Theoretical and Applied Genetics

, Volume 120, Issue 5, pp 909–919 | Cite as

Validation of QTLs for Orobanche crenata resistance in faba bean (Vicia faba L.) across environments and generations

  • Ramón Díaz-Ruiz
  • A. M. Torres
  • Z. Satovic
  • M. V. Gutierrez
  • J. I. Cubero
  • Belén Román
Original Paper
First Online:
Received:
Accepted:

Abstract

Broomrape (Orobanche crenata Forsk.) is a major root–parasite of faba bean (Vicia faba L.), that seriously limits crop cultivation in the whole Mediterranean area. This parasitic weed is difficult to control, difficult to evaluate and the resistance identified so far is of polygenic nature. This study was conducted to identify genetic regions associated with broomrape resistance in recombinant inbred lines (RILs) and to validate their previous location in the original F2 population derived from the cross between lines Vf6 and Vf136. A progeny consisting of 165 F6 RILs was evaluated in three environments across two locations in 2003 and 2004. Two hundred seventy seven molecular markers were assigned to 21 linkage groups (9 of them assigned to specific chromosomes) that covered 2,856.7 cM of the V. faba genome. The composite interval mapping on the F6 map detected more quantitative trait loci (QTL) than in the F2 analysis. In this sense, four QTLs controlling O. crenata resistance (Oc2–Oc5) were identified in the RI segregant population in three different environments. Only Oc1, previously reported in the F2 population, was not significant in the advanced lines. Oc2 and Oc3 were found to be associated with O. crenata resistance in at least two of the three environments, while the remaining two, Oc4 and Oc5, were only detected in Córdoba-04 and Mengíbar-04 and seemed to be environment dependent.

Keywords

Quantitative Trait Locus Resistance Index Quantitative Trait Locus Analysis Faba Bean Quantitative Trait Locus Position 
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.
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Notes

Acknowledgments

The authors research has been granted by projects AGL2005-07497-C02-01/AGR from MEC (Ministerio de Educación y Ciencia), RTA2007-00030 from INIA (Instituto Nacional de Investigaciones Agrarias) and by the European Community project EUFABA (QLK5-CT2002-02307).

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Ramón Díaz-Ruiz
    • 1
  • A. M. Torres
    • 2
  • Z. Satovic
    • 3
  • M. V. Gutierrez
    • 2
  • J. I. Cubero
    • 4
  • Belén Román
    • 2
  1. 1.Colegio de PostgraduadosMunicipio de San Pedro CholulaMexico
  2. 2.IFAPA_Centro Alameda del Obispo, Área de Mejora y BiotecnologíaCórdobaSpain
  3. 3.Department of Seed Science and Technology, Faculty of AgricultureUniversity of ZagrebZagrebCroatia
  4. 4.Departamento de GenéticaETSIAM, Universidad de CórdobaCórdobaSpain

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