An EST-based analysis identifies new genes and reveals distinctive gene expression features of Coffea arabica and Coffea canephora

Abstract

AbstractBackgroundCoffee is one of the world's most important crops; it is consumed worldwide and plays a significant role in the economy of producing countries.Coffea arabicaandC. canephoraare responsible for 70 and 30% of commercial production, respectively.C. arabicais an allotetraploid from a recent hybridization of the diploid species,C. canephoraandC. eugenioides.C. arabicahas lower genetic diversity and results in a higher quality beverage thanC. canephora. Research initiatives have been launched to produce genomic and transcriptomic data aboutCoffeaspp. as a strategy to improve breeding efficiency.ResultsAssembling the expressed sequence tags (ESTs) ofC. arabicaandC. canephoraproduced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters ofC. arabicaand 16,665 clusters ofC. canephora. We detected different GC3 profiles between these species that are related to their genome structure and mating system. BLAST analysis revealed similarities between coffee and grape (Vitis vinifera) genes. Using KA/KS analysis, we identified coffee genes under purifying and positive selection. Protein domain and gene ontology analyses suggested differences betweenCoffeaspp. data, mainly in relation to complex sugar synthases and nucleotide binding proteins. OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species. Among the interesting families annotated are new cystatins, glycine-rich proteins and RALF-like peptides. Hierarchical clustering was used to independently groupC. arabicaandC. canephoraexpression clusters according to expression data extracted from EST libraries, resulting in the identification of differentially expressed genes. Based on these results, we emphasize gene annotation and discuss plant defenses, abiotic stress and cup quality-related functional categories.ConclusionWe present the first comprehensive genome-wide transcript profile study ofC. arabicaandC. canephora, which can be freely assessed by the scientific community athttp://www.lge.ibi.unicamp.br/coffea. Our data reveal the presence of species-specific/prevalent genes in coffee that may help to explain particular characteristics of these two crops. The identification of differentially expressed transcripts offers a starting point for the correlation between gene expression profiles andCoffeaspp. developmental traits, providing valuable insights for coffee breeding and biotechnology, especially concerning sugar metabolism and stress tolerance.