HiCuT: An efficient and low input method to identify protein-directed chromatin interactions

Defining a TFAP2C-centered transcription factor network during murine peri-implantation

Transcription factors (TFs) play important roles in early embryonic development, but factors regulating TF action, relationships in signaling cascade, genome-wide localizations, and impacts on cell fate transitions during this process have not been clearly elucidated. In this study, we used uliCUT&RUN-seq to delineate a TFAP2C-centered regulatory network, showing that it involves promoter-enhancer interactions and regulates TEAD4 and KLF5 function to mediate cell polarization. Notably, we found that maternal retinoic acid metabolism regulates TFAP2C expression and function by inducing the active demethylation of SINEs, indicating that the RARG-TFAP2C-TEAD4/KLF5 axis connects the maternal-to-zygotic transition to polarization. Moreover, we found that both genomic imprinting and SNP-transferred genetic information can influence TF positioning to regulate parental gene expressions in a sophisticated manner. In summary, we propose a ternary model of TF regulation in murine embryonic development with TFAP2C as the core element and metabolic, epigenetic, and genetic information as nodes connecting the pathways.

Hi-Tag: a simple and efficient method for identifying protein-mediated long-range chromatin interactions with low cell numbers

Protein-mediated chromatin interactions can be revealed by coupling proximity-based ligation with chromatin immunoprecipitation. However, these techniques require complex experimental procedures and millions of cells per experiment, which limits their widespread application in life science research. Here, we develop a novel method, Hi-Tag, that identifies high-resolution, long-range chromatin interactions through transposase tagmentation and chromatin proximity ligation (with a phosphorothioate-modified linker). Hi-Tag can be implemented using as few as 100,000 cells, involving simple experimental procedures that can be completed within 1.5 days. Meanwhile, Hi-Tag is capable of using its own data to identify the binding sites of specific proteins, based on which, it can acquire accurate interaction information. Our results suggest that Hi-Tag has great potential for advancing chromatin interaction studies, particularly in the context of limited cell availability.

BL-Hi-C reveals the 3D genome structure of Brassica crops with high sensitivity

High-throughput Chromatin Conformation Capture (Hi-C) technologies can be used to investigate the three-dimensional genomic structure of plants. However, the practical utility of these technologies is impeded by significant background noise, hindering their capability in detecting fine 3D genomic structures. In this study, we optimized the Bridge Linker Hi-C technology (BL-Hi-C) to comprehensively investigate the 3D chromatin landscape of Brassica rapa and Brassica oleracea. The Bouquet configuration of both B. rapa and B. oleracea was elucidated through the construction of a 3D genome simulation. The optimized BL-Hi-C exhibited lower background noise compared to conventional Hi-C methods. Taking this advantage, we used BL-Hi-C to identify FLC gene loops in Arabidopsis, B. rapa, and B. oleracea. We observed that gene loops of FLC2 exhibited conservation across Arabidopsis, B. rapa, and B. oleracea. While gene loops of syntenic FLCs exhibited conservation across B. rapa and B. oleracea, variations in gene loops were evident among multiple paralogs FLCs within the same species. Collectively, our findings highlight the high sensitivity of optimized BL-Hi-C as a powerful tool for investigating the fine 3D genomic organization.

Technological advances in probing 4D genome organization

The last two decades of work on chromosome conformation in eukaryotic nuclei have revealed a complex and highly regulated hierarchy of architectural features, from self-associating domains and compartmental interactions to locus-specific loops. Recent findings have shown that these structures are dynamic and heterogeneous, with emerging insights into the factors that shape them and implications for the control of transcription and other nuclear processes. Here, we review the latest advances in the DNA sequencing- and microscopy-based technologies for probing these features in space and time (4D) and discuss how they have been combined with complementary approaches such as genetic perturbations, protein and RNA measurements, and modeling to gain mechanistic insights about genome regulation across space and time.

Transcriptional regulation of innate lymphoid cells and T cells by aryl hydrocarbon receptor

The aryl hydrocarbon receptor (Ahr) is a ligand-dependent transcription factor and facilitates immune cell environmental sensing through its activation by cellular, dietary, and microbial metabolites, as well as environmental toxins. Although expressed in various cell types, Ahr in innate lymphoid cells (ILCs) and their adaptive T cell counterparts regulates essential aspects of their development and function. As opposed to T cells, ILCs exclusively rely on germ-line encoded receptors for activation, but often share expression of core transcription factors and produce shared effector molecules with their T cell counterparts. As such, core modules of transcriptional regulation are both shared and diverge between ILCs and T cells. In this review, we highlight the most recent findings regarding Ahr’s transcriptional regulation of both ILCs and T cells. Furthermore, we focus on insights elucidating the shared and distinct mechanisms by which Ahr regulates both innate and adaptive lymphocytes.

Tn5 DNA Transposase in Multi-Omics Research

Tn5 transposase use in biotechnology has substantially advanced the sequencing applications of genome-wide analysis of cells. This is mainly due to the ability of Tn5 transposase to efficiently transpose DNA essentially randomly into any target DNA without the aid of other factors. This concise review is focused on the advances in Tn5 applications in multi-omics technologies, genome-wide profiling, and Tn5 hybrid molecule creation. The possibilities of other transposase uses are also discussed.

Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.

ChromLoops: a comprehensive database for specific protein-mediated chromatin loops in diverse organisms

Chromatin loops (or chromatin interactions) are important elements of chromatin structures. Disruption of chromatin loops is associated with many diseases, such as cancer and polydactyly. A few methods, including ChIA-PET, HiChIP and PLAC-Seq, have been proposed to detect high-resolution, specific protein-mediated chromatin loops. With rapid progress in 3D genomic research, ChIA-PET, HiChIP and PLAC-Seq datasets continue to accumulate, and effective collection and processing for these datasets are urgently needed. Here, we developed a comprehensive, multispecies and specific protein-mediated chromatin loop database (ChromLoops, https://3dgenomics.hzau.edu.cn/chromloops), which integrated 1030 ChIA-PET, HiChIP and PLAC-Seq datasets from 13 species, and documented 1 491 416 813 high-quality chromatin loops. We annotated genes and regions overlapping with chromatin loop anchors with rich functional annotations, such as regulatory elements (enhancers, super-enhancers and silencers), variations (common SNPs, somatic SNPs and eQTLs), and transcription factor binding sites. Moreover, we identified genes with high-frequency chromatin interactions in the collected species. In particular, we identified genes with high-frequency interactions in cancer samples. We hope that ChromLoops will provide a new platform for studying chromatin interaction regulation in relation to biological processes and disease.

In situ tools for chromatin structural epigenomics

Technological progress over the past 15 years has fueled an explosion in genome-wide chromatin profiling tools that take advantage of low-cost short-read sequencing technologies to map particular chromatin features. Here, we survey the recent development of epigenomic tools that provide precise positions of chromatin proteins genome-wide in intact cells or nuclei. Some profiling tools are based on tethering Micrococcal Nuclease to chromatin proteins of interest in situ, whereas others similarly tether Tn5 transposase to integrate DNA sequencing adapters (tagmentation) and so eliminate the need for library preparation. These in situ cleavage and tagmentation tools have gained in popularity over the past few years, with many protocol enhancements and adaptations for single-cell and spatial chromatin profiling. The application of experimental and computational tools to address problems in gene regulation, eukaryotic development, and human disease are helping to define the emerging field of chromatin structural epigenomics.