Single-Cell DNA Methylation Profiling: Technologies and Biological Applications

2018 ◽  
Vol 36 (9) ◽  
pp. 952-965 ◽  
Author(s):  
Ino D. Karemaker ◽  
Michiel Vermeulen
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Biological Applications ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

scholarly journals Introduction to Single-Cell DNA Methylation Profiling Methods

Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1013
Author(s):  
Jongseong Ahn ◽  
Sunghoon Heo ◽  
Jihyun Lee ◽  
Duhee Bang
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Gene Expression Regulation ◽  
Epigenetic Mechanism ◽  
Computational Data ◽  
Dna Methylation Profiling ◽  
Differentiation Gene ◽  
Experimental Strategies ◽  
Methylation Profiling ◽  
Blind Spots

DNA methylation is an epigenetic mechanism that is related to mammalian cellular differentiation, gene expression regulation, and disease. In several studies, DNA methylation has been identified as an effective marker to identify differences between cells. In this review, we introduce single-cell DNA-methylation profiling methods, including experimental strategies and approaches to computational data analysis. Furthermore, the blind spots of the basic analysis and recent alternatives are briefly described. In addition, we introduce well-known applications and discuss future development.

Forensic DNA methylation profiling from minimal traces: How low can we go?

2018 ◽  
Vol 33 ◽  
pp. 17-23 ◽  
Author(s):  
Jana Naue ◽  
Huub C.J. Hoefsloot ◽  
Ate D. Kloosterman ◽  
Pernette J. Verschure
Keyword(s):  
Dna Methylation ◽  
Forensic Dna ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

scholarly journals DNA Methylation Profiling of Uniparental Disomy Subjects Provides a Map of Parental Epigenetic Bias in the Human Genome

2016 ◽  
Vol 99 (3) ◽  
pp. 555-566 ◽  
Author(s):  
Ricky S. Joshi ◽  
Paras Garg ◽  
Noah Zaitlen ◽  
Tuuli Lappalainen ◽  
Corey T. Watson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Genome ◽  
Uniparental Disomy ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

scholarly journals Genome-wide DNA methylation profiling with MeDIP-seq using archived dried blood spots

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Nicklas H. Staunstrup ◽  
Anna Starnawska ◽  
Mette Nyegaard ◽  
Lene Christiansen ◽  
Anders L. Nielsen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Dried Blood Spots ◽  
Blood Spots ◽  
Genome Wide ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

DNA-methylation profiling during the promotion stage of mouse hepatocarcinogenesis

2008 ◽  
Vol 180 ◽  
pp. S122-S123
Author(s):  
Masaomi Kawai ◽  
Makoto Shibutani ◽  
U. Mami ◽  
Miwa Takahashi ◽  
Yasuaki Dewa ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

EPCO-17. METHYLATION ANALYSIS OF MATCHED PRIMARY AND RECURRENT IDHmt ASTROCYTOMA; AN UPDATE FROM THE GLIOMA LONGITUDINAL ANALYSIS NL (GLASS-NL) CONSORTIUM

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi5-vi5
Author(s):  
Wies Vallentgoed ◽  
Anneke Niers ◽  
Karin van Garderen ◽  
Martin van den Bent ◽  
Kaspar Draaisma ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Surgical Resection ◽  
Molecular Mechanisms ◽  
Relative Proportion ◽  
Low Grade ◽  
High Grade ◽  
Primary Tumors ◽  
Genome Wide ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

Abstract The GLASS-NL consortium, was initiated to gain insight into the molecular mechanisms underlying glioma evolution and to identify markers of progression in IDH-mutant astrocytomas. Here, we present the first results of genome-wide DNA-methylation profiling of GLASS-NL samples. 110 adult patients were identified with an IDH-mutant astrocytoma at first diagnosis. All patients underwent a surgical resection of the tumor at least twice, separated by at least 6 months (median 40.9 months (IQR: 24.0, 64.7). In 37% and 18% of the cases, patients were treated with radiotherapy or chemotherapy respectively, before surgical resection of the recurrent tumor. DNA-methylation profiling was done on 235 samples from 103 patients (102 1st, 101 2nd, 29 3rd, and 3 4th resection). Copy number variations were also extracted from these data. Methylation classes were determined according to Capper et al. Overall survival (OS) was measured from date of first surgery. Of all primary tumors, the methylation-classifier assigned 85 (87%) to the low grade subclass and 10 (10%) to the high grade subclass. The relative proportion of high grade tumors increased ~three-fold at tumor recurrence (32/101, 32%) and even further in the second recurrence (15/29, 52%). Methylation classes were prognostic, both in primary and recurrent tumors. The overall DNA-methylation levels of recurrent samples was lower than that of primary samples. This difference is explained by the increased number of high grade samples at recurrence, since near identical DNA-methylation levels were observed in samples that remained low grade. In an unsupervised analysis, DNA-methylation data derived from primary and first recurrence samples of individual patients mostly (79%) cluster together. Recurrent samples that do not cluster with their primary tumor, form a separate group with relatively low genome-wide DNA-methylation. Our data demonstrate that methylation profiling identifies a shift towards a higher grade at tumor progression coinciding with reduced genome-wide DNA-methylation levels.

Sign in / Sign up

Export Citation Format

Share Document