From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

Transient chromatin decompaction at the start of D. melanogaster male embryonic germline development

Embryonic germ cells develop rapidly to establish the foundation for future developmental trajectories, and in this process, they make critical lineage choices including the configuration of their unique identity and a decision on sex. Here, we use single-cell genomics patterns for the entire embryonic germline in Drosophila melanogaster along with the somatic gonadal precursors after embryonic gonad coalescence to investigate molecular mechanisms involved in the setting up and regulation of the germline program. Profiling of the early germline chromatin landscape revealed sex- and stage-specific features. In the male germline immediately after zygotic activation, the chromatin structure underwent a brief remodeling phase during which nucleosome density was lower and deconcentrated from promoter regions. These findings echoed enrichment analysis results of our genomics data in which top candidates were factors with the ability to mediate large-scale chromatin reorganization. Together, they point to the importance of chromatin regulation in the early germline and raise the possibility of a conserved epigenetic reprogramming-like process required for proper initiation of germline development.

Ki67 deficiency impedes chromatin accessibility and BCR gene rearrangement

The proliferation marker Ki67 has been attributed critical functions in maintaining mitotic chromosome morphology and heterochromatin organization during the cell cycle, indicating a potential role in developmental processes requiring rigid cell-cycle control. Here, we discovered that despite normal fecundity and organogenesis, germline deficiency in Ki67 resulted in substantial defects specifically in peripheral B and T lymphocytes. This was not due to impaired cell proliferation but rather to early lymphopoiesis at specific stages where antigen-receptor gene rearrangements occurred. We identified that Ki67 was required for normal global chromatin accessibility involving regulatory regions of genes critical for checkpoint stages in B cell lymphopoiesis. In line with this, mRNA expression of Rag1 was diminished and gene rearrangement was less efficient in the absence of Ki67. Transgenes encoding productively rearranged immunoglobulin heavy and light chains complemented Ki67 deficiency, completely rescuing early B cell development. Collectively, these results identify a unique contribution from Ki67 to somatic antigen-receptor gene rearrangement during lymphopoiesis.

Epigenomic landscape of the human dorsal root ganglion: sex differences and transcriptional regulation of nociceptive genes

Gene expression is influenced by chromatin architecture via controlled access of regulatory factors to DNA. To better understand gene regulation in the human dorsal root ganglion (hDRG) we used bulk and spatial transposase-accessible chromatin technology followed by sequencing (ATAC-seq). Using bulk ATAC-seq, we detected that in females diverse differentially accessible chromatin regions (DARs) mapped to the X chromosome and in males to autosomal genes. EGR1/3 and SP1/4 transcription factor binding motifs were abundant within DARs in females, and JUN, FOS and other AP-1 factors in males. To dissect the open chromatin profile in hDRG neurons, we used spatial ATAC-seq. The neuron cluster showed higher chromatin accessibility in GABAergic, glutamatergic, and interferon-related genes in females, and in Ca 2+ -signaling-related genes in males. Sex differences in transcription factor binding sites in neuron-proximal barcodes were consistent with the trends observed in bulk ATAC-seq data. We validated that EGR1 expression is biased to female hDRG compared to male. Strikingly, XIST , the long-noncoding RNA responsible for X inactivation, hybridization signal was found to be highly dispersed in the female neuronal but not non-neuronal nuclei suggesting weak X inactivation in female hDRG neurons. Our findings point to baseline epigenomic sex differences in the hDRG that likely underlie divergent transcriptional responses that determine mechanistic sex differences in pain.

The chromatin accessibility and transcriptomic landscape of the aging mice cochlea and the identification of potential functional super-enhancers in age-related hearing loss

BACKGROUND

Presbycusis, also referred to as age-related hearing loss (ARHL), is a condition that results from the cumulative effects of aging on an individual's auditory capabilities. Given the limited understanding of epigenetic mechanisms in ARHL, our research focuses on alterations in chromatin-accessible regions.

METHODS

We employed assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) in conjunction with unique identifier (UID) mRNA-seq between young and aging cochleae, and conducted integrated analysis as well as motif/TF-gene prediction. Additionally, the essential role of super-enhancers (SEs) in the development of ARHL was identified by comparative analysis to previous research. Meanwhile, an ARHL mouse model and an aging mimic hair cell (HC) model were established with a comprehensive identification of senescence phenotypes to access the role of SEs in ARHL progression.

RESULTS

The control cochlear tissue exhibited greater chromatin accessibility than cochlear tissue affected by ARHL. Furthermore, the levels of histone 3 lysine 27 acetylation were significantly depressed in both aging cochlea and aging mimic HEI-OC1 cells, highlighting the essential role of SEs in the development of ARHL. The potential senescence-associated super-enhancers (SASEs) of ARHL were identified, most of which exhibited decreased chromatin accessibility. The majority of genes related to the SASEs showed obvious decreases in mRNA expression level in aging HCs and was noticeably altered following treatment with JQ1 (a commonly used SE inhibitor).

CONCLUSION

The chromatin accessibility in control cochlear tissue was higher than that in cochlear tissue affected by ARHL. Potential SEs involved in ARHL were identified, which might provide a basis for future therapeutics targeting SASEs related to ARHL.

Fibroblasts as an in vitro model of circadian genetic and genomic studies

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 h period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

Emerging trends in the study of spiralian larvae

Many animals undergo indirect development, where their embryogenesis produces an intermediate life stage, or larva, that is often free-living and later metamorphoses into an adult. As their adult counterparts, larvae can have unique and diverse morphologies and occupy various ecological niches. Given their broad phylogenetic distribution, larvae have been central to hypotheses about animal evolution. However, the evolution of these intermediate forms and the developmental mechanisms diversifying animal life cycles are still debated. This review focuses on Spiralia, a large and diverse clade of bilaterally symmetrical animals with a fascinating array of larval forms, most notably the archetypical trochophore larva. We explore how classic research and modern advances have improved our understanding of spiralian larvae, their development, and evolution. Specifically, we examine three morphological features of spiralian larvae: the anterior neural system, the ciliary bands, and the posterior hyposphere. The combination of molecular and developmental evidence with modern high-throughput techniques, such as comparative genomics, single-cell transcriptomics, and epigenomics, is a promising strategy that will lead to new testable hypotheses about the mechanisms behind the evolution of larvae and life cycles in Spiralia and animals in general. We predict that the increasing number of available genomes for Spiralia and the optimization of genome-wide and single-cell approaches will unlock the study of many emerging spiralian taxa, transforming our views of the evolution of this animal group and their larvae.

From degraded to deciphered: ATAC-seq's application potential in forensic diagnosis

In recent years, molecular biology-based diagnostic techniques have made remarkable strides and are now extensively utilized in clinical practice, providing invaluable insights for disease diagnosis and treatment. However, forensic medicine, especially forensic pathology, has witnessed relatively limited progress in the application of molecular biology technologies. A significant challenge in employing molecular techniques for forensic diagnoses lies in the quantitative and qualitative changes observed in diagnostic markers due to sample degradation-a recognized and formidable obstacle. Inspired by the success of DNA sequencing in forensic practices, which enables accurate individual identification even in cases involving degraded and deteriorated tissues and organs, we propose the application of the assay for transposase-accessible chromatin with sequencing (ATAC-seq) to identify targets at the transcriptional onset, exploring chromatin and DNA-level alterations for injury and disease inference in forensic samples. This study employs ATAC-seq to explore alterations in chromatin accessibility post-injury and their subsequent changes over a 2-h degradation period, employing traumatic brain injury (TBI) as a representative model. Our findings reveal high sensitivity of chromatin accessibility sites to injury, evidenced by shifts in thousands of peak positions post-TBI. Remarkably, these alterations remain largely unaffected by early degradation. Our results robustly endorse the notion that integrating and incorporating these specific loci for injury and disease diagnosis in forensic samples holds tremendous promise for practical application. We further validated the above results using human cortical tissue, which supported that early degradation did not significantly affect chromatin accessibility. This pioneering advancement in molecular diagnostic techniques may revolutionize the field of forensic science, especially forensic pathology.

A new mechanism in negative pressure wound therapy: interleukin-17 alters chromatin accessibility profiling

Negative pressure wound therapy (NPWT) is extensively used in clinical settings to enhance the healing of wounds. Despite its widespread use, the molecular mechanisms driving the efficacy of NPWT have not been fully elucidated. In this study, skin wound-healing models were established, with administration of NPWT. Vimentin, collagen I, and MMP9 of skin tissues were detected by immunofluorescence (IF). Gene expression analysis of skin wound tissues was performed by RNA-sequencing (RNA-seq). Protein expression was assayed by a Western blotting or IF assay, and mRNA levels were quantified by quantitative PCR. Chromatin accessibility profiles of fibroblasts following NPWT or IL-17 exposure were analyzed by ATAC-seq. In rat wound-healing models, NPWT promoted wound repair by promoting reepithelialization, extracellular matrix (ECM) synthesis, and proliferation, which mainly occurred in the early stage of wound healing. These differentially expressed genes (DEGs) in NPWT wounds versus control wounds were enriched in the IL-17 signaling pathway. IL-17 was identified as an upregulated factor following NPWT in skin wounds. Moreover, the IL-17 inhibitor secukinumab (SEC) could abolish the promoting effect of NPWT on wound healing. Importantly, chromatin accessibility profiles were altered following NPWT and IL-17 stimulation in skin fibroblasts. Our findings suggest that NPWT upregulates IL-17 to promote wound healing by altering chromatin accessibility, which is a novel mechanism for NPWT's efficacy in wound healing.NEW & NOTEWORTHY To our knowledge, this is the first report of the efficacy of negative pressure wound therapy (NPWT) in promoting wound healing via IL-17. Moreover, NPWT and IL-17 can alter chromatin accessibility. Our study identifies a novel mechanism for NPWT's efficacy in wound healing.

Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue

Spatial epigenetic mapping of tissues enables the study of gene regulation programs and cellular functions with the dependency on their local tissue environment. Here we outline a complete procedure for two spatial epigenomic profiling methods: spatially resolved genome-wide profiling of histone modifications using in situ cleavage under targets and tagmentation (CUT&Tag) chemistry (spatial-CUT&Tag) and transposase-accessible chromatin sequencing (spatial-ATAC-sequencing) for chromatin accessibility. Both assays utilize in-tissue Tn5 transposition to recognize genomic DNA loci followed by microfluidic deterministic barcoding to incorporate spatial address codes. Furthermore, these two methods do not necessitate prior knowledge of the transcription or epigenetic markers for a given tissue or cell type but permit genome-wide unbiased profiling pixel-by-pixel at the 10 μm pixel size level and single-base resolution. To support the widespread adaptation of these methods, details are provided in five general steps: (1) sample preparation; (2) Tn5 transposition in spatial-ATAC-sequencing or antibody-controlled pA-Tn5 tagmentation in CUT&Tag; (3) library preparation; (4) next-generation sequencing; and (5) data analysis using our customed pipelines available at: https://github.com/dyxmvp/Spatial_ATAC-seq and https://github.com/dyxmvp/spatial-CUT-Tag . The whole procedure can be completed on four samples in 2-3 days. Familiarity with basic molecular biology and bioinformatics skills with access to a high-performance computing environment are required. A rudimentary understanding of pathology and specimen sectioning, as well as deterministic barcoding in tissue-specific skills (e.g., design of a multiparameter barcode panel and creation of microfluidic devices), are also advantageous. In this protocol, we mainly focus on spatial profiling of tissue region-specific epigenetic landscapes in mouse embryos and mouse brains using spatial-ATAC-sequencing and spatial-CUT&Tag, but these methods can be used for other species with no need for species-specific probe design.

Identifying dysregulated regions in amyotrophic lateral sclerosis through chromatin accessibility outliers

The high heritability of amyotrophic lateral sclerosis (ALS) contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone chromatin immunoprecipitation sequencing and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.

BIT: Bayesian Identification of Transcriptional Regulators

BIT is a novel Bayesian hierarchical model capable of predicting transcriptional regulators (TRs) from the input of user-provided epigenomic regions. TRs are critical molecules in transcriptional regulation. Many diseases and cancers are linked to the dysfunction of TRs. Knowing TRs in certain biological process can help find new biomarkers or therapeutic targets. Thus, BIT formulates a novel Bayesian hierarchical model with the Pólya-gamma data augmentation strategy. Based on collected ChIP-seq datasets, BIT can identify TRs responsible for the genome-wide binding pattern within the user-provided epigenomic regions. BIT has been validated by using a simulation study and three applications.

OneSC: A computational platform for recapitulating cell state transitions

Computational modelling of cell state transitions has been a great interest of many in the field of developmental biology, cancer biology and cell fate engineering because it enables performing perturbation experiments in silico more rapidly and cheaply than could be achieved in a wet lab. Recent advancements in single-cell RNA sequencing (scRNA-seq) allow the capture of high-resolution snapshots of cell states as they transition along temporal trajectories. Using these high-throughput datasets, we can train computational models to generate in silico 'synthetic' cells that faithfully mimic the temporal trajectories. Here we present OneSC, a platform that can simulate synthetic cells across developmental trajectories using systems of stochastic differential equations govern by a core transcription factors (TFs) regulatory network. Different from the current network inference methods, OneSC prioritizes on generating Boolean network that produces faithful cell state transitions and steady cell states that mimic real biological systems. Applying OneSC to real data, we inferred a core TF network using a mouse myeloid progenitor scRNA-seq dataset and showed that the dynamical simulations of that network generate synthetic single-cell expression profiles that faithfully recapitulate the four myeloid differentiation trajectories going into differentiated cell states (erythrocytes, megakaryocytes, granulocytes and monocytes). Finally, through the in-silico perturbations of the mouse myeloid progenitor core network, we showed that OneSC can accurately predict cell fate decision biases of TF perturbations that closely match with previous experimental observations.

Vaginal microbes alter epithelial transcriptome and induce epigenomic modifications providing insight into mechanisms for susceptibility to adverse reproductive outcomes

The cervicovaginal microbiome is highly associated with women's health, with microbial communities dominated by Lactobacillus species considered optimal. Conversely, a lack of lactobacilli and a high abundance of strict and facultative anaerobes, including Gardnerella vaginalis, have been associated with adverse reproductive outcomes. However, how host-microbial interactions alter specific molecular pathways and impact cervical and vaginal epithelial function remains unclear. Using RNA-sequencing, we characterized the in vitro cervicovaginal epithelial transcriptional response to different vaginal bacteria and their culture supernatants. We showed that G. vaginalis upregulates genes associated with an activated innate immune response. Unexpectedly, G. vaginalis specifically induced inflammasome pathways through activation of NLRP3-mediated increases in caspase-1, IL-1β and cell death, while live L. crispatus had minimal transcriptomic changes on epithelial cells. L. crispatus culture supernatants resulted in a shift in the epigenomic landscape of cervical epithelial cells that was confirmed by ATAC-sequencing showing reduced chromatin accessibility. This study reveals new insights into host-microbe interactions in the lower reproductive tract and suggests potential therapeutic strategies leveraging the vaginal microbiome to improve reproductive health.

Emerging Approaches to Profile Accessible Chromatin from Formalin-Fixed Paraffin-Embedded Sections

Nucleosomes are non-uniformly distributed across eukaryotic genomes, with stretches of 'open' chromatin strongly associated with transcriptionally active promoters and enhancers. Understanding chromatin accessibility patterns in normal tissue and how they are altered in pathologies can provide critical insights to development and disease. With the advent of high-throughput sequencing, a variety of strategies have been devised to identify open regions across the genome, including DNase-seq, MNase-seq, FAIRE-seq, ATAC-seq, and NicE-seq. However, the broad application of such methods to FFPE (formalin-fixed paraffin-embedded) tissues has been curtailed by the major technical challenges imposed by highly fixed and often damaged genomic material. Here, we review the most common approaches for mapping open chromatin regions, recent optimizations to overcome the challenges of working with FFPE tissue, and a brief overview of a typical data pipeline with analysis considerations.

A review of single-cell transcriptomics and epigenomics studies in maternal and child health

Single-cell sequencing technologies enhance our understanding of cellular dynamics throughout pregnancy. We outlined the workflow of single-cell sequencing techniques and reviewed single-cell studies in maternal and child health. We conducted a literature review of single cell studies on maternal and child health using PubMed. We summarized the findings from 16 single-cell atlases of the human and mammalian placenta across gestational stages and 31 single-cell studies on maternal exposures and complications including infection, obesity, diet, gestational diabetes, pre-eclampsia, environmental exposure and preterm birth. Single-cell studies provides insights on novel cell types in placenta and cell type-specific marks associated with maternal exposures and complications.

RNA expression changes driven by altered epigenetics status related to NASH etiology

Non-alcoholic fatty liver disease (NAFLD) is a growing health problem due to the increased obesity rates, among other factors. In its more severe stage (NASH), inflammation, hepatocellular ballooning and fibrosis are present in the liver, which can further evolve to total liver dysfunction or even hepatocarcinoma. As a metabolic disease, is associated to environmental factors such as diet and lifestyle conditions, which in turn can influence the epigenetic landscape of the cells, affecting to the gene expression profile and chromatin organization. In this study we performed ATAC-sequencing and RNA-sequencing to interrogate the chromatin status of liver biopsies in subjects with and without NASH and its effects on RNA transcription and NASH etiology. NASH subjects showed transcriptional downregulation for lipid and glucose metabolic pathways (e.g., ABC transporters, AMPK, FoxO or insulin pathways). A total of 229 genes were differentially enriched (ATAC and mRNA) in NASH, which were mainly related to lipid transport activity, nuclear receptor-binding, dicarboxylic acid transporter, and PPARA lipid regulation. Interpolation of ATAC data with known liver enhancer regions showed differential openness at 8 enhancers, some linked to genes involved in lipid metabolism, (i.e., FASN) and glucose homeostasis (i.e., GCGR). In conclusion, the chromatin landscape is altered in NASH patients compared to patients without this liver condition. This alteration might cause mRNA changes explaining, at least partially, the etiology and pathophysiology of the disease.

MMGAT: a graph attention network framework for ATAC-seq motifs finding

BACKGROUND

Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths. GNN-based methods has the limitation of using the edge weight information directly, makes it difficult to aggregate the neighboring nodes' information more efficiently when representing node embedding.

RESULTS

To address this challenge, we developed a novel graph attention network framework named MMGAT, which employs an attention mechanism to adjust the attention coefficients among different nodes. And then MMGAT finds multiple ATAC-seq motifs based on the attention coefficients of sequence nodes and k-mer nodes as well as the coexisting probability of k-mers. Our approach achieved better performance on the human ATAC-seq datasets compared to existing tools, as evidenced the highest scores on the precision, recall, F1_score, ACC, AUC, and PRC metrics, as well as finding 389 higher quality motifs. To validate the performance of MMGAT in predicting TFBSs and finding motifs on more datasets, we enlarged the number of the human ATAC-seq datasets to 180 and newly integrated 80 mouse ATAC-seq datasets for multi-species experimental validation. Specifically on the mouse ATAC-seq dataset, MMGAT also achieved the highest scores on six metrics and found 356 higher-quality motifs. To facilitate researchers in utilizing MMGAT, we have also developed a user-friendly web server named MMGAT-S that hosts the MMGAT method and ATAC-seq motif finding results.

CONCLUSIONS

The advanced methodology MMGAT provides a robust tool for finding ATAC-seq motifs, and the comprehensive server MMGAT-S makes a significant contribution to genomics research. The open-source code of MMGAT can be found at https://github.com/xiaotianr/MMGAT , and MMGAT-S is freely available at https://www.mmgraphws.com/MMGAT-S/ .

Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed)

BACKGROUND

Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g., in human base composition. In this article, we develop a class of Hidden Markov Models (HMMs) called oHMMed (ordered HMM with emission densities, the corresponding R package of the same name is available on CRAN): They identify the number of comparably homogeneous regions within autocorrelated observed sequences. These are modelled as discrete hidden states; the observed data points are realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are inferred.

RESULTS

We apply our oHMMed algorithms to the proportion of G and C bases (modelled as a mixture of normal distributions) and the number of genes (modelled as a mixture of poisson-gamma distributions) in windows along the human, mouse, and fruit fly genomes. This results in a partitioning of the genomes into regions by statistically distinguishable averages of these features, and in a characterisation of their continuous patterns of variation. In regard to the genomic G and C proportion, this latter result distinguishes oHMMed from segmentation algorithms based in isochore or compositional domain theory. We further use oHMMed to conduct a detailed analysis of variation of chromatin accessibility (ATAC-seq) and epigenetic markers H3K27ac and H3K27me3 (modelled as a mixture of poisson-gamma distributions) along the human chromosome 1 and their correlations.

CONCLUSIONS

Our algorithms provide a biologically assumption free approach to characterising genomic landscapes shaped by continuous, autocorrelated patterns of variation. Despite this, the resulting genome segmentation enables extraction of compositionally distinct regions for further downstream analyses.

The genetic regulatory architecture and epigenomic basis for age-related changes in rattlesnake venom

Developmental phenotypic changes can evolve under selection imposed by age- and size-related ecological differences. Many of these changes occur through programmed alterations to gene expression patterns, but the molecular mechanisms and gene-regulatory networks underlying these adaptive changes remain poorly understood. Many venomous snakes, including the eastern diamondback rattlesnake (Crotalus adamanteus), undergo correlated changes in diet and venom expression as snakes grow larger with age, providing models for identifying mechanisms of timed expression changes that underlie adaptive life history traits. By combining a highly contiguous, chromosome-level genome assembly with measures of expression, chromatin accessibility, and histone modifications, we identified cis-regulatory elements and trans-regulatory factors controlling venom ontogeny in the venom glands of C. adamanteus. Ontogenetic expression changes were significantly correlated with epigenomic changes within genes, immediately adjacent to genes (e.g., promoters), and more distant from genes (e.g., enhancers). We identified 37 candidate transcription factors (TFs), with the vast majority being up-regulated in adults. The ontogenetic change is largely driven by an increase in the expression of TFs associated with growth signaling, transcriptional activation, and circadian rhythm/biological timing systems in adults with corresponding epigenomic changes near the differentially expressed venom genes. However, both expression activation and repression contributed to the composition of both adult and juvenile venoms, demonstrating the complexity and potential evolvability of gene regulation for this trait. Overall, given that age-based trait variation is common across the tree of life, we provide a framework for understanding gene-regulatory-network-driven life-history evolution more broadly.

Single-cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveal heterogeneity of endothelial subtype and response to activating perturbations

Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nuclei using Microwell-seq3

Single cell chromatin accessibility profiling and transcriptome sequencing are the most widely used technologies for single-cell genomics. Here, we present Microwell-seq3, a high-throughput and facile platform for high-sensitivity single-nucleus chromatin accessibility or full-length transcriptome profiling. The method combines a preindexing strategy and a penetrable chip-in-a-tube for single nucleus loading and DNA amplification and therefore does not require specialized equipment. We used Microwell-seq3 to profile chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in ~50,000 nuclei from multiple adult mouse tissues. Compared with the existing polyadenylated transcript capture methods, integrative analysis of cell type-specific regulatory elements and total RNA expression uncovered comprehensive cell type heterogeneity in the brain. Gene regulatory networks based on chromatin accessibility profiling provided an improved cell type communication model. Finally, we demonstrated that Microwell-seq3 can identify malignant cells and their specific regulons in spontaneous lung tumors of aged mice. We envision a broad application of Microwell-seq3 in many areas of research.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

Dominance reversals: the resolution of genetic conflict and maintenance of genetic variation

Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait or sex) being dominant in that context but recessive where deleterious. This context dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here, we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods that could facilitate the identification of antagonistic genetic variation (dominance ordination, allele-specific expression and allele-specific ATAC-Seq (assay for transposase-accessible chromatin with sequencing)). There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation.

Fibroblasts as an in vitro model of circadian genetic and genomic studies: A temporal analysis

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 hour period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression (sLDSC) analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

Trisomy 21-driven metabolite alterations are linked to cellular injuries in Down syndrome

Down syndrome (DS) arises from a genetic anomaly characterized by an extra copy of chromosome 21 (exCh21). Despite high incidence of congenital diseases among DS patients, direct impacts of exCh21 remain elusive. Here, we established a robust DS model harnessing human-induced pluripotent stem cells (hiPSCs) from mosaic DS patient. These hiPSC lines encompassed both those with standard karyotype and those carrying an extra copy of exCh21, allowing to generate isogenic cell lines with a consistent genetic background. We unraveled that exCh21 inflicted disruption upon the cellular transcriptome, ushering in alterations in metabolic processes and triggering DNA damage. The impact of exCh21 was also manifested in profound modifications in chromatin accessibility patterns. Moreover, we identified two signature metabolites, 5-oxo-ETE and Calcitriol, whose biosynthesis is affected by exCh21. Notably, supplementation with 5-oxo-ETE promoted DNA damage, in stark contrast to the protective effect elicited by Calcitriol against such damage. We also found that exCh21 disrupted cardiogenesis, and that this impairment could be mitigated through supplementation with Calcitriol. Specifically, the deleterious effects of 5-oxo-ETE unfolded in the form of DNA damage induction and the repression of cardiogenesis. On the other hand, Calcitriol emerged as a potent activator of its nuclear receptor VDR, fostering amplified binding to chromatin and subsequent facilitation of gene transcription. Our findings provide a comprehensive understanding of exCh21's metabolic implications within the context of Down syndrome, offering potential avenues for therapeutic interventions for Down syndrome treatment.

Cross-Omic Transcription Factor Analysis: An Insight on Transcription Factor Accessibility and Expression Correlation

It is well known how sequencing technologies propelled cellular biology research in recent years, providing incredible insight into the basic mechanisms of cells. Single-cell RNA sequencing is at the front in this field, with single-cell ATAC sequencing supporting it and becoming more popular. In this regard, multi-modal technologies play a crucial role, allowing the possibility to simultaneously perform the mentioned sequencing modalities on the same cells. Yet, there still needs to be a clear and dedicated way to analyze these multi-modal data. One of the current methods is to calculate the Gene Activity Matrix (GAM), which summarizes the accessibility of the genes at the genomic level, to have a more direct link with the transcriptomic data. However, this concept is not well defined, and it is unclear how various accessible regions impact the expression of the genes. Moreover, the transcription process is highly regulated by the transcription factors that bind to the different DNA regions. Therefore, this work presents a continuation of the meta-analysis of Genomic-Annotated Gene Activity Matrix (GAGAM) contributions, aiming to investigate the correlation between the TF expression and motif information in the different functional genomic regions to understand the different Transcription Factors (TFs) dynamics involved in different cell types.

Common mitochondrial deletions in RNA-Seq: evaluation of bulk, single-cell, and spatial transcriptomic datasets

Common mitochondrial DNA (mtDNA) deletions are large structural variants in the mitochondrial genome that accumulate in metabolically active tissues with age and have been investigated in various diseases. We applied the Splice-Break2 pipeline (designed for high-throughput quantification of mtDNA deletions) to human RNA-Seq datasets and describe the methodological considerations for evaluating common deletions in bulk, single-cell, and spatial transcriptomics datasets. A robust evaluation of 1570 samples from 14 RNA-Seq studies showed: (i) the abundance of some common deletions detected in PCR-amplified mtDNA correlates with levels observed in RNA-Seq data; (ii) RNA-Seq library preparation method has a strong effect on deletion detection; (iii) deletions had a significant, positive correlation with age in brain and muscle; (iv) deletions were enriched in cortical grey matter, specifically in layers 3 and 5; and (v) brain regions with dopaminergic neurons (i.e., substantia nigra, ventral tegmental area, and caudate nucleus) had remarkable enrichment of common mtDNA deletions.

Improved metagenome assemblies through selective enrichment of bacterial genomic DNA from eukaryotic host genomic DNA using ATAC-seq

Genomics can be used to study the complex relationships between hosts and their microbiota. Many bacteria cannot be cultured in the laboratory, making it difficult to obtain adequate amounts of bacterial DNA and to limit host DNA contamination for the construction of metagenome-assembled genomes (MAGs). For example, Wolbachia is a genus of exclusively obligate intracellular bacteria that live in a wide range of arthropods and some nematodes. While Wolbachia endosymbionts are frequently described as facultative reproductive parasites in arthropods, the bacteria are obligate mutualistic endosymbionts of filarial worms. Here, we achieve 50-fold enrichment of bacterial sequences using ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) with Brugia malayi nematodes, containing Wolbachia (wBm). ATAC-seq uses the Tn5 transposase to cut and attach Illumina sequencing adapters to accessible DNA lacking histones, typically thought to be open chromatin. Bacterial and mitochondrial DNA in the lysates are also cut preferentially since they lack histones, leading to the enrichment of these sequences. The benefits of this include minimal tissue input (<1 mg of tissue), a quick protocol (<4 h), low sequencing costs, less bias, correct assembly of lateral gene transfers and no prior sequence knowledge required. We assembled the wBm genome with as few as 1 million Illumina short paired-end reads with >97% coverage of the published genome, compared to only 12% coverage with the standard gDNA libraries. We found significant bacterial sequence enrichment that facilitated genome assembly in previously published ATAC-seq data sets from human cells infected with Mycobacterium tuberculosis and C. elegans contaminated with their food source, the OP50 strain of E. coli. These results demonstrate the feasibility and benefits of using ATAC-seq to easily obtain bacterial genomes to aid in symbiosis, infectious disease, and microbiome research.

Ehf and Fezf2 regulate late medullary thymic epithelial cell and thymic tuft cell development

Thymic epithelial cells are indispensable for T cell maturation and selection and the induction of central immune tolerance. The self-peptide repertoire expressed by medullary thymic epithelial cells is in part regulated by the transcriptional regulator Aire (Autoimmune regulator) and the transcription factor Fezf2. Due to the high complexity of mTEC maturation stages (i.e., post-Aire, Krt10+ mTECs, and Dclk1+ Tuft mTECs) and the heterogeneity in their gene expression profiles (i.e., mosaic expression patterns), it has been challenging to identify the additional factors complementing the transcriptional regulation. We aimed to identify the transcriptional regulators involved in the regulation of mTEC development and self-peptide expression in an unbiased and genome-wide manner. We used ATAC footprinting analysis as an indirect approach to identify transcription factors involved in the gene expression regulation in mTECs, which we validated by ChIP sequencing. This study identifies Fezf2 as a regulator of the recently described thymic Tuft cells (i.e., Tuft mTECs). Furthermore, we identify that transcriptional regulators of the ELF, ESE, ERF, and PEA3 subfamily of the ETS transcription factor family and members of the Krüppel-like family of transcription factors play a role in the transcriptional regulation of genes involved in late mTEC development and promiscuous gene expression.

Positive Selection Drives cis-regulatory Evolution Across the Threespine Stickleback Y Chromosome

Allele-specific gene expression evolves rapidly on heteromorphic sex chromosomes. Over time, the accumulation of mutations on the Y chromosome leads to widespread loss of gametolog expression, relative to the X chromosome. It remains unclear if expression evolution on degrading Y chromosomes is primarily driven by mutations that accumulate through processes of selective interference, or if positive selection can also favor the down-regulation of coding regions on the Y chromosome that contain deleterious mutations. Identifying the relative rates of cis-regulatory sequence evolution across Y chromosomes has been challenging due to the limited number of reference assemblies. The threespine stickleback (Gasterosteus aculeatus) Y chromosome is an excellent model to identify how regulatory mutations accumulate on Y chromosomes due to its intermediate state of divergence from the X chromosome. A large number of Y-linked gametologs still exist across 3 differently aged evolutionary strata to test these hypotheses. We found that putative enhancer regions on the Y chromosome exhibited elevated substitution rates and decreased polymorphism when compared to nonfunctional sites, like intergenic regions and synonymous sites. This suggests that many cis-regulatory regions are under positive selection on the Y chromosome. This divergence was correlated with X-biased gametolog expression, indicating the loss of expression from the Y chromosome may be favored by selection. Our findings provide evidence that Y-linked cis-regulatory regions exhibit signs of positive selection quickly after the suppression of recombination and allow comparisons with recent theoretical models that suggest the rapid divergence of regulatory regions may be favored to mask deleterious mutations on the Y chromosome.

Representing and extracting knowledge from single-cell data

Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of advanced statistics and machine learning. This review attempts to explain the deeper theoretical concepts that underpin current state-of-the-art analysis methods. Single-cell analysis is covered from cell, through instruments, to current and upcoming models. The aim of this review is to spread concepts which are not yet in common use, especially from topology and generative processes, and how new statistical models can be developed to capture more of biology. This opens epistemological questions regarding our ontology and models, and some pointers will be given to how natural language processing (NLP) may help overcome our cognitive limitations for understanding single-cell data.

Application of Single-Cell Assay for Transposase-Accessible Chromatin with High Throughput Sequencing in Plant Science: Advances, Technical Challenges, and Prospects

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.

Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster ( Crassostrea ariakensis)

Glycogen serves as the principal energy reserve for metabolic processes in aquatic shellfish and substantially contributes to the flavor and quality of oysters. The Jinjiang oyster ( Crassostrea ariakensis) is an economically and ecologically important species in China. In the present study, RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) were performed to investigate gene expression and chromatin accessibility variations in oysters with different glycogen contents. Analysis identified 9 483 differentially expressed genes (DEGs) and 7 215 genes with significantly differential chromatin accessibility (DCAGs) were obtained, with an overlap of 2 600 genes between them. Notably, a significant proportion of these genes were enriched in pathways related to glycogen metabolism, including "Glycogen metabolic process" and "Starch and sucrose metabolism". In addition, genome-wide association study (GWAS) identified 526 single nucleotide polymorphism (SNP) loci associated with glycogen content. These loci corresponded to 241 genes, 63 of which were categorized as both DEGs and DCAGs. This study enriches basic research data and provides insights into the molecular mechanisms underlying the regulation of glycogen metabolism in C. ariakensis.

3D genome structural variations play important roles in regulating seed oil content of Brassica napus

Dissecting the complex regulatory mechanism of seed oil content (SOC) is one of the main research goals in Brassica napus. Increasing evidence suggests that genome architecture is linked to multiple biological functions. However, the effect of genome architecture on SOC regulation remains unclear. Here, we used high-throughput chromatin conformation capture to characterize differences in the three-dimensional (3D) landscape of genome architecture of seeds from two B. napus lines, N53-2 (with high SOC) and Ken-C8 (with low SOC). Bioinformatics analysis demonstrated that differentially accessible regions and differentially expressed genes between N53-2 and Ken-C8 were preferentially enriched in regions with quantitative trait loci (QTLs)/associated genomic regions (AGRs) for SOC. A multi-omics analysis demonstrated that expression of SOC-related genes was tightly correlated with genome structural variations in QTLs/AGRs of B. napus. The candidate gene BnaA09g48250D, which showed structural variation in a QTL/AGR on chrA09, was identified by fine-mapping of a KN double-haploid population derived from hybridization of N53-2 and Ken-C8. Overexpression and knockout of BnaA09g48250D led to significant increases and decreases in SOC, respectively, in the transgenic lines. Taken together, our results reveal the 3D genome architecture of B. napus seeds and the roles of genome structural variations in SOC regulation, enriching our understanding of the molecular mechanisms of SOC regulation from the perspective of spatial chromatin structure.

Traces of Canine Inflammatory Bowel Disease Reflected by Intestinal Organoids

Inflammatory bowel disease (IBD) is a chronic inflammatory condition that affects humans and several domestic animal species, including cats and dogs. In this study, we have analyzed duodenal organoids derived from canine IBD patients using quantitative proteomics. Our objective was to investigate whether these organoids show phenotypic traits of the disease compared with control organoids obtained from healthy donors. To this aim, IBD and control organoids were subjected to quantitative proteomics analysis via liquid chromatography-mass spectrometry. The obtained data revealed notable differences between the two groups. The IBD organoids exhibited several alterations at the levels of multiple proteins that are consistent with some known IBD alterations. The observed phenotype in the IBD organoids to some degree mirrors the corresponding intestinal condition, rendering them a compelling approach for investigating the disease and advancing drug exploration. Additionally, our study revealed similarities to some human IBD biomarkers, further emphasizing the translational and comparative value of dogs for future investigations related to the causes and treatment of IBD. Relevant proteins such as CALU, FLNA, MSN and HMGA2, which are related to intestinal diseases, were all upregulated in the IBD duodenal organoids. At the same time, other proteins such as intestinal keratins and the mucosal immunity PIGR were depleted in these IBD organoids. Based on these findings, we propose that these organoids could serve as a valuable tool for evaluating the efficacy of therapeutic interventions against canine IBD.

Integration of ATAC-Seq and RNA-Seq Analysis to Identify Key Genes in the Longissimus Dorsi Muscle Development of the Tianzhu White Yak

During the postnatal stages, skeletal muscle development undergoes a series of meticulously regulated alterations in gene expression. However, limited studies have employed chromatin accessibility to unravel the underlying molecular mechanisms governing muscle development in yak species. Therefore, we conducted an analysis of both gene expression levels and chromatin accessibility to comprehensively characterize the dynamic genome-wide chromatin accessibility during muscle growth and development in the Tianzhu white yak, thereby elucidating the features of accessible chromatin regions throughout this process. Initially, we compared the differences in chromatin accessibility between two groups and observed that calves exhibited higher levels of chromatin accessibility compared to adult cattle, particularly within ±2 kb of the transcription start site (TSS). In order to investigate the correlation between alterations in chromatin accessible regions and variations in gene expression levels, we employed a combination of ATAC-seq and RNA-seq techniques, leading to the identification of 18 central transcriptional factors (TFs) and 110 key genes with significant effects. Through further analysis, we successfully identified several TFs, including Sp1, YY1, MyoG, MEF2A and MEF2C, as well as a number of candidate genes (ANKRD2, ANKRD1, BTG2 and LMOD3) which may be closely associated with muscle growth and development. Moreover, we constructed an interactive network program encompassing hub TFs and key genes related to muscle growth and development. This innovative approach provided valuable insights into the molecular mechanism underlying skeletal muscle development in the postnatal stages of Tianzhu white yaks while also establishing a solid theoretical foundation for future research on yak muscle development.

Dynamics of chromatin accessibility and genome wide control of desiccation tolerance in the resurrection plant Haberlea rhodopensis

BACKGROUND

Drought is one of the main consequences of global climate change and this problem is expected to intensify in the future. Resurrection plants evolved the ability to withstand the negative impact of long periods of almost complete desiccation and to recover at rewatering. In this respect, many physiological, transcriptomic, proteomic and genomic investigations have been performed in recent years, however, few epigenetic control studies have been performed on these valuable desiccation-tolerant plants so far.

RESULTS

In the present study, for the first time for resurrection plants we provide evidences about the differential chromatin accessibility of Haberlea rhodopensis during desiccation stress by ATAC-seq (Assay for Transposase Accessible Chromatin with high-throughput sequencing). Based on gene similarity between species, we used the available genome of the closely related resurrection plant Dorcoceras hygrometricum to identify approximately nine hundred transposase hypersensitive sites (THSs) in H. rhodopensis. The majority of them corresponds to proximal and distal regulatory elements of different genes involved in photosynthesis, carbon metabolism, synthesis of secondary metabolites, cell signalling and transcriptional regulation, cell growth, cell wall, stomata conditioning, chaperons, oxidative stress, autophagy and others. Various types of binding motifs recognized by several families of transcription factors have been enriched from the THSs found in different stages of drought. Further, we used the previously published RNA-seq data from H. rhodopensis to evaluate the expression of transcription factors putatively interacting with the enriched motifs, and the potential correlation between the identified THS and the expression of their corresponding genes.

CONCLUSIONS

These results provide a blueprint for investigating the epigenetic regulation of desiccation tolerance in resurrection plant H. rhodopensis and comparative genomics between resurrection and non-resurrection species with available genome information.

A longitudinal single-cell atlas of treatment response in pediatric AML

Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse. At diagnosis, cellular composition differed between genetic subgroups. Upon relapse, cellular hierarchies transitioned toward a more primitive state regardless of subtype. Primitive cells in the relapsed tumor were distinct compared to cells at diagnosis, with under-representation of myeloid transcriptional programs and over-representation of other lineage programs. In some patients, this was accompanied by the appearance of a B-lymphoid-like hierarchy. Our data thus reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potentially targetable processes.

Sequential sequencing by synthesis and the next-generation sequencing revolution

The impact of next-generation sequencing (NGS) cannot be overestimated. The technology has transformed the field of life science, contributing to a dramatic expansion in our understanding of human health and disease and our understanding of biology and ecology. The vast majority of the major NGS systems today are based on the concept of 'sequencing by synthesis' (SBS) with sequential detection of nucleotide incorporation using an engineered DNA polymerase. Based on this strategy, various alternative platforms have been developed, including the use of either native nucleotides or reversible terminators and different strategies for the attachment of DNA to a solid support. In this review, some of the key concepts leading to this remarkable development are discussed.

Single-cell analysis of chromatin accessibility in the adult mouse brain

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

Warming during embryogenesis induces a lasting transcriptomic signature in fishes

Exposure to elevated temperatures during embryogenesis can influence the plasticity of tissues in later life. Despite these long-term changes in plasticity, few differentially expressed genes are ever identified, suggesting that the developmental programming of later life plasticity may occur through the modulation of other aspects of transcriptomic architecture, such as gene network organisation. Here, we use network modelling approaches to demonstrate that warm temperatures during embryonic development (developmental warming) have consistent effects in later life on the organisation of transcriptomic networks across four diverse species of fishes: Scyliorhinus canicula, Danio rerio, Dicentrarchus labrax, and Gasterosteus aculeatus. The transcriptomes of developmentally warmed fishes are characterised by an increased entropy of their pairwise gene interaction networks, implying a less structured, more 'random' set of gene interactions. We also show that, in zebrafish subject to developmental warming, the entropy of an individual gene within a network is associated with that gene's probability of expression change during temperature acclimation in later life. However, this association is absent in animals reared under 'control' conditions. Thus, the thermal environment experienced during embryogenesis can alter transcriptomic organisation in later life, and these changes may influence an individual's responsiveness to future temperature challenges.

CEMIG: prediction of the cis-regulatory motif using the de Bruijn graph from ATAC-seq

Sequence motif discovery algorithms enhance the identification of novel deoxyribonucleic acid sequences with pivotal biological significance, especially transcription factor (TF)-binding motifs. The advent of assay for transposase-accessible chromatin using sequencing (ATAC-seq) has broadened the toolkit for motif characterization. Nonetheless, prevailing computational approaches have focused on delineating TF-binding footprints, with motif discovery receiving less attention. Herein, we present Cis rEgulatory Motif Influence using de Bruijn Graph (CEMIG), an algorithm leveraging de Bruijn and Hamming distance graph paradigms to predict and map motif sites. Assessment on 129 ATAC-seq datasets from the Cistrome Data Browser demonstrates CEMIG's exceptional performance, surpassing three established methodologies on four evaluative metrics. CEMIG accurately identifies both cell-type-specific and common TF motifs within GM12878 and K562 cell lines, demonstrating its comparative genomic capabilities in the identification of evolutionary conservation and cell-type specificity. In-depth transcriptional and functional genomic studies have validated the functional relevance of CEMIG-identified motifs across various cell types. CEMIG is available at https://github.com/OSU-BMBL/CEMIG, developed in C++ to ensure cross-platform compatibility with Linux, macOS and Windows operating systems.

Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information

BACKGROUND

Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility.

RESULTS

Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson's R and Spearman's [Formula: see text] coefficients as well as Kendall's [Formula: see text] and Top-Down correlation. We also test the behavior of association measures, including the coefficient of determination R[Formula: see text], Kendall's W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearman's [Formula: see text], Kendall's [Formula: see text], and Kendall's W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R[Formula: see text] coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships.

CONCLUSIONS

Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

scATAC-seq preprocessing and imputation evaluation system for visualization, clustering and digital footprinting

Single-cell ATAC-seq (scATAC-seq) is a recently developed approach that provides means to investigate open chromatin at single cell level, to assess epigenetic regulation and transcription factors binding landscapes. The sparsity of the scATAC-seq data calls for imputation. Similarly, preprocessing (filtering) may be required to reduce computational load due to the large number of open regions. However, optimal strategies for both imputation and preprocessing have not been yet evaluated together. We present SAPIEnS (scATAC-seq Preprocessing and Imputation Evaluation System), a benchmark for scATAC-seq imputation frameworks, a combination of state-of-the-art imputation methods with commonly used preprocessing techniques. We assess different types of scATAC-seq analysis, i.e. clustering, visualization and digital genomic footprinting, and attain optimal preprocessing-imputation strategies. We discuss the benefits of the imputation framework depending on the task and the number of the dataset features (peaks). We conclude that the preprocessing with the Boruta method is beneficial for the majority of tasks, while imputation is helpful mostly for small datasets. We also implement a SAPIEnS database with pre-computed transcription factor footprints based on imputed data with their activity scores in a specific cell type. SAPIEnS is published at: https://github.com/lab-medvedeva/SAPIEnS. SAPIEnS database is available at: https://sapiensdb.com.

Vaginal microbes alter epithelial transcriptomic and epigenomic modifications providing insight into the molecular mechanisms for susceptibility to adverse reproductive outcomes

The cervicovaginal microbiome is highly associated with women's health with microbial communities dominated by Lactobacillus spp. being considered optimal. Conversely, a lack of lactobacilli and a high abundance of strict and facultative anaerobes including Gardnerella vaginalis , have been associated with adverse reproductive outcomes. However, the molecular pathways modulated by microbe interactions with the cervicovaginal epithelia remain unclear. Using RNA-sequencing, we characterize the in vitro cervicovaginal epithelial transcriptional response to different vaginal bacteria and their culture supernatants. We showed that G. vaginalis upregulated genes were associated with an activated innate immune response including anti-microbial peptides and inflammasome pathways, represented by NLRP3-mediated increases in caspase-1, IL-1β and cell death. Cervicovaginal epithelial cells exposed to L. crispatus showed limited transcriptomic changes, while exposure to L. crispatus culture supernatants resulted in a shift in the epigenomic landscape of cervical epithelial cells. ATAC-sequencing confirmed epigenetic changes with reduced chromatin accessibility. This study reveals new insight into host-microbe interactions in the lower reproductive tract and suggest potential therapeutic strategies leveraging the vaginal microbiome to improve reproductive health.

Seq2science: an end-to-end workflow for functional genomics analysis

Sequencing databases contain enormous amounts of functional genomics data, making them an extensive resource for genome-scale analysis. Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.

Discordance between chromatin accessibility and transcriptional activity during the human primed-to-naïve pluripotency transition process

Naïve pluripotent state can be obtained by several strategies from various types of cells, in which the cell fate roadmap as well as key biological events involved in the journey have been described in detail. Here, we carefully explored the chromatin accessibility dynamics during the primed-to-naïve transition by adopting a dual fluorescent reporter system and the assay for transposase-accessible chromatin (ATAC)-seq. Our results revealed critical chromatin remodeling events and highlight the discordance between chromatin accessibility and transcriptional activity. We further demonstrate that the differential epigenetic modifications and transcription factor (TF) activities may play a critical role in regulating gene expression, and account for the observed variations in gene expression despite similar chromatin landscapes.

cisDynet: An integrated platform for modeling gene-regulatory dynamics and networks

Chromatin accessibility sequencing has been widely used for uncovering genetic regulatory mechanisms and inferring gene regulatory networks. However, effectively integrating large-scale chromatin accessibility datasets has posed a significant challenge. This is due to the lack of a comprehensive end-to-end solution, as many existing tools primarily emphasize data preprocessing and overlook downstream analyses. To bridge this gap, we have introduced cisDynet, a holistic solution that combines streamlined data preprocessing using Snakemake and R functions with advanced downstream analysis capabilities. cisDynet excels in conventional data analyses, encompassing peak statistics, peak annotation, differential analysis, motif enrichment analysis, and more. Additionally, it allows to perform sophisticated data exploration, such as tissue-specific peak identification, time course data modeling, integration of RNA-seq data to establish peak-to-gene associations, constructing regulatory networks, and conducting enrichment analysis of genome-wide association study (GWAS) variants. As a proof of concept, we applied cisDynet to reanalyze comprehensive ATAC-seq datasets across various tissues from the Encyclopedia of DNA Elements (ENCODE) project. The analysis successfully delineated tissue-specific open chromatin regions (OCRs), established connections between OCRs and target genes, and effectively linked these discoveries with 1861 GWAS variants. Furthermore, cisDynet was instrumental in dissecting the time course open chromatin data of mouse embryonic development, revealing the dynamic behavior of OCRs over developmental stages and identifying key transcription factors governing differentiation trajectories. In summary, cisDynet offers researchers a user-friendly solution that minimizes the need for extensive coding, ensures the reproducibility of results, and greatly simplifies the exploration of epigenomic data.

Gene regulatory network inference in the era of single-cell multi-omics

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

Chromatin accessibility profiling of targeted cell populations with laser capture microdissection coupled to ATAC-seq

Spatially resolved omics technologies reveal context-dependent cellular regulatory networks in tissues of interest. Beyond transcriptome analysis, information on epigenetic traits and chromatin accessibility can provide further insights on gene regulation in health and disease. Nevertheless, compared to the enormous advancements in spatial transcriptomics technologies, the field of spatial epigenomics is much younger and still underexplored. In this study, we report laser capture microdissection coupled to ATAC-seq (LCM-ATAC-seq) applied to fresh frozen samples for the spatial characterization of chromatin accessibility. We first demonstrate the efficient use of LCM coupled to in situ tagmentation and evaluate its performance as a function of cell number, microdissected areas, and tissue type. Further, we demonstrate its use for the targeted chromatin accessibility analysis of discrete contiguous or scattered cell populations in tissues via single-nuclei capture based on immunostaining for specific cellular markers.