Limits...
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.

Show MeSH

Related in: MedlinePlus

Distribution of GC in the coding regions of Arabidopsis thaliana, Solanum lycopersicum, C. arabica and C. canephora.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3045888&req=5

Figure 3: Distribution of GC in the coding regions of Arabidopsis thaliana, Solanum lycopersicum, C. arabica and C. canephora.

Mentions: Based on the annotation of CDS, we evaluated the GC content in coding regions. In general, the GC and GC3 profiles (i.e., the GC level at the third codon position) of C. canephora and C. arabica are similar to Arabidopsis and tomato. The unimodal GC distribution is a common feature of dicotyledons (Figure 3), whereas bimodal distribution is common in monocotyledons [17,25]. Nevertheless, Coffea spp.and Arabidopsis have a slightly higher proportion of genes with high GC content than tomato and have a more accentuated peak shift in GC3 content (Figure 3). This difference between Arabidopsis and tomato was found previously [25] and was attributed to differences in the gene samples, such as the presence of intron-retained transcripts (differentially spliced transcripts) in tomato. A more detailed inspection revealed that C. arabica has only one GC3 peak, while C. canephora has two close peaks: the first similar to that found for C. arabica and the other positioned toward the "GC-rich content area". This C. canephora pattern may be related to its outcrossing mating system because allogamous species tend to accumulate more polymorphism in the third codon position and to be more GC-rich than autogamous species [26], as is the case of Arabica coffee, tomato and Arabidopsis.


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)

Distribution of GC in the coding regions of Arabidopsis thaliana, Solanum lycopersicum, C. arabica and C. canephora.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: Distribution of GC in the coding regions of Arabidopsis thaliana, Solanum lycopersicum, C. arabica and C. canephora.
Mentions: Based on the annotation of CDS, we evaluated the GC content in coding regions. In general, the GC and GC3 profiles (i.e., the GC level at the third codon position) of C. canephora and C. arabica are similar to Arabidopsis and tomato. The unimodal GC distribution is a common feature of dicotyledons (Figure 3), whereas bimodal distribution is common in monocotyledons [17,25]. Nevertheless, Coffea spp.and Arabidopsis have a slightly higher proportion of genes with high GC content than tomato and have a more accentuated peak shift in GC3 content (Figure 3). This difference between Arabidopsis and tomato was found previously [25] and was attributed to differences in the gene samples, such as the presence of intron-retained transcripts (differentially spliced transcripts) in tomato. A more detailed inspection revealed that C. arabica has only one GC3 peak, while C. canephora has two close peaks: the first similar to that found for C. arabica and the other positioned toward the "GC-rich content area". This C. canephora pattern may be related to its outcrossing mating system because allogamous species tend to accumulate more polymorphism in the third codon position and to be more GC-rich than autogamous species [26], as is the case of Arabica coffee, tomato and Arabidopsis.

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