Document details for 'Quantifying the power and precision of QTL analysis in autopolyploids under bivalent and multivalent genetic models'

Authors Bourke, PM., Hackett, C.A., Voorrips, R., Visser, R.G.F. and Maliepaard, C.
Publication details G3: Genes, Genomes, Genetics 9(7), 2107-2122.
Keywords Quantitative Trait Locus (QTL) analysis, autopolyploid, double reduction, QTL power, Bayesian Information Criterion (BIC), genotypic information coefficient (GIC).
Abstract New genotyping technologies, offering the possibility of high genetic resolution at low cost, have helped fuel a surge in interest in the genetic analysis of polyploid species. Nevertheless, autopolyploid species present extra challenges not encountered in diploids and allopolyploids, such as polysomic inheritance or double reduction. Here we investigate the power and precision of quantitative trait locus (QTL) analysis in outcrossing autotetraploids, comparing the results of a model that assumes random bivalent chromosomal pairing during meiosis to one that also allows for multivalents and double reduction. Through a series of simulation studies we found that marginal gains in QTL detection power are achieved using the double reduction model but at the cost of an impaired ability to determine the most likely QTL segregation type and mode of action. We also explored the effect of variable genotypic information across parental homologues and found that both QTL detection power and precision require high and uniform information contents. This suggests linkage analyses results for autopolyploids should be accompanied by marker coverage information across all parental homologues along with the per-homologue genotypic information coefficients (GIC). Visualising the GIC landscape of the homologues of interest around QTL peaks will help elucidate the limitations of QTL power and precision in further studies. Application of these methods to an autotetraploid potato (Solanum tuberosum L.) mapping population confirmed our ability to locate and dissect QTL in highly heterozygous outcrossing autotetraploid populations.
Last updated 2019-08-20

Unless explicitly stated otherwise, all material is copyright © Biomathematics and Statistics Scotland.

Biomathematics and Statistics Scotland (BioSS) is formally part of The James Hutton Institute (JHI), a registered Scottish charity No. SC041796 and a company limited by guarantee No. SC374831. Registered Office: JHI, Invergowrie, Dundee, DD2 5DA, Scotland