Skip to main content
SpringerLink
Log in

Application of Data Mining Algorithms to Classify Biological Data: The Coffea canephora Genome Case

  • Conference paper
  • First Online:
Advances in Computing (CCC 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 735))

Included in the following conference series:

Abstract

Bioinformatics is now one of the most important fields of modern sciences grouping different fields of research such as Biology, Genomics, Genetics and Molecular evolution. These fields generate a large amount of information via the utilization of the new generations of sequencing techniques (NGS). This amount of data requires the development of a new generation of tools able to store and analyze efficiently and rapidly the information. Coffea canephora also called the Robusta coffee is one of the most important tree for tropical countries. This genome has been recently sequenced. One of the characteristics of this genome is the presence of numerous repeated elements, representing more than 50% of the genome sequence. The analysis and classification of such amount of repeated sequences require innovative approaches. Here, we present how data mining and machine learning can contribute to process sequencing data for the fast classification of a class of repeated sequences, called transposable elements.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Bash is a user interface to Unix operating system that accepts commands and generally produces text-based output [46].

  2. 2.

    Fasta format is a standard for sequence files that each sequence has an identity line beginning with > character followed by its nucleotides [http://www.ncbi.nlm.nih.gov/blast/fasta.shtml].

References

  1. López-Gartner, G., Agudelo-Valencia, D., Castaño, S., Isaza, G.A., Castillo, L.F., Sánchez, M., Arango, J.: Identification of a putative ganoderic acid pathway enzyme in a Ganoderma Australe transcriptome by means of a Hidden Markov Model. In: Overbeek, R., Rocha, M.P., Fdez-Riverola, F., Paz, J.F. (eds.) 9th International Conference on Practical Applications of Computational Biology and Bioinformatics. AISC, vol. 375, pp. 107–115. Springer, Cham (2015). doi:10.1007/978-3-319-19776-0_12

    Chapter  Google Scholar 

  2. Orozco, S., Jeferson, A.: Aplication of artificial intelligence in bioinformatics, advances, definitions and tools. UGCiencia 22, 159–171 (2016)

    Article  Google Scholar 

  3. Castillo, L.F., López-gartner, G., Isaza, G.A., Sánchez, M.: GITIRBio: a semantic and distributed service oriented-architecture for bioinformatics pipeline. J. Integr. Bioinform. 12, 1–15 (2015)

    Google Scholar 

  4. Blankenberg, D., Von Kuster, G., Coraor, N., Ananda, G., Lazarus, R., Mangan, M., Nekrutenko, A., Taylor, J.: Galaxy: a web-based genome analysis tool for experimentalists. Curr. Protoc. Mol. Biol. 1–21 (2010)

    Google Scholar 

  5. Sumathi, S., Sivanandam, S.N.: Introduction to Data Mining Principles. Springer, Heidelberg (2006). doi:10.1007/978-3-540-34351-6

    Book  MATH  Google Scholar 

  6. Markov, Z., Russell, I.: An introduction to the WEKA data mining system. ACM SIGCSE Bull. 38, 367–368 (2006)

    Article  Google Scholar 

  7. Jaffar, J., Michaylov, S., Stuckey, P.J., Yap, R.H.C.: The CLP(R) language and system. ACM Trans. Program. Lang. Syst. 14, 339 (1992)

    Article  Google Scholar 

  8. Guyot, R., Darré, T., Dupeyron, M., de Kochko, A., Hamon, S., Couturon, E., Crouzillat, D., Rigoreau, M., Rakotomalala, J.J., Raharimalala, N.E., Akaffou, S.D., Hamon, P.: Partial sequencing reveals the transposable element composition of Coffea genomes and provides evidence for distinct evolutionary stories. Mol. Genet. Genomics 291, 1979–1990 (2016)

    Article  Google Scholar 

  9. Muszewska, A., Hoffman-Sommer, M., Grynberg, M.: LTR retrotransposons in fungi. PLoS One 6 (2011)

    Google Scholar 

  10. Beulé, T., Agbessi, M.D., Dussert, S., Jaligot, E., Guyot, R.: Genome-wide analysis of LTR-retrotransposons in oil palm. BMC Genom. 16, 1–14 (2015)

    Article  Google Scholar 

  11. Denoeud, F., Carretero-Paulet, L., Dereeper, A., Droc, G., Guyot, R., Pietrella, M., Zheng, C., Alberti, A., Anthony, F., Aprea, G., Aury, J.-M., Bento, P., Bernard, M., Bocs, S., Campa, C., Cenci, A., Combes, M.-C., Crouzillat, D., Da Silva, C., Daddiego, L., De Bellis, F., Dussert, S., Garsmeur, O., Gayraud, T., Guignon, V., Jahn, K., Jamilloux, V., Joët, T., Labadie, K., Lan, T., Leclercq, J., Lepelley, M., Leroy, T., Li, L.-T., Librado, P., Lopez, L., Muñoz, A., Noel, B., Pallavicini, A., Perrotta, G., Poncet, V., Pot, D., Priyono, Rigoreau, M., Rouard, M., Rozas, J., Tranchant-Dubreuil, C., VanBuren, R., Zhang, Q., Andrade, A.C., Argout, X., Bertrand, B., de Kochko, A., Graziosi, G., Henry, R.J., Jayarama, Ming, R., Nagai, C., Rounsley, S., Sankoff, D., Giuliano, G., Albert, V.A., Wincker, P., Lashermes, P.: The coffee genome provides insight into the convergent evolution of caffeine biosynthesis. Science 345, 1181–1184 (2014)

    Google Scholar 

  12. Chaparro, C., Gayraud, T., De Souza, R.F., Domingues, D.S., Akaffou, S., Vanzela, A.L.L., De Kochko, A., Rigoreau, M., Crouzillat, D., Hamon, S., Hamon, P., Guyot, R.: Terminal-repeat retrotransposons with gAG domain in plant genomes: a new testimony on the complex world of transposable elements. Genome Biol. Evol. 7, 493–504 (2015)

    Article  Google Scholar 

  13. Guyot, R., de la Mare, M., Viader, V., Hamon, P., Coriton, O., Bustamante-porras, J., Poncet, V., Campa, C., Hamon, S., de Kochko, A.: Microcollinearity in an ethylene receptor coding gene region of the Coffea canephora genome is extensively conserved with Vitis vinifera and other distant dicotyledonous sequenced genomes. BMC Plant Biol. 9, 1–15 (2009)

    Article  Google Scholar 

  14. Esteves Vieira, L.G., Andrade, A.C., Colombo, C.A., De Araújo Moraes, A.H., Metha, Â., De Oliveira, A.C., Labate, C.A., Marino, C.L., Monteiro-Vitorello, C.D.B., Monte, D.D.C., Giglioti, É., Kimura, E.T., Romano, E., Kuramae, E.E., Macedo Lemos, E.G., Pereira De Almeida, E.R., Jorge, É.C., Albuquerque, É.V.S., Da Silva, F.R., Da Vinecky, F., Sawazaki, H.E., Dorry, H.F.A., Carrer, H., Abreu, I.N., Batista, J.A.N., Teixeira, J.B., Kitajima, J.P., Xavier, K.G., De Lima, L.M., Aranha De Camargo, L.E., Protasio Pereira, L.F., Coutinho, L.L., Franco Lemos, M.V., Romano, M.R., Machado, M.A., Do Carmo Costa, M.M., Grossi De Sá, M.F., Goldman, M.H.S., Ferro, M.I.T., Penha Tinoco, M.L., Oliveira, M.C., Van Sluys, M.A., Shimizu, M.M., Maluf, M.P., Souza Da Eira, M.T., Guerreiro Filho, O., Arruda, P., Mazzafera, P., Correa Mariani, P.D.S., De Oliveira, R.L.B.C., Harakava, R., Balbao, S.F., Siu, M.T., Zingaretti Di Mauro, S.M., Santos, S.N., Siqueira, W.J., Lacerda Costa, G.G., Formighieri, E.F., Carazzolle, M.F., Guimarães Pereira, G.A.: Brazilian coffee genome project: An EST-based genomic resource. Brazilian J. Plant Physiol. 18, 95–108 (2006)

    Google Scholar 

  15. Dereeper, A., Guyot, R., Tranchant-Dubreuil, C., Anthony, F., Argout, X., de Bellis, F., Combes, M.C., Gavory, F., de Kochko, A., Kudrna, D., Leroy, T., Poulain, J., Rondeau, M., Song, X., Wing, R., Lashermes, P.: BAC-end sequences analysis provides first insights into coffee (Coffea canephora P.) genome composition and evolution. Plant Mol. Biol. 83, 177–189 (2013)

    Article  Google Scholar 

  16. Leroy, T., Marraccini, P., Dufour, M., Montagnon, C., Lashermes, P., Sabau, X., Ferreira, L.P., Jourdan, I., Pot, D., Andrade, A.C., Glaszmann, J.C., Vieira, L.G.E., Piffanelli, P.: Construction and characterization of a Coffea canephora BAC library to study the organization of sucrose biosynthesis genes. Theor. Appl. Genet. 111, 1032–1041 (2005)

    Article  Google Scholar 

  17. Yu, Q., Guyot, R., De Kochko, A., Byers, A., Navajas-Pérez, R., Langston, B.J., Dubreuil-Tranchant, C., Paterson, A.H., Poncet, V., Nagai, C., Ming, R.: Micro-collinearity and genome evolution in the vicinity of an ethylene receptor gene of cultivated diploid and allotetraploid coffee species (Coffea). Plant J. 67, 305–317 (2011)

    Article  Google Scholar 

  18. Llorens, C., Futami, R., Covelli, L., Domínguez-Escribá, L., Viu, J.M., Tamarit, D., Aguilar-Rodríguez, J., Vicente-Ripolles, M., Fuster, G., Bernet, G.P., et al.: The Gypsy Database (GyDB) of mobile genetic elements: release 2.0. Nucleic Acids Res. (2010). doi:10.1093/nar/gkq1061

    Google Scholar 

  19. Wicker, T., Sabot, F., Hua-Van, A., Bennetzen, J.L., Capy, P., Chalhoub, B., Flavell, A., Leroy, P., Morgante, M., Panaud, O., Paux, E., SanMiguel, P., Schulman, A.H.: A unified classification system for eukaryotic transposable elements. Nat. Rev. Genet. 8, 973–982 (2007)

    Article  Google Scholar 

  20. Witte, C.-P., Le, Q.H., Bureau, T., Kumar, A.: Terminal-repeat retrotransposons in miniature (TRIM) are involved in restructuring plant genomes. Proc. Natl. Acad. Sci. 98, 13778–13783 (2001)

    Article  Google Scholar 

  21. Kalendar, R., Vicient, C.M., Peleg, O., Anamthawat-Jonsson, K., Bolshoy, A., Schulman, A.H.: Large retrotransposon derivatives: abundant, conserved but nonautonomous retroelements of barley and related genomes. Genetics 166, 1437–1450 (2004)

    Article  Google Scholar 

  22. Tanskanen, J.A., Sabot, F., Vicient, C., Schulman, A.H.: Life without GAG: the BARE-2 retrotransposon as a parasite’s parasite. Gene 390, 166–174 (2007)

    Article  Google Scholar 

  23. Quesneville, H., Bergman, C.M., Andrieu, O., Autard, D., Nouaud, D., Ashburner, M., Anxolabehere, D.: Combined evidence annotation of transposable elements in genome sequences. PLoS Comput. Biol. 1, 166–175 (2005)

    Article  Google Scholar 

  24. Price, A.L., Jones, N.C., Pevzner, P.A.: De novo identification of repeat families in large genomes. Bioinformatics 21, 351–358 (2005)

    Article  Google Scholar 

  25. Ellinghaus, D., Kurtz, S., Willhoeft, U.: LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons. BMC Bioinform. 9, 18 (2008)

    Article  Google Scholar 

  26. McCarthy, E.M., McDonald, J.F.: LTR_STRUC: a novel search and identification program for LTR retrotransposons. Bioinformatics 19, 362–367 (2003)

    Article  Google Scholar 

  27. Xu, Z., Wang, H.: LTR-FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, 265–268 (2007)

    Article  Google Scholar 

  28. Disdero, E., Filée, J.: LoRTE: detecting transposon-induced genomic variants using low coverage PacBio long read sequences. Mob. DNA 8, 5 (2017)

    Article  Google Scholar 

  29. Zeng, F.-C., Zhao, Y.-J., Zhang, Q.-J., Gao, L.-Z.: LTRtype, an efficient tool to characterize structurally complex LTR retrotransposons and nested insertions on genomes. Front. Plant Sci. 8, 1–9 (2017)

    Google Scholar 

  30. Hoede, C., Arnoux, S., Moisset, M., Chaumier, T., Inizan, O., Jamilloux, V., Quesneville, H.: PASTEC: an automatic transposable element classification tool. PLoS One 9, 1–6 (2014)

    Article  Google Scholar 

  31. Steinbiss, S., Kastens, S., Kurtz, S.: LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons. Mob. DNA. 3, 18 (2012)

    Article  Google Scholar 

  32. Du, J., Tian, Z., Hans, C.S., Laten, H.M., Cannon, S.B., Jackson, S.A., Shoemaker, R.C., Ma, J.: Evolutionary conservation, diversity and specificity of LTR-retrotransposons in flowering plants: insights from genome-wide analysis and multi-specific comparison. Plant J. 63, 584–598 (2010)

    Article  Google Scholar 

  33. Vitte, C., Bennetzen, J.L.: Analysis of retrotransposon structural diversity uncovers properties and propensities in angiosperm genome evolution. Proc. Natl. Acad. Sci. 103, 17638–17643 (2006)

    Article  Google Scholar 

  34. Dupeyron, M., de Souza, R.F., Hamon, P., de Kochko, A., Crouzillat, D., Couturon, E., Domingues, D.S., Guyot, R.: Distribution of Divo in Coffea genomes, a poorly described family of angiosperm LTR-Retrotransposons. Mol. Genet. Genomics 292, 741–754 (2017)

    Article  Google Scholar 

  35. Zhang, Q.-J., Gao, L.-Z.: Rapid and recent evolution of LTR retrotransposons drives rice genome evolution during the speciation of AA-genome Oryza species. G3 Genes Genomes Genet. 7, 1875–1885 (2017)

    Google Scholar 

  36. Llorens, C., Muñoz-Pomer, A., Bernad, L., Botella, H., Moya, A.: Network dynamics of eukaryotic LTR retroelements beyond phylogenetic trees. Biol. Direct. 4, 41 (2009)

    Article  Google Scholar 

  37. Garavito, A., Montagnon, C., Guyot, R., Bertrand, B.: Identification by the DArTseq method of the genetic origin of the Coffea canephora cultivated in Vietnam and Mexico. BMC Plant Biol. 16, 242 (2016)

    Article  Google Scholar 

  38. Carneiro, F.A., Rego, E., Aquino, S.O., Costa, T.S., Lima, E.A., Rocha, O.C., Rodrigues, G.C., Carvalho, M.A.F., Veiga, A.D., Guerra, A.F., et al.: Genome wide association study for drought tolerance and other agronomic traits of a# Coffea canephora# population (2015)

    Google Scholar 

  39. Babova, O., Occhipinti, A., Maffei, M.E.: Chemical partitioning and antioxidant capacity of green coffee (Coffea arabica and Coffea canephora) of different geographical origin. Phytochemistry 123, 33–39 (2016)

    Article  Google Scholar 

  40. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Mag. 17, 37–54 (1996)

    Google Scholar 

  41. Denoeud, F., Carretero-Paulet, L., Dereeper, A., Droc, G., Guyot, R., Pietrella, M., Zheng, C., Alberti, A., Anthony, F., Aprea, G., et al.: The coffee genome provides insight into the convergent evolution of caffeine biosynthesis. Science 345(6201), 1181–1184 (2014)

    Article  Google Scholar 

  42. Rice, P., Longden, I., Bleasby, A.: EMBOSS: the European molecular biology open software suite. Trends Genet. 16, 276–277 (2000)

    Article  Google Scholar 

  43. Jurka, J., Klonowski, P., Dagman, V., Pelton, P.: CENSOR—a program for identification and elimination of repetitive elements from DNA sequences. Comput. Chem. 20, 119–121 (1996)

    Article  Google Scholar 

  44. Moine, J.M.: Metodologías para el descubrimiento de conocimiento en bases de datos: un estudio comparativo (2013)

    Google Scholar 

  45. Carreño, J.A.: Descubrimiento de conocimiento en los negocios (2008)

    Google Scholar 

  46. Newham, C., Rosenblatt, B.: Learning the Bash Shell: Unix Shell Programming. O’Reilly Media Inc., Sebastopol (2005)

    MATH  Google Scholar 

Download references

Acknowledgements

We thank the Centro de Bioinformática y Biología Computacional BIOS for using the supercomputer to process the dataset.

Author information

Authors and Affiliations

  1. FIET, Universidad del Cauca, Calle 5 Nº 4-70, Popayán, Colombia

    Jeferson Arango-López

  2. Facultad de Ingeniería, Universidad de Caldas, Calle 65 Nº 26-10, Manizales, Colombia

    Jeferson Arango-López

  3. Escuela de Administración y Mercadotecnia del Quindío (EAM), Av. Bolívar # 3-11, Armenia, Colombia

    Johnny A. Salazar

  4. Centro de Bioinformática y Biología Computacional (BIOS), Ecoparque los Yarumos, Manizales, Colombia

    Simon Orozco-Arias

  5. IRD, CIRAD, Univ. Montpellier, IPME, BP 64501, 34394, Montpellier Cedex 5, France

    Romain Guyot

  6. Departamento de lenguajes y sistemas informaticos, Universidad de Granada, Calle Periodista Daniel Saucedo Aranda, s/n, 18071, Granada, Spain

    Jeferson Arango-López

Authors
  1. Jeferson Arango-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Simon Orozco-Arias
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Johnny A. Salazar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Romain Guyot
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeferson Arango-López .

Editor information

Editors and Affiliations

  1. Universidad Autónoma de Occidente, Cali, Colombia

    Andrés Solano

  2. Universidad de San Buenaventura, Cali, Colombia

    Hugo Ordoñez

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Arango-López, J., Orozco-Arias, S., Salazar, J.A., Guyot, R. (2017). Application of Data Mining Algorithms to Classify Biological Data: The Coffea canephora Genome Case. In: Solano, A., Ordoñez, H. (eds) Advances in Computing. CCC 2017. Communications in Computer and Information Science, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-319-66562-7_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-66562-7_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66561-0

  • Online ISBN: 978-3-319-66562-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation