Profiling chromatin regulatory landscape: insights into the development of ChIP-seq and ATAC-seq

Unravelling the mosaic: Epigenetic diversity in glioblastoma

Glioblastoma is the most common primary malignant brain tumour. Despite decades of intensive research in the disease, its prognosis remains poor, with an average survival of only 14 months after diagnosis. The remarkable level of intra- and interpatient heterogeneity is certainly contributing to the lack of progress in tackling this tumour. Epigenetic dysregulation plays an important role in glioblastoma biology and significantly contributes to intratumour heterogeneity. However, it is becoming increasingly clear that it also contributes to intertumour heterogeneity, which historically had mainly been linked to diverse genetic events occurring in different patients. In this review, we explore how DNA methylation, chromatin remodelling, microRNA (miRNA) dysregulation, and long noncoding RNA (lncRNA) alterations contribute to intertumour heterogeneity in glioblastoma, including its implications for advanced tumour stratification, which is the essential first step for developing more effective patient-specific therapeutic approaches.

Generic and queryable data integration schema for transcriptomics and epigenomics studies

The expansion of multi-omics datasets raises significant challenges for data integration and querying. To overcome these challenges, we developed a generic RDF-based integration schema that connects various types of differential -omics data, epigenomics, and regulatory information. This schema employs the FALDO ontology to enable querying based on genomic locations. It is designed to be fully or partially populated, providing both flexibility and extensibility while supporting complex queries. We validated the schema by reproducing two recently published studies, one in biomedicine and the other in environmental science, proving its genericity and its ability to integrate data efficiently. This schema serves as an effective tool for managing and querying a wide range of multi-omics datasets.

A comprehensive study of Z-DNA density and its evolutionary implications in birds

BACKGROUND

Z-DNA, a left-handed helical form of DNA, plays a significant role in genomic stability and gene regulation. Its formation, associated with high GC content and repetitive sequences, is linked to genomic instability, potentially leading to large-scale deletions and contributing to phenotypic diversity and evolutionary adaptation.

RESULTS

In this study, we analyzed the density of Z-DNA-prone motifs of 154 avian genomes using the non-B DNA Motif Search Tool (nBMST). Our findings indicate a higher prevalence of Z-DNA motifs in promoter regions across all avian species compared to other genomic regions. A negative correlation was observed between Z-DNA density and developmental time in birds, suggesting that species with shorter developmental periods tend to have higher Z-DNA densities. This relationship implies that Z-DNA may influence the timing and regulation of development in avian species. Furthermore, Z-DNA density showed associations with traits such as body mass, egg mass, and genome size, highlighting the complex interactions between genome architecture and phenotypic characteristics. Gene Ontology (GO) analysis revealed that Z-DNA motifs are enriched in genes involved in nucleic acid binding, kinase activity, and translation regulation, suggesting a role in fine-tuning gene expression essential for cellular functions and responses to environmental changes. Additionally, the potential of Z-DNA to drive genomic instability and facilitate adaptive evolution underscores its importance in shaping phenotypic diversity.

CONCLUSIONS

This study emphasizes the role of Z-DNA as a dynamic genomic element contributing to gene regulation, genomic stability, and phenotypic diversity in avian species. Future research should experimentally validate these associations and explore the molecular mechanisms by which Z-DNA influences avian biology.

Beyond modular enhancers: new questions in cis-regulatory evolution

Our understanding of how cis-regulatory elements work has advanced rapidly, outpacing our evolutionary models. In this review, we consider the implications of new mechanistic findings for evolutionary developmental biology. We focus on three different debates: whether evolutionary innovation occurs more often via the modification of old cis-regulatory elements or the emergence of new ones; the extent to which individual elements are specific and autonomous or multifunctional and interdependent; and how the robustness of cis-regulatory architectures influences the rate of trait evolution. These discussions lead us to propose new questions for the evo-devo of cis-regulation.

The long noncoding RNA (LINC-RBE) expression in testicular cells is associated with aging of the rat

Long noncoding RNAs (lncRNAs) are important regulatory biomolecules responsible for many cellular processes. The aging of mammals is manifested by a slow and gradual decline of physiological functions after adulthood, progressively resulting in age-related diseases. Testis comprises different cell-types with defined functions for producing haploid gametes and androgens in males, contributing gene-pool to the next generation with genetic variations to species for evolutionary advantage. The LINC-RBE (long intergenic noncoding-rat brain expressed) RNA showed highest expression in the Leydig cells, responsible for steroidogenesis and production of testosterone; higher expression in primary spermatocytes (pachytene cells), responsible for generation of haploid gametes and high expression in Sertoli cells, the nursing cells of the testes. Testes of immature (4-weeks), adult (16- and 44-weeks), and nearly-old (70-weeks) rats showed low, high, and again low levels of expression, respectively. This along with the nuclear-cytoplasmic localization of LINC-RBE RNA showed age-related expression and function. Thus, expression of LINC-RBE is involved in the molecular physiology of testes, especially Leydig cells, primary spermatocytes, and Sertoli cells. The decline in its expression correlates with diminishing reproductive function of the testes during aging of the rat.

Long non-coding RNA (LncRNA) and epigenetic factors: their role in regulating the adipocytes in bovine

Investigating the involvement of long non-coding RNAs (lncRNAs) and epigenetic processes in bovine adipocytes can provide valuable new insights into controlling adipogenesis in livestock. Long non-coding RNAs have been associated with forming chromatin loops that facilitate enhancer-promoter interactions during adipogenesis, as well as regulating important adipogenic transcription factors like C/EBPα and PPARγ. They significantly influence gene expression regulation at the post-transcriptional level and are extensively researched for their diverse roles in cellular functions. Epigenetic modifications such as chromatin reorganization, histone alterations, and DNA methylation subsequently affect the activation of genes related to adipogenesis and the progression of adipocyte differentiation. By investigating how fat deposition is epigenetically regulated in beef cattle, scientists aim to unravel molecular mechanisms, identify key regulatory genes and pathways, and develop targeted strategies for modifying fat deposition to enhance desirable traits such as marbling and meat tenderness. This review paper delves into lncRNAs and epigenetic factors and their role in regulating bovine adipocytes while focusing on their potential as targets for genetic improvement to increase production efficiency. Recent genomics advancements, including molecular markers and genetic variations, can boost animal productivity, meeting global demands for high-quality meat products. This review establishes a foundation for future research on understanding regulatory networks linked to lncRNAs and epigenetic changes, contributing to both scholarly knowledge advancement and practical applications within animal agriculture.

Utilization of Microfluidic Droplet-Based Methods in Diagnosis and Treatment Methods of Hepatocellular Carcinoma: A Review

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and is associated with high morbidity and mortality. One of the main challenges in the management of HCC is late clinical presentation and thus diagnosis of the disease, which results in poor survival. The pathogenesis of HCC is complex and involves chronic liver injury and genetic alterations. Diagnosis of HCC can be made either by biopsy or imaging; however, conventional tissue-based biopsy methods and serological biomarkers such as AFP have limited clinical applications. While hepatocellular carcinoma is associated with a range of molecular alterations, including the activation of oncogenic signaling pathways, such as Wnt-TGFβ, PI3K-AKT-mTOR, RAS-MAPK, MET, IGF, and Wnt-β-catenin and TP53 and TERT promoter mutations, microfluidic applications have been limited. Early diagnosis is crucial for advancing treatments that would address the heterogeneity of HCC. In this context, microfluidic droplet-based methods are crucial, as they enable comprehensive analysis of the genome and transcriptome of individual cells. Single-cell RNA sequencing (scRNA-seq) allows the examination of individual cell transcriptomes, identifying their heterogeneity and cellular evolutionary relationships. Other microfluidic methods, such as Drop-seq, InDrop, and ATAC-seq, are also employed for single-cell analysis. Here, we examine and compare these microfluidic droplet-based methods, exploring their advantages and limitations in liver cancer research. These technologies provide new opportunities to understand liver cancer biology, diagnosis, treatment, and prognosis, contributing to scientific efforts in combating this challenging disease.

Review and Evaluate the Bioinformatics Analysis Strategies of ATAC-seq and CUT&Tag Data

Efficient and reliable profiling methods are essential to study epigenetics. Tn5, one of the first identified prokaryotic transposases with high DNA-binding and tagmentation efficiency, is widely adopted in different genomic and epigenomic protocols for high-throughputly exploring the genome and epigenome. Based on Tn5, the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and the Cleavage Under Targets and Tagmentation (CUT&Tag) were developed to measure chromatin accessibility and detect DNA-protein interactions. These methodologies can be applied to large amounts of biological samples with low-input levels, such as rare tissues, embryos, and sorted single cells. However, fast and proper processing of these epigenomic data has become a bottleneck because massive data production continues to increase quickly. Furthermore, inappropriate data analysis can generate biased or misleading conclusions. Therefore, it is essential to evaluate the performance of Tn5-based ATAC-seq and CUT&Tag data processing bioinformatics tools, many of which were developed mostly for analyzing chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here, we conducted a comprehensive benchmarking analysis to evaluate the performance of eight popular software for processing ATAC-seq and CUT&Tag data. We compared the sensitivity, specificity, and peak width distribution for both narrow-type and broad-type peak calling. We also tested the influence of the availability of control IgG input in CUT&Tag data analysis. Finally, we evaluated the differential analysis strategies commonly used for analyzing the CUT&Tag data. Our study provided comprehensive guidance for selecting bioinformatics tools and recommended analysis strategies, which were implemented into Docker/Singularity images for streamlined data analysis.

Cell-type specific and differential expression of LINC-RSAS long noncoding RNA declines in the testes during ageing of the rat

Long noncoding RNAs (lncRNAs) have emerged as major regulators of gene expression, chromatin structure, epigenetic changes, post-transcriptional processing of RNAs, translation of mRNAs into proteins as well as contributing to the process of ageing. Ageing is a universal, slow, progressive change in almost all physiological processes of organisms after attaining reproductive maturity and often associated with age-related diseases. Mammalian testes contain various cell-types, vast reservoir of transcriptome complexity, produce haploid male gametes for reproduction and testosterone for development and maintenance of male sexual characters as well as contribute genetic variation to the species. We report age-related decline in expression and cellular localization of Long intergenic noncoding repeat-rich sense-antisense (LINC-RSAS) RNA in the testes and its major cell-types such as primary spermatocytes, Leydig cells and Sertoli cells during ageing of the rat. LINC-RSAS expression in testes increased from immature (4-weeks) to adult (16- and 44-weeks) and declined from adult (44-weeks) to nearly-old (70-weeks) rats. Genomic DNA methylation in the testes showed a similar pattern. Cell-type specific higher expression of LINC-RSAS was observed in primary spermatocytes (pachytene cells), Leydig cells and Sertoli cells of testes of adult rats. Over-expression of LINC-RSAS in cultured human cell lines revealed its possible role in cell-cycle control and apoptosis. We propose that LINC-RSAS expression is involved in molecular physiology of primary spermatocytes, Leydig cells and Sertoli cells of adult testes and its decline is associated with diminishing function of testes during ageing of the rat.

Untangling the gordian knot: The intertwining interactions between developmental hormone signaling and epigenetic mechanisms in insects

Hormones control developmental and physiological processes, often by regulating the expression of multiple genes simultaneously or sequentially. Crosstalk between hormones and epigenetics is pivotal to dynamically coordinate this process. Hormonal signals can guide the addition and removal of epigenetic marks, steering gene expression. Conversely, DNA methylation, histone modifications and non-coding RNAs can modulate regional chromatin structure and accessibility and regulate the expression of numerous (hormone-related) genes. Here, we provide a review of the interplay between the classical insect hormones, ecdysteroids and juvenile hormones, and epigenetics. We summarize the mode-of-action and roles of these hormones in post-embryonic development, and provide a general overview of epigenetic mechanisms. We then highlight recent advances on the interactions between these hormonal pathways and epigenetics, and their involvement in development. Furthermore, we give an overview of several 'omics techniques employed in the field. Finally, we discuss which questions remain unanswered and possible avenues for future research.

Gene regulation supporting sociality shared across lineages and variation in complexity

Across evolutionary lineages, insects vary in social complexity, from those that exhibit extended parental care to those with elaborate divisions of labor. Here, we synthesize the sociogenomic resources from hundreds of species to describe common gene regulatory mechanisms in insects that regulate social organization across phylogeny and levels of social complexity. Different social phenotypes expressed by insects can be linked to the organization of co-expressing gene networks and features of the epigenetic landscape. Insect sociality also stems from processes like the emergence of parental care and the decoupling of ancestral genetic programs. One underexplored avenue is how variation in a group's social environment affects the gene expression of individuals. Additionally, an experimental reduction of gene expression would demonstrate how the activity of specific genes contributes to insect social phenotypes. While tissue specificity provides greater localization of the gene expression underlying social complexity, emerging transcriptomic analysis of insect brains at the cellular level provides even greater resolution to understand the molecular basis of social insect evolution.

GNNMF: a multi-view graph neural network for ATAC-seq motif finding

BACKGROUND

The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) utilizes the Transposase Tn5 to probe open chromatic, which simultaneously reveals multiple transcription factor binding sites (TFBSs) compared to traditional technologies. Deep learning (DL) technology, including convolutional neural networks (CNNs), has successfully found motifs from ATAC-seq data. Due to the limitation of the width of convolutional kernels, the existing models only find motifs with fixed lengths. A Graph neural network (GNN) can work on non-Euclidean data, which has the potential to find ATAC-seq motifs with different lengths. However, the existing GNN models ignored the relationships among ATAC-seq sequences, and their parameter settings should be improved.

RESULTS

In this study, we proposed a novel GNN model named GNNMF to find ATAC-seq motifs via GNN and background coexisting probability. Our experiment has been conducted on 200 human datasets and 80 mouse datasets, demonstrated that GNNMF has improved the area of eight metrics radar scores of 4.92% and 6.81% respectively, and found more motifs than did the existing models.

CONCLUSIONS

In this study, we developed a novel model named GNNMF for finding multiple ATAC-seq motifs. GNNMF built a multi-view heterogeneous graph by using ATAC-seq sequences, and utilized background coexisting probability and the iterloss to find different lengths of ATAC-seq motifs and optimize the parameter sets. Compared to existing models, GNNMF achieved the best performance on TFBS prediction and ATAC-seq motif finding, which demonstrates that our improvement is available for ATAC-seq motif finding.

Chromatin and DNA Dynamics in Mouse Models of Liver Cancers

In recent years, important efforts have been made to understand how the expression of a specific gene repertoire correlates with chromatin accessibility, histone mark deposition, as well as with chromatin looping establishing connectivity with regulatory regions. The emergence of new techniques for genome-wide analyses and their progressive optimization to work on low amounts of material allows the scientific community to obtain an integrated view of transcriptional landscapes in physiology and disease. Here, we describe our own experience aiming at correlating the TCF-4/β-catenin cistrome during liver tumorigenesis with chromatin remodeling, histone mark modifications, and long-distance DNA looping.

A comprehensive revisit of the machine-learning tools developed for the identification of enhancers in the human genome

Enhancers are non-coding DNA elements that play a crucial role in enhancing the transcription rate of a specific gene in the genome. Experiments for identifying enhancers can be restricted by their conditions and involve complicated, time-consuming, laborious, and costly steps. To overcome these challenges, computational platforms have been developed to complement experimental methods that enable high-throughput identification of enhancers. Over the last few years, the development of various enhancer computational tools has resulted in significant progress in predicting putative enhancers. Thus, researchers are now able to use a variety of strategies to enhance and advance enhancer study. In this review, an overview of machine learning (ML)-based prediction methods for enhancer identification and related databases has been provided. The existing enhancer-prediction methods have also been reviewed regarding their algorithms, feature selection processes, validation techniques, and software utility. In addition, the advantages and drawbacks of these ML approaches and guidelines for developing bioinformatic tools have been highlighted for a more efficient enhancer prediction. This review will serve as a useful resource for experimentalists in selecting the appropriate ML tool for their study, and for bioinformaticians in developing more accurate and advanced ML-based predictors.

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.

LiveG4ID-Seq for Profiling the Dynamic Landscape of Chromatin G-Quadruplexes During Cell Cycle in Living Cells

G-quadruplex (G4) structures exist in the single-stranded DNA of chromatin and regulate genome function. However, the native chromatin G4 landscape in living cells has yet to be fully characterized. Herein, a genetic-encoded live-cell G4 identifier probe (LiveG4ID) is constructed and its cellular localization, biocompatibility, and G4-binding specificity is evaluated. By coupling LiveG4ID with cleavage under targets and tagmentation (CUT&Tag), LiveG4ID-seq, a method for mapping native chromatin G4 landscape in living cells with high accuracy is established. Compared to the conventional G4 CUT&Tag method, LiveG4ID-seq can identify more chromatin G4 signals and have a higher ratio of true positive signals. Using LiveG4ID-seq, the dynamic landscape of chromatin G4 structures during the cell cycle is profiled. It is discovered that chromatin G4 structures are prevalent in the promoter regions of cell cycle-specific genes, even in the early M phase when the chromatin is condensed. These data demonstrate the capacity of LiveG4ID-seq to profile a more accurate G4 landscape in living cells and promote future studies on chromatin G4 structures.

Gene expression in organoids: an expanding horizon

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.

Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types

The human genome contains millions of candidate cis-regulatory elements (CREs) with cell-type-specific activities that shape both health and myriad disease states. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these CREs. Here, we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of over 680,000 sequences, representing a nearly comprehensive set of all annotated CREs among three cell types (HepG2, K562, and WTC11), finding 41.7% to be functional. By testing sequences in both orientations, we find promoters to have significant strand orientation effects. We also observe that their 200 nucleotide cores function as non-cell-type-specific 'on switches' providing similar expression levels to their associated gene. In contrast, enhancers have weaker orientation effects, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict CRE function with high accuracy and delineate regulatory motifs. Testing an additional lentiMPRA library encompassing 60,000 CREs in all three cell types, we further identified factors that determine cell-type specificity. Collectively, our work provides an exhaustive catalog of functional CREs in three widely used cell lines, and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

GAGAM v1.2: An Improvement on Peak Labeling and Genomic Annotated Gene Activity Matrix Construction

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is rapidly becoming a powerful technology for assessing the epigenetic landscape of thousands of cells. However, the sparsity of the resulting data poses significant challenges to their interpretability and informativeness. Different computational methods are available, proposing ways to generate significant features from accessibility data and process them to obtain meaningful results. Foremost among them is the peak calling, which interprets the raw scATAC-seq data generating the peaks as features. However, scATAC-seq data are not trivially comparable with single-cell RNA sequencing (scRNA-seq) data, an increasingly pressing challenge since the necessity of multimodal experiments integration. For this reason, this study wants to improve the concept of the Gene Activity Matrix (GAM), which links the accessibility data to the genes, by proposing an improved version of the Genomic-Annotated Gene Activity Matrix (GAGAM) concept. Specifically, this paper presents GAGAM v1.2, a new and better version of GAGAM v1.0. GAGAM aims to label the peaks and link them to the genes through functional annotation of the whole genome. Using genes as features in scATAC-seq datasets makes different datasets comparable and allows linking gene accessibility and expression. This link is crucial for gene regulation understanding and fundamental for the increasing impact of multi-omics data. Results confirm that our method performs better than the previous GAMs and shows a preliminary comparison with scRNA-seq data.

Integrated bioinformatics analysis of the transcription factor-mediated gene regulatory networks in the formation of spermatogonial stem cells

Background: In vitro induction of spermatogonial stem cells (SSCs) from embryonic stem cells (ESCs) provides a promising tool for the treatment of male infertility. A variety of molecules are involved in this complex process, which needs to be further clarified. Undoubtedly, the increased knowledge of SSC formation will be beneficial to facilitate the currently complex induction process. Methods: Based on ATAC-seq, DNase-seq, RNA-seq, and microarray data from GEO datasets, chromatin property data (ATAC-seq, DNase-seq) and gene expression data (RNA-seq, microarray data) were combined to search for SSC-specific transcription factors (TFs) and hub SSC-specific genes by using the WGCNA method. Then, we applied RNA-seq and microarray data screening for key SSC-specific TFs and constructed key SSC-specific TF-mediated gene regulatory networks (GRNs) using ChIP-seq data. Results: First, after analysis of the ATAC-seq and DNase-seq data of mouse ESCs, primordial germ cells (PGCs), and SSCs, 33 SSC-specific TFs and 958 targeting genes were obtained. RNA-seq and WGCNA revealed that the key modules (turquoise and red) were the most significantly related to 958 SSC-specific genes, and a total of 10 hub SSC-specific genes were identified. Next, when compared with the cell-specific TFs in human ESCs, PGCs, and SSCs, we obtained five overlapping SSC-specific TF motifs, including the NF1 family TF motifs (NFIA, NFIB, NFIC, and NFIX), GRE, Fox:Ebox, PGR, and ARE. Among these, Nfib and Nfix exhibited abnormally high expression levels relative to mouse ESCs and PGCs. Moreover, Nfib and Nfix were upregulated in the testis sample with impaired spermatogenesis when compared with the normal group. Finally, the ChIP-seq data results showed that NFIB most likely targeted the hub SSC-specific genes of the turquoise module (Rpl36al, Rps27, Rps21, Nedd8, and Sec61b) and the red module (Vcam1 and Ccl2). Conclusion: Our findings preliminarily revealed cell-specific TFs and cell-specific TF-mediated GRNs in the process of SSC formation. The hub SSC-specific genes and the key SSC-specific TFs were identified and suggested complex network regulation, which may play key roles in optimizing the induction efficiency of the differentiation of ESCs into SSCs in vitro.

The early function of cortisol in liver during Aeromonas hydrophila infection: Dynamics of the transcriptome and accessible chromatin landscapes

In China, channel catfish (Ictalurus punctatus) is an important aquaculture species; however, haemorrhagic disease (Aeromonas hydrophila induced disease) in these fish has caused tremendous economic loss due to high morbidity and mass mortality in the breeding industry. The role of cortisol in bacterial diseases, particularly in the acute phase, remains unclear. In this study, liver transcriptome (RNA-seq) and chromatin accessibility (ATAC-seq) analyses were employed to investigate the early functional role of cortisol in Aeromonas hydrophila-stimulated responses. Our experiments confirmed that A. hydrophila infection can initially significantly increase serum cortisol levels at 1 h after infection. At this time point, the increased serum cortisol levels can significantly regulate A. hydrophila-regulated genes by affecting both transcriptome and chromatin accessibility. Cross-analysis of RNA-seq and ATAC-seq revealed that a certain gene group (92 target_DEGs) was regulated at an early time point by cortisol. KEGG enrichment analysis revealed that the top three pathways according to target_DEGs were cancer, glutathione metabolism, and the Notch signalling pathway. The protein-protein interaction analysis of target_DEGs revealed that they may be primarily involved in cell proliferation, CD8⁺ T cell function, glutathione synthesis, and activation of the NF-κB signalling pathway. This suggests that after the emergence of immune stress, the early regulation of cortisol is positive against the immune response. It is possible that in this situation, the animal is attempting to avoid dangerous situations and risks and then cope with the imbalance produced by the stressor to ultimately restore homeostasis. Our results will contribute to future research on fish and provide valuable insight regarding the mechanism of immune regulation by cortisol and the study of bacterial haemorrhagic disease in channel catfish.

Changes in chromatin accessibility are not concordant with transcriptional changes for single-factor perturbations

A major goal in the field of transcriptional regulation is the mapping of changes in the binding of transcription factors to the resultant changes in gene expression. Recently, methods for measuring chromatin accessibility have enabled us to measure changes in accessibility across the genome, which are thought to correspond to transcription factor-binding events. In concert with RNA-sequencing, these data in principle enable such mappings; however, few studies have looked at their concordance over short-duration treatments with specific perturbations. Here, we used tandem, bulk ATAC-seq, and RNA-seq measurements from MCF-7 breast carcinoma cells to systematically evaluate the concordance between changes in accessibility and changes in expression in response to retinoic acid and TGF-β. We found two classes of genes whose expression showed a significant change: those that showed some changes in the accessibility of nearby chromatin, and those that showed virtually no change despite strong changes in expression. The peaks associated with genes in the former group had lower baseline accessibility prior to exposure to signal. Focusing the analysis specifically on peaks with motifs for transcription factors associated with retinoic acid and TGF-β signaling did not reduce the lack of correspondence. Analysis of paired chromatin accessibility and gene expression data from distinct paths along the hematopoietic differentiation trajectory showed a much stronger correspondence, suggesting that the multifactorial biological processes associated with differentiation may lead to changes in chromatin accessibility that reflect rather than driving altered transcriptional status. Together, these results show many gene expression changes can happen independently of changes in the accessibility of local chromatin in the context of a single-factor perturbation.

Butyrate Induces Modifications of the CTCF-Binding Landscape in Cattle Cells

Butyrate is produced in the rumen from microbial fermentation and is related to several functions, including cell differentiation and proliferation. Butyrate supplementation in calves can accelerate rumen development. DNA-protein interactions, such as the CCCTC-binding factor (CTCF), play essential roles in chromatin organization and gene expression regulation. Although CTCF-binding sites have been identified recently in cattle, a deeper characterization, including differentially CTCF-binding sites (DCBS), is vital for a better understanding of butyrate’s role in the chromatin landscape. This study aimed to identify CTCF-binding regions and DCBS under a butyrate-induced condition using ChIP-seq in bovine cells; 61,915 CTCF peaks were identified in the butyrate and 51,347 in the control. From these regions, 2265 DCBS were obtained for the butyrate vs. control comparison, comprising ~90% of induced sites. Most of the butyrate DCBS were in distal intergenic regions, showing a potential role as insulators. Gene ontology enrichment showed crucial terms for the induced DCBS, mainly related to cellular proliferation, cell adhesion, and growth regulation. Interestingly, the ECM-receptor interaction pathway was observed for the induced DCBS. Motif enrichment analysis further identified transcription factors, including CTCF, BORIS, TGIF2, and ZIC3. When DCBS was integrated with RNA-seq data, putative genes were identified for the repressed DCBS, including GATA4. Our study revealed promising candidate genes in bovine cells by a butyrate-induced condition that might be related to the regulation of rumen development, such as integrins, keratins, and collagens. These results provide a better understanding of the function of butyrate in cattle rumen development and chromatin landscape regulation.

The Landscape of Liver Chromatin Accessibility and Conserved Non-coding Elements in Larimichthys crocea, Nibea albiflora, and Lateolabrax maculatus

Large yellow croaker (Larimichthys crocea), yellow drum (Nibea albiflora), and Chinese seabass (Lateolabrax maculatus) are important economic marine fishes in China. The conserved non-coding elements (CNEs) in the liver tissues of the three kinds of fish are directly or indirectly involved in the regulation of gene expression and affect liver functions. However, the fishes' CNEs and even chromatin accessibility landscape have not been effectively investigated. Hence, this study established the landscapes of the fishes' genome-wide chromatin accessibility and CNEs by detecting regions of the open chromatin in their livers using an assay for transposase-accessible chromatin by high-throughput sequencing (ATAC-seq) and comparative genomics approach. The results showed that Smad1, Sp1, and Foxl1 transcription factor binding motifs were considerably enriched in the chromatin accessibility landscape in the liver of the three species, and the three transcription factors (TFs) had a wide range of common targets. The hypothetical gene set was targeted by one, two, or all three TFs, which was much higher than would be expected for an accidental outcome. The gene sets near the CNEs were mainly enriched through processes such as a macromolecule metabolic process and ribonucleoprotein complex biogenesis. The active CNEs were found in the promoter regions of genes such as ap1g1, hax1, and ndufs2. And 5 CNEs were predicted to be highly conserved active enhancers. These results demonstrated that Smad1, Sp1, and Foxl1 might be related to the liver function in the three fishes. In addition, we found a series of ATAC-seq-labeled CNEs located in the gene promoter regions, and highly conserved H3k27ac + -labeled CNEs located in the liver function genes. The highly conserved nature of these regulatory elements suggests that they play important roles in the liver in fish. This study mined the landscape of chromatin accessibility and CNEs of three important economic fishes to fill the knowledge gaps in this field. Moreover, the work provides useful data for the industrial application and theoretical research of these three fish species.

Studying Epigenetics of Cardiovascular Diseases on Chip Guide

Epigenetics is defined as the study of inheritable changes in the gene expressions and phenotypes that occurs without altering the normal DNA sequence. These changes are mainly due to an alteration in chromatin or its packaging, which changes the DNA accessibility. DNA methylation, histone modification, and noncoding or microRNAs can best explain the mechanism of epigenetics. There are various DNA methylated enzymes, histone-modifying enzymes, and microRNAs involved in the cause of various CVDs (cardiovascular diseases) such as cardiac hypertrophy, heart failure, and hypertension. Moreover, various CVD risk factors such as diabetes mellitus, hypoxia, aging, dyslipidemia, and their epigenetics are also discussed together with CVDs such as CHD (coronary heart disease) and PAH (pulmonary arterial hypertension). Furthermore, different techniques involved in epigenetic chromatin mapping are explained. Among these techniques, the ChIP-on-chip guide is explained with regard to its role in cardiac hypertrophy, a final form of heart failure. This review focuses on different epigenetic factors that are involved in causing cardiovascular diseases.

Breaking the Immune Complexity of the Tumor Microenvironment Using Single-Cell Technologies

Tumors are not a simple aggregate of transformed cells but rather a complicated ecosystem containing various components, including infiltrating immune cells, tumor-related stromal cells, endothelial cells, soluble factors, and extracellular matrix proteins. Profiling the immune contexture of this intricate framework is now mandatory to develop more effective cancer therapies and precise immunotherapeutic approaches by identifying exact targets or predictive biomarkers, respectively. Conventional technologies are limited in reaching this goal because they lack high resolution. Recent developments in single-cell technologies, such as single-cell RNA transcriptomics, mass cytometry, and multiparameter immunofluorescence, have revolutionized the cancer immunology field, capturing the heterogeneity of tumor-infiltrating immune cells and the dynamic complexity of tenets that regulate cell networks in the tumor microenvironment. In this review, we describe some of the current single-cell technologies and computational techniques applied for immune-profiling the cancer landscape and discuss future directions of how integrating multi-omics data can guide a new "precision oncology" advancement.

The Nuclear Lamina

Lamins interact with a host of nuclear membrane proteins, transcription factors, chromatin regulators, signaling molecules, splicing factors, and even chromatin itself to form a nuclear subcompartment, the nuclear lamina, that is involved in a variety of cellular processes such as the governance of nuclear integrity, nuclear positioning, mitosis, DNA repair, DNA replication, splicing, signaling, mechanotransduction and -sensation, transcriptional regulation, and genome organization. Lamins are the primary scaffold for this nuclear subcompartment, but interactions with lamin-associated peptides in the inner nuclear membrane are self-reinforcing and mutually required. Lamins also interact, directly and indirectly, with peripheral heterochromatin domains called lamina-associated domains (LADs) and help to regulate dynamic 3D genome organization and expression of developmentally regulated genes.

The Thioesterase ACOT1 as a Regulator of Lipid Metabolism in Type 2 Diabetes Detected in a Multi-Omics Study of Human Liver

Type 2 diabetes (T2D) is characterized by pathophysiological alterations in lipid metabolism. One strategy to understand the molecular mechanisms behind these abnormalities is to identify cis-regulatory elements (CREs) located in chromatin-accessible regions of the genome that regulate key genes. In this study we integrated assay for transposase-accessible chromatin followed by sequencing (ATAC-seq) data, widely used to decode chromatin accessibility, with multi-omics data and publicly available CRE databases to identify candidate CREs associated with T2D for further experimental validations. We performed high-sensitive ATAC-seq in nine human liver samples from normal and T2D donors, and identified a set of differentially accessible regions (DARs). We identified seven DARs including a candidate enhancer for the ACOT1 gene that regulates the balance of acyl-CoA and free fatty acids (FFAs) in the cytoplasm. The relevance of ACOT1 regulation in T2D was supported by the analysis of transcriptomics and proteomics data in liver tissue. Long-chain acyl-CoA thioesterases (ACOTs) are a group of enzymes that hydrolyze acyl-CoA esters to FFAs and coenzyme A. ACOTs have been associated with regulation of triglyceride levels, fatty acid oxidation, mitochondrial function, and insulin signaling, linking their regulation to the pathogenesis of T2D. Our strategy integrating chromatin accessibility with DNA binding and other types of omics provides novel insights on the role of genetic regulation in T2D and is extendable to other complex multifactorial diseases.

Histone post-translational modifications as potential therapeutic targets for pain management

Effective pharmacological management of pain associated with tissue pathology is an unmet medical need. Transcriptional modifications in nociceptive pathways are pivotal for the development and the maintenance of pain associated with tissue damage. Accumulating evidence has shown the importance of the epigenetic control of transcription in nociceptive pathways via histone post-translational modifications (PTMs). Hence, histone PTMs could be targets for novel effective analgesics. Here, we discuss the current understanding of histone PTMs in the modulation of gene expression affecting nociception and pain phenotypes following tissue injury. We also provide a critical view of the translational implications of preclinical models and discuss opportunities and challenges of targeting histone PTMs to relieve pain in clinically relevant tissue injuries.

Towards a Systems Immunology Approach to Understanding Correlates of Protective Immunity against HCV

Over the past decade, tremendous progress has been made in systems biology-based approaches to studying immunity to viral infections and responses to vaccines. These approaches that integrate multiple facets of the immune response, including transcriptomics, serology and immune functions, are now being applied to understand correlates of protective immunity against hepatitis C virus (HCV) infection and to inform vaccine development. This review focuses on recent progress in understanding immunity to HCV using systems biology, specifically transcriptomic and epigenetic studies. It also examines proposed strategies moving forward towards an integrated systems immunology approach for predicting and evaluating the efficacy of the next generation of HCV vaccines.

The metabolic-epigenetic nexus in type 2 diabetes mellitus

The prevalence of type 2 diabetes mellitus (T2DM) continues to rise globally. Yet the aetiology and pathophysiology of this noncommunicable, polygenic disease, is poorly understood. Lifestyle factors, such as poor dietary intake, lack of exercise, and abnormal glycaemia, are purported to play a role in disease onset and progression, and these environmental factors may disrupt specific epigenetic mechanisms, leading to a reprogramming of gene transcription. The hyperglycaemic cell per se, alters epigenetics through chemical modifications to DNA and histones via metabolic intermediates such as succinate, α-ketoglutarate and O-GlcNAc. To illustrate, α-ketoglutarate is considered a salient co-factor in the activation of the ten-eleven translocation (TET) dioxygenases, which drives DNA demethylation. On the contrary, succinate and other mitochondrial tricarboxylic acid cycle intermediates, inhibit TET activity predisposing to a state of hypermethylation. Hyperglycaemia depletes intracellular ascorbic acid, and damages DNA by enhancing the production of reactive oxygen species (ROS); this compromised cell milieu exacerbates the oxidation of 5-methylcytosine alongside a destabilisation of TET. These metabolic connections may regulate DNA methylation, affecting gene transcription and pancreatic islet β-cell function in T2DM. This complex interrelationship between metabolism and epigenetic alterations may provide a conceptual foundation for understanding how pathologic stimuli modify and control the intricacies of T2DM. As such, this narrative review will comprehensively evaluate and detail the interplay between metabolism and epigenetic modifications in T2DM.

Genetic Determinants of Peripheral Artery Disease

Peripheral artery disease-atherosclerosis of the abdominal aorta and lower extremity vascular bed-is a complex disease with both environmental and genetic determinants. Unmitigated disease is associated with major functional decline and can lead to chronic limb-threatening ischemia, amputation, and increased mortality. Over the last 10 years, major advances have been made in identifying the genetic basis of this common, complex disease. In this review, we provide an overview of the primary types of genetic analyses performed for peripheral artery disease, including heritability and linkage studies, and more recently biobank-based genome-wide association studies. Looking forward, we highlight areas of future study including efforts to identify causal peripheral artery disease genes, rare variant and structural variant analyses using whole-exome and whole-genome sequencing data, and the need to include individuals of diverse genetic ancestries.