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

Chromatin accessibility and transcriptional landscape in PK-15 cells during early exposure to Aflatoxin B1

Aflatoxin B1 (AFB1) not only causes significant losses in livestock production but also poses a serious threat to human health. It is the most carcinogenic among known chemicals. Pigs are more susceptible to AFB1 and experience a higher incidence. However, the molecular mechanism of the toxic effect of AFB1 remains unclear. In this study, we used assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq to uncover chromatin accessibility and gene expression dynamics in PK-15 cells during early exposure to AFB1. We observed that the toxic effects of AFB1 involve signaling pathways such as p53, PI3K-AKT, Hippo, MAPK, TLRs, apoptosis, autophagy, and cancer pathways. Basic leucine zipper (bZIP) transcription factors (TFs), including AP-1, Fos, JunB, and Fra2, play a crucial role in regulating the biological processes involved in AFB1 challenge. Several new TFs, such as BORIS, HNF1b, Atf1, and KNRNPH2, represent potential targets for the toxic mechanism of AFB1. In addition, it is crucial to focus on the concentration of intracellular zinc ions. These findings will contribute to a better understanding of the mechanisms underlying AFB1-induced nephrotoxicity and offer new molecular targets.

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.

Differential chromatin accessibility and Gene Expression Associated with Backfat Deposition in pigs

BACKGROUND

Backfat serves as a vital fat reservoir in pigs, and its excessive accumulation will adversely impact pig growth performance, farming efficiency, and pork quality. The aim of this research is to integrate assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and RNA sequencing (RNA-seq) to explore the molecular mechanisms underlying porcine backfat deposition.

RESULTS

ATAC-seq analysis identified 568 genes originating from 698 regions exhibiting differential accessibility, which were significantly enriched in pathways pertinent to adipocyte differentiation and lipid metabolism. Besides, a total of 283 transcription factors (TFs) were identified by motif analysis. RNA-seq analysis revealed 978 differentially expressed genes (DEGs), which were enriched in pathways related to energy metabolism, cell cycle and signal transduction. The integration of ATAC-seq and RNA-seq data indicates that DEG expression levels are associated with chromatin accessibility. This comprehensive study highlights the involvement of critical pathways, including the Wnt signaling pathway, Jak-STAT signaling pathway, and fatty acid degradation, in the regulation of backfat deposition. Through rigorous analysis, we identified several candidate genes (LEP, CTBP2, EHHADH, OSMR, TCF7L2, BCL2, FGF1, UCP2, CCND1, TIMP1, and VDR) as potentially significant contributors to backfat deposition. Additionally, we constructed TF-TF and TF-target gene regulatory networks and identified a series of potential TFs related to backfat deposition (FOS, STAT3, SMAD3, and ESR1).

CONCLUSIONS

This study represents the first application of ATAC-seq and RNA-seq, affording a novel perspective into the mechanisms underlying backfat deposition and providing invaluable resources for the enhancement of pig breeding programs.

Characterization of non-coding variants associated with transcription factor binding through ATAC-seq-defined footprint QTLs in liver

Non-coding variants discovered by genome-wide association studies (GWAS) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint". Here, we sought to identify variants associated with TF-binding, or "footprint quantitative trait loci" (fpQTLs) in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 693 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 80% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding site disruption in disease and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.

Artificial intelligence and machine learning applications for cultured meat

Cultured meat has the potential to provide a complementary meat industry with reduced environmental, ethical, and health impacts. However, major technological challenges remain which require time-and resource-intensive research and development efforts. Machine learning has the potential to accelerate cultured meat technology by streamlining experiments, predicting optimal results, and reducing experimentation time and resources. However, the use of machine learning in cultured meat is in its infancy. This review covers the work available to date on the use of machine learning in cultured meat and explores future possibilities. We address four major areas of cultured meat research and development: establishing cell lines, cell culture media design, microscopy and image analysis, and bioprocessing and food processing optimization. In addition, we have included a survey of datasets relevant to CM research. This review aims to provide the foundation necessary for both cultured meat and machine learning scientists to identify research opportunities at the intersection between cultured meat and machine learning.

Methods for constructing and evaluating consensus genomic interval sets

The amount of genomic region data continues to increase. Integrating across diverse genomic region sets requires consensus regions, which enable comparing regions across experiments, but also by necessity lose precision in region definitions. We require methods to assess this loss of precision and build optimal consensus region sets. Here, we introduce the concept of flexible intervals and propose three novel methods for building consensus region sets, or universes: a coverage cutoff method, a likelihood method, and a Hidden Markov Model. We then propose three novel measures for evaluating how well a proposed universe fits a collection of region sets: a base-level overlap score, a region boundary distance score, and a likelihood score. We apply our methods and evaluation approaches to several collections of region sets and show how these methods can be used to evaluate fit of universes and build optimal universes. We describe scenarios where the common approach of merging regions to create consensus leads to undesirable outcomes and provide principled alternatives that provide interoperability of interval data while minimizing loss of resolution.

A comparative analysis of planarian genomes reveals regulatory conservation in the face of rapid structural divergence

The planarian Schmidtea mediterranea is being studied as a model species for regeneration, but the assembly of planarian genomes remains challenging. Here, we report a high-quality haplotype-phased, chromosome-scale genome assembly of the sexual S2 strain of S. mediterranea and high-quality chromosome-scale assemblies of its three close relatives, S. polychroa, S. nova, and S. lugubris. Using hybrid gene annotations and optimized ATAC-seq and ChIP-seq protocols for regulatory element annotation, we provide valuable genome resources for the planarian research community and a first comparative perspective on planarian genome evolution. Our analyses reveal substantial divergence in protein-coding sequences and regulatory regions but considerable conservation within promoter and enhancer annotations. We also find frequent retrotransposon-associated chromosomal inversions and interchromosomal translocations within the genus Schmidtea and, remarkably, independent and nearly complete losses of ancestral metazoan synteny in Schmidtea and two other flatworm groups. Overall, our results suggest that platyhelminth genomes can evolve without syntenic constraints.

Epigenomic, transcriptomic and proteomic characterizations of reference samples

A variety of newly developed next-generation sequencing technologies are making their way rapidly into the research and clinical applications, for which accuracy and cross-lab reproducibility are critical, and reference standards are much needed. Our previous multicenter studies under the SEQC-2 umbrella using a breast cancer cell line with paired B-cell line have produced a large amount of different genomic data including whole genome sequencing (Illumina, PacBio, Nanopore), HiC, and scRNA-seq with detailed analyses on somatic mutations, single-nucleotide variations (SNVs), and structural variations (SVs). However, there is still a lack of well-characterized reference materials which include epigenomic and proteomic data. Here we further performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic analyses and provided a comprehensive catalog of the epigenomic landscape, which overlapped with the transcriptomes and proteomes for the two cell lines. We identified >7,700 peptide isoforms, where the majority (95%) of the genes had a single peptide isoform. Protein expression of the transcripts overlapping CGIs were much higher than the protein expression of the non-CGI transcripts in both cell lines. We further demonstrated the evidence that certain SNVs were incorporated into mutated peptides. We observed that open chromatin regions had low methylation which were largely regulated by CG density, where CG-rich regions had more accessible chromatin, low methylation, and higher gene and protein expression. The CG-poor regions had higher repressive epigenetic regulations (higher DNA methylation) and less open chromatin, resulting in a cell line specific methylation and gene expression patterns. Our studies provide well-defined reference materials consisting of two cell lines with genomic, epigenomic, transcriptomic, scRNA-seq and proteomic characterizations which can serve as standards for validating and benchmarking not only on various omics assays, but also on bioinformatics methods. It will be a valuable resource for both research and clinical communities.

Crossing epigenetic frontiers: the intersection of novel histone modifications and diseases

Histone post-translational modifications (HPTMs), as one of the core mechanisms of epigenetic regulation, are garnering increasing attention due to their close association with the onset and progression of diseases and their potential as targeted therapeutic agents. Advances in high-throughput molecular tools and the abundance of bioinformatics data have led to the discovery of novel HPTMs which similarly affect gene expression, metabolism, and chromatin structure. Furthermore, a growing body of research has demonstrated that novel histone modifications also play crucial roles in the development and progression of various diseases, including various cancers, cardiovascular diseases, infectious diseases, psychiatric disorders, and reproductive system diseases. This review defines nine novel histone modifications: lactylation, citrullination, crotonylation, succinylation, SUMOylation, propionylation, butyrylation, 2-hydroxyisobutyrylation, and 2-hydroxybutyrylation. It comprehensively introduces the modification processes of these nine novel HPTMs, their roles in transcription, replication, DNA repair and recombination, metabolism, and chromatin structure, as well as their involvement in promoting the occurrence and development of various diseases and their clinical applications as therapeutic targets and potential biomarkers. Moreover, this review provides a detailed overview of novel HPTM inhibitors targeting various targets and their emerging strategies in the treatment of multiple diseases while offering insights into their future development prospects and challenges. Additionally, we briefly introduce novel epigenetic research techniques and their applications in the field of novel HPTM research.

Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers

To identify cancer-associated gene regulatory changes, we generated single-cell chromatin accessibility landscapes across eight tumor types as part of The Cancer Genome Atlas. Tumor chromatin accessibility is strongly influenced by copy number alterations that can be used to identify subclones, yet underlying cis-regulatory landscapes retain cancer type-specific features. Using organ-matched healthy tissues, we identified the "nearest healthy" cell types in diverse cancers, demonstrating that the chromatin signature of basal-like-subtype breast cancer is most similar to secretory-type luminal epithelial cells. Neural network models trained to learn regulatory programs in cancer revealed enrichment of model-prioritized somatic noncoding mutations near cancer-associated genes, suggesting that dispersed, nonrecurrent, noncoding mutations in cancer are functional. Overall, these data and interpretable gene regulatory models for cancer and healthy tissue provide a framework for understanding cancer-specific gene regulation.

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.

MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.

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.

A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data

Eukaryotic gene regulation is a combinatorial, dynamic, and quantitative process that plays a vital role in development and disease and can be modeled at a systems level in gene regulatory networks (GRNs). The wealth of multi-omics data measured on the same samples and even on the same cells has lifted the field of GRN inference to the next stage. Combinations of (single-cell) transcriptomics and chromatin accessibility allow the prediction of fine-grained regulatory programs that go beyond mere correlation of transcription factor and target gene expression, with enhancer GRNs (eGRNs) modeling molecular interactions between transcription factors, regulatory elements, and target genes. In this review, we highlight the key components for successful (e)GRN inference from (sc)RNA-seq and (sc)ATAC-seq data exemplified by state-of-the-art methods as well as open challenges and future developments. Moreover, we address preprocessing strategies, metacell generation and computational omics pairing, transcription factor binding site detection, and linear and three-dimensional approaches to identify chromatin interactions as well as dynamic and causal eGRN inference. We believe that the integration of transcriptomics together with epigenomics data at a single-cell level is the new standard for mechanistic network inference, and that it can be further advanced with integrating additional omics layers and spatiotemporal data, as well as with shifting the focus towards more quantitative and causal modeling strategies.

Evidence of innate training in bovine γδ T cells following subcutaneous BCG administration

The Bacillus Calmette Guerin (BCG) vaccine has been shown to induce non-specific protection against diseases other than tuberculosis in vaccinated individuals, attributed to the induction of trained immunity. We have previously demonstrated that BCG administration induces innate immune training in mixed peripheral blood mononuclear cells and monocytes in calves. Gamma Delta (γδ) T cells are non-conventional T cells that exhibit innate and adaptive immune system features. They are in higher proportion in the peripheral blood of cattle than humans or rodents and play an essential role in bovine immune response to pathogens. In the current study, we determined if BCG administration induced innate immune training in bovine γδ T cells. A group of 16 pre-weaned Holstein calves (2-4 d age) were enrolled in the study and randomly assigned to vaccine and control groups (n=8/group). The vaccine group received two doses of 106 colony forming units (CFU) BCG Danish strain subcutaneously, separated by 2 weeks. The control group remained unvaccinated. Gamma delta T cells were purified from peripheral blood using magnetic cell sorting three weeks after receiving the 1st BCG dose. We observed functional changes in the γδ T cells from BCG-treated calves shown by increased IL-6 and TNF-α cytokine production in response to in vitro stimulation with Escherichia coli LPS and PAM3CSK4. ATAC-Seq analysis of 78,278 regions of open chromatin (peaks) revealed that γδ T cells from BCG-treated calves had an altered epigenetic status compared to cells from the control calves. Differentially accessible peaks (DAP) found near the promoters of innate immunity-related genes like Siglec14, Irf4, Ifna2, Lrrfip1, and Tnfrsf10d were 1 to 4-fold more accessible in cells from BCG-treated calves. MOTIF enrichment analysis of the sequences within DAPs, which explores transcription factor binding motifs (TFBM) upstream of regulatory elements, revealed TFBM for Eomes and IRF-5 were among the most enriched transcription factors. GO enrichment analysis of genes proximal to the DAPs showed enrichment of pathways such as regulation of IL-2 production, T-cell receptor signaling pathway, and other immune regulatory pathways. In conclusion, our study shows that subcutaneous BCG administration in pre-weaned calves can induce innate immune memory in the form of trained immunity in γδ T cells. This memory is associated with increased chromatin accessibility of innate immune response-related genes, thereby inducing a functional trained immune response evidenced by increased IL-6 and TNF-α cytokine production.

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.

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 Ca2+- 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.

Benchmarking Algorithms for Gene Set Scoring of Single-cell ATAC-seq Data

Gene set scoring (GSS) has been routinely conducted for gene expression analysis of bulk or single-cell RNA sequencing (RNA-seq) data, which helps to decipher single-cell heterogeneity and cell type-specific variability by incorporating prior knowledge from functional gene sets. Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a powerful technique for interrogating single-cell chromatin-based gene regulation, and genes or gene sets with dynamic regulatory potentials can be regarded as cell type-specific markers as if in single-cell RNA-seq (scRNA-seq). However, there are few GSS tools specifically designed for scATAC-seq, and the applicability and performance of RNA-seq GSS tools on scATAC-seq data remain to be investigated. Here, we systematically benchmarked ten GSS tools, including four bulk RNA-seq tools, five scRNA-seq tools, and one scATAC-seq method. First, using matched scATAC-seq and scRNA-seq datasets, we found that the performance of GSS tools on scATAC-seq data was comparable to that on scRNA-seq, suggesting their applicability to scATAC-seq. Then, the performance of different GSS tools was extensively evaluated using up to ten scATAC-seq datasets. Moreover, we evaluated the impact of gene activity conversion, dropout imputation, and gene set collections on the results of GSS. Results show that dropout imputation can significantly promote the performance of almost all GSS tools, while the impact of gene activity conversion methods or gene set collections on GSS performance is more dependent on GSS tools or datasets. Finally, we provided practical guidelines for choosing appropriate preprocessing methods and GSS tools in different application scenarios.

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.

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.

Estrogen Receptor Chromatin Profiling by CUT&RUN

Gonadal steroid hormones, namely, testosterone, progesterone, and estrogens, influence the physiological state of an organism through the regulation of gene transcription. Steroid hormones activate nuclear hormone receptor (HR), transcription factors (TFs), which bind DNA in a tissue- and cell type-specific manner to influence cellular function. Identifying the genomic binding sites of HRs is essential to understanding mechanisms of hormone signaling across tissues and disease contexts. Traditionally, chromatin immunoprecipitation followed by sequencing (ChIP-seq) has been used to map the genomic binding of HRs in cancer cell lines and large tissues. However, ChIP-seq lacks the sensitivity to detect TF binding in small numbers of cells, such as genetically defined neuronal subtypes in the brain. Cleavage Under Targets & Release Under Nuclease (CUT&RUN) resolves most of the technical limitations of ChIP-seq, enabling the detection of protein-DNA interactions with as few as 100-1000 cells. In this chapter, we provide a stepwise CUT&RUN protocol for detecting and analyzing the genome-wide binding of estrogen receptor α (ERα) in mouse brain tissue. The steps described here can be used to identify the genomic binding sites of most TFs in the brain.

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.