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Updated: Jul 7, 2026

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Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
Published on: September 3, 2009
UTR reconstruction and analysis using genomically aligned EST sequences
1Institute for Biomedical Computing, Washington University, St. Louis, MO 63110, USA. zkan@ibc.wustl.edu
Summary
A new computational tool, UTR-extender, accurately reconstructs messenger RNA untranslated regions (UTRs) from EST data. This tool also identifies alternative polyadenylation in human genes, revealing links between 3' UTR length and gene expression.
Area of Science:
- Computational Biology
- Genomics
- Molecular Biology
Background:
- Untranslated regions (UTRs) are crucial for posttranscriptional mRNA regulation.
- Vast amounts of expressed sequence tag (EST) data offer potential for UTR discovery.
- Accurate UTR identification is essential for understanding gene regulation.
Purpose of the Study:
- To develop computational tools for inferring and extending UTR sequences from EST data.
- To precisely map polyadenylation sites in human genomic sequences.
- To investigate the relationship between UTR characteristics and gene expression levels.
Main Methods:
- Development of UTR-extender for reconstructing UTRs from aligned ESTs.
- Implementation of polyadenylation site scan (PASS) for mapping polyadenylation sites.
- Analysis of splicing frequencies and conservation levels to validate predicted UTR extensions.
- Utilizing EST redundancy to estimate gene expression levels.
Main Results:
- UTR-extender accurately reconstructed 72% of 3' UTRs and 15% of 5' UTRs.
- The tool predicted extensions for 11% of 5' UTRs and 28% of 3' UTRs.
- PASS analysis indicated that 40-50% of human genes exhibit alternative polyadenylation.
- A significant correlation was found between shorter 3' UTRs and higher gene expression.
Conclusions:
- UTR-extender is an effective tool for mining UTR information from EST collections.
- Alternative polyadenylation is a widespread phenomenon in the human genome.
- 3' UTR length is a potential regulatory factor influencing gene expression levels.
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