Theoretical and Applied Genetics

, Volume 118, Issue 2, pp 205–211 | Cite as

The development of a PCR-based marker linked to resistance to the blackcurrant gall mite (Cecidophyopsis ribis Acari: Eriophyidae)

  • Rex BrennanEmail author
  • Linzi Jorgensen
  • Sandra Gordon
  • Ken Loades
  • Christine Hackett
  • Joanne Russell
Original Paper


Gall mite (Cecidophyopsis ribis) is the most serious pest of blackcurrant (Ribes nigrum L.), causing the damaging condition known as ‘big bud’ and also transmitting blackcurrant reversion virus (BRV) within and between plantations. The identification of resistant germplasm is at present a time-consuming and expensive process, dependent on field infestation plots. Resistance based on gene Ce introgressed from gooseberry has been used in UK breeding programmes for blackcurrant. Using a bulked segregant analysis, 90 AFLP primer combinations were screened and a linkage map constructed around the resistance locus controlled by Ce. Sixteen of the primer combinations produced a fragment in the resistant bulked progeny and the gall mite-resistant parent, but not in the susceptible bulked progeny and parent; subsequent testing on individual progeny identified an AFLP fragment closely linked to gall mite resistance. This fragment, designated E41M88-280, was converted to a PCR-based marker based on sequence-specific primers, amplifying only in resistant individuals. Validation of this marker across a range of susceptible and resistant blackcurrant germplasm with different genetic backgrounds confirmed its reliability in the identification of mite-resistant germplasm containing gene Ce. The conversion of an AFLP fragment to a sequence-based PCR marker simplifies its application and therefore increases its utility for selection of mite-resistant germplasm in high-throughput breeding programmes for blackcurrant.


Gall Mite Infestation Resistant Germplasm AFLP Fragment Mite Resistance 
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.



Financial support for this work was provided by the Scottish Government Rural and Environment Research and Analysis Directorate.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Rex Brennan
    • 1
    Email author
  • Linzi Jorgensen
    • 1
  • Sandra Gordon
    • 1
  • Ken Loades
    • 1
  • Christine Hackett
    • 2
  • Joanne Russell
    • 1
  1. 1.Scottish Crop Research InstituteInvergowrieDundeeScotland, UK
  2. 2.Biomathematics and Statistics ScotlandInvergowrieDundeeScotland, UK

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