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Next generation disease mapping

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Genetic mapping in disease

The advent of genomics technology necessitates methods for handling large chunks of information. This is of particular importance in human genetics, where an association is required with the disease phenotype.

Fundamental Research icon Fundamental Research
Health icon Health

Recent research has fuelled the discovery of over 500 validated single nucleotide polymorphism (SNP) phenotype associations. However, SNPs do not explain the heritability of many common genetic diseases and their effect at the cell level remains unknown. In the near future, disease mapping projects will have access to full genome sequencing. To be able to manage and analyse very high dimensional data in a statistically powerful way, and interpret these in relation to complex phenotypes, appropriate methods are urgently needed. The EU-funded NEXTGENE (Next generation disease mapping) project set out to develop new methods capable of identifying more variants contributing to disease by explicitly modelling their interaction and combining the statistical signal contributed by several rare variants. The approach analysed sequencing data and the frequencies of associated variants were based on those obtained from evolutionary theory. Additionally, they investigated how disease-associated genes are closer in protein interaction space and used this to devise a new method for the identification of disease genes. They also generated software capable of detecting insertion and deletion polymorphisms as well as enabling an efficient assembly of complete mitochondria in whole genome sequencing studies. Intriguingly, comparison of parent and offspring genomes allowed researchers to calculate the de novo mutation rate and find its contribution towards new diseases. Taken together, the deliverables of the NEXTGENE project provide a thorough understanding of how certain genetic variants contribute to disease. The generated tools and results are of clinical relevance and will drive future research projects in the field.

Keywords

Human genetics, SNP, NEXTGENE, mitochondria, mutation rate

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