Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays.
Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays.
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DOI：
10.1093/hmg/ddac112
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发表时间：
2022-09-10
影响因子：
3.5
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中科院分区：
文献类型：
--
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到目前为止，大多数表观遗传学流行病学都利用微阵列来确定基因组中DNA甲基化变异与环境暴露或疾病相关的位置。然而，这些基因在人类基因组中只有不到3%的DNA甲基化位点，可能会遗漏受影响的基因座，并阻止发现被破坏的生物途径。第三代测序技术，包括纳米孔测序，不仅通过提供真正的全基因组覆盖，而且通过直接从天然DNA分析表观遗传修饰，有可能彻底改变表观遗传数据的生成。在这里，我们通过与使用现有最全面的微阵列，Illumina EPIC阵列进行量化的DNA甲基化进行比较，来评估使用纳米孔测序进行流行病学的可行性。我们实施了CRISPR-Cas9靶向测序方法与纳米孔测序相结合，以分析三个基因组区域的DNA甲基化，试图重新发现现有技术显示在吸烟者中存在差异甲基化的基因组位置。使用纳米孔测序读数，DNA甲基化在1779cpgs的三个区域被量化，与EPIC阵列相比，提供了更好的DNA甲基化模式的分辨率。不同平台之间DNA甲基化水平的估计相关性很高。此外，我们确定了12个Cpg，其中低甲基化与吸烟状态显著相关，其中10个在AHRR基因内。总之，纳米孔测序是识别基因组座位的有效选择，其中dNaM的巨大差异与表型相关，并有可能促进我们对差异甲基化在复杂疾病病因学中所起作用的理解。
Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionize the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the etiology of complex disease.
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