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Updated: Jan 5, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

TreeExp2: An Integrated Framework for Phylogenetic Transcriptome Analysis.

Jingwen Yang^1,2, Hang Ruan³, Wenjie Xu¹

¹MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China.

Genome Biology and Evolution

|October 15, 2019

Summary

This summary is machine-generated.

Researchers developed TreeExp2, an R-package for analyzing RNA-sequencing (RNA-seq) data to study transcriptome evolution. This tool enhances the exploration of gene expression conservation and evolutionary selection across species.

Keywords:

R-package high-throughput analysis phylogenomics transcriptome evolution

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Area of Science:

Evolutionary biology
Genomics
Bioinformatics

Background:

Next-generation sequencing technologies like RNA-seq have produced vast amounts of comparative transcriptome data.
Understanding transcriptional regulatory systems requires robust analytical tools for phylogenetic transcriptome analysis.
Existing statistical methods and computational tools for evolutionary transcriptome analysis are underdeveloped.

Discussion:

TreeExp2 is an R-package specifically designed for RNA-sequencing data analysis.
It incorporates advanced methods for evolutionary transcriptome analysis, including ancestral transcriptome inference and expression conservation estimation.
The software provides a statistically sound framework for phylogenetic transcriptome analysis.

Key Insights:

TreeExp2 enables the estimation of expression conservation strength and introduces a new expression distance metric.
It facilitates the relative expression rate test for evolutionary analysis.
The package offers an integrated approach to exploring transcriptome evolution and selection.

Outlook:

TreeExp2 significantly enhances analytical capabilities for studying transcriptome evolution.
It provides a foundation for future research into the evolutionary dynamics of gene expression.
The software aims to advance our understanding of selection pressures at the transcriptome level.