Search Results (68)

The adult lumbar spinal cord plays a critical role in locomotor control and somatosensory integration, whose transcriptional architecture under physiological conditions has been characterized in various studies with restricted numbers of individuals (up to four). Here, we present an integrative single-nucleus RNA sequencing (snRNA-seq) atlas of the healthy adult mouse lumbar spinal cord, assembled from over 86,000 nuclei from 16 samples across five public datasets. Using a harmonized computational pipeline, we identify all major spinal cell lineages and resolve 17 transcriptionally distinct neuronal subtypes. A central novelty of our approach is the systematic inclusion of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) and pseudogenes. By comparing transcriptomic analyses based on coding-only, non-coding-only, and combined gene sets, we show that ncRNAs, despite accounting to a 10% of the recorded information of each cell, contribute to cell type-specific signatures. This resource offers a high-resolution, ncRNA-inclusive reference for the adult spinal cord and provides a foundation for future studies on spinal plasticity, injury, and regeneration. Full article

Drought is the single largest abiotic threat to soybean yield, yet the lectin genes that mediate drought perception and signaling in this crop have never been systematically mapped. We reanalyzed the public RNA-seq dataset GSE237798 (Williams 82 leaves, 7-day water withdrawal) with an updated fastp–HISAT2–featureCounts–DESeq2 pipeline and a curated catalog of 359 soybean lectin loci. Of the 127 lectin transcripts showing any drought-dependent shift, only 15 were stringently differentially expressed with substantial fold changes: 7 were upregulated and 8 downregulated. These genes span four families, GNA, legume, LysM and Nictaba-related lectins, and are heavily biased toward lectin receptor-like kinases (11 of 15), pinpointing the plasma membrane as the main control node. Gene Ontology enrichment highlights protein autophosphorylation and signal-transduction terms, and the inspection of AlphaFold models together with established lectin knowledge indicates that G- and L-type lectin domains have largely lost canonical carbohydrate-binding residues, whereas LysM and Nictaba proteins retain conserved folds compatible with ligand binding. The data expose a focused, modular lectin program rather than the broad activation often assumed: most soybean lectins stay silent under drought conditions, and only a defined subset toggles their expression, albeit mildly. Full article

Huanglongbing (HLB), caused mainly by Candidatus Liberibacter asiaticus (CLas), is a devastating disease threatening citrus production worldwide, leading to leaf mottling, fruit deformation, and significant yield losses. This study generated a comprehensive co-expression network analysis using RNA-seq data from 17 public datasets. Weighted gene co-expression network analysis (WGCNA) was applied to identify gene modules associated with citrus species, tissue types, and days post-infection (DPIs). These modules revealed significant enrichment in biological pathways related to stress responses, metabolic reprograming, ribosomal protein synthesis, chloroplast and plastid function, cellular architecture, and intracellular transport. The results offer a molecular framework for understanding HLB pathogenesis and host response. By elucidating module-specific functions and their correlation with species- and tissue-specific responses, this study provides a robust foundation for identifying key genetic targets. These insights facilitate breeding programs focused on developing HLB-tolerant citrus cultivars, contributing to the long-term sustainability and resilience of global citrus production. Full article

Background: Sepsis is a life-threatening condition characterized by organ dysfunction due to an imbalanced immune response to infection, with high mortality. Ferroptosis, an iron-dependent cell death process, and cellular senescence, which exacerbates inflammation, have recently been implicated in sepsis pathophysiology. Methods: Weighted gene co-expression network analysis (WGCNA) was used to identify ferroptosis- and senescence-related gene modules in sepsis. Differentially expressed genes (DEGs) were analyzed using public datasets (GSE57065, GSE65682, and GSE26378). Receiver operating characteristic (ROC) analysis was performed to evaluate their diagnostic potential, while single-cell RNA sequencing (scRNA-seq) was used to assess their immune-cell-specific expression. Molecular docking was conducted to predict drug interactions with key proteins. Results: Five key genes (CD82, MAPK14, NEDD4, TXN, and WIPI1) were significantly upregulated in sepsis patients and highly correlated with immune cell infiltration. MAPK14 and TXN exhibited strong diagnostic potential (AUC = 0.983, 0.978). Molecular docking suggested potential therapeutic interactions with diclofenac, flurbiprofen, and N-acetyl-L-cysteine. Conclusions: This study highlights ferroptosis and senescence as critical mechanisms in sepsis and identifies promising biomarkers for diagnosis and targeted therapy. Future studies should focus on clinical validation and precision medicine applications. Full article

Background: Hodgkin lymphoma (HL) is a B-cell-derived malignancy and one of the most frequent types of lymphoma. The tumour cells typically exhibit multiple genomic alterations together with aberrantly activated signalling pathways, driven by paracrine and/or autocrine modes. SPP1 (alias osteopontin) is a cytokine acting as a signalling activator and has been connected with relapse in HL patients. To understand its pathogenic role, here, we investigated the mechanisms and function of deregulated SPP1 in HL. Methods: We screened public patient datasets and cell lines for aberrant SPP1 expression. HL cell lines were stimulated with SPP1 and subjected to siRNA-mediated knockdown. Gene and protein activities were analyzed by RQ-PCR, ELISA, Western blot, and immuno-cytology. Results: SPP1 expression was detected in 8.3% of classic HL patients and in HL cell line SUP-HD1, chosen to serve as an experimental model. The gene encoding SPP1 is located at chromosomal position 4q22 and is genomically amplified in SUP-HD1. Transcription factor binding site analysis revealed TALE and HOX factors as potential regulators. Consistent with this finding, we showed that aberrantly expressed PBX1 and HOXB9 mediate the transcriptional activation of SPP1. RNA-seq data and knockdown experiments indicated that SPP1 signals via integrin ITGB1 in SUP-HD1. Accordingly, SPP1 activated NFkB in addition to MAPK/ERK which in turn mediated the nuclear import of ETS2, activating oncogenic JUNB expression. Conclusions: SPP1 is aberrantly activated in HL cell line SUP-HD1 via genomic copy number gain and by homeodomain transcription factors PBX1 and HOXB9. SPP1-activated NFkB and MAPK merit further investigation as potential therapeutic targets in affected HL patients. Full article

Growth traits are among the most important economic phenotypes targeted in the genetic improvement of beef cattle. To understand the genetic basis of growth traits in Huaxi cattle, we performed a genome-wide association study (GWAS) on body weight, eye muscle area, and back fat thickness across five developmental stages in a population of 202 Huaxi cattle. Additionally, publicly available RNA-seq data from the longissimus dorsi muscle of both young and adult cattle were analyzed to identify key genes and genetic markers associated with growth in Huaxi cattle. In total, 7.19 million high-quality variant loci (SNPs and INDELs) were identified across all samples. In the GWAS, the three multilocus models (FarmCPU, MLMM, and BLINK) outperformed the conventional single-locus models (CMLM, GLM, and MLM). Consequently, GWAS analysis was conducted using multilocus models, which identified 99 variant loci significantly associated with growth traits and annotated a total of 83 candidate genes (CDGs). Additionally, 23 of the 83 CDGs overlapped with significantly differentially expressed genes identified from public RNA-seq datasets of longissimus dorsi muscle between young and adult cattle. Furthermore, gene functional enrichment (KEGG and GO) analyses revealed that over 30% of the pathways and GO terms were associated with muscle development and fat deposition, crucial factors for beef production. Specifically, key genes identified included MGLL, SGMS1, SNX29 and AKAP6, which are implicated in lipid metabolism, adipogenesis, and muscle growth. In summary, this study provides new insights into the genetic mechanisms underlying growth traits in Huaxi cattle and presents promising markers for future breeding improvements. Full article

Clock genes regulate physiological and metabolic processes by responding to changes in environmental light and temperature, and genetic variations in these genes may facilitate environmental adaptation, offering opportunities for resilience to climate change. However, the genetic and molecular mechanisms remain unclear in marine organisms. In this study, we investigated the role of a key clock gene, the circadian locomotor output cycles kaput (Clock), in thermal adaptation using DNA affinity purification sequencing (DAP-Seq) and RNA interference (RNAi)-based transcriptome analysis. In cold-adapted Crassostrea gigas and warm-adapted Crassostrea angulata, Clock was subject to environmental selection and exhibited contrasting expression patterns. The transcriptome analysis revealed 2054 differentially expressed genes (DEGs) following the knockdown of the Clock expression, while DAP-Seq identified 150,807 genes regulated by Clock, including 5273 genes located in promoter regions. The combined analyses identified 201 overlapping genes between the two datasets, of which 98 were annotated in public databases. These 98 genes displayed distinct expression patterns in C. gigas and C. angulata under heat stress, which were potentially regulated by Clock, indicating its role in a molecular regulatory network that responds to heat stress. Notably, a heat-shock protein 70 family gene (Hsp12b) and a tripartite motif-containing protein (Trim3) were significantly upregulated in C. angulata but showed no significant changes in C. gigas, further highlighting their critical roles in thermal adaptation. This study preliminarily constructs a thermal regulatory network involving Clock, providing insights into the molecular mechanisms of clock genes in thermal adaptation. Full article

Background/Objectives: Vitamin D (VD) plays a crucial role in age-related diseases, and its influence on cellular senescence (CS) could help clarify its function in aging. Considering VD’s pleiotropic effects and the heterogeneity of CS. Methods: we utilized single-cell RNA sequencing (scRNA-seq) to explore these dynamics across multiple tissues. We analyzed three murine tissue datasets (bone, prostate, and skin) obtained from public repositories, enriching for senescence gene signatures. We then inferred gene regulatory networks (GRNs) at the tissue and cell-type levels and performed two cell communication analyses: one for senescent cells and another for interactions between senescent and non-senescent cells. Results: VD supplementation significantly decreased senescence scores in the skin (p = $3.96\times {10}^{-134}$) and prostate ($p=1.56\times {10}^{-34}$). GRN analysis of the prostate revealed an altered macrophage–fibroblast regulatory relationship. In bone, distinct aging-related modules emerged for different bone lineages. In skin, contrary differentiation patterns between suprabasal and basal cells were observed. The main VD-modulated pathways were involved in inflammation, extracellular matrix remodeling, protein metabolism, and translation. VD reduced fibroblast–macrophage interactions in the prostate and skin but increased overall cellular crosstalk in bone. Conclusions: Our findings demonstrate that VD alleviates CS burden across tissues by modulating inflammation and metabolic processes and promoting differentiation. Key aging-related genes modulated by VD were linked to anabolism and cellular differentiation, suggesting VD’s potential for therapeutic interventions targeting age-related diseases. Full article

Diabetic foot ulcers (DFUs) are a severe complication of diabetes mellitus (DM), which often lead to hospitalization and non-traumatic amputations in the United States. Diabetes prevalence estimates in South Texas exceed the national estimate and the number of diagnosed cases is higher among Hispanic adults compared to their non-Hispanic white counterparts. San Antonio, a predominantly Hispanic city, reports significantly higher annual rates of diabetic amputations compared to Texas. The late identification of severe foot ulcers minimizes the likelihood of reducing amputation risk. The aim of this study was to identify molecular factors related to the severity of DFUs by leveraging a multimodal approach. We first utilized electronic health records (EHRs) from two large demographic groups, encompassing thousands of patients, to identify blood tests such as cholesterol, blood sugar, and specific protein tests that are significantly associated with severe DFUs. Next, we translated the protein components from these blood tests into their ribonucleic acid (RNA) counterparts and analyzed them using public bulk and single-cell RNA sequencing datasets. Using these data, we applied a machine learning pipeline to uncover cell-type-specific and molecular factors associated with varying degrees of DFU severity. Our results showed that several blood test results, such as the Albumin/Creatinine Ratio (ACR) and cholesterol and coagulation tissue factor levels, correlated with DFU severity across key demographic groups. These tests exhibited varying degrees of significance based on demographic differences. Using bulk RNA-Sequenced (RNA-Seq) data, we found that apolipoprotein E (APOE) protein, a component of lipoproteins that are responsible for cholesterol transport and metabolism, is linked to DFU severity. Furthermore, the single-cell RNA-Seq (scRNA-seq) analysis revealed a cluster of cells identified as keratinocytes that showed overexpression of APOE in severe DFU cases. Overall, this study demonstrates how integrating extensive EHRs data with single-cell transcriptomics can refine the search for molecular markers and identify cell-type-specific and molecular factors associated with DFU severity while considering key demographic differences. Full article

Our study aimed to elucidate the mechanisms behind the interaction between calcium oxalate (CaOx) crystals and renal tubular epithelial cells through transcriptome sequencing analysis. HK-2 cells were stimulated with or without CaOx monohydrate crystals and subjected to RNA-seq to assess the effects of CaOx crystals on gene expression changes, key pathways, and molecular players during this interaction. A total of 629 differentially expressed genes (DEGs) were identified between the control group and experimental group, with 491 genes up-regulated and 138 down-regulated. Functional enrichment analysis indicated that the DEGs were significantly associated with endoplasmic reticulum stress (ERS) and unfolded protein response. To validate our findings, we compared our results with the public dataset GSE73680 and confirmed the increased expression of two ERS-related DEGs, CHAC1 and FGF21, in renal papillary tissues from patients with CaOx stones. Collectively, these findings suggest that ERS plays a crucial role in the crystal–cell interaction and highlight the potential for developing therapeutic strategies aimed at reducing CaOx stone formation by targeting ERS-related molecules and pathways. Full article

Single-cell RNA sequencing (scRNA-seq) is now a successful technology for identifying cell heterogeneity, revealing new cell subpopulations, and predicting developmental trajectories. A crucial component in scRNA-seq is the precise identification of cell subsets. Although many unsupervised clustering methods have been developed for clustering cell subpopulations, the performance of these methods is prone to be affected by dropout, high dimensionality, and technical noise. Additionally, most existing methods are time-consuming and fail to fully consider the potential correlations between cells. In this paper, we propose a novel unsupervised clustering method called scVGATAE (Single-cell Variational Graph Attention Autoencoder) for scRNA-seq data. This method constructs a reliable cell graph through network denoising, utilizes a novel variational graph autoencoder model integrated with graph attention networks to aggregate neighbor information and learn the distribution of the low-dimensional representations of cells, and adaptively determines the model training iterations for various datasets. Finally, the obtained low-dimensional representations of cells are clustered using kmeans. Experiments on nine public datasets show that scVGATAE outperforms classical and state-of-the-art clustering methods. Full article

Transcriptional regulatory networks (TRNs) associated with recombinant protein (rProt) synthesis in Yarrowia lipolytica are still under-described. Yet, it is foreseen that skillful manipulation with TRNs would enable global fine-tuning of the host strain’s metabolism towards a high-level-producing phenotype. Our previous studies investigated the transcriptomes of Y. lipolytica strains overproducing biochemically different rProts and the functional impact of transcription factors (TFs) overexpression (OE) on rProt synthesis capacity in this species. Hence, much knowledge has been accumulated and deposited in public repositories. In this study, we combined both biological datasets and enriched them with further experimental data to investigate an interplay between TFs and rProts synthesis in Y. lipolytica at transcriptional and functional levels. Technically, the RNAseq datasets were extracted and re-analyzed for the TFs’ expression profiles. Of the 140 TFs in Y. lipolytica, 87 TF-encoding genes were significantly deregulated in at least one of the strains. The expression profiles were juxtaposed against the rProt amounts from 125 strains co-overexpressing TF and rProt. In addition, several strains bearing knock-outs (KOs) in the TF loci were analyzed to get more insight into their actual involvement in rProt synthesis. Different profiles of the TFs’ transcriptional deregulation and the impact of their OE or KO on rProts synthesis were observed, and new engineering targets were pointed. Full article

Human tumors progress in part by accumulating epigenetic alterations, which include gains and losses of DNA methylation in different parts of the cancer cell genome. Recent work has revealed a link between these two opposite alterations by showing that DNA hypomethylation in tumors can induce the expression of transcripts that overlap downstream gene promoters and thereby induce their hypermethylation. Preliminary in silico evidence prompted us to investigate if this mechanism applies to the locus harboring AGO1, a gene that plays a central role in miRNA biogenesis and RNA interference. Inspection of public RNA-Seq datasets and RT-qPCR experiments show that an alternative transcript starting 13.4 kb upstream of AGO1 (AGO1-V2) is expressed specifically in testicular germ cells, and becomes aberrantly activated in different types of tumors, particularly in tumors of the esophagus, stomach, and lung. This expression pattern classifies AGO1-V2 into the group of “Cancer-Germline” (CG) genes. Analysis of transcriptomic and methylomic datasets provided evidence that transcriptional activation of AGO1-V2 depends on DNA demethylation of its promoter region. Western blot experiments revealed that AGO1-V2 encodes a shortened isoform of AGO1, corresponding to a truncation of 75 aa in the N-terminal domain, and which we therefore referred to as “∆NAGO1”. Interestingly, significant correlations between hypomethylation/activation of AGO1-V2 and hypermethylation/repression of AGO1 were observed upon examination of tumor cell lines and tissue datasets. Overall, our study reveals the existence of a process of interdependent epigenetic alterations in the AGO1 locus, which promotes swapping between two AGO1 protein-coding mRNA isoforms in tumors. Full article

To date, genomic and transcriptomic data on Coffea arabica L. in public databases are very limited, and there has been no comprehensive integrated investigation conducted on alternative splicing (AS). Previously, we have constructed and sequenced eighteen RNA-seq libraries of C. arabica at different ripening stages of fruit development. From this dataset, a total of 3824, 2445, 2564, 2990, and 3162 DSGs were identified in a comparison of different fruit ripening stages. The largest proportion of DSGs, approximately 65%, were of the skipped exon (SE) type. Biologically, 9 and 29 differentially expressed DSGs in the spliceosome pathway and carbon metabolism pathway, respectively, were identified. These DSGs exhibited significant variations, primarily in S1 vs. S2 and S5 vs. S6, and they involve many aspects of organ development, hormone transduction, and the synthesis of flavor components. Through the examination of research findings regarding the biological functions and biochemical pathways associated with DSGs and DEGs, it was observed that six DSGs significantly enriched in ABC transporters, namely, LOC113712394, LOC113726618, LOC113739972, LOC113725240, LOC113730214, and LOC113707447, were continually down-regulated at the fruit ripening stage. In contrast, a total of four genes, which were LOC113732777, LOC113727880, LOC113690566, and LOC113711936, including those enriched in the cysteine and methionine metabolism, were continually up-regulated. Collectively, our findings may contribute to the exploration of alternative splicing mechanisms for focused investigations of potential genes associated with the ripening of fruits in C. arabica. Full article

Accumulating evidence has revealed unexpected phenotypic heterogeneity and diverse functions of neutrophils in several diseases. Coronavirus disease (COVID-19) can alter the leukocyte phenotype based on disease severity, including neutrophil activation in severe cases. However, the plasticity of neutrophil phenotypes and their relative impact on COVID-19 pathogenesis has not been well addressed. This study aimed to identify and validate the heterogeneity of neutrophils in COVID-19 and evaluate the functions of each subpopulation. We analyzed public single-cell RNA-seq, bulk RNA-seq, and proteome data from healthy donors and patients with COVID-19 to investigate neutrophil subpopulations and their response to disease pathogenesis. We identified eight neutrophil subtypes: pro-neutrophil, pre-neutrophil, immature neutrophil, and five mature neutrophil subpopulations. The subtypes exhibited distinct features, including diverse activation signatures and multiple enriched pathways. The pro-neutrophil subtype was associated with severe and fatal disease, while the pre-neutrophil subtype was particularly abundant in mild/moderate disease. One of the mature neutrophil subtypes showed consistently large fractions in patients with different disease severity. Bulk RNA-seq dataset analyses using a cellular deconvolution approach validated the relative abundances of neutrophil subtypes and the expansion of pro-neutrophils in severe COVID-19 patients. Cell–cell communication analysis revealed representative ligand–receptor interactions among the identified neutrophil subtypes. Further investigation into transcription factors and differential protein abundance revealed the regulatory network differences between healthy donors and patients with severe COVID-19. Overall, we demonstrated the complex interactions among heterogeneous neutrophil subtypes and other blood cell types during COVID-19 disease. Our work has great value in terms of both clinical and public health as it furthers our understanding of the phenotypic and functional heterogeneity of neutrophils and other cell populations in multiple diseases. Full article