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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↗

PubMed2005

Iron-regulated transcription and capsule formation in the fungal pathogen Cryptococcus neoformans.

Cryptococcus neoformans is the leading cause of fungal meningitis in humans. Production of a polysaccharide capsule is a key virulence property for the fungus and capsule synthesis is regulated by iron levels. Given that iron acquisition is an important aspect of virulence for many pathogens, we employed serial analysis of gene expression (SAGE) to examine the transcriptome under iron-limiting and iron-replete conditions. Initially, we demonstrated by SAGE and Northern analysis that iron limitation results in an elevated transcript level for the CAP60 gene that is required for capsule production. We also identified genes encoding putative components for iron transport and homeostasis, including the FTR1 (iron permease) gene, with higher transcript levels in the low-iron condition. An FTR1 disruption mutant grows more slowly than wild-type cells in low-iron medium, and shows delayed growth and altered capsule regulation in iron-replete medium. Iron deprivation also resulted in elevated SAGE tags for putative extracellular mannoproteins and the GPI8 gene encoding a glycosylphosphatidylinositol (GPI) transamidase. The GPI8 gene appears to be essential while disruption of the CIG1 gene encoding a mannoprotein resulted in impaired growth in low-iron medium and altered capsule response to the iron-replete condition. Additionally, we found that iron-replete conditions led to elevated transcripts for genes for iron storage, nitrogen metabolism, glycolysis, mitochondrial function, lipid metabolism and calmodulin-calcineurin signalling. Overall, these studies provide the first view of the C. neoformans transcriptional response to different iron levels.

Bacterial Capsules↗

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↗

PubMed2006

From genomes to function: haloarchaea as model organisms.

Haloarchaea are adapted to high-salt environments and accumulate equally high salt concentrations in the cytoplasm. The genomes of representatives of six haloarchaeal genera have been fully or partially sequenced, allowing the analysis of haloarchaeal properties in silico. Transcriptome and proteome analyses have been established for Halobacterium salinarum and Haloferax volcanii. Genetic systems are available including methods that allow the fast in-frame deletion or modification of chromosomal genes. The high-efficiency transformation system of Hf. volcanii allows the isolation of genes essential for a biological process by complementation of loss-of-function mutants. For the analysis of haloarchaeal biology many molecular genetic, biochemical, structural and cell biological methods have been adapted to application at high salt concentrations. Recently it has become clear that several different mechanisms allow the adaptation of proteins to the high salt concentration of the cytoplasm. Taken together, the wealth of techniques available make haloarchaea excellent archaeal model species.

Adaptation, Physiological↗

PubMed2006

In silico assessment of gene function involved in cysteine biosynthesis in Arabidopsis: expression analysis of multiple isoforms of serine acetyltransferase.

In plants, the inorganic sulfur is first fixed into cysteine by the cysteine biosynthetic pathway. This biosynthetic pathway of cysteine involves several enzymatic reactions. In Arabidopsis thaliana, multiple isoforms seem to participate in each enzymatic step for cysteine biosynthesis. To obtain more insights on the specific role of each isoform involved in the cysteine biosynthesis, in silico analysis of these isoforms using Arabidopsis expressed sequence tags (EST) database was carried out. This EST database analysis revealed distinct population distribution of ESTs among multiple isoforms, suggesting that each isoform has its particular expression pattern, presumably associated with its specific role in cysteine biosynthesis. As another in silico analysis, co-expression analysis of genes involved in sulfur metabolism in Arabidopsis was performed using a public transcriptome database of DNA microarrays. This co-expression analysis also suggested specific function and co-regulation of some isoform genes for cysteine biosynthesis by consideration on the clustering of co-expressed genes. From the results of sensitivity to feedback regulation, subcellular localization and expression of mRNA analyses, each serine acetyltransferase (SATase) isoform seems to have its specific role for cysteine biosynthesis. Similar expression patterns were observed between the experimental results of expression data for SATase isoforms and the in silico results of "digital northern" analysis using EST database.

Arabidopsis↗

PubMed2004

Identifying secretomes in people, pufferfish and pigs.

The proteins processed by the secretory pathway (secretome) are critical players in the development of multi-cellular eukaryotic organisms but have yet to be comprehensively studied at the genomic level. In this study, we use the Target P algorithm to predict human (13-20% of proteins found in individual datasets) and Fugu (14%) secretomes based on analysis of their nearly complete proteomes. We combine internal processing with prediction software to automate secreted protein identification and overcome one of the major challenges associated with EST data: identification of the minority of clones that encode N-terminally-complete proteins. We discuss the use of these methods to predict secreted proteins in EST-based consensus sequence sets, and we validate these predictions using an assay for cell-free cotranslational translocation. Analysis of TIGR Porcine Gene Index 4.0 as a test dataset resulted in the identification of 352 N-terminally-complete, putative secreted proteins. In functional agreement with our predictions, 34 of 40 (85%) of these cDNAs were verified to be cotranslationally translocated in an in vitro translation system. The methods developed here are specifically designed to accept partial open reading frames and improve secreted protein predictions in eukaryotic transcriptomes, and are valuable for the analysis and annotation of eukaryotic EST databases.

Algorithms↗

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↗

PubMed2005

Transcriptional profiling of mefloquine-induced disruption of calcium homeostasis in neurons in vitro.

Mefloquine is associated with adverse neurological effects that are mediated via unknown mechanisms. Recent in vitro studies have shown that mefloquine disrupts neuronal calcium homeostasis via liberation of the endoplasmic reticulum (ER) store and induction of calcium influx across the plasma membrane. In the present study, global changes in gene expression induced in neurons in response to mefloquine-induced disruption of calcium homeostasis and appropriate control agents were investigated in vitro using Affymetrix arrays. The mefloquine transcriptome was found to be enriched for important regulatory sequences of the unfolded protein response and the drug was also found to induce key ER stress proteins, albeit in a manner dissimilar to, and at higher equivalent concentrations than, known ER-tropic agents like thapsigargin. Mefloquine also down-regulated several important functional categories of genes, including transcripts encoding G proteins and ion channels. These effects may be related to intrusion of extracellular calcium since they were also observed after glutamate, but not thapsigargin, hydrogen peroxide, or low-dose mefloquine treatment. Mefloquine could be successfully differentiated from other treatments on the basis of principle component analysis of its "calcium-relevant" transcriptome. These data may aid interpretation of expression of results from future in vivo studies.

Animals↗

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↗

PubMed2005

The study of metabolic pathways in tumors based on the transcriptome.

DNA microarray technology revolutionized gene-expression analysis in molecular biology to observe patterns of gene expression in genomic scale. We review the biological aspects of genome-wide gene-expression activity in tumors specially focusing on the analysis of enzyme coding genes. First, the methods for analyzing gene-expression data for the study of metabolome in silico are discussed showing SV40T antigen expressing liver tumor data as an example. Next, an application for tumor metabolome analysis utilizing a reference set of gene-expression profiles is shown.

Animals↗

PubMed2006

Transcriptome characterization of human mammary cell lines expressing different levels of ERBB2 by serial analysis of gene expression.

Over-expression of ERBB2, a member of the family of transmembrane receptor tyrosine kinases, occurs in 15-30% of primary breast tumors and is associated with poor prognosis and chemoresistance to a variety of anticancer drugs. In this study, aiming to identify differentially-expressed genes involved in erbB2-mediated transformation of the breast, we generated SAGE libraries from two human mammary cell lines, derived from normal luminal cells, expressing different levels of erbB2. The parental cell line HB4a expresses basal levels and the C5.2 expresses high levels of erbB2. A total of 161,632 tags was generated by sequencing, 81,684 from HB4a cells (30,854 unique tags) and 79,948 from C5.2 cells (30,568 unique tags). The comparison between the HB4a and C5.2 libraries revealed 334 distinct transcripts more expressed in HB4a cells and 328 distinct transcripts more expressed in C5.2 cells. The expression pattern of some of these transcripts was further validated by RT-PCR. The C5.2 cell line, which over-express ERBB2, showed in comparison to HB4a cells a higher percentage of genes involved in transport, RNA processing, apoptosis and protein folding. A higher percentage of the genes more expressed in HB4a cells compared to C5.2 were found to be involved in signal transduction and cytoskeleton organization. The use of SAGE analysis allowed us to identify a significant number of genes implicated in different cellular pathways up- or down-regulated in the presence of ERBB2 over-expression, including genes not previously implicated in breast cancer that could be considered as potential candidate markers for prognosis and therapy.

Breast↗

PubMed2003

Finding unexpected patterns in microarray data.

We describe the performance of a protocol based on the sequential application of unsupervised and supervised methods to analyze microarray samples defined by a combination of factors. Correspondence analysis is used to visualize the emerging patterns of three set of novel or previously published data: photoreceptor mutants of Arabidopsis grown under different light/dark conditions, Arabidopsis exposed to different types of biotic and abiotic stress, and human acute leukemia. We find, for instance, that light has a dramatic effect on plants despite the absence of the four major photoreceptors, that bacterial-, fungal-, and viral-induced responses converge at later stages of attack, and that sample preparation procedures used in different hospitals have large effects on transcriptome patterns. We use canonical discriminant analysis to identify the genes associated with these patters and hierarchical clustering to find groups of coregulated genes that are easily visualized in a second round of correspondence analysis and ordered tables. The unconventional combination of standard descriptive multivariate methods offers a previously unrecognized tool to uncover unexpected information.

Arabidopsis↗

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↗

PubMed2006

Profiling Caenorhabditis elegans non-coding RNA expression with a combined microarray.

Small non-coding RNAs (ncRNAs) are encoded by genes that function at the RNA level, and several hundred ncRNAs have been identified in various organisms. Here we describe an analysis of the small non-coding transcriptome of Caenorhabditis elegans, microRNAs excepted. As a substantial fraction of the ncRNAs is located in introns of protein-coding genes in C.elegans, we also analysed the relationship between ncRNA and host gene expression. To this end, we designed a combined microarray, which included probes against ncRNA as well as host gene mRNA transcripts. The microarray revealed pronounced differences in expression profiles, even among ncRNAs with housekeeping functions (e.g. snRNAs and snoRNAs), indicating distinct developmental regulation and stage-specific functions of a number of novel transcripts. Analysis of ncRNA-host mRNA relations showed that the expression of intronic ncRNA loci with conserved upstream motifs was not correlated to (and much higher than) expression levels of their host genes. Even promoter-less intronic ncRNA loci, though showing a clear correlation to host gene expression, appeared to have a surprising amount of 'expressional freedom', depending on host gene function. Taken together, our microarray analysis presents a more complete and detailed picture of a non-coding transcriptome than hitherto has been presented for any other multicellular organism.

Animals↗

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↗