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Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The prop...

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Detalles Bibliográficos
Autores principales: Das, Shibsankar, Chottopadhyay, Brajadulal, Sahoo, Satyabrata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389947/
https://www.ncbi.nlm.nih.gov/pubmed/28416948
http://dx.doi.org/10.5808/GI.2017.15.1.38
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author Das, Shibsankar
Chottopadhyay, Brajadulal
Sahoo, Satyabrata
author_facet Das, Shibsankar
Chottopadhyay, Brajadulal
Sahoo, Satyabrata
author_sort Das, Shibsankar
collection PubMed
description Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.
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spelling pubmed-53899472017-04-17 Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes Das, Shibsankar Chottopadhyay, Brajadulal Sahoo, Satyabrata Genomics Inform Original Article Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes. Korea Genome Organization 2017-03 2017-03-29 /pmc/articles/PMC5389947/ /pubmed/28416948 http://dx.doi.org/10.5808/GI.2017.15.1.38 Text en Copyright © 2017 by the Korea Genome Organization http://creativecommons.org/licenses/by-nc/4.0/ It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/).
spellingShingle Original Article
Das, Shibsankar
Chottopadhyay, Brajadulal
Sahoo, Satyabrata
Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title_full Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title_fullStr Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title_full_unstemmed Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title_short Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes
title_sort comparative analysis of predicted gene expression among crenarchaeal genomes
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389947/
https://www.ncbi.nlm.nih.gov/pubmed/28416948
http://dx.doi.org/10.5808/GI.2017.15.1.38
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