Characterization by suppression subtractive hybridization of transcripts that are differentially expressed in leaves of apple scab-resistant and susceptible cultivars of Malus domestica
- 6 April 2005
- journal article
- research article
- Published by Springer Nature in Molecular Genetics and Genomics
- Vol. 273 (4) , 326-335
- https://doi.org/10.1007/s00438-005-1136-7
Abstract
In order to compare transcription profiles in cultivars of Malus domestica that are differentially sensitive to apple scab (Venturia inaequalis), two cDNA libraries were constructed using the suppression subtractive hybridization (SSH) method. Subtraction hybridization was performed between cDNAs from uninfected young leaves of the resistant cultivar Remo and the susceptible Elstar. In total, 480 EST clones were obtained: 218 (ELSTAR) clones represent transcripts that are preferentially expressed in Elstar, while the other 262 (REMO) are derived from RNAs that are more highly expressed in Remo. The putative functions of about 50% of the cloned sequences could be identified by sequencing and subsequent homology searches in databases or by dot-blot hybridization to known targets. In the resistant cv. Remo the levels of transcripts encoding a number of proteins related to plant defense (such as β-1,3-glucanase, ribonuclease-like PR10, cysteine protease inhibitor, endochitinase, ferrochelatase, and ADP-ribosylation factor) or detoxification of reactive oxygen species (such as superoxide dismutase) were highly up-regulated relative to the amounts present in cv. Elstar. Most surprising was the large number of clones derived from mRNAs for metallothioneins of type 3 (91 out of 262) found in the REMO population. The corresponding transcripts were only present in small amounts in young uninfected leaves of the cv. Elstar, but were up-regulated in the susceptible cultivar after inoculation with V. inaequalis. These results indicate that constitutively high-level expression of PR proteins may protect cv. Remo from infection by different plant pathogens.Keywords
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