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Multi-individual microsatellite identification: A multiple genome approach to microsatellite design (MiMi)

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • G. Fox
  • R.F. Preziosi
  • R.E. Antwis
  • M. Benavides-Serrato
  • F.J. Combe
  • W.E. Harris
  • I.R. Hartley
  • A.C. Kitchener
  • S.R. de Kort
  • A.-I. Nekaris
  • J.K. Rowntree
<mark>Journal publication date</mark>1/11/2019
<mark>Journal</mark>Molecular Ecology Resources
Issue number6
Number of pages9
Pages (from-to)1672-1680
Publication StatusPublished
Early online date27/08/19
<mark>Original language</mark>English


Bespoke microsatellite marker panels are increasingly affordable and tractable to researchers and conservationists. The rate of microsatellite discovery is very high within a shotgun genomic data set, but extensive laboratory testing of markers is required for confirmation of amplification and polymorphism. By incorporating shotgun next‐generation sequencing data sets from multiple individuals of the same species, we have developed a new method for the optimal design of microsatellite markers. This new tool allows us to increase the rate at which suitable candidate markers are selected by 58% in direct comparisons and facilitate an estimated 16% reduction in costs associated with producing a novel microsatellite panel. Our method enables the visualisation of each microsatellite locus in a multiple sequence alignment allowing several important quality checks to be made. Polymorphic loci can be identified and prioritised. Loci containing fragment‐length‐altering mutations in the flanking regions, which may invalidate assumptions regarding the model of evolution underlying variation at the microsatellite, can be avoided. Priming regions containing point mutations can be detected and avoided, helping to reduce sample‐site‐marker specificity arising from genetic isolation, and the likelihood of null alleles occurring. We demonstrate the utility of this new approach in two species: an echinoderm and a bird. Our method makes a valuable contribution towards minimising genotyping errors and reducing costs associated with developing a novel marker panel. The Python script to perform our method of multi‐individual microsatellite identification (MiMi) is freely available from GitHub (https://github.com/graemefox/mimi).