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PubMed2026

Sexually dimorphic expression and hormonal responsiveness of steroidogenic Cyp genes during gonadal differentiation in mandarin fish.

Steroid hormones play a pivotal role in fish sex differentiation, yet the dynamic expression patterns of key steroidogenic enzymes during this process remain incompletely characterized. Here, we combined genome-wide identification, time series transcriptomes spanning gonadal development (5-360 days post-hatch), and multiple hormone treatment experiments (17α-methyltestosterone, estrone, and etonogestrel) to investigate the Cyp11, Cyp17, Cyp19, and Cyp21 subfamilies in mandarin fish (Siniperca chuatsi). Seven steroidogenic Cyp genes were identified, showing teleost-specific expansion, with one duplicated pair (cyp17a2 and cyp2u1) exhibiting strong purifying selection. Expression profiling revealed pronounced sexually dimorphic and stage-specific patterns: During female differentiation (20-30 days), cyp19a1a and associated genes were highly expressed, coinciding with ovarian differentiation; during male differentiation (30-60 days), cyp17a2 and related genes were upregulated, aligning with testicular development. Exogenous hormone treatments further demonstrated that these genes are dynamically responsive: cyp19a1a and cyp17a2 were highly responsive to androgenic and progestogenic treatments, and their expression changes correlated closely with gonadal sex reversal phenotypes observed histologically. Collectively, this study provides a comprehensive expression atlas of steroidogenic Cyp genes during gonadal differentiation and identifies key hormonally responsive candidates for sex control in aquaculture.

Animals↗

PubMed2004

Responses of the Rhodobacter sphaeroides transcriptome to blue light under semiaerobic conditions.

Exposure to blue light of the facultative phototrophic proteobacterium Rhodobacter sphaeroides grown semiaerobically results in repression of the puc and puf operons involved in photosystem formation. To reveal the genome-wide effects of blue light on gene expression and the underlying photosensory mechanisms, transcriptome profiles of R. sphaeroides during blue-light irradiation (for 5 to 135 min) were analyzed. Expression of most photosystem genes was repressed upon irradiation. Downregulation of photosystem development may be used to prevent photooxidative damage occurring when the photosystem, oxygen, and high-intensity light are present simultaneously. The photoreceptor of the BLUF-domain family, AppA, which belongs to the AppA-PpsR antirepressor-repressor system, is essential for maintenance of repression upon prolonged irradiation (S. Braatsch et al., Mol. Microbiol. 45:827-836, 2002). Transcriptome data suggest that the onset of repression is also mediated by the AppA-PpsR system, albeit via an apparently different sensory mechanism. Expression of several genes, whose products may participate in photooxidative damage defense, including deoxypyrimidine photolyase, glutathione peroxidase, and quinol oxidoreductases, was increased. Among the genes upregulated were genes encoding two sigma factors: sigmaE and sigma38. The consensus promoter sequences for these sigma factors were predicted in the upstream sequences of numerous upregulated genes, suggesting that coordinated action of sigmaE and sigma38 is responsible for the upregulation. Based on the dynamics of upregulation, the anti-sigmaE factor ChrR or its putative upstream partner is proposed to be the primary sensor. The identified transcriptome responses provided a framework for deciphering blue-light-dependent signal transduction pathways in R. sphaeroides.

Bacterial Proteins↗

PubMed2025

De novo clustering of large long-read transcriptome datasets with isONclust3.

MOTIVATION: Long-read sequencing techniques can sequence transcripts from end to end, greatly improving our ability to study the transcription process. Although there are several well-established tools for long-read transcriptome analysis, most are reference-based. This limits the analysis of organisms without high-quality reference genomes and samples or genes with high variability (e.g. cancer samples or some gene families). In such settings, analysis using a reference-free method is favorable. The computational problem of clustering long reads by region of common origin is well-established for reference-free transcriptome analysis pipelines. Such clustering enables large datasets to be split roughly by gene family and, therefore, an independent analysis of each cluster. There exist tools for this. However, none of those tools can efficiently process the large amount of reads that are now generated by long-read sequencing technologies. RESULTS: We present isONclust3, an improved algorithm over isONclust and isONclust2, to cluster massive long-read transcriptome datasets into gene families. Like isONclust, isONclust3 represents each cluster with a set of minimizers. However, unlike other approaches, isONclust3 dynamically updates the cluster representation during clustering by adding high-confidence minimizers from new reads assigned to the cluster and employs an iterative cluster-merging step. We show that isONclust3 yields results with higher or comparable quality to state-of-the-art algorithms but is 10-100 times faster on large datasets. Also, using a 256 Gb computing node, isONclust3 was the only tool that could cluster 37 million PacBio reads, which is a typical throughput of the recent PacBio Revio sequencing machine. AVAILABILITY AND IMPLEMENTATION: https://github.com/aljpetri/isONclust3.

Algorithms↗

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↗

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↗

PubMed2026

Optics-free spatial genomics for mapping mammalian brain aging by IRISeq.

Spatial transcriptomics has emerged as a transformative approach for in situ mapping of cellular heterogeneity and interactions, yet existing methods often compromise throughput, cost and tissue coverage. Here we introduce Imaging Reconstruction using Indexed Sequencing (IRISeq): an optics-free, cost-effective platform that leverages spatial interaction mapping by indexed sequencing to profile tissues at adjustable sizes and resolutions (5-50 µm). We applied IRISeq to map gene expression across more than 70 coronal sections from both adult and aged mouse brains, including wild-type and two lymphocyte-deficient models (Rag1 and Prkdc mutants) and generated more than 460,000 spatial transcriptome profiles. Our integrated analysis with 783,264 single-cell transcriptomes revealed region-specific aging signatures that are lymphocyte dependent, notably a downregulation of interferon signaling and inflammation in ventricular regions upon lymphocyte depletion, alongside mutant-specific upregulation of senescence pathways. Furthermore, lymphocyte deficiency was linked to preserved abundance of ependymal cells that line the brain's ventricles and to distinct microglial state dynamics, highlighting a key role for lymphocytes in driving inflammatory processes during brain aging. Overall, IRISeq provides a high-throughput and cost-effective solution for spatially resolved transcriptomic profiling, opening new avenues for elucidating region-specific cellular mechanisms underlying aging and identifying potential therapeutic targets to preserve brain homeostasis.

Animals↗

PubMed2025

Multi-omics analyses reveal DjTcf4 critical for proper timing of differentiation in planarian regeneration.

The blastema is key to forming complete tissues in regenerating Dugesia japonica (D. japonica). However, the dynamic changes in cellular compositions and transcription landscapes in blastema during regeneration are understudied. Here, through genome reannotation, 3D spatial transcriptome construction, single-cell RNA sequencing (scRNA-seq), and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) analyses of changes in gene expression and chromatin structures, we delineate key transcription factors regulating the developmental trajectories of major cell clusters in the regenerating head. Importantly, we find that the T cell factor 4 (DjTcf4)-positive cells highly accumulate at wound areas, and its gene network is critical for the proper timing of development during regeneration in multiple progenitor cells. Depletion of DjTcf4 and its target genes leads to singular eye and/or dull tail phenotypes and delays regeneration. Taken together, we build multi-omics atlases in D. japonica and reveal the noncanonical function of the DjTcf4 network in developmental pattern formation, laying a foundation for studies of regeneration in D. japonica.

Animals↗

PubMed2004

Gene expression analyzed by high-resolution state array analysis and quantitative proteomics: response of yeast to mating pheromone.

The transcriptome provides the database from which a cell assembles its collection of proteins. Translation of individual mRNA species into their encoded proteins is regulated, producing discrepancies between mRNA and protein levels. Using a new modeling approach to data analysis, a striking diversity is revealed in association of the transcriptome with the translational machinery. Each mRNA has its own pattern of ribosome loading, a circumstance that provides an extraordinary dynamic range of regulation, above and beyond actual transcript levels. Using this approach together with quantitative proteomics, we explored the immediate changes in gene expression in response to activation of a mitogen-activated protein kinase pathway in yeast by mating pheromone. Interestingly, in 26% of those transcripts where the predicted protein synthesis rate changed by at least 3-fold, more than half of these changes resulted from altered translational efficiencies. These observations underscore that analysis of transcript level, albeit extremely important, is insufficient by itself to describe completely the phenotypes of cells under different conditions.

Computational Biology↗

PubMed2025

Dynamic allelic expression in mouse mammary glands across the adult developmental cycle.

The mammary gland, which primarily develops postnatally, undergoes significant changes during pregnancy and lactation to facilitate milk production. Through the generation and analysis of 480 transcriptomes, we provide the most detailed allelic expression map of the mammary gland, cataloguing cell-type-specific expression from ex-vivo purified cell populations over 10 developmental stages, enabling comparative analysis. The work identifies genes involved in the mammary gland cycle, parental-origin-specific and genetic background-specific expression at cellular and temporal resolution, genes associated with human lactation disorders and breast cancer. Genomic imprinting, a mechanism regulating gene expression based on parental origin, is crucial for controlling gene dosage and stem cell potential throughout development. The analysis identified 25 imprinted genes monoallelically expressed in the mammary gland, with several showing allele-specific expression in distinct cell types. No novel imprinted genes were identified and the absence of biallelically expressed imprinted genes suggests that, unlike in brain, selective absence of imprinting does not regulate gene dosage in the mammary gland. This research highlights transcriptional dynamics within mammary gland cells and identifies novel candidate genes potentially significant in the tissue during pregnancy and lactation. Overall, this comprehensive atlas represents a valuable resource for future studies on expression and transcriptional dynamics in mammary cells.

Animals↗

PubMed2005

The mouse epididymal transcriptome: transcriptional profiling of segmental gene expression in the epididymis.

Maturation of spermatozoa, including the acquisition of motility and the ability to undergo capacitation, occurs during transit through the dynamic environment of the epididymis. The microenvironments created along the length of the epididymal tubule are essential to the molecular modifications of spermatozoa that result in fertile gametes. The secretory and resorptive processes of the epithelial cells that line this tubule generate these microenvironments. In the current study, 10 morphologically distinct segments of the mouse epididymis were identified by microdissection. We hypothesized that the changing environments of the epididymal lumen are established by differential gene expression among these segments. RNA isolated from each of the 10 segments was analyzed by microarray analysis. More than 17,000 genes are expressed in the mouse epididymis, compared with about 12,000 genes identified from whole epididymal samples. Screening a panel of normal mouse tissues identified both epididymal-selective and epididymal-specific transcripts. In addition, this study identified 2168 genes that are up-regulated or down-regulated by greater than 4-fold between at least two different segments. The expression patterns of these genes identify distinct patterns of segmental regulation. Using principal component analysis, we determined that the 10 segments form 6 different transcriptional units. These analyses elucidate the changes in gene expression along the length of the epididymis for 17,000 expressed transcripts and provide a powerful resource for the research community in future studies of the biological factors that mediate epididymal sperm maturation.

Animals↗

PubMed2025

Trajectory inference from single-cell genomics data with a process time model.

Single-cell transcriptomics experiments provide gene expression snapshots of heterogeneous cell populations across cell states. These snapshots have been used to infer trajectories and dynamic information even without intensive, time-series data by ordering cells according to gene expression similarity. However, while single-cell snapshots sometimes offer valuable insights into dynamic processes, current methods for ordering cells are limited by descriptive notions of "pseudotime" that lack intrinsic physical meaning. Instead of pseudotime, we propose inference of "process time" via a principled modeling approach to formulating trajectories and inferring latent variables corresponding to timing of cells subject to a biophysical process. Our implementation of this approach, called Chronocell, provides a biophysical formulation of trajectories built on cell state transitions. The Chronocell model is identifiable, making parameter inference meaningful. Furthermore, Chronocell can interpolate between trajectory inference, when cell states lie on a continuum, and clustering, when cells cluster into discrete states. By using a variety of datasets ranging from cluster-like to continuous, we show that Chronocell enables us to assess the suitability of datasets and reveals distinct cellular distributions along process time that are consistent with biological process times. We also compare our parameter estimates of degradation rates to those derived from metabolic labeling datasets, thereby showcasing the biophysical utility of Chronocell. Nevertheless, based on performance characterization on simulations, we find that process time inference can be challenging, highlighting the importance of dataset quality and careful model assessment.

Single-Cell Analysis↗

PubMed2026

NextLongIso: a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis.

SUMMARY: Long-read RNA sequencing technologies, including Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), enable direct characterization of full-length transcripts and transcriptome complexity. However, analysis of long-read RNA-seq data remains fragmented across multiple tools, limiting the ability to obtain a unified view of transcript structure, expression, and regulatory variation in long-read transcriptomes. We present NextLongIso, a scalable and reproducible Nextflow pipeline that enables coordinated analysis of multiple layers of transcript regulation. Rather than focusing solely on transcript reconstruction, NextLongIso integrates transcript discovery with downstream regulatory analyses to jointly characterize alternative splicing, isoform switching, transcript boundary dynamics (including alternative promoters and polyadenylation), and transposable element-associated transcription from both PacBio and ONT datasets. By eliminating complex cross-tool data harmonization, this unified framework facilitates the transition from transcript identification to functional interpretation of transcriptomic variation. AVAILABILITY AND IMPLEMENTATION: NextLongIso is implemented in Nextflow and is freely available at github: https://github.com/YidanSunResearchLab/nf-LongIso.git and Zenodo: https://doi.org/10.5281/zenodo.21049837.

Software↗

PubMed2026

Host-driven evolution shapes the polysaccharide utilization profiles of alga-associated Flavobacteriaceae.

BACKGROUND: Marine algae represent major producers of complex polysaccharides and serve as hosts for diverse microbial communities in the phycosphere. Flavobacteriaceae are among the key bacterial taxa involved in polysaccharide degradation and carbon remineralization in this environment. However, the extent to which algal hosts drive the divergence of polysaccharide utilization profiles in these bacteria remains unclear. RESULTS: We conducted a genome-resolved analysis of 103 cultured Flavobacteriaceae strains isolated from red, green, and brown macroalgae, as well as from diatoms and dinoflagellates. We found that macroalga-associated strains generally harbored more abundant and diverse CAZyme-encoding genes than their microalga-associated counterparts. Moreover, strains associated with different algal phyla showed distinct metabolic specializations that aligned with the typical polysaccharides of their respective hosts, strongly supporting host-specific adaptation. In four widely distributed genera (Maribacter, Flagellimonas, Polaribacter, Winogradskyella), CAZyme profile dissimilarity and key glycoside hydrolase gene divergence exhibited phylogenetic congruence with algal host phylogeny (Mantel r up to 0.76 and 0.85, respectively), indicative of host-associated functional adaptation. Using Maribacter as a model, cultivation experiments and transcriptome characterization demonstrated that polysaccharide utilization efficiency is not solely linked to the organization of genes into polysaccharide utilization loci (PULs), but also associated with the expression dynamics of key transcription factors (TFs), particularly those from AraC and DeoR families, whose expression patterns were coordinated with laminarin degradation. Notably, these two TF families also exhibited host-associated divergence patterns similar to those of CAZyme-encoding genes. Furthermore, analysis of the Tara Oceans metagenomic data indicated that, within the AraC and DeoR families, a higher proportion of genes were positively correlated with chlorophyll a content compared to other TF families, reinforcing their specialized roles in alga-associated bacterial lifestyles. CONCLUSIONS: Our integrative genomic and transcriptomic analyses reveal evolutionary and regulatory adaptation of marine Flavobacteriaceae to distinct algal hosts. These findings highlight algae-derived habitats as specialized niches that shape microbial metabolic potential, and suggest that carbohydrate metabolism plays a key role in host-driven bacterial evolution across global oceans. Video Abstract.

Flavobacteriaceae↗

PubMed2026

Big data analytics for CLEC5A dynamics based on single cell genomics and proteomics reveal its diverse functions in human diseases.

BACKGROUND: CLEC5A (C-type lectin domain family 5 member A) is an innate immune receptor implicated in inflammatory signaling, contributing to hyperinflammatory responses in infections and sterile inflammation. However, CLEC5A dynamics in human diseases remain to be identified. Here, we systematically characterized CLEC5A dynamics in humans across cells, tissues, and disease states, and to explore the functional significance of CLEC5A in macrophage activation based on single-cell genomics. METHODS: With multi-omics (scRNA-seq, proteomics and big data analytics), we analyzed extensive human transcriptomic datasets (>42,000 samples) to profile CLEC5A expression by cell type, tissue, and disease. Single-nucleus RNA-seq (snRNA-seq) from pediatric congenital heart disease and a virtual CLEC5A gene knockout were also performed to characterize CLEC5A dynamics in humans. RESULTS: CLEC5A is highly enriched in innate immune cells, particularly in macrophages and neutrophils. Baseline CLEC5A in most tissues is low, but it is markedly upregulated in inflammatory and infectious diseases. CLEC5A expression has sex-specific differences in certain organs. Single-cell analysis showed that CLEC5A can be considered novel marker of proinflammatory macrophages with elevated cytokine production, antigen presentation, and impaired phagocytosis. Virtual CLEC5A knockout analysis identified coordinated perturbation of immune-regulatory pathways and overlapping genes linking CLEC5A to macrophage activation networks. CONCLUSION: CLEC5A is predominantly expressed in myeloid cells and acts as a key amplifier of inflammation in human diseases. Our findings highlight CLEC5A as a potential biomarker and therapeutic target in myeloid-driven hyperinflammatory conditions, warranting further experimental and translational validation.

Humans↗

PubMed2026

Single-cell analysis of the human retina reveals stage-linked microglial states and neural-immune circuit rewiring in diabetic retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations-homeostatic and inflammatory-that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

Humans↗

PubMed2026

Glycerophospholipid remodeling under osmotic stress in grass carp gills.

Salinity fluctuations represent a pervasive environmental challenge for freshwater fishes, yet the cellular and metabolic programs governing early osmoregulatory responses remain understudied. Here, we investigated the time-dependent gill responses of juvenile grass carp (Ctenopharyngodon idella) subjected to an acute, sublethal salinity increase 9 parts per thousand (ppt). Histological and biochemical analyses revealed progressive gill lesions accompanied by elevated lactate dehydrogenase (LDH) activity and lipid peroxidation, indicating rapid tissue injury under osmotic stress. Integrative metabolomic and transcriptomic profiling uncovered pronounced temporal reprogramming, consistently highlighting glycerophospholipid metabolism as a central axis of response. In particular, phosphatidylcholine (PC) species exhibited dynamic remodeling, coupled with transcriptional enrichment of lipid turnover, membrane transport, and innate immune pathways. Network-based integration identified a PC-centered remodeling module characterized by accelerated PC headgroup turnover, disruption of the PLA2-LPCAT2 lyso-PC reacylation cycle, and enhanced ABC transporter-associated lipid and sterol export, reflected by cholesteryl sulfate accumulation and a shifted n-6 polyunsaturated fatty acid-derived oxylipin signature. Functional assays further demonstrated that PC and linoleic acid (LA) supplementation improved cell viability and alleviated oxidative stress and pro-inflammatory signaling in grass carp cells under salinity challenge. Collectively, these findings reveal phospholipid-centered membrane remodeling as an early, integrative mechanism linking osmotic stress to gill injury and immune activation in freshwater fish, providing insights into potential strategies of environmental stress adaptation.

Animals↗

PubMed2026

Transcriptional and phytohormonal regulation of positional ear development reveals yield strategies in maize.

Maize (Zea mays L.) is a vital global crop, contributing ∼37% of annual grain production. Enhancing yield per unit area is crucial for food security, yet research has primarily focused on single-ear traits, overlooking the regulation of double ears-a key determinant of prolificacy. While secondary ears drive yield variability under prolificacy-favoring conditions, the mechanisms governing ear formation across shoot positions remain poorly understood. Here, we performed high-resolution transcriptomic analysis of 66 samples from three ear types (primary, secondary and third) in maize inbred B73. We uncovered distinct hormonal developmental dynamics: strigolactone (SL) signaling genes, particularly SBP transcription factors, dominated in primary (I) ears, whereas ethylene-related genes (e.g., ZmEREB131, ZmACCO35) were enriched in third (III) ears. Functional validation confirmed that knockout of ZmEREB131 and ZmACCO35 accelerated development and elongated ears compared to wild-type, implicating ethylene (ETH) signaling in ear maturation arrest. Notably, SL inhibitor application synchronized primary and secondary ear development, boosting total yield by >20% without compromising primary ear performance. Our study elucidates the transcriptional networks underlying differential ear development and provides actionable strategies for yield improvement through targeted hormonal modulation. These findings advance the understanding of maize inflorescence biology and offer molecular tools for breeding high-yielding varieties.

RNA-seq↗

PubMed2026

Guidelines for evaluating endothelial function in vascular tissue.

The endothelium plays a central role in maintaining vascular homeostasis by orchestrating vascular tone, inflammation, healing, permeability, and thrombosis. Assessing endothelial function in vascular tissue is essential for understanding the cellular and molecular mechanisms underlying cardiovascular physiology and pathology. Traditional approaches, such as wire and pressure myography, have been instrumental in defining endothelium-dependent responses and identifying key pharmacological targets. However, the complexity and heterogeneity of endothelial cells across vascular beds and their dynamic phenotypic changes in health and disease necessitate the incorporation of new investigative strategies. Emerging methodologies, including bulk and single-cell transcriptomics, proteomics, and advanced imaging, now provide unprecedented insights into endothelial cell diversity and function. A team of leading experts in the field, who collectively reached a consensus on the most widely used techniques to evaluate endothelial function, developed these guidelines. The document establishes best practices for assessing endothelial function, from endothelial cell cultures to isolated vascular tissues, integrating conventional functional assays with modern molecular approaches. By fostering methodological consistency and embracing innovation, our goal is to enhance rigor, reproducibility, understanding, and discovery in endothelial biology.

Humans↗