Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis

We describe a large-scale random approach termed reduced representation bisulfite sequencing (RRBS) for analyzing and comparing genomic methylation patterns. BglII restriction fragments were size-selected to 500–600 bp, equipped with adapters, treated with bisulfite, PCR amplified, cloned and sequenced. We constructed RRBS libraries from murine ES cells and from ES cells lacking DNA methyltransferases Dnmt3a and 3b and with knocked-down (kd) levels of Dnmt1 (Dnmt[1^kd,3a^−/−,3b^−/−]). Sequencing of 960 RRBS clones from Dnmt[1^kd,3a^−/−,3b^−/−] cells generated 343 kb of non-redundant bisulfite sequence covering 66212 cytosines in the genome. All but 38 cytosines had been converted to uracil indicating a conversion rate of >99.9%. Of the remaining cytosines 35 were found in CpG and 3 in CpT dinucleotides. Non-CpG methylation was >250-fold reduced compared with wild-type ES cells, consistent with a role for Dnmt3a and/or Dnmt3b in CpA and CpT methylation. Closer inspection revealed neither a consensus sequence around the methylated sites nor evidence for clustering of residual methylation in the genome. Our findings indicate random loss rather than specific maintenance of methylation in Dnmt[1^kd,3a^−/−,3b^−/−] cells. Near-complete bisulfite conversion and largely unbiased representation of RRBS libraries suggest that random shotgun bisulfite sequencing can be scaled to a genome-wide approach.     

A comparison of existing global DNA methylation assays to low-coverage whole-genome bisulfite sequencing for epidemiological studies

DNA methylation is an epigenetic mark at the interface of genetic and environmental factors relevant to human disease. Quantitative assessments of global DNA methylation levels have therefore become important tools in epidemiology research, particularly for understanding effects of environmental exposures in complex diseases. Among the available methods of quantitative DNA methylation measurements, bisulfite sequencing is considered the gold standard, but whole-genome bisulfite sequencing (WGBS) has previously been considered too costly for epidemiology studies with high sample numbers. Pyrosequencing of repetitive sequences within bisulfite-treated DNA has been routinely used as a surrogate for global DNA methylation, but a comparison of pyrosequencing to WGBS for accuracy and reproducibility of methylation levels has not been performed. This study compared the global methylation levels measured from uniquely mappable (non-repetitive) WGBS sequences to pyrosequencing assays of several repeat sequences and repeat assay-matched WGBS data and determined uniquely mappable WGBS data to be the most reproducible and accurate measurement of global DNA methylation levels. We determined sources of variation in repetitive pyrosequencing assays to be PCR amplification bias, PCR primer selection bias in methylation levels of targeted sequences, and inherent variability in methylation levels of repeat sequences. Low-coverage, uniquely mappable WGBS showed the strongest correlation between replicates of all assays. By using multiplexing by indexed bar codes, the cost of WGBS can be lowered significantly to improve the accuracy of global DNA methylation assessments for human studies.     

血浆游离DNA全基因组甲基化测序的实用稳定性评估

随着液体活检技术的发展,血浆游离DNA成为当前的研究热点之一。血浆游离DNA的全基因组甲基化测序被认为在癌症检测等医学应用拥有巨大潜力,但目前尚缺乏针对该实验流程的实用稳定性评估。文中利用两名志愿者在不同时间采样的血浆游离DNA,在不同实验平台分别进行DNA甲基化的重亚硫酸盐转化前建库(Pre-BS)、转化后建库(Post-BS)和常规DNA建库,获取多因素影响下的测序数据样本。在此基础上,建立了一套血浆游离DNA测序数据分析的质量控制参考流程,综合评估了血液采集提取、游离DNA建库测序过程的实用稳定性,为血浆游离DNA全基因组甲基化测序应用于临床液体活检提供实用性的基础参考。     

DNA methylation analysis by digital bisulfite genomic sequencing and digital MethyLight

Alterations in cytosine-5 DNA methylation are frequently observed in most types of human cancer. Although assays utilizing PCR amplification of bisulfite-converted DNA are widely employed to analyze these DNA methylation alterations, they are generally limited in throughput capacity, detection sensitivity, and or resolution. Digital PCR, in which a DNA sample is analyzed in distributive fashion over multiple reaction chambers, allows for enumeration of discrete template DNA molecules, as well as sequestration of non-specific primer annealing templates into negative chambers, thereby increasing the signal-to-noise ratio in positive chambers. Here, we have applied digital PCR technology to bisulfite-converted DNA for single-molecule high-resolution DNA methylation analysis and for increased sensitivity DNA methylation detection. We developed digital bisulfite genomic DNA sequencing to efficiently determine single-basepair DNA methylation patterns on single-molecule DNA templates without an interim cloning step. We also developed digital MethyLight, which surpasses traditional MethyLight in detection sensitivity and quantitative accuracy for low quantities of DNA. Using digital MethyLight, we identified single-molecule, cancer-specific DNA hypermethylation events in the CpG islands of RUNX3, CLDN5 and FOXE1 present in plasma samples from breast cancer patients.     

Differential methylation analysis for bisulfite sequencing using DSS

Bisulfite sequencing (BS-seq) technology measures DNA methylation at single nucleotide resolution. A key task in BS-seq data analysis is to identify differentially methylation (DM) under different conditions. Here we provide a tutorial for BS-seq DM analysis using Bioconductor package DSS. DSS uses a beta-binomial model to characterize the sequence counts from BS-seq, and implements rigorous statistical method for hypothesis testing. It provides flexible functionalities for a variety of DM analyses.     

Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling

DNA methylation is an important epigenetic modification involved in gene regulation, which can now be measured using whole-genome bisulfite sequencing. However, cost, complexity of the data, and lack of comprehensive analytical tools are major challenges that keep this technology from becoming widely applied. Here we present BSmooth, an alignment, quality control and analysis pipeline that provides accurate and precise results even with low coverage data, appropriately handling biological replicates. BSmooth is open source software, and can be downloaded from http://rafalab.jhsph.edu/bsmooth.     

BatMeth: improved mapper for bisulfite sequencing reads on DNA methylation

DNA methylation plays a crucial role in higher organisms. Coupling bisulfite treatment with next generation sequencing enables the interrogation of 5-methylcytosine sites in the genome. However, bisulfite conversion introduces mismatches between the reads and the reference genome, which makes mapping of Illumina and SOLiD reads slow and inaccurate. BatMeth is an algorithm that integrates novel Mismatch Counting, List Filtering, Mismatch Stage Filtering and Fast Mapping onto Two Indexes components to improve unique mapping rate, speed and precision. Experimental results show that BatMeth is faster and more accurate than existing tools. BatMeth is freely available at http://code.google.com/p/batmeth/.     

Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling

Sequencing-based approaches have led to new insights about DNA methylation. While many different techniques for genome-scale mapping of DNA methylation have been employed, throughput has been a key limitation for most. To further facilitate the mapping of DNA methylation, we describe a protocol for gel-free multiplexed reduced representation bisulfite sequencing (mRRBS) that reduces the workload dramatically and enables processing of 96 or more samples per week. mRRBS achieves similar CpG coverage to the original RRBS protocol, while the higher throughput and lower cost make it better suited for large-scale DNA methylation mapping studies, including cohorts of cancer samples.     

A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus β-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.     

DNA methylome analysis using short bisulfite sequencing data

Bisulfite conversion of genomic DNA combined with next-generation sequencing (BS-seq) is widely used to measure the methylation state of a whole genome, the methylome, at single-base resolution. However, analysis of BS-seq data still poses a considerable challenge. Here we summarize the challenges of BS-seq mapping as they apply to both base and color-space data. We also explore the effect of sequencing errors and contaminants on inferred methylation levels and recommend the most appropriate way to analyze this type of data.     

Single-molecule polymerase chain reaction reduces bias: application to DNA methylation analysis by bisulfite sequencing

The treatment of DNA with bisulfite, which converts C to U but leaves 5-methyl-C unchanged, forms the basis of many analytical techniques for DNA methylation analysis. Many techniques exist for measuring the methylation state of a single CpG but, for analysis of an entire region, cloning and sequencing remains the gold standard. However, biases in polymerase chain reaction (PCR) amplification and in cloning can skew the results. We hypothesized that single-molecule PCR (smPCR) amplification would eliminate the PCR amplification bias because competition between templates that amplify at different efficiencies no longer exists. The amplified products can be sequenced directly, thus eliminating cloning bias. We demonstrated this accurate and unbiased approach by analyzing a sample that was expected to contain a 50:50 ratio of methylated to unmethylated molecules: a region of the X-linked FMR1 gene from a human female cell line. We compared traditional cloning and sequencing to smPCR and sequencing. Sequencing smPCR products gave an expected methylated to unmethylated ratio of 48:52, whereas conventional cloning and sequencing gave a biased ratio of 72:28. Our results show that smPCR sequencing can eliminate both PCR and cloning bias and represents an attractive approach to bisulfite sequencing.     

Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling

Genome-wide mapping of 5-methylcytosine is of broad interest to many fields of biology and medicine. A variety of methods have been developed, and several have recently been advanced to genome-wide scale using arrays and next-generation sequencing approaches. We have previously reported reduced representation bisulfite sequencing (RRBS), a bisulfite-based protocol that enriches CG-rich parts of the genome, thereby reducing the amount of sequencing required while capturing the majority of promoters and other relevant genomic regions. The approach provides single-nucleotide resolution, is highly sensitive and provides quantitative DNA methylation measurements. This protocol should enable any standard molecular biology laboratory to generate RRBS libraries of high quality. Briefly, purified genomic DNA is digested by the methylation-insensitive restriction enzyme MspI to generate short fragments that contain CpG dinucleotides at the ends. After end-repair, A-tailing and ligation to methylated Illumina adapters, the CpG-rich DNA fragments (40-220 bp) are size selected, subjected to bisulfite conversion, PCR amplified and end sequenced on an Illumina Genome Analyzer. Note that alignment and analysis of RRBS sequencing reads are not covered in this protocol. The extremely low input requirements (10-300 ng), the applicability of the protocol to formalin-fixed and paraffin-embedded samples, and the technique's single-nucleotide resolution extends RRBS to a wide range of biological and clinical samples and research applications. The entire process of RRBS library construction takes ～9 d.     

Comparison of bisulfite sequencing PCR with pyrosequencing for measuring differences in DNA methylation

DNA methylation strongly affects chromatin structure and the regulation of gene expression. For many years, bisulfite sequencing PCR (BSP) has served as the “gold standard” for measuring DNA methylation. However, with the evolution of pyrosequencing as a tool to evaluate DNA methylation, the need arises to compare the relative efficiencies of the two techniques in measuring DNA methylation. We provide for the first time a direct assessment of BSP and pyrosequencing to detect and quantify hypomethylation, hypermethylation, and mixed methylation of the ABCB1 promoter in various drug-sensitive and drug-resistant MCF-7 breast cancer cell lines through head-to-head experimentation. Our findings indicate that although both methods can reliably detect increased, decreased, and mixed methylation of DNA, BSP appears to be more sensitive than pyrosequencing at detecting strong hypermethylation of DNA. However, we also observed greater variability in the methylation of CpG sites by BSP, possibly due to the additional bacterial cloning step required by BSP over pyrosequencing. BSP and pyrosequencing equally detected hypomethylation and mixed methylation of DNA. The ability of pyrosequencing to reliably detect differences in DNA methylation across cell populations without requiring the cloning of bisulfite-treated DNA into bacterial expression vectors was seen as a major advantage of this technique.     

Ultra-deep whole genome bisulfite sequencing reveals a single methylation hotspot in human brain mitochondrial DNA

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Comparison and quantitative verification of mapping algorithms for whole-genome bisulfite sequencing

Coupling bisulfite conversion with next-generation sequencing (Bisulfite-seq) enables genome-wide measurement of DNA methylation, but poses unique challenges for mapping. However, despite a proliferation of Bisulfite-seq mapping tools, no systematic comparison of their genomic coverage and quantitative accuracy has been reported. We sequenced bisulfite-converted DNA from two tissues from each of two healthy human adults and systematically compared five widely used Bisulfite-seq mapping algorithms: Bismark, BSMAP, Pash, BatMeth and BS Seeker. We evaluated their computational speed and genomic coverage and verified their percentage methylation estimates. With the exception of BatMeth, all mappers covered >70% of CpG sites genome-wide and yielded highly concordant estimates of percentage methylation (r² ≥ 0.95). Fourfold variation in mapping time was found between BSMAP (fastest) and Pash (slowest). In each library, 8–12% of genomic regions covered by Bismark and Pash were not covered by BSMAP. An experiment using simulated reads confirmed that Pash has an exceptional ability to uniquely map reads in genomic regions of structural variation. Independent verification by bisulfite pyrosequencing generally confirmed the percentage methylation estimates by the mappers. Of these algorithms, Bismark provides an attractive combination of processing speed, genomic coverage and quantitative accuracy, whereas Pash offers considerably higher genomic coverage.     

The landscape of DNA methylation in hepatocellular carcinoma

Better understanding of the relationship between changes in the overall methylation status of hepatocellular carcinoma (HCC) and disease progression will help us find good strategies for the early detection and treatment of HCC patients. The purpose of the study was to study the relations between the methylation status changes in HCC patients and progression of the disease to enable early detection and treatment of HCC patients. First, the DNA methylation data of 50 HCC samples and the surrounding normal samples were extracted and the change pattern of methylation status in the DNA promoter region of HCC samples against that of normal samples was studied. Then, some DNA methylation genes that could accurately identify cancer and cancer-adjacent tissues were identified using the k-top scoring pair method. Also, a prognostic signature that could predict the survival of HCC patients was constructed based on the overall survival time and death information of the early HCC patients. Finally, the obtained prognostic signature was verified. In conclusion, this study described the changes in the methylation spectrum during the development of HCC and identified genes associated with HCC progression and prognosis, which may offer new opportunities for the diagnosis and treatment of HCC.     

DNA甲基化分析中重亚硫酸盐处理DNA转化效率的评估方法

为建立一种评估重亚硫酸盐处理DNA样本后胞嘧啶转化效率的有效方法,以两组不同的TaqMan qPCR检测梯度稀释的重亚硫酸盐处理和未处理的DNA标准品,建立转化与未转化的DNA Ct值以及对应的DNA拷贝数的标准曲线。使用相同的探针定量检测重亚硫酸盐处理后的DNA样本评估转化效率。结果显示该方法应用两组探针,根据相应的标准曲线,精确评估样本经重亚硫酸盐处理的转化效率。使用已知转化和未转化拷贝数的混合DNA作为模板,证实了该方法的可靠性。同时也对不同重亚硫酸盐试剂盒处理DNA的转化效率进行了评估,结果显示,该方法能够有效地评估DNA样品重亚硫酸盐的转化效率,为DNA甲基化准确分析提供了可靠快捷的方法。