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Neighbor QTL: an interval mapping method for quantitative trait loci underlying plant neighborhood effects
Author(s) -
Yasuhiro Sato,
Kazuya Takeda,
Atsushi J. Nagano
Publication year - 2021
Publication title -
g3 genes genomes genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.468
H-Index - 66
ISSN - 2160-1836
DOI - 10.1093/g3journal/jkab017
Subject(s) - biology , quantitative trait locus , inclusive composite interval mapping , family based qtl mapping , trait , interval (graph theory) , genetics , expression quantitative trait loci , evolutionary biology , gene mapping , statistics , single nucleotide polymorphism , gene , genotype , chromosome , mathematics , combinatorics , computer science , programming language
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.

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