Identifying the minimum number of microsatellite loci needed to assess population genetic structure: A case study in fly culturing. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Arthofer, Wolfgang; Heussler, Carina; Krapf, Patrick; Schlick-Steiner, Birgit C.; Steiner, Florian M.
• Is Part Of: Fly. Volume 12:Issue 1(2018)
• Page Start: 13
• Page End: 22
• Publication Date: 2018-01-02
• Subjects: population genetics -- microsatellite markers -- population structure -- genetic monitoring -- loss of genetic variation -- genetic drift -- Drosophila nigrosparsa; Drosophila -- Periodicals; 595.77
• DOI: 10.1080/19336934.2017.1396400
• Languages: English
• ISSNs: 1933-6934

Abstract

ABSTRACT: Small, isolated populations are constantly threatened by loss of genetic diversity due to drift. Such situations are found, for instance, in laboratory culturing. In guarding against diversity loss, monitoring of potential changes in population structure is paramount; this monitoring is most often achieved using microsatellite markers, which can be costly in terms of time and money when many loci are scored in large numbers of individuals. Here, we present a case study reducing the number of microsatellites to the minimum necessary to correctly detect the population structure of two Drosophila nigrosparsa populations. The number of loci was gradually reduced from 11 to 1, using the Allelic Richness (AR) and Private Allelic Richness (PAR) as criteria for locus removal. The effect of each reduction step was evaluated by the number of genetic clusters detectable from the data and by the allocation of individuals to the clusters; in the latter, excluding ambiguous individuals was tested to reduce the rate of incorrect assignments. We demonstrate that more than 95% of the individuals can still be correctly assigned when using eight loci and that the major population structure is still visible when using two highly polymorphic loci. The differences between sorting the loci by AR and PAR were negligible. The method presented here will most efficiently reduce genotyping costs when small sets of loci ("core sets") for long-time use in large-scale population screenings are compiled.