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Open Access Highly Accessed Research article

GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases

Sipko van Dam1, Rui Cordeiro1, Thomas Craig1, Jesse van Dam2, Shona H Wood1 and João Pedro de Magalhães1*

Author Affiliations

1 Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK

2 Laboratory of Systems and Synthetic Biology, Wageningen University, Wageningen, 6703 HB, Netherlands

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BMC Genomics 2012, 13:535  doi:10.1186/1471-2164-13-535

Published: 6 October 2012

Abstract

Background

Although many diseases have been well characterized at the molecular level, the underlying mechanisms are often unknown. Nearly half of all human genes remain poorly studied, yet these genes may contribute to a number of disease processes. Genes involved in common biological processes and diseases are often co-expressed. Using known disease-associated genes in a co-expression analysis may help identify and prioritize novel candidate genes for further study.

Results

We have created an online tool, called GeneFriends, which identifies co-expressed genes in over 1,000 mouse microarray datasets. GeneFriends can be used to assign putative functions to poorly studied genes. Using a seed list of disease-associated genes and a guilt-by-association method, GeneFriends allows users to quickly identify novel genes and transcription factors associated with a disease or process. We tested GeneFriends using seed lists for aging, cancer, and mitochondrial complex I disease. We identified several candidate genes that have previously been predicted as relevant targets. Some of the genes identified are already being tested in clinical trials, indicating the effectiveness of this approach. Co-expressed transcription factors were investigated, identifying C/ebp genes as candidate regulators of aging. Furthermore, several novel candidate genes, that may be suitable for experimental or clinical follow-up, were identified. Two of the novel candidates of unknown function that were co-expressed with cancer-associated genes were selected for experimental validation. Knock-down of their human homologs (C1ORF112 and C12ORF48) in HeLa cells slowed growth, indicating that these genes of unknown function, identified by GeneFriends, may be involved in cancer.

Conclusions

GeneFriends is a resource for biologists to identify and prioritize novel candidate genes involved in biological processes and complex diseases. It is an intuitive online resource that will help drive experimentation. GeneFriends is available online at: http://genefriends.org/ webcite.

Keywords:
Aging; Cancer; Functional genomics; Mitochondrial disease; Network biology