Ultra-mild bisulfite outperforms EM-seq for 5-methylcytosine detection with low inputs DNA
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE294197 | GEO | 2025/09/27
REPOSITORIES: GEO
Similar Datasets
Project description:Ultra-mild bisulfite outperforms EM-seq for 5-methylcytosine detection with low inputs DNA
| PRJNA1248537 | ENA
Project description:Here, we report an enrichment-based ultra-low input cfDNA methylation profiling method using methyl-CpG binding proteins capture, termed cfMBD-seq. We optimized the conditions of cfMBD capture by adjusting the amount of MethylCap protein along with using methylated filler DNA. Our data showed that cfMBD-seq performs equally to the standard MBD-seq (>1000 ng input) even when using 1 ng DNA as the input. cfMBD-seq demonstrated equivalent sequencing data quality as well as similar methylation profile when compared to cfMeDIP-seq. We showed that cfMBD-seq outperforms cfMeDIP-seq in the enrichment of CpG islands. This new bisulfite-free ultra-low input methylation profiling technology has a great potential in non-invasive and cost-effective cancer detection and classification.
2021-01-01 | GSE161331 | GEO
Project description:Cerebrospinal fluid (CSF) liquid biopsies serve as a rich source of tumor-derived cell-free DNA (cfDNA) for evaluating patients with central nervous system (CNS) tumors. However, challenges stemming from trace cfDNA yields and low mutational burden have hindered sensitivity, whereas first-generation clinical assays have relied on genetic alterations as biomarkers. Leveraging the diagnostic utility of DNA methylation classification in CNS tumors, we developed M-PACT (Methylation-based Predictive Algorithm for CNS Tumors), a robust deep neural network that accurately classifies tumors from sub-nanogram input cfDNA methylomes acquired through enzymatic methylation sequencing. In addition to tumor classification, this workflow enables methylation-based cellular deconvolution and sensitive copy number variation (CNV) detection. We benchmark our methodology in pediatric CNS embryonal tumors and further demonstrate accurate classification of intra-operative CSF, balanced tumor genomes, and secondary malignancies. Altogether, we provide a blueprint for CNS tumor classification from low input cfDNA methylomes, motivating prospective validation for future clinical implementation.
2025-11-17 | GSE292312 | GEO
Project description:Three-dimensional chromatin organization varies across different cell types and is essential for gene regulation. However, current technologies are unable to assess in vivo genome-wide chromatin organization non-invasively. Here, we showed that long-range correlations in the fragment length of cell-free DNA (cfDNA) estimated from whole-genome sequencing recapitulate three-dimensional chromatin organization. The inferred organization is highly concordant with that measured by Hi-C in white blood cells from healthy donors, and is not explained by technical bias or sequence composition. Furthermore, the inferred organization reflects the differing genome organizations in the various cell types contributing to cfDNA, allowing quantification of cfDNA tissue-of-origin that is concordant with previous methods, but at much lower required DNA input. Our results, demonstrated in cfDNA from healthy individuals and cancer patients, may enable noninvasive monitoring of in vivo genome organization and accurate quantification of cell death in different clinical conditions.
2019-05-07 | GSE124974 | GEO
Project description:DNA methylation at cytosine-phospho-guanine (CpG) residues is a vital biological process that regulates cell identity and function. Although widely used, bisulfite-based cytosine conversion procedures for DNA methylation sequencing require high temperature and extreme pH, which leads to DNA degradation, especially among unmethylated cytosines. This disproportionate damage to unmethylated cytosines contributes to inaccuracies in GC content representation. EM-seq, an enzyme-based cytosine conversion method, has been proposed as a less biased alternative to methylation profiling. Compared to bisulfite-based methods, EM-seq boasts greater genome coverage with less GC bias and has the potential to cover more CpGs with the same number of reads (i.e., higher signal-to-noise ratio). Reduced representation approaches enrich samples for CpG-rich genomic regions, thereby enhancing throughput and cost effectiveness. We hypothesized that enzyme-based technology could be adapted for reduced representation methylation sequencing to enable high-resolution DNA methylation profiling on low inputs samples. We leveraged the well-established differences in methylation profile between mouse CD4+ T cell populations to compare reduced representation EM-seq (RREM-seq) performance against our previously published modified reduced representation bisulfite sequencing (mRRBS). While the mRRBS method failed to generate reliable DNA libraries when using <2-ng inputs (equivalent to DNA from around 350 cells), the RREM-seq method successfully generated DNA libraries from 1–25 ng of mouse and human genomic DNA. These libraries fell within the expected size range, and primer contamination was not observed. Low-input (<2-ng) RREM-seq libraries’ final concentration, regulatory genomic element coverage, and methylation status within the lineage-defining Treg cell-specific super-enhancers were comparable to mRRBS libraries with more than 10-fold higher DNA input. RREM-seq libraries also successfully detected the methylation differences between alveolar Tconv and Treg cells in mechanically ventilated patients with severe SARS-CoV-2 pneumonia. Our results suggest that the RREM-seq method can generate reliable libraries for single-nucleotide resolution methylation profiling using low input clinical samples.
2025-06-02 | GSE266961 | GEO
Project description:We aimed to clarify the cell-free DNA (cfDNA) physiological role. We exposed THP1 cells to plasma from healthy individuals with and without cfDNA and compared their transcriptomes and proteomes.
2020-12-01 | E-MTAB-8574 | biostudies-arrayexpress
Project description:Nucleosomes are the basic unit of packaging of eukaryotic chromatin, and nucleosome positioning can differ substantially between cell types. Here, we sequence 14.5 billion plasma-borne cell-free DNA (cfDNA) fragments (700-fold coverage) to generate genome-wide maps of in vivo nucleosome occupancy. We identify 13 million local maxima of nucleosome protection, spanning 2.53 gigabases (Gb) of the human genome, whose positions and spacings correlate with nuclear architecture, gene structure and gene expression. We further show that short cfDNA fragments - poorly recovered by standard protocols - directly footprint the in vivo occupancy of DNA-bound transcription factors such as CTCF. The sequence composition of cfDNA has previously been used to noninvasively monitor cancer, pregnancy and organ transplantation, but a key limitation of this paradigm is its dependence on genotypic differences to distinguish between contributing tissues. We show that nucleosome spacing in gene bodies and cis-regulatory elements, inferred from cfDNA in healthy individuals, correlates most strongly with transcriptional and epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how in vivo nucleosome footprints can be used to infer the cell types that contribute to circulating cfDNA in pathological states such as cancer. Because it does not rely on genotypic differences, this strategy may enable the noninvasive cfDNA-based monitoring of a much broader set of clinical conditions than is currently possible. Sequencing of cfDNA libraries from healthy individuals, pooled healthy individuals and individuals with disease for the identification of nucleosomes and protection from other DNA binding proteins.
2015-11-04 | E-GEOD-71378 | biostudies-arrayexpress
Project description:Heterogeneity in DNA methylation status may exist between primary tumors and cfDNA. We compared the genome-wide DNA methylation status between FNA sample of pancreatic tumor and cfDNA samples from the same patients. MBD-sequencing (seq) was performed in paired samples of FNA and cfDNA from two patients. The majority of DNA methylation peaks overlapped in FNA and cfDNA samples (82.6% and 82.9% in patients #1 and #73, respectively). DNA methylation levels of each gene in FNA and cfDNA samples were highly correlated with each other (r=0.98 and 0.97 in samples 1 and 73, respectively)
2020-05-21 | GSE150468 | GEO
Project description:Current methods for mapping the tissue-of-origin of circulating cell-free DNA (cfDNA) are still insufficient. Here, we have extended a previously developed methylated CpG tandems amplification and sequencing (MCTA-Seq) method for quantitative analysis of tissue-of-origin of plasma cfDNA. By comparing paired plasma cfDNA and white blood cell genomic DNA, we have demonstrated that the liver is the major non-hematopoietic tissue contributing to plasma cfDNA in healthy adults, accounting for approximately 2%. Furthermore, we have detected changes in liver-derived DNA in patients with benign liver diseases and increases in pancreas-derived DNA in acute pancreatitis patients. Interestingly, our results suggest that DNA derived from pathological tissues makes a minor contribution to the increased cfDNA in many clinical cases. Finally, we have identified a tissue-specific hypermethylated cfDNA marker located in the intragenic regions of tissue-specifichighlyexpressed genes. This study represents valuable progress in the field of cfDNA and offers promise for clinical research and medical diagnostics using the described method.
2019-07-01 | GSE118690 | GEO