PERGOLA: fast and deterministic linkage mapping of polyploids

BMC Bioinformatics. 2017 Jan 4;18(1):12. doi: 10.1186/s12859-016-1416-8.

Abstract

Background: A large share of agriculturally and horticulturally important plant species are polyploid. Linkage maps are used to locate associations between genes and traits by breeders and geneticists. Linkage map creation for polyploid species is not supported by standard tools. We want to overcome this limitation and validate our results with simulation studies.

Results: We developed PERGOLA, a deterministic and heuristic method that addresses this problem. We show that it creates correct linkage groups, marker orders and distances for simulated and real datasets. We compare it to existing tools and demonstrate that it overcomes limitations in ploidy and outperforms them in computational time and mapping accuracy. We represent linkage maps as dendrograms and show that this has advantages in the comparison of different maps.

Conclusions: PERGOLA can be used successfully to calculate linkage maps for diploid and polyploid species and outperforms existing tools.

Keywords: Heuristic; Linkage mapping; Polyploids.

MeSH terms

  • Algorithms
  • Chromosome Mapping / methods*
  • Genetic Linkage
  • Internet
  • Polyploidy
  • User-Computer Interface*