Evidence map›Paper›PMID 39131347›Full record

ArticlebioRxiv : the preprint server for biology2024

Determining mesoscale chromatin structure parameters from spatially correlated cleavage data using a coarse-grained oligonucleosome model.

Ariana Brenner Clerkin, Nicole Pagane, Devany W West, Andrew J Spakowitz, Viviana I Risca

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ariana Brenner ClerkinLaboratory of Genome Architecture and Dynamics, The Rockefeller University, New York, NY.ORCID 0000-0003-0911-6619
Nicole PaganePresent affiliation: Computational and Systems Biology PhD Program, Massachusetts Institute of Technology, Cambridge, MA.ORCID 0009-0007-0079-0515
Devany W WestLaboratory of Genome Architecture and Dynamics, The Rockefeller University, New York, NY.
Andrew J SpakowitzDepartment of Chemical Engineering, Stanford University, Stanford, CA.ORCID 0000-0002-0585-1942
Viviana I RiscaLaboratory of Genome Architecture and Dynamics, The Rockefeller University, New York, NY.ORCID 0000-0003-2670-8704

Funding

Tri-Institutional PhD Program in Computational Biology & MedicineT32GM132083 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI Doron Betel, Iman Hajirasouliha · 2020 to 2026
$3.6M
Cross-regulation between loop extrusion, chromatin fiber structure and chromatin-associated RNAsDP2GM150021 · NIGMS · ROCKEFELLER UNIVERSITY · PI RISCA, VIVIANA I · 2022 to 2025
$2.5M
NIGMS NIH HHS DP2 GM150021NIGMS NIH HHS T32 GM132083
6 · The paper itself

Abstract

The three-dimensional structure of chromatin has emerged as an important feature of eukaryotic gene regulation. Recent technological advances in DNA sequencing-based assays have revealed locus- and chromatin state-specific structural patterns at the length scale of a few nucleosomes (~1 kb). However, interpreting these data sets remains challenging. Radiation-induced correlated cleavage of chromatin (RICC-seq) is one such chromatin structure assay that maps DNA-DNA-contacts at base pair resolution by sequencing single-stranded DNA fragments released from irradiated cells. Here, we develop a flexible modeling and simulation framework to enable the interpretation of RICC-seq data in terms of oligonucleosome structure ensembles. Nucleosomes are modeled as rigid bodies with excluded volume and adjustable DNA wrapping, connected by linker DNA modeled as a worm-like chain. We validate the model's parameters against cryo-electron microscopy and sedimentation data. Our results show that RICC-seq is sensitive to nucleosome spacing, nucleosomal DNA wrapping, and the strength of inter-nucleosome interactions. We show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data using a 1D convolutional neural net trained on RICC-seq signal predicted from simulated ensembles. We thus provide a suite of analysis tools that add quantitative structural interpretability to RICC-seq experiments.

Indexed as

chromatin fiberchromatin structurecoarse-grained chromatin simulationmesoscale chromatinRICC-seq

Identifiers

PMID39131347
PMCPMC11312488

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.