Determination and inference of eukaryotic transcription factor sequence specificity

Zygotic activation of transposable elements during zebrafish early embryogenesis

Although previous studies have shown that transposable elements (TEs) are conservatively activated to play key roles during early embryonic development, the details of zygotic TE activation (ZTA) remain poorly understood. Here, we employ long-read sequencing to precisely identify that only a small subset of TE loci are activated among numerous copies, allowing us to map their hierarchical transcriptional cascades at the single-locus and single-transcript level. Despite the heterogeneity of ZTA across family, subfamily, locus, and transcript levels, our findings reveal that ZTA follows a markedly different pattern from conventional zygotic gene activation (ZGA): ZTA occurs significantly later than ZGA and shows a pronounced bias for nuclear localization of TE transcripts. This study advances our understanding of TE activation by providing a high-resolution view of TE copies and creating a comprehensive catalog of thousands of previously unannotated transcripts and genes that are activated during early zebrafish embryogenesis. Among these genes, we highlight two that are essential for zebrafish development.

Asian diversity in human immune cells

The relationships of human diversity with biomedical phenotypes are pervasive yet remain understudied, particularly in a single-cell genomics context. Here, we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 donors, spanning 7 population groups across 5 Asian countries, and 6 controls. Though population groups are frequently compared at the continental level, we found that sub-continental diversity, age, and sex pervasively impacted cellular and molecular properties of immune cells. These included differential abundance of cell neighborhoods as well as cell populations and genes relevant to disease risk, pathogenesis, and diagnostics. We discovered functional genetic variants influencing cell-type-specific gene expression, which were under-represented in non-Asian populations, and helped contextualize disease-associated variants. AIDA enables analyses of multi-ancestry disease datasets and facilitates the development of precision medicine efforts in Asia and beyond.

Low overlap of transcription factor DNA binding and regulatory targets

DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes1,2. How multiple TFs cooperate to regulate individual genes is still unclear. In yeast, most TFs are thought to regulate transcription via binding to upstream activating sequences, which are situated within a few hundred base pairs upstream of the regulated gene3. Although this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way. Here we integrated information on the binding and expression targets for the near-complete set of yeast TFs and show that, contrary to expectations, there are few TFs with dedicated activator or repressor roles, and that most TFs have a dual function. Although nearly all protein-coding genes are regulated by one or more TFs, our analysis revealed limited overlap between TF binding and gene regulation. Rapid depletion of many TFs also revealed many regulatory targets that were distant from detectable TF binding sites, suggesting unexpected regulatory mechanisms. Our study provides a comprehensive survey of TF functions and offers insights into interactions between the set of TFs expressed in a single cell type and how they contribute to the complex programme of gene regulation.

Deubiquitinase-Targeting Chimeras (DUBTACs) as a Potential Paradigm-Shifting Drug Discovery Approach

Developing proteolysis-targeting chimeras (PROTACs) is well recognized through target protein degradation (TPD) toward promising therapeutics. While a variety of diseases are driven by aberrant ubiquitination and degradation of critical proteins with protective functions, target protein stabilization (TPS) rather than TPD is emerging as a unique therapeutic modality. Deubiquitinase-targeting chimeras (DUBTACs), a class of heterobifunctional protein stabilizers consisting of deubiquitinase (DUB) and protein-of-interest (POI) targeting ligands conjugated with a linker, can rescue such proteins from aberrant elimination. DUBTACs stabilize the levels of POIs in a DUB-dependent manner, removing ubiquitin from polyubiquitylated and degraded proteins. DUBTACs can induce a new interaction between POI and DUB by forming a POI-DUBTAC-DUB ternary complex. Herein, therapeutic benefits of TPS approaches for human diseases are introduced, and recent advances in developing DUBTACs are summarized. Relevant challenges, opportunities, and future perspectives are also discussed.

Interpreting regulatory mechanisms of Hippo signaling through a deep learning sequence model

Signaling pathway components are well studied, but how they mediate cell-type-specific transcription responses is an unresolved problem. Using the Hippo pathway in mouse trophoblast stem cells as a model, we show that the DNA binding of signaling effectors is driven by cell-type-specific sequence rules that can be learned genome wide by deep learning models. Through model interpretation and experimental validation, we show that motifs for the cell-type-specific transcription factor TFAP2C enhance TEAD4/YAP1 binding in a nucleosome-range and distance-dependent manner, driving synergistic enhancer activation. We also discovered that Tead double motifs are widespread, highly active canonical response elements. Molecular dynamics simulations suggest that TEAD4 binds them cooperatively through surprisingly labile protein-protein interactions that depend on the DNA template. These results show that the response to signaling pathways is encoded in the cis-regulatory sequences and that interpreting the rules reveals insights into the mechanisms by which signaling effectors influence cell-type-specific enhancer activity.

A comprehensive review of computational methods for Protein-DNA binding site prediction

Accurately identifying protein-DNA binding sites is essential for understanding the molecular mechanisms underlying biological processes, which in turn facilitates advancements in drug discovery and design. While biochemical experiments provide the most accurate way to locate DNA-binding sites, they are generally time-consuming, resource-intensive, and expensive. There is a pressing need to develop computational methods that are both efficient and accurate for DNA-binding site prediction. This study thoroughly reviews and categorizes major computational approaches for predicting DNA-binding sites, including template detection, statistical machine learning, and deep learning-based methods. The 14 state-of-the-art DNA-binding site prediction models have been benchmarked on 136 non-redundant proteins, where the deep learning-based, especially pre-trained large language model-based, methods achieve superior performance over the other two categories. Applications of these DNA-binding site prediction methods are also involved.

A statistical framework for inferring genetic requirements from embryo-scale single-cell sequencing experiments

Improvements in single-cell sequencing protocols have democratized their use for phenotyping at organism-scale and molecular resolution, but interpreting such experiments poses computational challenges. Identifying the genes and cell types directly impacted by genetic, chemical, or environmental perturbations requires explicit modeling of lineage relationships amongst many cell types, over time, from datasets with millions of cells collected from thousands of specimens. We describe two software tools, "Hooke" and "Platt", which exploit the rich statistical patterns within single-cell datasets to characterize the direct molecular and cellular consequences of experimental perturbations. We apply Hooke and Platt to a single-cell atlas of thousands of perturbed zebrafish embryos to synthesize a coherent map of lineage dependencies and leverage it to reveal previously unappreciated roles for fate-determining transcription factors. We show that the co-variation between cell types in single-cell datasets is a powerful source of information for inferring how cells depend on genes and one another in the program of vertebrate development.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Predicting the DNA binding specificity of transcription factor mutants using family-level biophysically interpretable machine learning

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with machine learning have made it possible to accurately define such molecular recognition in a biophysically interpretable way for hundreds of TFs across many structural families, providing new avenues for predicting how the sequence preference of a TF is impacted by disease-associated mutations in its DNA binding domain. We developed a method based on a reference-free tetrahedral representation of variation in base preference within a given structural family that can be used to accurately predict the effect of mutations in the protein sequence of the TF. Using the basic helix-loop-helix (bHLH) and homeodomain families as test cases, our results demonstrate the feasibility of accurately predicting the shifts (ΔΔΔG/RT) in binding free energy associated with TF mutants by leveraging high-quality DNA binding models for sets of homologous wild-type TFs.

Stratified Medicine Pediatrics: Cell-Free DNA and Serial Tumor Sequencing Identifies Subtype-Specific Cancer Evolution and Epigenetic States

SIGNIFICANCE

In tumors of childhood, we identify mutations in epigenetic genes as drivers of relapse, with matched cfDNA sequencing showing significant intratumor genetic heterogeneity and cell-state specific patterns of chromatin accessibility. This highlights the power of cfDNA analysis to identify both genetic and epigenetic drivers of aggressive disease in pediatric cancers.

Recent advances in designing synthetic plant regulatory modules

Introducing novel functions in plants through synthetic multigene circuits requires strict transcriptional regulation. Currently, the use of natural regulatory modules in synthetic circuits is hindered by our limited knowledge of complex plant regulatory mechanisms, the paucity of characterized promoters, and the possibility of crosstalk with endogenous circuits. Synthetic regulatory modules can overcome these limitations. This article introduces an integrative de novo approach for designing plant synthetic promoters by utilizing the available online tools and databases. The recent achievements in designing and validating synthetic plant promoters, enhancers, transcription factors, and the challenges of establishing synthetic circuits in plants are also discussed.

Specificity landscapes of 40 R2R3-MYBs reveal how paralogs target different cis-elements by homodimeric binding

Paralogous transcription factors (TFs) frequently recognize highly similar DNA motifs. Homodimerization can help distinguish them according to their different dimeric configurations. Here, by studying R2R3-MYB TFs, we show that homodimerization can also directly change the recognized DNA motifs to distinguish between similar TFs. By high-throughput SELEX, we profiled the specificity landscape for 40 R2R3-MYBs of subfamily VIII and curated 833 motif models. The dimeric models show that homodimeric binding has evoked specificity changes for AtMYBs. Focusing on AtMYB2 as an example, we show that homodimerization has modified its specificity and allowed it to recognize additional cis-regulatory sequences that are different from the closely related CCWAA-box AtMYBs and are unique among all AtMYBs. Genomic sites described by the modified dimeric specificities of AtMYB2 are conserved in evolution and involved in AtMYB2-specific transcriptional activation. Collectively, this study provides rich data on sequence preferences of VIII R2R3-MYBs and suggests an alternative mechanism that guides closely related TFs to respective cis-regulatory sites.

PmiProPred: A novel method towards plant miRNA promoter prediction based on CNN-Transformer network and convolutional block attention mechanism

It is crucial to understand the transcription mechanisms of miRNAs, especially considering the presence of peptides encoded by miRNAs. Since promoters function as the switch for gene transcription, precisely identifying these regions is essential for fully annotating miRNA transcripts. Nonetheless, existing computational methods still have room for improvement in the characterization of promoter regions. Here, we present PmiProPred, an advanced tool designed for predicting plant miRNA promoters from a wide spectrum of genomes. It consists of two core components: multi-stream deep feature extraction (MsDFE) and multi-stream deep feature refinement (MsDFR). The MsDFE utilizes Transformer and CNN to gather multi-view features, while the MsDFR focuses on aligning and refining them using channel and spatial attention mechanisms. Ultimately, a multi-layer perceptron is employed to accomplish the miRNA promoter identification task. Across three independent testing datasets, PmiProPred achieves accuracies of 94.630%, 96.659%, and 92.480%, respectively, substantially surpassing the latest methods. Additionally, PmiProPred is employed to identify potential core promoters in the upstream 2-kb regions of intergenic miRNAs in five plant species. We further conduct cis-regulatory elements mining on the predicted promoters and perform an in-depth analysis of the identified motifs. Altogether, PmiProPred is a robust and effective tool for discovering plant miRNA promoters.

Evolutionary Process Underlying Receptor Gene Expansion and Cellular Divergence of Olfactory Sensory Neurons in Honeybees

Olfaction is crucial for animals' survival and adaptation. Unlike the strict singular expression of odorant receptor (OR) genes in vertebrate olfactory sensory neurons (OSNs), insects exhibit complex OR gene expression patterns. In honeybees (Apis mellifera), a significant expansion of OR genes implies a selection preference for the olfactory demands of social insects. However, the mechanisms underlying receptor expression specificity and their contribution to OSN divergence remain unclear. In this study, we used single-nucleus multiomics profiling to investigate the transcriptional regulation of OR genes and the cellular identity of OSNs in A. mellifera. We identified three distinct OR expression patterns, singular OR expression, co-expression of multiple OR genes with a single active promoter, and co-expression of multiple OR genes with multiple active promoters. Notably, ∼50% of OSNs co-expressed multiple OR genes, driven by polycistronic transcription of tandemly duplicated OR genes via a single active promoter. In these OSNs, their identity was determined by the first transcribed receptor. The divergent activation of the promoter for duplicated OR genes ensures the coordinated increased divergence of OSN population. By integrating multiomics data with genomic architecture, we illustrate how fundamental genetic mechanisms drive OR gene expansion and influence flanking regulatory elements, ultimately contributing to the cellular divergence of OSNs. Our findings highlight the interplay between gene duplication and regulatory evolution in shaping OSN diversity, providing new insights into the evolution and adaptation of olfaction in social insects. This study also sheds light on how genetic innovations contribute to the evolution of complex traits.

Comprehensive multimodal and multiomic profiling reveals epigenetic and transcriptional reprogramming in lung tumors

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 stage I and II tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncover cancer-driving signaling cascade networks, changes in 3D genome modularity, differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules show no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

Chromatin accessibility landscape of mouse early embryos revealed by single-cell NanoATAC-seq2

In mammals, fertilized eggs undergo genome-wide epigenetic reprogramming to generate the organism. However, our understanding of epigenetic dynamics during preimplantation development at single-cell resolution remains incomplete. Here, we developed scNanoATAC-seq2, a single-cell assay for transposase-accessible chromatin using long-read sequencing for scarce samples. We present a detailed chromatin accessibility landscape of mouse preimplantation development, revealing distinct chromatin signatures in the epiblast, primitive endoderm, and trophectoderm during lineage segregation. Differences between zygotes and two-cell embryos highlight reprogramming in chromatin accessibility during the maternal-to-zygotic transition. Single-cell long-read sequencing enables in-depth analysis of chromatin accessibility in noncanonical imprinting, imprinted X chromosome inactivation, and low-mappability genomic regions, such as repetitive elements and paralogs. Our data provide insights into chromatin dynamics during mammalian preimplantation development and lineage differentiation.

Clonal memory of colitis accumulates and promotes tumor growth

Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.

Identification and characterization of human retinal stem cells capable of retinal regeneration

Human retinal stem cells hold great promise in regenerative medicine, yet their existence and characteristics remain elusive. Here, we performed single-cell multiomics and spatial transcriptomics of human fetal retinas and uncovered a cell subpopulation, human neural retinal stem-like cells (hNRSCs), distinct from retinal pigment epithelium stem-like cells and traditional retinal progenitor cells. We found that these hNRSCs reside in the peripheral retina in the ciliary marginal zone, exhibiting substantial self-renewal and differentiation potential. We conducted single-cell and spatial transcriptomic analyses of human retinal organoids (hROs) and revealed that hROs contain a population of hNRSCs with similar transcriptional profiles and developmental trajectories to hNRSCs in the fetal retina potentially capable of regenerating all retinal cells. Furthermore, we identified crucial transcription factors, such as MECOM, governing hNRSC commitment to neural retinogenesis and regulating repair processes in hROs. hRO-derived hNRSCs transplanted into the rd10 mouse model of retinitis pigmentosa differentiated and were integrated into the retina, alleviated retinal degeneration, and improved visual function. Overall, our work identifies and characterizes a distinct category of retinal stem cells from human retinas, underscoring their regenerative potential and promise for transplantation therapy.

Single-cell multiome and enhancer connectome of human retinal pigment epithelium and choroid nominate pathogenic variants in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss worldwide. Genome-wide association studies (GWAS) of AMD have identified dozens of risk loci that may house disease targets. However, variants at these loci are largely noncoding, making it difficult to assess their function and whether they are causal. Here, we present a single-cell gene expression and chromatin accessibility atlas of human retinal pigment epithelium (RPE) and choroid to systematically analyze both coding and noncoding variants implicated in AMD. We employ HiChIP and Activity-by-Contact modeling to map enhancers in these tissues and predict cell and gene targets of risk variants. We further perform allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to functionally test variant activity in RPE cells, including in the context of complement activation. Our work nominates new pathogenic variants and mechanisms in AMD and offers a rich and accessible resource for studying diseases of the RPE and choroid.

Single-molecule m6A detection empowered by endogenous labeling unveils complexities across RNA isoforms

The landscape of N6-methyadenosine (m6A) on different RNA isoforms is still incompletely understood. Here, in HEK293T cells, we endogenously label the methylated m6A sites on single Oxford Nanopore Technology (ONT) direct RNA sequencing (DRS) reads by APOBEC1-YTH-induced C-to-U mutations 10-100 nt away, obtaining 1,020,237 5-mer single-read m6A signals. We then trained m6Aiso, a deep residual neural network model that accurately identifies and quantifies m6A at single-read resolution. Analyzing m6Aiso-determined m6A on single reads and isoforms uncovers distance-dependent linkages of m6A sites along single molecules. It also uncovers specific methylation of identical m6A sites on intron-retained isoforms, partly due to their differential distances to exon junctions and isoform-specific binding of TARBP2. Moreover, we find that transcription factor SMAD3 promotes m6A deposition on its transcribed RNA isoforms during epithelial-mesenchymal transition, resulting in isoform-specific regulation of m6A on isoforms with alternative promoters. Our study underscores the effectiveness of m6Aiso in elucidating the intricate dynamics and complexities of m6A across RNA isoforms.

Setdb2 Regulates Inflammatory Trigger-Induced Trained Immunity of Macrophages Through Two Different Epigenetic Mechanisms

"Trained immunity" of innate immune cells occurs through a sequential two-step process where an initial pathogenic or sterile inflammatory trigger is followed by an amplified response to a later un-related secondary pathogen challenge. The memory effect is mediated at least in part through epigenetic modifications of the chromatin landscape. Here, we investigated the role of the epigenetic modifier Setdb2 in microbial (β-glucan) or sterile trigger (Western-diet-WD/oxidized-LDL-oxLDL)-induced trained immunity of macrophages. Using genetic mouse models and genomic analysis, we uncovered a critical role of Setdb2 in regulating proinflammatory and metabolic pathway reprogramming. We further show that Setdb2 regulates trained immunity through two different complementary mechanisms: one where it positively regulates glycolytic and inflammatory pathway genes via enhancer-promoter looping, and is independent of its enzymatic activity; while the second mechanism is associated with both increased promoter associated H3K9 methylation and repression of interferon response pathway genes. Interestingly, while both mechanisms occur in response to pathogenic training, only the chromatin-looping mechanism operates in response to the sterile inflammatory stimulus. These results reveal a previously unknown bifurcation in the downstream pathways that distinguishes between pathogenic and sterile inflammatory signaling responses associated with the innate immune memory response and may provide potential therapeutic opportunities to target cytokine vs. interferon pathways to limit complications of chronic inflammation.

CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

Transcriptomic and chromatin accessibility profiling unveils new regulators of heat hormesis in Caenorhabditis elegans

Heat hormesis describes the beneficial adaptations from transient exposure to mild heat stress, which enhances stress resilience and promotes healthy aging. It is thought to be the underlying basis of popular wellness practices like sauna therapy. Despite extensive documentation across species, the molecular basis of the long-term protective effects of heat hormesis remain poorly understood. This study bridges that critical gap through a comprehensive multiomic analysis, providing key insights into the transcriptomic and chromatin accessibility landscapes throughout a heat hormesis regimen adapted in C. elegans. We uncover highly dynamic dose-dependent molecular responses to heat stress and reveal that while most initial stress-induced changes revert to baseline, key differences in response to subsequent heat shock challenge are directly linked to physiological benefits. We identify new regulators of heat hormesis, including MARS-1/MARS1, SNPC-4/SNAPc, ELT-2/GATA4, FOS-1/c-Fos, and DPY-27/SMC4, which likely orchestrate gene expression programs that enhance stress resilience through distinct biological pathways. This study advances our understanding of stress resilience mechanisms, points to multiple new avenues of future investigations, and suggests potential strategies for promoting healthy aging through mid-life stress management.

A Latent Activated Olfactory Stem Cell State Revealed by Single-Cell Transcriptomic and Epigenomic Profiling

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration in response to injury. In this study, we used single-cell sequencing to identify the transcriptional cascades and epigenetic processes involved in determining olfactory epithelial stem cell fate during injury-induced regeneration. By combining gene expression and accessible chromatin profiles of individual lineage-traced olfactory stem cells, we identified transcriptional heterogeneity among activated stem cells at a stage when cell fates are being specified. We further identified a subset of resting cells that appears poised for activation, characterized by accessible chromatin around wound response and lineage-specific genes prior to their later expression in response to injury. Together these results provide evidence for a latent activated stem cell state, in which a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

SNPeBoT: a tool for predicting transcription factor allele specific binding

BACKGROUND

Mutations in non-coding regulatory regions of DNA may lead to disease through the disruption of transcription factor binding. However, our understanding of binding patterns of transcription factors and the effects that changes to their binding sites have on their action remains limited. To address this issue we trained a Deep learning model to predict the effects of Single Nucleotide Polymorphisms (SNP) on transcription factor binding. Allele specific binding (ASB) data from Chromatin Immunoprecipitation sequencing (ChIP-seq) experiments were paired with high sequence-identity DNA binding Domains assessed in Protein Binding Microarray (PBM) experiments. For each transcription factor a paired DNA binding Domain was selected from which we derived E-score profiles for reference and alternate DNA sequences of ASB events. A Convolutional Neural Network (CNN) was trained to predict whether these profiles were indicative of ASB gain/loss or no change in binding. 18211 E-score profiles from 113 transcription factors were split into train, validation and test data. We compared the performance of the trained model with other available platforms for predicting the effect of SNP on transcription factor binding. Our model demonstrated increased accuracy and ASB recall in comparison to the best scoring benchmark tools.

CONCLUSION

In this paper we present our model SNPeBoT (Single Nucleotide Polymorphism effect on Binding of Transcription Factors) in its standalone and web server form. The increased recovery and prediction accuracy of allele specific binding events could prove useful in discovering non-coding mutations relevant to disease.

Distinct gene regulatory dynamics drive skeletogenic cell fate convergence during vertebrate embryogenesis

Cell type repertoires have expanded extensively in metazoan animals, with some clade-specific cells being crucial to evolutionary success. A prime example are the skeletogenic cells of vertebrates. Depending on anatomical location, these cells originate from three different precursor lineages, yet they converge developmentally towards similar cellular phenotypes. Furthermore, their 'skeletogenic competency' arose at distinct evolutionary timepoints, thus questioning to what extent different skeletal body parts rely on truly homologous cell types. Here, we investigate how lineage-specific molecular properties are integrated at the gene regulatory level, to allow for skeletogenic cell fate convergence. Using single-cell functional genomics, we find that distinct transcription factor profiles are inherited from the three precursor states and incorporated at lineage-specific enhancer elements. This lineage-specific regulatory logic suggests that these regionalized skeletogenic cells are distinct cell types, rendering them amenable to individualized selection, to define adaptive morphologies and biomaterial properties in different parts of the vertebrate skeleton.

Terminal differentiation and persistence of effector regulatory T cells essential for preventing intestinal inflammation

Regulatory T (Treg) cells are a specialized CD4+ T cell lineage with essential anti-inflammatory functions. Analysis of Treg cell adaptations to non-lymphoid tissues that enable their specialized immunosuppressive and tissue-supportive functions raises questions about the underlying mechanisms of these adaptations and whether they represent stable differentiation or reversible activation states. Here, we characterize distinct colonic effector Treg cell transcriptional programs. Attenuated T cell receptor (TCR) signaling and acquisition of substantial TCR-independent functionality seems to facilitate the terminal differentiation of a population of colonic effector Treg cells that are distinguished by stable expression of the immunomodulatory cytokine IL-10. Functional studies show that this subset of effector Treg cells, but not their expression of IL-10, is indispensable for colonic health. These findings identify core features of the terminal differentiation of effector Treg cells in non-lymphoid tissues and their function.

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Understanding the role of transcription and transcription factors (TFs) in cellular identity and disease, such as cancer, is essential. However, comprehensive data resources for cell line-specific TF-to-target gene annotations are currently limited. To address this, we employed a straightforward method to define regulons that capture the cell-specific aspects of TF binding and transcript expression levels. By integrating cellular transcriptome and TF binding data, we generated regulons for 40 common cell lines comprising both proximal and distal cell line-specific regulatory events. Through systematic benchmarking involving TF knockout experiments, we demonstrated performance on par with state-of-the-art methods, with our method being easily applicable to other cell types of interest. We present case studies using three cancer single-cell datasets to showcase the utility of these cell-type-specific regulons in exploring transcriptional dysregulation. In summary, this study provides a valuable pipeline and a resource for systematically exploring cell line-specific transcriptional regulations, emphasizing the utility of network analysis in deciphering disease mechanisms.

Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis

Cell fate plasticity enables development, yet unlocked plasticity is a cancer hallmark. While transcription master regulators induce lineage-specific genes to restrict plasticity, it remains unclear whether plasticity is actively suppressed by lineage-specific repressors. Here we computationally predict so-called safeguard repressors for 18 cell types that block phenotypic plasticity lifelong. We validated hepatocyte-specific candidates using reprogramming, revealing that prospero homeobox protein 1 (PROX1) enhanced hepatocyte identity by direct repression of alternative fate master regulators. In mice, Prox1 was required for efficient hepatocyte regeneration after injury and was sufficient to prevent liver tumorigenesis. In line with patient data, Prox1 depletion caused hepatocyte fate loss in vivo and enabled the transition of hepatocellular carcinoma to cholangiocarcinoma. Conversely, overexpression promoted cholangiocarcinoma to hepatocellular carcinoma transdifferentiation. Our findings provide evidence for PROX1 as a hepatocyte-specific safeguard and support a model where cell-type-specific repressors actively suppress plasticity throughout life to safeguard lineage identity and thus prevent disease.

Hypoxia-induced CTCF mediates alternative splicing via coupling chromatin looping and RNA Pol II pause to promote EMT in breast cancer

Hypoxia influences the epithelial-mesenchymal transition (EMT) through the remodeling of the chromatin structure, epigenetics, and alternative splicing. Hypoxia drives CCCTC-binding factor (CTCF) induction through hypoxia-inducible factor 1-alpha (HIF1α), which promotes EMT, although the underlying mechanisms remain unclear. We find that hypoxia significantly increases CTCF occupancy at various EMT-related genes. We present a CTCF-mediated intricate mechanism promoting EMT wherein CTCF binding at the collagen type V alpha 1 chain (COL5A1) promoter is crucial for COL5A1 upregulation under hypoxia. Additionally, hypoxia drives exon64A inclusion in a mutually exclusive alternative splicing event of COL5A1exon64 (exon64A/64B). Notably, CTCF mediates COL5A1 promoter-alternatively spliced exon upstream looping that regulates DNA demethylation at distal exon64A. This further regulates the CTCF-mediated RNA polymerase II pause at COL5A1exon64A, leading to its inclusion in promoting the EMT under hypoxia. Genome-wide study indicates the association of gained CTCF occupancy with the alternative splicing of many cancer-related genes, similar to the proposed model. Specifically, disrupting the HIF1α-CTCF-COL5A1exon64A axis through the dCas9-DNMT3A system alleviates the EMT in hypoxic cancer cells and may represent a novel therapeutic target in breast cancer.

A single-cell and spatial wheat root atlas with cross-species annotations delineates conserved tissue-specific marker genes and regulators

Despite the broad use of single-cell/nucleus RNA sequencing in plant research, accurate cluster annotation in less-studied plant species remains a major challenge due to the lack of validated marker genes. Here, we generated a single-cell RNA sequencing atlas of soil-grown wheat roots and annotated cluster identities by transferring annotations from publicly available datasets in wheat, rice, maize, and Arabidopsis. The predictions from our orthology-based annotation approach were next validated using untargeted spatial transcriptomics. These results allowed us to predict evolutionarily conserved tissue-specific markers and generate cell type-specific gene regulatory networks for root tissues of wheat and the other species used in our analysis. In summary, we generated a single-cell and spatial transcriptomics resource for wheat root apical meristems, including numerous known and uncharacterized cell type-specific marker genes and developmental regulators. These data and analyses will facilitate future cell type annotation in non-model plant species.

Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

The MYB-related transcription factor family in rubber dandelion (Taraxacum kok-saghyz): An insight into a latex-predominant member, TkMYBR090

MYB-related (MYBR) proteins play diverse roles in plant growth and development. However, the MYBR genes in Taraxacum kok-saghyz, a promising alternative source of natural rubber, a valuable biopolymer, remain scarcely investigated. Here, a total of 122 MYBR genes, namely TkMYBRs, were identified and classified into the groups of GARP-like, CCA1-like/R-R, and a heterogenous one in T. kok-saghyz. Collinearity analysis revealed a high similarity in MYBRs across two Taraxacum species with contrasting rubber yield. TkMYBR090 showed predominant expression in latex, the cytoplasm of rubber-producing laticifers. Transient overexpression of TkMYBR090 in tobacco and T. kok-saghyz demonstrated its localizations in nucleus and cytoplasm. Yeast two-hybrid assay revealed that the C-terminus of TkMYBR090 possessed transcriptional activation activity. DAP-seq analysis identified 18,232 TkMYBR090-targeted candidate genes, and four significantly enriched TkMYBR090 DNA-binding promoter motifs that were validated by yeast one-hybrid assay. The binding of TkMYBR090 on the promoter of an ascorbate oxidase gene was verified by yeast one-hybrid and dual luciferase activity assays, suggesting a role in ROS metabolism. Such assumption was supported by heterologous expression assays of TkMYBR090 in tobacco and yeast. This study is beneficial to further functional dissection of MYBRs in T. kok-saghyz, especially the roles in development and function of rubber-producing laticifers.

Clonal memory of colitis accumulates and promotes tumor growth

Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.

Multiplexed CRISPRi Reveals a Transcriptional Switch Between KLF Activators and Repressors in the Maturing Neocortex

A critical phase of mammalian brain development takes place after birth. Neurons of the mouse neocortex undergo dramatic changes in their morphology, physiology, and synaptic connections during the first postnatal month, while properties of immature neurons, such as the capacity for robust axon outgrowth, are lost. The genetic and epigenetic programs controlling prenatal development are well studied, but our understanding of the transcriptional mechanisms that regulate postnatal neuronal maturation is comparatively lacking. By integrating chromatin accessibility and gene expression data from two subtypes of neocortical pyramidal neurons in the neonatal and maturing brain, we predicted a role for the Krüppel-Like Factor (KLF) family of Transcription Factors in the developmental regulation of neonatally expressed genes. Using a multiplexed CRISPR Interference (CRISPRi) knockdown strategy, we found that a shift in expression from KLF activators (Klf6, Klf7) to repressors (Klf9, Klf13) during early postnatal development functions as a transcriptional 'switch' to first activate, then repress a set of shared targets with cytoskeletal functions including Tubb2b and Dpysl3. We demonstrate that this switch is buffered by redundancy between KLF paralogs, which our multiplexed CRISPRi strategy is equipped to overcome and study. Our results indicate that competition between activators and repressors within the KLF family regulates a conserved component of the postnatal maturation program that may underlie the loss of intrinsic axon growth in maturing neurons. This could facilitate the transition from axon growth to synaptic refinement required to stabilize mature circuits.

Dynamic properties of transcriptional condensates modulate CRISPRa-mediated gene activation

CRISPR activation (CRISPRa) is a powerful tool for endogenous gene activation, yet the mechanisms underlying its optimal transcriptional activation remain unclear. By monitoring real-time transcriptional bursts, we find that CRISPRa modulates both burst duration and amplitude. Our quantitative imaging reveals that CRISPR-SunTag activators, with three tandem VP64-p65-Rta (VPR), form liquid-like transcriptional condensates and exhibit high activation potency. Although visible CRISPRa condensates are associated with some RNA bursts, the overall levels of phase separation do not correlate with transcriptional bursting or activation strength in individual cells. When the number of SunTag scaffolds is increased to 10 or more, solid-like condensates form, sequestering co-activators such as p300 and MED1. These condensates display low dynamicity and liquidity, resulting in ineffective gene activation. Overall, our studies characterize various phase-separated CRISPRa systems for gene activation, highlighting the foundational principles for engineering CRISPR-based programmable synthetic condensates with appropriate properties to effectively modulate gene expression.

Mapping cells through time and space with moscot

Single-cell genomic technologies enable the multimodal profiling of millions of cells across temporal and spatial dimensions. However, experimental limitations hinder the comprehensive measurement of cells under native temporal dynamics and in their native spatial tissue niche. Optimal transport has emerged as a powerful tool to address these constraints and has facilitated the recovery of the original cellular context1-4. Yet, most optimal transport applications are unable to incorporate multimodal information or scale to single-cell atlases. Here we introduce multi-omics single-cell optimal transport (moscot), a scalable framework for optimal transport in single-cell genomics that supports multimodality across all applications. We demonstrate the capability of moscot to efficiently reconstruct developmental trajectories of 1.7 million cells from mouse embryos across 20 time points. To illustrate the capability of moscot in space, we enrich spatial transcriptomic datasets by mapping multimodal information from single-cell profiles in a mouse liver sample and align multiple coronal sections of the mouse brain. We present moscot.spatiotemporal, an approach that leverages gene-expression data across both spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. We also resolve endocrine-lineage relationships of delta and epsilon cells in a previously unpublished mouse, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility. Our findings are confirmed through experimental validation of NEUROD2 as a regulator of epsilon progenitor cells in a model of human induced pluripotent stem cell islet cell differentiation. Moscot is available as open-source software, accompanied by extensive documentation.

Multiscale footprints reveal the organization of cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression and are dynamic in their structure and function, reflecting changes in the composition of diverse effector proteins over time1. However, methods for measuring the organization of effector proteins at CREs across the genome are limited, hampering efforts to connect CRE structure to their function in cell fate and disease. Here we developed PRINT, a computational method that identifies footprints of DNA-protein interactions from bulk and single-cell chromatin accessibility data across multiple scales of protein size. Using these multiscale footprints, we created the seq2PRINT framework, which uses deep learning to allow precise inference of transcription factor and nucleosome binding and interprets regulatory logic at CREs. Applying seq2PRINT to single-cell chromatin accessibility data from human bone marrow, we observe sequential establishment and widening of CREs centred on pioneer factors across haematopoiesis. We further discover age-associated alterations in the structure of CREs in murine haematopoietic stem cells, including widespread reduction of nucleosome footprints and gain of de novo identified Ets composite motifs. Collectively, we establish a method for obtaining rich insights into DNA-binding protein dynamics from chromatin accessibility data, and reveal the architecture of regulatory elements across differentiation and ageing.

Refining the cis-regulatory grammar learned by sequence-to-activity models by increasing model resolution

Chromatin accessibility can be measured genome-wide with ATAC-seq, enabling the discovery of regulatory regions that control gene expression and determine cell type. Deep genomic sequence-to-function (S2F) models link underlying genomic sequences to the measured chromatin state and identify motifs that regulate chromatin accessibility. Previously, we developed AI-TAC, a S2F model that predicts chromatin accessibility across 81 immune cell types and identifies sequence patterns that control their differential ATAC-seq signals. While AI-TAC provided valuable insights into the regulatory patterns that govern immune cell differentiation, later research established that ATAC-seq profiles (the distribution of Tn5 cuts) contain additional information about the exact location and strength of TF binding. To make use of this additional information, we developed bpAI-TAC, a multi-task neural network which models ATAC-seq at base-pair resolution across 90 immune cell types. We show that adding ATAC-profile information consistently improves predictions of differential chromatin accessibility. We also demonstrate that simultaneous learning of related cell types through multi-task modeling leads to better predictions than single task models. We then present a systematic framework for comparing how differences in model performance can be attributed to differences in what the model has learned. To understand what additional information bpAI-TAC gleans from ATAC-profiles, we use sequence attributions and identify motifs that have different effect sizes when trained on profiles. We conclude that modeling ATAC-seq at base-pair resolution enables the model to learn a more sensitive representation of the regulatory syntax that drives differences between immunocytes, and therefore will improve predictions of variant effects.

Telomemore enables single-cell analysis of cell cycle and chromatin condensation

Single-cell RNA-seq methods can be used to delineate cell types and states at unprecedented resolution but do little to explain why certain genes are expressed. Single-cell ATAC-seq and multiome (ATAC + RNA) have emerged to give a complementary view of the cell state. It is however unclear what additional information can be extracted from ATAC-seq data besides transcription factor binding sites. Here, we show that ATAC-seq telomere-like reads counter-inituively cannot be used to infer telomere length, as they mostly originate from the subtelomere, but can be used as a biomarker for chromatin condensation. Using long-read sequencing, we further show that modern hyperactive Tn5 does not duplicate 9 bp of its target sequence, contrary to common belief. We provide a new tool, Telomemore, which can quantify nonaligning subtelomeric reads. By analyzing several public datasets and generating new multiome fibroblast and B-cell atlases, we show how this new readout can aid single-cell data interpretation. We show how drivers of condensation processes can be inferred, and how it complements common RNA-seq-based cell cycle inference, which fails for monocytes. Telomemore-based analysis of the condensation state is thus a valuable complement to the single-cell analysis toolbox.

KAS-ATAC reveals the genome-wide single-stranded accessible chromatin landscape of the human genome

Gene regulation in most eukaryotes involves two fundamental processes: alterations in genome packaging by nucleosomes, with active cis-regulatory elements (CREs) generally characterized by open-chromatin configuration, and transcriptional activation. Mapping these physical properties and biochemical activities, through profiling chromatin accessibility and active transcription, is a key tool for understanding the logic and mechanisms of transcription and its regulation. However, the relationship between these two states has not been accessible to simultaneous measurement. To this end, we developed KAS-ATAC, a combination of the kethoxal-assisted ssDNA sequencing (KAS-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) methods for mapping single-stranded DNA (and thus active transcription) and chromatin accessibility, respectively, enabling the genome-wide identification of DNA fragments that are simultaneously accessible and contain ssDNA. We use KAS-ATAC to evaluate levels of active transcription over different CRE classes, to estimate absolute levels of transcribed accessible DNA over CREs, to map nucleosomal configurations associated with RNA polymerase activities, and to assess transcription factor association with transcribed DNA through transcription factor binding site (TFBS) footprinting. We observe lower levels of transcription over distal enhancers compared with promoters and distinct nucleosomal configurations around transcription initiation sites associated with active transcription. We find that most TFs associate equally with transcribed and nontranscribed DNA, but a few factors specifically do not exhibit footprints over ssDNA-containing fragments. We anticipate KAS-ATAC to continue to derive useful insights into chromatin organization and transcriptional regulation in other contexts in the future.

Multiomic analysis reveals cellular, transcriptomic and epigenetic changes in intestinal pouches of ulcerative colitis patients

Total proctocolectomy with ileal pouch anal anastomosis is the standard of care for patients with severe ulcerative colitis. We generated a cell-type-resolved transcriptional and epigenetic atlas of ileal pouches using scRNA-seq and scATAC-seq data from paired biopsy samples of the ileal pouch and the ileal segment above the pouch (pre-pouch) from patients (male=4, female=2), and paired biopsies of the terminal ileum and ascending colon from healthy individuals (male=3, female=3) serving as reference. Our study finds an additional population of absorptive and secretory epithelial cells within the pouch but not the pre-pouch. These pouch-specific enterocytes express a subset of colon-specific genes, including CEACAM5 and CD24. However, compared to normal colonocytes, expression of these genes is lower, and these enterocytes also express inflammatory and secretory genes while maintaining expression of some ileal-specific genes. This cell-type-resolved transcriptomic and epigenetic atlas of the ileal pouch establishes a reference for investigating pouch physiology and pathology.

Cis-Regulatory Element and Transcription Factor Circuitry Required for Cell-Type Specific Expression of FOXP3

FOXP3 is a lineage-defining transcription factor (TF) for immune-suppressive regulatory T cells (Tregs). While mice exclusively express FOXP3 in Tregs, humans also transiently express FOXP3 in stimulated conventional CD4+ T cells (Tconvs). Mechanisms governing these distinct expression patterns remain unknown. Here, we performed CRISPR screens tiling the FOXP3 locus and targeting TFs in human Tregs and Tconvs to discover cis-regulatory elements (CREs) and trans-regulators of FOXP3. Tconv FOXP3 expression depended on a subset of Treg CREs and Tconv-selective positive (TcNS+) and negative (TcNS-) CREs. The CREs are occupied and regulated by TFs we identified as critical regulators of FOXP3. Finally, mutagenesis of murine TcNS- revealed that it is critical for restriction of FOXP3 expression to Tregs. We discover CRE and TF circuitry controlling FOXP3 expression and reveal evolution of mechanisms regulating a gene indispensable to immune homeostasis.

Multiomic analysis reveals cellular, transcriptomic and epigenetic changes in intestinal pouches of ulcerative colitis patients

Total proctocolectomy with ileal pouch anal anastomosis is the standard of care for patients with severe ulcerative colitis. We generated a cell-type-resolved transcriptional and epigenetic atlas of ileal pouches using scRNA-seq and scATAC-seq data from paired biopsy samples of the ileal pouch and the ileal segment above the pouch (pre-pouch) from patients (male=4, female=2), and paired biopsies of the terminal ileum and ascending colon from healthy individuals (male=3, female=3) serving as reference. Our study finds previously uncharacterized populations of absorptive and secretory epithelial cells within the pouch but not the pre-pouch. These pouch-specific enterocytes express a subset of colon-specific genes, including CEACAM5 and CD24. However, compared to normal colonocytes, expression of these genes is lower, and these enterocytes also express inflammatory and secretory genes while maintaining expression of some ileal-specific genes. This cell-type-resolved transcriptomic and epigenetic atlas of the ileal pouch establishes a reference for investigating pouch physiology and pathology.

Transcriptomic and genetic analysis reveals a Zn2Cys6 transcription factor specifically required for conidiation in submerged cultures of Thermothelomyces thermophilus

Filamentous fungi are important producers of enzymes and secondary metabolites. The industrial thermophilic species, Thermothelomyces thermophilus, is closely related to the model fungus, Neurospora crassa. A critical aspect of the filamentous fungal life cycle is the production of asexual spores (conidia), which are regulated by various stimuli, including nutrient availability. Several species of fungi, including T. thermophilus, produce conidia under submerged fermentation conditions, which can be detrimental to product yields. In this study, transcriptional profiling of T. thermophilus was used to map changes during asexual development in submerged cultures, which revealed commonalities of regulation between T. thermophilus and N. crassa. We further identified a transcription factor, res1, whose deletion resulted in a complete loss of conidia production under fermentation conditions, but which did not affect conidiation on plates. Under fermentation conditions, the ∆res1 deletion strain showed increased biomass production relative to the wild-type strain, indicating that the manipulation of res1 in T. thermophilus has the potential to increase productivity in industrial settings. Overexpression of res1 caused a severe growth defect and early conidia production on both plates and in submerged cultures, indicating res1 overexpression can bypass regulatory aspects associated with conidiation on plates. Using chromatin-immunoprecipitation sequencing, we identified 35 target genes of Res1, including known conidiation regulators identified in N. crassa, revealing common and divergent aspects of asexual reproduction in these two species.IMPORTANCEFilamentous fungi, such as Thermothelomyces thermophilus, are important industrial species and have been harnessed in the Biotechnology industry for the production of industrially relevant chemicals and proteins. However, under fermentation conditions, some filamentous fungi will undergo a switch from mycelial growth to asexual development. In this study, we use transcriptional profiling of asexual development in T. thermophilus and identify a transcription factor that specifically regulates the developmental switch to the production of unwanted asexual propagules under fermentation conditions, thus altering secreted protein production. Mutations in this transcription factor Res1 result in the loss of asexual development in submerged cultures but do not affect asexual sporulation when exposed to air. The identification of stage-specific developmental regulation of asexual spore production and comparative analyses of conidiation in filamentous ascomycete species have the potential to further manipulate these species for industrial advantage.

Transcription factor-dependent regulatory networks of sexual reproduction in Fusarium graminearum

Transcription factors (TFs) involved in sexual reproduction in filamentous fungi have been characterized. However, we have little understanding of how these TFs synergize within regulatory networks resulting in sexual development. We investigated 13 TFs in Fusarium graminearum, whose knockouts exhibited abortive or arrested phenotypes during sexual development to elucidate the transcriptional regulatory cascade underlying the development of the sexual fruiting bodies. A Bayesian network of the TFs was inferred based on transcriptomic data from key stages of sexual development. We evaluated in silico knockout impacts to the networks of the developmental phenotypes among the TFs and guided knockout transcriptomics experiments to properly assess regulatory roles of genes with same developmental phenotypes. Additional transcriptome data were collected for the TF knockouts guided by the stage at which their phenotypes appeared and by the cognate in silico prediction. Global TF networks revealed that TFs within the mating-type locus (MAT genes) trigger a transcriptional cascade involving TFs that affected early stages of sexual development. Notably, PNA1, whose knockout mutants produced exceptionally small protoperithecia, was shown to be an upstream activator for MAT genes and several TFs essential for ascospore production. In addition, knockout mutants of SUB1 produced excessive numbers of protoperithecia, wherein MAT genes and pheromone-related genes exhibited dysregulated expression. We conclude that PNA1 and SUB1 play central and suppressive roles in initiating sexual reproduction, respectively. This comprehensive investigation contributes to our understanding of the transcriptional framework governing the multicellular body plan during sexual reproduction in F. graminearum.IMPORTANCEUnderstanding transcriptional regulation of sexual development is crucial to the elucidation of the complex reproductive biology in Fusarium graminearum. We performed gene knockouts on 13 transcription factors (TFs), demonstrating knockout phenotypes affecting distinct stages of sexual development. Using transcriptomic data across stages of sexual development, we inferred a Bayesian network of these TFs that guided experiments to assess the robustness of gene interactions using a systems biology approach. We discovered that the mating-type locus (MAT genes) initiates a transcriptional cascade, with PNA1 identified as an upstream activator essential for early sexual development and ascospore production. Conversely, SUB1 was found to play a suppressive role, with knockout mutants exhibiting excessive protoperithecia due to abnormally high expression of MAT and pheromone-related genes. These findings highlight the central roles of PNA1 and SUB1 in regulating other gene activity related to sexual reproduction, contributing to a deeper understanding of the mechanisms of the multiple TFs that regulate sexual development.

Integrative multiomics reveals common endotypes across PSEN1, PSEN2, and APP mutations in familial Alzheimer's disease

BACKGROUND

PSEN1, PSEN2, and APP mutations cause Alzheimer's disease (AD) with an early age at onset (AAO) and progressive cognitive decline. PSEN1 mutations are more common and generally have an earlier AAO; however, certain PSEN1 mutations cause a later AAO, similar to those observed in PSEN2 and APP.

METHODS

We examined whether common disease endotypes exist across these mutations with a later AAO (~ 55 years) using hiPSC-derived neurons from familial Alzheimer's disease (FAD) patients harboring mutations in PSEN1A79V, PSEN2N141I, and APPV717I and mechanistically characterized by integrating RNA-seq and ATAC-seq.

RESULTS

We identified common disease endotypes, such as dedifferentiation, dysregulation of synaptic signaling, repression of mitochondrial function and metabolism, and inflammation. We ascertained the master transcriptional regulators associated with these endotypes, including REST, ASCL1, and ZIC family members (activation), and NRF1 (repression).

CONCLUSIONS

FAD mutations share common regulatory changes within endotypes with varying severity, resulting in reversion to a less-differentiated state. The regulatory mechanisms described offer potential targets for therapeutic interventions.

Asymmetry of Motif Conservation Within Their Homotypic Pairs Distinguishes DNA-Binding Domains of Target Transcription Factors in ChIP-Seq Data

Transcription factors (TFs) are the main regulators of eukaryotic gene expression. The cooperative binding of at least two TFs to genomic DNA is a major mechanism of transcription regulation. Massive analysis of the co-occurrence of overrepresented pairs of motifs for different target TFs studied in ChIP-seq experiments can clarify the mechanisms of TF cooperation. We categorized the target TFs from M. musculus ChIP-seq and A. thaliana ChIP-seq/DAP-seq experiments according to the structure of their DNA-binding domains (DBDs) into classes. We studied homotypic pairs of motifs, using the same recognition model for each motif. Asymmetric and symmetric pairs consist of motifs of remote and close recognition scores. We found that asymmetric pairs of motifs predominate for all TF classes. TFs from the murine/plant 'Basic helix-loop-helix (bHLH)', 'Basic leucine zipper (bZIP)', and 'Tryptophan cluster' classes and murine 'p53 domain' and 'Rel homology region' classes showed the highest enrichment of asymmetric homotypic pairs of motifs. Pioneer TFs, despite their DBD types, have a higher significance of asymmetry within homotypic pairs of motifs compared to other TFs. Asymmetry within homotypic CEs is a promising new feature decrypting the mechanisms of gene transcription regulation.

Multi-Omics Atlas-Assisted Discovery of Transcription Factors for Selective T Cell State Programming

Transcription factors (TFs) regulate the differentiation of T cells into diverse states with distinct functionalities. To precisely program desired T cell states in viral infections and cancers, we generated a comprehensive transcriptional and epigenetic atlas of nine CD8 + T cell differentiation states for TF activity prediction. Our analysis catalogued TF activity fingerprints of each state, uncovering new regulatory mechanisms that govern selective cell state differentiation. Leveraging this platform, we focused on two critical T cell states in tumor and virus control: terminally exhausted T cells (TEX term ), which are dysfunctional, and tissue-resident memory T cells (T RM ), which are protective. Despite their functional differences, these states share significant transcriptional and anatomical similarities, making it both challenging and essential to engineer T cells that avoid TEX term differentiation while preserving beneficial T RM characteristics. Through in vivo CRISPR screening combined with single-cell RNA sequencing (Perturb-seq), we validated the specific TFs driving the TEX term state and confirmed the accuracy of TF specificity predictions. Importantly, we discovered novel TEX term -specific TFs such as ZSCAN20, JDP2, and ZFP324. The deletion of these TEX term -specific TFs in T cells enhanced tumor control and synergized with immune checkpoint blockade. Additionally, this study identified multi-state TFs like HIC1 and GFI1, which are vital for both TEX term and T RM states. Furthermore, our global TF community analysis and Perturb-seq experiments revealed how TFs differentially regulate key processes in T RM and TEX term cells, uncovering new biological pathways like protein catabolism that are specifically linked to TEX term differentiation. In summary, our platform systematically identifies TF programs across diverse T cell states, facilitating the engineering of specific T cell states to improve tumor control and providing insights into the cellular mechanisms underlying their functional disparities.

A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause

The fallopian tube undergoes extensive molecular changes during the menstrual cycle and menopause. We use single-cell RNA and ATAC sequencing to construct a comprehensive cell atlas of healthy human fallopian tubes during the menstrual cycle and menopause. Our scRNA-seq comparison of 85,107 pre- and 46,111 post-menopausal fallopian tube cells reveals substantial shifts in cell type frequencies, gene expression, transcription factor activity, and cell-to-cell communications during menopause and menstrual cycle. Menstrual cycle dependent hormonal changes regulate distinct molecular states in fallopian tube secretory epithelial cells. Postmenopausal fallopian tubes show high chromatin accessibility in transcription factors associated with aging such as Jun, Fos, and BACH1/2, while hormone receptors were generally downregulated, a small proportion of secretory epithelial cells had high expression of ESR2, IGF1R, and LEPR. While a pre-menopausal secretory epithelial gene cluster is enriched in the immunoreactive molecular subtype, a subset of genes expressed in post-menopausal secretory epithelial cells show enrichment in the mesenchymal molecular type of high-grade serous ovarian cancer.