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.     

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.     

Systematic assessment of reduced representation bisulfite sequencing to human blood samples: A promising method for large-sample-scale epigenomic studies

Complementary to the time- and cost-intensive direct bisulfite sequencing, we applied reduced representation bisulfite sequencing (RRBS) to the human peripheral blood mononuclear cells (PBMC) from YH, the Asian individual whose genome and epigenome has been deciphered in the YH project and systematically assessed the genomic coverage, coverage depth and reproducibility of this technology as well as the concordance of DNA methylation levels measured by RRBS and direct bisulfite sequencing for the detected CpG sites. Our result suggests that RRBS can cover more than half of CpG islands and promoter regions with a good coverage depth and the proportion of the CpG sites covered by the biological replicates reaches 80-90%, indicating good reproducibility. Given a smaller data quantity, RRBS enjoys much better coverage depth than direct bisulfite sequencing and the concordance of DNA methylation levels between the two methods is high. It can be concluded that RRBS is a time and cost-effective sequencing method for unbiased DNA methylation profiling of CpG islands and promoter regions in a genome-wide scale and it is the method of choice to assay certain genomic regions for multiple samples in a rapid way.     

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.     

Mapping the zebrafish brain methylome using reduced representation bisulfite sequencing

Reduced representation bisulfite sequencing (RRBS) has been used to profile DNA methylation patterns in mammalian genomes such as human, mouse and rat. The methylome of the zebrafish, an important animal model, has not yet been characterized at base-pair resolution using RRBS. Therefore, we evaluated the technique of RRBS in this model organism by generating four single-nucleotide resolution DNA methylomes of adult zebrafish brain. We performed several simulations to show the distribution of fragments and enrichment of CpGs in different in silico reduced representation genomes of zebrafish. Four RRBS brain libraries generated 98 million sequenced reads and had higher frequencies of multiple mapping than equivalent human RRBS libraries. The zebrafish methylome indicates there is higher global DNA methylation in the zebrafish genome compared with its equivalent human methylome. This observation was confirmed by RRBS of zebrafish liver. High coverage CpG dinucleotides are enriched in CpG island shores more than in the CpG island core. We found that 45% of the mapped CpGs reside in gene bodies, and 7% in gene promoters. This analysis provides a roadmap for generating reproducible base-pair level methylomes for zebrafish using RRBS and our results provide the first evidence that RRBS is a suitable technique for global methylation analysis in zebrafish.     

Q-RRBS: a quantitative reduced representation bisulfite sequencing method for single-cell methylome analyses

Reduced representation bisulfite sequencing (RRBS) is a powerful method of DNA methylome profiling that can be applied to single cells. However, no previous report has described how PCR-based duplication-induced artifacts affect the accuracy of this method when measuring DNA methylation levels. For quantifying the effects of duplication-induced artifacts on methylome profiling when using ultra-trace amounts of starting material, we developed a novel method, namely quantitative RRBS (Q-RRBS), in which PCR-induced duplication is excluded through the use of unique molecular identifiers (UMIs). By performing Q-RRBS on varying amounts of starting material, we determined that duplication-induced artifacts were more severe when small quantities of the starting material were used. However, through using the UMIs, we successfully eliminated these artifacts. In addition, Q-RRBS could accurately detect allele-specific methylation in absence of allele-specific genetic variants. Our results demonstrate that Q-RRBS is an optimal strategy for DNA methylation profiling of single cells or samples containing ultra-trace amounts of cells.     

Reduced representation bisulfite sequencing design for assessing the methylation of human CpG islands in large samples

The reduced representation bisulfite sequencing (RRBS) method has been developed for the high-throughput analysis of DNA methylation based on the sequencing of genomic libraries treated with sodium bisulfite by next-generation approaches. In contrast to whole-genome sequencing, the RRBS approach elaborates specific endonucleases to prepare libraries in order to produce pools of CpG-rich DNA fragments. The original RRBS technology based on the use of the MspI libraries allows one to increase the relative number of CpG islands in the pools of genomic fragments compared to whole-genome bisulfite sequencing. Nevertheless, this technology is rarely used due to the high cost compared with bisulfite methylation analysis with hybridization microarrays and significant residual amount of data represented by the sequences of genomic repeats that complicates the alignment and is not of particular interest for developing DNA methylation markers, which is often the main goal of biomedical research. We have developed an algorithm for estimating the likelihood that recognition sites of restriction endonucleases will be represented in CpG islands and present a method of reducing the effective size of the RRBS library without a significant loss of the CpG islands based on the use of the XmaI endonuclease for library preparation. In silico analysis demonstrates that the optimum range of the XmaI-RRBS fragment lengths is 110–200 base pairs. The sequencing of this library allows one to assess the methylation status of over 125000 CpG dinucleotides, of which over 90000 belong to CpG islands.

     

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 polymerase engineered for bisulfite sequencing

Bisulfite sequencing is a key methodology in epigenetics. However, the standard workflow of bisulfite sequencing involves heat and strongly basic conditions to convert the intermediary product 5,6-dihydrouridine-6-sulfonate (dhU6S) (generated by reaction of bisulfite with deoxycytidine (dC)) to uracil (dU). These harsh conditions generally lead to sample loss and DNA damage while milder conditions may result in incomplete conversion of intermediates to uracil. Both can lead to poor recovery of bisulfite-treated DNA by the polymerase chain reaction (PCR) as either damaged DNA and/or intermediates of bisulfite treatment are poor substrate for standard DNA polymerases. Here we describe an engineered DNA polymerase (5D4) with an enhanced ability to replicate and PCR amplify bisulfite-treated DNA due to an ability to bypass both DNA lesions and bisulfite intermediates, allowing significantly milder conversion conditions and increased sensitivity in the PCR amplification of bisulfite-treated DNA. Incorporation of the 5D4 DNA polymerase into the bisulfite sequencing workflow thus promises significant sensitivity and efficiency gains.     

Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM

Epigenetic changes, such as aberrant DNA methylation, contribute to cancer clonal expansion and disease progression. However, identifying subpopulation-level changes in a heterogeneous sample remains challenging. Thus, we have developed a computational approach, DXM, to deconvolve the methylation profiles of major allelic subpopulations from the bisulfite sequencing data of a heterogeneous sample. DXM does not require prior knowledge of the number of subpopulations or types of cells to expect. We benchmark DXM’s performance and demonstrate improvement over existing methods. We further experimentally validate DXM predicted allelic subpopulation-methylation profiles in four Diffuse Large B-Cell Lymphomas (DLBCLs). Lastly, as proof-of-concept, we apply DXM to a cohort of 31 DLBCLs and relate allelic subpopulation methylation profiles to relapse. We thus demonstrate that DXM can robustly find allelic subpopulation methylation profiles that may contribute to disease progression using bisulfite sequencing data of any heterogeneous sample.     

Baculovirus-encoded protein expression for epigenomic profiling in Drosophila cells

The expression and genome-wide mapping of epitope-tagged DNA- and chromatin-binding proteins in cultured cells has become a powerful strategy for epigenome characterization, especially in Drosophila, where cell lines derived from numerous tissues are now available. However this strategy relies on establishing transfected cell lines, which is time-consuming and introduces variability. Here we show that baculovirus-encoded proteins can be efficiently produced following infection of Drosophila cell lines of different types. Using chromatin affinity purification, we show that epitope-tagged proteins produced in baculovirus-infected cells provide genome-wide profiles of the histone variant H2Av that are comparable to those produced by plasmid-transfected cells. The ability to express multiple epitope-tagged proteins for epigenome analysis from a single culture, and to do this in a variety of Drosophila cell lines, significantly extends the range of epigenome analysis.     

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.     

Hybrid selection for sequencing pathogen genomes from clinical samples

We have adapted a solution hybrid selection protocol to enrich pathogen DNA in clinical samples dominated by human genetic material. Using mock mixtures of human and Plasmodium falciparum malaria parasite DNA as well as clinical samples from infected patients, we demonstrate an average of approximately 40-fold enrichment of parasite DNA after hybrid selection. This approach will enable efficient genome sequencing of pathogens from clinical samples, as well as sequencing of endosymbiotic organisms such as Wolbachia that live inside diverse metazoan phyla.     

Identification and resolution of artifacts in bisulfite sequencing

Bisulfite sequencing has become the most widely used application to detect 5-methylcytosine (5-MeC) in DNA, and provides a reliable way of detecting any methylated cytosine at single-molecule resolution in any sequence context. The process of bisulfite treatment exploits the different sensitivity of cytosine and 5-MeC to deamination by bisulfite under acidic conditions, in which cytosine undergoes conversion to uracil while 5-MeC remains unreactive. In this article, we address the more commonly encountered experimental artifacts associated with bisulfite sequencing, and provide methods for the detection and elimination of these artifacts. In particular, we focus on conditions that inhibit complete bisulfite-mediated conversion of cytosines in a target sequence, and demonstrate the necessity of complete protein removal from DNA samples prior to bisulfite treatment. We also include a brief summary of the experimental protocol for bisulfite treatment and tips for designing polymerase chain reaction (PCR) primers to amplify from bisulfite-treated DNA.     

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.     

Spatially resolved epigenomic profiling of single cells in complex tissues

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