Statistical power for detecting epistasis QTL effects under the F-2 design

Abstract

<p>Abstract</p> <p>Epistasis refers to gene interaction effect involving two or more genes. Statistical methods for mapping quantitative trait loci (QTL) with epistasis effects have become available recently. However, little is known about the statistical power and sample size requirements for mapping epistatic QTL using genetic markers. In this study, we developed analytical formulae to calculate the statistical power and sample requirement for detecting each epistasis effect under the F-2 design based on crossing inbred lines. Assuming two unlinked interactive QTL and the same absolute value for all epistasis effects, the heritability of additive × additive (a × a) effect is twice as large as that of additive × dominance (a × d) or dominance × additive (d × a) effect, and is four times as large as that of dominance × dominance (d × d) effect. Consequently, among the four types of epistasis effects involving two loci, 'a × a' effect is the easiest to detect whereas 'd × d' effect is the most difficult to detect. The statistical power for detecting 'a × a' effect is similar to that for detecting dominance effect of a single QTL. The sample size requirements for detecting 'a × d', 'd × a' and 'd × d' are highly sensitive to increased distance between the markers and the interacting QTLs. Therefore, using dense marker coverage is critical to detecting those effects.</p

Genetic mapping and analysis of traits related to improvement of popcorn

“…The D x A epistatic effect for GDU was considered minor or a type 1 error because it was detected in one year only. The relatively more consistent detection of A x A than A x D/D x A and D x D epistasis (detected for plant height) was in agreement with simulation studies which show that the power to detect epistasis decreases in the order A x A < A x D = D x A < D x D (Mao and Da, 2005).…”

“…A dominance x dominance (D x D) epistatic effect was detected for plant height between a QTL near bnlg125 on chromosome 2 and a QTL near bnlg244 on chromosome 9 in 2004. Among all genetic effects (additive, dominance and their two-locus interactions), D x D epistasis has the lowest power of detection in QTL mapping studies (Mao and Da, 2005), suggesting that the detected D x D epistatic effect could be a false positive (type I error).…”

“…Despite the small population size relative to those recommended by simulation studies (e.g. Mao and Da, 2005), the A x A epistatic effect detected for GDU was considered a true effect (rather than a false positive) because it was detected in one environment (year) and also in the combined analysis. The D x A epistatic effect for GDU was considered minor or a type 1 error because it was detected in one year only.…”

“…Epistasis may have an important role in quantitative trait variation (Carlborg and Haley, 2004;Doebley et al, 1995;Eshed and Zamir, 1996;Lark et al, 1995), but its detection for quantitative traits may be complicated by the fact that epistatic effects are generally smaller than the additive and dominance main effects, resulting in low power to detect interaction effects in typical QTL mapping population sizes (Mao and Da, 2005).…”

Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits

“…Conversely, if interacting loci are not considered, variation caused by epistasis is removed from the tested model and absorbed into residual error. Nevertheless, detecting epistasis genome-wide is cumbersome and often hampered by either computationally demanding algorithms, a lack of appropriate statistical methodology, or a reduced mapping population size (Doerge 2001 ; Mao and Da 2004 ). Conventional single-QTL mapping models, like IM and CIM, are not able to deal with interacting loci, treating epistasis as background noise.…”