Detect accessible chromatin using ATAC-sequencing, from principle to applications

The GW5-WRKY53-SGW5 module regulates grain size variation in rice

Grain size is a crucial agronomic trait that affects stable yield, appearance, milling quality, and domestication in rice. However, the molecular and genetic relationships among QTL genes (QTGs) underlying natural variation for grain size remain elusive. Here, we identified a novel QTG SGW5 (suppressor of gw5) by map-based cloning using an F2 segregation population by fixing same genotype of the master QTG GW5. SGW5 positively regulates grain width by influencing cell division and cell size in spikelet hulls. Two nearly isogenic lines exhibited a significant differential expression of SGW5 and a 12.2% increase in grain yield. Introducing the higher expression allele into the genetic background containing the lower expression allele resulted in increased grain width, while its knockout resulted in shorter grain hulls and dwarf plants. Moreover, a cis-element variation in the SGW5 promoter influenced its differential binding affinity for the WRKY53 transcription factor, causing the differential SGW5 expression, which ultimately leads to grain size variation. GW5 physically and genetically interacts with WRKY53 to suppress the expression of SGW5. These findings elucidated a new pathway for grain size regulation by the GW5-WRKY53-SGW5 module and provided a novel case for generally uncovering QTG interactions underlying the genetic diversity of an important trait in crops.

From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers. This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes. The sheer volume of data generated necessitates sophisticated informatics techniques, with machine-learning (ML) algorithms emerging as robust tools. These datasets not only refine disease classification but also enhance diagnostics and foster the development of targeted therapeutic strategies. Through the integration of high-throughput data, the review focuses on targeting and modeling multiple disease-regulated networks, validating interactions with multiple targets, and enhancing therapeutic potential using network pharmacology approaches. Ultimately, this exploration aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.

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.

Adipose tissue macrophage heterogeneity in the single-cell genomics era

It is now well-accepted that obesity-induced inflammation plays an important role in the development of insulin resistance and type 2 diabetes. A key source of the inflammation is the murine epididymal and human visceral adipose tissue. The current paradigm is that obesity activates multiple proinflammatory immune cell types in adipose tissue, including adipose-tissue macrophages (ATMs), T Helper 1 (Th1) T cells, and natural killer (NK) cells, while concomitantly suppressing anti-inflammatory immune cells such as T Helper 2 (Th2) T cells and regulatory T cells (Tregs). A key feature of the current paradigm is that obesity induces the anti-inflammatory M2 ATMs in lean adipose tissue to polarize into proinflammatory M1 ATMs. However, recent single-cell transcriptomics studies suggest that the story is much more complex. Here we describe the single-cell genomics technologies that have been developed recently and the emerging results from studies using these technologies. While further studies are needed, it is clear that ATMs are highly heterogeneous. Moreover, while a variety of ATM clusters with quite distinct features have been found to be expanded by obesity, none truly resemble classical M1 ATMs. It is likely that single-cell transcriptomics technology will further revolutionize the field, thereby promoting our understanding of ATMs, adipose-tissue inflammation, and insulin resistance and accelerating the development of therapies for type 2 diabetes.

WRN loss accelerates abnormal adipocyte metabolism in Werner syndrome

BACKGROUND

Metabolic dysfunction is one of the main symptoms of Werner syndrome (WS); however, the underlying mechanisms remain unclear. Here, we report that loss of WRN accelerates adipogenesis at an early stage both in vitro (stem cells) and in vivo (zebrafish). Moreover, WRN depletion causes a transient upregulation of late-stage of adipocyte-specific genes at an early stage.

METHODS

In an in vivo study, we generated wrn-/- mutant zebrafish and performed histological stain and Oil Red O staining to assess the fat metabolism. In an in vitro study, we used RNA-seq and ATAC-seq to profile the transcriptional features and chromatin accessibility in WRN depleted adipocytes. Moreover, we performed ChIP-seq to further study the regulatory mechanisms of metabolic dysfunction in WS.

RESULTS

Our findings show that mechanistically WRN deficiency causes SMARCA5 upregulation. SMARCA5 is crucial in chromatin remodeling and gene regulation. Additionally, rescuing WRN could normalize SMARCA5 expression and adipocyte differentiation. Moreover, we find that nicotinamide riboside (NR) supplementation restores adipocyte metabolism in both stem cells and zebrafish models.

CONCLUSIONS

Our findings unravel a new mechanism for the influence of WRN in the early stage of adipogenesis and provide a possible treatment for metabolic dysfunction in WS. These data provide promising insights into potential therapeutics for ageing and ageing-related diseases.

Epigenetic landscape analysis reveals the significance of early reduced chromatin accessibility in osteoclastogenesis

Recently improved techniques could provide snapshots of chromatin structure generated based on chromatin accessibility. Since chromatin accessibility determines transcriptional potential, it has been attempted in a variety of cell systems. However, there has been no genome-wide analysis of chromatin accessibility for the entire murine osteoclast (OC) differentiation process. We performed an Assay for Transposase-Accessible Chromatin (ATAC)-sequencing (seq) during RANKL-induced OC differentiation and found that global chromatin accessibility decreased, especially early in OC differentiation. The global histone H3K27Ac level, an active histone modification mark, was diminished during OC differentiation by western blot and histone extract experiments. Its genomic enrichment was also reduced based on publicly available H3K27Ac chromatin immunoprecipitation (ChIP)-seq data. ATAC-seq and H3K27Ac ChIP-seq data demonstrated that RANKL induced a less accessible chromatin state during OC differentiation. Restoration of reduced H3K27Ac, presumably representing accessible states upon acetate treatment, suppresses OC differentiation by provoking immune-related gene expression. Subsequential integrative analysis of ATAC-seq, RNA-seq after acetate treatment, and H3K27Ac ChIP-seq reveals that Irf8 and its downstream targets are the most vulnerable to chromatin accessibility changes and acetate supplementation. Taken together, our study generated chromatin accessibility maps during the whole OC differentiation and suggested perturbation of chromatin accessibility might be a potential therapeutic strategy for excessive OC diseases.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Current Status of Next-Generation Sequencing in Bone Genetic Diseases

The development of next-generation sequencing (NGS) has dramatically increased the speed and volume of genetic analysis. Furthermore, the range of applications of NGS is rapidly expanding to include genome, epigenome (such as DNA methylation), metagenome, and transcriptome analyses (such as RNA sequencing and single-cell RNA sequencing). NGS enables genetic research by offering various sequencing methods as well as combinations of methods. Bone tissue is the most important unit supporting the body and is a reservoir of calcium and phosphate ions, which are important for physical activity. Many genetic diseases affect bone tissues, possibly because metabolic mechanisms in bone tissue are complex. For instance, the presence of specialized immune cells called osteoclasts in the bone tissue, which absorb bone tissue and interact with osteoblasts in complex ways to support normal vital functions. Moreover, the many cell types in bones exhibit cell-specific proteins for their respective activities. Mutations in the genes encoding these proteins cause a variety of genetic disorders. The relationship between age-related bone tissue fragility (also called frailty) and genetic factors has recently attracted attention. Herein, we discuss the use of genomic, epigenomic, transcriptomic, and metagenomic analyses in bone genetic disorders.

Prediction accuracy of regulatory elements from sequence varies by functional sequencing technique

Introduction

Various sequencing based approaches are used to identify and characterize the activities of cis-regulatory elements in a genome-wide fashion. Some of these techniques rely on indirect markers such as histone modifications (ChIP-seq with histone antibodies) or chromatin accessibility (ATAC-seq, DNase-seq, FAIRE-seq), while other techniques use direct measures such as episomal assays measuring the enhancer properties of DNA sequences (STARR-seq) and direct measurement of the binding of transcription factors (ChIP-seq with transcription factor-specific antibodies). The activities of cis-regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers.

Methods

Here, machine learning models are employed to evaluate the accuracy with which cis-regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis-regulatory activity that is reflective of sequence content versus secondary processes.

Results and discussion

Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis-regulatory element prediction.

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.

FAM122A Is Required for Mesendodermal and Cardiac Differentiation of Embryonic Stem Cells

Mesendodermal specification and cardiac differentiation are key issues for developmental biology and heart regeneration medicine. Previously, we demonstrated that FAM122A, a highly conserved housekeeping gene, is an endogenous inhibitor of protein phosphatase 2A (PP2A) and participates in multifaceted physiological and pathological processes. However, the in vivo function of FAM122A is largely unknown. In this study, we observed that Fam122 deletion resulted in embryonic lethality with severe defects of cardiovascular developments and significantly attenuated cardiac functions in conditional cardiac-specific knockout mice. More importantly, Fam122a deficiency impaired mesendodermal specification and cardiac differentiation from mouse embryonic stem cells but showed no influence on pluripotent identity. Mechanical investigation revealed that the impaired differentiation potential was caused by the dysregulation of histone modification and Wnt and Hippo signaling pathways through modulation of PP2A activity. These findings suggest that FAM122A is a novel and critical regulator in mesendodermal specification and cardiac differentiation. This research not only significantly extends our understanding of the regulatory network of mesendodermal/cardiac differentiation but also proposes the potential significance of FAM122A in cardiac regeneration.

Immunotherapeutic Approaches in Ovarian Cancer

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

Mapping Nucleosome Location Using FS-Seq

The organization of nucleosomes in eukaryotic chromatin is thought to play a critical role in the regulation of the biological function of the chromatin. Because of this potential role in regulation, a number of techniques have been developed, which combine chromatin fragmentation around nucleosomes with next-generation sequencing to map the location of nucleosomes in chromatin. In this section, a procedure using a kit from New England Biolabs (NEB NEXT Ultra II FS DNA library prep Kit) to fragment chromatin in preparation for next-generation sequencing is described and compared to other available procedures for mapping nucleosome location.

AIscEA: unsupervised integration of single-cell gene expression and chromatin accessibility via their biological consistency

MOTIVATION

The integrative analysis of single-cell gene expression and chromatin accessibility measurements is essential for revealing gene regulation, but it is one of the key challenges in computational biology. Gene expression and chromatin accessibility are measurements from different modalities, and no common features can be directly used to guide integration. Current state-of-the-art methods lack practical solutions for finding heterogeneous clusters. However, previous methods might not generate reliable results when cluster heterogeneity exists. More importantly, current methods lack an effective way to select hyper-parameters under an unsupervised setting. Therefore, applying computational methods to integrate single-cell gene expression and chromatin accessibility measurements remains difficult.

RESULTS

We introduce AIscEA-Alignment-based Integration of single-cell gene Expression and chromatin Accessibility-a computational method that integrates single-cell gene expression and chromatin accessibility measurements using their biological consistency. AIscEA first defines a ranked similarity score to quantify the biological consistency between cell clusters across measurements. AIscEA then uses the ranked similarity score and a novel permutation test to identify cluster alignment across measurements. AIscEA further utilizes graph alignment for the aligned cell clusters to align the cells across measurements. We compared AIscEA with the competing methods on several benchmark datasets and demonstrated that AIscEA is highly robust to the choice of hyper-parameters and can better handle the cluster heterogeneity problem. Furthermore, AIscEA significantly outperforms the state-of-the-art methods when integrating real-world SNARE-seq and scMultiome-seq datasets in terms of integration accuracy.

AVAILABILITY AND IMPLEMENTATION

AIscEA is available at https://figshare.com/articles/software/AIscEA_zip/21291135 on FigShare as well as {https://github.com/elhaam/AIscEA} onGitHub.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Landscape of Accessible Chromatin during Yak Adipocyte Differentiation

Although significant advancement has been made in the study of adipogenesis, knowledge about how chromatin accessibility regulates yak adipogenesis is lacking. We here described genome-wide dynamic chromatin accessibility in preadipocytes and adipocytes by using the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), and thus revealed the unique characteristics of open chromatin during yak adipocyte differentiation. The chromatin accessibility of preadipocytes and adipocytes exhibited a similar genomic distribution, displaying a preferential location within the intergenic region, intron, and promoter. The pathway enrichment analysis identified that genes with differential chromatin accessibility were involved in adipogenic metabolism regulation pathways, such as the peroxisome proliferator activated receptor-γ (PPAR) signaling pathway, wingless-type MMTV integration site (Wnt) signaling pathway, and extracellular matrix-receptor (ECM–receptor) interaction. Integration of ATAC-seq and mRNA-seq revealed that genes with a high expression were associated with high levels of chromatin accessibility, especially within 1 kb upstream and downstream of the transcription start site. In addition, we identified a series of transcription factors (TFs) related to adipogenesis and created the TF regulatory network, providing the possible interactions between TFs during yak adipogenesis. This study is crucial for advancing the understanding of transcriptional regulatory mechanisms of adipogenesis and provides valuable information for understanding the adaptation of plateau species to high-altitude environments by maintaining whole body homeostasis through fat metabolism.

Relationship between ATOH1 and tumor microenvironment in colon adenocarcinoma patients with different microsatellite instability status

Background

Colon adenocarcinoma (COAD) is one of the major varieties of malignant tumors threatening human health today. Immune checkpoint inhibitors (ICIs) have recently begun to emerge as an effective option for the treatment of COAD patients, but not all patients can benefit from ICI treatment. Previous studies have suggested that ICIs boast significant clinical effects on patients with microsatellite instability-high (MSI-H), while conversely patients with microsatellite-stable/microsatellite instability-low (MSS/MSI-L) have shown limited response.

Methods

We used ATAC-seq, RNA-seq, and mutation data from The Cancer Genome Atlas Colon adenocarcinoma (TCGA-COAD) cohort to perform multi-omics differential analysis on COAD samples with different MSI statuses, then further screened genes by additionally combining these results with survival analysis. We analyzed the effects of the screened genes on the tumor microenvironment and immunogenicity of COAD patients, and subsequently determined their influence on the efficacy of ICIs in COAD patients using a series of predictive indexes.

Results

Twelve genes were screened in the TCGA-COAD cohort, and after the combined survival analysis, we identified ATOH1 as having significant effects. ATOH1 is characterized by high chromatin accessibility, high expression, and high mutation in COAD patients in the MSI-H group. COAD patients with high ATOH1 expression are associated with a better prognosis, unique immune microenvironment, and higher efficacy in ICI treatment. Enrichment analysis showed that COAD patients with high ATOH1 expression displayed significant upregulation in their humoral immunity and other related pathways.

Conclusions

We speculate that ATOH1 may influence the efficacy of ICIs therapy in patients with COAD by affecting the immune microenvironment and immunogenicity of the tumor.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02651-6.

Epigenetic Memories in Hematopoietic Stem and Progenitor Cells

The recent development of next-generation sequencing (NGS) technologies has contributed to research into various biological processes. These novel NGS technologies have revealed the involvement of epigenetic memories in trained immunity, which are responses to transient stimulation and result in better responses to secondary challenges. Not only innate system cells, such as macrophages, monocytes, and natural killer cells, but also bone marrow hematopoietic stem cells (HSCs) have been found to gain memories upon transient stimulation, leading to the enhancement of responses to secondary challenges. Various stimuli, including microbial infection, can induce the epigenetic reprogramming of innate immune cells and HSCs, which can result in an augmented response to secondary stimulation. In this review, we introduce novel NGS technologies and their application to unraveling epigenetic memories that are key in trained immunity and summarize the recent findings in trained immunity. We also discuss our most recent finding regarding epigenetic memory in aged HSCs, which may be associated with the exposure of HSCs to aging-related stresses.

Genome-Wide Analysis of Yeast Metabolic Cycle through Metabolic Network Models Reveals Superiority of Integrated ATAC-seq Data over RNA-seq Data

Saccharomyces cerevisiae undergoes robust oscillations to regulate its physiology for adaptation and survival under nutrient-limited conditions. Environmental cues can induce rhythmic metabolic alterations in order to facilitate the coordination of dynamic metabolic behaviors. Of such metabolic processes, the yeast metabolic cycle enables adaptation of the cells to varying nutritional status through oscillations in gene expression and metabolite production levels. In this process, yeast metabolism is altered between diverse cellular states based on changing oxygen consumption levels: quiescent (reductive charging [RC]), growth (oxidative [OX]), and proliferation (reductive building [RB]) phases. We characterized metabolic alterations during the yeast metabolic cycle using a variety of approaches. Gene expression levels are widely used for condition-specific metabolic simulations, whereas the use of epigenetic information in metabolic modeling is still limited despite the clear relationship between epigenetics and metabolism. This prompted us to investigate the contribution of epigenomic information to metabolic predictions for progression of the yeast metabolic cycle. In this regard, we determined altered pathways through the prediction of regulated reactions and corresponding model genes relying on differential chromatin accessibility levels. The predicted metabolic alterations were confirmed via data analysis and literature. We subsequently utilized RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) data sets in the contextualization of the yeast model. The use of ATAC-seq data considerably enhanced the predictive capability of the model. To the best of our knowledge, this is the first attempt to use genome-wide chromatin accessibility data in metabolic modeling. The preliminary results showed that epigenomic data sets can pave the way for more accurate metabolic simulations.

IMPORTANCE Dynamic chromatin organization mediates the emergence of condition-specific phenotypes in eukaryotic organisms. Saccharomyces cerevisiae can alter its metabolic profile via regulation of genome accessibility and robust transcriptional oscillations under nutrient-limited conditions. Thus, both epigenetic information and transcriptomic information are crucial in the understanding of condition-specific metabolic behavior in this organism. Based on genome-wide alterations in chromatin accessibility and transcription, we investigated the yeast metabolic cycle, which is a remarkable example of coordinated and dynamic yeast behavior. In this regard, we assessed the use of ATAC-seq and RNA-seq data sets in condition-specific metabolic modeling. To our knowledge, this is the first attempt to use chromatin accessibility data in the reconstruction of context-specific metabolic models, despite the extensive use of transcriptomic data. As a result of comparative analyses, we propose that the incorporation of epigenetic information is a promising approach in the accurate prediction of metabolic dynamics.

Bibliometric review of ATAC-Seq and its application in gene expression

With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.

Computational modeling of chromatin accessibility identified important epigenomic regulators

Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy.

One-pot universal NicE-seq: all enzymatic downstream processing of 4% formaldehyde crosslinked cells for chromatin accessibility genomics

Background

Accessible chromatin landscape allows binding of transcription factors, and remodeling of promoter and enhancer elements during development. Chromatin accessibility along with integrated multiomics approaches have been used for determining molecular subtypes of cancer in patient samples.

Results

One-pot Universal NicE-seq (One-pot UniNicE-seq) is an improved accessible chromatin profiling method that negate DNA purification and incorporate sonication free enzymatic fragmentation before library preparation and is suited to a variety of mammalian cells. One-pot UniNicE-seq is versatile, capable of profiling 4% formaldehyde fixed chromatin in as low as 25 fixed cells. Accessible chromatin profile is more efficient on formaldehyde-fixed cells using one-pot UniNicE-seq compared to Tn5 transposon mediated methods, demonstrating its versatility.

Conclusion

One-pot UniNicE-seq allows the entire process of accessible chromatin labeling and enrichment in one pot at 4% formaldehyde cross-linking conditions. It doesn’t require enzyme titration, compared to other technologies, since accessible chromatin is labelled with 5mC incorporation and deter degradation by nicking enzyme, thus opening the possibility for automation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-021-00427-2.

Single-cell sequencing: the technological revolution behind a new wave of multiomic studies in basic and cancer research

Amidst the development of new single-cell technologies and the implementation of multiomic approaches, two Stanford labs are spearheading a new field of research to combat cancer.

Productive visualization of high-throughput sequencing data using the SeqCode open portable platform

Large-scale sequencing techniques to chart genomes are entirely consolidated. Stable computational methods to perform primary tasks such as quality control, read mapping, peak calling, and counting are likewise available. However, there is a lack of uniform standards for graphical data mining, which is also of central importance. To fill this gap, we developed SeqCode, an open suite of applications that analyzes sequencing data in an elegant but efficient manner. Our software is a portable resource written in ANSI C that can be expected to work for almost all genomes in any computational configuration. Furthermore, we offer a user-friendly front-end web server that integrates SeqCode functions with other graphical analysis tools. Our analysis and visualization toolkit represents a significant improvement in terms of performance and usability as compare to other existing programs. Thus, SeqCode has the potential to become a key multipurpose instrument for high-throughput professional analysis; further, it provides an extremely useful open educational platform for the world-wide scientific community. SeqCode website is hosted at http://ldicrocelab.crg.eu, and the source code is freely distributed at https://github.com/eblancoga/seqcode.

Chromatin remodelling complexes in cerebral cortex development and neurodevelopmental disorders

The diverse number of neurons in the cerebral cortex are generated during development by neural stem cells lining the ventricle, and they continue maturing postnatally. Dynamic chromatin regulation in these neural stem cells is a fundamental determinant of the emerging property of the functional neural network, and the chromatin remodellers are critical determinants of this process. Chromatin remodellers participate in several steps of this process from proliferation, differentiation, migration leading to complex network formation which forms the basis of higher-order functions of cognition and behaviour. Here we review the role of these ATP-dependent chromatin remodellers in cortical development in health and disease and highlight several key mouse mutants of the subunits of the complexes which have revealed how the remodelling mechanisms control the cortical stem cell chromatin landscape for expression of stage-specific transcripts. Consistent with their role in cortical development, several putative risk variants in the subunits of the remodelling complexes have been identified as the underlying causes of several neurodevelopmental disorders. A basic understanding of the detailed molecular mechanism of their action is key to understating how mutations in the same networks lead to disease pathologies and perhaps pave the way for therapeutic development for these complex multifactorial disorders.

Employing core regulatory circuits to define cell identity

The interplay between extrinsic signaling and downstream gene networks controls the establishment of cell identity during development and its maintenance in adult life. Advances in next-generation sequencing and single-cell technologies have revealed additional layers of complexity in cell identity. Here, we review our current understanding of transcription factor (TF) networks as key determinants of cell identity. We discuss the concept of the core regulatory circuit as a set of TFs and interacting factors that together define the gene expression profile of the cell. We propose the core regulatory circuit as a comprehensive conceptual framework for defining cellular identity and discuss its connections to cell function in different contexts.

Low Replicative Stress Triggers Cell-Type Specific Inheritable Advanced Replication Timing

DNA replication timing (RT), reflecting the temporal order of origin activation, is known as a robust and conserved cell-type specific process. Upon low replication stress, the slowing of replication forks induces well-documented RT delays associated to genetic instability, but it can also generate RT advances that are still uncharacterized. In order to characterize these advanced initiation events, we monitored the whole genome RT from six independent human cell lines treated with low doses of aphidicolin. We report that RT advances are cell-type-specific and involve large heterochromatin domains. Importantly, we found that some major late to early RT advances can be inherited by the unstressed next-cellular generation, which is a unique process that correlates with enhanced chromatin accessibility, as well as modified replication origin landscape and gene expression in daughter cells. Collectively, this work highlights how low replication stress may impact cellular identity by RT advances events at a subset of chromosomal domains.

Systematic Chromatin Accessibility Analysis Based on Different Immunological Subtypes of Clear Cell Renal Cell Carcinoma

Background

Recent research of clear cell renal cell carcinoma (ccRCC) is focused on the tumor immune microenvironment (TIME). Chromatin accessibility is critical for regulation of gene expression. However, its role in different immunological subtypes of ccRCC based on immune cell infiltration has not been systematically studied.

Methods

Five hundred thirty patient data from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) were adopted to estimate immune cell infiltration. Twenty-four types of immune cells were evaluated with single-sample Gene Set Enrichment Analysis (ssGSEA). Patients were divided into two clusters based on immune cell infiltration. Systematic chromatin accessibility analysis was conducted based on the two clusters.

Results

We compared the relative expression of the immune gene signatures among 530 patients of TCGA-KIRC using ssGSEA. Overall survival (OS) analysis revealed 10 types of immune cells were significantly associated with prognosis. Patients were divided into two clusters based on 24 types of immune cell infiltration. Immune cell signals as well as PD-1/PD-L1 signal were higher in cluster 1. Among the two clusters, 2,400 differential peaks were found in TCGA-KIRC Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) data. The distribution of differential peaks and prognosis-related immune cells in 23 chromosomes are essentially the same. There is no peak distribution downstream. The proportion of peaks upstream of the 5’ transcription start site decreases, and both sides of binding regions of the TSS 0.1-1 kb becomes smaller. Enrichment analysis of GO and KEGG of these differential peaks showed that they are remarkably related to the immune regulation in tumor microenvironment. Known motifs and de novo motifs were found by linking motif annotations to different peaks. Survival analysis of related motif transcription factors were prognostic. The GSEA enrichment analysis showed that high SP1 expression positively correlates with TGF-beta signaling and inflammatory response, while negatively correlates with TNF-alpha signaling via NFKB. High KLF12 expression negatively correlates with interferon gamma response, IL2-STAT5 signaling, TNF-alpha signaling via NFKB, IL6-JAK-STAT3 signaling.

Conclusion

The abnormality of chromatin accessibility may play an important regulatory role in ccRCC immunity.

Pan-cancer chromatin analysis of the human vtRNA genes uncovers their association with cancer biology

Background: The vault RNAs (vtRNAs) are a class of 84-141-nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, associated to the ribonucleoprotein complex known as vault particle. Of the four human vtRNA genes, vtRNA1-1, vtRNA1-2 and vtRNA1-3, clustered at locus 1, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cohorts have been hindered by their unsuccessful sequencing using conventional transcriptomic approaches.

Methods: VtRNA expression in The Cancer Genome Atlas (TCGA) Pan-Cancer cohort was estimated using the genome-wide DNA methylation and chromatin accessibility data (ATAC-seq) of their genes as surrogate variables. The association between vtRNA expression and patient clinical outcome, immune subtypes and transcriptionally co-regulated gene programs was analyzed in the dataset.

Results: VtRNAs promoters are enriched in transcription factors related to viral infection. VtRNA2-1 is likely the most independently regulated homologue. VtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer tissues. Meanwhile, vtRNA2-1 and vtRNA1-2 expression is widely deregulated in neoplastic tissues and its alteration is compatible with a broad oncogenic role for vtRNA1-2, and both tumor suppressor and oncogenic functions for vtRNA2-1. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of vtRNAs co-regulated genes identify a chromosome regulatory domain, epithelial differentiation, immune and thyroid cancer gene sets for specific vtRNAs. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes and vtRNA1-2 expression is positively associated with cell proliferation and wound healing.

Conclusions: Our study presents the landscape of vtRNA chromatin status cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.

ATF3 drives senescence by reconstructing accessible chromatin profiles

Chromatin organization and transcriptional profiles undergo tremendous reordering during senescence. However, uncovering the regulatory mechanisms between chromatin reconstruction and gene expression in senescence has been elusive. Here, we depicted the landscapes of both chromatin accessibility and gene expression to reveal gene regulatory networks in human umbilical vein endothelial cell (HUVEC) senescence and found that chromatin accessibilities are redistributed during senescence. Particularly, the intergenic chromatin was massively shifted with the increased accessibility regions (IARs) or decreased accessibility regions (DARs), which were mainly enhancer elements. We defined AP‐1 transcription factor family as being responsible for driving chromatin accessibility reconstruction in IARs, where low DNA methylation improved binding affinity of AP‐1 and further increased the chromatin accessibility. Among AP‐1 transcription factors, we confirmed ATF3 was critical to reconstruct chromatin accessibility to promote cellular senescence. Our results described a dynamic landscape of chromatin accessibility whose remodeling contributes to the senescence program, we identified that AP‐1 was capable of reorganizing the chromatin accessibility profile to regulate senescence.

PeakMatcher facilitates updated Aedes aegypti embryonic cis-regulatory element map

BACKGROUND

The Aedes aegypti mosquito is a threat to human health across the globe. The A. aegypti genome was recently re-sequenced and re-assembled. Due to a combination of long-read PacBio and Hi-C sequencing, the AaegL5 assembly is chromosome complete and significantly improves the assembly in key areas such as the M/m sex-determining locus. Release of the updated genome assembly has precipitated the need to reprocess historical functional genomic data sets, including cis-regulatory element (CRE) maps that had previously been generated for A. aegypti.

RESULTS

We re-processed and re-analyzed the A. aegypti whole embryo FAIRE seq data to create an updated embryonic CRE map for the AaegL5 genome. We validated that the new CRE map recapitulates key features of the original AaegL3 CRE map. Further, we built on the improved assembly in the M/m locus to analyze overlaps of open chromatin regions with genes. To support the validation, we created a new method (PeakMatcher) for matching peaks from the same experimental data set across genome assemblies.

CONCLUSION

Use of PeakMatcher software, which is available publicly under an open-source license, facilitated the release of an updated and validated CRE map, which is available through the NIH GEO. These findings demonstrate that PeakMatcher software will be a useful resource for validation and transferring of previous annotations to updated genome assemblies.

ATAC-Seq identifies regions of open chromatin in the bronchial lymph nodes of dairy calves experimentally challenged with bovine respiratory syncytial virus

Background

Bovine Respiratory Syncytial Virus (BRSV) is a cause of Bovine Respiratory Disease (BRD). DNA-based biomarkers contributing to BRD resistance are potentially present in non-protein-coding regulatory regions of the genome, which can be determined using ATAC-Seq. The objectives of this study were to: (i) identify regions of open chromatin in DNA extracted from bronchial lymph nodes (BLN) of healthy dairy calves experimentally challenged with BRSV and compare them with those from non-challenged healthy control calves, (ii) elucidate the chromatin regions that were differentially or uniquely open in the BRSV challenged relative to control calves, and (iii) compare the genes found in regions proximal to the differentially open regions to the genes previously found to be differentially expressed in the BLN in response to BRSV and to previously identified BRD susceptibility loci. This was achieved by challenging clinically healthy Holstein-Friesian calves (mean age 143 ± 14 days) with either BRSV inoculum (n = 12) or with sterile phosphate buffered saline (PBS) (n = 6) and preparing and sequencing ATAC-Seq libraries from fresh BLN tissues.

Results

Using Diffbind, 9,144 and 5,096 differentially accessible regions (P < 0.05, FDR < 0.05) were identified between BRSV challenged and control calves employing DeSeq2 and EdgeR, respectively. Additionally, 8,791 chromatin regions were found to be uniquely open in BRSV challenged calves. Seventy-six and 150 of the genes that were previously found to be differentially expressed using RNA-Seq, were located within 2 kb downstream of the differentially accessible regions, and of the regions uniquely open in BRSV challenged calves, respectively. Pathway analyses within ClusterProfiler indicated that these genes were involved in immune responses to infection and participated in the Th1 and Th2 pathways, pathogen recognition and the anti-viral response. There were 237 differentially accessible regions positioned within 40 previously identified BRD susceptibility loci.

Conclusions

The identified open chromatin regions are likely to be involved in the regulatory response of gene transcription induced by infection with BRSV. Consequently, they may contain variants which impact resistance to BRD that could be used in breeding programmes to select healthier, more robust cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07268-5.

Measuring Chromatin Accessibility: ATAC-Seq

Assay for Transposase-Accessible Chromatin using sequencing (ATAC-Seq) is a method to investigate the accessibility of chromatin in a genome-wide fashion. In this chapter, we provide a brief history of the chromatin accessibility field followed by a detailed protocol to perform ATAC-Seq assay.

ATAC-seq with unique molecular identifiers improves quantification and footprinting

ATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) provides an efficient way to analyze nucleosome-free regions and has been applied widely to identify transcription factor footprints. Both applications rely on the accurate quantification of insertion events of the hyperactive transposase Tn5. However, due to the presence of the PCR amplification, it is impossible to accurately distinguish independently generated identical Tn5 insertion events from PCR duplicates using the standard ATAC-seq technique. Removing PCR duplicates based on mapping coordinates introduces increasing bias towards highly accessible chromatin regions. To overcome this limitation, we establish a UMI-ATAC-seq technique by incorporating unique molecular identifiers (UMIs) into standard ATAC-seq procedures. UMI-ATAC-seq can rescue about 20% of reads that are mistaken as PCR duplicates in standard ATAC-seq in our study. We demonstrate that UMI-ATAC-seq could more accurately quantify chromatin accessibility and significantly improve the sensitivity of identifying transcription factor footprints. An analytic pipeline is developed to facilitate the application of UMI-ATAC-seq, and it is available at https://github.com/tzhu-bio/UMI-ATAC-seq .

Comparing a new method for mapping nucleosomes in simian virus 40 chromatin to standard procedures

The location of nucleosomes in chromatin significantly impacts many biological processes including DNA replication, repair, and gene expression. A number of techniques have been developed for mapping nucleosome locations in chromatin including MN-Seq (micrococcal nuclease digestion followed by next-generation sequencing), ATAC-Seq (Assay for Transposase-Accessible Chromatin followed by next-generation sequencing), and ChIP-Seq (chromatin immunoprecipitation and fragmentation followed by next-generation sequencing). All of these techniques have been successfully used, but each with its own limitations. Recently, New England Biolabs has marketed a new kit, the NEBNext Ultra II FS Library Prep kit, for preparing libraries for next-generation sequencing from purified genomic DNA. This kit is based on a novel proprietary DNA fragmentation procedure which appears to cleave DNA that is not bound by proteins. Because DNA is fragmented directly in the FS kit, we tested whether the kit might also be useful for mapping the location of nucleosomes in chromatin. Using simian virus 40 (SV40) chromatin isolated at different times in an infection, we have compared nucleosome mapping using the NEB FS kit (referred to as FS-Seq) to MN-Seq, ATAC-Seq, and ChIP-Seq. Mapping nucleosomes using FS-Seq generated nucleosome profiles similar to those generated by ATAC-Seq and ChIP-Seq in regulatory regions of the SV40 genome. We conclude that FS-Seq is a simple, robust, cost-effective procedure for mapping nucleosomes in SV40 chromatin that should be useful for other forms of chromatin as well. We also present evidence that FS-Seq may be useful for mapping transcription factors.

Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets

While the methods available for single-cell ATAC-seq analysis are well optimized for clustering cell types, the question of how to integrate multiple scATAC-seq data sets and/or sequencing modalities is still open. We present an analysis framework that enables such integration across scATAC-seq data sets by applying the CoGAPS Matrix Factorization algorithm and the projectR transfer learning program to identify common regulatory patterns across scATAC-seq data sets. We additionally integrate our analysis with scRNA-seq data to identify orthogonal evidence for transcriptional regulators predicted by scATAC-seq analysis. Using publicly available scATAC-seq data, we find patterns that accurately characterize cell types both within and across data sets. Furthermore, we demonstrate that these patterns are both consistent with current biological understanding and reflective of novel regulatory biology.