Abstract
Coffee (Coffea arabica L.), one of the key export and cash crops in tropical and subtropical countries, suffers severe losses from the rust fungus Hemileia vastatrix. The transcriptome of H. vastatrix was analysed during a compatible interaction with coffee to obtain an exhaustive repertoire of the genes expressed during infection and to identify potential effector genes. Large-scale sequencing (454-GS-FLEX Titanium) of mixed coffee and rust cDNAs obtained from 21-day rust-infected leaves generated 352 146 sequences which assembled into 22 774 contigs. In the absence of any reference genomic sequences for Coffea or Hemileia, specific trinucleotide frequencies within expressed sequence tags (ESTs) and blast homology against a set of dicots and basidiomycete genomes were used to distinguish pathogen from plant sequences. About 30% (6763) of the contigs were assigned to H. vastatrix and 61% (13 951) to C. arabica. The majority (60%) of the rust sequences did not show homology to any genomic database, indicating that they were potential novel fungal genes. In silico analyses of the 6763 H. vastatrix contigs predicted 382 secreted proteins and identified homologues of the flax rust haustorially expressed secreted proteins (HESPs) and bean rust transferred protein 1 (RTP1). These rust candidate effectors showed conserved amino-acid domains and conserved patterns of cysteine positions suggestive of conserved functions during infection of host plants. Quantitative reverse transcription-polymerase chain reaction profiling of selected rust genes revealed dynamic expression patterns during the time course of infection of coffee leaves. This study provides the first valuable genomic resource for the agriculturally important plant pathogen H. vastatrix and the first comprehensive C. arabica EST dataset.