Mapping RNA-chromatin interactions by sequencing with iMARGI

The landscape of RNA-chromatin interaction reveals small non-coding RNAs as essential mediators of leukemia maintenance

RNA constitutes a large fraction of chromatin. Spatial distribution and functional relevance of most of RNA-chromatin interactions remain unknown. We established a landscape analysis of RNA-chromatin interactions in human acute myeloid leukemia (AML). In total more than 50 million interactions were captured in an AML cell line. Protein-coding mRNAs and long non-coding RNAs exhibited a substantial number of interactions with chromatin in cis suggesting transcriptional activity. In contrast, small nucleolar RNAs (snoRNAs) and small nuclear RNAs (snRNAs) associated with chromatin predominantly in trans suggesting chromatin specific functions. Of note, snoRNA-chromatin interaction was associated with chromatin modifications and occurred independently of the classical snoRNA-RNP complex. Two C/D box snoRNAs, namely SNORD118 and SNORD3A, displayed high frequency of trans-association with chromatin. The transcription of SNORD118 and SNORD3A was increased upon leukemia transformation and enriched in leukemia stem cells, but decreased during myeloid differentiation. Suppression of SNORD118 and SNORD3A impaired leukemia cell proliferation and colony forming capacity in AML cell lines and primary patient samples. Notably, this effect was leukemia specific with less impact on healthy CD34+ hematopoietic stem and progenitor cells. These findings highlight the functional importance of chromatin-associated RNAs overall and in particular of SNORD118 and SNORD3A in maintaining leukemia propagation.

Exploring the roles of RNAs in chromatin architecture using deep learning

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we have compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improve the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores reveal the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identify non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several new RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT1, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.

RNA-DNA triplexes: molecular mechanisms and functional relevance

Interactions of RNA with DNA are principles of gene expression control that have recently gained considerable attention. Among RNA-DNA interactions are R-loops and RNA-DNA hybrid G-quadruplexes, as well as RNA-DNA triplexes. It is proposed that RNA-DNA triplexes guide RNA-associated regulatory proteins to specific genomic locations, influencing transcription and epigenetic decision making. Although triplex formation initially was considered solely an in vitro event, recent progress in computational, biochemical, and biophysical methods support in vivo functionality with relevance for gene expression control. Here, we review the central methodology and biology of triplexes, outline paradigms required for triplex function, and provide examples of physiologically important triplex-forming long non-coding RNAs.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

Cooltools: Enabling high-resolution Hi-C analysis in Python

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

Pairtools: From sequencing data to chromosome contacts

The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools-a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. The core operations provided by pairtools are parsing of.sam alignments into Hi-C pairs, sorting and removal of PCR duplicates. In addition, pairtools provides auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for restriction-based protocols, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.

Single-cell multiplex chromatin and RNA interactions in ageing human brain

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1-3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4-7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA-chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an 'older' transcriptomic signature and Alzheimer's disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

Single-cell multiplex chromatin and RNA interactions in aging human brain

The dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA (caRNA) 1-3. Chromatin complex compositions change during cellular differentiation and aging, and are expected to be highly heterogeneous among terminally differentiated single cells 4-7. Here we introduce the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei. Applied to 14 human frontal cortex samples from elderly donors, MUSIC delineates diverse cortical cell types and states. We observed the nuclei exhibiting fewer short-range chromatin interactions are correlated with an "older" transcriptomic signature and with Alzheimer's pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter tends to be the cell type where these cis eQTLs specifically affect their target gene's expression. Additionally, the female cortical cells exhibit highly heterogeneous interactions between the XIST non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

Regulation of nuclear transcription by mitochondrial RNA in endothelial cells

Chromatin-associated RNAs (caRNAs) form a relatively poorly recognized layer of the epigenome. The caRNAs reported to date are transcribed from the nuclear genome. Here, leveraging a recently developed assay for detection of caRNAs and their genomic association, we report that mitochondrial RNAs (mtRNAs) are attached to the nuclear genome and constitute a subset of caRNA, thus termed mt-caRNA. In four human cell types analyzed, mt-caRNAs preferentially attach to promoter regions. In human endothelial cells (ECs), the level of mt-caRNA-promoter attachment changes in response to environmental stress that mimics diabetes. Suppression of a non-coding mt-caRNA in ECs attenuates stress-induced nascent RNA transcription from the nuclear genome, including that of critical genes regulating cell adhesion, and abolishes stress-induced monocyte adhesion, a hallmark of dysfunctional ECs. Finally, we report increased nuclear localization of multiple mtRNAs in the ECs of human diabetic donors, suggesting many mtRNA translocate to the nucleus in a cell stress and disease-dependent manner. These data nominate mt-caRNAs as messenger molecules responsible for mitochondrial-nuclear communication and connect the immediate product of mitochondrial transcription with the transcriptional regulation of the nuclear genome.

Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improved the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores revealed the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identified non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several novel RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide new insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.

Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells

The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.

The RNA interactome in the Hallmarks of Cancer

Ribonucleic acid (RNA) molecules are indispensable for cellular homeostasis in healthy and malignant cells. However, the functions of RNA extend well beyond that of a protein-coding template. Rather, both coding and non-coding RNA molecules function through critical interactions with a plethora of cellular molecules, including other RNAs, DNA, and proteins. Deconvoluting this RNA interactome, including the interacting partners, the nature of the interaction, and dynamic changes of these interactions in malignancies has yielded fundamental advances in knowledge and are emerging as a novel therapeutic strategy in cancer. Here, we present an RNA-centric review of recent advances in the field of RNA-RNA, RNA-protein, and RNA-DNA interactomic network analysis and their impact across the Hallmarks of Cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

Approaches for Modes of Action Study of Long Non-Coding RNAs: From Single Verification to Genome-Wide Determination

Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nucleotides (nt) that are not translated into known functional proteins. This broad definition covers a large collection of transcripts with diverse genomic origins, biogenesis, and modes of action. Thus, it is very important to choose appropriate research methodologies when investigating lncRNAs with biological significance. Multiple reviews to date have summarized the mechanisms of lncRNA biogenesis, their localization, their functions in gene regulation at multiple levels, and also their potential applications. However, little has been reviewed on the leading strategies for lncRNA research. Here, we generalize a basic and systemic mind map for lncRNA research and discuss the mechanisms and the application scenarios of ‘up-to-date’ techniques as applied to molecular function studies of lncRNAs. Taking advantage of documented lncRNA research paradigms as examples, we aim to provide an overview of the developing techniques for elucidating lncRNA interactions with genomic DNA, proteins, and other RNAs. In the end, we propose the future direction and potential technological challenges of lncRNA studies, focusing on techniques and applications.

Pairtools: from sequencing data to chromosome contacts

The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools - a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. Pairtools provides both crucial core tools as well as auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for multi-way contacts, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.

Recent Development in Biomedical Applications of Oligonucleotides with Triplex-Forming Ability

A DNA structure, known as triple-stranded DNA, is made up of three oligonucleotide chains that wind around one another to form a triple helix (TFO). Hoogsteen base pairing describes how triple-stranded DNA may be built at certain conditions by the attachment of the third strand to an RNA, PNA, or DNA, which might all be employed as oligonucleotide chains. In each of these situations, the oligonucleotides can be employed as an anchor, in conjunction with a specific bioactive chemical, or as a messenger that enables switching between transcription and replication through the triplex-forming zone. These data are also considered since various illnesses have been linked to the expansion of triplex-prone sequences. In light of metabolic acidosis and associated symptoms, some consideration is given to the impact of several low-molecular-weight compounds, including pH on triplex production in vivo. The review is focused on the development of biomedical oligonucleotides with triplexes.

Elucidating the structure and function of the nucleus-The NIH Common Fund 4D Nucleome program

Genomic architecture appears to play crucial roles in health and a variety of diseases. How nuclear structures reorganize over different timescales is elusive, partly because the tools needed to probe and perturb them are not as advanced as needed by the field. To fill this gap, the National Institutes of Health Common Fund started a program in 2015, called the 4D Nucleome (4DN), with the goal of developing and ultimately applying technologies to interrogate the structure and function of nuclear organization in space and time.

Computational Methods to Study DNA:DNA:RNA Triplex Formation by lncRNAs

Long non-coding RNAs (lncRNAs) impact cell function via numerous mechanisms. In the nucleus, interactions between lncRNAs and DNA and the consequent formation of non-canonical nucleic acid structures seems to be particularly relevant. Along with interactions between single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA), such as R-loops, ssRNA can also interact with double-stranded DNA (dsDNA) to form DNA:DNA:RNA triplexes. A major challenge in the study of DNA:DNA:RNA triplexes is the identification of the precise RNA component interacting with specific regions of the dsDNA. As this is a crucial step towards understanding lncRNA function, there exist several computational methods designed to predict these sequences. This review summarises the recent progress in the prediction of triplex formation and highlights important DNA:DNA:RNA triplexes. In particular, different prediction tools (Triplexator, LongTarget, TRIPLEXES, Triplex Domain Finder, TriplexFFP, TriplexAligner and Fasim-LongTarget) will be discussed and their use exemplified by selected lncRNAs, whose DNA:DNA:RNA triplex forming potential was validated experimentally. Collectively, these tools revealed that DNA:DNA:RNA triplexes are likely to be numerous and make important contributions to gene expression regulation.

Methods to Study RNA-Chromatin Interactions

RNA plays a fundamental role in the organization of chromatin as well as the regulation of gene expression. Although the chromatin is pervasively attached by both coding and noncoding RNAs, the impact of these chromatin-associated RNAs (caRNAs) on gene expression and cellular functions and their underlying mechanisms have just begun to be unraveled. One approach to understand the potential mechanism of gene regulation by caRNAs is to identify the caRNA-associated genomic regions. Several groups have developed methods to capture RNA-chromatin interactions in either one RNA vs the whole genome, i.e., "one-to-all" or all RNAs vs the whole genome, i.e., "all-to-all" manner. In this chapter, we discuss several state-of-the-art methods highlighting the principles behind them, the experimental procedures, the advantages and limitations, and their applications. Our goal is to provide an overview and guide to researchers interested in exploring caRNAs using these techniques.

NPInter v5.0: ncRNA interaction database in a new era

Noncoding RNAs (ncRNAs) play key regulatory roles in biological processes by interacting with other biomolecules. With the development of high-throughput sequencing and experimental technologies, extensive ncRNA interactions have been accumulated. Therefore, we updated the NPInter database to a fifth version to document these interactions. ncRNA interaction entries were doubled from 1 100 618 to 2 596 695 by manual literature mining and high-throughput data processing. We integrated global RNA-DNA interactions from iMARGI, ChAR-seq and GRID-seq, greatly expanding the number of RNA-DNA interactions (from 888 915 to 8 329 382). In addition, we collected different types of RNA interaction between SARS-CoV-2 virus and its host from recently published studies. Long noncoding RNA (lncRNA) expression specificity in different cell types from tumor single cell RNA-seq (scRNA-seq) data were also integrated to provide a cell-type level view of interactions. A new module named RBP was built to display the interactions of RNA-binding proteins with annotations of localization, binding domains and functions. In conclusion, NPInter v5.0 (http://bigdata.ibp.ac.cn/npinter5/) provides informative and valuable ncRNA interactions for biological researchers.

A universal model of RNA.DNA:DNA triplex formation accurately predicts genome-wide RNA-DNA interactions

RNA.DNA:DNA triple helix (triplex) formation is a form of RNA-DNA interaction which regulates gene expression but is difficult to study experimentally in vivo. This makes accurate computational prediction of such interactions highly important in the field of RNA research. Current predictive methods use canonical Hoogsteen base pairing rules, which whilst biophysically valid, may not reflect the plastic nature of cell biology. Here, we present the first optimization approach to learn a probabilistic model describing RNA-DNA interactions directly from motifs derived from triplex sequencing data. We find that there are several stable interaction codes, including Hoogsteen base pairing and novel RNA-DNA base pairings, which agree with in vitro measurements. We implemented these findings in TriplexAligner, a program that uses the determined interaction codes to predict triplex binding. TriplexAligner predicts RNA-DNA interactions identified in all-to-all sequencing data more accurately than all previously published tools in human and mouse and also predicts previously studied triplex interactions with known regulatory functions. We further validated a novel triplex interaction using biophysical experiments. Our work is an important step towards better understanding of triplex formation and allows genome-wide analyses of RNA-DNA interactions.

Detecting TAD-like domains from RNA-associated interactions

Topologically associated domains (TADs) are crucial chromatin structural units. Evidence has illustrated that RNA-chromatin and RNA-RNA spatial interactions, so-called RNA-associated interactions (RAIs), may be associated with TAD-like domains (TLDs). To decode hierarchical TLDs from RAIs, we proposed SuperTLD, a domain detection algorithm incorporating imputation. We applied SuperTLD on four RAI data sets and compared TLDs with the TADs identified from the corresponding Hi-C datasets. The TLDs and TADs share a moderate similarity of hierarchies ≥ 0.5312 and the finest structures ≥ 0.8295. Comparison between boundaries and domains further demonstrated the novelty of TLDs. Enrichment analysis of epigenetic characteristics illustrated that the novel TLDs exhibit an enriched CTCF by 0.6245 fold change and H3 histone marks enriched within domains. GO analysis on the TLD novel boundaries exhibited enriched diverse terms, revealing TLDs' formation mechanism related closely to gene regulation.

The 4D Nucleome Data Portal as a resource for searching and visualizing curated nucleomics data

The 4D Nucleome (4DN) Network aims to elucidate the complex structure and organization of chromosomes in the nucleus and the impact of their disruption in disease biology. We present the 4DN Data Portal ( https://data.4dnucleome.org/ ), a repository for datasets generated in the 4DN network and relevant external datasets. Datasets were generated with a wide range of experiments, including chromosome conformation capture assays such as Hi-C and other innovative sequencing and microscopy-based assays probing chromosome architecture. All together, the 4DN data portal hosts more than 1800 experiment sets and 36000 files. Results of sequencing-based assays from different laboratories are uniformly processed and quality-controlled. The portal interface allows easy browsing, filtering, and bulk downloads, and the integrated HiGlass genome browser allows interactive visualization and comparison of multiple datasets. The 4DN data portal represents a primary resource for chromosome contact and other nuclear architecture data for the scientific community.

Bioinformatics Approaches for Determining the Functional Impact of Repetitive Elements on Non-coding RNAs

With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

Quantitative analysis of biochemical processes in living cells at a single-molecule level: a case of olaparib-PARP1 (DNA repair protein) interactions

Quantitative description of biochemical processes inside living cells and at single-molecule levels remains a challenge at the forefront of modern instrumentation and spectroscopy. This paper demonstrates such single-cell, single-molecule analyses performed to study the mechanism of action of olaparib - an up-to-date, FDA-approved drug for germline-BRCA mutated metastatic breast cancer. We characterized complexes formed with PARPi-FL - fluorescent analog of olaparib in vitro and in cancer cells using the advanced fluorescent-based method: Fluorescence Correlation Spectroscopy (FCS) combined with a length-scale dependent cytoplasmic/nucleoplasmic viscosity model. We determined in vitro olaparib-PARP1 equilibrium constant (6.06 × 10⁸ mol L^-1). In the cell nucleus, we distinguished three states of olaparib: freely diffusing drug (24%), olaparib-PARP1 complex (50%), and olaparib-PARP1-RNA complex (26%). We show olaparib accumulation in 3D spheroids, where intracellular concentration is twofold higher than in 2D cells. Moreover, olaparib concentration was tenfold higher (506 nmol L^-1vs. 57 nmol L^-1) in cervical cancer (BRCA1 high abundance) than in breast cancer cells (BRCA1 low abundance) but with a lower toxic effect. Thus we confirmed that the amount of BRCA1 protein in the cells is a better predictor of the therapeutic effect of olaparib than its penetration into cancer tissue. Our single-molecule and single-cell approach give a new perspective of drug action in living cells. FCS provides a detailed in vivo insight, valuable in drug development and targeting.

The macro and micro of chromosome conformation capture

The 3D organization of the genome facilitates gene regulation, replication, and repair, making it a key feature of genomic function and one that remains to be properly understood. Over the past two decades, a variety of chromosome conformation capture (3C) methods have delineated genome folding from megabase-scale compartments and topologically associating domains (TADs) down to kilobase-scale enhancer-promoter interactions. Understanding the functional role of each layer of genome organization is a gateway to understanding cell state, development, and disease. Here, we discuss the evolution of 3C-based technologies for mapping 3D genome organization. We focus on genomics methods and provide a historical account of the development from 3C to Hi-C. We also discuss ChIP-based techniques that focus on 3D genome organization mediated by specific proteins, capture-based methods that focus on particular regions or regulatory elements, 3C-orthogonal methods that do not rely on restriction digestion and proximity ligation, and methods for mapping the DNA-RNA and RNA-RNA interactomes. We consider the biological discoveries that have come from these methods, examine the mechanistic contributions of CTCF, cohesin, and loop extrusion to genomic folding, and detail the 3D genome field's current understanding of nuclear architecture. Finally, we give special consideration to Micro-C as an emerging frontier in chromosome conformation capture and discuss recent Micro-C findings uncovering fine-scale chromatin organization in unprecedented detail. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Regulatory Mechanisms Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics.

Genome-wide regulation of CpG methylation by ecCEBPα in acute myeloid leukemia

Background: Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by genetic and epigenetic aberrations that alter the differentiation capacity of myeloid progenitor cells. The transcription factor CEBPα is frequently mutated in AML patients leading to an increase in DNA methylation in many genomic locations. Previously, it has been shown that ecCEBPα (extra coding CEBP α) - a lncRNA transcribed in the same direction as CEBPα gene - regulates DNA methylation of CEBPα promoter in cis. Here, we hypothesize that ecCEBPα could participate in the regulation of DNA methylation in trans.

Method: First, we retrieved the methylation profile of AML patients with mutated CEBPα locus from The Cancer Genome Atlas (TCGA). We then predicted the ecCEBPα secondary structure in order to check the potential of ecCEBPα to form triplexes around CpG loci and checked if triplex formation influenced CpG methylation, genome-wide.

Results: Using DNA methylation profiles of AML patients with a mutated CEBPα locus, we show that ecCEBPα could interact with DNA by forming DNA:RNA triple helices and protect regions near its binding sites from global DNA methylation. Further analysis revealed that triplex-forming oligonucleotides in ecCEBPα are structurally unpaired supporting the DNA-binding potential of these regions. ecCEBPα triplexes supported with the RNA-chromatin co-localization data are located in the promoters of leukemia-linked transcriptional factors such as MLF2.

Discussion: Overall, these results suggest a novel regulatory mechanism for ecCEBPα as a genome-wide epigenetic modulator through triple-helix formation which may provide a foundation for sequence-specific engineering of RNA for regulating methylation of specific genes.

"Enhancing" mechanosensing: Enhancers and enhancer-derived long non-coding RNAs in endothelial response to flow

Endothelial cells (ECs), uniquely localized and strategically forming the inner lining of vascular wall, constitute the largest cell surface by area in the human body. The dynamic sensing and response of ECs to mechanical cues, especially shear stress, is crucial for maintenance of vascular homeostasis. It is well recognized that different flow patterns associated with atheroprotective vs atheroprone regions in the arterial tree, result in distinct EC functional phenotypes with differential transcriptome profiles. Mounting evidence has demonstrated an integrative and essential regulatory role of non-coding genome in EC biology. In particular, recent studies have begun to reveal the importance of enhancers and enhancer-derived transcripts in flow-regulated EC gene expression and function. In this minireview, we summarize studies in this area and discuss examples in support of the emerging importance of enhancers and enhancer(-derived) long non-coding RNAs (elncRNAs) in EC mechanosensing, with a focus on flow-responsive EC transcription. Finally, we will provide perspective and discuss standing questions to elucidate the role of these novel regulators in EC mechanobiology.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

Stress-induced RNA-chromatin interactions promote endothelial dysfunction

Chromatin-associated RNA (caRNA) has been proposed as a type of epigenomic modifier. Here, we test whether environmental stress can induce cellular dysfunction through modulating RNA-chromatin interactions. We induce endothelial cell (EC) dysfunction with high glucose and TNFα (H + T), that mimic the common stress in diabetes mellitus. We characterize the H + T-induced changes in gene expression by single cell (sc)RNA-seq, DNA interactions by Hi-C, and RNA-chromatin interactions by iMARGI. H + T induce inter-chromosomal RNA-chromatin interactions, particularly among the super enhancers. To test the causal relationship between H + T-induced RNA-chromatin interactions and the expression of EC dysfunction-related genes, we suppress the LINC00607 RNA. This suppression attenuates the expression of SERPINE1, a critical pro-inflammatory and pro-fibrotic gene. Furthermore, the changes of the co-expression gene network between diabetic and healthy donor-derived ECs corroborate the H + T-induced RNA-chromatin interactions. Taken together, caRNA-mediated dysregulation of gene expression modulates EC dysfunction, a crucial mechanism underlying numerous diseases.

Global interaction of chromatin-associated RNAs and DNA can be identified in situ. Here the authors report the genome-wide increase of interchromosomal RNA-DNA interactions and demonstrate the importance of such RNA-DNA contacts exemplified by LINC00607 RNA and SERPINE1 gene’s super enhancer in dysfunctional endothelial cell models.

Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)

Long noncoding RNAs (lncRNAs) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. They are a divergent group of RNAs and are easily differentiated from other types with unique characteristics, functions, and mechanisms of action. In this review, we provide a list of some of the prominent data repositories containing lncRNAs, their interactome, and predicted and validated disease associations. Next, we discuss various wet-lab experiments formulated to obtain the data for these repositories. We also provide a critical review of in silico methods available for the identification purpose and suggest techniques to further improve their performance. The bulk of the methods currently focus on distinguishing lncRNA transcripts from the coding ones. Functional annotation of these transcripts still remains a grey area and more efforts are needed in that space. Finally, we provide details of current progress, discuss impediments, and illustrate a roadmap for developing a generalized computational pipeline for comprehensive annotation of lncRNAs, which is essential to accelerate research in this area.

Long non-coding RNAs and transposable elements: A functional relationship

Long non-coding RNAs (lncRNAs) have become increasingly important in the past decade. They are known to regulate gene expression and to interact with chromatin, proteins and other coding and non-coding RNAs. The study of lncRNAs has been challenging due to their low expression and the lack of tools developed to adapt to their particular features. Studies on lncRNAs performed to date have largely focused on cellular functions, whereas details on the mechanism of action has only been thoroughly investigated for a small number of lncRNAs. Nevertheless, some studies have highlighted the potential of these transcripts to contain functional domains, following the same accepted trend as proteins. Interestingly, many of these identified "domains" are attributed to functional units derived from transposable elements. Here, we review several types of functions of lncRNAs and relate these functions to lncRNA-embedded transposable elements.

Programming DNA-Based Systems through Effective Molarity Enforced by Biomolecular Confinement

The fundamental concept of effective molarity is observed in a variety of biological processes, such as protein compartmentalization within organelles, membrane localization and signaling paths. To control molecular encountering and promote effective interactions, nature places biomolecules in specific sites inside the cell in order to generate a high, localized concentration different from the bulk concentration. Inspired by this mechanism, scientists have artificially recreated in the lab the same strategy to actuate and control artificial DNA-based functional systems. Here, it is discussed how harnessing effective molarity has led to the development of a number of proximity-induced strategies, with applications ranging from DNA-templated organic chemistry and catalysis, to biosensing and protein-supported DNA assembly.

Genome-Wide Technologies to Study RNA-Chromatin Interactions

An increasing number of studies have revealed that long non-coding RNAs (lncRNAs) play important roles in gene regulation and nuclear organization. Although the mechanisms are still largely unknown, many lncRNAs have been shown to interact with chromatin. Thus, one approach to understanding the function of these lncRNAs is to identify their sites of genomic interaction. Hybridization capture methods using oligonucleotide probes have been used for years to study chromatin-associated RNA. Recently, several groups have developed novel methods based on proximity ligation to investigate RNA–chromatin interactions at a genome-wide scale. This review discusses these technologies and highlights their advantages and disadvantages for the consideration of potential users.