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POLYAR, a new computer program for prediction of poly(A) sites in human sequences

BACKGROUND: mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. RESULTS: 28761 human mapped poly(A) s...

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Autores principales: Akhtar, Malik Nadeem, Bukhari, Syed Abbas, Fazal, Zeeshan, Qamar, Raheel, Shahmuradov, Ilham A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3053588/
https://www.ncbi.nlm.nih.gov/pubmed/21092114
http://dx.doi.org/10.1186/1471-2164-11-646
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author Akhtar, Malik Nadeem
Bukhari, Syed Abbas
Fazal, Zeeshan
Qamar, Raheel
Shahmuradov, Ilham A
author_facet Akhtar, Malik Nadeem
Bukhari, Syed Abbas
Fazal, Zeeshan
Qamar, Raheel
Shahmuradov, Ilham A
author_sort Akhtar, Malik Nadeem
collection PubMed
description BACKGROUND: mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. RESULTS: 28761 human mapped poly(A) sites have been classified into three classes containing different known forms of polyadenylation signal (PAS) or none of them (PAS-strong, PAS-weak and PAS-less, respectively) and a new computer program POLYAR for the prediction of poly(A) sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A) sites) while searching for PAS-strong poly(A) sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7%) and specificity (66.4% versus 51.7%) However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A) sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A) sites is not sufficient to identify such polyadenylation regions. CONCLUSIONS: We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A) sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A) sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A) sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A) sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm.
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spelling pubmed-30535882011-03-15 POLYAR, a new computer program for prediction of poly(A) sites in human sequences Akhtar, Malik Nadeem Bukhari, Syed Abbas Fazal, Zeeshan Qamar, Raheel Shahmuradov, Ilham A BMC Genomics Methodology Article BACKGROUND: mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. RESULTS: 28761 human mapped poly(A) sites have been classified into three classes containing different known forms of polyadenylation signal (PAS) or none of them (PAS-strong, PAS-weak and PAS-less, respectively) and a new computer program POLYAR for the prediction of poly(A) sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A) sites) while searching for PAS-strong poly(A) sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7%) and specificity (66.4% versus 51.7%) However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A) sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A) sites is not sufficient to identify such polyadenylation regions. CONCLUSIONS: We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A) sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A) sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A) sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A) sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm. BioMed Central 2010-11-19 /pmc/articles/PMC3053588/ /pubmed/21092114 http://dx.doi.org/10.1186/1471-2164-11-646 Text en Copyright ©2010 Akhtar et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Akhtar, Malik Nadeem
Bukhari, Syed Abbas
Fazal, Zeeshan
Qamar, Raheel
Shahmuradov, Ilham A
POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title_full POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title_fullStr POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title_full_unstemmed POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title_short POLYAR, a new computer program for prediction of poly(A) sites in human sequences
title_sort polyar, a new computer program for prediction of poly(a) sites in human sequences
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3053588/
https://www.ncbi.nlm.nih.gov/pubmed/21092114
http://dx.doi.org/10.1186/1471-2164-11-646
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