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Updated: Jun 6, 2026
A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
POLYAR, a new computer program for prediction of poly(A) sites in human sequences
Malik Nadeem Akhtar1, Syed Abbas Bukhari, Zeeshan Fazal
1Department of Biosciences, COMSATS Institute of Information Technology, Islamabad, Pakistan.
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.
Insights
A new classification and computer program, POLYAR, improve the prediction of strong polyadenylation sites in human pre-mRNA. While POLYAR shows high accuracy for strong sites, further research is needed for weak and poly(A) signal-less sites.
Area of Science:
- Molecular Biology
- Bioinformatics
Background:
- Messenger RNA (mRNA) polyadenylation is a critical step in eukaryotic gene expression.
- Accurate prediction of polyadenylation sites is essential for defining gene boundaries and understanding gene regulation.
Purpose of the Study:
- To classify human polyadenylation sites into distinct categories.
- To develop a novel computational tool, POLYAR, for predicting polyadenylation sites.
Main Methods:
- Classification of 28,761 human mapped poly(A) sites into PAS-strong, PAS-weak, and PAS-less groups.
- Development and comparative analysis of the POLYAR program against existing tools like polya_svm.
Main Results:
- POLYAR demonstrated significantly higher prediction sensitivity (80.8%) and specificity (66.4%) for PAS-strong poly(A) sites compared to polya_svm.
- Both POLYAR and polya_svm exhibited low accuracy for predicting PAS-weak and PAS-less poly(A) sites, indicating incomplete understanding of their regulatory factors.
Conclusions:
- A new classification and the POLYAR program enhance the prediction of strong polyadenylation sites.
- Further investigation is required to elucidate the factors governing PAS-weak and PAS-less polyadenylation sites.
- The POLYAR program is available for download.
