Data from: Rapid microsatellite isolation from a butterfly by de novo transcriptome sequencing: performance and a comparison with AFLP-derived distances

BACKGROUND: The 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 FINDINGS: By 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.

研究背景：微卫星标记（microsatellite markers）的分离工作往往费力且成本高昂。对于鳞翅目（Lepidoptera）等类群而言，微卫星标记的开发难度尤甚，因为多数标记似乎位于重复DNA区域中，且侧翼序列近乎完全一致。本研究尝试通过生物信息学手段，从某蝴蝶（Euphydryas editha）的从头测序转录组（de novo-sequenced transcriptome）中挖掘微卫星序列，以此规避上述难题。主要研究结果：通过对组装完成的序列数据进行完美微卫星重复序列检索，本研究共筛选得到10个多态性位点。尽管与多数表达序列标签（expressed sequence tag, EST）来源的微卫星标记类似，本研究开发的标记在诸多种群中均显著偏离哈迪-温伯格平衡（Hardy-Weinberg equilibrium），且部分位点存在较高的无效等位基因（null alleles）发生率，但本研究证实，这些标记仍可用于种群分化程度的评估，其结果与扩增片段长度多态性（amplified fragment length polymorphism, AFLP）分析所得结果一致。对23个种群的成对种群分化程度进行估算后发现，微卫星数据与同一批样本的AFLP分析结果具有高度一致性（相关系数r=0.71, p<0.00001，样本涵盖23个种群共425个个体）。研究意义：从头转录组测序技术对于难以开发微卫星标记的基因组而言，是一种快速且经济高效的标记开发工具。