2012 **Abstract:** Knowledge of the nature and magnitude of gene effects, as well as their contribution to the control of metric traits, is important in formulating efficient breeding programs for the improvement of plant genetics. Information concerning a genetic parameter such as the additive-by-additive epistatic effect can be useful in traditional breeding. This report describes the results obtained by applying weighted multiple linear regression to estimate the parameter connected with an additive-by-additive epistatic inte…

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“…Epistasis between quantitative trait loci (QTLs) assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone (Edwards et al , 1987; Doebley and Stec, 1991; Paterson et al , 1991; Stuber et al , 1992; De-Vicente and Tanksley, 1993; Lin et al , 1995; Xiao et al , 1995). Recently epistatic effects have been considered by many researchers as important for complex traits (Lark et al , 1995; Eshed and Zamir, 1996; Cockerham and Zeng, 1996; Yu et al , 1997; Conti et al , 2011; Gowda et al , 2011; Jiang et al , 2011; Li et al , 2011; Mao et al , 2011; Upadhyaya et al , 2011; Bocianowski, 2012a,b,c). Hence, genetic models for QTL mapping assuming no epistasis could lead to a biased estimation of QTL parameters.…”

confidence: 99%

“…Epistasis between quantitative trait loci (QTLs) assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone (Edwards et al , 1987; Doebley and Stec, 1991; Paterson et al , 1991; Stuber et al , 1992; De-Vicente and Tanksley, 1993; Lin et al , 1995; Xiao et al , 1995). Recently epistatic effects have been considered by many researchers as important for complex traits (Lark et al , 1995; Eshed and Zamir, 1996; Cockerham and Zeng, 1996; Yu et al , 1997; Conti et al , 2011; Gowda et al , 2011; Jiang et al , 2011; Li et al , 2011; Mao et al , 2011; Upadhyaya et al , 2011; Bocianowski, 2012a,b,c). Hence, genetic models for QTL mapping assuming no epistasis could lead to a biased estimation of QTL parameters.…”

confidence: 99%

“…A common problem reported so far as associated with the analyses of data is that analyses of single-locus QTLs and epistatic interactions were conducted separately using different analytical tools (Xing et al , 2002; Bocianowski, 2008, 2012a,b,c; Krajewski et al , 2012). Although both of the analytical tools can provide statistical estimates for the amount of the effects and the proportions of variance explained, it is necessary for a joint estimation to evaluate the relative importance of individual QTLs and epistatic interactions in determining the performance of these traits.…”

confidence: 99%

“…With increasing evidence supporting the claim that epistatic interactions are usually involved in the genetic variation of complex traits (Mao et al 2006;Tabanao and Bernardo 2007), several complicated mapping models were developed to analyze epistatic effects: expanded composite interval mapping (CIM) to multiple interval mapping (Kao et al 1999), mixed linear model based CIM (Wang et al 1999), Bayesian approach (Yang et al 2007;Yi et al 2007), and weighted multiple linear regression (Bocianowski 2012c). Jannink and Jansen (2001) suggested mapping QTLs with epistasis between QTLs and backgrounds using one-dimensional genome search.…”

confidence: 99%

“…Epistasis is a phenomenon in which the effect of one genetic variant is masked or modified by one or more genetic variants and is often defined as the departure from additive effects in a linear model (Fisher 1918). Many statistical methods, including regression-based methods, have been developed to detect epistasis in quantitative genetic analysis (Cordell 2009;Chen and Cui 2010;Bocianowski 2012). However, these methods were originally designed to detect epistasis for common variants (Steen 2011) and are difficult to apply to rare variants because of their high type 1 error rates and poor ability to detect interactions between rare variants.…”

confidence: 99%