Microsatellites for the Marsh Fritillary Butterfly: <i>De Novo</i> Transcriptome Sequencing, and a Comparison with Amplified Fragment Length Polymorphism (AFLP) Markers

<div><p>Background</p><p>Until recently the isolation of microsatellite markers from Lepidoptera has proved troublesome, expensive and time-consuming. Following on from a previous study of Edith's checkerspot butterfly, <i>Euphydryas editha</i>, we developed novel microsatellite markers for the vulnerable marsh fritillary butterfly, <i>E. aurinia</i>. Our goal was to optimize the process in order to reduce both time and cost relative to prevailing techniques. This was accomplished by using a combination of previously developed techniques: <i>in silico</i> mining of a <i>de novo</i> assembled transcriptome sequence, and genotyping the microsatellites found there using an economic method of fluorescently labelling primers.</p><p>Principal Findings</p><p>In total, we screened nine polymorphic microsatellite markers, two of which were previously published, and seven that were isolated <i>de novo</i>. These markers were able to amplify across geographically isolated populations throughout Continental Europe and the UK. Significant deviations from Hardy-Weinberg equilibrium were evident in some populations, most likely due to the presence of null alleles. However, we used an F_st outlier approach to show that these markers are likely selectively neutral. Furthermore, using a set of 128 individuals from 11 populations, we demonstrate consistency in population differentiation estimates with previously developed amplified fragment length polymorphism (AFLP) markers (r = 0.68, p<0.001).</p><p>Significance</p><p>Rapid development of microsatellite markers for difficult taxa such as Lepidoptera, and concordant results with other putatively neutral molecular markers, demonstrate the potential of <i>de novo</i> transcriptional sequencing for future studies of population structure and gene flow that are desperately needed for declining species across fragmented landscapes.</p>