Information theoretic perspective on genome clustering
Shannon’s information theoretic perspective of communication helps one to understand the storage and processing of information in one-dimensional sequences. An information theoretic analysis of 937 available completely sequenced prokaryotic genomes and 238 eukaryotic chromosomes is presented. Inform...
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Veröffentlicht in: | Saudi journal of biological sciences 2021-03, Vol.28 (3), p.1867-1889 |
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Sprache: | eng |
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Zusammenfassung: | Shannon’s information theoretic perspective of communication helps one to understand the storage and processing of information in one-dimensional sequences. An information theoretic analysis of 937 available completely sequenced prokaryotic genomes and 238 eukaryotic chromosomes is presented. Information content (Id) values were used to cluster these chromosomes. Chargaff’s second parity rule i.e compositional self-complementarity, an empirical fact is observed in all the genomes, except for the proteobacteria Candidatus Hodgkinia cicadicola. High information content, arising out of biased base composition in all the 14 chromosomes of Plasmodium falciparum is found among two other genomes of prokaryotes viz. Buchnera aphidicola str. Cc (Cinara cedri) and Candidatus Carsonella ruddii PV. Despite size and compositional variations, both prokaryotic and eukaryotic genomes do not deviate significantly from an equiprobable and random situation. Eukaryotic chromosomes of an organism tend to have similar informational restraints as seen when a simple distance based method is used to cluster them. In eukaryotes, in certain cases, Id values are also similar for the two arms (p and q arm) of the chromosomes. The results of this current study confirm that the information content can provide insights into the clustering of genomes and the evolution of messaging strategies of the genomes. An efficient and robust Perl CGI standalone tool is created based on this information theory algorithm for the analysis of the whole genomes and is made available at https://github.com/AlagurajVeluchamy/InformationTheory. |
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ISSN: | 1319-562X 2213-7106 |
DOI: | 10.1016/j.sjbs.2020.12.039 |