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Transcriptome analysis in Coffea eugenioides, an Arabica coffee ancestor, reveals differentially expressed genes in leaves and fruits

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Abstract

Studies in diploid parental species of polyploid plants are important to understand their contributions to the formation of plant and species evolution. Coffea eugenioides is a diploid species that is considered to be an ancestor of allopolyploid Coffea arabica together with Coffea canephora. Despite its importance in the evolutionary history of the main economic species of coffee, no study has focused on C. eugenioides molecular genetics. RNA-seq creates the possibility to generate reference transcriptomes and identify coding genes and potential candidates related to important agronomic traits. Therefore, the main objectives were to obtain a global overview of transcriptionally active genes in this species using next-generation sequencing and to analyze specific genes that were highly expressed in leaves and fruits with potential exploratory characteristics for breeding and understanding the evolutionary biology of coffee. A de novo assembly generated 36,935 contigs that were annotated using eight databases. We observed a total of ~5000 differentially expressed genes between leaves and fruits. Several genes exclusively expressed in fruits did not exhibit similarities with sequences in any database. We selected ten differentially expressed unigenes in leaves and fruits to evaluate transcriptional profiles using qPCR. Our study provides the first gene catalog for C. eugenioides and enhances the knowledge concerning the mechanisms involved in the C. arabica homeologous. Furthermore, this work will open new avenues for studies into specific genes and pathways in this species, especially related to fruit, and our data have potential value in assisted breeding applications.

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Acknowledgments

We are grateful to thank João Batista Gonçalves Dias da Silva (COCARI) for providing the C. eugenioides leaves and fruits used in this study and Juliana Costa Silva (UTFPR-Cornélio Procópio) for bioinformatics assistance. This work was funded by CAPES/Agropolis (1002-02 PHEGECO), CNPq, INCT-Café, FINEP (01.05.0665-00) and Fundação Araucária. We acknowledge the scholarships from CAPES (Priscila M. Yuyama, Suzana T. Ivamoto). Luiz Filipe P. Pereira received a research fellowship from CNPq. We also acknowledge the Center for Computational Engineering and Sciences at UNICAMP, SP, Brazil (FAPESP/CEPID project #2013/08293-7).

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  1. Douglas Silva Domingues

    Present address: Department of Botany, Instituto de Biociências de Rio Claro, Universidade Estadual Paulista (UNESP), Rio Claro, São Paulo, Brazil

Authors and Affiliations

  1. Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Estadual de Londrina (UEL), Londrina, Paraná, Brazil

    Priscila Mary Yuyama & Suzana Tiemi Ivamoto

  2. Laboratório de Biotecnologia Vegetal, Instituto Agronômico do Paraná (IAPAR), Londrina, Paraná, Brazil

    Priscila Mary Yuyama, Suzana Tiemi Ivamoto, Douglas Silva Domingues & Luiz Filipe Protasio Pereira

  3. Laboratório de Genômica e Expressão, Departamento de Genética, Evolução e Bioagentes, Instituto de Biologia, Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, Brazil

    Osvaldo Reis Júnior, Marcelo Falsarella Carazzolle & Gonçalo Amarante Guimarães Pereira

  4. Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR AGAP, 34398, Montpellier, France

    Pierre Charmetant & Thierry Leroy

  5. Embrapa Café, Brasília, DF, Brazil

    Luiz Filipe Protasio Pereira

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Correspondence to Luiz Filipe Protasio Pereira.

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The experiments in this manuscript comply with the current laws of the country in which they were performed. This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by S. Hohmann.

P. M. Yuyama, O. Reis Júnior and S. T. Ivamoto contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

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Supplementary material 1 Fig. S1 Contigs length distribution in C. eugenioides. Size distribution of the contigs obtained from de novo assembly of high quality clean reads (TIFF 9874 kb)

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Supplementary material 2 Fig. S2 C. eugenioides contigs involved in the starch and sucrose pathway using KEGG. All colored E.C. numbers (square) are the contigs with similarity (>1e-5) to their respective protein described for this metabolic pathway. Colors are used to differentiate the different enzymes within one map and enzymes with the same colors are the same (TIFF 11557 kb)

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Supplementary material 3 Fig. S3 Relative expression values of unigenes up-regulated in leaves (green) and fruits (red) organs by qPCR (Ct values scale). Bars represent the standard deviation values (TIFF 7494 kb)

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Supplementary material 4 Fig. S4 Phylogenetic analysis of C. eugenioides, A. thaliana and P. trichocarpa BURP genes. The abbreviations of species names are as follows: CE, Coffea eugenioides; AT, Arabidopsis thaliana; and PT, Populus trichocarpa. Bootstrap values are indicated in percentage (TIFF 13599 kb)

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Supplementary material 5 Table S1 Description based on the blast hit obtained by a sequential blast search of three protein databases (NCBI-nr, Swiss-Prot and PlantCyc) for the all C. eugenioides contigs (XLS 8163 kb)

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Supplementary material 6 Table S2 The 100 top-hit species distribution of BLAST matches of C. eugenioides contigs. The BLASTX score was defined as 1e-5 (XLS 42 kb)

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Supplementary material 7 Table S3 C. eugenioides contigs not annotated in Coffea EST database. a No hits genes in C. arabica ESTs b No hits genes in C. canephora CDS (XLS 2990 kb)

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Supplementary material 8 Table S4 Domains description of InterProScan in C. eugenioides contigs. 4a Output direct results of InterProScan domains. 4b Data used in Fig. 1, after manual filter of InterProScan annotation (XLS 586 kb)

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Supplementary material 9 Table S5 Description of 20 contigs with high expression levels in leaves and fruits and annotations in NCBI-nr and Swiss-Prot database. The BLASTX score was defined as 1e-5 (XLS 36 kb)

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Yuyama, P.M., Reis Júnior, O., Ivamoto, S.T. et al. Transcriptome analysis in Coffea eugenioides, an Arabica coffee ancestor, reveals differentially expressed genes in leaves and fruits. Mol Genet Genomics 291, 323–336 (2016). https://doi.org/10.1007/s00438-015-1111-x

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