Modelling dominance in a flexible intercross analysis

Rönnegård, Lars; Besnier, François; Carlborg, Örjan

doi:10.1186/1471-2156-10-30

Cited by 1 publication

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, a variance component approach has been proposed to detect segregation of multiple alleles in line-cross experiments—the FIA method (Rönnegård et al 2008 , 2009 ). NOIA has already been used to perform estimates of general genetic effects of biallelic loci detected by FIA (Besnier et al 2010 ), and it can now be used for the same task with multiallelic loci, which are the recurrent output of variance component mapping methods in general.…”

Section: Discussionmentioning

confidence: 99%

Multiallelic models of genetic effects and variance decomposition in non-equilibrium populations

Álvarez-Castro

Yang

2011

Genetica

View full text Add to dashboard Cite

Quantitative genetics stems from the theoretical models of genetic effects, which are re-parameterizations of the genotypic values into parameters of biological (genetic) relevance. Different formulations of genetic effects are adequate to address different subjects. We thus need to generalize and unify them under a common framework for enabling researchers to easily transform genetic effects between different biological meanings. The Natural and Orthogonal Interactions (NOIA) model of genetic effects has been developed to achieve this aim. Here, we further implement the statistical formulation of NOIA with multiple alleles under Hardy–Weinberg departures (HWD). We show that our developments are straightforwardly connected to the decomposition of the genetic variance and we point out several emergent properties of multiallelic quantitative genetic models, as compared to the biallelic ones. Further, NOIA entails a natural extension of one-locus developments to multiple epistatic loci under linkage equilibrium. Therefore, we present an extension of the orthogonal decomposition of the genetic variance to multiple epistatic, multiallelic loci under HWD. We illustrate this theory with a graphical interpretation and an analysis of published data on the human acid phosphatase (ACP1) polymorphism.

show abstract

Section: Discussionmentioning

confidence: 99%