ChIPr : accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features

© 2024. The Author(s)..

The three-dimensional genome organization influences diverse nuclear processes. Here we present Chromatin Interaction Predictor (ChIPr), a suite of regression models based on deep neural networks, random forest, and gradient boosting to predict cohesin-mediated chromatin interaction strength between any two loci in the genome. The predictions of ChIPr correlate well with ChIA-PET data in four cell lines. The standard ChIPr model requires three experimental inputs: ChIP-Seq signals for RAD21, H3K27ac, and H3K27me3 but works well with just RAD21 signal. Integrative analysis reveals novel insights into the role of CTCF motif, its orientation, and CTCF binding on cohesin-mediated chromatin interactions.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:25

Enthalten in:

Genome biology - 25(2024), 1 vom: 12. Jan., Seite 15

Sprache:

Englisch

Beteiligte Personen:

Abbas, Ahmed [VerfasserIn]
Chandratre, Khyati [VerfasserIn]
Gao, Yunpeng [VerfasserIn]
Yuan, Jiapei [VerfasserIn]
Zhang, Michael Q [VerfasserIn]
Mani, Ram S [VerfasserIn]

Links:

Volltext

Themen:

CCCTC-Binding Factor
Cell Cycle Proteins
Chromatin
Chromosomal Proteins, Non-Histone
Cohesins
Journal Article

Anmerkungen:

Date Completed 15.01.2024

Date Revised 10.02.2024

published: Electronic

Citation Status MEDLINE

doi:

10.1186/s13059-023-03158-7

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM367075776