ArticleNucleic acids research2017
Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed.
- Exploring single-cell and multi-omics technologies and their role in unraveling tumor heterogeneity of hepatocellular carcinoma.Journal of liver cancer · 2026Review
- Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
- DNA methylation in melanoma immunotherapy: mechanisms and therapeutic opportunities.Clinical epigenetics · 2025Review
- Epigenomic heterogeneity as a source of tumour evolution.Nature reviews. Cancer · 2025Review
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- Review
- Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review).Oncology letters · 2024Review
- Population epigenetics: DNA methylation in the plant omics era.Plant physiology · 2024Article
- Single-cell Technologies Provide Novel Insights into Liver Physiology and Pathology.Journal of clinical and translational hepatology · 2024Review
- Shortcut barcoding and early pooling for scalable multiplex single-cell reduced-representation CpG methylation sequencing at single nucleotide resolution.Nucleic acids research · 2023Article
- Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer.Military Medical Research · 2023Review
- Advanced Omics Techniques for Understanding Cochlear Genome, Epigenome, and Transcriptome in Health and Disease.Biomolecules · 2023Review
- Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity.Clinical epigenetics · 2023Review
- Review
- Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications.Biomarker research · 2023Review
- Computational Methods for Single-cell DNA Methylome Analysis.Genomics, proteomics & bioinformatics · 2023Review
- Technologies and applications of single-cell DNA methylation sequencing.Theranostics · 2023Review
- The role of serum amyloid A1 in the adipogenic differentiation of human adipose-derived stem cells basing on single-cell RNA sequencing analysis.Stem cell research & therapy · 2022Article
- Single-Cell Sequencing and Its Applications in Liver Cancer.Frontiers in oncology · 2022Review
- Advances in single-cell sequencing technology in the field of hepatocellular carcinoma.Frontiers in genetics · 2022Review
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.