Emerging Technologies

Planta

, Volume 235, Issue 5, pp 1065-1080

dHPLC efficiency for semi-automated cDNA-AFLP analyses and fragment collection in the apple scab-resistance gene model

  • Roberta ParisAffiliated withDepartment of Fruit Tree and Woody Plant Science, University of Bologna Email author 
  • , Luca DondiniAffiliated withDepartment of Fruit Tree and Woody Plant Science, University of Bologna
  • , Graziano ZanniniAffiliated withDepartment of Fruit Tree and Woody Plant Science, University of Bologna
  • , Daniela BastiaAffiliated withCentre for Applied Biomedical Research (CRBA), S. Orsola-Malpighi Hospital, University of Bologna
  • , Elena MarascoAffiliated withCentre for Applied Biomedical Research (CRBA), S. Orsola-Malpighi Hospital, University of Bologna
  • , Valentina GualdiAffiliated withGenomics Platform, Parco Tecnologico Padano
  • , Valeria RizziAffiliated withGenomics Platform, Parco Tecnologico Padano
  • , Pietro PiffanelliAffiliated withGenomics Platform, Parco Tecnologico Padano
  • , Vilma MantovaniAffiliated withCentre for Applied Biomedical Research (CRBA), S. Orsola-Malpighi Hospital, University of Bologna
    • , Stefano TartariniAffiliated withDepartment of Fruit Tree and Woody Plant Science, University of Bologna

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

Abstract

cDNA-AFLP analysis for transcript profiling has been successfully applied to study many plant biological systems, particularly plant–microbe interactions. However, the separation of cDNA-AFLP fragments by gel electrophoresis is reported to be labor-intensive with only limited potential for automation, and the collection of differential bands for gene identification is even more cumbersome. In this work, we present the use of dHPLC (denaturing high performance liquid chromatography) and automated DNA fragment collection using the WAVE® System to analyze and recover cDNA-AFLP fragments. The method is successfully applied to the MalusVenturia inaequalis interaction, making it possible to collect 66 different transcript-derived fragments for apple genes putatively involved in the defense response activated by the HcrVf2 resistance gene. The results, validated by real time quantitative RT-PCR, were consistent with the plant–pathogen interaction under investigation and this further supports the suitability of dHPLC for cDNA-AFLP transcript profiling. Features and advantages of this new approach are discussed, evincing that it is an almost fully automatable and cost-effective solution for processing large numbers of samples and collecting differential genes involved in other biological processes and non-model plants.

Keywords

Chromatography Defense Gene ontology annotation Malus x domestica qRT-PCR Plant–pathogen interaction