Something old and something new: wedding recombinant inbred lines with traditional line cross analysis increases power to describe gene interactions

• Published in: PloS one 2010-04, Vol.5 (4), p.e10200-e10200
• Main Authors: Elnaccash, Tarek W, Tonsor, Stephen J
• Format: Article
• Language: English
• Subjects: Alzheimer's disease; Alzheimers disease; Analysis; Animal behavior; Arabidopsis; Arabidopsis - genetics; Arabidopsis thaliana; Architecture; Autosomal dominant inheritance; Confidence intervals; Critical components; Dominance; Ecology; Epistasis; Epistasis, Genetic; Estimates; Evolution; Evolutionary Biology/Evolutionary and Comparative Genetics; Evolutionary Biology/Plant Genetics and Gene Expression; Gene loci; Gene mapping; Genes, Plant - genetics; Genetic effects; Genetic engineering; Genetic research; Genetics and Genomics/Complex Traits; Genetics and Genomics/Gene Discovery; Genetics and Genomics/Plant Genomes and Evolution; Hypothesis testing; Inbreeding; Inbreeding depression; Loci; Mimulus; Power; Quantitative genetics; Quantitative Trait Loci; Studies; Tribolium; Tribolium castaneum; Weddings
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0010200

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.