Database Commons

a catalog of worldwide biological databases

Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.

Co-expression networks have proven effective at assigning putative functions to genes based on the functional annotation of their co-expressed partners, in candidate gene prioritization studies and in improving our understanding of regulatory networks. The growing number of genome resequencing efforts and genome-wide association studies often identify loci containing novel genes and there is a need to infer their functions and interaction partners. To facilitate this we have expanded GeneFriends, an online database that allows users to identify co-expressed genes with one or more user-defined genes. This expansion entails an RNA-seq-based co-expression map that includes genes and transcripts that are not present in the microarray-based co-expression maps, including over 10,000 non-coding RNAs. The results users obtain from GeneFriends include a co-expression network as well as a summary of the functional enrichment among the co-expressed genes. Novel insights can be gathered from this database for different splice variants and ncRNAs, such as microRNAs and lincRNAs. Furthermore, our updated tool allows candidate transcripts to be linked to diseases and processes using a guilt-by-association approach. GeneFriends is freely available from http://www.GeneFriends.org and can be used to quickly identify and rank candidate targets relevant to the process or disease under study. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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. 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. 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/.