux M, Delourme R (2015) Comparative genomic analysis of duplicated homoeologous regions involved in the resistance of Brassica napus to stem canker. Front Plant Sci 6:772

    Article  PubMed  PubMed Central  Google Scholar 

  • Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M et al (2002) The structure of haplotype blocks in the human genome. Science 296:2225–2229

    Article  PubMed  CAS  Google Scholar 

  • Goh L, Yap VB (2009) Effects of normalization on quantitative traits in association test. BMC Bioinform 10:415

    Article  CAS  Google Scholar 

  • Gore MA, Fang DD, Poland JA, Zhang J, Percy RG, Cantrell RG et al (2014) Linkage map construction and quantitative trait locus analysis of agronomic and fiber quality traits in cotton. Plant Genome. https://doi.org/10.3835/plantgenome2013.07.0023

    Article  Google Scholar 

  • Haddadi P, Ma L, Wang H, Borhan MH (2016) Genome-wide transcriptomic analyses provide insights into the lifestyle transition and effector repertoire of Leptosphaeria maculans during the colonization of Brassica napus seedlings. Mol Plant Pathol 17:1196–1210

    Article  PubMed  CAS  Google Scholar 

  • Huang YJ, Pirie EJ, Evans N, Delourme R, King GJ, Fitt BDL (2009) Quantitative resistance to symptomless growth of Leptosphaeria maculans (phoma stem canker) in Brassica napus (oilseed rape). Plant Pathol 58:314–323

    Article  Google Scholar 

  • Huang YJ, Jestin C, Welham SJ, King GJ, Manzanares-Dauleux MJ, Fitt BDL, Delourme R (2016) Identification of environmentally stable QTL for resistance against Leptosphaeria maculans in oilseed rape (Brassica napus). Theor Appl Genet 129:169–180

    Article  PubMed  CAS  Google Scholar 

  • Ichimura K, Shinozaki K, Tena G, Sheen J, Henry Y, Champion A et al (2002) Mitogen-activated protein kinase cascades in plants: a new nomenclature. Trends Plant Sci 7:301–308

    Article  CAS  Google Scholar 

  • Jestin C, Lodé M, Vallée P, Domin C, Falentin C, Horvais R, Coedel S, Manzanares-Dauleux MJ, Delourme R (2011) Association mapping of quantitative resistance for Leptosphaeria maculans in oilseed rape (Brassica napus L.). Mol Breed 27:271–287

    Article  Google Scholar 

  • Jestin C, Vallée P, Domin C, Manzanares-Dauleux MJ, Delourme R (2012) Assessment of a new strategy for selective phenotyping applied to complex traits in Brassica napus. Open J Genet 2:190–201

    Article  CAS  Google Scholar 

  • Jestin C, Bardol N, Lodé M, Duffé P, Domin C, Vallée P, Mangin B, Manzanares-Dauleux MJ, Delourme R (2015) Connected populations for detecting quantitative resistance factors to phoma stem canker in oilseed rape (Brassica napus L.). Mol Breed 35:1–16

    Article  Google Scholar 

  • Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178:1709–1723

    Article  PubMed  PubMed Central  Google Scholar 

  • Kruijer W, Boer MP, Malosetti M, Flood PJ, Engel B, Kooke R, Keurentjes JJ, van Eeuwijk FA (2015) Marker-based estimation of heritability in immortal populations. Genetics 199:379–398

    Article  PubMed  Google Scholar 

  • Kushalappa AC, Gunnaiah R (2013) Metabolo-proteomics to discover plant biotic stress resistance genes. Trends Plant Sci 18:522–531

    Article  PubMed  CAS  Google Scholar 

  • Kushalappa AC, Yogendra KN, Karre S (2016) Plant innate immune response: qualitative and quantitative resistance. Crit Rev Plant Sci 35:38–55

    Article  CAS  Google Scholar 

  • Larkan NJ, Raman H, Lydiate DJ, Robinson SJ, Yu F, Barbulescu DM, Raman R, Luckett DJ, Burton W, Wratten N, Salisbury PA, Rimmer SR, Borhan MH (2016) Multi-environment QTL studies suggest a role for cysteine-rich protein kinase genes in quantitative resistance to blackleg disease in Brassica napus. BMC Plant Biol 16:183

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Lay FT, Anderson MA (2005) Defensins-components of the innate immune system in plants. Curr Protein Pept Sci 6:85–101

    Article  PubMed  CAS  Google Scholar 

  • Li H, Sivasithamparam K, Barbetti MJ (2003) Breakdown of a Brassica rapa subsp. sylvestris single dominant blackleg resistance gene in B. napus rapeseed by Leptosphaeria maculans field isolates in Australia. Plant Dis 87:752

    Article  Google Scholar 

  • Long Y, Wang Z, Sun Z, Fernando DWG, McVetty PBE, Li G (2011) Identification of two blackleg resistance genes and fine mapping of one of these two genes in a Brassica napus canola cultivar ‘Surpass 400’. Theor Appl Genet 122:1223–1231

    Article  PubMed  Google Scholar 

  • Lowe RG, Cassin A, Grandaubert J, Clark BL, Van De Wouw AP, Rouxel T et al (2014) Genomes and transcriptomes of partners in plant-fungal-interactions between canola (Brassica napus) and two Leptosphaeria species. PLoS ONE 9:e103098

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Marcroft SJ, Purwantara A, Salisbury P, Potter TD, Wratter N, Khangura R et al (2002) Reaction of a range of Brassica species under Australian conditions to the fungus, Leptosphaeria maculans, the causal agent of blackleg. Aust J Exp Agric 42:587–594

    Article  Google Scholar 

  • Mitchell-Olds T, Schmitt J (2006) Genetic mechanisms and evolutionary significance of natural variation in Arabidopsis. Nature 441:947–952

    Article  PubMed  CAS  Google Scholar 

  • Nawrot R, Barylski J, Nowicki G, Broniarczyk J, Buchwald W, Gózdzicka-Józefiak A (2014) Plant antimicrobial peptides. Folia Microbiol 59:181–196

    Article  CAS  Google Scholar 

  • Nordborg M, Weigel D (2010) Next-generation genetics in plants. Nature 456:10–13

    Google Scholar 

  • Pilet ML, Delourme R, Foisset N, Renard M (1998) Identification of loci contributing to quantitative field resistance to blackleg disease, causal agent Leptosphaeria maculans (Desm.) Ces. et de Not., in Winter rapeseed (Brassica napus L.). Theor Appl Genet 96:23–30

    Article  Google Scholar 

  • Pilet ML, Duplan G, Archipiano M, Barret P, Baron C, Horvais R, Tanguy X, Lucas MO, Renard M, Delourme R (2001) Stability of QTL for field resistance to blackleg across two genetic backgrounds in oilseed rape. Crop Sci 41:197–205

    Article  CAS  Google Scholar 

  • Pilet-Nayel ML, Moury B, Caffier V, Montarry J, Kerlan MC, Fournet S, Durel CE, Delourme R (2017) Quantitative resistance to plant pathogens in pyramiding strategies for durable crop protection. Front Plant Sci 8:1838

    Article  PubMed  PubMed Central  Google Scholar 

  • Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/

  • Rabbi IY, Hamblin MT, Kumar PL, Gedil M, Ikpan AS, Jannink J-L, Kulakow P (2014) High-resolution mapping of resistance to cassava mosaic geminiviruses in cassava using genotyping-by-sequencing and its implications for breeding. Virus Res 186:87–96

    Article  PubMed  CAS  Google Scholar 

  • Raman R, Taylor B, Marcroft S, Stiller J, Eckermann P, Coombes N et al (2012) Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans; causing blackleg disease in canola (Brassica napus L.). Theor Appl Genet 125:405–418

    Article  PubMed  CAS  Google Scholar 

  • Raman H, Raman R, Larkan N (2013) Genetic dissection of blackleg resistance loci in rapeseed (Brassica napus L). In: Andersen SB (ed) Plant breeding from laboratories to fields. InTech, Luton. https://doi.org/10.5772/53611. ISBN 978-953-51-1090-3

    Chapter  Google Scholar 

  • Raman H, Raman R, Coombes N, Song J, Prangnell R, Bandaranayake C et al (2016) Genome-wide association analyses reveal complex genetic architecture underlying natural variation for flowering time in canola. Plant Cell Environ 39:1228–1239

    Article  PubMed  CAS  Google Scholar 

  • Rimmer SR (2006) Resistance genes to Leptosphaeria maculans in Brassica napus. Can J Plant Pathol 28:S288–S297

    Article  CAS  Google Scholar 

  • Rouxel T, Penaud A, Pinochet X, Brun H, Gout L, Delourme R et al (2003) A 10-year survey of populations of Leptosphaeria maculans in France indicates a rapid adaptation towards the Rlm1 resistance gene of oilseed rape. Eur J Plant Pathol 109:871–881

    Article  CAS  Google Scholar 

  • Schwender H, Ickstadt K (2008) Imputing missing genotypes with k nearest neighbors. Technical report, SFB 475, Department of Statistics, University of Dortmund

  • Tan B, Grattapaglia D, Martins GS, Zamprogno Ferreira K, Sundberg B, Ingvarsson PK (2017) Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids. BMC Plant Biol 17:110

    Article  PubMed  PubMed Central  Google Scholar 

  • Thomma BP, Cammue BP, Thevissen K (2002) Plant defensins. Planta 216:193–202

    Article  PubMed  CAS  Google Scholar 

  • West JS, Kharbanda PD, Barbetti MJ, Fitt BDL (2001) Epidemiology and management of Leptosphaeria maculans (phoma stem canker) on oilseed rape in Australia, Canada and Europe. Plant Pathol 50:10–27

    Article  Google Scholar 

  • Wong JH, Xia L, Ng TB (2007) A review of defensins of diverse origins. Curr Protein Pept Sci 8:446–459

    Article  PubMed  CAS  Google Scholar 

  • Yu F, Lydiate DJ, Rimmer SR (2005) Identification of two novel genes for blackleg resistance in Brassica napus. Theor Appl Genet 110:969–979

    Article  PubMed  CAS  Google Scholar 

  • Yu F, Lydiate DJ, Rimmer SR (2008) Identification and mapping of a third blackleg resistance locus in Brassica napus derived from B rapa subsp sylvestris. Genome 51:64–72

    Article  PubMed  CAS  Google Scholar 

  • Yu F, Gugel RK, Kutcher HR, Peng G, Rimmer SR (2013) Identification and mapping of a novel blackleg resistance locus LepR4 in the progenies from Brassica napus × B rapa subsp sylvestris. Theor Appl Genet 126:307–315

    Article  PubMed  CAS  Google Scholar 

  • Zhang X, Huang C, Wu D et al (2017) High-throughput phenotyping and QTL mapping reveals the genetic architecture of maize plant growth. Plant Physiol 173:1554–1564

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Zheng X, Levine D, Shen J, Gogarten SM, Laurie C, Weir BS (2012) A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28:3326–3328

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We would like to acknowledge Gilles Lassalle and Anne Laperche for the script that was used to choose the markers for QTL analysis and Mathieu Rousseau-Gueutin, Jérôme Morice for Circos representation of homoeologous relationships between the QTL regions. The authors are grateful to Claude Domin and the INRA Experimental Unit (UE La Motte, Le Rheu) for field experimentations. The authors would like to thank the BrACySol biological resource center (INRA Ploudaniel, France) for providing the seeds used in this study. This work was supported by the French ‘Institut National de la Recherche Agronomique’—Department of ‘Biologie et Amélioration des Plantes’, Terres Inovia and PROMOSOL. VK was funded through the European PLANT-KBBE-IV research program in the French-German Project GEWIDIS (Exploiting genome-wide diversity for disease resistance improvement in oilseed rape; ANR13-KBBE-0004-01).

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Correspondence to Régine Delourme.

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Communicated by Heiko C. Becker.

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Kumar, V., Paillard, S., Fopa-Fomeju, B. et al. Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg. Theor Appl Genet 131, 1627–1643 (2018). https://doi.org/10.1007/s00122-018-3103-9

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