Project description:Background 5? methylation of cytosines in DNA molecules is an important epigenetic mark in eukaryotes. Bisulfite sequencing is the gold standard of DNA methylation detection, and whole-genome bisulfite sequencing (WGBS) has been widely used to detect methylation at single-nucleotide resolution on a genome-wide scale. However, sodium bisulfite is known to severely degrade DNA, which, in combination with biases introduced during PCR amplification, leads to unbalanced base representation in the final sequencing libraries. Enzymatic conversion of unmethylated cytosines to uracils can achieve the same end product for sequencing as does bisulfite treatment and does not affect the integrity of the DNA; enzymatic methylation sequencing may, thus, provide advantages over bisulfite sequencing. Results Using an enzymatic methyl-seq (EM-seq) technique to selectively deaminate unmethylated cytosines to uracils, we generated and sequenced libraries based on different amounts of Arabidopsis input DNA and different numbers of PCR cycles, and compared these data to results from traditional whole-genome bisulfite sequencing. We found that EM-seq libraries were more consistent between replicates and had higher mapping and lower duplication rates, lower background noise, higher average coverage, and higher coverage of total cytosines. Differential methylation region (DMR) analysis showed that WGBS tended to over-estimate methylation levels especially in CHG and CHH contexts, whereas EM-seq detected higher CG methylation levels in certain highly methylated areas. These phenomena can be mostly explained by a correlation of WGBS methylation estimation with GC content and methylated cytosine density. We used EM-seq to compare methylation between leaves and flowers, and found that CHG methylation level is greatly elevated in flowers, especially in pericentromeric regions. Conclusion We suggest that EM-seq is a more accurate and reliable approach than WGBS to detect methylation. Compared to WGBS, the results of EM-seq are less affected by differences in library preparation conditions or by the skewed base composition in the converted DNA. It may therefore be more desirable to use EM-seq in methylation studies.
Project description:Methylation of cytosine in genomic DNA is a well-characterized epigenetic modification involved in many cellular processes and diseases. Whole-genome bisulfite sequencing (WGBS), such as MethylC-seq and post-bisulfite adaptor tagging sequencing (PBAT-seq), uses the power of high-throughput DNA sequencers and provides genome-wide DNA methylation profiles at single-base resolution. However, the accuracy and consistency of WGBS outputs in relation to the operating conditions of high-throughput sequencers have not been explored.We have used the Illumina HiSeq platform for our PBAT-based WGBS, and found that different versions of HiSeq Control Software (HCS) and Real-Time Analysis (RTA) installed on the system provided different global CpG methylation levels (approximately 5% overall difference) for the same libraries. This problem was reproduced multiple times with different WGBS libraries and likely to be associated with the low sequence diversity of bisulfite-converted DNA. We found that HCS was the major determinant in the observed differences. To determine which version of HCS is most suitable for WGBS, we used substrates with predetermined CpG methylation levels, and found that HCS v2.0.5 is the best among the examined versions. HCS v2.0.12 showed the poorest performance and provided artificially lower CpG methylation levels when 5-methylcytosine is read as guanine (first read of PBAT-seq and second read of MethylC-seq). In addition, paired-end sequencing of low diversity libraries using HCS v2.2.38 or the latest HCS v2.2.58 was greatly affected by cluster densities.Software updates in the Illumina HiSeq platform can affect the outputs from low-diversity sequencing libraries such as WGBS libraries. More recent versions are not necessarily the better, and HCS v2.0.5 is currently the best for WGBS among the examined HCS versions. Thus, together with other experimental conditions, special care has to be taken on this point when CpG methylation levels are to be compared between different samples by WGBS.
Project description:DNA CpG methylation is a widespread epigenetic mark in high eukaryotes including mammals. DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and control of gene expression. Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to measure DNA methylation in a genome-wide fashion, making it possible to comprehensively investigate the role of DNA methylation. Several methods have been developed, such as Whole Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), and enrichment-based methods including Methylation Dependent ImmunoPrecipitation followed by sequencing (MeDIP-seq), methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq), methyltransferase-directed Transfer of Activated Groups followed by sequencing (mTAG), and Methylation-sensitive Restriction Enzyme digestion followed by sequencing (MRE-seq). These methods differ by their genomic CpG coverage, resolution, quantitative accuracy, cost, and software for analyzing the data. Among these, WGBS is considered the gold standard. However, it is still a cost-prohibitive technology for a typical laboratory due to the required sequencing depth. We found that by integrating two enrichment-based methods that are complementary in nature (i.e., MeDIP-seq and MRE-seq), we can significantly increase the efficiency of whole DNA methylome profiling. By using two recently developed computational algorithms (i.e., M&M and methylCRF), the combination of MeDIP-seq and MRE-seq produces genome-wide CpG methylation measurement at high coverage and high resolution, and robust predictions of differentially methylated regions. Thus, the combination of the two enrichment-based methods provides a cost-effective alternative to WGBS. In this article we describe both the experimental protocols for performing MeDIP-seq and MRE-seq, and the computational protocols for running M&M and methylCRF.
Project description:DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation at single base resolution. The analysis of BS-Seq data involves the use of customized aligners for mapping bisulfite converted reads and the bioinformatic pipelines for downstream data analysis.Here we developed MethGo, a software tool designed for the analysis of data from whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). MethGo provides both genomic and epigenomic analyses including: 1) coverage distribution of each cytosine; 2) global cytosine methylation level; 3) cytosine methylation level distribution; 4) cytosine methylation level of genomic elements; 5) chromosome-wide cytosine methylation level distribution; 6) Gene-centric cytosine methylation level; 7) cytosine methylation levels at transcription factor binding sites (TFBSs); 8) single nucleotide polymorphism (SNP) calling, and 9) copy number variation (CNV) calling.MethGo is a simple and effective tool for the analysis of BS-Seq data including both WGBS and RRBS. It contains 9 analyses in 5 major modules to profile (epi)genome. It profiles genome-wide DNA methylation in global and in gene level scale. It can also analyze the methylation pattern around the transcription factor binding sites, and assess genetic variations such as SNPs and CNVs. MethGo is coded in Python and is publically available at http://paoyangchen-laboratory.github.io/methgo/.
Project description:Understanding the role of DNA methylation often requires accurate assessment and comparison of these modifications in a genome-wide fashion. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA CpG methylomes. These include whole genome bisulfite sequencing (WGBS), Reduced-Representation Bisulfite-Sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. An investigator needs a method that is flexible with the quantity of input DNA, provides the appropriate balance among genomic CpG coverage, resolution, quantitative accuracy, and cost, and comes with robust bioinformatics software for analyzing the data. In this chapter, we describe four protocols that combine state-of-the-art experimental strategies with state-of-the-art computational algorithms to achieve this goal. We first introduce two experimental methods that are complementary to each other. MeDIP-seq, or methylation-dependent immunoprecipitation followed by sequencing, uses an anti-methylcytidine antibody to enrich for methylated DNA fragments, and uses massively parallel sequencing to reveal identity of enriched DNA. MRE-seq, or methylation-sensitive restriction enzyme digestion followed by sequencing, relies on a collection of restriction enzymes that recognize CpG containing sequence motifs, but only cut when the CpG is unmethylated. Digested DNA fragments enrich for unmethylated CpGs at their ends, and these CpGs are revealed by massively parallel sequencing. The two computational methods both implement advanced statistical algorithms that integrate MeDIP-seq and MRE-seq data. M&M is a statistical framework to detect differentially methylated regions between two samples. methylCRF is a machine learning framework that predicts CpG methylation levels at single CpG resolution, thus raising the resolution and coverage of MeDIP-seq and MRE-seq to a comparable level of WGBS, but only incurring a cost of less than 5% of WGBS. Together these methods form an effective, robust, and affordable platform for the investigation of genome-wide DNA methylation.
Project description:Whole-genome bisulfite sequencing (WGBS) has been widely used to quantify cytosine DNA methylation frequency in an expanding array of cell and tissue types. Because of the denaturing conditions used, this method ultimately leads to the measurement of methylation frequencies at single cytosines. Hence, the methylation frequency of CpG dyads (two complementary CG dinucleotides) can be only indirectly inferred by overlaying the methylation frequency of two cytosines measured independently. Furthermore, hemi-methylated CpGs (hemiCpGs) have not been previously analyzed in WGBS studies. We recently developed in silico strand annealing (iSA), a bioinformatics method applicable to WGBS data, to resolve the methylation status of CpG dyads into unmethylated, hemi-methylated, and methylated. HemiCpGs account for 4-20% of the DNA methylome in different cell types, and some can be inherited across cell divisions, suggesting a role as a stable epigenetic mark. Therefore, it is important to resolve hemiCpGs from fully methylated CpGs in WGBS studies. This protocol describes step-by-step commands to accomplish this task, including dividing alignments by strand, pairing alignments between strands, and extracting single-fragment methylation calls. The versatility of iSA enables its application downstream of other WGBS-related methods such as nasBS-seq (nascent DNA bisulfite sequencing), ChIP-BS-seq (ChIP followed by bisulfite sequencing), TAB-seq, oxBS-seq, and fCAB-seq. iSA is also tunable for analyzing the methylation status of cytosines in any sequence context. We exemplify this flexibility by uncovering the single-fragment non-CpG methylome. This protocol provides enough details for users with little experience in bioinformatic analysis and takes 2-7 h.
Project description:Stem cells have been found in most tissues/organs. These somatic stem cells produce replacements for lost and damaged cells, and it is not completely understood how this regenerative capacity becomes diminished during aging. To study the possible involvement of epigenetic changes in somatic stem cell aging, we used murine hematopoiesis as a model system. Hematopoietic stem cells (HSCs) were enriched for via Hoechst exclusion activity (SP-HSC) from young, medium-aged and old mice and subjected to comprehensive, global methylome (MeDIP-seq) analysis. With age, we observed a global loss of DNA methylation of approximately 5%, but an increase in methylation at some CpG islands. Just over 100 significant (FDR<0.2) aging-specific differentially methylated regions (aDMRs) were identified, which are surprisingly few considering the profound age-based changes that occur in HSC biology. Interestingly, the polycomb repressive complex -2 (PCRC2) target genes Kiss1r, Nav2 and Hsf4 were hypermethylated with age. The promoter for the Sdpr gene was determined to be progressively hypomethylated with age. This occurred concurrently with an increase in gene expression with age. To explore this relationship further, we cultured isolated SP-HSC in the presence of 5-aza-deoxycytdine and demonstrated a negative correlation between Sdpr promoter methylation and gene expression. We report that DNA methylation patterns are well preserved during hematopoietic stem cell aging, confirm that PCRC2 targets are increasingly methylated with age, and suggest that SDPR expression changes with age in HSCs may be regulated via age-based alterations in DNA methylation.
Project description:Global DNA demethylation in humans is a fundamental process that occurs in pre-implantation embryos and reversion to naive ground state pluripotent stem cells (PSCs). However, the extent of DNA methylation reprogramming in human germline cells is unknown. Here, we performed whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq) of human prenatal germline cells from 53 to 137 days of development. We discovered that the transcriptome and methylome of human germline is distinct from both human PSCs and the inner cell mass (ICM) of human blastocysts. Using this resource to monitor the outcome of global DNA demethylation with reversion of primed PSCs to the naive ground state, we uncovered hotspots of ultralow methylation at transposons that are protected from demethylation in the germline and ICM. Taken together, the human germline serves as a valuable in vivo tool for monitoring the epigenome of cells that have emerged from a global DNA demethylation event.
Project description: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.
Project description:<h4>Background</h4>DNA methylation is an epigenetic regulatory form that plays an important role in regulating the gene expression and the tissues development.. However, DNA methylation regulators involved in sheep muscle development remain unclear. To explore the functional importance of genome-scale DNA methylation during sheep muscle growth, this study systematically investigated the genome-wide DNA methylation profiles at key stages of Hu sheep developmental (fetus and adult) using deep whole-genome bisulfite sequencing (WGBS).<h4>Results</h4>Our study found that the expression levels of DNA methyltransferase (DNMT)-related genes were lower in fetal muscle than in the muscle of adults. The methylation levels in the CG context were higher than those in the CHG and CHH contexts, and methylation levels were highest in introns, followed by exons and downstream regions. Subsequently, we identified 48,491, 17, and 135 differentially methylated regions (DMRs) in the CG, CHG, and CHH sequence contexts and 11,522 differentially methylated genes (DMGs). The results of bisulfite sequencing PCR (BSP) correlated well with the WGBS-Seq data. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation analysis revealed that some DMGs were involved in regulating skeletal muscle development and fatty acid metabolism. By combining the WGBS-Seq and previous RNA-Seq data, a total of 159 overlap genes were obtained between differentially expressed genes (DEGs) and DMGs (FPKM >?10 and fold change >?4). Finally, we found that 9 DMGs were likely to be involved in muscle growth and metabolism of Hu sheep.<h4>Conclusions</h4>We systemically studied the global DNA methylation patterns of fetal and adult muscle development in Hu sheep, which provided new insights into a better understanding of the epigenetic regulation of sheep muscle development.