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Theoretical and Applied Genetics

, Volume 126, Issue 1, pp 143–158 | Cite as

Genetic mapping of a major dominant gene for resistance to Ralstonia solanacearum in eggplant

  • A. Lebeau
  • M. Gouy
  • M. C. Daunay
  • E. WickerEmail author
  • F. Chiroleu
  • P. Prior
  • A. Frary
  • J. DintingerEmail author
Original Paper

Abstract

Resistance of eggplant against Ralstonia solanacearum phylotype I strains was assessed in a F6 population of recombinant inbred lines (RILs) derived from a intra-specific cross between S. melongena MM738 (susceptible) and AG91-25 (resistant). Resistance traits were determined as disease score, percentage of wilted plants, and stem-based bacterial colonization index, as assessed in greenhouse experiments conducted in Réunion Island, France. The AG91-25 resistance was highly efficient toward strains CMR134, PSS366 and GMI1000, but only partial toward the highly virulent strain PSS4. The partial resistance found against PSS4 was overcome under high inoculation pressure, with heritability estimates from 0.28 to 0.53, depending on the traits and season. A genetic map was built with 119 AFLP, SSR and SRAP markers positioned on 18 linkage groups (LG), for a total length of 884 cM, and used for quantitative trait loci (QTL) analysis. A major dominant gene, named ERs1, controlled the resistance to strains CMR134, PSS366, and GMI1000. Against strain PSS4, this gene was not detected, but a significant QTL involved in delay of disease progress was detected on another LG. The possible use of the major resistance gene ERs1 in marker-assisted selection and the prospects offered for academic studies of a possible gene for gene system controlling resistance to bacterial wilt in solanaceous plants are discussed.

Keywords

Quantitative Trait Locus Amplify Fragment Length Polymorphism Amplify Fragment Length Polymorphism Marker Bacterial Wilt Sequence Characterize Amplify Region Marker 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors are grateful to A. Palloix, M. Pitrat, M. Causse, and V. Lefebvre (Institut National de la Recherche Agronomique (INRA), UR 1052) for their help in analysing the segregation results as well as for early review of this paper. We also thank E. Chapier-Fontaine, J. J. Chéron, J. M. Baptiste and S. Lebon (Centre de coopération International en Recherche Agronomique pour le Développement (CIRAD), Réunion) for providing technical assistance. This work was funded by De Ruiter Seeds, Enza Zaden, Gautier Semences, Nunhems, Rijk Zwaan, and Vilmorin & Cie; the European Regional Development Funds (FEDER) of the European Union, Conseil Régional de la Réunion also provided financial support as part of the programme “Lutte génétique contre les maladies émergentes chez les solanées maraîchères”(GENETOM).

Supplementary material

122_2012_1969_MOESM1_ESM.doc (76 kb)
Supplementary material 1 (DOC 75 kb)
122_2012_1969_MOESM2_ESM.doc (48 kb)
Supplementary material 2 (DOC 48 kb)

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© Springer-Verlag 2012

Authors and Affiliations

  1. 1.CIRAD, UMR Peuplements végétaux et Bioagresseurs en Milieu Tropical (PVBMT)Saint PierreFrance
  2. 2.INRA/CIRAD, UMR PVBMTSaint-Pierre CedexFrance
  3. 3.Unité de Génétique et Amélioration des Fruits et LégumesInstitut National de la Recherche Agronomique (INRA), Centre d’Avignon, UR1052MontfavetFrance
  4. 4.Department of Molecular Biology and GeneticsIzmir Institute of TechnologyUrlaTurkey

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