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

Abstract
The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms develop and respond to their environment through the identification of genes and their alleles that contribute to trait variation. This knowledge can help guide and accelerate breeding programs aimed at developing superior genotypes through genomics-assisted breeding. Performing such analyses at higher ploidy levels, relevant for many important crop species, requires specialised tools. Moreover, deciphering meiotic processes at higher ploidy levels can deepen our understanding of the reproductive dynamics of these species and help uncover potential barriers to their genetic improvement. Here we present polyqtlR, a software tool to facilitate such analyses in autopolyploids that performs QTL interval mapping in F1 populations of outcrossing autopolyploids and segmental allopolyploids of any ploidy level using identity-by-descent (IBD) probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualisation tools within the package facilitate this process, and options to include genetic co-factors and experimental blocks 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. polyqtlR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR.
Year
2021
Category
Refereed journal
Output Tags
WP 2.1 Crop and grassland production and disease control (RESAS 2016-21)