BiQ Analyzer Research Articles

Applications of bioinformatics in epigenetics.

Epigenetic modifications such as DNA methylation, post-translational chromatin modifications and non-coding RNA-mediated mechanisms are responsible for epigenetic inheritance. Change in gene expression due to these epigenetic modifications are responsible for new traits in different organisms leading to various diseases including cancer, diabetic kidney disease (DKD), diabetic nephropathy (DN) and renal fibrosis. Bioinformatics is an effective approach for epigenomic profiling. These epigenomic data can be analyzed by a large number of bioinformatics tools and software. Many databases are available online, which comprises huge amount of information regarding these modifications. Recent methodologies include many sequencing and analytical techniques to extrapolate different types of epigenetic data. This data can be used to design drugs against diseases linked to epigenetic modifications. This chapter briefly highlights different epigenetics databases (MethDB, REBASE, Pubmeth, MethPrimerDB, Histone Database, ChromDB, MeInfoText database, EpimiR, Methylome DB, and dbHiMo), and tools (compEpiTools, CpGProD, MethBlAST, EpiExplorer, and BiQ analyzer), which are being utilized to retrieve the data and mechanistically analysis of epigenetics modifications.

Role of SPDEF gene enhancer and promoter methylation in prostate cancer cell metastasis and therapeutic resistance

Background Prostate cancer (PCa) is the second most prevalent carcinoma in men which results in over 30,000 deaths annually in the United States, mostly due to the metastatic castration-resistant (mCRPC) disease. Our previous studies demonstrated that Transcription factor SAM-pointed domain-containing Ets-like factor (SPDEF) inhibits prostate cancer metastasis, in part by promoting luminal differentiation. Decreased SPDEF expression was associated with higher grades of prostate tumors in cell line models and clinical cohorts, with a complete loss of PDEF expression in Neuro-endocrine form of PCa. In the present study we assessed role of epigenetic mechanisms in SPDEF expression during prostate cancer progression. Methods Differential expression analysis of epigenetic writer enzymes were established by obtaining large scale clinical data published on the TCGA database. We used bisulfite sequencing method from assessing promoter and enhancer methylation from various PCa cells lines (LNCaP, PC3, Du-145, and LNCaP-C4-2B). Samples were treated with sodium bisulfite, regions amplified using PCR technique, cloned into pGEM vector using TA cloning technique, and sequenced using M13 reverse primer. Data were quantified using BiQ Analyzer and QUMA tools. To functionally check the role of DNA methylation, cells were treated with 5-aza cytidine (a DNA methyl transferase inhibitor) followed by SPDEF gene expression studies. Results Clinical data analysis revealed a significant differential expression of several epigenetic writers including DNMT1, DNMT3a, DNMT3b, as well as EZH2 in a large cohort of prostate cancer patients with various Gleason scores. Our Bisulfite sequencing study also revealed that both enhancer and promoter regions of SPDEF gene undergo significant hypermethylation in aggressive cell models compared to local representatives. Moreover, promoter, but not enhancer, showed a higher methylation level in the androgen insensitive cell models compared to sensitive cells; both suggesting an active role of DNA methylation in metastasis and therapy resistance. Consistently, the aggressive cells with lower SPDEF levels were able to recover SPDEF levels following 5-aza Cytidine in a dose- and time-dependent manner. Conclusions Our data point to a key role for epigenetic regulation in suppression of SPDEF in metastatic and therapy resistant PCa, suggesting a potential role for targeting epigenetic pathways in preventing metastasis and overcoming therapy resistance in subsets of PCa patients with loss of SPDEF.

High-Throughput Targeted Repeat Element Bisulfite Sequencing (HT-TREBS).

High-throughput targeted repeat element bisulfite sequencing (HT-TREBS) is designed to assay the methylation level of individual retrotransposon loci of a targeted family, in a locus-specific manner, and on a genome-wide scale. Briefly, genomic DNA is sheared and ligated to Ion Torrent A adaptors (with methylated cytosines), followed by bisulfite-conversion, and amplification with primers designed to bind the targeted retrotransposon. Since the primers carry the Ion Torrent P1 adaptor as a 5'-extension, the amplified library is ready to be size-selected and sequenced on a next-generation sequencing platform. Once sequenced, each retrotransposon is mapped to a particular genomic locus, which is achieved through ensuring at least a 10-bp overlap with flanking unique sequence, followed by the calculation of methylation levels of the mapped retrotransposon using a BiQ Analyzer HT. A complete protocol for library construction as well as the bioinformatics for HT-TREBS is described in this chapter.

DNA Methylation as a Biomarker for Body Fluid Identification

Currently, available identification techniques for forensic samples are either enzyme or protein based, which can be subjected to degradation, thus limiting its storage potentials. Epigenetic changes arising due to DNA methylation and histone acetylation can be used for body fluid identification. Markers DACT1, USP49, ZC3H12D, FGF7, cg23521140, cg17610929, chromosome 4 (25287119–25287254), chromosome 11 (72085678–72085798, 57171095–57171236, 1493401–1493538), and chromosome 19 (47395505–47395651) are currently being used for semen identification. Markers cg26107890, cg20691722, cg01774894 and cg14991487 are used to differentiate saliva and vaginal secretions from other body fluids. However, such markers show overlapping methylation pattern. This review article aimed to highlight the feasibility of using DNA methylation of certain genetic markers in body fluid identification and its implications for forensic investigations. The reviewed articles have employed molecular genetics techniques such as Bisulfite sequencing PCR (BSP), methylation specific PCR (MSP), Pyrosequencing, Combined Bisulfite Restriction Analysis (COBRA), Methylation-sensitive Single Nucleotide Primer Extension (SNuPE), and Multiplex SNaPshot Microarray. Bioinformatics software such as MATLAB and BiQ Analyzer has been used. Biological fluids have different methylation patterns and thus, this difference can be used to identify the nature of the biological fluid found at the crime scene. Using DNA methylation to identify the body fluids gives accurate results without consumption of the trace evidence and requires a minute amount of DNA for analysis. Recent studies have incorporated next-generation sequencing aiming to find out more reliable markers that can differentiate between different body fluids. Nonetheless, new DNA methylation markers are yet to be discovered to accurately differentiate between saliva and vaginal secretions with high confidence. Epigenetic changes are dynamic and it is important to find stable DNA sequences that can be used as biomarkers. Keywords: Forensic Science; DNA analysis; Methylation; body fluid; identification; Pyrosequencing; DACT1; USP49; ZC3H12D; FGF7.

P124: Targeted bisulfite sequencing of potential prostate cancer cell-free DNA markers: novel approach to reveal diagnostically significant molecules

Cancer cells display altered methylation signatures distinguishing them from normal cells. Originating from all tissues and cells of the body cell-free DNA (cfDNA) including aberrantly methylated DNA reflect epigenetic aberrations occurs not only in tumor cells but also in tumor microenvironment. Actually, aberrantly methylated cfDNA has proved to be a promising biomarker for noninvasive detection of cancer with several clinically-certified tests (Epi-pro Colon®, Epi-pro Lung®, Cologuard®). However only one test (Epi-pro Colon®) uses blood plasma – the most convenient source of cfDNA. Input of tissue and age specific methylation along with unidentified reasons lead to the presence of molecules with every conceivable cytosine-methylation patterns which decrease probability of tumor DNA identification. Among numerous variants of cfDNA methylation patterns only few reflect cancer related changes. To identify those tumor-specific profiles single nucleotide resolution of methylated cytosine locations in the individual circulating DNA molecules is obviously required. We performed target bisulfite sequencing of potential prostate cancer (PC) cfDNA markers (GSTP1; RNF219) isolated from blood plasma of 18 healthy donors (HD), 17 benign hyperplasia (BPH) and 20 PC patients using MiSeq platform (Illumina). RNF219 gene was shown to have high diagnostic potential in our previous comparative study of cfDNA from HD, PC and BHP patients using HCGI12k microarrays (Cortese, et al., 2012). GSTP1 is a common pathological DNA methylation event in PC and is most widely studied and promising methylation marker in the cfDNA of PC patients (Wu, et al., 2011). Selected loci were amplified after bisulfite conversion (Zymo Research) of cfDNA with methyl-independent barcoded primers and sequenced with coverage ranging from 23509 to 143953. Identification of CpG methylation status in DNA fragments was performed with the BiQ Analyzer HT Software. All statistical analysis was performed using R Statistical Software (version 3.1.1) To reveal diagnostically significant differences, several approaches to data analysis were used. Conventional approach is a prediction of patient’s diagnosis based on differences in methylation level of CpG-sites. Another approach used in this study relies on discrimination of cancer-related correlation between methylation statuses of CpG-sites within individual molecules of cfDNA – Intramolecular Correlation of Methylation Statuses (ICoMS). Study population was randomly subsampled into training and test cohorts. The logit regression model based on methylation level of CpG-sites achieved an area under the ROC curve (AUC) exceeding 0.94 in both cohorts for GSTP1 gene and 0.81 – for RNF219 gene. A novel approach to identify diagnostic significance of cfDNA methylation was based on comparison of correlation matrices (pairwise phi coefficient between methylation statuses of CpG sites) for HD, BHP and PC groups. Binomial regression models with LASSO penalization were used to predict patient’s diagnosis. ROC curves for fitted models show AUC, specificity and sensitivity as 0.99, 100% and 92% for GSTP1 gene and 0.99, 100% and 90% for RNF219 (test cohort). The ICoMS approach estimates diagnostic value of target genes and reveals cancer-related cytosine methylation. That could potentially input in gene expression, identify the features of tumor physiology and on a par with conventional approaches provide helpful information for rational design of noninvasive, methylation-specific cfDNA-based diagnostics for PC. Moreover, the planned further evaluation of relationship between the revealed correlations associated with cancer and tumor biology could increase the basic knowledge of carcinogenesis.

Epigenetic Regulation of Von Willebrand Factor Gene Expression May Contribute to Von Willebrand Disease Severity

Background: Von Willebrand disease (VWD) is the most common inherited bleeding disorder with a prevalence ranging from 0.8 to 1.3%. VWD is characterized by incomplete penetrance, variable expressivity with markedly variable VWD antigen levels, even in families with a unifying VWF mutation, suggesting the presence of modifier genes or epigenetic modifications affecting expression of the VWF gene. We had previously diagnosed and characterized an 821-member, multigenerational Amish family in which 121 individuals exhibit a single autosomal-dominant C4120T mutation (R1374C) in the A1 domain of the mature VWF molecule. VWF antigen levels were found to vary significantly, from 9-76 in the individuals exhibiting the C4120T mutation vs 46-483 in the individuals not exhibiting the mutation. To date, very little is known about the epigenetics of VWD and no data exist investigating promoter methylation as a modifier of disease severity. We hypothesized that VWF gene is epigenetically silenced by aberrant DNA methylation resulting in differential expression of VWF protein in patients with VWD. We report our findings suggesting that promoter methylation within the VWF gene may modify VWD severity.Methods: Genomic DNA previously extracted from whole blood using DNeasy kit was CT converted with the use of the EZ DNA Methylation Kit. Primers encompassing a CpG island containing 4 CpG sites in the 5’ region of the VWF gene spanning from 138 to 490 were designed using MethPrimer. The resulting PCR products were gel-extracted and purified, cloned using the TOPO TA Cloning Kit, transformed into competent, Amp resistant E. coli cells and grown on an Ampicillin containing media. This was done in 30 samples, 20 of which contain the disease-characterizing C4120T mutation and 10 which did not. Approximately 20 colonies from each of the 30 samples were randomly chosen and grown in culture media. Plasmid DNA was extracted and sequenced on an ABI-Prism 3100 Genetic Analyzer. The methylation status of 4 CpG dinucleotides of the VWF promoter regions was analyzed using BiQ Analyzer software.Results: We performed ANOVA comparing the high VWF antigen level clones against the low VWF antigen level clones within the C4120T mutation subset and similarly for the controls. Methylation percentage was higher in the low antigen level group at each of the four CpG sites although none reached statistical significance. At two sites, we achieved near statistical significance CpG1 (p=0.100) and CpG2 (p=0.063). Among the control individuals, we did not observe this trend. Methylation was higher in the low antigen group vs the high antigen level group at CpG sites 2 and 3, but lower at CpG sites 1 and 4 with CpG4 bordering on statistical significant (p=0.053). We also performed a Spearman Rank-Order Correlation Coefficient which yielded a near-significant trend between VWF antigen level and methylation percentage within the mutation-bearing, low-expression subset at CpG4 (p=0.064).Discussion: Promoter methylation is known to modify gene expression in numerous disease processes. For the first time, we demonstrate a possible epigenetic effect contributing to the known variance in severity of von Willebrand Disease that is known to correlate with VWF antigen levels. Although our data do not achieve statistical significance, we observed a trend of higher methylation associated with low antigen levels in individuals with the C4120T mutation at two CpG sites. We also observed a near significant association between degree of methylation and VWF antigen levels at 1 CpG site within the mutation-bearing, low antigen level subset. Further studies with larger number of individuals will confirm or refute this observation. DisclosuresNo relevant conflicts of interest to declare.

BiQ Analyzer HiMod: an interactive software tool for high-throughput locus-specific analysis of 5-methylcytosine and its oxidized derivatives.

Recent data suggest important biological roles for oxidative modifications of methylated cytosines, specifically hydroxymethylation, formylation and carboxylation. Several assays are now available for profiling these DNA modifications genome-wide as well as in targeted, locus-specific settings. Here we present BiQ Analyzer HiMod, a user-friendly software tool for sequence alignment, quality control and initial analysis of locus-specific DNA modification data. The software supports four different assay types, and it leads the user from raw sequence reads to DNA modification statistics and publication-quality plots. BiQ Analyzer HiMod combines well-established graphical user interface of its predecessor tool, BiQ Analyzer HT, with new and extended analysis modes. BiQ Analyzer HiMod also includes updates of the analysis workspace, an intuitive interface, a custom vector graphics engine and support of additional input and output data formats. The tool is freely available as a stand-alone installation package from http://biq-analyzer-himod.bioinf.mpi-inf.mpg.de/.

Bi-PROF

The use of next generation sequencing has expanded our view on whole mammalian methylome patterns. In particular, it provides a genome-wide insight of local DNA methylation diversity at single nucleotide level and enables the examination of single chromosome sequence sections at a sufficient statistical power. We describe a bisulfite-based sequence profiling pipeline, Bi-PROF, which is based on the 454 GS-FLX Titanium technology that allows to obtain up to one million sequence stretches at single base pair resolution without laborious subcloning. To illustrate the performance of the experimental workflow connected to a bioinformatics program pipeline (BiQ Analyzer HT) we present a test analysis set of 68 different epigenetic marker regions (amplicons) in five individual patient-derived xenograft tissue samples of colorectal cancer and one healthy colon epithelium sample as a control. After the 454 GS-FLX Titanium run, sequence read processing and sample decoding, the obtained alignments are quality controlled and statistically evaluated. Comprehensive methylation pattern interpretation (profiling) assessed by analyzing 102-104 sequence reads per amplicon allows an unprecedented deep view on pattern formation and methylation marker heterogeneity in tissues concerned by complex diseases like cancer.

Epigenetic regulation of DNMT1 gene in mouse model of asthma disease

Asthma is a complex genetic disease, which arises from the interaction of multiple genes and environmental stimuli. These influences are important to asthma pathogenesis. These can be mechanically explained by the Epigenetic phenomenon, which consists of the chromatin and its modifications, as well as a covalent modification of cytosines residing at the dinucleotide sequence CG in DNA by methylation. This reaction is catalyzed by a family of DNA methyltransferase enzyme (DNMTs). DNMT1 is one of them which maintained the methylation status during replication and also critical for the development, differentiation and regulation of Th1 and Th2 cells. Therefore we studied the DNMT1 mRNA expression profiling as well as CpG methylation status in promoter region. For these studies we developed asthma mouse model, and used Flow cytometer, qRT(2)-PCR, Methylation specific PCR, bisulfate conversion and BiQ analyzer. We found that DNMT1 expression level was low in all the tissues (lung, trachea and BALF cells) of asthmatic in comparison to normal mice. This was due to the methylation of regulatory sites of DNMT1 promoter region at cytosine residue. As the incidence of asthma is increasing globally and in world, this study assumes greater significance in designing and developing therapeutic means.

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data.

53 IMPACTS OF USING PROCAINE AS A DNA-DEMETHYLATING AGENT IN IN VITRO CULTURE OF BOVINE CELLS

Euchromatin and heterochromatin organisation define the specificity of each cell type. This structure is controlled by epigenetic modifications and the DNA methylation is one of the best known for inducing transcriptional repression. Recently, procaine was uncovered as a DNA-demethylating agent, but there are few reports about its dynamic epigenetic action on somatic cells. Mono-allelic expression of imprinted genes is controlled by DNA methylation and inherited to somatic tissues of a sex-specific manner. The aim was to investigate the effects of using procaine, a DNA-demethylating agent, in in vitro culture of bovine (Bos taurus indicus) fibroblast for 72 h (passage 4). We have evaluated cell viability, chromosome integrity, and DNA methylation patterns. To evaluate cell viability, we have used trypan blue 0.4%. To evaluate chromosome integrity, we have used conventional cytogenetic analysis. To investigate DNA methylation patterns, we have analysed 2 differentially methylated regions (DMR) located into the exon 10 of IGF2 and exon 1 of XIST imprinted genes, using the bisulfite sequencing method (EZ DNA methylation kit, Zymo Research, Orange, CA, USA). After bisulfite treatment and nested-PCR, the amplicons were separated in agarose gel electrophoresis, purified with GenClean III kit (MP Biomedicals, Irvine, CA, USA), cloned in a pGEM-T easy vector system (Promega, Madison, WI), and sequenced. The DNA sequences were analysed using the BiQ Analyzer v. 2.0 (2008) software. The cell viability data were analysed using ANOVA and Tukey or Kruskal-Wallis and Mann-Whitney tests, and the methylation status were analysed using Student’s t-test or Mann-Whitney tests in the Prophet software (BBN Systems and Technologies). Cell culture using 0.1 mM or 0.5 mM of procaine were viable and the number of cells with intact membrane was higher than the control and 2.0 mM of procaine groups (P ≤ 0.05). The total number of cells was lower in the group with 2.0 mM of procaine (P ≤ 0.01). Cytogenetic analysis showed no differences among the groups, with no chromosome abnormalities detected. The methylation pattern was not different for both DMR evaluated among the groups. We have observed that there was a beneficial effect to the cells that have received supplementation with 0.1 mM or 0.5 mM of procaine, because there was an increase in the number of viable cells without chromosomal abnormalities. We cannot ignore that a global DNA demethylation may have occurred, which was not detected in the specific analysed regions. The results obtained here may contribute to improving the efficiency of animal cloning, transgenic animal production, and the knowledge about stem cells. Supported by Embrapa Genetic Resources and Biotechnology and CAPES.

278 METHYLATION STATUS IN THE INTRAGENIC DIFFERENTIALLY METHYLATED REGION OF THE IGF2 LOCUS IN UNSORTED AND SEX-SORTED SPERM

Methylation is the main coordinator of epigenetic inheritance between generations, influencing the regulation of gene expression. Therefore, changes of its pattern in any cell can cause important alterations affecting its function. The methylation pattern of imprinted genes has been reported to be altered by numerous environmental factors such as nutrition, diseases, and drugs. Sexing by flow cytometry exposes the sperm cells to various procedures that can affect sperm quality and could induce methylation changes, resulting in lower fertilization when compared with conventional sperm. Although many studies have related changes in methylation pattern to in vitro culture of oocytes and embryos, no reports have evaluated these changes in sperm caused by the sexing process. The IGF2 imprinted gene, which is predominantly expressed by the paternal allele with the maternal one silenced, is expected to have its intragenic differentially methylated region (DMR) highly methylated in the sperm. Therefore, it became an excellent candidate region to be used for evaluating changes in methylation status of the sperm. The objective of this study was to evaluate the influence of sexing by flow cytometry on the methylation pattern of the DMR located in exon 10 of the IGF2 gene. Frozen–thawed unsorted and sex-sorted sperm samples from 4 Nellore bulls were used (5–10 years old). Each ejaculate was separated into 3 fractions: nonsexed (NS), sexed for X-sperm (SX), and sexed for Y-sperm (SY). Then, 1 straw of each treatment/bull was thawed, placed in 40:70 Percoll gradient (GE Bioscience®, Uppsala, Sweden) and centrifuged at 700 × g for 45 min to separate the somatic cells from the sperm. Sperm pellets were then used for DNA extraction. After that, DNA was treated with sodium bisulfite using the EZ DNA methylation kit (Zymo Research®, Orange, CA, USA). Bisulfite-treated DNA was amplified in 2-round PCR strategy (nested-PCR) and the amplicons were purified using GenClean III kit (MP Biomedical®, Solon, OH, USA). The purified amplicons were cloned into the pGEM-T easy vector system (Promega®, Madison, WI, USA) and transformed into Escherichia coli cells (XL-1 Blue). The resulting individual clones were sequenced, using a dideoxy fluorescence terminator system (ABI 3130xl, Applied Biosystems, Foster City, CA, USA). The experiment was performed in 3 replicates per bull. Sequences were analysed using the BiQ Analyzer software with a GenBank sequence (X53553) as a reference. At least 60 clones were sequenced per group. The methylation status of the 28 CpG sites was compared among the groups using analysis of variance and Tukey test in the Prophet software. No differences in DNA methylation were found between NS (97.5 ± 1.7%), SX (95.8 ± 1.8%), and SY (97.3 ± 0.2%) (P = 0.36). Moreover, 100% of analysed sequences in all groups were hypermethylated. Therefore, we can conclude that the process of sexing by flow cytometry does not change the methylation pattern in the intragenic DMR located in exon 10 of the IGF2 gene. Financial support: FAPESP and Embrapa.

Cytosine methylation in the HPV16 3’ L1/ 5’LCR region characterized from anal epithelia of HPV-HIV coinfected men

Anal specimens derived from 83 HIV-HPV16 co-infected men were analyzed for cytosine methylation using bisulfite modification, PCR amplification, cloning, and sequencing. Data were processed using the ClustalW alignment algorithm within BiQ Analyzer Software and input into SAS 9.2 to generate heat maps and histograms(Figure ​histograms(Figure1).1). Approximately 10 clones were characterized for each specimen across 81 CpA, CpT, CpC (denovo methylation) and 10 CpG sites within the 3’-L1 and 5’LCR region of HPV16 genomes. Analyses were confined to 64 denovo cytosine residues and 10 CpGs outside the primer annealing regions. Clinical outcome evaluation by a single examiner showed seven men with no anal intraepithelial neoplasias (AIN), 26 with AIN-1, and 50 with AIN-2. Data showed the average prevalence (standard deviation) of methylcytosines was 11% (0.3) across 7,553 bases/residues and did not vary across maintained or denovo cytosine groups, i.e., 6,723 denovo sites and 830 CpGs. Evaluation by a single examiner using cytology and histology showed 7 with no anal intraepithelial neoplasias (AIN), 26 showed AIN-1, and 50 showed AIN-2. Mean and median prevalence of denovo and CpG methylation were closely approximated across AIN groups. Maxima were observed in two regions: 7111 to 7119, and 7505 to 7514 that showed a methylcytocine prevalence of 24% (0.4), and 18% (0.4), respectively. Logistic regression suggests that with each year of age, risk for moderate-severe methylation ≥30% at each site decreases; however, among smokers risk for ≥30% methylation increases. Specifically, moderate cytosine-methylation decreased by 5% (OR=0.95, 95% CI, (0.92, 0.99) for each year of age, centered around the mean of the sample. Smokers were nearly twice as likely to show moderate cytosine methylation overall (OR=1.9, (1.1, 3.3) and these estimates did not vary across CpG-denovo sites. Although not statistically significant, moderate cytosine methylation was inversely associated with grade of AIN in these data (when compared to high-grade, low-grade and no AIN showed OR=1.5 (0.8, 2.7) and 2.0 (0.9, 4.5), respectively, p=0.2). Figure 1 Heatmap of Methylcytosines in the 3’L1 and 5’LCR Region of HPV16.

Bisulfite sequencing Data Presentation and Compilation (BDPC) web server – a useful tool for DNA methylation analysis

During bisulfite genomic sequencing projects large amount of data are generated. The Bisulfite sequencing Data Presentation and Compilation (BDPC) web interface (http://biochem.jacobs-university.de/BDPC/) automatically analyzes bisulfite datasets prepared using the BiQ Analyzer. BDPC provides the following output: (i) MS-Excel compatible files compiling for each PCR product (a) the average methylation level, the number of clones analyzed and the percentage of CG sites analyzed (which is an indicator of data quality), (b) the methylation level observed at each CG site and (c) the methylation level of each clone. (ii) A methylation overview table compiling the methylation of all amplicons in all tissues. (iii) Publication grade figures in PNG format showing the methylation pattern for each PCR product embedded in an HMTL file summarizing the methylation data, the DNA sequence and some basic statistics. (iv) A summary file compiling the methylation pattern of different tissues, which is linked to the individual HTML result files, and can be directly used for presentation of the data in the internet. (v) A condensed file, containing all primary data in simplified format for further downstream data analysis and (vi) a custom track file for display of the results in the UCSC genome browser.

Bisulfite sequencing Data Presentation and Compilation (BDPC) web server--a useful tool for DNA methylation analysis

During bisulfite genomic sequencing projects large amount of data are generated. The Bisulfite sequencing Data Presentation and Compilation (BDPC) web interface (http://biochem.jacobs-university.de/BDPC/) automatically analyzes bisulfite datasets prepared using the BiQ Analyzer. BDPC provides the following output: (i) MS-Excel compatible files compiling for each PCR product (a) the average methylation level, the number of clones analyzed and the percentage of CG sites analyzed (which is an indicator of data quality), (b) the methylation level observed at each CG site and (c) the methylation level of each clone. (ii) A methylation overview table compiling the methylation of all amplicons in all tissues. (iii) Publication grade figures in PNG format showing the methylation pattern for each PCR product embedded in an HMTL file summarizing the methylation data, the DNA sequence and some basic statistics. (iv) A summary file compiling the methylation pattern of different tissues, which is linked to the individual HTML result files, and can be directly used for presentation of the data in the internet. (v) A condensed file, containing all primary data in simplified format for further downstream data analysis and (vi) a custom track file for display of the results in the UCSC genome browser.

The Krüppel-associated Box Repressor Domain Can Trigger de Novo Promoter Methylation during Mouse Early Embryogenesis

The Krüppel-associated box (KRAB) domain is a transcriptional repression module responsible for the DNA binding-dependent gene silencing activity of hundreds of vertebrate zinc finger proteins. We previously exploited KRAB-mediated repression within the context of a tet repressor-KRAB fusion protein and of lentiviral vectors to create a method of external gene control. We demonstrated that with this system transcriptional silencing was fully reversible in cell culture as well as in vivo. Here we reveal that, in sharp contrast, KRAB-mediated repression results in irreversible gene silencing through promoter DNA methylation if it acts during the first few days of mouse development.

BiQ Analyzer: visualization and quality control for DNA methylation data from bisulfite sequencing

Manual processing of DNA methylation data from bisulfite sequencing is a tedious and error-prone task. Here we present an interactive software tool that provides start-to-end support for this process. In an easy-to-use manner, the tool helps the user to import the sequence files from the sequencer, to align them, to exclude or correct critical sequences, to document the experiment, to perform basic statistics and to produce publication-quality diagrams. Emphasis is put on quality control: The program automatically assesses data quality and provides warnings and suggestions for dealing with critical sequences. The BiQ Analyzer program is implemented in the Java programming language and runs on any platform for which a recent Java virtual machine is available. The program is available without charge for non-commercial users and can be downloaded from http://biq-analyzer.bioinf.mpi-inf.mpg.de/