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Generation of spCAS9 expressing human mesenchymal stem cell line to study gene function during osteoblast differentiation.

Human bone marrow-derived stromal cells (hMSCs) are a great resource for studying how genes influence cell fate and differentiation into various cell types like osteoblasts, adipocytes, and chondrocytes, among other cell types. However, genetic manipulation of primary hMSCs has been challenging due to their short lifespan and cellular senescence after limited passaging. Their low and unstable transfection efficiency also complicates gene delivery or inactivation, hindering long-term functional studies. The limited lifespan has been effectively solved by immortalizing hMSCs with telomerase reverse transcriptase (hMSCs-TERT). The use of these cells is ideal for functional studies of osteoblast and adipocyte differentiation through genetic manipulation, providing a stable and reliable model. Here, we have engineered a stable CAS9 expressing hMSC-TERT cell line (hMSC-TERTCAS9) via lentiviral transduction. The constitutive expression of spCas9 enables efficient and reproducible gene editing. We demonstrate the potential of these hMSC-TERTCAS9 cells for generating gene disruptions using plasmid delivery of guide RNAs as a fast and efficient strategy for targeted genome editing. The edited cells can be sorted and expanded as single cells to obtain homogenous clonal cell lines with mono- as well as bi-allelic gene deletions, a crucial step for producing reliable experimental results. We further validate this cell line as a powerful tool for studying gene function during hMSC proliferation and differentiation, providing 3 distinct examples of its utility. Through the generation of indels, single-cell sorting, and clonal selection, we have efficiently inactivated the vitamin D receptor and created both larger (256 nucleotides) gene disruptions in Forkhead box protein O1 and precise removals of a small genomic sequence (73 nucleotides) coding for microRNA MIR675. This novel hMSC-TERTCAS9 cell line represents a significant advancement, offering a stable, efficient, and versatile platform for advanced genetic studies, high-throughput screening, and the creation of reliable cellular disease models.

CRISPR-Cas9↗

Site-specific gene integration by recombinase-mediated cassette exchange in anhydrobiotic Pv11 cells.

Pv11 cells, derived from Polypedilum vanderplanki, uniquely tolerate complete desiccation (anhydrobiosis). Although a CRISPR/Cas9-based precise integration method (CRIS-PITCh) has been developed for Pv11 cells, a CRISPR-free strategy that fixes both the genomic locus and transgene copy number has not yet been established. Here, we implement recombinase-mediated cassette exchange (RMCE) in Pv11 cells and generate master cell lines that retain anhydrobiosis following genetic engineering. We first evaluated the activity of multiple site-specific recombinases in Pv11 cells using a transient two-plasmid reporter assay. Flp, Cre, and Bxb1 recombinases all excised a test cassette and activated a green fluorescent protein (GFP) reporter, whereas phiC31 integrase mediated recombination at the DNA sequence level but did not induce reporter expression under our construct configuration. To enable genomic RMCE, we inserted an FRT/FRT3-landing pad (LP) into a previously identified genomic safe-harbor locus using CRIS-PITCh and isolated clonal master cell lines by single-cell sorting. Using the established master line, Flp-based RMCE achieved site-specific cassette exchange at the LP, producing HaloTag fluorescence and drug resistance upon successful exchange. In addition, the expected post-exchange sequence was confirmed by sequencing. We further established an all-in-one RMCE vector combining the Flp recombinase and donor cassette on a single plasmid. Together, these results demonstrate locus-defined, single-copy transgene integration in anhydrobiotic Pv11 cells via RMCE and provide a standardized, CRISPR-free workflow for routine genetic manipulation in this unique cell line. This workflow facilitates both fundamental research and applied biotechnological applications using desiccation-tolerant cells.

Anhydrobiosis↗

Barcoded mutant library enables high-throughput functional genomics in a filamentous fungus.

Advances in sequencing technology enabling rapid and inexpensive whole-genome sequencing highlight how few genes are functionally characterized. This problem is particularly acute in filamentous fungi, where even in the best studied organisms upward of half of genes are poorly characterized or unannotated. High-throughput tools to identify gene function exist for single-celled organisms, like yeast and bacteria. However, filamentous fungi present challenges to high-throughput gene characterization, including low transformation efficiency and multinucleate cells. Filamentous fungi are critical components of nutrient cycling in ecosystems, form symbioses with plants that improve nutrient uptake, and are devastating human, plant, and animal pathogens causing millions of deaths and substantial crop loss each year. Thus, it is critical to overcome challenges to rapid gene characterization in filamentous fungi. We generated a library of hundreds of millions of uniquely barcoded plasmids containing a broad host-range drug resistance marker for ectopic insertion into filamentous fungal genomes by Agrobacterium tumefaciens. We then optimized A. tumefaciens mediated transformation of the biocontrol agent Trichoderma atroviride and made an insertional mutagenesis library containing 83,311 barcoded insertions, disrupting 5,331 of 11,863 predicted genes. This library enables high-throughput screens to rapidly connect genotype to phenotype. Quantifying relative barcode abundance in the pooled library before and after exposure to experimental conditions identified candidate genes and recovered known pathway components in amino acid biosynthetic, fructose utilization, and xylose utilization pathways. This resource establishes a scalable platform for high-throughput functional genomics in filamentous fungi, enabling investigations of fungal biology to improve medical outcomes, biotechnology, and sustainable agriculture.

Genomics↗

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms↗

Epigenetic Reprogramming and Zygotic Genome Activation in Human Preimplantation Development: Mechanisms, Models, and Translational Prospects.

PURPOSE: Early human embryogenesis unfolds through a tightly coupled sequence of events-clearance of maternal transcripts, remodeling of parental chromatin, zygotic genome activation (ZGA), lineage segregation, implantation, and post-implantation patterning-accompanied by epigenetic reprogramming, including X-chromosome dosage compensation around the time of implantation. This review aims to synthesize recent advances in understanding this developmental program and to consider their implications for reproductive medicine. METHODS: I review recent literature on human early embryogenesis, with particular emphasis on findings enabled by single-cell genomics and stem-cell-based embryo modeling, and integrate these insights to identify human-specific features of early development. RESULTS: These approaches have made previously inaccessible aspects of human early embryogenesis experimentally tractable, revealing molecular and epigenetic features that distinguish human development from that of model organisms, including species-specific dynamics of ZGA, maternal transcript clearance, chromatin reprogramming, and X-chromosome dosage compensation. CONCLUSIONS: Advances in single-cell genomics and embryo modeling are transforming our understanding of human early embryogenesis. Building on these insights, while recognizing their current limitations, I propose a vision for improving reproductive medicine, including the potential for next-generation embryo selection strategies.

Journal Article↗

Generation and validation of a Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of disease-associated smooth muscle cell states.

BACKGROUND: Phenotypic modulation of vascular smooth muscle cells (VSMCs) is a hallmark of vascular remodeling and cardiovascular disease. Recent lineage-tracing and single-cell transcriptomic studies have identified secreted phosphoprotein 1 (SPP1) as a prominent marker associated with disease-associated VSMC states, particularly those linked to fibrotic remodeling and vascular calcification. However, the cellular origins and fate of SPP1-associated VSMC populations remain incompletely understood. METHODS AND RESULTS: We generated a novel Spp1-rSTOPr-Cre (Spp1Cre) knock-in mouse line in which Cre recombinase is expressed from the endogenous Spp1 locus following Dre-mediated excision of a rox-flanked transcriptional STOP cassette. Correct targeting of the knock-in allele was validated by internal, 5' junction, 3' junction, and long-range PCR analyses, as well as Sanger sequencing. To establish an intersectional lineage-tracing strategy, Spp1Cre mice were crossed with Myh11DreERT2 and Rosa26-RSR-LSL-tdTomato-LSL-eGFP reporter mice, enabling permanent labeling of VSMC-derived populations following activation of the endogenous Spp1 locus. Under physiological conditions, eGFP-positive cells were detected at low frequency within the vascular wall and were predominantly negative for the contractile markers ACTA2 and MYH11. As a proof-of-principle application, eGFP-positive cells markedly expanded within atherosclerotic lesions induced by AAV-PCSK9D377Y and high-fat diet feeding. These lineage-traced cells remained largely ACTA2- and MYH11-negative, consistent with a modulated phenotype. Notably, only a minority of eGFP-positive cells expressed SPP1 or fibronectin at the time of analysis, demonstrating the utility of permanent lineage tracing for tracking cells with a history of endogenous Spp1 activation during vascular remodeling. CONCLUSION: We report the generation and validation of a novel Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of VSMC-derived populations that have activated the endogenous Spp1 locus. This genetic resource provides a valuable platform for investigating the origin, fate, and phenotypic evolution of Spp1-associated VSMC populations during vascular remodeling and cardiovascular disease.

Animals↗

The current and future perspective of ChickenGTEx project and its applications in precision breeding.

The Chicken Genotype-Tissue Expression (ChickenGTEx) project was established to systematically characterize the regulatory landscape of the chicken genome and to accelerate the translation of functional genomics into precision breeding. By integrating whole-genome sequencing with multi-tissue transcriptomic profiling, ChickenGTEx provides a comprehensive atlas of gene expression regulation across diverse tissues and physiological systems. Current findings demonstrate that complex production traits are governed by coordinated regulatory networks rather than isolated loci, with substantial contributions from tissue-specific gene expression, structural variation, and genotype-by-sex interactions. Sex-dependent regulatory effects further refine the genetic architecture of metabolic, immune, and reproductive traits, highlighting the importance of incorporating sex as a biological variable in genomic analyses. Application of integrative omics frameworks within elite layer populations has revealed multilayer regulatory mechanisms underlying extended laying performance, feed efficiency, metabolic health, and eggshell quality. By partitioning phenotypic variance into genetic, regulatory, and host-microbiome components, these approaches move beyond association-based mapping toward causal inference and biological interpretation. Importantly, validated regulatory loci identified through ChickenGTEx and related analyses provide actionable markers for genomic selection and rational targets for precision genome modification. Looking forward, continued expansion of regulatory atlases, incorporation of single-cell and longitudinal data in diverse environmental conditions, and integration of functional annotation into breeding pipelines will further enhance prediction accuracy and sustainable genetic improvement. The ChickenGTEx project thus represents a foundational platform bridging functional genomics and practical poultry breeding.

Animals↗

From wild to domestic: Single-cell transcriptomic perspectives on hippocampal regulation and evolution.

How domestication shapes brain evolution remains an open question. In this study, we integrated single-nucleus RNA sequencing (snRNA-seq), population genomics, and machine learning to investigate the hippocampal evolution under domestication. Across-species comparisons revealed that hippocampal cell type profiles are largely conserved across vertebrate species, while supporting the presence of adult hippocampal neurogenesis in birds. We further found that domestication and selective breeding likely influence the cellular composition and molecular regulation of the hippocampus. Our findings provide cellular evidence supporting the hypothesis that domestication affects adult hippocampal neurogenesis. Additionally, we showed that genes associated with neural progenitor cells (NPC) states and cell-marker programs are enriched for signatures of selection. Many of these genes function as regulators of neurogenesis and pathways mediating stress and fear reduction. Specifically, we identified selection at the FKBP5 promoter that may influence its expression in the NPC lineage, potentially contributing to stress-response regulation during domestication. Collectively, these results suggest that domestication is associated with hippocampal remodeling as part of an adaptive response to human-managed environments. This study provides a cellular and genetic perspective on how domestication reshapes the brain and offers a basis for further investigation into the mechanisms of neural evolution within the context of microevolution.

Animals↗

Cell-type signatures of Alzheimer's disease shared across population groups.

Genomic studies at single-cell resolution have identified several cell types associated with clinical and pathological traits in Alzheimer's disease1-9, but have not examined associations that are shared across populations. To bridge this gap, here we use single-nucleus RNA sequencing and assay for transposase-accessible chromatin with sequencing to profile cortical and subcortical regions in post-mortem brain-tissue samples from Latin, white (excluding Latin) and African American (excluding Latin) individuals. Using discrete and continuous dissections of molecular programs, we identify cell-type-specific clusters associated with Alzheimer's disease in a region-specific manner across all three population groups, including microglial (GPNMB+ and CD74+ subgroups), astrocytic (SERPINH1+, CD44+ and WIF1+ subgroups) and neuronal (SST+ GABAergic and superficial-layer glutamatergic) signatures. We also report continuous gene-expression factors in astrocytes and oligodendrocytes that are not captured by discrete cluster assignments, but which show strong associations with disease phenotypes; these factors are enriched for genes associated with annotated functions such as lipid processing and neurotransmitter reuptake. Finally, we find that molecular programs reveal six distinct subgroups of individuals with cognitive impairment that span all three populations, are not captured by neuropathology, and are instead distinguished by molecular signatures that are not universally present but are nonetheless associated with ante-mortem impairment. Overall, our study identifies key cell types and gene programs implicated in Alzheimer's disease that are shared across population groups, and underscores how representative sampling can capture both shared signatures and disease heterogeneity, thereby enabling better prioritization of key cell types for further investigation.

Female↗

Integrated Genomic and Proteomic Analysis Reveals T-B Lymphocyte Signatures in the MYCN Driven "Immune Desert" of Specific Neuroblastoma Subtypes.

AIMS: This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high-risk neuroblastoma, elucidating key mechanisms underlying immune evasion. METHODS: We performed an integrated multi-omics analysis of bulk RNA-seq (n = 721), single-cell RNA-seq (n = 9), proteomic data (n = 49) and spatial transcriptomics (Visium, with external validation in melanoma). Analyses included unsupervised clustering, cell-cell communication inference, transcriptional regulatory network reconstruction, and spatial proximity assessment to map the immune landscape. RESULTS: A distinct molecular subtype (Class C), defined by MYCN amplification and poor prognosis, exhibited a comprehensive "immune desert" phenotype characterized by low immune scores and minimal leukocyte infiltration. Single-cell analysis confirmed significant depletion of T and B lymphocytes within the Class C TME. Dysregulated transcriptional networks were identified, including upregulation of REL and EOMES in T cells-with EOMES potentially driving exhaustion via regulation of Transient Receptor Potential (TRP) genes, and REL inhibition enhancing cytotoxic function in vitro. A unique immunosuppressive B-cell subset (B7) engaged in enhanced crosstalk with exhausted T cells and harbored a MYC-centered network linked to cell cycle dysregulation and poor survival. Spatial transcriptomics revealed significant proximity between B7-active regions and Treg/exhaustion-enriched areas, externally validated in melanoma. Proteomic data validated elevated REL expression in MYCN-amplified tumors. CONCLUSION: This work delineates the immunosuppressive architecture of MYCN-driven neuroblastoma, revealing novel regulatory nodes within specific lymphocyte compartments. Integrating single-cell, spatial, and proteomic evidence, we propose REL inhibition as a therapeutic candidate, the EOMES/TRP axis as a bioinformatically supported hypothesis, and the B7/MYC hub as a hypothesis supported by transcriptomic and spatial evidence.

Humans↗

Genomic characterization of a hypervirulent Aeromonas veronii NN0115 from Nile tilapia and head kidney transcriptome of infected fish reveals B-cell-dominated immune response with specific immunoglobulin downregulation.

Aeromonas veronii is a pathogen of multiple fish species, yet systematic understanding of its infection in Nile tilapia (Oreochromis niloticus) remains limited. A dominant strain, NN0115, was isolated from a natural outbreak and identified as A. veronii by 16S rRNA and whole-genome average nucleotide identity (ANI, 96.33%). Experimental infection revealed high virulence (LD50 = 3.41 × 106 CFU/mL, equivalent to 8.53 × 104 CFU/fish). The genome is 4.58 Mb (58.57% GC) and encodes 4216 proteins. Virulence factor analysis identified 1253 genes, dominated by motility-related (264) and immune modulation (208) factors. Genomic island GI2 harbors 7 virulence genes and two dual-function resistance-virulence genes. The strain is resistant to 9 of 25 agents tested but carries three RND efflux pump genes whose predicted resistance was not phenotypically observed. The head kidney transcriptome of tilapia at 24 h post-bacterial infection identified 773 differentially expressed genes; among them, 57 were immunoglobulin (Ig) genes, and 56 were down-regulated. Integration of published single-cell transcriptomic data showed that non-Ig B-cell marker genes were down-regulated by 32%, whereas Ig genes were reduced by 63%, indicating selective transcriptional suppression of Ig genes rather than a general decrease in B-cell transcriptional activity. Together, this study provides a comprehensive characterization of a highly virulent A. veronii from Nile tilapia and reveals that selective downregulation of B-cell Ig genes is the dominant transcriptional feature of the host head kidney response.

Animals↗

Multimodal computational framework resolves B cell maturation in autoimmunity and ageing.

Identification of the origin of pathogenic immune cells is crucial for therapeutic interventions and diagnosis but pseudotime methods struggle to trace immune cells accurately. Current trajectory inference methods for B cell development and response in health and disease either ignore or underutilize antigen receptor sequence information, limiting their ability to resolve developmental pathways, particularly for pathogenic populations. Widely used methods such as Monocle 3 reconstruct developmental paths from transcriptomic similarity alone, discarding the features from immune receptors. Dandelion has combined the immune receptor features with transcriptomics but it struggles to simulate the trajectory path of B cells. Here we present ClonoTrace, a computational framework that integrates BCR sequence features with transcriptomic trajectory inference through gated fusion of multimodal embeddings. In fetal B cell development and germinal centre development, ClonoTrace demonstrates closer concordance with the canonical reference ordering than Monocle 3 and Dandelion. Applied to systemic lupus erythematosus, ClonoTrace indicates a memory B cell extrafollicular maturation route alongside the naïve B cell route, accompanied by induction of ZEB2 with a concomitant decline of BACH2 along the trajectory, as a candidate alternative route to pathogenic double negative 2 B cells (DN2) in systemic lupus erythematosus (SLE) patients. In healthy ageing, ClonoTrace resolved three candidate age-related B cell maturation routes, from naïve, IgM+ memory and switched-memory B cells, each passing through a DN2-associated transcriptional state that is ordered before age-associated B cells along the inferred trajectory. ClonoTrace's fate probability algorithm indicated that IgM+ memory B cell to ABC transition as the leading candidate age-associated transition, which may be distinct from SLE DN2 maturation. ClonoTrace provides a generalizable framework for receptor-informed trajectory inference, describing candidate developmental routes of pathogenic B cell populations in autoimmunity and ageing.

Humans↗

Decoding the landscape of cell-type-specific co-expressed transcription factors in soybean.

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its protein-coding genes. Here, we present Tabula Glycine max, a soybean single-cell resolution transcriptome atlas. This atlas comprises single-nucleus RNA-sequencing data from ten different G. max organs and morphological structures constituting the entire soybean plant. These nuclei are grouped into 156 different clusters based on their transcriptomic profiles. The breadth of various organs, tissues and cell types represented in Tabula Glycine max reveals that the pattern of co-expressed transcription factor genes is sufficient to define most cell types based on their function and organ of origin. Defining cell-type-specific co-expressed transcription factor genes offers a new perspective to engineer cell-type-specific programmes and enhance the biology of unique soybean cell types. This cellular resolution and breadth make the Tabula Glycine max an exceptional resource for the plant and soybean communities.

Journal Article↗

VINE-seq and MultiVINE-seq for single-nucleus and multiome profiling of the brain vasculature.

The human cerebrovasculature is a critical yet historically understudied component of neurological health. Dysfunction of the diverse endothelial, mural, and perivascular cells that comprise cerebral vessels is central to diseases ranging from stroke to Alzheimer's disease. However, characterizing these cell populations at a molecular level has proven exceptionally challenging. Encased within a robust basement membrane, vascular cells resist standard dissociation methods, leading to their systematic depletion and underrepresentation in existing single-nucleus genomic atlases. This has created a major blind spot in neuroscience. To overcome this barrier, we developed vessel isolation and nucleus extraction for sequencing (VINE-seq) and its advanced iteration, MultiVINE-seq. The protocol provides a robust, reproducible workflow for the enrichment and high-resolution profiling of vascular, perivascular, and immune cells from fresh or frozen human and mouse brain tissue. First, intact vessels (predominantly capillaries and small arterioles/venules, 100 µm in diameter) are isolated from homogenized brain tissue via dextran-based density-gradient centrifugation, separating the vascular pellet from myelin and the parenchymal fraction. Second, the collected vessels are rigorously washed over a cell strainer to remove trapped contaminants. A critical innovation lies in the third stage: the optimized extraction of nuclei from purified vessels using enzymatic digestion. After extraction, the protocol uses fluorescence-activated cell sorting (FACS) to ensure collection of high-purity nuclei suitable for widely used droplet-based sequencing platforms (e.g., 10x Genomics single cell 3' or multiome). This protocol requires 4-5 h to complete and can be carried out by researchers with single-cell and flow cytometry training.

Journal Article↗

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗

Single-nucleus profiling of postmortem diffuse midline gliomas identifies mitochondrial biogenesis as a resistance mechanism to imipridone therapy.

BACKGROUND: Imipridone ONC201 is the first FDA-approved therapy for H3K27-altered diffuse midline glioma; however, clinical responses remain limited. Defining tumor-intrinsic determinants and microenvironmental, extrinsic factors that shape sensitivity or resistance to imipridones will identify actionable therapeutic opportunities and inform improved clinical strategies. METHODS: To identify mechanisms of imipridone resistance, we obtained postmortem brain tissue from DMG patients who had received imipridones and/or standard care. Single-nucleus RNA and open-chromatin sequencing were performed on N = 22 cases. Immunofluorescence-based myeloid phenotyping was performed on N = 46 cases. Mitochondrial copy-number analysis was performed on N = 19 cases. Validation of imipridone sensitivity, its effect on mitochondrial density, and its synergy with inhibition of mitochondrial biogenesis were assessed in DMG primary cells. RESULTS: We established a single-cell RNA/open-chromatin atlas from postmortem DMG cases and found imipridone treatment resulting in regressed mesenchymal transition, reduced myeloid-derived suppressive cells, and reversed aberrant H3K27-altered enhancer activity. Resistant tumors showed increased mitochondrial density, turnover, and membrane potential. Mitochondrial biogenesis and PPARGC1A emerged as resistance biomarkers and actionable targets. CONCLUSIONS: These studies implicate mitochondrial biogenesis as a biomarker of imipridone resistance and a focus for the development of combinatorial strategies to provide effective therapeutic options for a challenging pediatric brain tumor.

Humans↗

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗

Amino acid reprogramming and biofilm-specific tricarboxylate transporters in PET-degrading Piscinibacter sakaiensis.

Plastic-degrading bacteria predominantly colonize polymer surfaces as biofilms, yet it remains unclear whether the biofilm phenotype contributes to metabolism beyond retaining extracellular enzymes. Here, we combine population-level RNA-sequencing across three conditions-biofilm cells on polyethylene terephthalate (PET), planktonic cells incubated with PET, and planktonic cells on maltose-with single-cell Raman spectroscopy to characterize the PET response of Piscinibacter sakaiensis (formerly Ideonella sakaiensis). This integrated approach reveals two metabolically distinct response layers. A carbon-source-driven response shared by all PET-exposed cells is dominated by a broad amino acid reprogramming, led by upregulation of branched-chain amino acid transport genes, enhanced serine biosynthesis, and reduced chemotaxis. A biofilm-specific layer selectively induces tripartite tricarboxylate transporter genes from three distinct genomic loci. This transcriptional feature is accompanied by a single-cell phenotype consistent with a protein-rich and saturated membrane. These results suggest that biofilm formation is not limited to enzyme retention but is associated with selective activation of transport systems, consistent with a putative role in capturing PET-derived intermediates at the polymer interface. This two-layer model separates general metabolic adaptation to PET from biofilm-specific functions and provides a framework for understanding how surface-associated bacterial physiology contributes to plastic degradation.IMPORTANCEPolyethylene terephthalate (PET) degradation in natural and engineered environments is largely mediated by surface-attached microbial communities, yet the physiological role of biofilm state during plastic degradation remains poorly understood. Using the model PET degrader Piscinibacter sakaiensis, we show that biofilm-associated cells are not simply retained near the polymer surface but exhibit a distinct metabolic program characterized by selective induction of tripartite tricarboxylate transporters. In contrast, extensive amino acid reprogramming occurs in both biofilm and planktonic PET-exposed cells, indicating that it is driven by carbon source rather than surface attachment. These findings reveal that PET degradation involves two separable physiological layers: a general metabolic response to PET-derived carbon shared across cell phenotypes, and a biofilm-specific transport response potentially linked to substrate capture at the plastic interface. This work advances our understanding of how microbial physiology is organized during plastic biodegradation and identifies transport processes as previously unrecognized components of PET-degrading biofilms.

PET biodegradation↗