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Updated: Jul 31, 2025

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

Transcript Assembly and Annotations: Bias and Adjustment.

Qimin Zhang¹, Mingfu Shao^1,2

¹Department of Computer Science and Engineering, School of Electrical Engineering and Computer Science, The Pennsylvania State University.

Biorxiv : the Preprint Server for Biology

|May 3, 2023

Summary

This summary is machine-generated.

Transcript annotations significantly impact gene expression analysis and transcript assembly. Our study reveals that differing annotations, particularly at the intron level, cause biased results, and we offer a tool to mitigate this.

Keywords:

intron retention transcript annotation transcript assembly

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Area of Science:

Transcriptomics
Bioinformatics
Computational Biology

Background:

Transcript annotations are crucial for gene expression analysis and transcript assembly.
Discrepancies between major annotation sources (RefSeq, Ensembl/GENCODE) impact results.
The influence of annotations on transcript assembly accuracy is not fully understood.

Approach:

Investigated the impact of different transcript annotations on transcript assembly.
Compared structural similarities across annotations, identifying intron-chain level differences.
Analyzed biotype biases in annotated and assembled transcripts, focusing on intron retention.

Key Points:

Conflicting conclusions arise when evaluating transcript assemblers with different annotations.
Intron retention bias in annotations and assembly explains contradictory findings.
A novel tool (irtool) is developed to generate assemblies without intron retentions.

Conclusions:

Annotation choice significantly affects transcript assembly outcomes.
Addressing intron retention bias is key to accurate transcript assembly.
Guidance is provided for selecting appropriate assembly tools based on annotation characteristics.