scholarly journals A novel core promoter element induces bidirectional transcription in CpG island

2017 ◽  
Author(s):  
Amin Mahpour ◽  
Dominic Smiraglia ◽  
Benjamin S. Scruggs ◽  
Irwin H. Gelman ◽  
Toru Ouchi
Keyword(s):  
Gene Expression ◽  
Cpg Island ◽  
Core Promoter ◽  
Consensus Sequence ◽  
Cpg Islands ◽  
Housekeeping Genes ◽  
Bidirectional Transcription ◽  
Evolutionarily Conserved ◽  
Active Research ◽  
Activate Gene

AbstractHow TATA-less promoters such as those within CpG islands (CGI) control gene expression is still a subject of active research. Here, we have identified the “CGCG element”, a ten-base pair motif with a consensus sequence of TCTCGCGAGA present in a group of promoter-associated CGIs of ribosomal protein and housekeeping genes. This element is evolutionarily conserved in vertebrates, found in DNase-accessible regions and employs RNA polymerase 2 to activate gene expression. Through extensive analysis of several endogenous promoters, we demonstrate that this element activates bidirectional transcription through divergent start sites. Methylation of this element abrogates the associated promoter activity. When coincident with a TATA-box directional transcription remains CGCG-dependent. Because the CGCG element is sufficient to drive transcription, we propose that its unmethylated form functions as a core promoter of TATA-less CGI-associated promoters.

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 653-653 ◽  
Author(s):  
Ying Qu ◽  
Andreas Lennartsson ◽  
Verena I. Gaidzik ◽  
Stefan Deneberg ◽  
Sofia Bengtzén ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Features of Methylation and Gene Expression in the Promoter-Associated CpG Islands Using Human Methylome Data

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Xin Du ◽  
Leng Han ◽  
An-Yuan Guo ◽  
Zhongming Zhao
Keyword(s):  
Gene Expression ◽  
Methylation Level ◽  
Cpg Island ◽  
Expression Patterns ◽  
Cpg Islands ◽  
Gc Content ◽  
Gene Markers ◽  
A Genome ◽  
Genome Level ◽  
Lower Ratio

CpG islands are typically located in the 5′end of genes and considered as gene markers because they play important roles in gene regulation via epigenetic change. In this study, we compared the features of CpG islands identified by several major algorithms by setting the parameter cutoff values in order to obtain a similar number of CpG islands in a genome. This approach allows us to systematically compare the methylation and gene expression patterns in the identified CpG islands. We found that Takai and Jones’ algorithm tends to identify longer CpG islands but with weaker CpG island features (e.g., lower GC content and lower ratio of the observed over expected CpGs) and higher methylation level. Conversely, the CpG clusters identified by Hackenberg et al.’s algorithm using stringent criteria are shorter and have stronger features and lower methylation level. In addition, we used the genome-wide base-resolution methylation profile in two cell lines to show that genes with a lower methylation level at the promoter-associated CpG islands tend to express in more tissues and have stronger expression. Our results validated that the DNA methylation of promoter-associated CpG islands suppresses gene expression at the genome level.

CpG islands in genes showing tissue-specific expression

1990 ◽  
Vol 326 (1235) ◽  
pp. 207-215 ◽  
Keyword(s):  
Gene Expression ◽  
Cpg Islands ◽  
Housekeeping Genes ◽  
Tissue Expression ◽  
Proximal Promoter ◽  
Cell Type ◽  
Promoter Regions ◽  
Specific Expression ◽  
Tissue Specific ◽  
Single Cell Type

Patterns of DNA methylation at GpG dinucleotides and their relations with gene expression are complex. Methylation-free CpG clusters, so-called HTF islands, are most often associated with the promoter regions of housekeeping genes, whereas genes expressed in a single-cell type are usually deficient in these sequences. However, in the human carbonic anhydrase (CA) gene family, both the ubiquitously expressed CAII and the muscle specific CAIII appear to have such CpG islands although erythrocyte-specific CAI does not. The CAII island is quantitatively more CpG rich than that of CAIII, with a CpG :GpC ratio of 0.94 compared with 0.82 for CAIII. Estimation of CpG:GpC ratios in the proximal-promoter regions of 44 vertebrate genes suggest that 40% of genes with tissue-specific or limited tissue distribution may show methylation-free CpG clusters in their promoter regions. In many cases the CpG:GpC ratio is less than that found in housekeeping genes and this may reflect variation in the interaction of CpG clusters with regulatory factors that define different patterns of tissue expression.

scholarly journals Small Activating RNAs: Towards the Development of New Therapeutic Agents and Clinical Treatments

Cells ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 591
Author(s):  
Hossein Ghanbarian ◽  
Shahin Aghamiri ◽  
Mohamad Eftekhary ◽  
Nicole Wagner ◽  
Kay-Dietrich Wagner
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Cultured Cells ◽  
Exogenous Dna ◽  
Evolutionarily Conserved ◽  
Rna Activation ◽  
Endogenous Genes ◽  
Cellular Machinery ◽  
Eukaryotic Organisms ◽  
Activate Gene

Small double-strand RNA (dsRNA) molecules can activate endogenous genes via an RNA-based promoter targeting mechanism. RNA activation (RNAa) is an evolutionarily conserved mechanism present in diverse eukaryotic organisms ranging from nematodes to humans. Small activating RNAs (saRNAs) involved in RNAa have been successfully used to activate gene expression in cultured cells, and thereby this emergent technique might allow us to develop various biotechnological applications, without the need to synthesize hazardous construct systems harboring exogenous DNA sequences. Accordingly, this thematic issue aims to provide insights into how RNAa cellular machinery can be harnessed to activate gene expression leading to a more effective clinical treatment of various diseases.

Genome Wide Study of DNA Methylation In AML

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3618-3618
Author(s):  
Marwa Saied ◽  
Sabah Khaled ◽  
Thomas Down ◽  
Jacek Marzec ◽  
Paul Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Promoter Regions ◽  
Gene Body Methylation ◽  
Normal Bone ◽  
Genome Wide

Abstract Abstract 3618 DNA methylation is the most stable epigenetic modification and has a major role in cancer initiation and progression. The two main aims for this research were, firstly, to use the genome wide analysis of DNA methylation to better understand the development of acute myeloid leukemia (AML). The second aim was to detect differentially methylated genes/regions between certain subtypes of AML and normal bone marrow (NBM). We used the methylated DNA immunoprecipitation technique followed by high-throughput sequencing by Illumina Genome Analyser II (MeDIP -seq) for 9 AML samples for which ethical approval has been obtained. The selected leukemias included three with the t(8; 21), three with the t(15; 17) translocations and three with normal karyotypes (NK). The control samples were 3 normal bone marrows (NBMs) from healthy donors. The number of reads generated from Illumina ranged between 18– 20 million paired-end reads/lane with a good base quality from both ends (base quality > 30 represented 75%-85% of reads). The reads were aligned using 2 algorithms (Maq and Bowtie) and the methylation analysis was performed by Batman software (Bayesian Tool for Methylation Analysis). The creation of this genome-wide methylation map for AML permits the examination of the patterns for key genetic elements. Investigation of the 35,072 promoter regions identified 80 genes, which showed a significant differential methylation levels in leukemic cases in comparison to NBM; consistently high methylation levels in leukaemia were detected in the promoters of 70 genes e.g. DPP6, ID4, DCC, whereas high methylation levels in NBM, lost in leukaemia was observed in 10 genes e.g. ATF4. For each AML subtype, we also identified significant differentially methylated promoter regions e.g. PAX1 for t(8; 21), GRM7 for t(15; 17), NPM2 for NK. An analysis of gene body methylation identified 49 genes with significantly higher methylation in AML in comparison to NBM e.g. MYOD1 and 31 genes with a higher methylation in NBMs than AML e.g. GNG8. A similar analysis of 23,600 CpG islands identified 400 CpG islands with significant differential methylation levels between leukaemia and NBMs (212 CpG islands were found to have significantly increased methylation in leukaemia and 188 CpG islands had significantly higher methylation in NBMs). The pattern of methylation in CpG island “shores” (2 KB from either side of each CpG island) has been investigated and 312 CpG island shores showed a higher methylation in leukaemia and 88 CpG shores had a significant increase methylation levels in NBMs. This genome wide methylation map has been validated by using direct bisulfite sequencing of the regions identified above (Spearman r= 0.8, P <0.0001) and also by using Illumina Infinium assay (Spearman r= 0.7 P <0.0001) which interrogates regions at single representative CpGs. Comparison of previous array based gene expression data with this methylation map revealed a significant negative correlation between promoter methylation and gene expression (Pearson r= -0.9, P< 0.0001) while, gene body methylation showed a small negative correlation with gene expression, that was found in genes of CpG density >3% (Pearson r= -0.3, P< 0.0001). Conclusion: we have established a high-resolution (100bp) map of DNA methylation in AML and thus identified a novel list of genes, which have significantly differential methylation levels in AML. Disclosures: No relevant conflicts of interest to declare.

CpG-island-based annotation and analysis of human housekeeping genes

2020 ◽  
Author(s):  
Le Zhang ◽  
Zichun Dai ◽  
Jun Yu ◽  
Ming Xiao
Keyword(s):  
Gene Expression Regulation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Enrichment Analysis ◽  
Housekeeping Genes ◽  
Density Variation ◽  
Individual Gene ◽  
Go Enrichment ◽  
Lineage Specificity ◽  
Gene Structures

Abstract By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CpG islands (CGIs), their methylation states, CpG spacing and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be explained at individual gene and gene-family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI) and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA box on HK genes, remains to be elucidated. First, this study introduces such a problem-solving protocol for human-genome annotation, which is based on a combination of GTEx, JBLA and Gene Ontology (GO) analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; the HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic based on GO enrichment analysis. Finally, we demonstrate that Hadoop MapReduce-based MR-JBLA algorithm is more efficient than the original JBLA in k-mer counting and CGI-associated gene analysis.

DNA Methylation Independent Silencing of the RARα Gene Expression in Acute Myeloid Leukemia.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2225-2225
Author(s):  
Annegret Glasow ◽  
Angela Barrett ◽  
Manuel Boix Chornet ◽  
Rajeev Gupta ◽  
Da-cheng Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Retinoic Acid ◽  
Cell Lines ◽  
Cpg Island ◽  
Synergistic Effects ◽  
Cpg Islands ◽  
Regulatory Region ◽  
Histone H3 ◽  
Acute Myeloid

Abstract All-trans-retinoic acid (ATRA) and the gene encoding retinoic acid receptor-α (RARα) have been implicated in the pathogenesis and treatment of acute promyelocytic leukemia (APL). Nevertheless, the role of these molecules in the pathogenesis and therapy of non-APL acute myeloid leukemias (AMLs) remains unclear. Previously we have shown that expression of the ATRA-inducible RARα2 isoform is downregulated in a variety of AML cell lines and increases with hematopoietic differentiation along the myelomonocytic lineage. Using quantitative real-time PCR we have now investigated expression of the RARα gene in primary AML cells (n=23) and report that as in AML cell lines the levels of RARα2 mRNAs are markedly reduced (by 48 fold in APL, p≤0.05, and by 52 fold in non-APL AML, p≤0.01) relative to cord blood (CB) derived CD33 (or CD34) positive cell population (n=4). However, in contrast to the AML cell lines and normal hematopoietic progenitors, the expression of the RARα1 isoform was also significantly reduced in primary AML samples (up to 26 fold, p≤0.05). Examination of potential mechanisms underlying the silencing of the RARα gene expression in AML revealed that the RARα2 promoter possesses two small CpG islands that are fully methylated in all AML cell lines examined. Consistent with the expression pattern of RARα1 a single CpG island in the RARα1 promoter region was unmethylated in all these samples. As expected from such results expression of RARα2, but not RARα1, could be stimulated with a DNA demethylating agent 5-aza-2′deoxycytidine and synergistic effects between 5-aza-2′deoxycytidine and ATRA were observed on both RARα2 expression and cellular differentiation of APL and non-APL AML cell lines. Extending this analysis to clinical material we have surprisingly discovered that RARα1 and RARα2 CpG islands are unmethylated in all AML patient samples, including 3 APL cases, suggesting that DNA methylation may not play a significant role in silencing of the RARα gene expression in primary AML cells. Chromatin immunoprecipitation of the RARα2 regulatory region with antibodies to specific histone modifications revealed presence of other negatively acting chromatin states in primary AML samples (relative to normal CD33 positive CB cells), including decreased histone H3 acetylation as well as decreased di- and tri-methylation of histone H3 lysine 4. A possibility that microRNAs targeting sequences in the common 3′-UTR regions of the RARα1 and α2 isoforms may also contribute to silencing of both RARα1 and α2 expression in AML cannot be excluded. These results underscore the complexities of mechanisms that are responsible for silencing of gene expression in AML and support the notion that diminished RARα expression contributes to leukemogenesis.

scholarly journals Diversification of CpG-Island Promoters Revealed by Comparative Analysis Between Human and Rhesus Monkey Genomes

2020 ◽  
Vol 31 (7-8) ◽  
pp. 240-251
Author(s):  
Saki Aoto ◽  
Mayu Fushimi ◽  
Kei Yura ◽  
Kohji Okamura
Keyword(s):  
Rhesus Monkey ◽  
Cpg Island ◽  
Cpg Islands ◽  
Housekeeping Genes ◽  
Transcription Start ◽  
Cpg Dinucleotides ◽  
Transcription Start Sites ◽  
Cpg Sites ◽  
Mammalian Genomes ◽  
Ncbi Refseq

Abstract While CpG dinucleotides are significantly reduced compared to other dinucleotides in mammalian genomes, they can congregate and form CpG islands, which localize around the 5ʹ regions of genes, where they function as promoters. CpG-island promoters are generally unmethylated and are often found in housekeeping genes. However, their nucleotide sequences and existence per se are not conserved between humans and mice, which may be due to evolutionary gain and loss of the regulatory regions. In this study, human and rhesus monkey genomes, with moderately conserved sequences, were compared at base resolution. Using transcription start site data, we first validated our methods’ ability to identify orthologous promoters and indicated a limitation using the 5ʹ end of curated gene models, such as NCBI RefSeq, as their transcription start sites. We found that, in addition to deamination mutations, insertions and deletions of bases, repeats, and long fragments contributed to the mutations of CpG dinucleotides. We also observed that the G + C contents tended to change in CpG-poor environments, while CpG content was altered in G + C-rich environments. While loss of CpG islands can be caused by gradual decreases in CpG sites, gain of these islands appear to require two distinct nucleotide altering steps. Taken together, our findings provide novel insights into the process of acquisition and diversification of CpG-island promoters in vertebrates.

scholarly journals Characteristics of DNA methylation and gene expression in regulatory features on the Infinium 450k Beadchip

2015 ◽  
Author(s):  
David Martino ◽  
Richard Saffery
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Association Studies ◽  
Cpg Islands ◽  
Transcriptional Unit ◽  
Gene Body ◽  
Genomic Context ◽  
Methylation Array ◽  
The Relationship

Understanding the relationship between variations in DNA methylation and gene expression has been challenging. Evidence suggests the function of DNA methylation may vary with genomic context, and few consistent rules linking methylation to expression have been noted. For array-based studies, the content of current DNA methylation array platforms provide broad coverage of the genome but target only a fraction of the potentially methylated CG dinucleotides. A better understanding of the interplay between DNA methylation and gene expression is beneficial for users of these platforms, and may aid with candidate prioritization in epigenome-wide association studies (EWAS). To address this we examined the relationship between DNA methylation levels and gene expression in primary T-lymphocytes at discreet genomic regions around the transcriptional unit (Promoters, gene body, untranslated regions) and at CpG island-associated regions (islands, shores and shelves), stratifying by high and low expressed genes. As anticipated we found evidence that DNA methylation at CpG sites near promoter regions are tightly correlated with gene expression in both the stably expressed and developmentally regulated genes, however this is dependent on CpG density. DNA methylation within the gene body was not consistently associated with changes in gene expression. CpG islands and island shores exhibited strong correlations with gene expression, but this was not true for island shelves. We found these relationships were generally preserved at both dynamic and steady state genes, with some notable exceptions. In combination these insights may be useful for prioritising candidates identified in epigenome-wide association studies for subsequent functional studies.

scholarly journals Bidding the CpG island goodbye

eLife ◽  
2013 ◽  
Vol 2 ◽  
Author(s):  
John M Greally
Keyword(s):  
Cpg Island ◽  
Cpg Islands ◽  
Regulatory Elements ◽  
Methylated Dna ◽  
Evolutionarily Conserved

Experiments on seven vertebrates suggest that identifying the locations of islands of non-methylated DNA provides more insights into evolutionarily-conserved epigenetic regulatory elements than studies of CpG islands.

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