CpG_MPs: identification of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data

High-throughput bisulfite sequencing is widely used to measure cytosine methylation at single-base resolution in eukaryotes. It permits systems-level analysis of genomic methylation patterns associated with gene expression and chromatin structure. However, methods for large-scale identification of methylation patterns from bisulfite sequencing are lacking. We developed a comprehensive tool, CpG_MPs, for identification and analysis of the methylation patterns of genomic regions from bisulfite sequencing data. CpG_MPs first normalizes bisulfite sequencing reads into methylation level of CpGs. Then it identifies unmethylated and methylated regions using the methylation status of neighboring CpGs by hotspot extension algorithm without knowledge of pre-defined regions. Furthermore, the conservatively and differentially methylated regions across paired or multiple samples (cells or tissues) are identified by combining a combinatorial algorithm with Shannon entropy. CpG_MPs identified large amounts of genomic regions with different methylation patterns across five human bisulfite sequencing data during cellular differentiation. Different sequence features and significantly cell-specific methylation patterns were observed. These potentially functional regions form candidate regions for functional analysis of DNA methylation during cellular differentiation. CpG_MPs is the first user-friendly tool for identifying methylation patterns of genomic regions from bisulfite sequencing data, permitting further investigation of the biological functions of genome-scale methylation patterns.     

Study of Tissue-Specific CpG Methylation of DNA in Extended Genomic Loci

Modern approaches for studies on genome functioning include investigation of its epigenetic regulation. Methylation of cytosines in CpG dinucleotides is an inherited epigenetic modification that is responsible for both functional activity of certain genomic loci and total chromosomal stability. This review describes the main approaches for studies on DNA methylation. Under consideration are site-specific approaches based on bisulfite sequencing and methyl-sensitive PCR, whole-genome approaches aimed at searching for new methylation hot spots, and also mapping of unmethylated CpG sites in extended genomic loci.     

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.     

BSMAP: whole genome bisulfite sequence MAPping program

Background  

Bisulfite sequencing is a powerful technique to study DNA cytosine methylation. Bisulfite treatment followed by PCR amplification specifically converts unmethylated cytosines to thymine. Coupled with next generation sequencing technology, it is able to detect the methylation status of every cytosine in the genome. However, mapping high-throughput bisulfite reads to the reference genome remains a great challenge due to the increased searching space, reduced complexity of bisulfite sequence, asymmetric cytosine to thymine alignments, and multiple CpG heterogeneous methylation.     

Heterogeneity and randomness of DNA methylation patterns in human embryonic stem cells

DNA methylation has been proposed to be important in many biological processes and is the subject of intense study. Traditional bisulfite genomic sequencing allows detailed high-resolution methylation pattern analysis of each molecule with haplotype information across a few hundred bases at each locus, but lacks the capacity to gather voluminous data. Although recent technological developments are aimed at assessing DNA methylation patterns in a high-throughput manner across the genome, the haplotype information cannot be accurately assembled when the sequencing reads are short or when each hybridization target only includes one or two cytosine-phosphate-guanine (CpG) sites. Whether a distinct and nonrandom DNA methylation pattern is present at a given locus is difficult to discern without the haplotype information, and the DNA methylation patterns are much less apparent because the data are often obtained only as methylation frequencies at each CpG site with some of these methods. It would facilitate the interpretation of data obtained from high-throughput bisulfite sequencing if the loci with nonrandom DNA methylation patterns could be distinguished from those that are randomly methylated. In this study, we carried out traditional genomic bisulfite sequencing using the normal diploid human embryonic stem (hES) cell lines, and utilized Hamming distance analysis to evaluate the existence of a distinct and nonrandom DNA methylation pattern at each locus studied. Our findings suggest that Hamming distance is a simple, quick, and useful tool to identify loci with nonrandom DNA methylation patterns and may be utilized to discern links between biological changes and DNA methylation patterns in the high-throughput bisulfite sequencing data sets.     

High density DNA methylation array with single CpG site resolution

We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R² of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research.     

Genetic and epigenetic instability of human bone marrow mesenchymal stem cells expanded in autologous serum or fetal bovine serum

Culture of mesenchymal stem cells (MSCs) under conditions promoting proliferation and differentiation, while supporting genomic and epigenetic stability, is essential for therapeutic use. We report here the extent of genome-wide DNA gains and losses and of DNA methylation instability on 170 cancer-related promoters in bone marrow (BM) MSCs during culture to late passage in medium containing fetal bovine serum (FBS) or autologous serum (AS). Comparative genomic hybridization indicates that expansion of BMMSCs elicits primarily telomeric deletions in a subpopulation of cells, the extent of which varies between donors. However, late passage cultures in AS consistently display normal DNA copy numbers. Combined bisulfite restriction analysis and bisulfite sequencing show that although DNA methylation states are overall stable in culture, AS exhibits stronger propensity than FBS to maintain unmethylated states. Comparison of DNA methylation in BMMSCs with freshly isolated and cultured adipose stem cells (ASCs) also reveals that most genes unmethylated in both BMMSCs and ASCs in early passage are also unmethylated in uncultured ASCs. We conclude that (i) BMMSCs expanded in AS or FBS may display localized genetic alterations, (ii) AS tends to generate more consistent genomic backgrounds and DNA methylation patterns, and (iii) the unmethylated state of uncultured MSCs is more likely to be maintained in culture than the methylated state.     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of 12 human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.Key words: Tissue specific methylation, CpG island methylation, neural, brain tissue, grey matter, white matter     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of twelve human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.     

A distinct sequence (ATAAA)n separates methylated and unmethylated domains at the 5'-end of the GSTP1 CpG island

What defines the boundaries between methylated and unmethylated domains in the genome is unclear. In this study we used bisulfite genomic sequencing to map the boundaries of methylation that flank the 5'- and 3'-ends of the CpG island spanning the promoter region of the glutathione S-transferase (GSTP1) gene. We show that GSTP1 is expressed in a wide range of tissues including brain, lung, skeletal muscle, spleen, pancreas, bone marrow, prostate, heart, and blood and that this expression is associated with the CpG island being unmethylated. In these normal tissues a marked boundary was found to separate the methylated and unmethylated regions of the gene at the 5'-flank of the CpG island, and this boundary correlated with an (ATAAA)(19-24) repeated sequence. In contrast, the 3'-end of the CpG island was not marked by a sharp transition in methylation but by a gradual change in methylation density over about 500 base pairs. In normal tissue the sequences on either side of the 5'-boundary appear to lie in separate domains in which CpG methylation is independently controlled. These separate methylation domains are lost in all prostate cancer where GSTP1 expression is silenced and methylation extends throughout the island and spans across both the 5'- and 3'-boundary regions.     

Kismeth: Analyzer of plant methylation states through bisulfite sequencing

Background  

There is great interest in probing the temporal and spatial patterns of cytosine methylation states in genomes of a variety of organisms. It is hoped that this will shed light on the biological roles of DNA methylation in the epigenetic control of gene expression. Bisulfite sequencing refers to the treatment of isolated DNA with sodium bisulfite to convert unmethylated cytosine to uracil, with PCR converting the uracil to thymidine followed by sequencing of the resultant DNA to detect DNA methylation. For the study of DNA methylation, plants provide an excellent model system, since they can tolerate major changes in their DNA methylation patterns and have long been studied for the effects of DNA methylation on transposons and epimutations. However, in contrast to the situation in animals, there aren't many tools that analyze bisulfite data in plants, which can exhibit methylation of cytosines in a variety of sequence contexts (CG, CHG, and CHH).     

DHPLC-based method for DNA methylation analysis of differential methylated regions from imprinted genes

The bisulfite genomic sequencing method is one of the most widely used techniques for methylation analysis in heterogeneous unbiased PCR, amplifying for both methylated and unmethylated alleles simultaneously. However, it requires labor-intensive and time-consuming cloning and sequencing steps. In the current study, we used a denaturing high-performance liquid chromatography (DHPLC) procedure in a complementary way with the bisulfite genomic sequencing to analyze the methylation of differentially methylated regions (DMRs) of imprinted genes. We showed reliable and reproducible results in distinguishing overall methylation profiles of DMRs regions of human SNRPN, H19, MEST/PEG1, LIT1, IGF2, TSSC5, WT1 antisense, and mouse H19, Mest/Peg1, Igf2R imprinted genes. These DHPLC profiles were in accordance with bisulfite genomic sequencing data and may serve as a type of "fingerprint," revealing the overall methylation status of DMRs associated with sample heterogeneity. We conclude that DHPLC analysis could be used to increase the throughput efficiency of methylation pattern analysis of imprinted genes after the bisulfite conversion of genomic DNA and unbiased PCR amplification.     

Improved reduced representation bisulfite sequencing for epigenomic profiling of clinical samples

Background

DNA methylation plays crucial roles in epigenetic gene regulation in normal development and disease pathogenesis. Efficient and accurate quantification of DNA methylation at single base resolution can greatly advance the knowledge of disease mechanisms and be used to identify potential biomarkers. We developed an improved pipeline based on reduced representation bisulfite sequencing (RRBS) for cost-effective genome-wide quantification of DNA methylation at single base resolution. A selection of two restriction enzymes (Taq^αI and MspI) enables a more unbiased coverage of genomic regions of different CpG densities. We further developed a highly automated software package to analyze bisulfite sequencing results from the Solexa GAIIx system.

Results

With two sequencing lanes, we were able to quantify ~1.8 million individual CpG sites at a minimum sequencing depth of 10. Overall, about 76.7% of CpG islands, 54.9% of CpG island shores and 52.2% of core promoters in the human genome were covered with at least 3 CpG sites per region.

Conclusions

With this new pipeline, it is now possible to perform whole-genome DNA methylation analysis at single base resolution for a large number of samples for understanding how DNA methylation and its changes are involved in development, differentiation, and disease pathogenesis.     

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.     

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.

     

FadE: whole genome methylation analysis for multiple sequencing platforms

DNA methylation plays a central role in genomic regulation and disease. Sodium bisulfite treatment (SBT) causes unmethylated cytosines to be sequenced as thymine, which allows methylation levels to reflected in the number of ‘C’-‘C’ alignments covering reference cytosines. Di-base color reads produced by lifetech’s SOLiD sequencer provide unreliable results when translated to bases because single sequencing errors effect the downstream sequence. We describe FadE, an algorithm to accurately determine genome-wide methylation rates directly in color or nucleotide space. FadE uses SBT unmethylated and untreated data to determine background error rates and incorporate them into a model which uses Newton–Raphson optimization to estimate the methylation rate and provide a credible interval describing its distribution at every reference cytosine. We sequenced two slides of human fibroblast cell-line bisulfite-converted fragment library with the SOLiD sequencer to investigate genome-wide methylation levels. FadE reported widespread differences in methylation levels across CpG islands and a large number of differentially methylated regions adjacent to genes which compares favorably to the results of an investigation on the same cell-line using nucleotide-space reads at higher coverage levels, suggesting that FadE is an accurate method to estimate genome-wide methylation with color or nucleotide reads. http://code.google.com/p/fade/.