During the metagenomics era, high-throughput sequencing efforts both in mice and humans indicate that non-coding RNAs (ncRNAs) constitute a significant fraction of the transcribed genome. During the past decades, the regulatory role of these non-coding transcripts along with their interactions with other molecules have been extensively characterized. However, the study of long non-coding RNAs (lncRNAs), an ncRNA regulatory class with transcript lengths that exceed 200 nucleotides, revealed that certain non-coding transcripts are transcriptional \"by-products\", while their loci exert their downstream regulatory functions through RNA-independent mechanisms. Such mechanisms include, but are not limited to, chromatin interactions and complex promoter-enhancer competition schemes that involve the underlying ncRNA locus with or without its nascent transcription, mediating significant or even exclusive roles in the regulation of downstream target genes in mammals. Interestingly, such RNA-independent mechanisms often drive pathological manifestations, including oncogenesis. In this review, we summarize selective examples of lncRNAs that regulate target genes independently of their produced transcripts.

Recent advances in chromatin conformation capture technologies, such as SPRITE and Pore-C, have enabled the detection of simultaneous contacts among multiple chromatin loci. This has made it possible to investigate the cooperative transcriptional regulation involving multiple genes and regulatory elements at the resolution of a single molecule. However, these technologies are unavoidably subject to the random polymer looping effect and technical biases, making it challenging to distinguish genuine regulatory relationships directly from random polymer interactions. Here, we present HyperloopFinder, a method for identifying regulatory multi-way chromatin contacts (hyperloops) by jointly modeling the random polymer looping effect and technical biases to estimate the statistical significance of multi-way contacts. The results show that our model can accurately estimate the expected interaction frequency of multi-way contacts based on the distance distribution of pairwise contacts, revealing that most multi-way contacts can be formed by randomly linking the pairwise contacts adjacent to each other. Moreover, we observed the spatial colocalization of the interaction sites of hyperloops from image-based data. Our results also revealed that hyperloops can function as scaffolds for the cooperation among multiple genes and regulatory elements. In summary, our work contributes novel insights into higher-order chromatin structures and functions and has the potential to enhance our understanding of transcriptional regulation and other cellular processes.

Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds. Chromosome territories, compartments, loops, Barr bodies, and inactive X chromosome (Xi) superdomains persist. The active and inactive genome compartments in mammoth skin more closely resemble Asian elephant skin than other elephant tissues. Our analyses uncover new biology. Differences in compartmentalization reveal genes whose transcription was potentially altered in mammoths vs. elephants. Mammoth Xi has a tetradic architecture, not bipartite like human and mouse. We hypothesize that, shortly after this mammoth\'s death, the sample spontaneously freeze-dried in the Siberian cold, leading to a glass transition that preserved subfossils of ancient chromosomes at nanometer scale.

The most significant genetic influence on eye color pigmentation is attributed to the intronic SNP rs12913832 in the HERC2 gene, which interacts with the promoter region of the contiguous OCA2 gene. This interaction, through the formation of a chromatin loop, modulates the transcriptional activity of OCA2, directly affecting eye color pigmentation. Recent advancements in technology have elucidated the precise spatial organization of the genome within the cell nucleus, with chromatin architecture playing a pivotal role in regulating various genome functions. In this study, we investigated the organization of the chromatin close to the HERC2/OCA2 locus in human lymphocyte nuclei using fluorescence in situ hybridization (FISH) and high-throughput chromosome conformation capture (Hi-C) data. The 3 Mb of genomic DNA that belonged to the chromosomal region 15q12-q13.1 revealed the presence of three contiguous chromatin loops, which exhibited a different level of compaction depending on the presence of the A or G allele in the SNP rs12913832. Moreover, the analysis of the genomic organization of the genes has demonstrated that this chromosomal region is evolutionarily highly conserved, as evidenced by the analysis of syntenic regions in species from other Vertebrate classes. Thus, the role of rs12913832 variant is relevant not only in determining the transcriptional activation of the OCA2 gene but also in the chromatin compaction of a larger region, underscoring the critical role of chromatin organization in the proper regulation of the involved genes. It is crucial to consider the broader implications of this finding, especially regarding the potential regulatory role of similar polymorphisms located within intronic regions, which do not influence the same gene by modulating the splicing process, but they regulate the expression of adjacent genes. Therefore, caution should be exercised when utilizing whole-exome sequencing for diagnostic purposes, as intron sequences may provide valuable gene regulation information on the region where they reside. Thus, future research efforts should also be directed towards gaining a deeper understanding of the precise mechanisms underlying the role and mode of action of intronic SNPs in chromatin loop organization and transcriptional regulation.

HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

Chromatin loops between gene pairs have been observed in diverse contexts in both flies and vertebrates. Combining high-resolution Capture-C, DNA fluorescence in situ hybridization, and genetic perturbations, we dissect the functional role of three loops between genes with related function during Drosophila embryogenesis. By mutating the loop anchor (but not the gene) or the gene (but not loop anchor), we disentangle loop formation and gene expression and show that the 3D proximity of paralogous gene loci supports their co-regulation. Breaking the loop leads to either an attenuation or enhancement of expression and perturbs their relative levels of expression and cross-regulation. Although many loops appear constitutive across embryogenesis, their function can change in different developmental contexts. Taken together, our results indicate that chromatin gene-gene loops act as architectural scaffolds that can be used in different ways in different contexts to fine-tune the coordinated expression of genes with related functions and sustain their cross-regulation.

Single-cell Hi-C (scHi-C) has made it possible to analyze chromatin organization at the single-cell level. However, scHi-C experiments generate inherently sparse data, which poses a challenge for loop calling methods. The existing approach performs significance tests across the imputed dense contact maps, leading to substantial computational overhead and loss of information at the single-cell level. To overcome this limitation, a lightweight framework called scGSLoop is proposed, which sets a new paradigm for scHi-C loop calling by adapting the training and inferencing strategies of graph-based deep learning to leverage the sequence features and 1D positional information of genomic loci. With this framework, sparsity is no longer a challenge, but rather an advantage that the model leverages to achieve unprecedented computational efficiency. Compared to existing methods, scGSLoop makes more accurate predictions and is able to identify more loops that have the potential to play regulatory roles in genome functioning. Moreover, scGSLoop preserves single-cell information by identifying a distinct group of loops for each individual cell, which not only enables an understanding of the variability of chromatin looping states between cells, but also allows scGSLoop to be extended for the investigation of multi-connected hubs and their underlying mechanisms.

Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global threat to human lives. To advance the development of innovative diagnostic and treatment approaches, it is essential to examine the hidden features of HCC, particularly its 3D genome architecture, which is not well understood. In this study, we investigated the 3D genome organization of four HCC cell lines-Hep3B, Huh1, Huh7, and SNU449-using in situ Hi-C and assay for transposase-accessible chromatin sequencing. Our findings revealed that HCC cell lines had more long-range interactions, both intra-and interchromosomal, compared to human mammary epithelial cells (HMECs). Unexpectedly, HCC cell lines displayed cell line-specific compartmental modifications at the megabase (Mb) scale, which could potentially be leveraged in determining HCC subtypes. At the sub-Mb scale, we observed decreases in intra-TAD (topologically associated domain) interactions and chromatin loops in HCC cell lines compared to HMECs. Lastly, we discovered a correlation between gene expression and the 3D chromatin architecture of SLC8A1, which encodes a sodium-calcium antiporter whose modulation is known to induce apoptosis by comparison between HCC cell lines and HMECs. Our findings suggest that HCC cell lines have a distinct 3D genome organization that is different from those of normal and other cancer cells based on the analysis of compartments, TADs, and chromatin loops. Overall, we take this as evidence that genome organization plays a crucial role in cancer phenotype determination. Further exploration of epigenetics in HCC will help us to better understand specific gene regulation mechanisms and uncover novel targets for cancer treatment.

High-throughput chromosome conformation capture (Hi-C) technology has been applied to explore the chromatin interactions and shed light on the biological functions of three-dimensional genomic features. However, it remains challenging to guarantee the high quality of Hi-C library in plants and hence the reliable capture of chromatin structures, especially loops, due to insufficient fragmentation and low efficiency of proximity ligations. To overcome these deficiencies, we optimized the parameters of the Hi-C protocol, principally the cross-linking agents and endonuclease fragmentation strategy. The double cross-linkers (FA+DSG) and double restriction enzymes (DpnII+DdeI) were utilized. Thus, a systematic in situ Hi-C protocol was designed using plant tissues embedded with comprehensive quality controls to monitor the library construction. This upgraded method, termed Hi-C 3.0, was applied to cotton leaves for trial. In comparison with the conventional Hi-C 2.0, Hi-C 3.0 can obtain more than 50% valid contacts at a given sequencing depth to improve the signal-to-noise ratio. Hi-C 3.0 can furthermore enhance the capturing of loops almost as twice as that of Hi-C 2.0. In addition, Hi-C 3.0 showed higher efficiency of compartment detection and identified compartmentalization more accurately. In general, Hi-C 3.0 contributes to the advancement of the Hi-C method in plants by promoting its capability on decoding the chromatin organization.

The chromatin loops in the three-dimensional (3D) structure of chromosomes are essential for the regulation of gene expression. Despite the fact that high-throughput chromatin capture techniques can identify the 3D structure of chromosomes, chromatin loop detection utilizing biological experiments is arduous and time-consuming. Therefore, a computational method is required to detect chromatin loops. Deep neural networks can form complex representations of Hi-C data and provide the possibility of processing biological datasets. Therefore, we propose a bagging ensemble one-dimensional convolutional neural network (Be-1DCNN) to detect chromatin loops from genome-wide Hi-C maps. First, to obtain accurate and reliable chromatin loops in genome-wide contact maps, the bagging ensemble learning method is utilized to synthesize the prediction results of multiple 1DCNN models. Second, each 1DCNN model consists of three 1D convolutional layers for extracting high-dimensional features from input samples and one dense layer for producing the prediction results. Finally, the prediction results of Be-1DCNN are compared to those of the existing models. The experimental results indicate that Be-1DCNN predicts high-quality chromatin loops and outperforms the state-of-the-art methods using the same evaluation metrics. The source code of Be-1DCNN is available for free at https://github.com/HaoWuLab-Bioinformatics/Be1DCNN.