In-solution hybrid capture of bisulfite-converted DNA for targeted bisulfite sequencing of 174 ADME genes

DNA methylation is one of the most important epigenetic alterations involved in the control of gene expression. Bisulfite sequencing of genomic DNA is currently the only method to study DNA methylation patterns at single-nucleotide resolution. Hence, next-generation sequencing of bisulfite-converted DNA is the method of choice to investigate DNA methylation profiles at the genome-wide scale. Nevertheless, whole genome sequencing for analysis of human methylomes is expensive, and a method for targeted gene analysis would provide a good alternative in many cases where the primary interest is restricted to a set of genes.Here, we report the successful use of a custom Agilent SureSelect Target Enrichment system for the hybrid capture of bisulfite-converted DNA. We prepared bisulfite-converted next-generation sequencing libraries, which are enriched for the coding and regulatory regions of 174 ADME genes (i.e. genes involved in the metabolism and distribution of drugs). Sequencing of these libraries on Illumina’s HiSeq2000 revealed that the method allows a reliable quantification of methylation levels of CpG sites in the selected genes, and validation of the method using pyrosequencing and the Illumina 450K methylation BeadChips revealed good concordance.     

A Bayesian Framework to Identify Methylcytosines from High-Throughput Bisulfite Sequencing Data

High-throughput bisulfite sequencing technologies have provided a comprehensive and well-fitted way to investigate DNA methylation at single-base resolution. However, there are substantial bioinformatic challenges to distinguish precisely methylcytosines from unconverted cytosines based on bisulfite sequencing data. The challenges arise, at least in part, from cell heterozygosis caused by multicellular sequencing and the still limited number of statistical methods that are available for methylcytosine calling based on bisulfite sequencing data. Here, we present an algorithm, termed Bycom, a new Bayesian model that can perform methylcytosine calling with high accuracy. Bycom considers cell heterozygosis along with sequencing errors and bisulfite conversion efficiency to improve calling accuracy. Bycom performance was compared with the performance of Lister, the method most widely used to identify methylcytosines from bisulfite sequencing data. The results showed that the performance of Bycom was better than that of Lister for data with high methylation levels. Bycom also showed higher sensitivity and specificity for low methylation level samples (<1%) than Lister. A validation experiment based on reduced representation bisulfite sequencing data suggested that Bycom had a false positive rate of about 4% while maintaining an accuracy of close to 94%. This study demonstrated that Bycom had a low false calling rate at any methylation level and accurate methylcytosine calling at high methylation levels. Bycom will contribute significantly to studies aimed at recalibrating the methylation level of genomic regions based on the presence of methylcytosines.     

Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications

SUMMARY: A combination of bisulfite treatment of DNA and high-throughput sequencing (BS-Seq) can capture a snapshot of a cell's epigenomic state by revealing its genome-wide cytosine methylation at single base resolution. Bismark is a flexible tool for the time-efficient analysis of BS-Seq data which performs both read mapping and methylation calling in a single convenient step. Its output discriminates between cytosines in CpG, CHG and CHH context and enables bench scientists to visualize and interpret their methylation data soon after the sequencing run is completed. Availability and implementation: Bismark is released under the GNU GPLv3+ licence. The source code is freely available from www.bioinformatics.bbsrc.ac.uk/projects/bismark/.     

Detection of Cytosine Methylation in Ancient DNA from Five Native American Populations Using Bisulfite Sequencing

While cytosine methylation has been widely studied in extant populations, relatively few studies have analyzed methylation in ancient DNA. Most existing studies of epigenetic marks in ancient DNA have inferred patterns of methylation in highly degraded samples using post-mortem damage to cytosines as a proxy for cytosine methylation levels. However, this approach limits the inference of methylation compared with direct bisulfite sequencing, the current gold standard for analyzing cytosine methylation at single nucleotide resolution. In this study, we used direct bisulfite sequencing to assess cytosine methylation in ancient DNA from the skeletal remains of 30 Native Americans ranging in age from approximately 230 to 4500 years before present. Unmethylated cytosines were converted to uracils by treatment with sodium bisulfite, bisulfite products of a CpG-rich retrotransposon were pyrosequenced, and C-to-T ratios were quantified for a single CpG position. We found that cytosine methylation is readily recoverable from most samples, given adequate preservation of endogenous nuclear DNA. In addition, our results indicate that the precision of cytosine methylation estimates is inversely correlated with aDNA preservation, such that samples of low DNA concentration show higher variability in measures of percent methylation than samples of high DNA concentration. In particular, samples in this study with a DNA concentration above 0.015 ng/μL generated the most consistent measures of cytosine methylation. This study presents evidence of cytosine methylation in a large collection of ancient human remains, and indicates that it is possible to analyze epigenetic patterns in ancient populations using direct bisulfite sequencing approaches.     

Comparison of whole‐genome (13X) and capture (87X) resequencing methods for SNP and genotype callings

The number of polymorphisms identified with next‐generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole‐genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down‐sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture‐related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.     

Evidence for non-CpG methylation in mammals

In mammals, the existence of cytosine methylation on non-CpG sequences is controversial. Here, we adapted a LuminoMetric-based Assay (LUMA) to determine global non-CpG methylation levels in rodent and human tissues. We observed that < 1% cytosines in non-CpG motifs were methylated in 3T3-L1 fibroblasts, whereas 7–13% cytosines in non-CpG motifs were methylated in mouse tissues or embryonic fibroblasts. Analysis of cytosine methylation in human, rat, and mouse tissues by bisulfite sequencing revealed non-CpG methylation levels up to 7.5% of all non-CpG cytosines. These levels dropped to 1.5% when a second round of PCR was performed prior to bisulfite sequencing, providing an explanation for the common underestimation of non-CpG methylation levels. Collectively, our results provide evidence that non-CpG methylation exists at substantial levels in mammals.     

Statistical quantification of methylation levels by next-generation sequencing

Background/Aims

Recently, next-generation sequencing-based technologies have enabled DNA methylation profiling at high resolution and low cost. Methyl-Seq and Reduced Representation Bisulfite Sequencing (RRBS) are two such technologies that interrogate methylation levels at CpG sites throughout the entire human genome. With rapid reduction of sequencing costs, these technologies will enable epigenotyping of large cohorts for phenotypic association studies. Existing quantification methods for sequencing-based methylation profiling are simplistic and do not deal with the noise due to the random sampling nature of sequencing and various experimental artifacts. Therefore, there is a need to investigate the statistical issues related to the quantification of methylation levels for these emerging technologies, with the goal of developing an accurate quantification method.

Methods

In this paper, we propose two methods for Methyl-Seq quantification. The first method, the Maximum Likelihood estimate, is both conceptually intuitive and computationally simple. However, this estimate is biased at extreme methylation levels and does not provide variance estimation. The second method, based on Bayesian hierarchical model, allows variance estimation of methylation levels, and provides a flexible framework to adjust technical bias in the sequencing process.

Results

We compare the previously proposed binary method, the Maximum Likelihood (ML) method, and the Bayesian method. In both simulation and real data analysis of Methyl-Seq data, the Bayesian method offers the most accurate quantification. The ML method is slightly less accurate than the Bayesian method. But both our proposed methods outperform the original binary method in Methyl-Seq. In addition, we applied these quantification methods to simulation data and show that, with sequencing depth above 40–300 (which varies with different tissue samples) per cleavage site, Methyl-Seq offers a comparable quantification consistency as microarrays.     

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine methylation patterns in cells. Reduced representation of whole genome bisulfite sequencing was developed to detect quantitative base pair resolution cytosine methylation patterns at GC-rich genomic loci. This is accomplished by combining the use of a restriction enzyme followed by bisulfite conversion. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) increases the biologically relevant genomic loci covered and has been used to profile cytosine methylation in DNA from human, mouse and other organisms. ERRBS initiates with restriction enzyme digestion of DNA to generate low molecular weight fragments for use in library preparation. These fragments are subjected to standard library construction for next generation sequencing. Bisulfite conversion of unmethylated cytosines prior to the final amplification step allows for quantitative base resolution of cytosine methylation levels in covered genomic loci. The protocol can be completed within four days. Despite low complexity in the first three bases sequenced, ERRBS libraries yield high quality data when using a designated sequencing control lane. Mapping and bioinformatics analysis is then performed and yields data that can be easily integrated with a variety of genome-wide platforms. ERRBS can utilize small input material quantities making it feasible to process human clinical samples and applicable in a range of research applications. The video produced demonstrates critical steps of the ERRBS protocol.     

Genome‐wide DNA methylation analysis using next‐generation sequencing to reveal candidate genes responsible for boar taint in pigs

Boar taint (BT) is an offensive flavor observed in non‐castrated male pigs that reduces the carcass price. Surgical castration effectively avoids the taint but is associated with animal welfare concerns. The functional annotation of farm animal genomes for understanding the biology of complex traits can be used in the selection of breeding animals to achieve favorable phenotypic outcomes. The characterization of pig epigenomes/methylation changes between animals with high and low BT and genome‐wide epigenetic markers that can predict BT are lacking. Reduced representation bisulfite sequencing of DNA methylation patterns based on next‐generation sequencing is an efficient technology to identify candidate epigenetic biomarkers associated with BT. Three different BT levels were analyzed using reduced representation bisulfite sequencing data to calculate the methylation levels of cytosine and guanine dinucleotide (CpG) sites. The co‐analysis of differentially methylated CpG sites identified by this study and differentially expressed genes identified by a previous study found 32 significant co‐located genes. The joint analysis of GO terms and pathways revealed that methylation and gene expression of seven candidate genes were associated with BT; in particular, FASN plays a key role in fatty acid biosynthesis, and PEMT might be involved in estrogen regulation and the development of BT. This study is the first to report the genome‐wide DNA methylation profiles of BT in pigs using next‐generation sequencing and summarize candidate genes associated with epigenetic markers of BT, which could contribute to the understanding of the functional biology of BT traits and selective breeding of pigs against BT based on epigenetic biomarkers.     

DNA methylation analysis of a male reproductive organ specific gene (MROS1) during pollen development.

Pollen grains of angiosperm plants represent a good model system for studies of chromatin structure and remodelling factors, but very little is known about the DNA methylation status of particular genes in pollen. In this study, we present an analysis of the DNA methylation patterns of the MROS1 gene, which is expressed in the late phases of pollen development in Silene latifolia (syn. Meladrium album). The genomic sequencing technique revealed similar DNA methylation patterns in leaves, binucleate pollen, and trinucleate pollen. Extremely high DNA methylation levels occurred in the CG dinucleotides of the upstream region (99%), whereas only a low level of CG methylation was observed in the transcribed sequence (7%). Low levels of methylation were also observed in asymmetric sequences (in both regions; 2% methylated). The results obtained in the MROS1 gene are discussed in consequence with the immunohistochemical data showing a hypermethylation of DNA in the vegetative nucleus.     

DNA Methylation Analysis of Chromosome 21 Gene Promoters at Single Base Pair and Single Allele Resolution

Differential DNA methylation is an essential epigenetic signal for gene regulation, development, and disease processes. We mapped DNA methylation patterns of 190 gene promoter regions on chromosome 21 using bisulfite conversion and subclone sequencing in five human cell types. A total of 28,626 subclones were sequenced at high accuracy using (long-read) Sanger sequencing resulting in the measurement of the DNA methylation state of 580427 CpG sites. Our results show that average DNA methylation levels are distributed bimodally with enrichment of highly methylated and unmethylated sequences, both for amplicons and individual subclones, which represent single alleles from individual cells. Within CpG-rich sequences, DNA methylation was found to be anti-correlated with CpG dinucleotide density and GC content, and methylated CpGs are more likely to be flanked by AT-rich sequences. We observed over-representation of CpG sites in distances of 9, 18, and 27 bps in highly methylated amplicons. However, DNA sequence alone is not sufficient to predict an amplicon's DNA methylation status, since 43% of all amplicons are differentially methylated between the cell types studied here. DNA methylation in promoter regions is strongly correlated with the absence of gene expression and low levels of activating epigenetic marks like H3K4 methylation and H3K9 and K14 acetylation. Utilizing the single base pair and single allele resolution of our data, we found that i) amplicons from different parts of a CpG island frequently differ in their DNA methylation level, ii) methylation levels of individual cells in one tissue are very similar, and iii) methylation patterns follow a relaxed site-specific distribution. Furthermore, iv) we identified three cases of allele-specific DNA methylation on chromosome 21. Our data shed new light on the nature of methylation patterns in human cells, the sequence dependence of DNA methylation, and its function as epigenetic signal in gene regulation. Further, we illustrate genotype–epigenotype interactions by showing novel examples of allele-specific methylation.     

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.     

Pulling out the 1%: Whole-Genome Capture for the Targeted Enrichment of Ancient DNA Sequencing Libraries

Most ancient specimens contain very low levels of endogenous DNA, precluding the shotgun sequencing of many interesting samples because of cost. Ancient DNA (aDNA) libraries often contain <1% endogenous DNA, with the majority of sequencing capacity taken up by environmental DNA. Here we present a capture-based method for enriching the endogenous component of aDNA sequencing libraries. By using biotinylated RNA baits transcribed from genomic DNA libraries, we are able to capture DNA fragments from across the human genome. We demonstrate this method on libraries created from four Iron Age and Bronze Age human teeth from Bulgaria, as well as bone samples from seven Peruvian mummies and a Bronze Age hair sample from Denmark. Prior to capture, shotgun sequencing of these libraries yielded an average of 1.2% of reads mapping to the human genome (including duplicates). After capture, this fraction increased substantially, with up to 59% of reads mapped to human and enrichment ranging from 6- to 159-fold. Furthermore, we maintained coverage of the majority of regions sequenced in the precapture library. Intersection with the 1000 Genomes Project reference panel yielded an average of 50,723 SNPs (range 3,062–147,243) for the postcapture libraries sequenced with 1 million reads, compared with 13,280 SNPs (range 217–73,266) for the precapture libraries, increasing resolution in population genetic analyses. Our whole-genome capture approach makes it less costly to sequence aDNA from specimens containing very low levels of endogenous DNA, enabling the analysis of larger numbers of samples.     

Systematic cross-validation of 454 sequencing and pyrosequencing for the exact quantification of DNA methylation patterns with single CpG resolution

Background  

New high-throughput sequencing technologies promise a very sensitive and high-resolution analysis of DNA methylation patterns in quantitative terms. However, a detailed and comprehensive comparison with existing validated DNA methylation analysis methods is not yet available. Therefore, a systematic cross-validation of 454 sequencing and conventional pyrosequencing, both of which offer exact quantification of methylation levels with a single CpG dinucleotide resolution, was performed.     

Development of a Novel Output Value for Quantitative Assessment in Methylated DNA Immunoprecipitation-CpG Island Microarray Analysis

In DNA methylation microarray analysis, quantitative assessment of intermediate methylation levels in samples with various global methylation levels is still difficult. Here, specifically for methylated DNA immunoprecipitation-CpG island (CGI) microarray analysis, we developed a new output value. The signal log ratio reflected the global methylation levels, but had only moderate linear correlation (r = 0.72) with the fraction of DNA molecules immunoprecipitated. By multiplying the signal log ratio using a coefficient obtained from the probability value that took account of signals in neighbouring probes, its linearity was markedly improved (r = 0.94). The new output value, Me value, reflected the global methylation level, had a strong correlation also with the fraction of methylated CpG sites obtained by bisulphite sequencing (r = 0.88), and had an accuracy of 71.8 and 83.8% in detecting completely methylated and unmethylated CGIs. Analysis of gastric cancer cell lines using the Me value showed that methylation of CGIs in promoters and gene bodies was associated with low and high, respectively, gene expression. The degree of demethylation of promoter CGIs after 5-aza-2''-deoxycytidine treatment had no association with that of induction of gene expression. The Me value was considered to be useful for analysis of intermediate methylation levels of CGIs.     

Strategies for complete plastid genome sequencing

Plastid sequencing is an essential tool in the study of plant evolution. This high‐copy organelle is one of the most technically accessible regions of the genome, and its sequence conservation makes it a valuable region for comparative genome evolution, phylogenetic analysis and population studies. Here, we discuss recent innovations and approaches for de novo plastid assembly that harness genomic tools. We focus on technical developments including low‐cost sequence library preparation approaches for genome skimming, enrichment via hybrid baits and methylation‐sensitive capture, sequence platforms with higher read outputs and longer read lengths, and automated tools for assembly. These developments allow for a much more streamlined assembly than via conventional short‐range PCR. Although newer methods make complete plastid sequencing possible for any land plant or green alga, there are still challenges for producing finished plastomes particularly from herbarium material or from structurally divergent plastids such as those of parasitic plants.     

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.