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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↗

PubMed2026

Cerium dioxide nanoparticle exposure attenuates mobility-linked antibiotic resistome signatures across the soil-lettuce continuum.

Antibiotic resistance genes (ARGs) are contaminants of emerging concern in agricultural microbiomes. Their association with mobile genetic elements (MGEs) can enhance dissemination across soil-plant interfaces, creating potential environmental and food-chain exposure risks. However, how engineered nanoparticles modulate relative ARG abundance and mobility-linked resistome features in plant-associated microbiomes remains poorly understood. Here, we examined the effects of graded, experimentally elevated cerium dioxide nanoparticle (CeO2 NP) loadings in a soil-lettuce system by integrating compartment-resolved metagenomics, ARG-MGE co-occurrence analysis, putative host-reservoir profiling, transcriptomics, and functional assays. Metagenomic profiling identified 16 ARG types and 125 subtypes and revealed niche-dependent microbiome restructuring under CeO2 NP exposure. Rhizosphere relative ARG abundance showed a negative dose-associated trend, although overall inter-group differences were not significant, whereas leaf endophytes showed a weaker response. Relative MGE abundance decreased significantly in both compartments, and lower assembly-level ARG-MGE co-occurrence reflected fewer ARGs detected in MGE-associated genomic contexts, whereas fewer multi-ARG contigs suggested reduced ARG clustering and potential co-selection. Putative host-reservoir analysis associated key efflux determinants with bacterial families whose relative representation declined following CeO2 NP exposure. Transcriptomic profiling of representative putative ARG hosts revealed host-specific responses, including downregulation of genes involved in central metabolism and Sec-dependent trafficking. Complementary host assays showed reduced apparent envelope permeability and lower recovery of tetracycline-resistant recipient-identity colonies in the plasmid-associated host system. Together, under the tested elevated-loading conditions, CeO2 NP exposure was associated with lower relative ARG signals and weaker mobility-linked resistome features across the soil-lettuce continuum, providing mechanistic insight into nanoparticle-resistome interactions in soil-plant systems.

ARG dissemination↗

PubMed2026

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair↗

PubMed2026

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals↗

PubMed2026

Integrated Multi-Omics Analysis Reveals the Genetic Basis of Phenotypic Variation in Tibetan Sheep.

Body size is a key economic trait influencing the profitability of farmed animals. This study used genome-wide association studies (GWAS) to identify five single nucleotide polymorphisms (SNPs) significantly associated with body size in the Tibetan sheep population, advancing molecular breeding and providing a basis for genomic selection. These SNPs are located within five candidate genes. SNaPshot validated GWAS results, demonstrating significant correlations between candidate SNPs and body size traits in Tibetan sheep. Concurrently, hematoxylin and eosin staining, alongside muscle fiber analysis, confirmed pronounced morphological differences in muscle tissue between sheep of varying conformation. Therefore, transcriptome and proteomics were performed on the longest dorsi muscle from large and small Tibetan sheep of both sexes. The transcriptome, together with weighted gene co-expression network analysis (WGCNA), identified VEPH1 and PRKG1 as core genes regulating body characteristics in Tibetan sheep through their involvement in the PI3K-Akt signaling pathway and pathways related to fat deposition. The integrative analyses demonstrated significantly different expression of CARNS1 and CRYAB at both transcriptional and protein levels between the muscles of large- and small-sized Tibetan sheep of both sexes, suggesting their importance in body size traits by influencing muscle morphology. This study provides valuable genomic resources that advance sheep genetics research.

GWAS↗

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↗

PubMed2025

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19.

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 and donor lung tissue with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage. We identify changes in cellular composition across progressive damage, including waves of molecularly distinct macrophages and depletion of epithelial and endothelial populations. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early damage, and fibrosis-related collagens in late damage. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early steps of alveolar damage. These results provide a comprehensive, spatially resolved atlas of alveolar damage progression in COVID-19, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways in severe disease.

COVID-19↗

PubMed2025

RNAcare: integrating clinical data with transcriptomic evidence using rheumatoid arthritis as a case study.

BACKGROUND: Gene expression analysis is a crucial tool for uncovering the biological mechanisms that underlie differences between patient subgroups, offering insights that can inform clinical decisions. However, despite its potential, gene expression analysis remains challenging for clinicians due to the specialised skills required to access, integrate, and analyse large datasets. Existing tools primarily focus on RNA-Seq data analysis, providing user-friendly interfaces but often falling short in several critical areas: they typically do not integrate clinical data, lack support for patient-specific analyses, and offer limited flexibility in exploring relationships between gene expression and clinical outcomes in disease cohorts. Users, including clinicians with a general knowledge of transcriptomics, however, who may have limited programming experience, are increasingly seeking tools that go beyond traditional analysis. To overcome these issues, computational tools must incorporate advanced techniques, such as machine learning, to better understand how gene expression correlates with patient symptoms of interest. RESULTS: Our RNAcare platform, addresses these limitations by offering an interactive and reproducible solution specifically designed for analysing transcriptomic data from patient samples in a clinical context. This enables researchers to directly integrate gene expression data with clinical features, perform exploratory data analysis, and identify patterns among patients with similar diseases. By enabling users to integrate transcriptomic and clinical data, and customise the target label, the platform facilitates the analysis of the relationships between gene expression and clinical symptoms like pain and fatigue. This allows users to generate hypotheses and illustrative visualisations/reports to support their research. As proof of concept, we use RNAcare to link inflammation-related genes to pain and fatigue in rheumatoid arthritis (RA) and detect signatures in the drug response group, confirming previous findings. CONCLUSION: We present a novel computational platform allowing the interpretation of clinical and transcriptomics data in real-time. The platform can be used for data generated by the user, such as the patient data presented here or using published datasets. The platform is available at https://rna-care.mvls.gla.ac.uk/ , and its source code is https://github.com/sii-scRNA-Seq/RNAcare/ .

Humans↗

PubMed2002

Sugar-coated microarrays: a novel slide surface for the high-throughput analysis of glycans.

The development of DNA and protein microarrays represents a significant advance in transcriptomics and proteomics research. Such arrays allow the high-throughput, parallel analysis of protein occurrence and interactions and gene expression. However, this advance has not been matched by equivalent technology for analysis of glycomes. One reason for this is that compared to proteins, it is difficult to reliably immobilise populations of chemically and structurally diverse glycans. We describe the development of a new microarray slide surface to which diverse glycan structures can be directly immobilised without prior derivatisation of the slide surface or any modification of the arrayed samples. The slides can be used to produce comprehensive microarrays of carbohydrates, glycoproteins and proteoglycans using isolated samples or cell extracts. Using standard microarray equipment, a series of carbohydrate microarrays were generated and probed with a panel of monoclonal antibodies with specificities for glycan epitopes. The arrays were highly reproducible, stable, and could be stored dry for several months. Glycans play central roles in development, carcinogenesis, cell adhesion, and immunity and are increasingly the subject of therapeutic approaches. We anticipate that the development of carbohydrate microarrays will be important for the high-throughput analysis of glycans and their molecular interactions.

Animals↗

PubMed2026

Cell Type-Resolved Causal Inference and Spatial Transcriptomic Integration Reveal Immune-Specific Genetic Drivers of Autoimmune and Malignant Thyroid Disease.

BACKGROUND: Thyroid diseases, including autoimmune thyroid disease (AITD) and thyroid cancer, are characterized by immune dysregulation, yet the cell type-specific genetic mechanisms underlying these conditions remain poorly understood. Most genome-wide association studies (GWAS) have relied on bulk tissue expression quantitative trait loci (eQTL), which cannot resolve the heterogeneity of immune cell populations. METHODS: We performed two-sample Mendelian randomization (MR) analyses using single-cell cis-eQTLs from 14 immune cell subtypes (OneK1K cohort) as instrumental variables against GWAS summary statistics for four thyroid outcomes: autoimmune hyperthyroidism, autoimmune hypothyroidism, thyroid cancer and autoimmune thyroiditis. Causal associations were validated through Bayesian colocalization, phenome-wide association analysis (PheWAS) and multi-layered transcriptomic validation encompassing spatial transcriptomics of AITD tissue (GSE248205), bulk RNA-seq of thyroid cancer (GSE3678) and single-cell RNA-seq of thyroid tumours (GSE250521). gsMap spatial LD score regression was applied to map disease heritability onto spatial tissue architecture. RESULTS: We identified six Bonferroni-significant causal gene-cell type pairs for autoimmune hyperthyroidism, including protective effects of ABHD16A in naïve/immature B cells (OR = 0.440), HIST1H3H in CD8 NC T cells (OR = 0.324), HMGN4 in NK recruiting cells (OR = 0.556) and ZKSCAN4 in CD8 S100B T cells (OR = 0.427), with five pairs showing strong colocalization (PP.H4 ≥ 86%). Three pairs reached significance for autoimmune hypothyroidism, including a risk association of HLA-F in CD4 NC T cells (OR = 1.139). For autoimmune thyroiditis, FAM134B/RETREG1 showed consistent suggestive protective associations across both CD4 and CD8 NC T cells (PP.H4 ≥ 90% for both), suggesting a possible involvement of ER phagy regulation in thyroiditis susceptibility. Thyroid cancer showed a suggestive association with HLA-G in classical monocytes (OR = 1.899, PP.H4 = 53%). Spatial transcriptomic validation demonstrated progressive immune infiltration from control tissue to Graves' disease to Hashimoto's thyroiditis (7.7%-15.7%, 46.1%-54.1%, respectively) and strong spatial correlation between target gene expression and corresponding cell type enrichment (e.g., plasma cell-HLA-DQB1: r = 0.491, p < 10-300). HLA-G was independently validated in thyroid cancer bulk (log2fc = 0.542, p = 9.51 × 10-3, AUC = 0.857) and single-cell datasets. PheWAS revealed no significant associations detected for the core candidates. gsMap identified significant enrichment of autoimmune hypothyroidism heritability in gastrointestinal tract, adrenal gland and adipose tissue (all Bonferroni p < 0.002). CONCLUSIONS: This study establishes a multi-scale analytical framework integrating cell type-resolved genetic inference with spatial tissue validation, revealing distinct immunogenetic architectures underlying autoimmune versus malignant thyroid disease. Protective genetic programs in autoimmune hyperthyroidism converge on chromatin remodelling (HIST1H3H, HMGN4, ZKSCAN4) and lipid metabolism (ABHD16A) across lymphocyte subsets, whereas thyroid cancer risk involves immune escape mediated by HLA-G in myeloid cells. The ER-phagy receptor RETREG1 represents a candidate pathway warranting further investigation in autoimmune thyroiditis. These findings provide genetically supported, cell type-specific therapeutic targets and demonstrate a generalizable strategy for dissecting the immune-mediated mechanisms of complex thyroid diseases.

Mendelian randomization↗

PubMed2026

Genome-Wide Identification and Expression Pattern of the ANK Gene Family in Sorghum bicolor Under Salt Stress.

The Ankyrin-repeat proteins (ANKs) play a key role in plant development and in response to abiotic stress. This research identified family members of the ANK genes in Sorghum bicolor at the whole-genome level, analyzed their sequence characteristics, evolutionary relationships, and expression patterns, and provided a scientific basis for elucidating the functionality of SbANK genes and for salt-tolerant breeding. Using bioinformatics methods, this study conducted a comprehensive identification of the SbANK gene family, analyzing its physicochemical properties, domain composition, chromosomal distribution, colinearity relationships, promoter cis-acting elements, and conserved protein motifs. Transcriptomic data and qRT-PCR were used to detect changes in their expression under salt stress. A total of 186 ANK family members were identified in the Sorghum bicolor genome, classified into 13 subfamilies and unevenly distributed across 10 chromosomes. Intra-species colinearity analysis revealed 7 pairs of duplicated genes, while inter-species colinearity analysis showed that S. bicolor and Oryza sativa share 88 pairs of orthologs, far exceeding the number found in Arabidopsis thaliana (11 pairs). Promoter analysis indicated that SbANK genes are enriched with cis-acting elements associated with hormone responses (particularly MeJA elements, accounting for 51.7%) and stress responses (particularly anaerobic-inducible elements, accounting for 60.9%). Transcriptomic expression analysis revealed that SbANK genes exhibit distinct tissue specificity, with the ANK-IQ subfamily highly expressed in leaves and the ANK-M subfamily showing the most widespread response under salt stress. Expression levels of the 10 candidate genes showing the most significant responses to salt stress were analyzed using qRT-PCR. The results indicated that SbANK91, SbANK135, and SbANK136 were significantly upregulated under 200 mmol/L NaCl treatment. The SbANK family is distinguished by a large number of member genes and structural diversity, with the ANK-M subfamily being the primary group responding to salt stress. SbANK91, SbANK135, and SbANK136 are identified as putative candidate genes for salt stress responses.

Sorghum↗

PubMed2026

Crosstalk mediators implicated in the Stevens-Johnson Syndrome through gene regulatory network analysis.

Stevens-Johnson syndrome (SJS) is a rare and severe mucocutaneous disorder often triggered by medications or infections. Our previous research identified that four key genes, Ikzf1, Ptger3, Mavs, and Tlr3 are involved in SJS susceptibility and the conjunctival epithelial innate immune response, demonstrating their role in regulating interferon-stimulated genes. However, the interplay among these regulatory factors remains unclear. This study aimed to elucidate the crosstalk mechanisms between the pathways regulated by these four genes in conjunctival epithelial cells. We constructed a comprehensive gene regulatory network using transcriptomic data from murine conjunctival epithelial cells under 16 distinct conditions, including polyI:C stimulation across wild-type, knockout, and transgenic backgrounds for the key genes. A targeted network analysis systematically identified numerous candidate genes mediating the crosstalk between the regulatory pathways initiated by Ikzf1, Ptger3, Mavs, and Tlr3. The identified candidates suggest the involvement of diverse signaling pathways previously unlinked to SJS pathology. Our findings suggest that the pathogenesis of SJS may arise not from the dysfunction of isolated genes but from the disruption of a balance maintained by intricate pathway crosstalk.

Animals↗

PubMed2026

Increased expression of Ribonucleic acid export 1 (RAE1) gene promotes gastric carcinogenesis and is associated with Hippo signaling pathway.

BACKGROUND: Ribonucleic acid export 1 (RAE1) autoantibody may have good potential for early detection of gastric cancer (GC). However, the carcinogenicity of RAE1 in GC remains unknown. We aimed to explore the role and the potential mechanism for RAE1 in the carcinogenesis of GC. METHODS: Immunohistochemical assay was applied to analyze the expression of RAE1 in GC and precancerous lesion (PL) tissues and its relationship with clinical characteristics. The effects of RAE1 on proliferation, migration, apoptosis, and cell cycle were explored by constructing RAE1 knockdown and overexpression in GC cells. The effects of RAE1 knockdown on tumor growth were observed in a murine xenograft model. The signaling pathways involved in GC development that may be affected by RAE1 were investigated by transcriptome sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. RESULTS: Immunohistochemical expression of RAE1 was significantly higher in early GC patients than in PL and normal tissues, and the RAE1 expression was correlated with clinical stage (P<0.001). In vitro, knockdown of RAE1 inhibited the proliferation and migration of GC cells with promoted apoptosis and arrested cell cycle in the S phase, while overexpression of RAE1 showed the opposite trend. In vivo, knockdown of RAE1 inhibited the growth of subcutaneous graft tumors in mice. Transcriptome sequencing and subsequent analysis of RAE1 knockdown cells revealed that the Hippo signaling pathway was activated by RAE1 knockdown. CONCLUSIONS: RAE1 promotes GC cells proliferation and migration and is associated with the inhibition of the Hippo signaling pathway, and may be a potential biomarker for early diagnosis and treatment of GC.

Gastric cancer (GC)↗

PubMed2025

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2002

Oligonucleotide microarray analysis of gene expression in follicle-stimulating hormone-treated rat Sertoli cells.

Spermatogenesis requires the presence of functional somatic Sertoli cells in the seminiferous tubules of the testis. Sertoli cells provide support and factors necessary for the successful progression of germ cells into spermatozoa. Sertoli cells are regulated to a large degree by the glycoprotein hormone FSH, which is required for the testis to acquire full size and spermatogenic capacity. Signaling events initiated by the binding of FSH to its receptor lead to an alteration of Sertoli cell gene expression. To characterize the changes in gene expression in FSH-treated Sertoli cells, we used the mRNA from these cells to screen Affymetrix U34A rat GeneChip oligonucleotide microarrays. Sertoli cells from 20-d-old rats were cultured in the presence of 25 ng/ml ovine FSH. At 0, 2, 4, 8, and 24 h after the addition of FSH, total RNA was purified and used to prepare biotinylated target, which was hybridized to the U34A rat microarray containing approximately 9000 rat genes. Analysis identified 100-300 transcripts at each time point that were up-regulated or down-regulated by 2-fold or greater. Genes previously reported to be FSH or cAMP regulated in rat Sertoli cells were identified, in addition to numerous genes not reported to be expressed or FSH regulated in Sertoli cells. The expression patterns of five of these genes, encoding nerve growth factor inducible gene B, PRL-1, PC3 nerve growth factor-inducible antiproliferative putative secreted protein, diacylglycerol acyltransferase, and an expressed sequence tag, in FSH- and N,O'-dibutyryl cAMP-treated rat Sertoli cells were confirmed and characterized by Northern blot analysis. Thus, we have begun to define the transcriptome induced and repressed by FSH in rat Sertoli cells, and we have generated datasets of genes available for further analysis in regard to spermatogenesis and Sertoli cell signaling.

Acyltransferases↗

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

ORFannotate: reproducible coding sequence annotation of transcriptome assemblies.

SUMMARY: Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and do not reintegrate coding sequence (CDS) information back into transcript models, limiting their utility in long-read sequencing workflows where GTF/GFF annotations are the primary output. We present ORFannotate, a lightweight, GTF-native Python command-line tool that predicts ORFs from transcript annotations and reinserts precise, exon-aware CDS and UTR features into the original GTF/GFF file. In addition, ORFannotate provides biologically informative translational context by annotating Kozak sequence strength, detecting non-overlapping upstream ORFs (uORFs) with coding probabilities, characterising 5' and 3' untranslated regions (UTRs), and predicting nonsense-mediated decay (NMD) susceptibility. All annotations are consolidated in a transcript-level summary to support downstream analysis. By generating GTF files with accurate CDS annotations, ORFannotate facilitates reproducible analysis of both long- and short-read transcriptomes and integrates seamlessly with visualization tools, genome browsers, and comparative transcript analysis workflows. ORFannotate is fast, scalable and provides a practical solution for transcriptome annotation beyond coding potential prediction alone. AVAILABILITY AND IMPLEMENTATION: ORFannotate is implemented in Python and freely available under the GNU General Public License v3 (GPL-3.0) at: https://github.com/egustavsson/ORFannotate (DOI: https://doi.org/10.5281/zenodo.16812866).

Open Reading Frames↗

PubMed2003

A snapshot of the low temperature stress transcriptome of developing rice seedlings (Oryza sativa L.) via ESTs from subtracted cDNA library.

Rice (Oryza sativa L.) is sensitive to chilling particularly during early seedling development. Given the biochemical complexity of tolerance mechanisms, genetic potential for this trait depends on highly coordinated expression of many genes. We used a simple cDNA subtraction strategy to develop Expressed Sequence Tags (ESTs) that represent an important subset of cold stress-upregulated genes. The 3,084 subtracted cDNA clones represent a total of 1,967 unigenes from 1,354 singletons and 613 contigs. As expected in the developing seedlings, genes involved in basic cellular processes, i.e., metabolism, growth and development, protein synthesis, folding and destination, cellular transport, cell division and DNA replication were widely represented. Genes with stress-related and regulatory functions comprised 23.17% of the total ESTs. These categories included proteins with known function in cellular defenses against abiotic (drought, cold and salinity) and biotic (pathogen) stresses, and proteins involved in developmental and stress response signalling and transcription. Based on the types of genes represented, tolerance mechanisms rely on precise integration of developmental processes with stress-related responses. A large fraction of the ESTs (38.7%) represents unknown proteins. This EST library is a rich source of cold stress-related genes, and supplements for other publicly available libraries for comprehensive analysis of the stress-response transcriptome.

Cold Temperature↗