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Microsatellites for the marsh fritillary butterfly: de novo transcriptome sequencing, and a comparison with amplified
Melanie R Smee1, Yannick Pauchet, Paul Wilkinson
1Department of Biology, University of York, York, United Kingdom. melaniesmee@gmail.com
Background:
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, Euphydryas editha, we developed novel microsatellite markers for the vulnerable marsh fritillary butterfly, E. aurinia. 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: in silico mining of a de novo assembled transcriptome sequence, and genotyping the microsatellites found there using an economic method of fluorescently labelling primers.
Principal Findings:
In total, we screened nine polymorphic microsatellite markers, two of which were previously published, and seven that were isolated de novo. 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).
Significance:
Rapid development of microsatellite markers for difficult taxa such as Lepidoptera, and concordant results with other putatively neutral molecular markers, demonstrate the potential of de novo transcriptional sequencing for future studies of population structure and gene flow that are desperately needed for declining species across fragmented landscapes.
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