polymapR—linkage analysis and genetic map construction from F1 populations of outcrossing polyploids

• Published in: Bioinformatics Vol. 34; no. 20; pp. 3496 - 3502
• Main Authors: Bourke, Peter M, van Geest, Geert, Voorrips, Roeland E, Jansen, Johannes, Kranenburg, Twan, Shahin, Arwa, Visser, Richard G F, Arens, Paul, Smulders, Marinus J M, Maliepaard, Chris
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.10.2018
• Subjects: EPS; Laboratorium voor Plantenveredeling; Laboratory of Plant Breeding; Original Papers; PBR Biodiversiteit en Genetische Variatie; PBR Biodiversity and genetic variation; PBR Kwantitatieve aspecten; PBR Ornamentals, tissue culture and gene transfer; PBR Quantitative aspects of Plant Breeding; PBR Siergewassen, Tissue Culture; PE&RC; Plant Breeding; WUR PB Biodiversiteit en Genetische Variatie; WUR PB Kwantitatieve Aspecten; WUR PB Siergewassen, Tissue Culture; WUR Plant Breeding
• DOI: 10.1093/bioinformatics/bty371
• ISSN: 1367-4803; 1367-4811

Abstract Motivation Polyploid species carry more than two copies of each chromosome, a condition found in many of the world’s most important crops. Genetic mapping in polyploids is more complex than in diploid species, resulting in a lack of available software tools. These are needed if we are to realize all the opportunities offered by modern genotyping platforms for genetic research and breeding in polyploid crops. Results polymapR is an R package for genetic linkage analysis and integrated genetic map construction from bi-parental populations of outcrossing autopolyploids. It can currently analyse triploid, tetraploid and hexaploid marker datasets and is applicable to various crops including potato, leek, alfalfa, blueberry, chrysanthemum, sweet potato or kiwifruit. It can detect, estimate and correct for preferential chromosome pairing, and has been tested on high-density marker datasets from potato, rose and chrysanthemum, generating high-density integrated linkage maps in all of these crops. Availability and implementation polymapR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polymapR. Supplementary information Supplementary data are available at Bioinformatics online.