Using probabilistic genotypes in linkage analysis of polyploids

• Published in: Theoretical and applied genetics Vol. 134; no. 8; pp. 2443 - 2457
• Main Authors: Liao, Yanlin, Voorrips, Roeland E., Bourke, Peter M., Tumino, Giorgio, Arens, Paul, Visser, Richard G. F., Smulders, Marinus J. M., Maliepaard, Chris
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2021; Springer; Springer Nature B.V
• Subjects: Agriculture; Alleles; Analysis; Biochemistry; Biomedical and Life Sciences; Biotechnology; chromosome mapping; Chromosome Mapping - methods; Chromosomes; Chromosomes, Plant - genetics; Computer Simulation; computer software; data quality; Diploids; diploidy; Dosage; Gene Expression Regulation, Plant; Gene mapping; Genetic aspects; Genetics; Genomes; Genotype; Genotype & phenotype; Genotypes; Genotyping; heterozygosity; homozygosity; Information management; Life Sciences; Linkage analysis; Original; Original Article; Plant Biochemistry; Plant Breeding/Biotechnology; Plant Genetics and Genomics; Plant Proteins - genetics; Plant Proteins - metabolism; Polymorphism, Single Nucleotide; Polyploidy; Potatoes; Quantitative Trait Loci; single nucleotide polymorphism arrays; Single-nucleotide polymorphism; Software packages; Solanum tuberosum; Solanum tuberosum - genetics; Solanum tuberosum - growth & development; uncertainty
• DOI: 10.1007/s00122-021-03834-x
• ISSN: 0040-5752; 1432-2242

Key message In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato ( Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.