1. Epigenetics is increasingly recognized as an important molecular mechanism underlying phenotypic variation. To study DNA methylation in ecological and evolutionary contexts, epiRADseq is a cost‐effective next‐generation sequencing (NGS) technique based on reduced representation sequencing of genomic regions surrounding non‐/methylated sites. EpiRADseq for genome‐wide methylation abundance and ddRADseq for genome‐wide single‐nucleotide polymorphism (SNP) genotyping follow very similar library and sequencing protocols, but to date these two types of dataset have been handled separately. Here we test the performance of using epiRADseq data to generate SNPs for population genomic analyses.
2. We tested the robustness of using epiRADseq data for population genomics with two independent datasets: a newly generated single‐end dataset for the European whitefish Coregonus lavaretus, and a re‐analysis of publicly available, previously published paired‐end data on corals. Using standard bioinformatic pipelines with a reference genome and without (i.e. de novo catalogue loci), we compared the number of SNPs retained, population genetic summary statistics and population genetic structure between data drawn from ddRADseq and epiRADseq library preparations.
3. We found that SNPs drawn from epiRADseq are similar in number to those drawn from ddRADseq, with 55%–83% of SNPs being identified by both methods. Genotyping error rate was <5% in both approaches. EpiRADseq‐specific allele dropout was low (~1%). For summary statistics, such as heterozygosity and nucleotide diversity, there is a strong correlation between methods (Spearman's rho > 0.88). Furthermore, identical patterns of population genetic structure were recovered using SNPs from epiRADseq and ddRADseq approaches.
4. We show that SNPs obtained from epiRADseq are highly similar to those from ddRADseq and are equivalent for estimating genetic diversity and population structure. This finding is particularly relevant to researchers interested in genetics and epigenetics on the same individuals because using a single epigenomic approach to generate two datasets greatly reduces the time and financial costs compared to using these techniques separately. It also efficiently enables correction of epigenetic estimates with population genetic data. Many studies will benefit from a combinatorial approach with genetic and epigenetic markers and this demonstrates a single, efficient method to do so.

中文翻译：

---

表观遗传RAD的群体基因组SNP：通过单一的已建立的下一代测序方法获得遗传和表观遗传数据

1. 表观遗传学已被越来越多地视为表型变异的重要分子机制。为了研究生态和进化环境中的DNA甲基化，epiRADseq是一种经济高效的下一代测序（NGS）技术，它基于非/甲基化位点周围的基因组区域的简化表示测序。用于全基因组范围内的甲基化丰度的EpiRADseq和用于全基因组范围内的单核苷酸多态性（SNP）基因分型的ddRADseq遵循非常相似的文库和测序方案，但迄今为止，这两种类型的数据集已分别处理。在这里，我们测试了使用epiRADseq数据生成SNP进行人群基因组分析的性能。
2. 我们通过两个独立的数据集测试了使用epiRADseq数据进行种群基因组学分析的稳健性：一个是欧洲白鲑Coregonus lavaretus的新生成的单端数据集，另一个是对先前可公开获得的关于珊瑚的双端数据的重新分析。使用具有参考基因组且没有参考基因组的标准生物信息流水线，我们比较了从ddRADseq和epiRADseq文库制备数据中保留的SNP数量，群体遗传总结统计数据和群体遗传结构。
3. 我们发现，从epiRADseq提取的SNP的数量与从ddRADseq提取的SNP的数量相似，两种方法均可鉴定出55％–83％的SNP。两种方法的基因分型错误率均<5％。EpiRADseq特异的等位基因缺失很低（〜1％）。对于摘要统计，例如杂合性和核苷酸多样性，方法之间存在很强的相关性（Spearman的rho> 0.88）。此外，使用来自epiRADseq和ddRADseq方法的SNP恢复了相同的种群遗传结构模式。
4. 我们表明，从epiRADseq获得的SNP与从ddRADseq获得的SNP高度相似，并且在估计遗传多样性和种群结构方面是等效的。这一发现与对同一个体的遗传和表观遗传学感兴趣的研究人员特别相关，因为与单独使用这些技术相比，使用单一表观基因组学方法生成两个数据集可大大减少时间和财务成本。它还可以有效地利用群体遗传数据校正表观遗传估计。许多研究将受益于遗传和表观遗传标记的组合方法，这证明了一种有效的方法。