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  • Review Article
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Genotype–phenotype databases: challenges and solutions for the post-genomic era

Nature Reviews Genetics volume 10, pages 9–18 (2009)Cite this article

Key Points

  • Research data concerning the genetic basis of health and disease is accumulating rapidly, as modern, high-throughput experimental techniques deliver increasingly larger data sets.

  • Data integration efforts in the field face numerous challenges, including the increased data size and complexity, quality control, data sensitivity and personal privacy, data access and publication bias.

  • Traditional approaches of gathering data into centralized repositories and publishing results in static paper journals, which have proved successful in the past, will not be sufficient to address the emerging and future needs of the field.

  • The alternative of a partially centralized and partially federated model has been proposed to solve this problem. This will entail a distributed, decentralized network of interconnected information sources and analysis services, the first incarnations of which are now starting to appear. A central requirement of this model is the far greater use of standardization for data models and exchange formats, and in the deployment of existing and emerging software components and network protocols.

  • Community adoption of new database technologies, and the development of robust data standards, will be vital to achieving the global integration of G2P data in the future. This might also help to address other challenges, such as accrediting and rewarding data submitters and database managers, as we move towards the emergence of a universal G2P 'knowledge environment'.

Abstract

The flow of research data concerning the genetic basis of health and disease is rapidly increasing in speed and complexity. In response, many projects are seeking to ensure that there are appropriate informatics tools, systems and databases available to manage and exploit this flood of information. Previous solutions, such as central databases, journal-based publication and manually intensive data curation, are now being enhanced with new systems for federated databases, database publication, and more automated management of data flows and quality control. Along with emerging technologies that enhance connectivity and data retrieval, these advances should help to create a powerful knowledge environment for genotype–phenotype information.

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Figure 1: Extreme models for database integration.
Figure 2: Databases and database networks.
Figure 3: Success depends upon recognition and reward.

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Acknowledgements

The authors acknowledge the valuable ideas, advice and funding provided by the GEN2PHEN project as part of the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement number 200754, which enabled the preparation of this Review.

Author information

Authors and Affiliations

  1. Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK

    Gudmundur A. Thorisson & Anthony J. Brookes

  2. Institute for Molecular Medicine Finland, University of Helsinki, Haartmaninkatu 8, Helsinki, FIN-00290, Finland

    Juha Muilu

Authors
  1. Gudmundur A. Thorisson
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  2. Juha Muilu
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  3. Anthony J. Brookes
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Corresponding author

Correspondence to Anthony J. Brookes.

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Related links

Related links

FURTHER INFORMATION

AlzGene

Biobanking and Biomolecular Resources Research Infrastructure (BBMRI)

Cancer Biomedical Informatics Grid (caBIG)

Coordination and Sustainability of International Mouse Informatics Resources (CASIMIR)

dbGaP

Enabling Grids for E-sciencE (EGEE)

ENCODEdb

EuroGenetest

European Advanced Translational Research Infrastructure in Medicine (EATRIS)

European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI)

European Clinical Research Infrastructures Network (ECRIN)

European Genotype Archive (EGA)

European Life Sciences Infrastructure for Biological Information (ELIXIR)

European Model for Bioinformatics Research and Community Education (EMBRACE)

European Network of Genomic and Genetic Epidemiology (ENGAGE)

European Strategy Forum on Research Infrastructures (ESFRI)

FINDbase

Framingham Heart Study

GEN2PHEN project

Generic Model Organism Database (GMOD)

Genes, Environment and Health Initiative

Genetic Association Database (GAD)

GenomEUtwin

GWAS Database, Japan

Health Level Seven (HL7)

HGVbaseG2P

Human Gene Mutation Database (HGMD)

Human Genome Epidemiology Network (HuGENet)

Human Genome Variation Society

Human Genomics and Proteomics journal

Human Variation Project (HVP)

International Nucleotide Sequence Database Collaboration (INSDC)

Minimum Information for Biological and Biomedical Investigations (MIBBI)

Minimum Information for QTLs and Association Studies specification (MIQAS)

Obiba

Online Mendelian Inheritance in Man (OMIM)

Open Biomedical Ontologies (OBO)

OpenEHR

PDGene

Persistent Uniform Resource Locator (PURL)

Pharmacogenetics and Pharmacogenoics Knowledge Base (PharmGKB)

Phenotype and Genotype Experiment Object Model (PaGE-OM)

PhenX

Public Population Project in Genomics (P3G)

Public Population Project in Genomics observatory

Resource Description Framework (RDF)

Service-oriented architecture (SOA)

SZGene

Type 1 Diabetes Genetics Consortium

UK Biobank

Glossary

Screen-scraping

The automated process of extracting data from web pages intended for human viewing.

Genotype-to-phenotype

(G2P). The relationship between genetic variation in an organism and how this affects its observable characteristics.

Genome-wide association study

(GWA study). Examination of DNA variation (typically SNPs) across the whole genome in a large number of individuals who have been matched for population ancestry and assessed for a disease or trait of interest. Correlations between variants and the trait are used to locate genetic risk factors.

Knowledge representation

Structured presentation of information that facilitates the drawing of inferences or conclusions, often giving predictive abilities.

ENCODE

(Encyclopedia of DNA Elements). An international research project to identify all functional elements in the human genome.

Biobanking

Assembling large collections of biosamples and associated information, for the purpose of biomedical investigation.

Syntax

The syntax of information is concerned with how the data is organized, ordered and structured.

Semantics

The semantics of information is concerned with the meaning of the data elements, such as words.

Semantic web

An extension of the World Wide Web that embeds semantics, or meaning, in documents, in links between documents and in descriptions of web services, thereby enabling navigation and reasoning by automated agents.

Genetic association database

A catalogue of reported genetic associations between genotype and phenotype.

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Thorisson, G., Muilu, J. & Brookes, A. Genotype–phenotype databases: challenges and solutions for the post-genomic era. Nat Rev Genet 10, 9–18 (2009). https://doi.org/10.1038/nrg2483

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