Abstract
Phenotypes of sessile organisms, such as plants, rely not only on their own genotypes but also on those of neighboring individuals. Previously, we incorporated such neighbor effects into a single-marker regression using the Ising model of ferromagnetism. However, little is known regarding how neighbor effects should be incorporated in quantitative trait locus (QTL) mapping. In this study, we propose a new method for interval QTL mapping of neighbor effects, designated “neighbor QTL,” the algorithm of which includes: (1) obtaining conditional self-genotype probabilities with recombination fraction between flanking markers; (2) calculating conditional neighbor genotypic identity using the self-genotype probabilities; and (3) estimating additive and dominance deviations for neighbor effects. Our simulation using F2 and backcross lines showed that the power to detect neighbor effects increased as the effective range decreased. The neighbor QTL was applied to insect herbivory on Col × Kas recombinant inbred lines of Arabidopsis thaliana. Consistent with previous results, the pilot experiment detected a self-QTL effect on the herbivory at the GLABRA1 locus. Regarding neighbor QTL effects on herbivory, we observed a weak QTL on the top of chromosome 4, at which a weak self-bolting QTL was also identified. The neighbor QTL method is available as an R package (https://cran.r-project.org/package=rNeighborQTL), providing a novel tool to investigate neighbor effects in QTL studies.
Highlights
Sessile organisms, such as land plants, have no active mobility to escape neighboring individuals
Genomewide association studies (GWAS) have been developed, there are several limitations of this approach such as false positive signals due to the population structure (Hayes, 2013) and small-effect variants being overlooked if they are rare in the sample population (Korte and Farlow, 2013)
Assuming that two marker effects a and d were unlikely to be equivalent between self and neighbor effects, we introduced a1 and d1 to the self quantitative trait locus (QTL) effects; and a2 and d2 to the neighbor QTL effects
Summary
Sessile organisms, such as land plants, have no active mobility to escape neighboring individuals. Field studies have shown that the phenotypes of an individual plant depend on their own genotype and on those of neighboring plants (Barbosa et al, 2009). QTL mapping of neighbor effects is more complicated than single-marker analysis because QTL studies employ the maximum likelihood method for interval mapping between flanking markers (Haley and Knott, 1992; Jansen, 1993; Broman and Sen, 2009). Such an interval mapping requires a stepwise inference from genotype imputation to phenotype prediction.
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