Gene expression analysis by cDNA-AFLP in barley ( Hordeum vulgare L.) after powdery mildew ( Blumeria graminis f.sp. hordei , Bgh ) inoculation revealed 615 (3.7%) of 16 500 screened cDNA fragments being differentially regulated 4 and/or 12 h after inoculation. Of these transcript derived fragments (TDFs), 120 were sequenced, and for 28 out of 29 tested, induction was confirmed via RT-PCR. Most TDFs did not show any homology to sequences with known functions, others showed homology to genes involved in primary and secondary metabolism, pathogen response, redox regulation, and signal transduction. TDFs with homology to a MAP kinase ( PWMK1 ), a WRKY transcription factor, a heparanase, an immunophilin, a cytochrome P450, and a receptor-like protein kinase were isolated as full length cDNAs. Knockdown by RNA interference via biolistic delivery of sequence specific double stranded RNA to leaf segments tagged two of these genes as possible candidates being causally involved in the outcome of the barley- Bgh interaction. Knockdown of the receptor-like protein kinase and the WRKY transcription factor increased resistance to the fungus, while knockdown of PWMK1 only led to a slightly enhanced susceptibility of epidermal cells to Bgh . This suggests that the receptor-like protein kinase and the WRKY protein are candidates for negative regulators of powdery mildew resistance. Based on expression analyses, PWMK1 appears to be more generally involved in stress response.

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Powdery mildew is an important pathogen of barley in many barleygrowing areas. To identify molecular markers for the resistance gene Mlg located on chromosome 4H, a cDNA-AFLP approach was carried out on near-isogenic lines. Based on the identification of a differentiating fragment of 37 bp, which turned out to be part of a nucleoside diphosphate kinase as estimated by BLASTN, a CAPS marker has been developed, which co-segregated with Mlg in a population of 738 F 2 -plants. Due to its co-dominant inheritance, clear banding pattern and close linkage this marker is well suited for marker-based selection procedures.