Department of Biology, Stanford University, 371 Serra Mall, Stanford, CA, 94305, USA; Rocky Mountain Biological Laboratory, Crested Butte, CO, 81224, USA.
Mol Ecol. 2014 Jan;23(1):136-50. doi: 10.1111/mec.12591. Epub 2013 Dec 5.
The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.
对自然种群的分子数据进行分析，使研究人员能够回答以前难以解决的各种生态问题。特别是，生态学家通常对种群的人口历史感兴趣，而这些信息很少从历史记录中获得。已经开发出从基因组数据推断人口统计参数的方法，但对于推断出的参数与真实种群历史的比较，以及这些参数如何取决于实验设计的各个方面，人们的理解还很有限。在这里，我们提出并评估了一种使用 RNA 测序进行 SNP 发现的方法，以及使用程序δaδi进行人口推断的方法，该程序使用等位基因频率谱的扩散逼近来拟合人口统计模型。我们在CheckerSpot 蝴蝶 Euphydryas gillettii 的一个种群中测试了这些方法。这个种群于 1977 年被有意引入科罗拉多州的哥特式，经历了极端波动，包括据几乎每年的实地调查记录，其种群数量曾减少到不到 25 个成年人。我们对来自科罗拉多州的 8 个人和怀俄明州的一个本地种群的 8 个人进行 RNA 测序，为这个系统生成了第一个基因组资源。虽然人口推断通常用于研究古代人口，但我们的研究表明，我们这种廉价的、一站式的标记发现和基因分型方法提供了足够的数据，可以准确推断最近瓶颈的时间。这种人口状况与许多具有保护意义的物种有关，而这些物种中很少有测序的基因组。我们的结果对样本量或基因组标记数量的变化非常不敏感，这对于将这种方法应用于其他非模型系统具有重要意义。
