Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect

Abstract

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

Estimation of additive and epistatic gene effects of doubled haploid lines of winter oilseed rape (Brassica napus L.)

“…parental, F 1 , F 2 , BC 1 . However, more effective estimation of additive and epistasis effects is on the basis of homozygous lines (Bocianowski 2012a(Bocianowski , 2013(Bocianowski , 2014Bocianowski and Nowosad 2015;Kim et al 2015;Monnahan and Kelly 2015;Ober et al 2015).…”

Mixed linear model approaches in mapping QTLs with epistatic effects by a simulation study

“…Determining the contribution of epistasis is important for understanding the genetic basis of complex traits. Hence, genetic models for QTL mapping assuming no epistasis can lead to a biased estimation of QTL parameters (Bocianowski 2013). A large number of epistatic effects have recently been detected in rice (Oryza sativa L.) using polymorphic markers in the whole genome (Hua et al 2002;Mei et al 2003Mei et al , 2005.…”

“…Strong interactions between QTLs have also been observed in maize (Lukens and Doebley 1999) and soybean (Lark et al 1995). Recent genetic analyses using molecular markers in several plant species have clearly shown that, in addition to single locus QTLs, epistatic interactions play an important role on the genetic basis of quantitative traits (Lark et al 1995;Maughan et al 1996;Li et al 1997;Yu et al 1997;Poelwijk et al 2011;Krajewski et al 2012;Bocianowski 2012cBocianowski , 2013Bocianowski , 2014.…”

High Density Mapping of Quantitative Trait Loci Conferring Gluten Strength in Canadian Durum Wheat

“…The identification of epistatic interactions for the QTL whose effects mostly dependent on the genotypes of other loci, can provide a more comprehensive understanding of genetic components controlling the expression of complex traits and a more accurate prediction for the phenotypic traits (Bocianowski, 2013). Of note, in the present study the epistatic interaction between QGlu.spa-1A and QGlu.spa-1B.1 was repeatedly detected in 4 out of 6 environments indicating a positive interaction between alleles of HMW-GS and LMW-GS.…”