Rapid Microsatellite Isolation from a Butterfly by De Novo Transcriptome Sequencing: Performance and a Comparison with AFLP-Derived Distances

Alexander S Mikheyev,Tanya Vo,Camille Parmesan,Brian Wee,Michael C Singer,Bengt Hansson

doi:10.1371/journal.pone.0011212

Abstract

BackgroundThe isolation of microsatellite markers remains laborious and expensive. For some taxa, such as Lepidoptera, development of microsatellite markers has been particularly difficult, as many markers appear to be located in repetitive DNA and have nearly identical flanking regions. We attempted to circumvent this problem by bioinformatic mining of microsatellite sequences from a de novo-sequenced transcriptome of a butterfly (Euphydryas editha).Principal FindingsBy searching the assembled sequence data for perfect microsatellite repeats we found 10 polymorphic loci. Although, like many expressed sequence tag-derived microsatellites, our markers show strong deviations from Hardy-Weinberg equilibrium in many populations, and, in some cases, a high incidence of null alleles, we show that they nonetheless provide measures of population differentiation consistent with those obtained by amplified fragment length polymorphism analysis. Estimates of pairwise population differentiation between 23 populations were concordant between microsatellite-derived data and AFLP analysis of the same samples (r = 0.71, p<0.00001, 425 individuals from 23 populations).Significance De novo transcriptional sequencing appears to be a rapid and cost-effective tool for developing microsatellite markers for difficult genomes.

Highlights

Many types of genetic analysis take advantage of microsatellite markers, which are highly polymorphic loci of simple sequence repeats located through the genome
Following the initial screening performed of eight individuals, we developed four multiplex PCR cocktails containing a total 10 polymorphic loci for large-scale genotyping (Table S1)
Microsatellite isolation from lepidopteran genomes has been difficult, possibly because microsatellite loci appear to be rare, and may have very similar flanking regions [6], which makes the design of primers problematic

Summary

Introduction

Many types of genetic analysis take advantage of microsatellite markers, which are highly polymorphic loci of simple sequence repeats located through the genome. Given the broad-scale utility of these markers, a large number of approaches have been developed for their isolation from genomic DNA [3] These approaches typically involve some form of microsatellite enrichment, followed by time consuming and costly brute force sequencing. For reasons not fully understood, isolation of microsatellites from Lepidopteran genomes is extremely difficult [4,5,6]. This problem is not confined to Lepidoptera, affecting bivalve mollusks [7], mosquitoes [8], mites [9], ticks [8], nematodes [10,11] and birds [12,13]. We attempted to circumvent this problem by bioinformatic mining of microsatellite sequences from a de novo-sequenced transcriptome of a butterfly (Euphydryas editha)

Methods

Results

Conclusion