Exploiting the proteome to improve the genome-wide genetic analysis of epistasis in common human diseases |
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Authors: | Kristine A Pattin Jason H Moore |
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Institution: | Computational Genetics Laboratory, Norris-Cotton Cancer Center, Dartmouth Medical School, Lebanon, NH, USA. |
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Abstract: | One of the central goals of human genetics is the identification of loci with alleles or genotypes that confer increased susceptibility.
The availability of dense maps of single-nucleotide polymorphisms (SNPs) along with high-throughput genotyping technologies
has set the stage for routine genome-wide association studies that are expected to significantly improve our ability to identify
susceptibility loci. Before this promise can be realized, there are some significant challenges that need to be addressed.
We address here the challenge of detecting epistasis or gene–gene interactions in genome-wide association studies. Discovering
epistatic interactions in high dimensional datasets remains a challenge due to the computational complexity resulting from
the analysis of all possible combinations of SNPs. One potential way to overcome the computational burden of a genome-wide
epistasis analysis would be to devise a logical way to prioritize the many SNPs in a dataset so that the data may be analyzed
more efficiently and yet still retain important biological information. One of the strongest demonstrations of the functional
relationship between genes is protein-protein interaction. Thus, it is plausible that the expert knowledge extracted from
protein interaction databases may allow for a more efficient analysis of genome-wide studies as well as facilitate the biological
interpretation of the data. In this review we will discuss the challenges of detecting epistasis in genome-wide genetic studies
and the means by which we propose to apply expert knowledge extracted from protein interaction databases to facilitate this
process. We explore some of the fundamentals of protein interactions and the databases that are publicly available. |
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