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Genome Annotation and Assembly

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Related Experiment Video

Updated: Nov 21, 2025

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

Revising transcriptome assemblies with phylogenetic information.

August Guang^1,2, Mark Howison³, Felipe Zapata⁴

¹Center for Computational Biology of Human Disease, Brown University, Providence, RI, United States of America.

|January 12, 2021

Summary

This summary is machine-generated.

Transcriptome assembly errors can misidentify gene transcripts. The treeinform method uses phylogenetic analysis to correct these errors, improving gene assembly accuracy within species.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Transcriptome assembly is crucial for understanding gene expression.
A common error involves mistaking transcripts of the same gene for those of related genes.
This error is challenging to detect during the assembly process.

Purpose of the Study:

To introduce treeinform, a novel method for refining transcriptome assemblies.
To address the specific error of misidentifying homologous transcripts as separate genes.
To improve the accuracy of gene transcript identification in transcriptome assemblies.

Main Methods:

Utilizing phylogenetic analysis across species to diagnose assembly errors.
Identifying clades of tips from the same species with short branch lengths as indicative of errors.
Developing the treeinform method to reassign incorrectly identified transcripts.

Main Results:

treeinform successfully identifies and corrects errors where single gene transcripts are erroneously split into multiple genes.
The method leverages phylogenetic information to refine within-species transcriptome assemblies.
Phylogenetic gene trees reveal errors as clades with short branch lengths from the same species.

Conclusions:

treeinform offers a robust solution for a common transcriptome assembly error.
The method enhances the accuracy of gene transcript assignment.
The phylogenetic approach is broadly applicable to other bioinformatics contexts.