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Abstract：
Comprehensive genome-wide DNA methylation profiling is critical to gain insights into epigenetic reprogramming during development and disease processes. Among the different genome-wide DNA methylation technologies, whole genome bisulphite sequencing (WGBS) is considered the gold standard for assaying genome-wide DNA methylation at single base resolution. However, the high sequencing cost to achieve the optimal depth of coverage limits its application in both basic and clinical research. To achieve 15× coverage of the human methylome, using WGBS, requires approximately three lanes of 100-bp-paired-end Illumina HiSeq 2500 sequencing. It is important, therefore, for advances in sequencing technologies to be developed to enable cost-effective high-coverage sequencing.
In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16-20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r > 0.9×).
Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.
In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16-20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r > 0.9×).
Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.
摘要：
全面的全基因组DNA甲基化分析对于在发育和疾病过程中获得表观遗传重编程的见解至关重要。在不同的全基因组DNA甲基化技术中，全基因组亚硫酸氢盐测序(WGBS)被认为是以单碱基分辨率测定全基因组DNA甲基化的金标准.然而,实现最佳覆盖深度的高测序成本限制了其在基础和临床研究中的应用。为了实现人类甲基化的15倍覆盖率，使用WGBS，需要大约三个100bp配对末端IlluminaHiSeq2500测序泳道。这很重要,因此,促进测序技术的进步，以实现具有成本效益的高覆盖率测序。
在这项研究中,我们提供优化的WGBS方法，从文库制备到测序和数据处理，为了使HiSeqXTen的每个单通道的全基因组覆盖率达到16-20倍，HCS3.3.76.为了处理和分析数据，我们开发了一个WGBS管道(MET10X)，它速度快，可以调用SNP。我们对来自福尔马林固定的石蜡包埋组织的高质量完整DNA和降解DNA进行了WGBS。首先,我们在HiSeq2500平台上比较了不同的文库制备方法，以确定在HiSeqXTen上测序的最佳方法。第二,我们优化了PhiX和基因组尖峰，以在HiSeqXTen上实现更高质量和更高的WGBS数据覆盖率。第三，我们在HiSeqXTen的单道中对同一DNA样本进行了整合全基因组测序(WGS)和WGBS,以提高数据输出.最后,我们比较了HiSeq2500和HiSeqXTen的甲基化数据，发现高度一致性(Pearsonr>0.9×)。
我们一起提供一个系统的，在HiSeqXTen上执行和分析WGBS的有效和完整的方法。我们的协议允许在HiSeqXTen平台上以合理的处理时间和成本进行大规模的WGBS研究。
在这项研究中,我们提供优化的WGBS方法，从文库制备到测序和数据处理，为了使HiSeqXTen的每个单通道的全基因组覆盖率达到16-20倍，HCS3.3.76.为了处理和分析数据，我们开发了一个WGBS管道(MET10X)，它速度快，可以调用SNP。我们对来自福尔马林固定的石蜡包埋组织的高质量完整DNA和降解DNA进行了WGBS。首先,我们在HiSeq2500平台上比较了不同的文库制备方法，以确定在HiSeqXTen上测序的最佳方法。第二,我们优化了PhiX和基因组尖峰，以在HiSeqXTen上实现更高质量和更高的WGBS数据覆盖率。第三，我们在HiSeqXTen的单道中对同一DNA样本进行了整合全基因组测序(WGS)和WGBS,以提高数据输出.最后,我们比较了HiSeq2500和HiSeqXTen的甲基化数据，发现高度一致性(Pearsonr>0.9×)。
我们一起提供一个系统的，在HiSeqXTen上执行和分析WGBS的有效和完整的方法。我们的协议允许在HiSeqXTen平台上以合理的处理时间和成本进行大规模的WGBS研究。
