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Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy

Transcription is an intricate mechanism and is orchestrated at the promoter region. The cognate motifs in the promoters are observed in only a subset of total genes across different domains of life. Hence, sequence-motif based promoter prediction may not be a holistic approach for whole genomes. Con...

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Autores principales: Yella, Venkata Rajesh, Kumar, Aditya, Bansal, Manju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5852095/
https://www.ncbi.nlm.nih.gov/pubmed/29540741
http://dx.doi.org/10.1038/s41598-018-22129-8
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author Yella, Venkata Rajesh
Kumar, Aditya
Bansal, Manju
author_facet Yella, Venkata Rajesh
Kumar, Aditya
Bansal, Manju
author_sort Yella, Venkata Rajesh
collection PubMed
description Transcription is an intricate mechanism and is orchestrated at the promoter region. The cognate motifs in the promoters are observed in only a subset of total genes across different domains of life. Hence, sequence-motif based promoter prediction may not be a holistic approach for whole genomes. Conversely, the DNA structural property, duplex stability is a characteristic of promoters and can be used to delineate them from other genomic sequences. In this study, we have used a DNA duplex stability based algorithm ‘PromPredict’ for promoter prediction in a broad range of eukaryotes, representing various species of yeast, worm, fly, fish, and mammal. Efficiency of the software has been tested in promoter regions of 48 eukaryotic systems. PromPredict achieves recall values, which range from 68 to 92% in various eukaryotes. PromPredict performs well in mammals, although their core promoter regions are GC rich. ‘PromPredict’ has also been tested for its ability to predict promoter regions for various transcript classes (coding and non-coding), TATA-containing and TATA-less promoters as well as on promoter sequences belonging to different gene expression variability categories. The results support the idea that differential DNA duplex stability is a potential predictor of promoter regions in various genomes.
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spelling pubmed-58520952018-03-22 Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy Yella, Venkata Rajesh Kumar, Aditya Bansal, Manju Sci Rep Article Transcription is an intricate mechanism and is orchestrated at the promoter region. The cognate motifs in the promoters are observed in only a subset of total genes across different domains of life. Hence, sequence-motif based promoter prediction may not be a holistic approach for whole genomes. Conversely, the DNA structural property, duplex stability is a characteristic of promoters and can be used to delineate them from other genomic sequences. In this study, we have used a DNA duplex stability based algorithm ‘PromPredict’ for promoter prediction in a broad range of eukaryotes, representing various species of yeast, worm, fly, fish, and mammal. Efficiency of the software has been tested in promoter regions of 48 eukaryotic systems. PromPredict achieves recall values, which range from 68 to 92% in various eukaryotes. PromPredict performs well in mammals, although their core promoter regions are GC rich. ‘PromPredict’ has also been tested for its ability to predict promoter regions for various transcript classes (coding and non-coding), TATA-containing and TATA-less promoters as well as on promoter sequences belonging to different gene expression variability categories. The results support the idea that differential DNA duplex stability is a potential predictor of promoter regions in various genomes. Nature Publishing Group UK 2018-03-14 /pmc/articles/PMC5852095/ /pubmed/29540741 http://dx.doi.org/10.1038/s41598-018-22129-8 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yella, Venkata Rajesh
Kumar, Aditya
Bansal, Manju
Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title_full Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title_fullStr Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title_full_unstemmed Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title_short Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy
title_sort identification of putative promoters in 48 eukaryotic genomes on the basis of dna free energy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5852095/
https://www.ncbi.nlm.nih.gov/pubmed/29540741
http://dx.doi.org/10.1038/s41598-018-22129-8
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