Lab Anim Res.
2019 Dec;35(4):165-171. 10.1186/s42826-019-0023-z.
TarGo: network based target gene selection system for human disease related mouse models
- Affiliations
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- 1National Cancer Center, 323 Ilsan-ro, Goyang-si, Kyeonggi-do 10408, Republic of Korea. sooycho@ncc.re.kr
- 2MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK.
- 3Laboratory of Developmental Biology and Genomics, Research Institute for Veterinary Science, and BK21 Plus Program for Creative Veterinary Science, College of Veterinary Medicine, Seoul National University, Seoul 08826, Republic of Korea. snumouse@snu.ac.kr
- 4Korea Mouse Phenotyping Center (KMPC), Seoul National University, Seoul 08826, Republic of Korea.
- 5Interdisciplinary Program for Bioinformatics, Program for Cancer Biology and BIO-MAX institute, Seoul National University, Seoul 08826, Republic of Korea.
- KMID: 2470013
- DOI: http://doi.org/10.1186/s42826-019-0023-z
Abstract
- Genetically engineered mouse models are used in high-throughput phenotyping screens to understand genotype-phenotype associations and their relevance to human diseases. However, not all mutant mouse lines with detectable phenotypes are associated with human diseases. Here, we propose the "Target gene selection system for Genetically engineered mouse models" (TarGo). Using a combination of human disease descriptions, network topology, and genotype-phenotype correlations, novel genes that are potentially related to human diseases are suggested. We constructed a gene interaction network using protein-protein interactions, molecular pathways, and co-expression data. Several repositories for human disease signatures were used to obtain information on human disease-related genes. We calculated disease- or phenotype-specific gene ranks using network topology and disease signatures. In conclusion, TarGo provides many novel features for gene function prediction.
