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ChemGenome2.1: An Ab Initio Gene Prediction Software

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Gene Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1962))

Abstract

Gene prediction, also known as gene identification, gene finding, gene recognition, or gene discovery, is among one of the important problems of molecular biology and is receiving increasing attention due to the advent of large-scale genome sequencing projects. We designed an ab initio model (called ChemGenome) for gene prediction in prokaryotic genomes based on physicochemical characteristics of codons. In this chapter, we present the methodology of the latest version of this model ChemGenome2.1 (CG2.1). The first module of the protocol builds a three-dimensional vector from three calculated quantities for each codon—the double-helical trinucleotide base pairing energy, the base pair stacking energy, and an index of the propensity of a codon for protein-nucleic acid interactions. As this three-dimensional vector moves along any genome, the net orientation of the resultant vector should differ significantly for gene and non-genic regions to make a distinction feasible. The predicted putative protein-coding genes from above parameters are passed through a second module of the protocol which reduces the number of false positives by utilizing a filter based on stereochemical properties of protein sequences. The chemical properties of amino acid side chains taken into consideration are the presence of sp3 hybridized γ carbon atom, hydrogen bond donor ability, short/absence of δ carbon and linearity of the side chains/non-occurrence of bi-dentate forks with terminal hydrogen atoms in the side chain. The final prediction of the potential protein-coding genes is based on the frequency of occurrence of amino acids in the predicted protein sequences and their deviation from the frequency values of Swissprot protein sequences, both at monomer and tripeptide levels. The final screening is based on Z-score. Though CG2.1 is a gene finding tool for prokaryotes, considering the underlying similarity in the chemical and physical properties of DNA among prokaryotes and eukaryotes, we attempted to evaluate its applicability for gene finding in the lower eukaryotes. The results give a hope that the concept of gene finding based on physicochemical model of codons is a viable idea for eukaryotes as well, though, undoubtedly, improvements are needed.

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Author information

Authors and Affiliations

  1. Supercomputing Facility for Bioinformatics and Computational Biology, Indian Institute of Technology Delhi, New Delhi, India

    Akhilesh Mishra, Priyanka Siwach, Poonam Singhal & B. Jayaram

  2. Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, New Delhi, India

    Akhilesh Mishra & B. Jayaram

  3. Department of Biotechnology, Chaudhary Devi Lal University, Sirsa, Haryana, India

    Priyanka Siwach

  4. Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India

    B. Jayaram

Authors
  1. Akhilesh Mishra
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  2. Priyanka Siwach
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  3. Poonam Singhal
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  4. B. Jayaram
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Corresponding author

Correspondence to B. Jayaram .

Editor information

Editors and Affiliations

  1. Group Systems Biology of Motor Proteins, Department NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Goettingen, Germany

    Martin Kollmar

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Mishra, A., Siwach, P., Singhal, P., Jayaram, B. (2019). ChemGenome2.1: An Ab Initio Gene Prediction Software. In: Kollmar, M. (eds) Gene Prediction. Methods in Molecular Biology, vol 1962. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9173-0_7

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  • DOI: https://doi.org/10.1007/978-1-4939-9173-0_7

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9172-3

  • Online ISBN: 978-1-4939-9173-0

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