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PubMed2026

MACS3: A Peak-calling Platform for Bulk and Single-cell Regulatory Genomics.

Since the original publication of Model-based Analysis for ChIP-Seq (MACS), the software has been widely used to identify enriched genomic regions in ChIP-seq, ATAC-seq, CUT&RUN, DNase-seq, and related regulatory genomics assays. Over the years, MACS has evolved substantially, with MACS version 3 (MACS3) now serving as the actively maintained implementation. MACS3 preserves the core MACS framework for fragment pileup, dynamic local background noise, statistical enrichment testing, and peak refinement, while adding functionality needed for contemporary bulk and single-cell workflows. It supports conventional bulk peak calling, paired-end and fragment-based file formats, modular signal processing, direct analysis of single-cell ATAC-seq fragment files, barcode-restricted pseudobulk and cluster-level peak calling, specialized ATAC-seq and variant-calling modules, as well as command-line and programmatic interfaces. MACS3 is distributed through standard software channels and supported by continuous testing across operating systems, Python versions, and CPU architectures. Here we describe the architecture, current capabilities, and recommended use of MACS3, providing an updated reference for applying the MACS framework in contemporary bulk and single-cell regulatory genomics workflows. MACS3 is open-source software available at https://github.com/macs3-project/MACS.

Bioinformatics software↗

PubMed2025

Development and validation of blood-based diagnostic biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) using EpiSwitch® 3-dimensional genomic regulatory immuno-genetic profiling.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating, multifactorial disorder characterised by profound fatigue, post-exertional malaise, cognitive impairments, and autonomic dysfunction. Despite its significant impact on quality of life, ME/CFS lacks definitive diagnostic biomarkers, complicating diagnosis and management. Recent evidence highlights potential blood tests for ME/CFS biomarkers in immunological, genetic, metabolic, and bioenergetic domains. Chromosome conformations (CCs) are potent epigenetic regulators of gene expression and cross-tissue exosome signalling. We have previously developed an epigenetic assay, EpiSwitch®, that employs an algorithm-based CCs analysis. Using EpiSwitch® technology, we have shown the presence of disease-specific CCs in peripheral blood mononuclear cells (PBMCs) of patients with amyotrophic lateral sclerosis (ALS), rheumatoid arthritis (RA), prostate and colorectal cancers, diffuse Large B-cell lymphoma and severe COVID-19. In a recent paper, we have identified a profile of systemic chromosome conformations in cancer patients reflective of the predisposition to respond to immune checkpoint inhibitors, PD-1/PD-L1 antagonists, with 85% accuracy. In this Retrospective case/control study (EPI-ME, Epigenetic Profiling Investigation in Myalgic Encephalomyelitis), we used whole blood samples retrospectively collected from n = 47 patients with severe ME/CFS and n = 61 age-matched healthy control patients to perform whole-genome 3D DNA screening for CCs correlating to ME/CFS diagnosis. We identified a 200-marker model for ME/CFS diagnosis (Episwitch®CFS test). First testing on the retrospective independent validation cohort demonstrated a strong systemic ME/CFS signal with a sensitivity of 92% and a specificity of 98%.Pathways analysis revealed several likely contributors to the pathology of ME/CFS, including interleukins, TNFα, neuroinflammatory pathways, toll-like receptor signalling and JAK/STAT. Comparison with pathways involved in the action of Rituximab and glatiramer acetate (Copaxone) (therapies with potential in ME/CFS treatment) identified IL2 as a shared pathway with clear patient clustering, indicating a possibility of a potential responder group for targeted treatment.

Humans↗

PubMed2026

Using the DNA language model, GROVER, to parse effects of sequence, chromatin and regulatory features on genome stability.

MOTIVATION: Genome stability is shaped by DNA sequence and chromatin context, but their relative contributions to double-strand break (DSB) sensitivity remain unclear. RESULTS: We show that the DNA language model, GROVER, can infer DSB location based on sequence. DSB hotspots tend to contain GC-rich sequences that belong to promoters, genes and short interspersed nuclear elements (SINEs). Additionally, we identified several specific short sequences (tokens) that are associated with modulating DSB sensitivity. Another model using chromatin and genome regulatory features outperforms the sequence-only model, highlighting complementary and cell-type specific information. Integrating sequence and genome biological features yields the best performance, demonstrating their synergy. Analyzing this model revealed that, dependent on the sample, genome stability information encoded in H3K36me3 and DNase-seq can be learned from the sequence, but not H3K27ac or H3K9me3. Embedding chromatin data directly into the GROVER architecture enabled cell-type specific modeling with performance matching the full chromatin feature model. Our results suggest that while chromatin and regulatory context provides important information, such as cell-type specificity, much of the information shaping DSB patterns is already encoded in the DNA sequence itself. Our integrative modeling approach not only reveals DSB patterns but also provides a generalizable strategy for tracing predictions in genomic data. AVAILABILITY: Data, models, and a tutorial are available on Zenodo.

Chromatin↗

PubMed2025

Genome editing research initiatives and regulatory landscape of genome edited crops in India.

Food and nutritional security are the top priorities in Indian agriculture. Exponential population growth coupled with climate change effects has become a serious challenge for sustainable agriculture. Genome editing has revolutionized the agricultural sector because of its ability to create precise, stable and predictable modifications in the genome and therefore, offers great opportunities for crop improvement in India. However, for harvesting the real benefits of this technology in agriculture sector, there is a strong need of creating awareness among the end users and development of suitable policies for regularization of genome edited products. Many regulatory agencies around the world have been modernizing their regulatory approaches to be more risk proportionate and to reflect a more science-based approach. In this article, recent research initiatives and developments undertaken by different Indian institutes/organizations for the genetic improvement of agricultural and horticultural crops via genome editing technologies are summarized. Furthermore, to benefit from this potential technology in our country, regulatory policies must be clear, science-based and proportionate. Therefore, in the present review, the regulatory policies related to the genome editing of crop products in India are discussed in detail. This review will sensitize researchers and stakeholders to the application of genome editing techniques in crop improvement and various biosafety committees involved in the development and regulation of genome edited crops.

Crops, Agricultural↗

PubMed2026

Protocol to predict gene expression from transcriptomic data using PREDICT.

Linking DNA sequence variation to context-specific transcriptional programs is a critical challenge in regulatory genomics, especially for non-model organisms. Here, we present PREDICT, a modular Python package for discovering cis-regulatory elements and transcription factor binding motifs. We describe steps to identify enriched k-mers from differentially expressed genes, map them to known motifs, quantify their impact on gene expression, and visualize motif co-occurrences. PREDICT provides a robust, k-mer-based approach to uncover regulatory logic in diverse genomic systems. For complete details on the use and execution of this protocol, please refer to Yen et al. and Liu et al.1,2.

Gene Expression Profiling↗

PubMed2026

Cooperation of transposable elements to endow global networks of initiators of hybrid assembly pathways of endogenous multiprotein complexes.

Mechanisms governing initiation steps of the assembly of endogenous multi-protein complexes (EMC) remain incompletely understood. Here, multiple lines of observations are reported describing the function-aligned initiation sequence of hybrid assembly pathways (HAP) of EMC. The first step of HAP-guided chain reactions of protein-protein interactions (PPI) of EMC assemblies constitutes the creation of cell type-specific pools of hetero and homo dimers. The molecular anatomy of HAP was elucidated by defining qualitative and quantitative characteristics of protein binding to a compendium of 200,393 distinct genomic regulatory elements (GRE), including 49,667 sequences representing control sets of genomic loci as well as 150,726 GRE of different evolutionary origins. The consensus sequence of HAP actions consists of: a) Initiation on genomic DNA of the formation of metastable hetero- and homodimers of EMCs' protein constituents; b) Release of dimers from DNA templates for delivery to the EMC assembly compartments; c) Assembly of defined EMC by sequential on demand addition of proteins to preformed dimers serving as attractors of EMC-specific ensembles of monomers. Chromosome-naïve DNA scaffolds facilitating creation of intracellular dimer pools engage networks of ~700 transcription factors (TFs), 534 of which manifest region-specific patterns of significantly enriched expression in 1358 brain regions. HAP initiators appear to operate within nucleosome-depleted islands of transposable elements (TE) - derived sequences within heterochromatin. PPI assembly lines of EMCs operate in 2 concurrent modes: TF-TF PPI cascade and PPI HUB protein cascade. Regardless of the number of DNA-bound initiator TFs (ranging from one to 716 TFs), both modes of operations reached the equilibrium at the PPI constituents saturation levels of ~245 proteins for TF-TF PPI modes and of ~351 proteins for PPI HUB protein modes. Distinct panels of DNA-bound initiator TFs and proteins of PPI cascade ensembles are enriched in either defined sets of neuroanatomical structures (TF-TF mode) or among structural-functional constituents of synapses (HUB proteins mode). Thus, these bifurcated cascades appear biologically congruent: TF-TF constituents map to transcriptional signatures of hundreds of brain regions, whereas HUB constituents map to synaptogenesis and synaptic structures, suggesting the unified logic of genomic functions coordinating region identity and connectivity. Evidence-supported examples of default operations of PPI-guided assemblies of hetero- and homodimers of Yamanaka factors, neurogenesis constituents, and protein components of postsynaptic density of excitatory and inhibitory synaptogenesis are reported with detailed analytical focus on human Claustrum. The foundational set of observations reported in this contribution should facilitate experimental and theoretical explorations of TE-seeded genomic codes for initiators of PPI chain reactions of protein dimerization creating pools of attractors to guide and accelerate the EMC assemblies.

Humans↗

PubMed2026

gMISpy: integration of complex regulatory networks and genome scale metabolic models.

MOTIVATION: Genome-scale metabolic models lack explicit regulatory mechanisms, limiting their predictive accuracy for genetic interventions. Current methods for computing genetic Minimal Cut Sets either ignore regulatory networks entirely or use simplified acyclic representations that cannot capture regulatory feedback loops, ubiquitous features critical in cellular modeling. RESULTS: We developed gMISpy, a Python package that that enables efficient computation of genetic Minimal Intervention Sets (gMISs) in integrated genome-scale metabolic and regulatory networks. gMISpy incorporates cyclic regulatory logic into our previous computational framework using layered Boolean networks and BoNesis framework, resulting in a more accurate modeling of how regulatory interactions affect metabolic genes. Benchmarking across four different regulatory networks with Human-GEM showed consistent improvements in prediction accuracy, with Matthews correlation coefficient gains ranging from 2.50% to 14.42%. Validation against cancer data from DepMap and Project Score confirmed that cyclic integration reduces false positives and better captures biological vulnerabilities compared to acyclic approaches. AVAILABILITY AND IMPLEMENTATION: https://github.com/PlanesLab/cyclic-gMISpy.

Software↗

PubMed2025

Flashzoi: an enhanced Borzoi for accelerated genomic analysis.

MOTIVATION: Accurately predicting how DNA sequence drives gene regulation and how genetic variants alter gene expression is a central challenge in genomics. Borzoi, which models over ten thousand genomic assays including RNA-seq coverage from over half a megabase of sequence context alone promises to become an important foundation model in regulatory genomics, both for massively annotating variants and for further model development. However, the currently used relative positional encodings limit Borzoi's computational efficiency. RESULTS: We present Flashzoi, an enhanced Borzoi model that leverages rotary positional encodings and FlashAttention-2. This achieves over 3-fold faster training and inference and up to 2.4-fold reduced memory usage, while maintaining or improving accuracy in modeling various genomic assays including RNA-seq coverage, predicting variant effects, and enhancer-promoter linking. Flashzoi's improved efficiency facilitates large-scale genomic analyses and opens avenues for exploring more complex regulatory mechanisms and modeling. AVAILABILITY AND IMPLEMENTATION: The Flashzoi model architecture is part of the MIT-licensed borzoi-pytorch package, can be found at https://github.com/johahi/borzoi-pytorch and installed via pip. Model weights for all four Flashzoi and Borzoi replicates are available at https://huggingface.co/johahi under the MIT license. The code has been archived at https://zenodo.org/records/15669913.

Genomics↗

PubMed2025

Dual transcriptional activities of PAX3 and PAX7 spatially encode spinal cell fates through distinct gene networks.

Understanding how transcription factors regulate organized cellular diversity in developing tissues remains a major challenge due to their pleiotropic functions. We addressed this by monitoring and genetically modulating the activity of PAX3 and PAX7 during the specification of neural progenitor pools in the embryonic spinal cord. Using mouse models, we show that the balance between the transcriptional activating and repressing functions of these factors is modulated along the dorsoventral axis and is instructive to the patterning of spinal progenitor pools. By combining loss-of-function experiments with functional genomics in spinal organoids, we demonstrate that PAX-mediated repression and activation rely on distinct cis-regulatory genomic modules. This enables both the coexistence of their dual activity in dorsal cell progenitors and the specific control of two major differentiation programs. PAX promote H3K27me3 deposition at silencers to repress ventral identities, while at enhancers, they act as pioneer factors, opening and activating cis-regulatory modules to specify dorsal-most identities. Finally, we show that this pioneer activity is restricted to cells exposed to BMP morphogens, ensuring spatial specificity. These findings reveal how PAX proteins, modulated by morphogen gradients, orchestrate neuronal diversity in the spinal cord, providing a robust framework for neural subtype specification.

Animals↗

PubMed2026

Repeated drought induces a reproducible DNA methylation response associated with gene expression in Quercus lobata.

UNLABELLED: Long-lived trees must continually adjust to environmental change and face sustained climatic shifts over their lifetimes. One increasingly important challenge is the rising frequency of drought caused by climate change. Environmentally responsive DNA methylation is widespread in plants, but whether it contributes to gene expression during environmental stress remains unclear, particularly in long-lived trees. Here, we integrated long read methylomes and transcriptomes from valley oak ( Quercus lobata ) seedlings exposed to repeated drought and well-watered treatments. Repeated drought induced a reproducible DNA methylation response that repeatedly targeted the same genomic regions despite turnover of individual methylated sites. These repeatedly targeted regions were transposable elements (TEs) located near genes. Genes adjacent to CHH-methylated TEs were enriched for core drought-response pathways, including abscisic acid signaling, osmotic adjustment and cell-wall remodeling, and remained transcriptionally activated under drought. However, higher CHH methylation levels were associated with progressively smaller transcriptional responses, suggesting that environmentally responsive DNA methylation influences how strongly drought- response genes are activated rather than simply switching them on or off. At the same time, greater CHH methylation was associated with continued repression of nearby TEs, suggesting that this response may simultaneously regulate gene activity while maintaining genome stability. Together, these findings identify a reproducible genome- regulatory response associated with repeated environmental stress in a long-lived tree. By repeatedly targeting the same genomic regions despite turnover of individual sites, this response provides a framework for how long-lived trees repeatedly adjust gene expression while maintaining genome stability during environmental change. SIGNIFICANCE STATEMENT: Plants cannot escape environmental change, and trees must repeatedly respond to stresses, such as drought, over lifetimes spanning decades to centuries. Yet little is known about the molecular mechanisms that make this remarkable resilience possible. Using a widespread California oak, we show that repeated drought repeatedly induced the same DNA methylation pattern in the same parts of the genome, even though the differentially methylated individual sites changed between drought events. This pattern was linked to how strongly drought-response genes were activated, suggesting that trees repeatedly deploy the same molecular program to respond to environmental stress. Our findings provide a new framework for understanding how long-lived organisms repeatedly adjust to changing climates.

Journal Article↗

PubMed2026

Long-term (>7-year) parental consumption of genetically modified maize (Cry1Ab/Cry2Aj and EPSPS) induces no adverse sperm DNA methylation alterations across two generations of cynomolgus monkeys.

This study assessed the long-term safety of genetically modified (GM) maize from a male reproductive perspective, using a non-human primate model. We analyzed the sperm DNA methylation profiles in cynomolgus monkeys fed GM maize, non-GM parental maize, or a conventional diet over two generations (F0/F1). Whole-genome bisulfite sequencing (WGBS) revealed no significant differences in global methylation levels among groups. The identified differentially methylated regions (DMRs) were short, enriched in non-regulatory genomic areas, and did not cluster after treatment. Functional enrichment analysis showed that DMR-associated genes were consistently involved in the same core biological pathways (e.g., mTOR and Wnt signaling) across all dietary comparisons. These findings indicate that GM maize consumption did not induce specific adverse epigenetic alterations in sperm, with the observed changes reflecting common physiological adaptations to dietary variations rather than GM-related effects.

Animals↗

PubMed2023

Genome-wide identification of transcriptional enhancers during human placental development and association with function, differentiation, and disease†.

The placenta is a dynamic organ that must perform a remarkable variety of functions during its relatively short existence in order to support a developing fetus. These functions include nutrient delivery, gas exchange, waste removal, hormone production, and immune barrier protection. Proper placenta development and function are critical for healthy pregnancy outcomes, but the underlying genomic regulatory events that control this process remain largely unknown. We hypothesized that mapping sites of transcriptional enhancer activity and associated changes in gene expression across gestation in human placenta tissue would identify genomic loci and predicted transcription factor activity related to critical placenta functions. We used a suite of genomic assays [i.e., RNA-sequencing (RNA-seq), Precision run-on-sequencing (PRO-seq), and Chromatin immunoprecipitation-sequencing (ChIP-seq)] and computational pipelines to identify a set of >20 000 enhancers that are active at various time points in gestation. Changes in the activity of these enhancers correlate with changes in gene expression. In addition, some of these enhancers encode risk for adverse pregnancy outcomes. We further show that integrating enhancer activity, transcription factor motif analysis, and transcription factor expression can identify distinct sets of transcription factors predicted to be more active either in early pregnancy or at term. Knockdown of selected identified transcription factors in a trophoblast stem cell culture model altered the expression of key placental marker genes. These observations provide a framework for future mechanistic studies of individual enhancer-transcription factor-target gene interactions and have the potential to inform genetic risk prediction for adverse pregnancy outcomes.

Humans↗

PubMed2026

Maternal immune activation disrupts epigenomic and functional maturation of cortical excitatory neurons.

Elevated levels of maternal pro-inflammatory cytokines following severe infection during gestation can disrupt offspring neural development and increase the risk of neurodevelopmental disorders. The viral mimetic Poly(I:C) reproduces the effects of gestational influenza exposure, leading to behavioral outcomes that recapitulate neurodevelopmental disorder phenotypes. Although Poly(I:C)-induced maternal immune activation (PIC-MIA) alters the epigenome, behavior and cognition of offspring in adulthood, it remains unclear when these changes occur and how MIA influences the epigenomic regulatory programming across the transition from embryonic development to the mature brain. Here, we examined the effects of PIC-MIA on the epigenomic maturation of the frontal cortex, focusing on excitatory neuron-specific DNA methylation and transcriptomic dynamics throughout perinatal development. Mid-gestation PIC-MIA disrupted development of the excitatory neuron transcriptome, with the largest alterations observed at birth. PIC-MIA altered the development of the mature DNA methylation program of excitatory neurons at thousands of genomic regulatory regions that normally gain or lose methylation during development. Transcription factor binding site analyses of these differentially methylated regions revealed a significant enrichment of Tbr1 motifs within hyper-methylated deep-layer neuron-specific regions at birth. Notably, transcriptional targets of Tbr1 were down-regulated at birth despite up-regulation of Tbr1 transcription, suggesting PIC-MIA uncouples Tbr1 expression from its regulatory function in deep-layer neurons. Electrophysiological recordings of intrinsic and firing properties further confirmed a lasting disruption in deep-layer neuronal activity. Our results suggest that mid-gestation MIA may alter the development of deep-layer neurons through an epigenomic blockade of Tbr1 function, thereby perturbing normal cortical circuit formation.

Journal Article↗

PubMed2025

The genomic origin of the unique chaetognath body plan.

The emergence of animal phyla, each with their unique body plan, was a rapid event in the history of animal life, yet its genomic underpinnings are still poorly understood1. Here we investigate at the genomic, regulatory and cellular levels, the origin of one of the most distinctive animal phyla, the chaetognaths, whose organismal characteristics have historically complicated their phylogenetic placement2,3. We show that these characteristics are reflected at the cell-type level by the expression of genes that originated in the chaetognath lineage, contributing to adaptation to planktonic life at the sensory and structural levels4. Similarly to other members of gnathiferans (which also include rotifers and several other microscopic phyla)5,6, chaetognaths have undergone accelerated genomic evolution with gene loss and chromosomal fusions7,8. Furthermore, they secondarily duplicated thousands of genes9,10, without evidence for a whole-genome duplication, yielding, for instance, tandemly expanded Hox genes, as well as many phylum-specific genes. We also detected repeat-rich highly methylated neocentromeres and a simplified DNA methylation toolkit that is involved in mobile element repression rather than transcriptional control. Consistent with fossil evidence11,12, our observations suggest that chaetognaths emerged after a phase of morphological simplification through a reinvention of organ systems paralleled by massive genomic reorganization, explaining the uniqueness of their body plan.

Animals↗

PubMed2026

Genome-Wide Characterization of β-Glucosidase (TaBGLU) Genes in Bread Wheat and Their Expression Under Drought, Cold, and Combined Stress.

Glycoside hydrolase 1 (GH1) β-glucosidases were known to activate hormone conjugates and defense metabolites, yet their genomic organization and stress-response dynamics in wheat remained incompletely defined. We therefore performed an integrated characterization of TaBGLUs spanning phylogeny, gene structure and conserved motifs, subcellular localization, promoter cis-elements, Gene Ontology enrichment, protein-protein interaction networks, and targeted expression profiling. Wheat TaBGLUs partitioned into well-supported clades that shared canonical GH1 catalytic residues and a largely conserved motif scaffold. Subcellular localization predictions indicated predominant nuclear and chloroplast targeting, with a smaller cohort directed to secretory or endomembrane compartments. Promoters were enriched for light-responsive, hormone-related (ABA, JA/SA, auxin, GA) and stress-associated (MYB/WRKY, heat, low temperature) cis-elements, and functional annotations were consistent with roles in carbohydrate and cell-wall metabolism, hormone homeostasis, and defense. Network analysis revealed a densely connected TaBGLU submodule embedded within broader carbohydrate and defense interaction networks, suggesting coordinated or cooperative functions. Expression profiling under cold, drought, and combined drought and cold demonstrated broad stress inducibility, with early activation detected by 6 h, cold-responsive maxima typically at 12 h, drought-responsive peaks predominating at 24 h, and combined stress eliciting both earlier and more sustained expression maxima between 12-24 h. Representative strongly responsive genes included TaBGLU20, TaBGLU44, TaBGLU6, and TaBGLU23, which showed pronounced late induction under combined stress, TaBGLU30, which exhibited an earlier combined-stress peak, and TaBGLU12, which displayed a marked late drought-specific response. Taken together, this integrated genomic, regulatory, and expression atlas refined the wheat BGLU repertoire relative to previous gene model inventories, highlighted candidate TaBGLUs with central network positions and strong stress inducibility, and provided concrete entry points for functional validation and breeding for improved stress resilience.

Triticum↗

PubMed2026

Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks↗

PubMed2025

YAP/TEAD4/SP1-induced VISTA expression as a tumor cell-intrinsic mechanism of immunosuppression in colorectal cancer.

Hyperactivation of the YAP/TEAD transcriptional complex in cancers facilitates the development of an immunosuppressive tumor microenvironment. Herein, we observed that the transcription factor SP1 physically interacts with and stabilizes the YAP/TEAD complex at regulatory genomic loci in colorectal cancer (CRC). In response to serum stimulation, PKCζ (protein kinase C ζ) was found to phosphorylate SP1 and enhance its interaction with TEAD4. As a result, SP1 enhanced the transcriptional activity of YAP/TEAD and coregulated the expression of a group of YAP/TEAD target genes. The immune checkpoint V-domain Ig suppressor of T-cell activation (VISTA) was identified as a direct target of the SP1-YAP/TEAD4 complex and found to be widely expressed in CRC cells. Importantly, YAP-induced VISTA upregulation in human CRC cells was found to strongly suppress the antitumor function of CD8+ T cells. Consistently, elevated VISTA expression was found to be correlated with hyperactivation of the SP1-YAP/TEAD axis and associated with poor prognosis of CRC patients. In addition, we found by serendipity that enzymatic deglycosylation significantly improved the anti-VISTA antibody signal intensity, resulting in more accurate detection of VISTA in clinical tumor samples. Overall, our study identified SP1 as a positive modulator of YAP/TEAD for the transcriptional regulation of VISTA and developed a protein deglycosylation strategy to better detect VISTA expression in clinical samples. These findings revealed a new tumor cell-intrinsic mechanism of YAP/TAZ-mediated cancer immune evasion.

Humans↗

PubMed1977

Nonspecific DNA binding of genome-regulating proteins as a biological control mechanism: measurement of DNA-bound Escherichia coli lac repressor in vivo.

Binding of genome regulatory proteins to nonspecific DNA sites may play an important role in controlling the thermodynamics and kinetics of the interactions of these proteins with their specific target DNA sequences. An estimate of the fraction of Escherichia coli lac repressor molecules bound in vivo to the operator region and to nonoperator sites on the E. coli chromosome is derived by measurement of the distribution of repressor between a minicell-producing E. coli strain (P678-54) and the DNA-free minicells derived therefrom. Assuming the minicell cytoplasm to be representative of that of the parent E. coli cells, we find that less than 10% of the repressor tetramers of the average cell are free in solution; the remainder are presumed to be bound to the bacterial chromosome. The minimum in vivo value of the association constant for repressor to bulk nonoperator DNA (K(RD)) calculated from these results is about 10(3) M(-1), and analysis of the sources of error in the minicell experiment suggests that the actual in vivo value of K(RD) could be substantially greater. The value of K(RD), coupled with in vitro data on the ionic strength dependence of this parameter, can be used to estimate that the effective intracellular cation activity of E. coli is no greater than about 0.24 M (and probably no less than 0.17 M) in terms of sodium ion equivalents. The minicell distribution experiments also confirm that the association constant for the binding of inducer-repressor complex to bulk nonoperator DNA (K(RID)) is [unk] K(RD)in vivo. These results are used to calculate minimum in vivo values of K(RO) and K(RIO) (association constants for repressor and for inducer-repressor complex binding to operator) of about 10(12) M(-1) and about 10(9) M(-1), respectively. The results fit a quantitative model for operon regulation in which nonspecific DNA-repressor complexes play a key role in determining basal and constitutive levels of gene expression [von Hippel, P. H., Revzin, A., Gross, C. A. & Wang, A. C. (1974) Proc. Natl. Acad. Sci. USA 71, 4808-4812].

Bacterial Proteins↗