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

Mondego JM, Vidal RO, Carazzolle MF, Tokuda EK, Parizzi LP, Costa GG, Pereira LF, Andrade AC, Colombo CA, Vieira LG, Pereira GA, Brazilian Coffee Genome Project Consorti - BMC Plant Biol. (2011)

Bottom Line: OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species.Hierarchical clustering was used to independently group C. arabica and C. canephora expression 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Centro de Recursos Genéticos Vegetais, Instituto Agronômico de Campinas, CP 28, 13001-970, Campinas-SP, Brazil.

ABSTRACT

Background: Coffee 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 arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency.

Results: Assembling the expressed sequence tags (ESTs) of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. 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 between Coffea spp. 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 group C. arabica and C. canephora expression 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.

Conclusion: We present the first comprehensive genome-wide transcript profile study of C. arabica and C. canephora, which can be freely assessed by the scientific community at http://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 and Coffea spp. developmental traits, providing valuable insights for coffee breeding and biotechnology, especially concerning sugar metabolism and stress tolerance.

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Flow diagram of bioinformatics procedures applied in C. arabica and C. canephora transcriptomic analyses.
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Figure 1: Flow diagram of bioinformatics procedures applied in C. arabica and C. canephora transcriptomic analyses.

Mentions: To evaluate ESTs from Coffea spp. we collected 187,412 ESTs derived from 43 cDNA libraries produced by the Brazilian Coffee Genome Project initiative [21]. The C. arabica libraries represent diverse organs, plant developmental stages and stress treatments from Mundo Novo and Catuaí cultivars, excluding germinating seeds (cv Rubi) (Additional File 1). In the case of C. canephora, 62,823 ESTs from six cDNA libraries of the Nestlé and Cornell C. canephora sequencing initiative [22] and 15,647 C. canephora ESTs from three cDNA libraries constructed by the Brazilian Coffee Genome Project initiative [21] were collected yielding a total of 78,470 ESTs (Additional File 1). All ESTs were produced by the Sanger method, and cDNA clones were subjected only to 5' sequencing. The pipeline of C. arabica and C. canephora EST analysis is described in Figure 1.


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

Mondego JM, Vidal RO, Carazzolle MF, Tokuda EK, Parizzi LP, Costa GG, Pereira LF, Andrade AC, Colombo CA, Vieira LG, Pereira GA, Brazilian Coffee Genome Project Consorti - BMC Plant Biol. (2011)

Flow diagram of bioinformatics procedures applied in C. arabica and C. canephora transcriptomic analyses.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3045888&req=5

Figure 1: Flow diagram of bioinformatics procedures applied in C. arabica and C. canephora transcriptomic analyses.
Mentions: To evaluate ESTs from Coffea spp. we collected 187,412 ESTs derived from 43 cDNA libraries produced by the Brazilian Coffee Genome Project initiative [21]. The C. arabica libraries represent diverse organs, plant developmental stages and stress treatments from Mundo Novo and Catuaí cultivars, excluding germinating seeds (cv Rubi) (Additional File 1). In the case of C. canephora, 62,823 ESTs from six cDNA libraries of the Nestlé and Cornell C. canephora sequencing initiative [22] and 15,647 C. canephora ESTs from three cDNA libraries constructed by the Brazilian Coffee Genome Project initiative [21] were collected yielding a total of 78,470 ESTs (Additional File 1). All ESTs were produced by the Sanger method, and cDNA clones were subjected only to 5' sequencing. The pipeline of C. arabica and C. canephora EST analysis is described in Figure 1.

Bottom Line: OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species.Hierarchical clustering was used to independently group C. arabica and C. canephora expression 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Centro de Recursos Genéticos Vegetais, Instituto Agronômico de Campinas, CP 28, 13001-970, Campinas-SP, Brazil.

ABSTRACT

Background: Coffee 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 arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency.

Results: Assembling the expressed sequence tags (ESTs) of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. 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 between Coffea spp. 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 group C. arabica and C. canephora expression 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.

Conclusion: We present the first comprehensive genome-wide transcript profile study of C. arabica and C. canephora, which can be freely assessed by the scientific community at http://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 and Coffea spp. developmental traits, providing valuable insights for coffee breeding and biotechnology, especially concerning sugar metabolism and stress tolerance.

Show MeSH
Related in: MedlinePlus