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At least 685 records · Page 38Linked to original sources
PubMed2025

CAFs activated by YAP1 upregulate cancer matrix stiffness to mediate hepatocellular carcinoma progression.

BACKGROUND: The stiffness of the matrix is closely related to the progression of hepatocellular carcinoma (HCC). Although direct targeting of stromal rigidity in HCC remains a clinical challenge, cancer-associated fibroblasts (CAFs) are considered key contributors to this process. Given the heterogeneity of CAFs, this study explored the relationship between specific CAF subsets and liver cancer matrix stiffness, aiming to identify novel therapeutic targets for HCC patients. METHODS: Single-cell sequencing datasets were leveraged to identify cell types within liver cancer and characterize the transcriptomic profiles of CAFs. Prognostic analysis, utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) liver cancer datasets, assessed the correlation between matrix stiffness-related genes and HCC patient outcomes. Pseudo-time analysis was applied to trace the developmental trajectories of CAFs. By calculating intercellular communication probabilities and analyzing transcription factor activity, the functions and interactions of different CAF subsets were elucidated. Gene Ontology (GO) analysis was used to explore the functional roles of CAFs in distinct Yes-associated protein 1 (YAP1) groups. Finally, cellular experiments and animal experiments were further conducted to validate the hypotheses of this study. RESULTS: This study identified CAF subpopulations based on single-cell sequencing data and analyzed transcriptional changes within these subpopulations. Key findings include the identification of collagen type I alpha 1 (COL1A1), collagen type III alpha 1 (COL3A1), and lysyloxidase (LOX) as pivotal node genes during CAF development. Moreover, the expression of matrix stiffness-related genes was inversely correlated with the prognosis of HCC patients. Notably, the YAP1-positive CAF subpopulation emerged as the primary contributor to matrix stiffness in liver cancer. This subpopulation upregulates the expression of matrix stiffness-related genes and promotes tumor progression by activating signaling pathways such as autophagy and GTPase activity regulation. Cellular experiments and animal studies further validated this conclusion. CONCLUSION: This single-cell analysis uncovered the functional roles of CAFs in liver cancer. The YAP1-positive CAF subpopulation, in particular, was shown to contribute to matrix stiffness by upregulating the expression of relevant genes and promoting tumor progression through the activation of specific signaling pathways.

Carcinoma, Hepatocellular↗
PubMed2025

Proper 5'-3' cotranslational mRNA decay in yeast requires import of Xrn1 to the nucleus.

The budding yeast Xrn1 protein shuttles between the nucleus, where it stimulates transcription, and the cytoplasm, where it executes the major cytoplasmic mRNA decay. In the cytoplasm, apart from catalyzing 5'→3' decay onto non translated mRNAs, Xrn1 can follow the last translating ribosome to degrade the decapped mRNA template, a process known as "cotranslational mRNA decay". We have previously observed that the import of Xrn1 to the nucleus is required for efficient cytoplasmic mRNA decay. Here by using an Xrn1 mutant that cannot enter the nucleus, but is otherwise functional in ribonuclease activity, we show that nuclear import is necessary for proper global cotranslational decay of mRNAs along coding regions and also affects degradation in the of 5' region of a large group of mRNAs, which comprise about 20% of the transcriptome. Furthermore, a principal component analysis of the genomic datasets of this mutant and other Xrn1 mutants also shows that lack of a cytoplasmic 5'→3' exoribonuclease is the primary cause of the physiological defects seen in a xrn1Δ mutant, but also suggests that Xrn1 import into the nucleus is necessary for its full in vivo functions.

Exoribonucleases↗
PubMed2002

Proteomic approaches to central nervous system disorders.

The discovery, design and evaluation of new medicines is critically dependent on the elucidation of protein mechanisms involved in human diseases. Since the proteome of a cell or tissue is not a simple reflection of its transcriptome, direct protein-based analysis is needed. Advances in proteomic technologies are improving the analysis of membrane proteins and signaling complexes with increased speed and molecular detail. Changes in protein isoforms due to post-translational modifications, such as phosphorylation induced by cell signaling events and alternative splice forms of receptors, may be mapped to an altered protein expression pattern in clinically relevant cell populations with a causative or diagnostic disease link. A CNS proteome database derived from primary human tissues may avoid ambiguities of experimental models. It will also accelerate the development of more specific diagnostic and prognostic disease markers as well as new selective therapeutics. Proteomics is also being applied to resolve in silico gene prediction uncertainties by direct open reading frame verification. These advances hold great promise for improvements in the understanding, diagnosis and therapy of central nervous system disorders.

Biomarkers↗
PubMed2001

Transcriptome of a mouse kidney cortical collecting duct cell line: effects of aldosterone and vasopressin.

Aldosterone and vasopressin are responsible for the final adjustment of sodium and water reabsorption in the kidney. In principal cells of the kidney cortical collecting duct (CCD), the integral response to aldosterone and the long-term functional effects of vasopressin depend on transcription. In this study, we analyzed the transcriptome of a highly differentiated mouse clonal CCD principal cell line (mpkCCD(cl4)) and the changes in the transcriptome induced by aldosterone and vasopressin. Serial analysis of gene expression (SAGE) was performed on untreated cells and on cells treated with either aldosterone or vasopressin for 4 h. The transcriptomes in these three experimental conditions were determined by sequencing 169,721 transcript tags from the corresponding SAGE libraries. Limiting the analysis to tags that occurred twice or more in the data set, 14,654 different transcripts were identified, 3,642 of which do not match known mouse sequences. Statistical comparison (at P < 0.05 level) of the three SAGE libraries revealed 34 AITs (aldosterone-induced transcripts), 29 ARTs (aldosterone-repressed transcripts), 48 VITs (vasopressin-induced transcripts) and 11 VRTs (vasopressin-repressed transcripts). A selection of the differentially-expressed, hormone-specific transcripts (5 VITs, 2 AITs and 1 ART) has been validated in the mpkCCD(cl4) cell line either by Northern blot hybridization or reverse transcription-PCR. The hepatocyte nuclear transcription factor HNF-3-alpha (VIT39), the receptor activity modifying protein RAMP3 (VIT48), and the glucocorticoid-induced leucine zipper protein (GILZ) (AIT28) are candidate proteins playing a role in physiological responses of this cell line to vasopressin and aldosterone.

Aldosterone↗
PubMed2026

Single-cell transcriptomics reveals that air-liquid interface culture promotes goblet cell differentiation and inhibits glycolysis in organoid cell monolayers.

Faithfully recapitulating the cellular heterogeneity of the intestinal epithelium is essential when using organoid models. Air-liquid interface (ALI) culture has been shown to promote secretory cell differentiation, but its impact on gene expression in each epithelial cell type remains unclear. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize the cellular heterogeneity of rabbit cecum-derived organoid monolayers grown under immerged or ALI conditions. We then compared these organoid cell type-specific gene expression profiles to a scRNA-seq atlas of the rabbit cecal epithelium in vivo. We selected the rabbit model notably because, unlike mice, it possesses BEST4+ epithelial cells, a newly discovered subset of mature absorptive cells. Our analysis revealed a high degree of transcriptomic similarity between in vivo and organoid-derived stem and transit-amplifying cells. ALI culture markedly enhanced the differentiation of the secretory lineage, especially goblet cells, whose transcriptome closely resembled that of in vivo goblet cells. Furthermore, ALI was the only condition allowing the detection of enteroendocrine cells. BEST4+ cells, however, were absent from organoids in immerged or ALI conditions despite their presence in vivo. In addition, ALI culture led to a consistent downregulation of hypoxia and glycolysis-associated genes across all cell types, which suggests a metabolic shift likely driven by increased oxygen availability in ALI conditions. Cell-cell communication analyses further indicated that ALI more closely mirrored in vivo patterns than immerged condition. Altogether, these results demonstrate that ALI culture allows for better recapitulation of the in vivo cellular heterogeneity and molecular signatures of the intestinal epithelium.NEW & NOTEWORTHY Using single-cell RNA sequencing, this study shows that air-liquid interface (ALI) culture enhances secretory lineage differentiation of intestinal organoid cell monolayers and improves transcriptomic similarity to the native epithelium. ALI reduced hypoxia-associated gene expression and better recapitulates in vivo-like cell-cell interactions, supporting its value for modeling intestinal epithelial heterogeneity in organoids.

Animals↗
PubMed2026

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗
PubMed2003

The genetic architecture of odor-guided behavior in Drosophila: epistasis and the transcriptome.

We combined transcriptional profiling and quantitative genetic analysis to elucidate the genetic architecture of olfactory behavior in Drosophila melanogaster. We applied whole-genome expression analysis to five coisogenic smell-impaired (smi) mutant lines and their control. We used analysis of variance to partition variation in transcript abundance between males and females and between smi genotypes and to determine the genotype-by-sex interaction. A total of 666 genes showed sexual dimorphism in transcript abundance, and 530 genes were coregulated in response to one or more smi mutations, showing considerable epistasis at the level of the transcriptome in response to single mutations. Quantitative complementation tests of mutations at these coregulated genes with the smi mutations showed that in most cases (67%) epistatic interactions for olfactory behavior mirrored epistasis at the level of transcription, thus identifying new candidate genes regulating olfactory behavior.

Animals↗
PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗
PubMed2000

Operomics: molecular analysis of tissues from DNA to RNA to protein.

The identification of coding sequences in a number of species, including human in the near future, has ushered in the post-genome era. In this era, technologies are becoming available that allow the profiling of tissues and cell populations at the genomic, transcriptomic and proteomic levels. The molecular analysis of tissues at all three levels has been referred to as operomics. This review covers some basic technologies for operomics and their application to some lymphoid disorders. It is proposed that no one type of analysis is fully informative and that information that can be derived from the different compartments encompassed in operomics is complementary. Prospects for introducing such profiling technologies into the clinical laboratory will depend on their robustness, their user friendliness and the clinical relevance of the added information they provide, which cannot be captured through other technologies in use in the clinical laboratory.

Genomics↗
PubMed2002

Transcriptomics in predictive toxicology.

Once again, genomics is about to change drug development. Following its major impact on target discovery and assay development, which increased the number of compounds at early stages of the process, genomics is now zeroing in on the prediction of potential toxicological problems of compounds. Toxicogenomics is the analysis of toxicological processes at the transcriptome level of a target organ or cell. By simultaneously monitoring the effect of a compound on the transcription levels of hundreds to thousands of genes, toxicogenomics can provide an enormous amount of data. This data bears information on the way in which compounds act at the molecular level, reaching far beyond the mere conclusion of whether or not a particular toxicological outcome is elicited. By compiling transcription profiles for well-known toxicants, we are beginning to learn how to analyze this novel type of data in the context of mechanistic and predictive toxicology.

Animals↗
PubMed2025

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

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

Humans↗
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↗
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

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&#x2009;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&#xa0;and donor lung&#xa0;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↗