rna-associated-chromatin-dna-dna-interaction-method

RNA-Associated Chromatin DNA-DNA Interaction Method

RNA-Associated Chromatin DNA-DNA Interaction Method (RDD) is a targeted strategy for mapping chromatin interactions anchored by a specific RNA. It ...

Southern University of Science and Technology

Pore-C simultaneously captures genome-wide multi-way chromatin interaction and associated DNA methylation status in Arabidopsis.

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies not only offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for multi-way chromatin interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell-cycle-associated genes. Taken together, MCIBox represents an invaluable tool for the study of multiple chromatin interactions and inaugurates a previously unappreciated view of 3D genome structure.

MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification.

Chromatin structural domains, or topologically associated domains (TADs), are a general organizing principle in chromatin biology. RNA polymerase II (RNAPII) mediates multiple chromatin interactive loops, tethering together as RNAPII-associated chromatin interaction domains (RAIDs) to offer a framework for gene regulation. RAID and TAD alterations have been found to be associated with diseases. They can be further dissected as micro-domains (micro-TADs and micro-RAIDs) by clustering single-molecule chromatin-interactive complexes from next-generation three-dimensional (3D) genome techniques, such as ChIA-Drop. Currently, there are few tools available for micro-domain boundary identification. In this work, we developed the MCI-frcnn deep learning method to train a Faster Region-based Convolutional Neural Network (Faster R-CNN) for micro-domain boundary detection. At the training phase in MCI-frcnn, 50 images of RAIDs from  RNAPII ChIA-Drop data, containing 261 micro-RAIDs with ground truth boundaries, were trained for 7 days. Using this well-trained MCI-frcnn, we detected micro-RAID boundaries for the input new images, with a fast speed (5.26 fps), high recognition accuracy (AUROC = 0.85, mAP = 0.69), and high boundary region quantification (genomic IoU = 76%). We further applied MCI-frcnn to detect human micro-TADs boundaries using human GM12878 SPRITE data and obtained a high region quantification score (mean gIoU = 85%). In all, the MCI-frcnn deep learning method which we developed in this work is a general tool for micro-domain boundary detection.

MCI-frcnn: A deep learning method for topological micro-domain boundary detection.

Single-cell multiomics techniques have been widely applied to detect the key signature of cells. These methods have achieved a single-molecule resolution and can even reveal spatial localization. These emerging methods provide insights elucidating the features of genomic, epigenomic and transcriptomic heterogeneity in individual cells. However, they have given rise to new computational challenges in data processing. Here, we describe Single-cell Single-molecule multiple Omics Pipeline (ScSmOP), a universal pipeline for barcode-indexed single-cell single-molecule multiomics data analysis. Essentially, the C language is utilized in ScSmOP to set up spaced-seed hash table-based algorithms for barcode identification according to ligation-based barcoding data and synthesis-based barcoding data, followed by data mapping and deconvolution. We demonstrate high reproducibility of data processing between ScSmOP and published pipelines in comprehensive analyses of single-cell omics data (scRNA-seq, scATAC-seq, scARC-seq), single-molecule chromatin interaction data (ChIA-Drop, SPRITE, RD-SPRITE), single-cell single-molecule chromatin interaction data (scSPRITE) and spatial transcriptomic data from various cell types and species. Additionally, ScSmOP shows more rapid performance and is a versatile, efficient, easy-to-use and robust pipeline for single-cell single-molecule multiomics data analysis.

ScSmOP: a universal computational pipeline for single-cell single-molecule multiomics data analysis.

The three-dimensional (3D) organization of chromatin within the nucleus is crucial for gene regulation. However, the 3D architectural features that coordinate the activation of an entire chromosome remain largely unknown. We introduce an omics method, RNA-associated chromatin DNA-DNA interactions, that integrates RNA polymerase II (RNAPII)-mediated regulome with stochastic optical reconstruction microscopy to investigate the landscape of noncoding RNA -associated chromatin topology for gene equalization to achieve dosage compensation. Our findings reveal that  anchors to the target gene transcription end sites (TESs) and spreads in a distinctive boot-shaped configuration, promoting a more open chromatin state for hyperactivation. Furthermore,  arches TES to transcription start sites to enhance transcriptional loops, potentially facilitating RNAPII convoying and connecting proximal promoter-promoter transcriptional hubs for synergistic gene regulation. These TESs cluster as  compartments, surrounded by inactive domains for coactivation of multiple genes within the  territory. In addition,  structures gradually form and scaffold for stepwise coactivation in dosage compensation.

3D chromatin structures associated with ncRNA  for hyperactivation and coactivation across the entire X chromosome.

CRISPR/Cas-based transcriptional activators can be enhanced by intrinsically disordered regions (IDRs). However, the underlying mechanisms are still debatable. Here, we examine 12 well-known IDRs by fusing them to the dCas9-VP64 activator, of which only seven can augment activation, albeit independently of their phase separation capabilities. Moreover, modular domains (MDs), another class of multivalent molecules, though ineffective in enhancing dCas9-VP64 activity on their own, show substantial enhancement in transcriptional activation when combined with dCas9-VP64-IDR. By varying the number of gRNA binding sites and fusing dCas9-VP64 with different IDRs/MDs, we uncover that optimal, rather than maximal, cis-trans cooperativity enables the most robust activation. Finally, targeting promoter-enhancer pairs yields synergistic effects, which can be further amplified via enhancing chromatin interactions. Overall, our study develops a versatile platform for efficient gene activation and sheds important insights into CRIPSR-based transcriptional activators enhanced with multivalent molecules.

Specific multivalent molecules boost CRISPR-mediated transcriptional activation.

The recombinant human p53 adenovirus (Ad-p53) offers a promising approach for cancer therapy, yet its chromatin structure and effects on host chromatin organization and gene expression are not fully understood.

Chromatin structure and gene transcription of recombinant p53 adenovirus vector within host.

Transcription factors (TFs) play a crucial role in the regulation of gene expression and the structural organization of chromatin. They interact with proteins, RNA, and chromatin DNA to exert their functions. Therefore, an efficient and straightforward experimental approach that simultaneously captures the interactions of transcription factors with DNA, RNA, and proteins is essential for studying these regulatory proteins. In this study, we developed a novel method, TF-chRDP (Transcription Factor binding Chromatin-associated RNA, DNA, and Protein), which allows for the concurrent capture of these biomolecules in a single experiment. We enriched chromatin complexes using specific antibodies and divided the chromatin into three fractions: one for DNA library preparation to analyze the genomic binding sites of transcription factors, another for RNA library preparation to investigate the RNA associated with transcription factor binding, and the third for proteomic analysis to identify protein cofactors interacting with transcription factors. We applied this method to study the transcription factor p53 and its associated chromatin complexes. The results demonstrated high specificity in the enrichment of DNA, RNA and proteins. This method provides an efficient tool for simultaneously capturing chromatin-associated RNA, DNA and protein bound to specific TF, making it particularly useful for analyzing the role of protein-DNA-RNA complexes in transcriptional regulation.

TF-chRDP: a method for simultaneously capturing transcription factor binding chromatin-associated RNA, DNA and protein.

The three-dimensional (3D) chromatin structure of Epstein-Barr virus (EBV) within host cells and the underlying mechanisms of chromatin interaction and gene regulation, particularly those involving EBV's noncoding RNAs (ncRNAs), have remained incompletely characterized. In this study, we employed state-of-the-art techniques of 3D genome mapping, including protein-associated chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), RNA-associated chromatin interaction technique (RDD), and super-resolution microscopy, to delineate the spatial architecture of EBV in human lymphoblastoid cells. We systematically analyzed EBV-to-EBV (E-E), EBV-to-host (E-H), and host-to-host (H-H) interactions linked to host proteins and EBV RNAs. Our findings reveal that EBV utilizes host CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) to form distinct chromatin contact domains (CCDs) and RNAPII-associated interaction domains (RAIDs). The anchors of these chromatin domains serve as platforms for extensive interactions with host chromatin, thus modulating host gene expression. Notably, EBV ncRNAs, especially Epstein-Barr-encoded RNAs (EBERs), target and interact with less accessible regions of host chromatin to repress a subset of genes via the inhibition of RNAPII-associated chromatin loops. This process involves the cofactor nucleolin (NCL) and its RNA recognition motifs, and depletion of either NCL or EBERs alters expression of genes crucial for host infection control, immune response, and cell cycle regulation. These findings unveil a sophisticated interplay between EBV and host chromatin.

Article	Year
Pore-C simultaneously captures genome-wide multi-way chromatin interaction and associated DNA methylation status in Arabidopsis. Plant biotechnology journal\| PubMed ID: 35313066	2022
MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification. Briefings in bioinformatics\| PubMed ID: 36094071	2022
MCI-frcnn: A deep learning method for topological micro-domain boundary detection. Frontiers in cell and developmental biology\| PubMed ID: 36531953	2022
ScSmOP: a universal computational pipeline for single-cell single-molecule multiomics data analysis. Briefings in bioinformatics\| PubMed ID: 37779245	2023
3D chromatin structures associated with ncRNA for hyperactivation and coactivation across the entire X chromosome. Science advances\| PubMed ID: 39058769	2024
Specific multivalent molecules boost CRISPR-mediated transcriptional activation. Nature communications\| PubMed ID: 39174527	2024
Chromatin structure and gene transcription of recombinant p53 adenovirus vector within host. Frontiers in molecular biosciences\| PubMed ID: 40092712	2025
TF-chRDP: a method for simultaneously capturing transcription factor binding chromatin-associated RNA, DNA and protein. Frontiers in cell and developmental biology\| PubMed ID: 40123855	2025
Landscape of the Epstein-Barr virus-host chromatin interactome and gene regulation. The EMBO journal\| PubMed ID: 40425856	2025

Simon Zhongyuan Tian

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