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PubMed2026

Selective saccular plasticity under microgravity links peripheral transcriptomic remodeling to postflight vestibular dysfunction.

Long-duration exposure to microgravity disrupts human balance and spatial orientation, yet the molecular mechanisms underlying vestibular adaptation to spaceflight remain poorly understood. Here, we tested the hypothesis that the saccule, the primary gravity-sensing otolith organ, undergoes selective remodeling during spaceflight and contributes to transient postflight postural instability. Using a cross-species approach, we combined transcriptomic analysis of mouse otolith organs with physiological assessments in astronauts. Laser microdissection-based RNA sequencing of mouse otolith sensory epithelia after a 35-d spaceflight revealed pronounced, organ-specific transcriptomic remodeling in the saccule, whereas the utricle remained stable. Principal component and clustering analyses demonstrated that the saccular transcriptome shifted toward an utricle-like profile under microgravity, accompanied by changes in genes related to synaptic and neuronal function. Promoter motif analysis identified NFAT-associated transcriptional networks, suggesting Ca2+-dependent regulation of synaptic plasticity as a potential molecular substrate of gravity-dependent adaptation. In parallel, vestibular testing in astronauts following long-duration missions (157 to 328 d) revealed selective attenuation of saccule-mediated cervical vestibular-evoked myogenic potentials and increased postural sway immediately after return to Earth, while utricle-mediated responses and semicircular canal function were preserved. Both saccular function and postural stability recovered within approximately 10 d. Notably, early postflight postural instability was partially mitigated by noisy galvanic vestibular stimulation, consistent with stochastic resonance-mediated sensory enhancement. Together, these findings identify the saccule as a plastic gravity sensor and establish a mechanistic link between peripheral molecular remodeling and functional balance deficits after spaceflight, providing a framework for developing countermeasures to facilitate vestibular readaptation during human space exploration.

Animals↗
PubMed2025

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans↗
PubMed2002

Genome-wide transcriptional profiling of the Bacillus subtilis cold-shock response.

The transcriptome of Bacillus subtilis was analysed at different time points (30, 60 and 90 min) after a temperature downshift from 37 to 18 degrees C using DNA macroarrays. This approach allowed the identification of around 50 genes exhibiting an increased mRNA level and around 50 genes exhibiting a decreased mRNA level under cold-shock conditions. Many of the repressed genes encode enzymes involved in the biosynthesis of amino acids, nucleotides and coenzymes, indicating metabolic adaptation of the cells to the decreased growth rate at the lower temperature. The strongest cold-inducible gene encodes fatty acid desaturase, which forms unsaturated fatty acids from saturated phospholipid precursors, thereby increasing membrane fluidity. The cold-shock-induced increase of mRNA levels of the classical cold-shock genes cspB, cspC and cspD could be verified. Furthermore, besides many genes encoding proteins of unknown function, some genes encoding ribosomal proteins were transcriptionally up-regulated, which points to an adaptive reprogramming of the ribosomes under cold-shock conditions. Interestingly, the amount of mRNA specified by the operon ptb-bcd-buk-lpd-bkdA1-bkdA2-bkdB, which encodes enzymes involved in degradation of branched-chain amino acids, also increases after a temperature downshift. As cells utilize the isoleucine and valine degradation intermediates alpha-methylbutyryl-CoA and isobutyryl-CoA for synthesis of branched-chain fatty acids, this finding reflects the adaptation of membrane lipid composition, ensuring the maintenance of appropriate membrane fluidity at low temperatures. The results of the DNA array analyses were verified for several selected genes by RNA slot-blot analysis and compared with two-dimensional PAGE analyses.

Bacillus subtilis↗
PubMed2003

Integration of proteomics and genomics in platelets: a profile of platelet proteins and platelet-specific genes.

Platelets, while anucleate, contain RNA, some of which is translated into protein upon activation. Hypothesising that the platelet proteome is reflected in the transcriptome, we identified 82 proteins secreted from activated platelets and compared these, as well as published proteomic data, to the transcriptional profile. We also compared the transcriptome of platelets to other tissues to identify platelet-specific genes and used ontology to determine gene categories over-represented in platelets. RNA was isolated from highly pure platelet preparations for hybridization to Affymetrix oligonucleotide arrays. We identified 2,928 distinct messages as being present in platelets. The platelet transcriptome was compared with the proteome by relating both to UniGene clusters. Platelet proteomic data correlated well with the transcriptome, with 69% of secreted proteins detectable at the mRNA level, and similar concordance was obtained using two published datasets. While many of the most abundant mRNAs are for known platelet proteins, messages were detected for proteins not previously reported in platelets. Some of these may represent residual megakaryocyte messages; however, proteomic analysis confirmed the expression of many previously unreported genes in platelets. Transcripts for well-described platelet proteins are among the most platelet-specific messages. Ontological categories related to signal transduction, receptors, ion channels, and membranes are over-represented in platelets, while categories involved in protein synthesis are depleted. Despite the absence of gene transcription, the platelet proteome is mirrored in the transcriptome. Conversely, transcriptional analysis predicts the presence of novel proteins in the platelet. Transcriptional analysis is relevant to platelet biology, providing insights into platelet function and the mechanisms of platelet disorders.

Blood Platelets↗
PubMed2026

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays↗
PubMed2026

Ten quick tips for spatial transcriptomics analysis.

Spatial transcriptomics (ST) enables genome-wide gene expression profiling while retaining spatial context within tissue sections. Since the foundational work by Ståhl et al. in 2016, the field has expanded rapidly, with diverse platforms now spanning sequencing-based (e.g., Visium, Visium HD, Slide-seq, Stereo-seq, and Seq-Scope) and imaging-based (e.g., MERFISH, Xenium, and CosMx SMI) approaches. The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers. Here, we present ten quick tips spanning the entire ST research workflow: whether ST suits a given biological question, how to select a platform aligned with study objectives, how to understand and process ST data, and which software tools to employ for analysis and visualization. We further discuss interpreting spatial patterns in biological context, integrating complementary modalities such as single-cell RNA sequencing and spatial proteomics, and leveraging public datasets and sharing results. Finally, we highlight current limitations of ST, particularly the challenge of reconstructing three-dimensional tissue architecture from serial tissue sections. This review provides biologists, bioinformaticians, and clinician-scientists with a concise, platform-neutral roadmap for incorporating ST into research, from experimental design to biological discovery.

Spatial Transcriptomics↗
PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗
PubMed2026

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects function. However, the reliability of current benchmarks of spatially aware clustering (SAC) methods is undermined by their narrow focus on Visium and brain tissue datasets and the incorrect interpretation of manual annotation as ground truth. Here we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration and metric evaluation, enabling rapid inclusion of new methods and datasets. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods and shows that anatomical labels commonly used as ground truths are often biased, error prone and unsuitable for benchmarking. Rather than ranking methods, we propose a consensus-guided workflow where descriptive spatial metrics highlight high-entropy regions of method disagreement, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual SAC methods and manual annotations, highlighting the need for iterative, expert-in-the-loop evaluation.

Benchmarking↗
PubMed2026

Identification of compounds that repress DUX4 expression in facioscapulohumeral muscular dystrophy.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by epigenetic dysregulation of the disease locus, leading to pathogenic misexpression of DUX4 in skeletal muscle. Thus, most FSHD therapeutic approaches target DUX4. Our previous study identified the chromatin remodeling factor BAZ1A (bromodomain adjacent to zinc finger domain protein 1A) as a promising target for therapeutic development. Here we used an artificial intelligence-based screening pipeline to identify molecules predicted to bind the BAZ1A bromodomain, and validated hit compounds using FSHD-specific assays in FSHD myocytes. One compound, termed C06, emerged as a potent repressor of DUX4 and DUX4 target gene expression. Interestingly, while C06 exhibited binding to BAZ1A in vitro, it can also inhibit multiple kinases, including p38α, an upstream activator of DUX4. Despite this, at low doses C06 was an equally effective and more specific repressor of DUX4 than losmapimod, which is a robust and specific p38 inhibitor. At low concentrations, C06 returns the DUX4 gene expression signature to a healthier profile without major effects on the muscle transcriptome. Thus, C06 is a useful tool for potent and specific DUX4 suppression, and a viable candidate for further development. Our results highlight both the utility and limitations of AI for targeted drug discovery, and the importance of using an FSHD-specific functional screening strategy for selecting relevant candidates.

Muscular Dystrophy, Facioscapulohumeral↗
PubMed2002

The Chlamydomonas reinhardtii organellar genomes respond transcriptionally and post-transcriptionally to abiotic stimuli.

The Chlamydomonas reinhardtii plastid and mitochondrial transcriptomes were surveyed for changes in RNA profiles resulting from growth in 12 culture conditions representing 8 abiotic stimuli. Organellar RNA abundance exhibited marked changes during nutrient stress and exposure to UV light, as revealed by both RNA gel blot and DNA microarray analyses. Of particular note were large increases in tufA and clpP transcript abundance during nutrient limitation. Phosphate and sulfur limitation resulted in the most global, yet opposite, effects on organellar RNA abundance, changes that were dissected further using run-on transcription assays. Removal of sulfate from the culture medium, which is known to reduce photosynthesis, resulted in 2-fold to 10-fold decreases in transcription rates, which were reflected in lower RNA abundance. The decrease in transcriptional activity was completely reversible and recovered to twice the control level after sulfate replenishment. Conversely, phosphate limitation resulted in a twofold to threefold increase in RNA abundance that was found to be a post-transcriptional effect, because it could be accounted for by increased RNA stability. This finding is consistent with the known metabolic slowdown under phosphate stress. Additionally, inhibitor studies suggested that unlike those in higher plants, Chlamydomonas chloroplasts lack a nucleus-encoded plastid RNA polymerase. The apparently single type of polymerase could contribute to the rapid and genome-wide transcriptional responses observed within the chloroplast.

Animals↗
PubMedDate not supplied

The essential similarity of TGFbeta and activin receptor transcriptional responses in cancer cells.

The binding of activin and TGFbeta to their respective receptors initiates signals that are carried by common intermediates (Smad proteins) to induce transcriptional activation of downstream genes. Mutations in tumors indicate that both receptor types convey tumorsuppressive signals, among other biologic roles, but their respective sets of transcriptional targets (transcriptomes) and the shared degree of transcriptome similarity are not well explored in these cells. Transcriptome changes were analyzed by gene expression profiling after expression of constitutively active activin type I (ALK4m) and TGFbeta type I (ALK5m) receptors and by variation of Smad4 expression in cancer cells. Eleven of 15 previously reported TGFbeta downstream genes were confirmed to be responsive to TGFb and activin receptors in cancer cells. Expression profiling detected eight of these 11, as well as 13 new Smad4-dependent transcripts. Although Smad4-dependent CDKN1A/p21 induction represents the sole known effector of TGFbeta and activin tumor-suppressor effects, many downstream genes have not yet been evaluated for a suppressive role. A high similarity of TGFbeta and activin responses among the known and new transcriptional target genes indicated an essential redundancy of the two related inputs. This similarity helps relate the mutations seen in both receptor systems and their Smad mediators in human cancers.

Activin Receptors, Type I↗
PubMed2026

Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.

Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.

Journal Article↗
PubMed2002

A quantitative and validated SAGE transcriptome reference for adult mouse heart.

Transcriptome comparisons facilitate the identification of developmental, aging, and disease-related genes. To quantify the functionally active genome of adult C57BL/6 mouse heart (AMH), we used serial analysis of gene expression (SAGE) to sequence a total of 88,860 tags or 23,941 unique tags. Over 66% of the unique tags matched either known genes or ESTs. Mitochondrial transcripts accounted for 18.7% of the total transcripts, whereas sarcomeric proteins accounted for 3.2% of all tags. After comparison of AMH expression profiles obtained by SAGE and cDNA arrays, we observed numerous quantitative discrepancies (for example: arrays, mt-Co1 > mt-Co2 > mt-Co3; SAGE, mt-Co1 >> mt-Co3 >or= mt-Co2). We carried out quantitative PCR analyses as an independent test of transcript abundance and determined that SAGE yielded quantitatively reliable data. These SAGE results thus represent the first quantitative expression profile of AMH and serve as a reliable transcriptome reference to identify dynamic changes in cardiac gene expression.

Animals↗
PubMed2026

Transcriptomic signatures of mind-body transformations therapy in breast cancer: Downregulation of the interferon signaling pathway.

BACKGROUND: Growing evidence has shown that Mind-Body Transformations-Therapies (MBT-T) are able to modulate chronic inflammation, a well-known driver of cancer progression and drug resistance. In our previous work, we showed that a specific MBT-T protocol was able to reduce the release of various pro-inflammatory cytokines and chemokines in the sera of patients with breast cancer that completed adjuvant chemotherapy. Despite these clinical observations, the underlying molecular pathways through which this therapy exerts its effects remain unclear. This study aims to address this gap by characterizing genome-wide transcriptional profiles in patients undergoing a novel MBT-T protocol. METHODS: In this proof-of-concept study, patients with breast cancer were randomized into two groups: Group 1 (CTL), receiving standard follow-up care, and Group 2 (MBT-T), receiving standard follow-up plus biweekly MBT-T for 4 months. Blood samples were collected at different timepoints during the treatment. After RNA extraction from whole blood, gene expression was analyzed on twenty-one patients (CTL, n = 7; MBT-T, n = 14) using the nCounter® Human Inflammation Panel (249 genes). RESULTS: Patients undergoing MBT-T showed a significant global downregulation of inflammatory gene expression compared to the control group. The analysis revealed that the Interferon (IFN) signaling pathway was the most significantly suppressed, by downregulation of key genes such as IFIT1, IFIT3, IFI44, MX1 and OASL in the MBT-T group. CONCLUSIONS: MBT-T acts as a biological modulator capable of downregulating key inflammatory pathways at the transcriptional level. These findings provide a genomic basis for the clinical benefits of mind-body interventions in oncology.

Breast cancer↗
PubMed2025

Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.

The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a novel unsupervised machine learning approach (COFE) that can use single high-throughput omics samples (without time labels) from individuals to reconstruct circadian rhythms across cohorts. COFE can simultaneously assign time labels to samples and identify rhythmic data features used for temporal reconstruction, while also detecting invalid orderings. With COFE, we discovered widespread de novo circadian gene expression rhythms in 11 different human adenocarcinomas using data from The Cancer Genome Atlas (TCGA) database. The arrangement of peak times of core clock gene expression was conserved across cancers and resembled a healthy functional clock except for the mistiming of a few key genes. Moreover, rhythms in the transcriptome were strongly associated with the cancer-relevant proteome. The rhythmic genes and proteins common to all cancers were involved in metabolism and the cell cycle. Although these rhythms were synchronized with the cell cycle in many cancers, they were uncoupled with clocks in healthy matched tissue. The targets of most of FDA-approved and potential anti-cancer drugs were rhythmic in tumor tissue with different amplitudes and peak times. These findings emphasize the utility of considering "time" in cancer therapy, and suggest a focus on clocks in healthy tissue rather than free-running clocks in cancer tissue. Our approach thus creates new opportunities to repurpose data without time labels to study circadian rhythms.

Humans↗
PubMed2026

Decoding regional keratinization in human oral mucosa through high-resolution spatial transcriptomics.

Oral mucosa exhibits region-specific keratinization, essential for periodontal health, yet the spatial and molecular mechanisms driving these differences remain poorly understood. This study aimed to generate a high-resolution spatial transcriptomic atlas of the human oral mucosa around the mucogingival junction, to reveal stromal-epithelial interactions, that distinguish keratinized from non-keratinized programs. Formalin-fixed paraffin-embedded specimens from the mucogingival junction area of two healthy donors were analyzed with the 10 × Genomics Visium HD platform, yielding two keratinized and two non-keratinized regions. Spatial clustering, pseudotime trajectory inference, cell-type integration with a single-cell reference, and ligand-receptor network analysis were applied to delineate epithelial and stromal compartments. Sixteen reproducible clusters, recapitulating tissue architecture, were identified and revealed distinct transcriptional signatures, distinguishing gingiva from lining mucosa. Pseudotime analysis revealed bifurcating epithelial lineages, originating from a shared basal progenitor layer into keratinized and non-keratinized programs. Gingival keratinization was driven by stromal collagen ligands (COL1A1, COL1A2, COL6A1, COL6A2) engaging epithelial receptors (CD44, SDC1), further reinforced within the epithelium by desmosomal adhesion via DSG1-DSC2/3. Gingival keratinization emerges from integrated stromal collagen signaling and epithelial adhesion. This spatially resolved framework advances understanding of oral mucosal specialization and provides a foundation for biologically guided regenerative therapies.

Humans↗
PubMed2026

Longitudinal multiorgan transcriptomic atlas of salt-induced hypertension.

High dietary salt intake elevates blood pressure and drives multiorgan damage. However, the molecular programs underlying progressive organ injury remain poorly defined. Here, we present a longitudinal multiorgan transcriptomic atlas of salt-induced hypertensive injury. We profiled kidney cortex, kidney medulla, heart, and liver across 4 stages, spanning early hypertension to advanced pathology in Dahl salt-sensitive rats. We identified dynamic and tissue-specific molecular trajectories, including a shared early proliferative response that converges on proinflammatory and fibrotic remodeling. Notably, we uncovered compartment-specific renal responses, showing that the cortex and medulla, despite their proximity, follow distinct molecular trajectories during disease progression. We further identified 79 stage- and tissue-specific transcription factors that drive gene expression dynamics in salt-induced hypertensive injury. Integration with human genome-wide association studies revealed conserved pathways in endocrine signaling, ion transport, lipid metabolism, and detoxification, establishing cross-species relevance and highlighting mechanistic targets of clinical importance. Compound-transcriptome analysis revealed stage- and organ-specific therapeutic opportunities, prioritizing kinase and epigenetic modulators as candidates to rebalance maladaptive gene programs. Overall, this study provides a resource for understanding molecular mechanisms from early salt-induced hypertension to tissue-specific injury and underscores the need for precision interventions.

Animals↗