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Updated: Jul 5, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Phylogenomic inference of protein molecular function.

Nandini Krishnamurthy¹, Kimmen Sjölander

¹University of California, Berkeley, California, USA.

Current Protocols in Bioinformatics

|April 23, 2008

Summary

Accurate protein function prediction is crucial with vast sequence data. Phylogenomic methods improve accuracy by analyzing evolutionary relationships, reducing errors in homology-based function prediction.

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Accurate protein function prediction is vital for prioritizing experimental research, especially with the rapid growth of sequence data.
Homology-based methods are efficient for high-throughput analysis but can lead to annotation errors due to evolutionary processes like gene duplication and domain shuffling.
Standard sequence comparison may fail to distinguish between homologs with divergent molecular functions.

Purpose of the Study:

To describe phylogenomic approaches for reducing error rates in protein function prediction.
To provide a framework for inferring protein molecular function using evolutionary relationships.

Main Methods:

Identify clusters of homologous proteins.
Construct multiple sequence alignments and phylogenetic trees for these homologs.

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Last Updated: Jul 5, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Published on: August 14, 2018

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Overlay phylogenetic trees with experimental data to trace biochemical function changes across evolution.

Main Results:

Phylogenomic approaches can effectively reduce errors in protein function prediction compared to standard sequence-comparison methods.
Tracing biochemical function changes along evolutionary trees provides a more accurate functional annotation.
The described methods enable a more reliable prioritization of experimental investigations.

Conclusions:

Phylogenomic inference offers a robust strategy to enhance the accuracy of protein function prediction.
This approach mitigates the risks of misannotation inherent in simpler homology-based methods.
Integrating evolutionary insights is key to advancing high-throughput functional genomics.