Cargando…

Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries

BACKGROUND: Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful...

Descripción completa

Detalles Bibliográficos
Autores principales: Serb, Jeanne M., Orr, Megan C., West Greenlee, M. Heather
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2932711/
https://www.ncbi.nlm.nih.gov/pubmed/20824082
http://dx.doi.org/10.1371/journal.pone.0012525
_version_ 1782186092380815360
author Serb, Jeanne M.
Orr, Megan C.
West Greenlee, M. Heather
author_facet Serb, Jeanne M.
Orr, Megan C.
West Greenlee, M. Heather
author_sort Serb, Jeanne M.
collection PubMed
description BACKGROUND: Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seed-network of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development. METHODOLOGY/PRINCIPAL FINDINGS: Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina. CONCLUSIONS/SIGNIFICANCE: We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses.
format Text
id pubmed-2932711
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-29327112010-09-07 Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries Serb, Jeanne M. Orr, Megan C. West Greenlee, M. Heather PLoS One Research Article BACKGROUND: Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seed-network of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development. METHODOLOGY/PRINCIPAL FINDINGS: Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina. CONCLUSIONS/SIGNIFICANCE: We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses. Public Library of Science 2010-09-02 /pmc/articles/PMC2932711/ /pubmed/20824082 http://dx.doi.org/10.1371/journal.pone.0012525 Text en Serb et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Serb, Jeanne M.
Orr, Megan C.
West Greenlee, M. Heather
Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title_full Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title_fullStr Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title_full_unstemmed Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title_short Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
title_sort using evolutionary conserved modules in gene networks as a strategy to leverage high throughput gene expression queries
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2932711/
https://www.ncbi.nlm.nih.gov/pubmed/20824082
http://dx.doi.org/10.1371/journal.pone.0012525
work_keys_str_mv AT serbjeannem usingevolutionaryconservedmodulesingenenetworksasastrategytoleveragehighthroughputgeneexpressionqueries
AT orrmeganc usingevolutionaryconservedmodulesingenenetworksasastrategytoleveragehighthroughputgeneexpressionqueries
AT westgreenleemheather usingevolutionaryconservedmodulesingenenetworksasastrategytoleveragehighthroughputgeneexpressionqueries