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A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

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Published on: December 2, 2009

peaks2utr: a robust Python tool for the annotation of 3' UTRs.

William Haese-Hill¹, Kathryn Crouch¹, Thomas D Otto¹

¹School of Infection & Immunity, MVLS, University of Glasgow, Glasgow G12 8TA, United Kingdom.

Bioinformatics (Oxford, England)

|March 3, 2023

Summary

Accurately annotating untranslated regions (UTRs) is vital for gene expression analysis. We developed peaks2utr, a Python tool leveraging single-cell data to improve 3' UTR annotation for nonmodel organisms.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Accurate gene annotation is essential for understanding biological processes.
Untranslated regions (UTRs) are critical for gene expression regulation but often poorly annotated.
Nonmodel organisms present unique challenges for genomic annotation.

Purpose of the Study:

To develop an accessible computational tool for annotating 3' UTRs.
To address the overlooked challenge of UTR annotation in standard pipelines.
To leverage single-cell RNA sequencing data for improved gene annotation.

Main Methods:

Developed peaks2utr, a Python command-line tool.
Utilized UTR enrichment patterns from single-cell technologies (e.g., 10× Chromium).
Integrated with existing canonical gene annotations.

Main Results:

peaks2utr enables accurate 3' UTR annotation.
The tool is designed for ease of use in research settings.
Demonstrates the utility of single-cell data for refining gene models.

Conclusions:

peaks2utr provides a solution for UTR annotation in nonmodel organisms.
Improves the accuracy of transcriptomic analysis by enhancing gene annotation.
Facilitates downstream analyses reliant on precise gene expression quantification.