Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “transcriptome sequencing”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16Linked to original sources
PubMed2025

Epitranscriptomic reprogramming in response to low CO2 stress and m6A engineering to enhance biomass production in Nannochloropsis oceanica.

N6-adenine methylation (m6A) as an epitranscriptomic mark is the most abundant modification in eukaryotic RNA and plays a dynamically regulated role. However, m6A dynamics, deposition and engineering in microalgae remain largely unknown. Here, in Nannochloropsis oceanica, the dynamic alterations and reprogramming in m6A RNA modifications after the shift from high to low CO2 conditions were first investigated using methylated RNA immunoprecipitation sequencing. The m6A peaks in N. oceanica were mainly enriched in 3'UTR. A positive association between m6A abundance and mRNA transcription of CO2-responsive genes was observed; moreover, N. oceanica cells adopted versatile strategies in a dynamic reprogramming of m6A in response to low CO2 stress. Secondly, knockout of two putative m6A methylases including NoMTA (NO04G02990) and NoMTB (NO07G02450) by genome editing induced methylation reprogramming, which was associated with expression changes of low-CO2 responsive genes such as carbon/nitrogen metabolism, and photorespiration genes that underlie reductions in growth and biomass. Lastly, m6A modification reprogramming was first engineered to increase low-CO2 stress tolerance and biomass productivity by the CRISPR/dCas13 system combined with MTA and NoMTB under low CO2 in N. oceanica. Therefore, these strides would pave the way for microalgal epigenetics and future industrial applications.

Microalgae↗
PubMed2026

Disease-driven post-transcriptional alterations and alternative splicing in podocytes in focal segmental glomerulosclerosis.

Focal segmental glomerulosclerosis (FSGS) is a major cause of nephrotic syndrome and progression to end-stage renal disease, yet its molecular pathogenesis remains still incompletely defined. While transcriptional alterations in podocytes have been extensively characterized, the contribution of post-transcriptional regulatory mechanisms is poorly understood. Here, we combined a zebrafish podocyte-specific injury model with glomerulus-resolved transcriptomic profiling to dissect RNA regulatory alterations during FSGS progression. Integrated analyses of bulk RNA sequencing, small RNA profiling, and alternative splicing revealed pronounced, time-dependent remodeling of the glomerular transcriptome. We demonstrate that podocyte injury is associated with loss of key podocyte-specific proteins, activation of inflammatory pathways, remodeling of the extracellular matrix, and altered microRNA expression, such as miR-21 and miR-193. Moreover, we found that alternative splicing influences key podocyte gene expression, affecting genes critical for slit diaphragm integrity, actin cytoskeleton organization, and glomerular basement membrane stability. Isoform analyses identified FSGS-associated isoform switches in SRSF3 and EPB41L5. Importantly, these changes were also evident in glomeruli from FSGS patients, demonstrating that the zebrafish model recapitulates key molecular features of human disease and highlighting alternative splicing as a central regulatory mechanism in FSGS.

Animals↗
PubMed2026

A critical appraisal of base-resolution m6A profiling techniques.

N6-methyladenosine (m6A) is the most prevalent internal modification in eukaryotic mRNA, influencing RNA fate and gene regulation. Early antibody-based approaches enabled transcriptome-wide profiling but lacked resolution and quantitative accuracy. Newer approaches now achieve base-resolution m6A detection using improved crosslinking, chemical or enzymatic conversion, and single-molecule sequencing. Antibody-free methods provide quantitative stoichiometry from minimal input, while nanopore direct RNA sequencing offers real-time, single-molecule readouts across entire transcriptomes. Collectively, these methods form a versatile toolkit that integrates global mapping with precise site-level analysis, advancing knowledge of context-dependent m6A regulation in physiology and disease. This review compares their principles, strengths, and limitations to guide method selection and highlight how next-generation epitranscriptomic tools are paving the way for clinical and therapeutic applications.

Humans↗
PubMed2026

Unveiling tumor heterogeneity by single cell RNA-sequencing: From basic considerations to clinical applications.

Tumor heterogeneity-encompassing diverse cellular phenotypes, genomic alterations, and microenvironmental contexts-is a principal barrier to effective cancer therapy. Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve this complexity by capturing transcriptomes at single-cell resolution. Here, we review the technical foundations required for high-quality scRNA-seq studies. We then trace the evolution of scRNA-seq platforms from manual micromanipulation to high-throughput systems, and describe the computational pipelines that enable reliable data interpretation. The application of scRNA-seq is exemplarily shown in the context of lung cancer, where single-cell profiling has revealed (i) the clonal and sub-clonal architecture of tumors, (ii) extensive remodeling of the immune microenvironment, iii) key mechanisms underlying resistance to targeted agents and immune-checkpoint blockade, and (iv) the dynamics of neo-antigen-specific T-cell responses. Integrating machine-learning techniques-such as deep-learning classifiers and graph-based models-with single-cell transcriptomic data has markedly sped up biomarker discovery, produced more accurate risk-stratification scores, and enabled the generation of patient-specific therapeutic predictions. We surveyed the major trial registry ClinicalTrials.gov and identified ∼380 ongoing or completed studies that explicitly incorporate scRNA-seq as a correlative or pharmacodynamic endpoint. Overall, the analysis shows that scRNA-seq becomes an increasingly important component of modern trials, providing high-resolution cellular and molecular readouts that complement conventional imaging and bulk-omics endpoints. While key challenges remain, ranging from costs, scalability and need for rigorous validation before routine clinical deployment, ongoing technological advances continue to expand the potential of scRNA-seq as a cornerstone of precision medicine.

Humans↗
PubMed2026

Hyperprogression Upon Cemiplimab Alone or With Short Course Chemotherapy in PD-L1 ≥ 50% Non-small Cell Lung Cancer: A Biomarker Guided Multicenter International Phase 2 Trial-HYPERBOLIC Study.

BACKGROUND: Immune checkpoint inhibitor (ICI) monotherapy is the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) with PD-L1 ≥ 50%; however, up to 30% of patients experience early progression or death, including cases of hyperprogressive disease (HPD). High baseline levels (≥ 30.5%) of circulating CD10- low-density neutrophils (LDNs) have been associated with increased HPD occurrence. Emerging evidence suggests that combining ICI with platinum-based chemotherapy (PCT) may mitigate the risk of HPD. Currently, no prospective studies have addressed HPD prevention in this context. PATIENTS AND METHODS: HYPERBOLIC (NCT07274384) is a phase 2, randomized, open-label, multicenter, international trial evaluating whether adding 3 cycles of PCT to first-line cemiplimab reduces HPD rate in stage IV NSCLC with PD-L1 ≥ 50% and CD10- LDNs (identified by flow cytometry as CD15⁺CD11b⁺ within the PBMC fraction, with immature cells defined by loss of CD10) ≥ 30.5%. Seventy-four patients will be randomized (1:1 ratio) to receive cemiplimab alone or cemiplimab plus 3 PCT cycles, followed by cemiplimab maintenance. Randomization will be stratified by Lung Immune Prognostic Index. The first computed tomography scan at week 7 after treatment start will assess HPD occurrence, defined as RECIST v 1.1. disease progression with a delta tumor growth rate (ΔTGR) ≥ 50% and/or TGR ratio ≥ 2. The primary endpoint will be the combined rate of HPD and early death (death within 12 weeks with no radiological evaluation). Secondary endpoints will be HPD rate according to alternative definitions, overall survival, progression free survival, objective response rate, and safety. An extensive translational research platform will include spatial transcriptomics of tumor tissue, single-cell RNA sequencing of PBMCs, circulating-free DNA and plasma factors profiling, and saliva/stool microbiome genomics and metabolomics, to longitudinally explore tumor-host dynamic interactions during treatment. CONCLUSION: to our knowledge, HYPERBOLIC is the first prospective, biomarker-driven trial investigating early treatment escalation based on HPD risk in PD-L1-high NSCLC.

CD10↗
PubMed2026

Time-dependent effects of rapid-acting antidepressants in iPSC-derived neurons from treatment-resistant depression and healthy volunteers.

Rapid-acting antidepressants like ketamine and serotonergic psychedelics show promise for treatment-resistant depression (TRD), but the molecular mechanisms that contribute to their therapeutic effects remain unclear. Induced pluripotent stem cells (iPSCs) offer a platform to model human cortical neurons and investigate drug effects in a human-relevant system. Here, iPSCs from individuals with TRD and healthy volunteers (HVs) were differentiated into mature cortical-like neurons and treated for six and 24 h with agents being investigated as rapid-acting antidepressants, including (2 R,6 R)-hydroxynorketamine (HNK), psilocybin, lysergic acid diethylamide (LSD), and 2,5-Dimethoxy-4-iodoamphetamine (DOI). Bulk and single-cell RNA sequencing assessed global and cell-type-specific transcriptomic responses. Synaptic proteins were evaluated via Western blotting and immunocytochemistry. To validate translational relevance, transcriptomic results were compared to CSF proteomics from ketamine-treated HVs. Despite differing initial pharmacological targets, overall gene expression across all compounds was highly correlated at matched timepoints compared to vehicle control, suggesting shared downstream effects. Both glutamatergic and serotonergic drugs converged on pathways involving inflammation, mTORC1 signaling, and cellular growth. At the single-cell level, (2 R,6 R)-HNK showed distinct cell-type specific alterations: upregulation in excitatory neurons and concomitant downregulation of inhibitory neuron populations. Differentially expressed genes from (2 R,6 R)-HNK-treated neurons also overlapped with CSF proteomic signatures from ketamine-treated individuals, supporting the model's translational relevance. This study is the first to assess multiple putative rapid-acting antidepressants in parallel using an iPSC-derived neuron model. Both convergent and drug-specific changes in gene expression and pathway enrichment were observed across diverse compounds, supporting the use of human iPSC-derived neurons in antidepressant drug discovery. Clinical Trial Registry: www.clinical trials.gov, NCT02484456.

Journal Article↗
PubMed2025

De novo assembly of transcriptomes of six Hua species (Semisulcospiridae, Cerithioidea, Gastropoda).

Species in Semisulcospiridae are important in freshwater ecology and have great research value, yet their genomic resources remain very limited. Here, we present de novo assembled transcriptomes from six species of Hua in Semisulcospiridae, including Hua textrix (Heude, 1888), H. yangi L.-N. Du, J.-X. Yang & Chen, 2023, H. wujiangensis L.-N. Du, J.-X. Yang & Chen, 2023, and three undescribed species. Assembly was performed using Trinity, resulting in average contig lengths ranging from 716.6 to 883.3 bp and transcript numbers ranging from 147,147 to 268,741. Benchmarking Universal Single-Copy Ortholog (BUSCO) analysis was used to assess the transcriptome completeness. The functional annotation of transcripts for each species had over 18,000 BLAST hits, 17,000 GO terms, 15,000 KEGG pathways, 8,000 Pfam accessions, and 140 COG functional categories. This study provides valuable transcriptomic resources for the six Hua species, which can be used for various research of Semisulcospiridae, including biodiversity, phylogeny, and comparative genomics.

Transcriptome↗
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↗
PubMed2026

Epigenetic and metabolic reprogramming of innate immune cells establishes immunological memory in the Schistosomiasis vector snail Biomphalaria glabrata.

Innate immune memory enables non-vertebrates to mount faster and more effective immune responses upon re-exposure to a previously encountered pathogen, yet its cellular and molecular bases remain poorly understood. The freshwater snail Biomphalaria glabrata, intermediate host of the human parasite Schistosoma mansoni, provides a powerful model to investigate this phenomenon. Here, we show that innate immune memory in B. glabrata is carried by hemocytes and relies on profound metabolic and epigenetic reprogramming initiated during primary infection. Using an integrative multi-omics approach combining transcriptomics, chromatin accessibility profiling, whole-genome bisulfite sequencing and targeted metabolomics, we reveal that the first parasite encounter induces a stable rewiring of hemocyte metabolism and chromatin landscape. This reprogramming primes hemocytes for a massive and rapid transcriptional response upon secondary challenge, characterized by an immune shift toward highly specific humoral effector pathways. Metabolic analyses demonstrate an early switch toward aerobic glycolysis, altered tricarboxylic acid cycle activity and amino acid metabolism, consistent with a Warburg-like metabolic state previously described in vertebrate trained immunity. Notably, metabolic and epigenetic remodeling occurs primarily during the primary infection and remains stable upon secondary exposure, suggesting that immune memory is encoded prior to pathogen re-encounter. Together, our results identify conserved metabolic and epigenetic mechanisms underlying innate immune memory in a non-vertebrate host and provide direct evidence that hemocyte-mediated innate immune memory in B. glabrata shares core features with trained immunity described in vertebrates.

Animals↗
PubMed2026

Time-Dependent Effects of Rapid-Acting Antidepressants in iPSC-Derived Neurons from Treatment-Resistant Depression and Healthy Volunteers.

UNLABELLED: Rapid-acting antidepressants like ketamine and serotonergic psychedelics show promise for treatment-resistant depression (TRD), but the molecular mechanisms that contribute to their therapeutic effects remain unclear. Induced pluripotent stem cells (iPSCs) offer a platform to model human cortical neurons and investigate drug effects in a human-relevant system. Here, iPSCs from individuals with TRD and healthy volunteers (HVs) were differentiated into mature cortical-like neurons and treated for six and 24 hours with agents being investigated as rapid-acting antidepressants, including (2R,6R)-hydroxynorketamine (HNK), psilocybin, lysergic acid diethylamide (LSD), and 2,5-Dimethoxy-4-iodoamphetamine (DOI). Bulk and single-cell RNA sequencing assessed global and cell-type-specific transcriptomic responses. Synaptic proteins were evaluated via Western blotting and immunocytochemistry. To validate translational relevance, transcriptomic results were compared to CSF proteomics from ketamine-treated HVs. Despite differing initial pharmacological targets, overall gene expression across all compounds was highly correlated at matched timepoints compared to vehicle control, suggesting shared downstream effects. Both glutamatergic and serotonergic drugs converged on pathways involving inflammation, mTORC1 signaling, and cellular growth. At the single-cell level, HNK showed distinct cell-type specific alterations: upregulation in excitatory neurons and concomitant downregulation of inhibitory neuron populations. Differentially expressed genes from HNK-treated neurons also overlapped with CSF proteomic signatures from ketamine-treated individuals, supporting the model's translational relevance. This study is the first to assess multiple putative rapid-acting antidepressants in parallel using an iPSC-derived neuron model. Both convergent and drug-specific changes in gene expression and pathway enrichment were observed across diverse compounds, supporting the use of human iPSC-derived neurons in antidepressant drug discovery. CLINICAL TRIAL REGISTRY: www.clinicaltrials.gov, NCT02484456.

Journal Article↗
PubMed2025

Unsupervised multiscale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes.

BACKGROUND: Cell clustering is an essential step in uncovering cellular architectures in single-cell RNA sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. RESULTS: Here, we develop a multiscale clustering (MSC) approach to construct a sparse cell-cell correlation network for unsupervised identification of de novo cell types and subtypes across multiple resolutions. Based upon simulated silver- and gold-standard data as well as real scRNA-seq data in diseases, MSC demonstrates significantly improved performance compared to established benchmark methods and reveals a biologically meaningful cell hierarchy to facilitate the discovery of novel disease-associated cell subtypes and mechanisms. CONCLUSIONS: We present MSC as a new single-cell multiscale clustering framework as a powerful tool for advancing discoveries in disease-associated cell populations using single-cell sequencing data.

Single-Cell Analysis↗
PubMed2026

A Molecularly Anchored Spatial Transcriptomic Framework for Precise CA1-Subiculum Parcellation and Region-Resolved Analysis in Alzheimer's Disease.

BACKGROUND: The precise molecular delineation of the interface between the Subiculum (Sub) and cornu ammonis 1 (CA1) is a challenge in hippocampal research, as conventional cytoarchitectural boundaries are often ambiguous and limit reproducible regional annotation. Here, we developed a molecularly anchored spatial transcriptomic framework to define CA1-Sub regional identities using high-definition spatial transcriptomics (Stereo-seq) and single-nucleus RNA sequencing (snRNA-seq) references. FINDINGS: Using a human hippocampal Stereo-seq dataset from 12 donors, we established a data-driven parcellation framework that defines reproducible molecular features distinguishing CA1 and Sub while capturing the transition between these regions. FN1 was identified as a Sub-enriched marker in a subset of EX_Sub and, together with ETV1 and additional regional markers, enabled molecular assignment of CA1 and Sub identities across datasets. The Sub association of FN1 and ETV1 was further supported by human 10X Genomics spatial transcriptomics, mouse in situ hybridization data, and a mouse spatial transcriptomic dataset. Applying this framework to Alzheimer's disease (AD) tissues revealed region-specific transcriptional alterations across CA1 and Sub, including enrichment of mitochondrial energy metabolism-related transcripts in the Sub, suggesting exploratory transcriptional associations of altered metabolic function. CONCLUSIONS: This study provides a molecularly anchored framework for human CA1-Sub parcellation that complements conventional annotation. By defining regional molecular states while preserving the biological continuum across CA1-Sub interface, this approach enables more consistent regional analysis of human hippocampus tissue across donors, datasets, and disease conditions.

Journal Article↗
PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗
PubMed2025

Alternative Splicing in Mechanically Stretched Podocytes as a Model of Glomerular Hypertension.

KEY POINTS: Mechanical stretch induced over 3000 alternative splicing events in podocytes, affecting gene expression and protein abundance. Seventeen genes showed consistent splicing events across multiple analysis tools, with key isoform changes. Shroom3 and Myl6 underwent isoform switches under mechanical stretch, altering the C-terminal sequence and interaction properties of Myl6. BACKGROUND: Alterations in pre-mRNA splicing are crucial to the pathophysiology of various diseases. However, the effects of alternative splicing of mRNA on podocytes in hypertensive nephropathy are still unknown. The Sys_CARE project aimed to identify alternative splicing events involved in the development and progression of glomerular hypertension. METHODS: Murine podocytes were exposed to mechanical stretch, after which proteins and mRNA were analyzed by proteomics, RNA sequencing, and several bioinformatic alternative splicing tools. RESULTS: Using transcriptomic and proteomic analysis, we identified significant changes in gene expression and protein abundance because of mechanical stretch. RNA-Seq identified over 3000 alternative spliced genes after mechanical stretch, including all types of alternative splicing events. Among these, 17 genes exhibited an alternative splicing event across four different splicing analysis tools. From this group, we focused on Myl6, a component of the myosin protein complex, and Shroom3, an actin-binding protein essential for podocyte function. We identified two Shroom3 isoforms with significant expression changes under mechanical stretch, which was validated by quantitative RT-PCR and in situ hybridization. In addition, we observed an expression switch of two Myl6 isoforms after mechanical stretch, accompanied by an alteration in the C-terminal amino acid sequence. CONCLUSIONS: A comprehensive RNA-Seq analysis of mechanically stretched podocytes identified novel potential podocyte-specific biomarkers and highlighted significant alternative splicing events, notably in the mRNA of Shroom3 and Myl6.

podocyte↗
PubMed2026

HyLnc: a hybrid deep learning and feature-based approach for long non-coding RNA prediction.

Long non-coding RNAs (lncRNAs) play important roles in gene regulation, development and disease, yet accurate identification of lncRNAs from transcriptomic data remains a major computational challenge. Existing methods often rely either on handcrafted sequence features or deep learning approaches, each with their inherent limitations in capturing the full complexity of RNA sequences. In this study, we proposed HyLnc, a computational framework that integrates transformer-based contextual embeddings with biologically meaningful sequence features for improved lncRNA prediction. A custom BERT-based model was first pre-trained on a large corpus of metazoan RNA sequences using a masked language modelling strategy to learn contextual nucleotide dependencies. The model was subsequently fine-tuned on curated datasets of lncRNAs and protein-coding transcripts and 256-dimensional deep sequence embeddings were extracted. Parallelly, 348 handcrafted features, including ORF characteristics, untranslated region (UTR) properties, nucleotide composition and Fickett scores, were computed. A multi-stage feature selection strategy was applied to identify the most informative features, resulting in optimized hybrid feature sets. Multiple machine learning classifiers were evaluated, with the RF model achieving the best performance. The proposed framework attained an accuracy of 91.30%, F1-score of 91.23% and MCC of 82.60 on an independent validation dataset, outperforming several existing lncRNA prediction tools. Thus, HyLnc demonstrates that integrating deep contextual representations with biologically interpretable features enhances lncRNA prediction. This approach provides a robust and scalable solution for large-scale transcriptome annotation and can be extended to other sequence-based prediction.

RNA, Long Noncoding↗
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↗
PubMed2025

Root growth promotion by Penicillium melinii : mechanistic insights and agricultural applications.

This study characterizes Penicillium melinii , an endophytic fungus isolated from Arabidopsis thaliana roots, as a plant growth-promoting fungus with potential use as a model to study root development and as a biostimulant for sustainable agriculture. Although endophytes are known to promote plant growth, the underlying molecular mechanisms often remain poorly understood. Here, we aimed to elucidate how P. melinii enhances root system development and to assess its applicability across different crops. Phenotypic assays were conducted in Arabidopsis, quinoa and tomato under in vitro , greenhouse and field conditions. Root architecture and biomass were quantified using image-based phenotyping. Transcriptomic and phytohormone profiling assessed plant responses, and fungal genome sequencing coupled with secretome analysis was used to identify candidate effectors and metabolic traits. P. melinii consistently promoted root growth and increased plant biomass across species and environments, both in vitro and in the greenhouse. In tomato field trials, this translated into a significant increase in yield. The fungus colonized root surfaces without vascular penetration and triggered a mild transcriptomic response: early activation of stress-response genes followed by their attenuation and sustained upregulation of auxin-related pathways. Notably, the interaction modulates the SLR-ARF-LBD pathway and the number of pre-branch sites probably through increased auxin signalling in the oscillation zone. Additional hormonal changes were limited and mainly associated with the attenuation of the plant response to microorganisms. P. melinii enhances lateral root formation through a subtle molecular and metabolic dialogue with the host plant, underscoring its relevance as a model for studying root developmental plasticity. Its strong and reproducible growth-promoting effect, demonstrated with different fungal strains and under controlled and field conditions, supports its potential as a biostimulant for sustainable crop production.

Journal Article↗
PubMed2026

A High-Resolution Stereo-Seq Spatial Transcriptomic Resource for Adult Holstein Cattle Liver.

The bovine liver is a highly compartmentalized organ that plays essential roles in continuous gluconeogenesis and nitrogen recycling; however, its spatial molecular architecture has remained largely uncharacterized due to the limitations of traditional bulk and single-cell approaches. To address this gap, Spatial Enhanced Resolution Omics-sequencing (Stereo-seq) was utilized to generate a subcellular-resolution (500 nm) transcriptomic map of an adult Holstein cattle liver, and a refined reference-guided workflow was implemented to overcome standard annotation limitations in livestock. Raw sequencing data were processed using the Stereo-seq Analysis Workflow and analyzed with Stereopy, Seurat, SingleR, and reference-guided workflows. Spatial aggregation was evaluated at Bin20, Bin50, Bin100, Bin150, and Bin200. Increasing bin size increased molecular identifier counts and detected-gene complexity while progressively reducing spatial granularity. Bin50, corresponding to 50 × 50 DNA nanoballs and an approximate nominal footprint of 25 × 25 µm, was therefore selected as a practical intermediate aggregation level for the primary analyses. Quality-control assessment, Leiden clustering, UMAP visualization, reference-based cell-type annotation, cluster-marker analysis, and spatial mapping of canonical hepatic genes demonstrated preservation of biologically interpretable liver transcriptional organization. Raw sequencing data processed spatial matrices, annotated objects, and analysis code are publicly available to support reanalysis and computational benchmarking. In summary, we present a Stereo-seq spatial transcriptomic resource generated from liver tissue of an adult Holstein cow. This initial resource provides a valuable foundation for future studies of bovine liver biology, comparative genomics, and the spatial basis of livestock health and production traits.

Animals↗