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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Adapting simultaneous analysis phylogenomic techniques to study complex disease gene relationships.

Joseph D Romano¹, William G Tharp², Indra Neil Sarkar³

¹Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT 05405, USA.

Journal of Biomedical Informatics

|January 17, 2015

Summary

This study introduces ASAP2, a novel phylogenomic method to build gene networks for complex diseases. It reveals evolutionary relationships among Alzheimer Disease genes, offering new insights for network medicine.

Keywords:

Alzheimer Disease Bioinformatics Comparative genomics Phylogenetics Simultaneous analysis

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Area of Science:

Genomics
Bioinformatics
Evolutionary Biology

Background:

Complex diseases involve intricate genetic and environmental interactions, posing challenges for biomedical research.
Network medicine offers a holistic approach to understanding these multifactorial conditions.
Phylogenomic techniques can provide evolutionary insights into gene networks.

Purpose of the Study:

To develop an automated method leveraging genomic data and phylogenetics to construct gene networks.
To demonstrate the utility of this approach through a case study of Alzheimer Disease genes.
To enhance network medicine strategies by incorporating evolutionary perspectives.

Main Methods:

An automated pipeline (ASAP2) using Ruby scripts was developed.
It employs PSI-BLAST and NCBI BLAST+ for orthologue identification.
Maximum parsimony phylogenetic trees are constructed, and various phylogenetic metrics are calculated to assess evolutionary conservation and topological similarity.

Main Results:

ASAP2 successfully generated a gene network based on evolutionary similarity for nine Alzheimer Disease-associated genes.
Phylogenetic metrics provided an empirical assessment of evolutionary conservation within the network.
The method identified potential co-evolutionary clusters warranting further investigation.

Conclusions:

Phylogenomic approaches, like ASAP2, can uncover gene relationships for complex diseases that single-gene methods might miss.
This study provides an initial evolutionary history of an Alzheimer Disease gene network.
The findings support the integration of evolutionary insights into network medicine frameworks.