scholarly journals DNA Methylation Landscape Reflects the Spatial Organization of Chromatin in Different Cells

2016 ◽  
Author(s):  
Ling Zhang ◽  
Wen Jun Xie ◽  
Sirui Liu ◽  
Luming Meng ◽  
Chan Gu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Long Range ◽  
Power Law ◽  
Chromatin Structure ◽  
Spatial Organization ◽  
Large Set ◽  
Sequencing Data ◽  
Scaling Exponents ◽  
Cell Class ◽  
Partially Methylated

AbstractThe relation between DNA methylation and chromatin structure is still largely unknown. By analyzing a large set of sequencing data, we observed a long-range power law correlation of DNA methylation with cell-class-specific scaling exponents in the range of thousands to millions of base pairs. We showed such cell-class-specific scaling exponents are caused by different patchiness of DNA methylation in different cells. By modeling the chromatin structure using Hi-C data and mapping the methylation level onto the modeled structure, we demonstrated the patchiness of DNA methylation is related to chromatin structure. The scaling exponents of the power law correlation is thus a display of the spatial organization of chromatin. Besides, the local correlation of DNA methylation is associated with nucleosome positioning and different between partially-methylated-domain and non-partially-methylated-domain, suggesting their different chromatin structures at several nucleosomes level. Our study provides a novel view of the spatial organization of chromatin structure from a perspective of DNA methylation, in which both long-range and local correlations of DNA methylation along the genome reflect the spatial organization of chromatin.

THE ORTHOGONAL V-SYSTEM DETRENDED FLUCTUATION ANALYSIS

2011 ◽  
Vol 10 (02) ◽  
pp. 189-206 ◽  
Author(s):  
AIJING LIN ◽  
PENGJIAN SHANG ◽  
HUI MA
Keyword(s):  
Long Range ◽  
Power Law ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Smoothing Algorithm ◽  
Scaling Exponents ◽  
Long Range Correlations ◽  
Piecewise Function ◽  
Robust Techniques ◽  
Detrended Fluctuation

The Detrended Fluctuation Analysis (DFA) and its extensions (MF-DFA) have been proposed as robust techniques to determine possible long-range correlations in self-affine signals. However, many studies have reported the susceptibility of DFA to trends which give rise to spurious crossovers and prevent reliable estimations of the scaling exponents. Lately, several modifications of the DFA method have been reported with many different techniques for eliminating the monotonous and periodic trends. In this study, a smoothing algorithm based on the Orthogonal V-system (OVS) is proposed to minimize the effect of power-law trends, periodic trends, assembled trends and piecewise function trends. The effectiveness of the new method is demonstrated on monofractal data and multifractal data corrupted with different trends.

scholarly journals Long-range Temporal Correlations in the Broadband Resting state Activity of the Human Brain revealed by Neuronal Avalanches

2020 ◽  
Author(s):  
Fabrizio Lombardi ◽  
Oren Shriki ◽  
Hans J. Herrmann ◽  
Lucilla de Arcangelis
Keyword(s):  
Long Range ◽  
Power Law ◽  
Resting State ◽  
Brain Activity ◽  
Neural Systems ◽  
Scaling Exponents ◽  
Long Range Correlations ◽  
Temporal Correlations ◽  
Neuronal Avalanches ◽  
The Brain

AbstractResting-state brain activity is characterized by the presence of neuronal avalanches showing absence of characteristic size. Such evidence has been interpreted in the context of criticality and associated with the normal functioning of the brain. At criticality, a crucial role is played by long-range power-law correlations. Thus, to verify the hypothesis that the brain operates close to a critical point and consequently assess deviations from criticality for diagnostic purposes, it is of primary importance to robustly and reliably characterize correlations in resting-state brain activity. Recent works focused on the analysis of narrow band electroencephalography (EEG) and magnetoencephalography (MEG) signal amplitude envelope, showing evidence of long-range temporal correlations (LRTC) in neural oscillations. However, this approach is not suitable for assessing long-range correlations in broadband resting-state cortical signals. To overcome such limitation, here we propose to characterize the correlations in the broadband brain activity through the lens of neuronal avalanches. To this end, we consider resting-state EEG and long-term MEG recordings, extract the corresponding neuronal avalanche sequences, and study their temporal correlations. We demonstrate that the broadband resting-state brain activity consistently exhibits long-range power-law correlations in both EEG and MEG recordings, with similar values of the scaling exponents. Importantly, although we observe that avalanche size distribution depends on scale parameters, scaling exponents characterizing long-range correlations are quite robust. In particular, they are independent of the temporal binning (scale of analysis), indicating that our analysis captures intrinsic characteristics of the underlying dynamics. Because neuronal avalanches constitute a fundamental feature of neural systems with universal characteristics, the proposed approach may serve as a general, systems- and experiment-independent procedure to infer the existence of underlying long-range correlations in extended neural systems, and identify pathological behaviors in the complex spatio-temporal interplay of cortical rhythms.

CORRELATIONS OF PITCHES IN MUSIC

Fractals ◽  
1996 ◽  
Vol 04 (04) ◽  
pp. 547-553 ◽  
Author(s):  
YU SHI
Keyword(s):  
Power Spectrum ◽  
Long Range ◽  
Power Law ◽  
Piano Music ◽  
Fundamental Principle ◽  
Mean Square ◽  
Scaling Exponents ◽  
One Dimensional ◽  
Mean Square Fluctuation ◽  
The Mean

We investigate correlations among pitches in several songs and pieces of piano music. Real values of tones are mapped to positions within a one-dimensional walk. The structure of music, such as beat, measure and stanza, are reflected in the change of scaling exponents of the mean square fluctuation. Usually the pitches within one beat are nearly random, while nontrivial correlations are found within duration around a measure; for longer duration the mean square fluctuation is nearly flat, indicating exact 1/f power spectrum. Some interesting features are observed. Correlations are also studied by treating different tones as different symbols. This kind of correlation cannot reflect the structure of music, though long-range power-law is also discovered. Our results support the viewpoint that the fundamental principle of music is the balance between repetition and contrast.

scholarly journals Extended power-law scaling of air permeabilities measured on a block of tuff

2012 ◽  
Vol 16 (1) ◽  
pp. 29-42 ◽  
Author(s):  
M. Siena ◽  
A. Guadagnini ◽  
M. Riva ◽  
S. P. Neuman
Keyword(s):  
Power Law ◽  
Structure Functions ◽  
Self Similarity ◽  
Scaling Exponents ◽  
Multi Scale ◽  
Sample Structure ◽  
Heavy Tailed ◽  
Non Gaussian ◽  
Nonlinear Fashion ◽  
Extended Power

Abstract. We use three methods to identify power-law scaling of multi-scale log air permeability data collected by Tidwell and Wilson on the faces of a laboratory-scale block of Topopah Spring tuff: method of moments (M), Extended Self-Similarity (ESS) and a generalized version thereof (G-ESS). All three methods focus on q-th-order sample structure functions of absolute increments. Most such functions exhibit power-law scaling at best over a limited midrange of experimental separation scales, or lags, which are sometimes difficult to identify unambiguously by means of M. ESS and G-ESS extend this range in a way that renders power-law scaling easier to characterize. Our analysis confirms the superiority of ESS and G-ESS over M in identifying the scaling exponents, ξ(q), of corresponding structure functions of orders q, suggesting further that ESS is more reliable than G-ESS. The exponents vary in a nonlinear fashion with q as is typical of real or apparent multifractals. Our estimates of the Hurst scaling coefficient increase with support scale, implying a reduction in roughness (anti-persistence) of the log permeability field with measurement volume. The finding by Tidwell and Wilson that log permeabilities associated with all tip sizes can be characterized by stationary variogram models, coupled with our findings that log permeability increments associated with the smallest tip size are approximately Gaussian and those associated with all tip sizes scale show nonlinear variations in ξ(q) with q, are consistent with a view of these data as a sample from a truncated version (tfBm) of self-affine fractional Brownian motion (fBm). Since in theory the scaling exponents, ξ(q), of tfBm vary linearly with q we conclude that nonlinear scaling in our case is not an indication of multifractality but an artifact of sampling from tfBm. This allows us to explain theoretically how power-law scaling of our data, as well as of non-Gaussian heavy-tailed signals subordinated to tfBm, are extended by ESS. It further allows us to identify the functional form and estimate all parameters of the corresponding tfBm based on sample structure functions of first and second orders.

scholarly journals PATH-11. PROSPECTIVE (EPI-)GENETIC CLASSIFICATION OF > 1,000 PEDIATRIC CNS TUMORS—THE MNP 2.0 STUDY

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii426-iii426
Author(s):  
Dominik Sturm ◽  
Felix Sahm ◽  
Felipe Andreiuolo ◽  
David Capper ◽  
Marco Gessi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Gene Panel ◽  
Cns Tumors ◽  
Lower Grade ◽  
High Grade ◽  
Sequencing Data ◽  
Cns Tumor ◽  
Gene Panel Sequencing ◽  
Tumor Entities ◽  
Panel Sequencing

Abstract The large variety of CNS tumor entities affecting children and adolescents, some of which are exceedingly rare, results in very diverging patient outcomes and renders accurate diagnosis challenging. To assess the diagnostic utility of routine DNA methylation-based CNS tumor classification and gene panel sequencing, the Molecular Neuropathology 2.0 study prospectively integrated these (epi-)genetic analyses with reference neuropathological diagnostics as an international trial for newly-diagnosed pediatric patients. In a four-year period, 1,215 patients with sufficient tissue were enrolled from 65 centers, receiving a reference neuropathological diagnosis according to the WHO classification in >97%. Using 10 FFPE sections as input, DNA methylation analysis was successfully performed in 95% of cases, of which 78% with sufficient tumor cell content were assigned to a distinct epigenetic tumor class. The remaining 22% did not match any of 82 represented classes, indicating novel rare tumor entities. Targeted gene panel sequencing of >130 genes performed for 96% of patients with matched blood samples detected diagnostically, prognostically, or therapeutically relevant somatic alterations in 48%. Germline DNA sequencing data indicated potential predisposition syndromes in ~10% of patients. Discrepant results by neuropathological and epigenetic classification (29%) were enriched in histological high-grade gliomas and implicated clinical relevance in 5% of all cases. Clinical follow-up suggests improved survival for some patients with high-grade glioma histology and lower-grade molecular profiles. Routine (epi-)genetic profiling at the time of primary diagnosis adds a valuable layer of information to neuropathological diagnostics and will improve clinical management of CNS tumors.

scholarly journals Impact of DNA methylation on 3D genome structure

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Diana Buitrago ◽  
Mireia Labrador ◽  
Juan Pablo Arcon ◽  
Rafael Lema ◽  
Oscar Flores ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Chromatin Structure ◽  
Chromatin Condensation ◽  
Genome Structure ◽  
Dna Methyltransferases ◽  
Model System ◽  
Structure And Function ◽  
3D Genome ◽  
Cellular Machinery ◽  
And Function

AbstractDetermining the effect of DNA methylation on chromatin structure and function in higher organisms is challenging due to the extreme complexity of epigenetic regulation. We studied a simpler model system, budding yeast, that lacks DNA methylation machinery making it a perfect model system to study the intrinsic role of DNA methylation in chromatin structure and function. We expressed the murine DNA methyltransferases in Saccharomyces cerevisiae and analyzed the correlation between DNA methylation, nucleosome positioning, gene expression and 3D genome organization. Despite lacking the machinery for positioning and reading methylation marks, induced DNA methylation follows a conserved pattern with low methylation levels at the 5’ end of the gene increasing gradually toward the 3’ end, with concentration of methylated DNA in linkers and nucleosome free regions, and with actively expressed genes showing low and high levels of methylation at transcription start and terminating sites respectively, mimicking the patterns seen in mammals. We also see that DNA methylation increases chromatin condensation in peri-centromeric regions, decreases overall DNA flexibility, and favors the heterochromatin state. Taken together, these results demonstrate that methylation intrinsically modulates chromatin structure and function even in the absence of cellular machinery evolved to recognize and process the methylation signal.

scholarly journals Power-law bounds for critical long-range percolation below the upper-critical dimension

2021 ◽  
Author(s):  
Tom Hutchcroft
Keyword(s):  
Long Range ◽  
Power Law ◽  
Upper Bound ◽  
Mean Field ◽  
Maximum Size ◽  
Finite Graph ◽  
Critical Dimension ◽  
Point Function ◽  
Upper Critical Dimension ◽  
Infinite Cluster

AbstractWe study long-range Bernoulli percolation on $${\mathbb {Z}}^d$$ Z d in which each two vertices x and y are connected by an edge with probability $$1-\exp (-\beta \Vert x-y\Vert ^{-d-\alpha })$$ 1 - exp ( - β ‖ x - y ‖ - d - α ) . It is a theorem of Noam Berger (Commun. Math. Phys., 2002) that if $$0<\alpha <d$$ 0 < α < d then there is no infinite cluster at the critical parameter $$\beta _c$$ β c . We give a new, quantitative proof of this theorem establishing the power-law upper bound $$\begin{aligned} {\mathbf {P}}_{\beta _c}\bigl (|K|\ge n\bigr ) \le C n^{-(d-\alpha )/(2d+\alpha )} \end{aligned}$$ P β c ( | K | ≥ n ) ≤ C n - ( d - α ) / ( 2 d + α ) for every $$n\ge 1$$ n ≥ 1 , where K is the cluster of the origin. We believe that this is the first rigorous power-law upper bound for a Bernoulli percolation model that is neither planar nor expected to exhibit mean-field critical behaviour. As part of the proof, we establish a universal inequality implying that the maximum size of a cluster in percolation on any finite graph is of the same order as its mean with high probability. We apply this inequality to derive a new rigorous hyperscaling inequality $$(2-\eta )(\delta +1)\le d(\delta -1)$$ ( 2 - η ) ( δ + 1 ) ≤ d ( δ - 1 ) relating the cluster-volume exponent $$\delta $$ δ and two-point function exponent $$\eta $$ η .

Retrovirus-induced interference with collagen I gene expression in Mov13 fibroblasts is maintained in the absence of DNA methylation

1991 ◽  
Vol 11 (1) ◽  
pp. 47-54
Author(s):  
H Chan ◽  
S Hartung ◽  
M Breindl
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Chromatin Structure ◽  
Transcriptional Activity ◽  
Xenopus Laevis Oocytes ◽  
Regulatory Sequences ◽  
Type I ◽  
Wild Type ◽  
Col1a1 Gene

We have studied the role of DNA methylation in repression of the murine alpha 1 type I collagen (COL1A1) gene in Mov13 fibroblasts. In Mov13 mice, a retroviral provirus has inserted into the first intron of the COL1A1 gene and blocks its expression at the level of transcriptional initiation. We found that regulatory sequences in the COL1A1 promoter region that are involved in the tissue-specific regulation of the gene are unmethylated in collagen-expressing wild-type fibroblasts and methylated in Mov13 fibroblasts, confirming and extending earlier observations. To directly assess the role of DNA methylation in the repression of COL1A1 gene transcription, we treated Mov13 fibroblasts with the demethylating agent 5-azacytidine. This treatment resulted in a demethylation of the COL1A1 regulatory sequences but failed to activate transcription of the COL1A1 gene. Moreover, the 5-azacytidine treatment induced a transcription-competent chromatin structure in the retroviral sequences but not in the COL1A1 promoter. In DNA transfection and microinjection experiments, we found that the provirus interfered with transcriptional activity of the COL1A1 promoter in Mov13 fibroblasts but not in Xenopus laevis oocytes. In contrast, the wild-type COL1A1 promoter was transcriptionally active in Mov13 fibroblasts. These experiments showed that the COL1A1 promoter is potentially transcriptionally active in the presence of proviral sequences and that Mov13 fibroblasts contain the trans-acting factors required for efficient COL1A1 gene expression. Our results indicate that the provirus insertion in Mov13 can inactivate COL1A1 gene expression at several levels. It prevents the developmentally regulated establishment of a transcription-competent methylation pattern and chromatin structure of the COL1A1 domain and, in the absence of DNA methylation, appears to suppress the COL1A1 promoter in a cell-specific manner, presumably by assuming a dominant chromatin structure that may be incompatible with transcriptional activity of flanking cellular sequences.

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