Genome-wide study of correlations between genomic features and their relationship with the regulation of gene expression

Kravatsky, Yuri V.; Chechetkin, V. R.; Tchurikov, Nickolai A.; Kravatskaya, Galina I.

doi:10.1093/dnares/dsu044

Cited by 18 publications

(28 citation statements)

References 36 publications

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“…The RAFT protocol from which our data are derived is theoretically enriched for blunt-ended forum domain termini, previously shown to be associated with transcriptional control [6], [10], [11]. They will be biased towards termini that occur within a particular range of genomic distances from a Sau 3AI restriction endonuclease site.…”

Section: Discussionmentioning

confidence: 99%

Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells

et al. 2017

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Constitutional biological processes involve the generation of DNA double-strand breaks (DSBs). The production of such breaks and their subsequent resolution are also highly relevant to neurodegenerative diseases and cancer, in which extensive DNA fragmentation has been described Stephens et al. (2011), Blondet et al. (2001). Tchurikov et al. Tchurikov et al. (2011, 2013) have reported previously that frequent sites of DSBs occur in chromosomal domains involved in the co-ordinated expression of genes. This group report that hot spots of DSBs in human HEK293T cells often coincide with H3K4me3 marks, associated with active transcription Kravatsky et al. (2015) and that frequent sites of DNA double-strand breakage are likely to be relevant to cancer genomics Tchurikov et al. (2013, 2016) . Recently, they applied a RAFT (rapid amplification of forum termini) protocol that selects for blunt-ended DSB sites and mapped these to the human genome within defined co-ordinate ‘windows’. In this paper, we re-analyse public RAFT data to derive sites of DSBs at the single-nucleotide level across the built genome for human HEK293T cells (https://figshare.com/s/35220b2b79eaaaf64ed8). This refined mapping, combined with accessory ENCODE data tracks and ribosomal DNA-related sequence annotations, will likely be of value for the design of clinically relevant targeted assays such as those for cancer susceptibility, diagnosis, treatment-matching and prognostication.

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Section: Discussionmentioning

confidence: 99%

Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells

et al. 2017

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“…In recent years, the bioinformatics community has actively developed methods for assessment of colocalization of genomic features [6,9,14,28,31]. The features are typically represented as a set of intervals on the genome (genes, repeats, CpG islands, etc.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, most genome-wide correlation algorithms [e.g., 14,31] compare genomic features at identical genomic coordinates (called overlapping coordinates). However, biologically regulatory relationships may often occur between features within a neighborhood of genomic coordinates (called adjacent coordinates).…”

Section: Introductionmentioning

confidence: 99%

“…For example, gene expression profiles (RNA-seq coverage) correlate with transcription factor binding sites or chromatin state in nearby promoter regions or distant enhancer regions. Interval and point-based approaches developed for genome-wide correlation account for associations between adjacent coordinates by estimating distance-based statistics [6,9,14].…”

Section: Introductionmentioning

confidence: 99%

“…The interval and point-wise genome-wide correlations are addressed in [6,10,11], [16]. A common approach to investigating genomic features is to represent these features as intervals, computed from the original continuous coverage data using a threshold or more sophisticated algorithms [46].…”

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confidence: 99%

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StereoGene: Rapid Estimation of Genomewide Correlation of Continuous or Interval Feature Data

Stavrovskaya

Niranjan

Fertig

et al. 2016

Preprint

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Motivation: High throughput sequencing methods produce massive amounts of data. The most common first step in interpretation of these data is to map the data to genomic intervals and then overlap with genome annotations. A major interest in computational genomics is spatial genome-wide correlation among genomic features (e.g. between transcription and histone modification). The key hypothesis here is that features that are similarly distributed along a genome may be functionally related.Results: Here, we propose a method that rapidly estimates genomewide correlation of genomic annotations; these annotations can be derived from high throughput experiments, databases, or other means. The method goes far beyond the simple overlap and proximity tests that are commonly used, by enabling correlation of continuous data, so that the loss of data that occurs upon reduction to intervals is unnecessary. To include analysis of nonoverlapping but spatially related features, we use kernel correlation. Implementation of this method allows for correlation analysis of two or three profiles across the human genome in a few minutes on a personal computer. Another novel and extraordinarily powerful feature of our approach is the local correlation track output that enables overlap with other correlations (correlation of correlations). We applied our method to the datasets from the Human Epigenome Atlas and FANTOM CAGE. We observed the changes of the correlation between epigenomic features across developmental trajectories of several tissue types, and found unexpected strong spatial correlation of CAGE clusters with splicing donor sites and with poly(A) sites.Modern high throughput genomic methods generate large amounts of data, which can come from experimental designs that compare tissue-specific or developmental stage-specific phenomena for human [7] and model organisms [4]. Single-cell approaches are also rapidly advancing [3]. Such datasets are integrated into several different archive databases [8,37,44] and manually curated databases [25].An important challenge of genome-wide data analysis is to reveal and assess the interactions between biological processes, e.g. chromatin profiles and gene expression. A rapidly emerging approach to this challenge is to represent data as functions on genomic positions and to estimate correlations between these functions.Numerous recent biological publications employ the correlation-based approach. Several research papers [41,43] focus on relationships between transcription factor binding and chromatin state. These studies also include information on DNA accessibility [1], higher-order chromosomal organization [19], and association of chromatin modifications and alternative splicing [18,23]. The research field has broadened its focus on analysis of individual and cell/tissue specific variation of epigenomic features and their relationship with diverse traits [31]. An interesting "Comparative epigenomics" paradigm [42] has emerged from an observation that combinations of epigenetic marks are more...

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Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding

Busa

Favorov

Fertig

et al. 2021

Cell Reports Methods

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Genome-wide study of correlations between genomic features and their relationship with the regulation of gene expression

Cited by 18 publications

References 36 publications

Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells

Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells

StereoGene: Rapid Estimation of Genomewide Correlation of Continuous or Interval Feature Data

Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding

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