02351nas a2200193   4500008004100000022001400041245023400055210006900289260001200358300001200370490000800382520160200390100002301992700002302015700002302038700002402061700002702085856004502112       2018                        eng d  a0022-339500aDevelopment and Characterization of 12 Novel Polymorphic Microsatellite Loci for the Mammal Chewing Louse Geomydoecus aurei (Insecta: Phthiraptera) and a Comparison of Next-Generation Sequencing Approaches for Use in Parasitology0 aDevelopment and Characterization of 12 Novel Polymorphic Microsa  c02/2018  a89 - 950 v1043 a<p>Next-generation sequencing methodologies open the door for evolutionary studies of wildlife parasites. We used 2 next-generation sequencing approaches to discover microsatellite loci in the pocket gopher chewing louse Geomydoecus aurei for use in population genetic studies. In one approach, we sequenced a library enriched for microsatellite loci; in the other approach, we mined microsatellites from genomic sequences. Following microsatellite discovery, promising loci were tested for amplification and polymorphism in 390 louse individuals from 13 pocket gopher hosts. In total, 12 loci were selected for analysis (6 from each methodology), none of which exhibited evidence of null alleles or heterozygote deficiencies. These 12 loci showed adequate genetic diversity for population-level analyses, with 3&ndash;9 alleles per locus with an average HE per locus ranging from 0.32 to 0.70. Analysis of Molecular Variance (AMOVA) indicated that genetic variation among infrapopulations accounts for a low, but significant, percentage of the overall genetic variation, and individual louse infrapopulations showed FST values that were significantly different from zero in the majority of pairwise infrapopulation comparisons, despite all 13 infrapopulations being taken from the same locality. Therefore, these 12 polymorphic markers will be useful at the infrapopulation and population levels for future studies involving G. aurei. This study shows that next-generation sequencing methodologies can successfully be used to efficiently obtain data for a variety of evolutionary questions.</p>
1 aLight, Jessica, E.1 aHarper, Sheree, E.1 aJohnson, Kevin, P.1 aDemastes, James, W.1 aSpradling, Theresa, A.  uhttp://www.bioone.org/doi/10.1645/17-130