Creation and implications of a phenome-genome network

Abstract

Although gene and protein measurements are increasing in quantity and comprehensiveness, they do not characterize a sample's entire phenotype in an environmental or experimental context. Here we comprehensively consider associations between components of phenotype, genotype and environment to identify genes that may govern phenotype and responses to the environment. Context from the annotations of gene expression data sets in the Gene Expression Omnibus is represented using the Unified Medical Language System, a compendium of biomedical vocabularies with nearly 1-million concepts. After showing how data sets can be clustered by annotative concepts, we find a network of relations between phenotypic, disease, environmental and experimental contexts as well as genes with differential expression associated with these concepts. We identify novel genes related to concepts such as aging. Comprehensively identifying genes related to phenotype and environment is a step toward the Human Phenome Project5.

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Figure 1: The method of extracting and relating genome, phenome and envirome data from GEO data sets.
Figure 2: Hierarchical clustering of 448 GEO data sets by context, created by treating each data set as a vector representing the presence or absence of a mapping from that data set to each UMLS concept, then calculating binary distance between data sets and clustering using complete linkage.
Figure 3: Network of relations between 46 biomedical concepts extracted from the annotations of data sets in Gene Expression Omnibus and 444 genes with differential expression associated with the presence or absence of the concept.

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Acknowledgements

We thank Tarangini Deshpande for critical comments on and suggestions for the manuscript. The authors thank Partners Healthcare Research Computing for use of and assistance with the Linux High Performance Computing Cluster. The work was supported by grants from the Lucille Packard Foundation for Children's Health, National Institutes of Health National Center for Biomedical Computing (U54 LM008748), the National Library of Medicine (K22 LM008261), National Institute of Diabetes and Digestive and Kidney Diseases (K12 DK63696, R01 DK62948 and R01 DK060837), the Harvard-MIT Division of Health Sciences and Technology and the Lawson Wilkins Pediatric Endocrine Society.

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Correspondence to Atul J Butte.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Example relations between genes and phenotypes and environment. (PDF 406 kb)

Supplementary Fig. 2

An illustrative subset of concepts and relations from UMLS. (PDF 142 kb)

Supplementary Table 1

Number of concepts mapped to each of the seven GEO free-text annotations. (PDF 30 kb)

Supplementary Note (PDF 49 kb)

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Butte, A., Kohane, I. Creation and implications of a phenome-genome network. Nat Biotechnol 24, 55–62 (2006). https://doi.org/10.1038/nbt1150

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