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Identification of a Putative Ganoderic Acid Pathway Enzyme in a Ganoderma Australe Transcriptome by Means of a Hidden Markov Model

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9th International Conference on Practical Applications of Computational Biology and Bioinformatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 375))

Abstract

Ganoderma australe is a fungus widely used as a traditional medicine mainly in Eastern countries, but not studied in silico at the genomic level. This species is probably related to other well characterized fungus with similar properties, which may facilitate gene finding through comparative molecular analysis using appropriated bioinformatics tools. This paper aims to present a preliminary analysis of a G. australe transcriptome through some computational biology techniques implementing Hidden Markov Models (HMM) in order to predict a key putative enzyme (lanosterol synthase, EC 5.4.99.7) involved in the metabolic pathway of triterpenoids of therapeutic interest. The findings suggest that the HMM approach results more efficient than traditional comparisons by homology based on methods of multiple sequences alignment. Here we report the first evidence of a putative lanosterol synthase protein being expressed in cell cultures of G. australe.

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Notes

  1. 1.

    Castillo, L.F; López-Gartner, G.; Isaza, G.; Sánchez, M.; Arango, J.; Agudelo-Valencia, D.; Castaño, S. GITIRBio: A Semantic and Distributed Service Oriented-Architecture for Bioinformatics Pipeline. Sent to: Journal of Integrative Bioinformatics (JIB). In Review.

  2. 2.

    HMMER web server: interactive sequence similarity searching R.D. Finn, J. Clements, S.R. Eddy Nucleic Acids Research (2011).

  3. 3.

    http://transdecoder.sourceforge.net/.

  4. 4.

    ftp://ftp.sanger.ac.uk/pub/databases/Pfam/current_release.

  5. 5.

    ftp://ftp.jcvi.org/pub/data/TIGRFAMs/.

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Acknowledgments

This work is supported by the Call for Special Project funding for Research and Innovation at the University of Caldas 2013.

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Authors and Affiliations

  1. Biology Sciences Department, GITIR Research Group, Universidad de Caldas, Street 65 # 26–10, Manizales, Colombia

    Germán López-Gartner, Daniel Agudelo-Valencia & Mariana Sánchez

  2. Systems and Informatics Department, GITIR Research Group, Universidad de Caldas, Street 65 # 26–10, Manizales, Colombia

    Sergio Castaño, Gustavo A. Isaza, Luis F. Castillo & Jeferson Arango

Authors
  1. Germán López-Gartner
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  2. Daniel Agudelo-Valencia
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  3. Sergio Castaño
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  4. Gustavo A. Isaza
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  5. Luis F. Castillo
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  6. Mariana Sánchez
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  7. Jeferson Arango
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Corresponding author

Correspondence to Germán López-Gartner .

Editor information

Editors and Affiliations

  1. Fellowship for the Interpretation of Genomes, Burr Ridge, Illinois, USA

    Ross Overbeek

  2. Centre of Biological Engineering, Department of Informatics, University of Minho, Braga, Portugal

    Miguel P. Rocha

  3. Department of Informatics, University of Vigo, ESEI: Escuela Superior de Ingeniería Informática, Ourense, Spain

    Florentino Fdez-Riverola

  4. Departamento de Informática y Automática, University of Salamanca, Facultad de Ciencias, Salamanca, Spain

    Juan F. De Paz

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López-Gartner, G. et al. (2015). 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., Fdez-Riverola, F., De Paz, J. (eds) 9th International Conference on Practical Applications of Computational Biology and Bioinformatics. Advances in Intelligent Systems and Computing, vol 375. Springer, Cham. https://doi.org/10.1007/978-3-319-19776-0_12

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  • DOI: https://doi.org/10.1007/978-3-319-19776-0_12

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