Analysis Of RNA Sequencing Data Research Articles

A multi-faceted approach to unravel coding and non-coding gene fusions and target chimeric proteins in ataxia

Ataxia represents a heterogeneous group of neurodegenerative disorders characterized by a loss of balance and coordination, often resulting from mutations in genes vital for cerebellar function and maintenance. Recent advances in genomics have identified gene fusion events as critical contributors to various cancers and neurodegenerative diseases. However, their role in ataxia pathogenesis remains largely unexplored. Our study Hdelved into this possibility by analyzing RNA sequencing data from 1443 diverse samples, including cell and mouse models, patient samples, and healthy controls. We identified 7067 novel gene fusions, potentially pivotal in disease onset. These fusions, notably in-frame, could produce chimeric proteins, disrupt gene regulation, or introduce new functions. We observed conservation of specific amino acids at fusion breakpoints and identified potential aggregate formations in fusion proteins, known to contribute to ataxia. Through AI-based protein structure prediction, we identified topological changes in three high-confidence fusion proteins—TEN1-ACOX1, PEX14-NMNAT1, and ITPR1-GRID2—which could potentially alter their functions. Subsequent virtual drug screening identified several molecules and peptides with high-affinity binding to fusion sites. Molecular dynamics simulations confirmed the stability of these protein-ligand complexes at fusion breakpoints. Additionally, we explored the role of non-coding RNA fusions as miRNA sponges. One such fusion, RP11-547P4-FLJ33910, showed strong interaction with hsa-miR-504-5p, potentially acting as its sponge. This interaction correlated with the upregulation of hsa-miR-504-5p target genes, some previously linked to ataxia. In conclusion, our study unveils new aspects of gene fusions in ataxia, suggesting their significant role in pathogenesis and opening avenues for targeted therapeutic interventions. Communicated by Ramaswamy H. Sarma

Integrated analysis of single-cell and bulk RNA sequencing data reveals the association between hypoxic tumor cells and exhausted T cells in predicting immune therapy response

Continuous stimulation of tumor neoantigens and various cytokines in the tumor microenvironment leads to T cell dysfunction, but the specific mechanisms by which these key factors are distributed among different cell subpopulations and how they affect patient outcomes and treatment response are incompletely characterized.By integrating single-cell and bulk sequencing data of non-small cell lung cancer patients, we constructed a clinical outcome-associated T cell exhaustion signature. We discovered a significant association between the T cell exhaustion state and tumor cell hypoxia. Hypoxic malignant cells were significantly correlated with the proportion of exhausted T cells, and they co-occurred in patients at advanced stage. By analyzing the ligand-receptor interactions between these two cell states, we observed that T cells were recruited towards tumor cells through production of chemokines such as CXCL16-CXCR6 axis and CCL3/CCL4/CCL5-CCR5 axis. Based on 15 immune checkpoint blockade (ICB)-treatment cohorts, we constructed an interaction signature that can be used to predict the response to immune checkpoint blockade therapy. Among genes composed of the signature, CXCR6 alone has similarly high prediction efficacy (Area Under Curve (AUC) = 1, 0.89 and 0.73 for GSE126044, GSE135222 and GSE93157, respectively) with the signature and thus could serve as a potential biomarker for predicting immunotherapy response.Together, we have discovered and validated a significant association between exhausted T cells and hypoxic malignant cells, elucidating key interaction factors that significantly associated with response to immunotherapy.

High CD133 expression in proximal tubular cells in diabetic kidney disease: good or bad?

BackgroundProximal tubular cells (PTCs) play a critical role in the progression of diabetic kidney disease (DKD). As one of important progenitor markers, CD133 was reported to indicate the regeneration of dedifferentiated PTCs in acute kidney disease. However, its role in chronic DKD is unclear. Therefore, we aimed to investigate the expression patterns and elucidate its functional significance of CD133 in DKD.MethodsData mining was employed to illustrate the expression and molecular function of CD133 in PTCs in human DKD. Subsequently, rat models representing various stages of DKD progression were established. The expression of CD133 was confirmed in DKD rats, as well as in human PTCs (HK-2 cells) and rat PTCs (NRK-52E cells) exposed to high glucose. The immunofluorescence and flow cytometry techniques were utilized to determine the expression patterns of CD133, utilizing proliferative and injury indicators. After overexpression or knockdown of CD133 in HK-2 cells, the cell proliferation and apoptosis were detected by EdU assay, real-time cell analysis and flow analysis. Additionally, the evaluation of epithelial, progenitor cell, and apoptotic indices was performed through western blot and quantitative RT-PCR analyses.ResultsThe expression of CD133 was notably elevated in both human and rat PTCs in DKD, and this expression increased as DKD progressed. CD133 was found to be co-expressed with CD24, KIM-1, SOX9, and PCNA, suggesting that CD133+ cells were damaged and associated with proliferation. In terms of functionality, the knockdown of CD133 resulted in a significant reduction in proliferation and an increase in apoptosis in HK-2 cells compared to the high glucose stimulus group. Conversely, the overexpression of CD133 significantly mitigated high glucose-induced cell apoptosis, but had no impact on cellular proliferation. Furthermore, the Nephroseq database provided additional evidence to support the correlation between CD133 expression and the progression of DKD. Analysis of single-cell RNA-sequencing data revealed that CD133+ PTCs potentially play a role in the advancement of DKD through multiple mechanisms, including heat damage, cell microtubule stabilization, cell growth inhibition and tumor necrosis factor-mediated signaling pathway.ConclusionOur study demonstrates that the upregulation of CD133 is linked to cellular proliferation and protects PTC from apoptosis in DKD and high glucose induced PTC injury. We propose that heightened CD133 expression may facilitate cellular self-protective responses during the initial stages of high glucose exposure. However, its sustained increase is associated with the pathological progression of DKD. In conclusion, CD133 exhibits dual roles in the advancement of DKD, necessitating further investigation.

A195 IL-13 DRIVES CROHN’S DISEASE ASSOCIATED-INTESTINAL FIBROSIS IN SHIP DEFICIENT MICE

Abstract Background Crohn’s disease (CD) is an immune-mediated disease characterized by chronic, relapsing and remitting, or progressive inflammation of the digestive tract. One in 3 people with CD will develop intestinal fibrosis requiring surgery within 10 years of diagnosis. Biological therapy is effective at reducing inflammation in CD and early and aggressive treatment with biologics will reduce the incidence of fibrosis. However, in children, for whom a step-up approach to therapy is used, and populations that are refractory to biological therapy; fibrosis remains a serious concern. Treatments are urgently needed as currently there are no treatments that target intestinal fibrosis directly in CD. Mice deficient in the Src homology 2 domain-containing inositolpolyphosphate 5’-phosphatase (SHIP-/-) develop spontaneous CD-like ileal inflammation and fibrosis. Fibrosis is dependent on PI3Kp110δ activity. IL-4 and IL-13 lead to downstream activation of PI3Kp110δ. Recent work in our lab has shown through pharmacological inhibition that the development of fibrosis in SHIP-/- mice is dependenet on IL-13 signaling, but not IL-4. Aims Aim 1: To determine whether genetic ablation of IL-13 prevents ileal fibrosis in SHIP-/- mice Aim 2: To determine the cellular source of IL-13 in the distal ileum of SHIP-/- mice Aim 3: To determine the cellular source of IL-13 in the distal ileum of individuals with CD Methods SHIP-/- mice were crossed with IL-13 deficient mice (IL13-/-) to generate SHIP+/+IL13+/+, SHIP+/+IL13-/-, SHIP-/-IL13+/+, and SHIP-/-IL13-/- mice. Measurements of ileal fibrosis included gross and histopathology, muscle thickening, and collagen accumulation (Masson’s trichrome staining for fibrosis). Single cell RNA sequencing (snRNA-seq) was performed on the distal ileum of SHIP-/- mice to determine the cellular source of IL-13. Previously published scRNA-seq data were analyzed to determine the cellular source of IL-13 in individuals with CD. Results Genetic ablation of IL-13 in SHIP-/- mice (SHIP-/-IL13-/-) reduced the development of ileal fibrosis. Analysis of single cell RNA sequencing data (scRNA seq) has revealed mast cells as the cellular source of IL-13 in the distal ileum of people with CD. Conclusions Mast cell derived IL-13 may be driving the development of intestinal fibrosis in CD. Our data suggest that an antibody-based biologic targeting IL-13 may be an effective strategy to prevent fibrosis in people with Crohn’s Disease. Funding Agencies CAG, CIHR

Genome assembly and transcriptomic analysis to elucidate the ability of Nasonovia ribisnigri to break host plant resistance.

Aphid genomic resources enable the study of complex life history traits and provide information on vector biology, host adaption and speciation. The currant-lettuce aphid (Nasonovia ribisnigri (Hemiptera: Aphididae) (Mosley)) is a cosmopolitan pest of outdoor lettuce (Lactuca sativa (Asterales: Asteraceae) (Linnaeus)). Until recently, the use of resistant cultivars was an effective method for managing N. ribisnigri. A resistant cultivar containing a single gene (Nr-locus), introduced in the 1980s, conferred complete resistance to feeding. Overreliance of this Nr-locus in lettuce resulted in N. ribisnigri's ability to break resistance mechanism, with first reports during 2003. Our work attempts to understand which candidate gene(s) are associated with this resistance-breaking mechanism. We present two de novo draft assembles for N. ribisnigri genomes, corresponding to both avirulent (Nr-locus susceptible) and virulent (Nr-locus resistant) biotypes. Changes in gene expression of the two N. ribisnigri biotypes were investigated using transcriptomic analyses of RNA-sequencing (RNA-seq) data to understand the potential mechanisms of resistance to the Nr-locus in lettuce. The draft genome assemblies were 94.2% and 91.4% complete for the avirulent and virulent biotypes, respectively. Out of the 18,872 differentially expressed genes, a single gene/locus was identified in N. ribisnigri that was shared between two resistant-breaking biotypes. This locus was further explored and validated in Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) experiments and has predicted localisations in both the cytoplasm and nucleus. This is the first study to provide evidence that a single gene/locus is likely responsible for the ability of N. ribisnigri to overcome the Nr-locus resistance in the lettuce host.

Overexpression of Aurora Kinase B Is Correlated with Diagnosis and Poor Prognosis in Hepatocellular Carcinoma.

Aurora kinase B (AURKB) overexpression promotes tumor initiation and development by participating in the cell cycle. In this study, we focused on the mechanism of AURKB in hepatocellular carcinoma (HCC) progression and on AURKB's value as a diagnostic and prognostic biomarker in HCC. We used data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to analyze AURKB expression in HCC. We found that the expression levels of AURKB in HCC samples were higher than those in the corresponding control group. R packages were used to analyze RNA sequencing data to identify AURKB-related differentially expressed genes (DEGs), and these genes were found to be significantly enriched during the cell cycle. The biological function of AURKB was verified, and the results showed that cell proliferation was slowed down and cells were arrested in the G2/M phase when AURKB was knocked down. AURKB overexpression resulted in significant differences in clinical symptoms, such as the clinical T stage and pathological stage. Kaplan-Meier survival analysis, Cox regression analysis, and Receiver Operating Characteristic (ROC) curve analysis suggested that AURKB overexpression has good diagnostic and prognostic potential in HCC. Therefore, AURKB may be used as a potential target for the diagnosis and cure of HCC.

Benchmarking algorithms for gene set scoring of single-cell ATAC-seq data

Abstract Gene set scoring (GSS) has been routinely conducted for gene expression analysis of bulk or single-cell RNA sequencing (RNA-seq) data, which helps to decipher single-cell heterogeneity and cell-type-specific variability by incorporating prior knowledge from functional gene sets. Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a powerful technique for interrogating single-cell chromatin-based gene regulation, and genes or gene sets with dynamic regulatory potentials can be regarded as cell-type-specific markers as if in single-cell RNA-seq (scRNA-seq). However, there are few GSS tools specifically designed for scATAC-seq, and the applicability and performance of RNA-seq GSS tools on scATAC-seq data remain to be investigated. We systematically benchmarked ten GSS tools, including four bulk RNA-seq tools, five scRNA-seq tools, and one scATAC-seq method. First, using matched scATAC-seq and scRNA-seq datasets, we found that the performance of GSS tools on scATAC-seq data is comparable to that on scRNA-seq, suggesting their applicability to scATAC-seq. Then the performance of different GSS tools were extensively evaluated using up to ten scATAC-seq datasets. Moreover, we evaluated the impact of gene activity conversion, dropout imputation, and gene set collections on the results of GSS. Results show that dropout imputation can significantly promote the performance of almost all GSS tools, while the impact of gene activity conversion methods or gene set collections on GSS performance is more dependent on GSS tools or datasets. Finally, we provided practical guidelines for choosing appropriate pre-processing methods and GSS tools in different application scenarios.

The Schwann cell-specific G-protein Gαo (Gnao1) is a cell-intrinsic controller contributing to the regulation of myelination in peripheral nerve system

Myelin sheath abnormality is the cause of various neurodegenerative diseases (NDDs). G-proteins and their coupled receptors (GPCRs) play the important roles in myelination. Gnao1, encoding the major Gα protein (Gαo) in mammalian nerve system, is required for normal motor function. Here, we show that Gnao1 restricted to Schwann cell (SCs) lineage, but not neurons, negatively regulate SC differentiation, myelination, as well as re-myelination in peripheral nervous system (PNS). Mice lacking Gnao1 expression in SCs exhibit faster re-myelination and motor function recovery after nerve injury. Conversely, mice with Gnao1 overexpression in SCs display the insufficient myelinating capacity and delayed re-myelination. In vitro, Gnao1 deletion in SCs promotes SC differentiation. We found that Gnao1 knockdown in SCs resulting in the elevation of cAMP content and the activation of PI3K/AKT pathway, both associated with SC differentiation. The analysis of RNA sequencing data further evidenced that Gnao1 deletion cause the increased expression of myelin-related molecules and activation of regulatory pathways. Taken together, our data indicate that Gnao1 negatively regulated SC differentiation by reducing cAMP level and inhibiting PI3K-AKT cascade activation, identifying a novel drug target for the treatment of demyelinating diseases.

Age-associated CD4+ T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunity.

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated "age-associated T helper (THA) cells." THA cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of THA cells, gene expression in THA cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that THA cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of THA cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.

UPP1 promotes lung adenocarcinoma progression through the induction of an immunosuppressive microenvironment

The complexity of the tumor microenvironment (TME) is a crucial factor in lung adenocarcinoma (LUAD) progression. To gain deeper insights into molecular mechanisms of LUAD, we perform an integrative single-cell RNA sequencing (scRNA-seq) data analysis of 377,574 cells from 117 LUAD patient samples. By linking scRNA-seq data with bulk gene expression data, we identify a cluster of prognostic-related UPP1high tumor cells. These cells, primarily situated at the invasive front of tumors, display a stronger association with the immunosuppressive components in the TME. Our cytokine array analysis reveals that the upregulation of UPP1 in tumor cells leads to the increased release of various immunosuppressive cytokines, with TGF-β1 being particularly prominent. Furthermore, this UPP1 upregulation also elevates the expression of PD-L1 through the PI3K/AKT/mTOR pathway, which contributes to the suppression of CD8 + T cells. Cytometry by time-of-flight (CyTOF) analysis provides additional evidence of the role of UPP1 in shaping the immunosuppressive nature of the TME. Using patient-derived organoids (PDOs), we discover that UPP1high tumors exhibit relatively increased sensitivity to Bosutinib and Dasatinib. Collectively, our study highlights the immunosuppressive role of UPP1 in LUAD, and these findings may provide insights into the molecular features of LUAD and facilitate the development of personalized treatment strategies.

Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data Reveals Memory-like NK Cell Subset Associated with Mycobacterium tuberculosis Latency.

Natural killer (NK) cells are innate-like lymphocytes that belong to the family of type-1 innate lymphoid cells and rapidly respond to virus-infected and tumor cells. In this study, we have combined scRNA-seq data and bulk RNA-seq data to define the phenotypic and molecular characteristics of peripheral blood NK cells. While the role of NK cells in immune surveillance against virus infections and tumors has been well established, their contribution to protective responses to other intracellular microorganisms, such as Mycobacterium tuberculosis (Mtb), is still poorly understood. In this study, we have combined scRNA-seq data and bulk RNA-seq data to illuminate the molecular characteristics of circulating NK cells in patients with active tuberculosis (TB) disease and subjects with latent Mtb infection (LTBI) and compared these characteristics with those of healthy donors (HDs) and patients with non-TB other pulmonary infectious diseases (ODs). We show here that the NK cell cluster was significantly increased in LTBI subjects, as compared to patients with active TB or other non-TB pulmonary diseases and HD, and this was mostly attributable to the expansion of an NK cell population expressing KLRC2, CD52, CCL5 and HLA-DRB1, which most likely corresponds to memory-like NK2.1 cells. These data were validated by flow cytometry analysis in a small cohort of samples, showing that LTBI subjects have a significant expansion of NK cells characterized by the prevalence of memory-like CD52+ NKG2C+ NK cells. Altogether, our results provide some new information on the role of NK cells in protective immune responses to Mtb.

Integrative analysis of single-cell and bulk RNA-sequencing data revealed disulfidptosis genes-based molecular subtypes and a prognostic signature in lung adenocarcinoma.

Disulfidoptosis is an unconventional form of programmed cell death that distinguishes itself from well-established cell death pathways like ferroptosis, pyroptosis, and necroptosis. Initially, we conducted a single-cell analysis of the GSE131907 dataset from the GEO database to identify disulfidoptosis-related genes (DRGs). We utilized differentially expressed DRGs to classify TCGA samples with an unsupervised clustering algorithm. Prognostic models were built using Cox regression and LASSO regression. Two DRG-related clusters (C1 and C2) were identified based on the DEGs from single-cell sequencing data analysis. In comparison to C1, C2 exhibited significantly worse overall prognosis, along with lower expression levels of immune checkpoint genes (ICGs) and chemoradiotherapy sensitivity-related genes (CRSGs). Furthermore, C2 displayed a notable enrichment in metabolic pathways and cell cycle-associated mechanisms. C2 was also linked to the development and spread of tumors. We created a prognostic risk model known as the DRG score, which relies on the expression levels of five DRGs. Patients were categorized into high-risk and low-risk groups depending on their DRG score, with the former group being linked to a poorer prognosis and higher TMB score. Moreover, the DRG score displayed significant correlations with CRSGs, ICGs, the tumor immune dysfunction and exclusion (TIDE) score, and chemotherapeutic sensitivity. Subsequently, we identified a significant correlation between the DRG score and monocyte macrophages. Additionally, crucial DRGs were additionally validated using qRT-PCR. Our new DRG score can predict the immune landscape and prognosis of LUAD, serving as a reference for immunotherapy and chemotherapy.

Synaptotagmin-4 induces anhedonic responses to chronic stress via BDNF signaling in the medial prefrontal cortex

Stressful circumstances are significant contributors to mental illnesses such as major depressive disorder. Anhedonia, defined as loss of the ability to enjoy pleasure in pleasurable situations, including rewarding activities or social contexts, is considered a key symptom of depression. Although stress-induced depression is associated with anhedonia in humans and animals, the underlying molecular mechanisms of anhedonic responses remain poorly understood. In this study, we demonstrated that synaptotagmin-4 (SYT4), which is involved in the release of neurotransmitters and neurotrophic factors, is implicated in chronic stress-induced anhedonia. Employing chronic unpredictable stress (CUS), we evaluated two subpopulations of mice, susceptible (SUS, anhedonic) and resilient (RES, nonanhedonic), based on sucrose preference, which was strongly correlated with social reward. The FosTRAP (targeted recombination in active populations) system and optogenetic approach revealed that neural activity in the medial prefrontal cortex (mPFC) was significantly associated with CUS-induced anhedonic behavioral phenotypes. By conducting weighted gene coexpression network analysis of RNA sequencing data from the mPFC of SUS and RES mice, we identified Syt4 as a hub gene in a gene network that was unique to anhedonia. We also confirmed that Syt4 overexpression in the mPFC was pro-susceptible, while Syt4 knockdown was pro-resilient; the pro-susceptible effects of SYT4 were mediated through a reduction in brain-derived neurotrophic factor (BDNF)-tropomyosin receptor kinase B (TrkB) signaling in the mPFC. These findings suggest that SYT4-BDNF interactions in the mPFC represent a crucial regulatory mechanism of anhedonic susceptibility to chronic stress.

CCR10-mediated Enhancement of T Cell Trafficking for Improved Tumor Immunotherapy.

The effectiveness of adoptive T cell therapy for solid tumors remains suboptimal, partly attributed to insufficient T cell infiltration into the tumor site. A promising strategy involves directing T cells towards the tumor utilizing tumor-specific chemokine receptors. We analyzed chemokine receptor expression in activated T cells and chemokine expression in breast and lung cancer using The Cancer Genome Atlas (TCGA) data. Subsequently, we generated 1G4 T cell receptor-engineered T (TCR-T) cells with CCR10 and performed in vitro and in vivo efficacy tests. CCR10 exhibited insufficient expression in various human T cells. Analysis of TCGA RNA sequencing data revealed elevated expression of the chemokine CCL28, the corresponding chemokine for CCR10, in breast and lung cancer. Consequently, we generated CCR10-1G4 TCR-T cells. CCR10-1G4 dual expressing TCR-T cells exhibited comparable cellular cytotoxicity but increased mobility compared to 1G4 TCR-T cells in vitro. Furthermore, injecting CCR10-1G4 dual expressing TCR-T cells into a xenograft tumor model demonstrated enhanced in vivo trafficking and a greater reduction of tumor burden. This study highlights the potential of CCR10 for developing efficient adoptive T-cell treatments targeting solid tumors.

CTISL: a dynamic stacking multi-class classification approach for identifying cell types from single-cell RNA-seq data.

Effective identification of cell types is of critical importance in single-cell RNA-sequencing (scRNA-seq) data analysis. To date, many supervised machine learning-based predictors have been implemented to identify cell types from scRNA-seq datasets. Despite the technical advances of these state-of-the-art tools, most existing predictors were single classifiers, of which the performances can still be significantly improved. It is therefore highly desirable to employ the ensemble learning strategy to develop more accurate computational models for robust and comprehensive identification of cell types on scRNA-seq datasets. We propose a two-layer stacking model, termed CTISL (Cell Type Identification by Stacking ensemble Learning), which integrates multiple classifiers to identify cell types. In the first layer, given a reference scRNA-seq dataset with known cell types, CTISL dynamically combines multiple cell-type-specific classifiers (i.e. support-vector machine and logistic regression) as the base learners to deliver the outcomes for the input of a meta-classifier in the second layer. We conducted a total of 24 benchmarking experiments on 17 human and mouse scRNA-seq datasets to evaluate and compare the prediction performance of CTISL and other state-of-the-art predictors. The experiment results demonstrate that CTISL achieves superior or competitive performance compared to these state-of-the-art approaches. We anticipate that CTISL can serve as a useful and reliable tool for cost-effective identification of cell types from scRNA-seq datasets. The webserver and source code are freely available at http://bigdata.biocie.cn/CTISLweb/home and https://zenodo.org/records/10568906, respectively.

Age-related dysregulation of intestinal epithelium fucosylation is linked to an increased risk of colon cancer.

Colon cancer affects people of all ages. However, its frequency, as well as the related morbidity and mortality, are high among older adults. The complex physiological changes in the aging gut substantially limit the development of cancer therapies. Here, we identify a potentially unique intestinal microenvironment that is linked with an increased risk of colon cancer in older adults. Our findings show that aging markedly influenced persistent fucosylation of the apical surfaces of intestinal epithelial cells, which resulted in a favorable environment for tumor growth. Furthermore, our findings shed light on the importance of the host-commensal interaction, which facilitates the dysregulation of fucosylation and promotes tumor growth as people get older. We analyzed colonic microbial populations at the species level to find changes associated with aging that could contribute to the development of colon cancer. Analysis of single-cell RNA-sequencing data from previous publications identified distinct epithelial cell subtypes involved in dysregulated fucosylation in older adults. Overall, our study provides compelling evidence that excessive fucosylation is associated with the development of colon cancer, that age-related changes increase vulnerability to colon cancer, and that a dysbiosis in microbial diversity and metabolic changes in the homeostasis of older mice dysregulate fucosylation levels with age.

Sperm exposure to accessory gland secretions alters the transcriptomic response of the endometrium in cattle

In cattle, mating to intact, but not vasectomised, bulls has been shown to modify the endometrial transcriptome, suggesting an important role of sperm in the modulation of the uterine environment in this species. However, it is not clear whether these changes are driven by intrinsic sperm factors, or by factors of accessory gland (AG) origin that bind to sperm at ejaculation. Therefore, the aim of the present study was to determine whether ejaculated sperm, which are suspended in the secretions of the AGs, elicit a different endometrial transcriptomic response than epididymal sperm, which have never been exposed to AG factors. To this end, bovine endometrial explants collected from heifers in oestrus were (co-)incubated for 6 h alone (control), or with epididymal sperm or ejaculated sperm, following which transcriptomic changes in the endometrium were evaluated. Epididymal sperm elicited a more dramatic endometrial response than ejaculated sperm, in terms of the number of differentially expressed genes (DEGs). Indeed, RNA-sequencing data analysis revealed 1912 DEGs in endometrial explants exposed to epididymal sperm compared with control explants, whereas 115 DEGs were detected between endometrial explants exposed to ejaculated sperm in comparison to control explants. The top pathways associated with genes upregulated by epididymal sperm included T cell regulation and TNF, NF-KB and IL17 signalling. Interestingly, ejaculated sperm induced downregulation of genes associated with T cell immunity and Th17 differentiation, and upregulation of genes involved in NF-KB signalling, in comparison to epididymal sperm. These data indicate that factors of AG origin modulate the interaction between sperm and the endometrium in cattle.

Transcriptomic Analysis of Metastatic Colorectal Tumor with Low Mutational Burden

Objective: To identify potential drug targets for metastasis colorectal cancer (CRC) patients with low mutational burden by examining differences in immune-related gene expression. Methods: For this study, 623 samples were collected from The Cancer Genome Atlas (TCGA) database, comprising tumor mutational burden (TMB), RNA sequencing (RNA-Seq), and clinical data. Differential gene expression analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the identified genes were conducted using the R package. Additionally, a comparative analysis of immune infiltrating cell composition in metastatic and non-metastatic groups was performed. Hub genes, exhibiting high levels of interaction, were selected using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The Drug Gene Interaction Database (DGIdb) was then utilized to estimate drugs targeting the identified hub genes. Results: The transcriptome data of 326 colorectal cancer patients with low TMB were analyzed, comprising 58 patients with metastasis and 268 patients without metastasis. Among the differential expression in 1,111 genes for patients with metastasis compared to those without metastasis, 733 genes were upregulated, and 378 genes were downregulated. KEGG and GO enrichment analysis indicated significant differences in gene expression in CRC metastatic patients with low TMB compared to non-metastasis patients with low TMB. Enriched pathways included humoral immuneresponse, immunoglobulin production, and regulation of AMPA receptor activity. Two genes related to interleukin-12 were identified through secondary enrichment for immune-related genes. Analysis of tumor-infiltrating immune cell data revealed significant differences in memory-activated T cell CD4 and T cell CD8. Conclusions: This analysis of RNA sequencing data and immune-filtrating cell data revealed significant differences between metastatic colorectal cancer patients with low TMB and their non-metastatic counterparts. These distinctions suggest the possibility of identifying more effective drugs or therapies for metastatic colorectal cancer patients with low TMB.

ScHybridBERT: integrating gene regulation and cell graph for spatiotemporal dynamics in single-cell clustering.

Graph learning models have received increasing attention in the computational analysis of single-cell RNA sequencing (scRNA-seq) data. Compared with conventional deep neural networks, graph neural networks and language models have exhibited superior performance by extracting graph-structured data from raw gene count matrices. Established deep neural network-based clustering approaches generally focus on temporal expression patterns while ignoring inherent interactions at gene-level as well as cell-level, which could be regarded as spatial dynamics in single-cell data. Both gene-gene and cell-cell interactions are able to boost the performance of cell type detection, under the framework of multi-view modeling. In this study, spatiotemporal embedding and cell graphs are extracted to capture spatial dynamics at the molecular level. In order to enhance the accuracy of cell type detection, this study proposes the scHybridBERT architecture to conduct multi-view modeling of scRNA-seq data using extracted spatiotemporal patterns. In this scHybridBERT method, graph learning models are employed to deal with cell graphs and the Performer model employs spatiotemporal embeddings. Experimental outcomes about benchmark scRNA-seq datasets indicate that the proposed scHybridBERT method is able to enhance the accuracy of single-cell clustering tasks by integrating spatiotemporal embeddings and cell graphs.

Improving cell type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning.

Cell type identification is an important task for single-cell RNA-sequencing (scRNA-seq) data analysis. Many prediction methods have recently been proposed, but the predictive accuracy of difficult cell type identification tasks is still low. In this work, we proposed a novel Gaussian noise augmentation-based scRNA-seq contrastive learning method (GsRCL) to learn a type of discriminative feature representations for cell type identification tasks. A large-scale computational evaluation suggests that GsRCL successfully outperformed other state-of-the-art predictive methods on difficult cell type identification tasks, while the conventional random genes masking augmentation-based contrastive learning method also improved the accuracy of easy cell type identification tasks in general.