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Epistasis refers to genetic interactions in which the mutation of one gene masks the phenotypic effects of a mutation at another locus. Systematic analysis of these epistatic interactions can provide insight into the structure and function of genetic pathways. Examining the phenotypes resulting from pairs of mutations helps in understanding how the function of these genes intersects. Genetic interactions are generally classified as either Positive/Alleviating or Negative/Aggravating. Fitness epistasis (an interaction between non-allelic genes) is positive (in other words, diminishing, antagonistic or buffering) when a loss of function mutation of two given genes results in exceeding the fitness predicted from individual effects of deleterious mutations, and it is negative (that is, reinforcing, synergistic or aggravating) when it decreases fitness. Ryszard Korona and Lukas Jasnos showed that the epistatic effect is usually positive in Saccharomyces cerevisiae. Usually, even in case of positive interactions double mutant has smaller fitness than single mutants.〔 The positive interactions occur often when both genes lie within the same pathway Conversely, negative interactions are characterized by an even stronger defect than would be expected in the case of two single mutations, and in the most extreme cases (synthetic sick/lethal) the double mutation is lethal. This aggravated phenotype arises when genes in compensatory pathways are both knocked out. High-throughput methods of analyzing these types of interactions have been useful in expanding our knowledge of genetic interactions. ''Synthetic genetic arrays'' (SGA), ''diploid based synthetic lethality analysis on microarrays'' (dSLAM), and ''epistatic miniarray profiles'' (E-MAP) are three important methods which have been developed for the systematic analysis and mapping of genetic interactions. This systematic approach to studying epistasis on a genome wide scale has significant implications for functional genomics. By identifying the negative and positive interactions between an unknown gene and a set genes within a known pathway, these methods can elucidate the function of previously uncharacterized genes within the context of a metabolic or developmental pathway. ==Inferring function: alleviating and aggravating mutations== In order to understand how information about epistatic interactions relates to gene pathways, let us consider a simple example of vulval cell differentiation in C. elegans. Cells differentiate from Pn cells to Pn.p cells to VP cells to vulval cells. Mutation of lin-26〔http://www.ncbi.nlm.nih.gov/gene?cmd=retrieve&list_uids=3565051〕 blocks differentiation of Pn cells to Pn.p cells. Mutants of lin-36〔http://www.ncbi.nlm.nih.gov/gene/176128〕 behave similarly, blocking differentiation at the transition to VP cells. In both cases, the resulting phenotype is marked by an absence of vulval cells as there is an upstream block in the differentiation pathway. A double mutant in which both of these genes have been disrupted exhibits an equivalent phenotype that is no worse than either single mutant. The upstream disruption at lin-26 masks the phenotypic effect of a mutation at lin-36 〔 in a classic example of an alleviating epistatic interaction. Aggravating mutations on the other hand give rise to a phenotype which is worse than the cumulative effect of each single mutation. This aggravated phenotype is indicative of two genes in compensatory pathways. In the case of the single mutant a parallel pathway is able to compensate for the loss of the disrupted pathway however, in the case of the double mutant the action of this compensatory pathway is lost as well, resulting in the more dramatic phenotype observed. This relationship has been significantly easier to detect than the more subtle alleviating phenotypes and has been extensively studied in S. cerevisiae through synthetic sick/lethal (SSL) screens which identify double mutants with significantly decreased growth rates. It should be pointed out that these conclusions from double-mutant analysis, while they apply to many pathways and mutants, are not universal. For example, genes can act in opposite directions in pathways, so that knocking out both produces a near-normal phenotype, while each single mutant is severely affected (in opposite directions). A well-studied example occurs during early development in Drosophila, wherein gene products from the ''hunchback'' and ''nanos'' genes are present in the egg, and act in opposite directions to direct anterior-posterior pattern formation. Something similar often happens in signal transduction pathways, where knocking out a negative regulator of the pathway causes a hyper-activation phenotype, while knocking out a positively acting component produces an opposite phenotype. In linear pathways with a single "output", when knockout mutations in two oppositely-acting genes are combined in the same individual, the phenotype of the double mutant is typically the same as the phenotype of the single mutant whose normal gene product acts downstream in the pathway. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Epistasis and functional genomics」の詳細全文を読む スポンサード リンク
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