Functional Genomics is concerned with the effect of Genome-wide information on transcription, translation and interactions between genes or gene-products [1 ]. A traditional approach in functional genomic studies is the use of genome-wide data as opposed to analyzing one gene at a time. This data is typically high-thoughput and as such, the use of computational tools in order to interpret it is crucial. Within functional genomics itself there are a few genetic phenomena which, because of their biological importance and implications, developed into their own fields. One such field is Epistasis.
Epistasis was first defined in 1909 to describe the masking effect that one variant or allele at one locus had on the variant at another locus [2 ]. In the pentrance table shown below we notice that the phenotype being observed (0 or 1) depends on at least two loci: A and B. The epistatic interaction between these two loci dictates that the genotype of the A allele is masked by the B genotype; we observe a phenotype only when the B genotype is present. If one wishes to identify Epistasis in genome-wide data, the use of systematic approaches is required. When Epistasis is observed from the data we have, it tells us something very interesting about the biological pathway leading to the phenotype of interest. Moreover, identification of epistatic interactions can also tell us something interesting about the biological interactions between the proteins produced by the genes at hand. Many human geneticists believe that Epistatic interactions are likely to be ubiquitous in common human diseases [3 ].
1. Wikipedia, "Functional Genomics", http://en.wikipedia.org/wiki/Functional_genomics, accessed on 09/03/2013
2. Cordell, H. J. (2002), "Epistasis: what it means, what is doesn't mean and statistical methods to detect it in humans". Human Molecular Genetics 11: 2463-2468.
3. Moore, J. H. (2003), "The ubiquitous nature of Epistasis in determining susceptibility to common human diseases". Human Heredity 56: 73-82.