Detecting quantitative trait loci and exploring chromosomal pairing in autopolyploids using polyqtlR

• Published in: Bioinformatics (Oxford, England) Vol. 37; no. 21; pp. 3822 - 3829
• Main Authors: Bourke, Peter M, Voorrips, Roeland E, Hackett, Christine A, van Geest, Geert, Willemsen, Johan H, Arens, Paul, Smulders, Marinus J M, Visser, Richard G F, Maliepaard, Chris
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 05.11.2021
• Subjects: Chromosome Mapping; Humans; Likelihood Functions; Original Papers; Polyploidy; Quantitative Trait Loci; Software
• ISSN: 1367-4803; 1367-4811; 1367-4811
• DOI: 10.1093/bioinformatics/btab574

Abstract Motivation The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), requiring specialized tools for such analyses. Moreover, deciphering meiotic processes at higher ploidy levels is not straightforward, but is necessary to understand the reproductive dynamics of these species, or uncover potential barriers to their genetic improvement. Results Here, we present polyqtlR, a novel software tool to facilitate such analyses in (auto)polyploid crops. It performs QTL interval mapping in F1 populations of outcrossing polyploids of any ploidy level using identity-by-descent probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualization tools within the package facilitate this process, and options to include genetic co-factors and experimental factors are included. Detailed information on polyploid meiosis including prediction of multivalent pairing structures, detection of preferential chromosomal pairing and location of double reduction events can be performed. Availabilityand implementation polyqtlR is freely available from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR. Supplementary information Supplementary data are available at Bioinformatics online.