Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

31 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deep bisulfite amplicon sequencing and visualisation reveal diverse and heterogeneous DNA methylation patterns.

ABSTRACT: DNA methylation at a gene promoter region has the potential to regulate gene transcription. Their patterns are often complex with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). The methylation state at adjacent CpG sites is therefore lost when data is summarised this way. Methylation patterns can only be characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. We have developed an analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. We have performed multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Using Methpat, we demonstrate clonal diversity of epialleles analysed at specific gene promoter regions. We also describe the existence of DNA methylation within the mitochondrial genome. Multiplex bisulfite PCR and Next Generation sequencing of 35 samples

ORGANISM(S): Homo sapiens

SUBMITTER: Nicholas Wong

PROVIDER: E-GEOD-67856 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Deep bisulfite amplicon sequencing and visualisation reveal diverse and heterogeneous DNA methylation patterns.

Project description:DNA methylation at a gene promoter region has the potential to regulate gene transcription. Their patterns are often complex with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). The methylation state at adjacent CpG sites is therefore lost when data is summarised this way. Methylation patterns can only be characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. We have developed an analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. We have performed multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Using Methpat, we demonstrate clonal diversity of epialleles analysed at specific gene promoter regions. We also describe the existence of DNA methylation within the mitochondrial genome.

2015-11-23 | GSE67856 | GEO

Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat.

Project description:DNA methylation is a complex epigenetic marker that can be analysed using a wide variety of methods. Interpretation and visualisation of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, however visualisation of massively parallel sequencing results remains a significant challenge. We created a program called Methpat that facilitates visualisation and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 95 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab delimited text file for each sample that summarises DNA methylation patterns and their read counts for each amplicon and a HTML file that summarises this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) datasets with sufficient read depths. Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarised and visualised for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and reveal further biological insight in existing datasets. Multiplex bisulfite PCR and Next Generation sequencing of primary human samples and breast cancer cell lines.

2015-11-23 | E-GEOD-71804 | biostudies-arrayexpress

Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat.

2015-11-23 | GSE71804 | GEO

Rapid and affordable genome-wide bisulfite DNA sequencing by XmaI-RRBS

Project description:We describe XmaI-RRBS method for rapid and affordable genome-wide DNA methylation analysis, with library preparation taking only four days and sequencing possible within four hours. Small sizes of the XmaI-RRBS libraries allow their multiplexing and sequencing on the benchtop high-throughput machines. Described here is the first RRBS protocol validated for the Ion Torrent Personal Genome Machine. DNA from MCF7 cell line and 6 normal breast samples (total 7 samples) were subjected to reduced representation bisulfite sequencing analysis (XmaI-RRBS) by using Ion Torrent platform.

2015-11-01 | E-GEOD-74126 | biostudies-arrayexpress

DNA hypermethylation encroachment at CpG island borders in cancer is predisposed by H3K4 monomethylation [WGBS_Hs]

Project description:DNA methylation plays a key role in demarcation of regulatory regions, including promoter-associated CpG islands. While CpG islands are typically maintained in an unmethylated state in normal cells, a proportion of CpG islands are subject to hypermethylation in cancer cells. It still remains elusive how the exquisite demarcation of the bimodal methylation state is established and maintained at the CpG island flanks and conversely what triggers the erosion of CpG island DNA methylation in tumorigenesis. Here, we applied whole-genome bisulphite sequencing to study the comprehensive methylation patterns of prostate normal and cancer tissues. Alongside we performed TET-assisted bisulphite sequencing to study genome-wide DNA hydroxymethylation patterns of normal prostate and prostate cancer tissues.

2019-01-23 | GSE104789 | GEO

DNA hypermethylation encroachment at CpG island borders in cancer is predisposed by H3K4 monomethylation [TAB-Seq]

2019-01-23 | GSE104780 | GEO

Genome-wide characterization of mitochondrial DNA methylation in human brain

Project description:Here, we present a novel approach to interrogate the mitochondrial DNA (mtDNA) methylome at single base resolution using targeted bisulfite sequencing. We applied this method to investigate mitochondrial DNA methylation patterns in post-mortem superior temporal gyrus and cerebellum brain tissue from seven human donors. We show that mitochondrial DNA methylation patterns are relatively low but conserved, with peaks in DNA methylation >5% at a number of sites and higher levels of methylation at non-CpG compared to CpG sites. We identify a number of loci that show differential DNA methylation patterns associated with age, sex and brain region. Finally we validate differences between cortical and cerebellar mitochondrial DNA methylation patterns using data previously generated using methylated DNA immunoprecipitation sequencing.

2022-12-20 | GSE189565 | GEO

Deep proteomic analysis of Dnmt1 mutant/hypomorphic colorectal cancer cells reveals dys-regulation of Epithelial-Mesenchymal Transition and subcellular re-localization of Beta-Catenin

Project description:DNA methyltransferase I plays the central role in maintenance of CpG DNA methylation patterns across the genome and alteration of CpG methylation patterns is a frequent and significant occurrence across many cancers. Cancer cells carrying hypomorphic alleles of Dnmt1 have become important tools for understanding Dnmt1 function and CpG methylation. In this study, we analyse colorectal cancer cells with a homozygous deletion of exons 3 to 5 of Dnmt1, resulting in reduced Dnmt1 activity. Although this cell model has been widely used to study the epigenome, the effects of the Dnmt1 hypomorph on cell signalling pathways and the wider proteome are largely unknown. In this study, we perform the first quantitative proteomic analysis of this important cell model and identify multiple signalling pathways and processes that are significantly dysregulated in the hypomorph cells. In Dnmt1 hypomorph cells, we observed a clear and unexpected signature of increased Epithelial-to-Mesenchymal transition (EMT) markers as well as reduced expression and sub-cellular re-localization of Beta-Catenin. Expression of wild-type Dnmt1 in hypomorph cells or knock-down of wild-type Dnmt1 did not recapitulate or rescue the observed protein profiles in Dnmt1 hypomorph cells suggesting that hypomorphic Dnmt1 causes changes not solely attributable to Dnmt1 protein levels. In summary we present the first comprehensive proteomic analysis of the widely studied Dnmt1 hypomorph colorectal cancer cells and identify redistribution of Dnmt1 and its interaction partner Beta-Catenin

2021-09-08 | PXD014632 | Pride

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias. [methylation]

Project description:Aberrant DNA-methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti-cancer treatment, though molecular mechanisms and biological signifi- cance remain elusive. Genome-scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG-rich regions (CpG islands). We report the first high-coverage whole-genome map in cancer using the long-read nanopore technol- ogy, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, af- ter chemotherapy. Long-read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution (> 99% CpGs), extending analyses of CpG is- lands to sparse CpGs, which represent half of all differentially-methylated regions. We showed that the

2023-04-12 | GSE213685 | GEO