Gene insulation. Part II: natural strategies in vertebrates

2010 ◽  
Vol 88 (6) ◽  
pp. 885-898 ◽  
Author(s):  
Michèle Amouyal
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Protein Interactions ◽  
Dna Looping ◽  
Chromatin Domain ◽  
Trna Genes ◽  
Binding Factor ◽  
Genomic Environment ◽  
Nuclear Structures ◽  
Definition Of

The way a gene is insulated from its genomic environment in vertebrates is not basically different from what is observed in yeast and Drosophila (preceding article in this issue). If the formation of a looped chromatin domain, whether generated by attachment to the nuclear matrix or not, has become a classic way to confine an enhancer to a specific genomic domain and to coordinate, sequentially or simultaneously, gene expression in a given program, its role has been extended to new networks of genes or regulators within the same gene. A wider definition of the bases of the chromatin loops (nonchromosomal nuclear structures or genomic interacting elements) is also available. However, whereas insulation in Drosophila is due to a variety of proteins, in vertebrates insulators are still practically limited to CTCF (the CCCTC-binding factor), which appears in all cases to be the linchpin of an architecture that structures the assembly of DNA–protein interactions for gene regulation. As in yeast and Drosophila, the economy of means is the rule and the same unexpected diversion of known transcription elements (active or poised RNA polymerases, TFIIIC elements out of tRNA genes, permanent histone replacement) is observed, with variants peculiar to CTCF. Thus, besides structuring DNA looping, CTCF is a barrier to DNA methylation or interferes with all sorts of transcription processes, such as that generating heterochromatin.

scholarly journals Single-molecule simultaneous profiling of DNA methylation and DNA-protein interactions with Nanopore-DamID

2021 ◽  
Author(s):  
Seth W Cheetham ◽  
Yohaann M.A Jafrani ◽  
Stacey B Andersen ◽  
Natasha Jansz ◽  
Adam D Ewing ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Single Molecule ◽  
Protein Interactions ◽  
Cytosine Methylation ◽  
Cpg Methylation ◽  
Eukaryotic Gene Expression ◽  
Eukaryotic Gene ◽  
Transcriptional Start Sites ◽  
Dna Protein Interactions

DNA-protein interactions and cytosine methylation control eukaryotic gene expression. Here, we present an approach to simultaneously detect cytosine methylation and DNA-protein interactions from single molecules, through selective sequencing of adenine-labelled DNA. Applying this approach to LaminB1-associated heterochromatin domains, we identify strict CpG methylation maintenance at transcriptional start sites amid a generalised relaxation of methylation, potentially to prevent ectopic aberrant heterochromatic gene expression.

Role of small nuclear RNAs in eukaryotic gene expression

2013 ◽  
Vol 54 ◽  
pp. 79-90 ◽  
Author(s):  
Saba Valadkhan ◽  
Lalith S. Gunawardane
Keyword(s):  
Gene Expression ◽  
Protein Interactions ◽  
Rna Stability ◽  
Splice Sites ◽  
Branch Site ◽  
Small Nuclear Rnas ◽  
Eukaryotic Gene Expression ◽  
Eukaryotic Gene ◽  
Rna Biogenesis

Eukaryotic cells contain small, highly abundant, nuclear-localized non-coding RNAs [snRNAs (small nuclear RNAs)] which play important roles in splicing of introns from primary genomic transcripts. Through a combination of RNA–RNA and RNA–protein interactions, two of the snRNPs, U1 and U2, recognize the splice sites and the branch site of introns. A complex remodelling of RNA–RNA and protein-based interactions follows, resulting in the assembly of catalytically competent spliceosomes, in which the snRNAs and their bound proteins play central roles. This process involves formation of extensive base-pairing interactions between U2 and U6, U6 and the 5′ splice site, and U5 and the exonic sequences immediately adjacent to the 5′ and 3′ splice sites. Thus RNA–RNA interactions involving U2, U5 and U6 help position the reacting groups of the first and second steps of splicing. In addition, U6 is also thought to participate in formation of the spliceosomal active site. Furthermore, emerging evidence suggests additional roles for snRNAs in regulation of various aspects of RNA biogenesis, from transcription to polyadenylation and RNA stability. These snRNP-mediated regulatory roles probably serve to ensure the co-ordination of the different processes involved in biogenesis of RNAs and point to the central importance of snRNAs in eukaryotic gene expression.

DNA Methylation Inhibites ANXA1 Gene Expression in Nasopharyngeal Carcinoma Cell Lines*

2009 ◽  
Vol 36 (10) ◽  
pp. 1319-1326 ◽  
Author(s):  
Shuang-Xiang TAN ◽  
Rui-Cheng HU ◽  
Ai-Guo DAI ◽  
Cen-E TANG ◽  
Hong YI ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Nasopharyngeal Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Nasopharyngeal Carcinoma Cell ◽  
Carcinoma Cell Lines

scholarly journals Epigenetic Changes During Mechanically Induced Osteogenic Lineage Commitment

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Julia C. Chen ◽  
Mardonn Chua ◽  
Raymond B. Bellon ◽  
Christopher R. Jacobs
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Shear Stress ◽  
Fluid Shear Stress ◽  
Methylation Status ◽  
Lineage Commitment ◽  
Fluid Shear ◽  
Osteogenic Lineage ◽  
Osteogenic Markers ◽  
Heterochromatin Structure

Osteogenic lineage commitment is often evaluated by analyzing gene expression. However, many genes are transiently expressed during differentiation. The availability of genes for expression is influenced by epigenetic state, which affects the heterochromatin structure. DNA methylation, a form of epigenetic regulation, is stable and heritable. Therefore, analyzing methylation status may be less temporally dependent and more informative for evaluating lineage commitment. Here we analyzed the effect of mechanical stimulation on osteogenic differentiation by applying fluid shear stress for 24 hr to osteocytes and then applying the osteocyte-conditioned medium (CM) to progenitor cells. We analyzed gene expression and changes in DNA methylation after 24 hr of exposure to the CM using quantitative real-time polymerase chain reaction and bisulfite sequencing. With fluid shear stress stimulation, methylation decreased for both adipogenic and osteogenic markers, which typically increases availability of genes for expression. After only 24 hr of exposure to CM, we also observed increases in expression of later osteogenic markers that are typically observed to increase after seven days or more with biochemical induction. However, we observed a decrease or no change in early osteogenic markers and decreases in adipogenic gene expression. Treatment of a demethylating agent produced an increase in all genes. The results indicate that fluid shear stress stimulation rapidly promotes the availability of genes for expression, but also specifically increases gene expression of later osteogenic markers.

scholarly journals DNA methylation and gene expression integration in cardiovascular disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guillermo Palou-Márquez ◽  
Isaac Subirana ◽  
Lara Nonell ◽  
Alba Fernández-Sanlés ◽  
Roberto Elosua
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Cardiovascular Diseases ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Risk Function ◽  
Predictive Biomarkers ◽  
Independent Study ◽  
Cell Type

Abstract Background The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. Results Four independent latent factors (9, 19, 21—only in women—and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. Conclusions Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.

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