Abstract

In this paper we present a novel approach to quantifying genetic architecture that combines recombinant inbred lines (RIL) with line cross analysis (LCA). LCA is a method of quantifying directional genetic effects (i.e. summed effects of all loci) that differentiate two parental lines. Directional genetic effects are thought to be critical components of genetic architecture for the long term response to selection and as a cause of inbreeding depression. LCA typically begins with two inbred parental lines that are crossed to produce several generations such as F1, F2, and backcrosses to each parent. When a RIL population (founded from the same P1 and P2 as was used to found the line cross population) is added to the LCA, the sampling variance of several nonadditive genetic effect estimates is greatly reduced. Specifically, estimates of directional dominance, additive x additive, and dominance x dominance epistatic effects are reduced by 92%, 94%, and 56% respectively. The RIL population can be simultaneously used for QTL identification, thus uncovering the effects of specific loci or genomic regions as elements of genetic architecture. LCA and QTL mapping with RIL provide two qualitatively different measures of genetic architecture with the potential to overcome weaknesses of each approach alone. This approach provides cross-validation of the estimates of additive and additive x additive effects, much smaller confidence intervals on dominance, additive x additive and dominance x dominance estimates, qualitatively different measures of genetic architecture, and the potential when used together to balance the weaknesses of LCA or RIL QTL analyses when used alone.

Highlights

  • Understanding the genetic basis of complex phenotypes, i.e. genetic architecture, is of fundamental importance both for modeling evolutionary change and for genetic manipulation of crop plants

  • Hansen and colleagues [2,32,33] have shown that the directional epistasis revealed by line cross analysis may be a key to understanding continued response to long term selection, and empirical work in corn and chicken is consistent with this theoretical prediction [34,35,12]

  • In this paper we present a novel approach to quantifying genetic architecture that combines recombinant inbred lines (RIL) with line cross analysis

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Summary

Introduction

Understanding the genetic basis of complex phenotypes, i.e. genetic architecture, is of fundamental importance both for modeling evolutionary change and for genetic manipulation of crop plants. Genetic architecture is a broad term for all factors that influence the determination of phenotype from genotype It includes all genetic effects on traits: the number of genes, allelic effects, epistasis, pleiotropy, and genotype x environment interactions [1]. Studies of genetic architecture have revealed that epistasis, i.e. interactions between loci, is a common component of most quantitative traits. Line cross analysis (LCA) is a well established method of quantifying genetic architecture with a long history of use in agriculture. Hansen and colleagues [2,32,33] have shown that the directional epistasis revealed by line cross analysis may be a key to understanding continued response to long term selection, and empirical work in corn and chicken is consistent with this theoretical prediction [34,35,12]. These two uses of a RIL population yield qualitatively different information about genetic architecture and can be used in a powerful and complementary manner

Materials and Methods
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Results and Discussion
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