scholarly journals Cell-Type Specific DNA Methylation Patterns Define Human Breast Cellular Identity

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e52299 ◽  
Author(s):  
Petr Novak ◽  
Martha R. Stampfer ◽  
Jose L. Munoz-Rodriguez ◽  
James C. Garbe ◽  
Mathias Ehrich ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Breast ◽  
Cell Type ◽  
Cell Type Specific ◽  
Cellular Identity ◽  
Methylation Patterns

scholarly journals Cell type-specific DNA methylation patterns in the human breast

2008 ◽  
Vol 105 (37) ◽  
pp. 14076-14081 ◽  
Author(s):  
N. Bloushtain-Qimron ◽  
J. Yao ◽  
E. L. Snyder ◽  
M. Shipitsin ◽  
L. L. Campbell ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Breast ◽  
Cell Type ◽  
Cell Type Specific ◽  
Methylation Patterns

Neuronal cell‐type specific DNA methylation patterns of the Cacna1c gene

2012 ◽  
Vol 31 (2) ◽  
pp. 89-95 ◽  
Author(s):  
Masaki Nishioka ◽  
Takafumi Shimada ◽  
Miki Bundo ◽  
Wataru Ukai ◽  
Eri Hashimoto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neuronal Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Methylation Patterns

Genome-Wide DNA Methylation Profiling of Hematopoietic Stem and Progenitor Cells Reveals Over-Representation of ETS Transcrition Factor Binding Sites

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 211-211
Author(s):  
Amber Hogart ◽  
Jens Lichtenberg ◽  
Subramanian Ajay ◽  
Elliott Margulies ◽  
David M. Bodine
Keyword(s):  
Dna Methylation ◽  
Transcription Factor ◽  
Cpg Islands ◽  
Hematopoietic Cells ◽  
Cell Type ◽  
Hematopoietic Stem ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Methylation Patterns

Abstract Abstract 211 The hematopoietic system is ideal for the study of epigenetic changes in primary cells because hematopoietic cells representing distinct stages of hematopoiesis can be enriched and isolated by differences in surface marker expression. DNA methylation is an essential epigenetic mark that is required for normal development. Conditional knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment have revealed that methylation is critical for long-term renewal and lineage differentiation of hematopoietic stem cells (Broske et al 2009, Trowbridge el al 2009). To better understand the role of DNA methylation in self-renewal and differentiation of hematopoietic cells, we characterized genome-wide DNA methylation in primary cells representing three distinct stages of hematopoiesis. We isolated mouse hematopoietic stem cells (HSC; Lin- Sca-1+ c-kit+), common myeloid progenitor cells (CMP; Lin- Sca-1- c-kit+), and erythroblasts (ERY; CD71+ Ter119+). Methyl Binding Domain Protein 2 (MBD2) is an endogenous reader of DNA methylation that recognizes DNA with a high concentration of methylated CpG residues. Recombinant MBD2 enrichment of DNA followed by massively-parallel sequencing was used to map and compare genome-wide DNA methylation patterns in HSC, CMP and ERY. Two biological replicates were sequenced for each cell type with total read counts ranging from 32,309,435–46,763,977. Model-based analysis of ChIP Seq (MACS) with a significance cutoff of p<10−5 was used to determine statistically significant peaks of methylation in each replicate. Globally, the number of methylation peaks was highest in HSC (85,797peaks), lower in CMP (50,638 peaks), and lowest in ERY (27,839 peaks). Comparison of the peaks in HSC, CMP and ERY revealed that only 2% of the peaks in CMP or ERY are absent in HSC indicating that the vast majority of methylation in HSC is lost during differentiation. Comparison of methylation with genomic features revealed that CpG islands associated with promoters are hypomethylated, while many non-promoter CpG islands are methylated. Furthermore, methylation of non-promoter associated CpG islands occurs infrequently in cell-type specific peaks but is more abundant in common methylation peaks. When the DNA methylation patterns were compared to mRNA expression, we found that as expected, proximal promoter sequences of expressed genes were hypomethylated in all three cell types, while methylation in the gene body positively correlated with gene expression in HSC and CMP. Utilizing de novo motif discovery we found a subset of transcription factor consensus binding motifs that were overrepresented in methylated sequences. Motifs for several ETS transcription factors, including GABPalpha and ELF1 were found to be overrepresented in cell-type specific as well as common methylated regions. Other transcription factor consensus sites, such as the NFAT factors involved in T-cell activation, were specifically overrepresented in the methylated promoter regions of CMP and ERY. Comparison of our methylation data with the occupancy of hematopoietic transcription factors in the HPC7 cell line, which is similar to CMP (Wilson et al 2010), revealed a significant anti-correlation between DNA methylation and the binding of Fli1, Lmo2, Lyl1, Runx1, and Scl. Our genome-wide survey provides new insights into the role of DNA methylation in hematopoiesis. Firstly, the methylation of CpG islands is associated with the most primitive hematopoietic cells and is unlikely to drive hematopoietic differentiation. We feel that the elevated genome-wide DNA methylation in HSC compared to CMP and ERY, combined with the positive association between gene body methylation and gene expression demonstrates that DNA methylation is a mark of cellular plasticity in HSC. Finally, the finding that transcription factor binding sites are over represented in the methylated sequences of the genome leads us to conclude that DNA methylation modulates key hematopoietic transcription factor programs that regulate hematopoiesis. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Differential DNA methylation patterns of homeobox genes in proximal and distal colon epithelial cells

2016 ◽  
Vol 48 (4) ◽  
pp. 257-273 ◽  
Author(s):  
Alan Barnicle ◽  
Cathal Seoighe ◽  
Aaron Golden ◽  
John M. Greally ◽  
Laurence J. Egan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Epithelial Cells ◽  
Distal Colon ◽  
Human Colon ◽  
Differential Methylation ◽  
Cell Type ◽  
Cell Type Specific ◽  
Inflammatory Bowel ◽  
Methylation Patterns

Region and cell-type specific differences in the molecular make up of colon epithelial cells have been reported. Those differences may underlie the region-specific characteristics of common colon epithelial diseases such as colorectal cancer and inflammatory bowel disease. DNA methylation is a cell-type specific epigenetic mark, essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. Little is known about any region-specific variations in methylation patterns in human colon epithelial cells. Using purified epithelial cells and whole biopsies ( n = 19) from human subjects, we generated epigenome-wide DNA methylation data (using the HELP-tagging assay), comparing the methylation signatures of the proximal and distal colon. We identified a total of 125 differentially methylated sites (DMS) mapping to transcription start sites of protein-coding genes, most notably several members of the homeobox ( HOX) family of genes. Patterns of differential methylation were validated with MassArray EpiTYPER. We also examined DNA methylation in whole biopsies, applying a computational technique to deconvolve variation in methylation within cell types and variation in cell-type composition across biopsies. Including inferred epithelial proportions as a covariate in differential methylation analysis applied to the whole biopsies resulted in greater overlap with the results obtained from purified epithelial cells compared with when the covariate was not included. Results obtained from both approaches highlight region-specific methylation patterns of HOX genes in colonic epithelium. Regional variation in methylation patterns has implications for the study of diseases that exhibit regional expression patterns in the human colon, such as inflammatory bowel disease and colorectal cancer.

scholarly journals Virtual methylome dissection facilitated by single-cell analyses

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Liduo Yin ◽  
Yanting Luo ◽  
Xiguang Xu ◽  
Shiyu Wen ◽  
Xiaowei Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Nonnegative Matrix ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Cell Type ◽  
Mixed Cell ◽  
Numerous Cell ◽  
Cell Type Specific ◽  
Methylation Patterns

Abstract Background Numerous cell types can be identified within plant tissues and animal organs, and the epigenetic modifications underlying such enormous cellular heterogeneity are just beginning to be understood. It remains a challenge to infer cellular composition using DNA methylomes generated for mixed cell populations. Here, we propose a semi-reference-free procedure to perform virtual methylome dissection using the nonnegative matrix factorization (NMF) algorithm. Results In the pipeline that we implemented to predict cell-subtype percentages, putative cell-type-specific methylated (pCSM) loci were first determined according to their DNA methylation patterns in bulk methylomes and clustered into groups based on their correlations in methylation profiles. A representative set of pCSM loci was then chosen to decompose target methylomes into multiple latent DNA methylation components (LMCs). To test the performance of this pipeline, we made use of single-cell brain methylomes to create synthetic methylomes of known cell composition. Compared with highly variable CpG sites, pCSM loci achieved a higher prediction accuracy in the virtual methylome dissection of synthetic methylomes. In addition, pCSM loci were shown to be good predictors of the cell type of the sorted brain cells. The software package developed in this study is available in the GitHub repository (https://github.com/Gavin-Yinld). Conclusions We anticipate that the pipeline implemented in this study will be an innovative and valuable tool for the decoding of cellular heterogeneity.

WITHDRAWN: Neuronal cell-type specific DNA methylation patterns of the Cacna1cgene

2013 ◽  
Author(s):  
Masaki Nishioka ◽  
Takafumi Shimada ◽  
Miki Bundo ◽  
Wataru Ukai ◽  
Eri Hashimoto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neuronal Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Methylation Patterns

Locus-wide detection of cell type specific DNA methylation patterns using comparative methyl-CpG-Immunoprecipitation (MCIp)

2008 ◽  
Vol 2008 (Spring) ◽  
Author(s):  
Christian Schmidl ◽  
Maja Klug ◽  
Tina Böld ◽  
Petra Hoffmann ◽  
Matthias Edinger ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cell Type ◽  
Cell Type Specific ◽  
Methylation Patterns

scholarly journals Low Replicative Stress Triggers Cell-Type Specific Inheritable Advanced Replication Timing

2021 ◽  
Vol 22 (9) ◽  
pp. 4959
Author(s):  
Lilas Courtot ◽  
Elodie Bournique ◽  
Chrystelle Maric ◽  
Laure Guitton-Sert ◽  
Miguel Madrid-Mencía ◽  
...  
Keyword(s):  
Replication Timing ◽  
Replication Stress ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Replicative Stress ◽  
Daughter Cells ◽  
Origin Activation ◽  
Cell Type Specific ◽  
Cellular Identity ◽  
Dna Replication Timing

DNA replication timing (RT), reflecting the temporal order of origin activation, is known as a robust and conserved cell-type specific process. Upon low replication stress, the slowing of replication forks induces well-documented RT delays associated to genetic instability, but it can also generate RT advances that are still uncharacterized. In order to characterize these advanced initiation events, we monitored the whole genome RT from six independent human cell lines treated with low doses of aphidicolin. We report that RT advances are cell-type-specific and involve large heterochromatin domains. Importantly, we found that some major late to early RT advances can be inherited by the unstressed next-cellular generation, which is a unique process that correlates with enhanced chromatin accessibility, as well as modified replication origin landscape and gene expression in daughter cells. Collectively, this work highlights how low replication stress may impact cellular identity by RT advances events at a subset of chromosomal domains.

scholarly journals Calling differential DNA methylation at cell-type resolution: addressing misconceptions and best practices

2021 ◽  
Author(s):  
Elior Rahmani ◽  
Brandon Jew ◽  
Regev Schweiger ◽  
Brooke Rhead ◽  
Lindsey A. Criswell ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Best Practices ◽  
Regression Model ◽  
Association Studies ◽  
Composition Analysis ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Interaction Terms ◽  
Mathematical Explanations ◽  
Cell Type Specific

AbstractWe benchmarked two approaches for the detection of cell-type-specific differential DNA methylation: Tensor Composition Analysis (TCA) and a regression model with interaction terms (CellDMC). Our experiments alongside rigorous mathematical explanations show that TCA is superior over CellDMC, thus resolving recent criticisms suggested by Jing et al. Following misconceptions by Jing and colleagues with modelling cell-type-specificity and the application of TCA, we further discuss best practices for performing association studies at cell-type resolution. The scripts for reproducing all of our results and figures are publicly available at github.com/cozygene/CellTypeSpecificMethylationAnalysis.

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