Integrating haplotype-specific linkage maps in tetraploid species using SNP markers View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-11

AUTHORS

Peter M. Bourke, Roeland E. Voorrips, Twan Kranenburg, Johannes Jansen, Richard G. F. Visser, Chris Maliepaard

ABSTRACT

KEY MESSAGE: Linkage mapping can help unravel the complexities of polyploid genomes. Here, we integrate haplotype-specific linkage maps in autotetraploid potato and explore the possibilities for mapping in other polyploid species. High-density linkage mapping in autopolyploid species has become possible in recent years given the increasing number of molecular markers now available through modern genotyping platforms. Such maps along with larger experimental populations are needed before we can obtain sufficient accuracy to make marker-trait association studies useful in practice. Here, we describe a method to create genetic linkage maps for an autotetraploid species with large numbers of markers and apply it to an F1 population of tetraploid potato (Solanum tuberosum L.) of 235 individuals genotyped using a 20K SNP array. SNP intensity values were converted to allele dosages after which we calculated pairwise maximum likelihood estimates of recombination frequencies between all marker segregation types under the assumption of random bivalent pairing. These estimates were used in the clustering of markers into linkage groups and their subsequent ordering into 96 homologue maps. The homologue maps were integrated per chromosome, resulting in a total map length of 1061 cM from 6910 markers covering all 12 potato chromosomes. We examined the questions of marker phasing and binning and propose optimal strategies for both. We also investigated the effect of quadrivalent formation and preferential pairing on recombination frequency estimation and marker phasing, which is of great relevance not only for potato but also for genetic studies in other tetraploid species for which the meiotic pairing behaviour is less well understood. More... »

PAGES

2211-2226

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00122-016-2768-1

DOI

http://dx.doi.org/10.1007/s00122-016-2768-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033375982

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27561740


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