Construction Of Regulatory Networks Research Articles

Unveiling the molecular mechanisms of recurrent miscarriage through endoplasmic reticulum stress related gene expression

Recurrent miscarriage (RM) is a reproductive disorder affecting couples worldwide. The underlying molecular mechanisms remain elusive, even though emerging evidence has implicated endoplasmic reticulum stress (ERS). We investigated RM- and ERS-related genes to develop a diagnostic model that can enhance predictive ability. We utilized the R package GEO query to extract and process Gene Expression Omnibus data, applying batch correction, normalization, and differential gene expression analysis with limma. ERS-related differentially expressed genes (ERSRGs) were identified through Gene Ontology and Kyoto Encyclopedia of genes and genomes analyses, and their diagnostic potential was assessed. Diagnostic models were developed using logistic regression, support vector machines, and least absolute shrinkage and selection operators, complemented by immune infiltration analysis and regulatory network construction. Integrated analysis revealed 1395 differentially expressed genes (DEGs), including 626 upregulated and 769 downregulated genes. Seventeen ERSRGs were identified. KEAP1 and YIPF5 displayed high diagnostic accuracy (area under the curve [AUC] > 0.9). Gene Ontology and Kyoto Encyclopedia of genes and genomes analyses highlighted the role of ESRDEGs in cellular responses to ERS, protein processing, and apoptosis. Diagnostic models demonstrated robust predictive performance (AUC > 0.9). A molecular interaction was found between RM and the ERS response, and the identified ESRDEGs could serve as potential biomarkers for diagnosis.

Comprehensive characterization of the transcriptional landscape in Alzheimer's disease (AD) brains.

Alzheimer's disease (AD) is the leading dementia among the elderly with complex origins. Despite extensive investigation into the AD-associated protein-coding genes, the involvement of noncoding RNAs (ncRNAs) and posttranscriptional modification (PTM) in AD pathogenesis remains unclear. Here, we comprehensively characterized the landscape of ncRNAs and PTM events in 1460 samples across six brain regions sourced from the Mount Sinai/JJ Peters VA Medical Center Brain Bank Study and Mayo cohorts, encompassing 33,321 long ncRNAs, 92,897 enhancer RNAs, 53,763 alternative polyadenylation events, and 900,221 A-to-I RNA editing events. We additionally identified 25,351 aberrantly expressed ncRNAs and altered PTM events associated with AD traits and further identified the corresponding protein-coding genes to construct regulatory networks. Furthermore, we developed a user-friendly data portal, ADatlas, facilitating users in exploring our results. Our study aims to establish a comprehensive data platform for ncRNAs and PTMs in AD to advance related research.

Comprehensive analyses reveal the promising value of gasdermins as prognostic biomarkers and immunotherapeutic targets in head and neck squamous cell carcinoma.

In several studies of head and neck squamous cell carcinoma (HNSC), the regulation of tumorigenesis and therapeutic sensitivity by pyroptosis has been observed. However, a systematic analysis of gasdermin family members (GSDMs, including GSDMA/B/C/D/E and PJVK), which are deterministic executors of pyroptosis, has not yet been reported in HNSC. We performed comprehensive analyses of the expression profile, prognostic value, regulatory network, and immune infiltration modulation of GSDMs in HNSC on the basis of a computational approach and bioinformatic analysis of publicly available datasets. A total of 18.65% (94/504) of HNSC patients harbored GSDM alterations, with the most dominant type being amplification. Compared with those in normal tissues, the mRNA and protein levels of GSDMs, especially GSDMD/E, were commonly elevated in HNSC (P<0.05). Additionally, the expression of GSDMs differed significantly between the clinicopathological subgroups of HNSC patients. Overall survival of HNSC patients benefited from increased GSDMC expression (HR=0.67, P=0.0053) and decreased GSDME expression (HR=1.42, P=0.0140). Regulatory network analysis revealed several essential biological processes associated with GSDMs, including positive regulation of cytokine production involved in the immune response. Notably, almost all infiltrating immune cells and immune checkpoints were negatively correlated with GSDMA/C/E expression and positively related to GSDMB/D and PJVK expression. We indicated the potential role of GSDMs (especially GSDME) in HNSC pathogenesis, progression and response to immunotherapy, providing important evidence for further prospective studies and molecular mechanism exploration.

Exploring PDE5A upregulation in bipolar disorder: insights from single-nucleus RNA sequencing of human basal ganglia

Basal ganglia is proposed to mediate symptoms underlying bipolar disorder (BD). To understand the cell type-specific gene expression and network changes of BD basal ganglia, we performed single-nucleus RNA sequencing of 30,752 nuclei from caudate, putamen, globus pallidus, and substantia nigra of control human postmortem brain and 24,672 nuclei from BD brain. Differential expression analysis revealed major difference lying in caudate, with BD medium spiny neurons (MSNs) expressing significantly higher PDE5A, a cGMP-specific phosphodiesterase. Gene co-expression analysis (WGCNA) showed a strong correlation of caudate MSNs and gene module green, with a PDE5A-containing hub gene network. Gene regulatory network analysis (SCENIC) indicated key regulons among different cell types and basal ganglia regions, with downstream targets of key transcriptional factors showing overlapping genes such as PDEs. Upregulation of PDE5A was further validated in 7 pairs of control and BD caudate sections. Overexpression of PDE5A in primary cultured lateral ganglion eminence-derived striatal neurons led to decreased dendrite complexity, increased apoptosis, and enhanced neuronal excitability and membrane resistance. This effect could be rescued by PDE5 specific inhibitor, tadalafil. Overexpression of PDE5A in mouse striatum by stereotaxic injection caused a decreased cGMP level, an increased gene expression profile of neuroinflammation, and BD-like behaviors. Collectively, our findings provided cell type-specific gene expression profile, and indicated a causative role of PDE5A upregulation in BD basal ganglia.This study provides a single-nucleus transcriptomic profile of human control and bipolar disorder (BD) basal ganglia. Differential expression, gene co-expression, and gene regulatory network analyses collectively indicated upregulation of PDE5A in BD caudate medium spiny neurons (MSNs), which was further validated in another cohort of BD brains. The causative role of PDE5A upregulation in BD etiology is supported by the effects of PDE5A overexpression in cultured mouse MSNs in vitro and in adult mouse striatum in vivo. The former led to reduced dendrite complexity, increased apoptosis, and neuronal hyper-excitability, which could be rescued by PDE5 specific inhibitor tadalafil. The latter caused lower cGMP levels, upregulated genes associated with neuroinflammation, and BD-like behaviors.

Characterization of circulating miRNA in cow milk and colostrum.

MicroRNAs (miRNAs) are short RNA molecules, typically 21-25 nucleotides long, synthesized within eukaryotic cells. They play a crucial role in coordinating complex gene expression regulatory networks. The miRNAs are involved in post-transcriptional regulation, either by degrading target mRNA or suppressing their transcription, thereby influencing protein translation. Also, the variation of miRNAs expression in different milk components suggests diverse metabolic pathways. Additionally, characteristics of farm production systems exert a noticeable influence on miRNAs profiles, shaping the functional properties of bovine milk. In this study, milk and colostrum samples of Holstein cows (Bos taurus) were collected for RNA extraction and sequencing. Sequencing data underwent quality controls, and short non-coding RNA reads were analyzed to identify and compare miRNAs profiles. The sequencing runs yielded 73,567,661 and 44,283,978 reads for milk and colostrum samples, respectively. Following trimming, 8,335,860 and 7,778,212 reads for milk and colostrum samples were retained. A total of 4.3% milk and 37.8% colostrum reads were identified as miRNAs. Overall, 157 miRNAs were common to milk and colostrum, 2 were unique to milk, and 90 were unique to colostrum. After applying a minimal cutoff of 100 reads per miRNA, 146 miRNAs were considered as expressed. In milk, bta-miR-101 was unique; in colostrum, bta-miR-18a, bta-miR-262-3p, bta-miR-130a, and bta-miR-224 were unique; and 141 miRNAs were common to colostrum and milk. Chromosome distribution of these miRNAs varied, with higher representation on autosome 19 and sexual chromosome X. Overall, colostrum contained a greater number of miRNAs, although specific miRNAs such as miR-11-988b, miR-140, and miR-146b were more abundant in milk. Conversely, miRNAs such as miR-7a-5p, let-7e, and miR-16a were more prevalent in colostrum. Validation through qPCR confirmed the expression levels of selected miRNAs from RNA sequencing, establishing concordance between the methods. Analysis of gene regulation by specific miRNAs identified key miRNAs (e.g., miR-223, miR-181a, and miR-155) involved in regulating various genes. Distinct miRNAs profiles in milk and colostrum suggest various functionalities, potentially influencing calf development and immune responses. The study unveils a comprehensive map of miRNAs in milk and colostrum and highlights their potential roles in regulating biological processes, as they play an essential role in calf development, disease resistance, and metabolism.

Key Regulatory Elements of the TGFβ-LRRC15 Axis Predict Disease Progression and Immunotherapy Resistance Across Cancer Types.

Transforming growth factor-beta (TGFβ) has dual roles in cancer, initially suppressing tumors but later promoting metastasis and immune evasion. Efforts to inhibit TGFβ have been largely unsuccessful due to significant toxicity and indiscriminate immunosuppression. Leucine-rich repeat-containing protein 15 (LRRC15) is a TGFβ-regulated antigen expressed by mesenchymal-derived cancer cells and cancer-associated fibroblasts (CAFs). In preclinical studies, ablation of TGFβ-driven LRRC15+ CAFs increased tumor infiltration of CD8+ T cells. However, the underlying pathobiological mechanisms prompting TGFβ's upregulation of LRRC15 expression are unclear. Using an integrated approach combining functional compound screening with single-cell RNA sequencing, we reveal key genomic features regulating TGFβ's ability to increase LRRC15 expression on cancer cells. Construction of gene regulatory networks converged our analyses on four key genes- MMP2, SPARC, TGF β R2, and WNT5B -central to TGFβ-induced LRRC15 pathobiology. Validation of these genes in cell models and their use in predicting immunotherapy responses highlight their potential in refining immunotherapy strategies and personalizing co-treatment options.

Pituitary whole transcriptome analysis reveals key genes regulating reproduction in Hy-Line Brown hens and the construction of their ceRNA molecular regulatory network

BackgroundThe development and egg-laying performance of hens are precisely regulated by hormones secreted by the pituitary. In this study, we performed comprehensive transcriptome sequencing of pituitary from Hy-Line Brown hens at 15, 20, 30 and 68 W of age. Through association analysis, we identified key genes and ceRNA regulatory networks related to pituitary development and egg production.ResultsBased on the comprehensive transcriptome data, we identified 470 differentially expressed lncRNAs (DE-lncRNAs), 38 differentially expressed miRNAs (DE-miRNAs), and 2,449 differentially expressed mRNAs (DE-mRNAs). Time-series analysis pinpointed genes and signaling pathways that significantly influence pituitary hormone secretion at various stages. At 15 W, the high expression of GHRHR, NPY1R, and TSHR in the pituitary supports growth. At 20 and 30 W, elevated GNRHR expression sustains continuous egg production. In the late laying period, the expression of PRL may lead to a decline in egg production. Additionally, association analysis enabled the construction of a ceRNA regulatory network involving non-coding RNAs that regulate the development and reproduction of hens.ConclusionThis study elucidated the comprehensive transcriptome expression profiles of the pituitary gland during the development and egg-laying processes in Hy-Line Brown hens and constructed the associated molecular regulatory networks. These findings lay the foundation for investigating the mechanisms by which non-coding RNAs regulate pituitary hormone secretion.

Construction and Analysis of miRNA-mRNA Interaction Network in Ovarian Tissue of Wanxi White Geese Across Different Breeding Stages.

Ovarian development significantly influences the laying performance of geese. In this study, the transcriptome analysis was conducted on the ovarian tissues of Wanxi White Geese during the pre-laying (KL), laying (CL), and ceased-laying period (XL). Short Time-series Expression Miner (STEM) analysis and miRNA-mRNA regulatory network construction were performed to identify the key genes and miRNAs regulating laying traits. Comparative analysis of KL vs. CL, CL vs. XL, and XL vs. KL groups resulted in the identification of 337, 136, and 525 differentially expressed genes (DEGs), and 258, 1131, and 909 differentially expressed miRNAs (DEMs), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (p < 0.05) revealed that the main enrichment pathways of DEGs and DEMs at different breeding periods were Neuroactive ligand-receptor interaction, GnRH signaling pathway and Wnt signaling pathway, all associated with ovarian development. According to the three groups of common pathways, four DEGs were screened out, including INHBB, BMP5, PRL, and CGA, along with five DEMs, including let-7-x, miR-124-y, miR-1-y, and miR-10926-z, all of them may affect ovarian development. A miRNA-mRNA regulatory network was constructed through integrated analysis of DEGs and DEMs, revealing nine miRNAs highly associated with ovarian development: miR-101-y, let-7-x, miR-1-x, miR-17-y, miR-103-z, miR-204-x, miR-101-x, miR-301-y, and miR-151-x. The dual-luciferase reporter gene verified the target relationship between WIF1 and miR-204-x, suggesting that these miRNAs may influence ovarian development in Wanxi White Goose by regulating the expression levels of their target genes within ovarian tissue. This study provides a theoretical foundation for analyzing the mechanisms of ovarian development across different breeding periods and accelerating the cultivation of new breeds through post-transcriptional regulation levels.

Transcriptome Analysis Reveals the Crucial Role of Phenylalanine Ammonia-Lyase in Low Temperature Response in Ammopiptanthus mongolicus.

Background: Ammopiptanthus mongolicus is a rare temperate evergreen shrub with high tolerance to low temperature, and understanding the related gene expression regulatory network can help advance research on the mechanisms of plant tolerance to abiotic stress. Methods: Here, time-course transcriptome analysis was applied to investigate the gene expression network in A. mongolicus under low temperature stress. Results: A total of 12,606 differentially expressed genes (DEGs) were identified at four time-points during low temperature stress treatment, and multiple pathways, such as plant hormones, secondary metabolism, and cell membranes, were significantly enriched in the DEGs. Trend analysis found that the expression level of genes in cluster 19 continued to upregulate under low temperatures, and the genes in cluster 19 were significantly enriched in plant hormone signaling and secondary metabolic pathways. Based on the transcriptome data, the expression profiles of the genes in abscisic acid, salicylic acid, and flavonoid metabolic pathways were analyzed. It was found that biosynthesis of abscisic acid and flavonoids may play crucial roles in the response to low temperature stress. Furthermore, members of the phenylalanine ammonia-lyase (PAL) family in A. mongolicus were systematically identified and their structures and evolution were characterized. Analysis of cis-acting elements showed that the PAL genes in A. mongolicus were closely related to abiotic stress response. Expression pattern analysis showed that PAL genes responded to various environmental stresses, such as low temperature, supporting their involvement in the low temperature response in A. mongolicus. Conclusions: Our study provides important data for understanding the mechanisms of tolerance to low temperatures in A. mongolicus.

Abstract 4121148: A functional survey of postnatal heart maturation with in vivo Perturb-seq in spatial and temporal resolution

Background: Cardiomyocyte maturation is a crucial process that involves intricate molecular and structural changes necessary for more vigorous and efficient heart function after birth. Understanding the regulatory mechanisms of this process is essential for leveraging these insights to develop advanced therapies for heart disease. Despite recent advancements, the limitations of current in vivo genetic and single-cell approaches - such as the low throughput of in vivo genetics, lack of spatial information in single-cell RNA-seq, and, most importantly, the lack of high-throughput combined use of both approaches - hinder the construction of a comprehensive regulatory network of cardiomyocyte maturation. Methods: Here, we established an experimental pipeline combining time-course single-nucleus RNA sequencing and spatial transcriptomics with our optimized in vivo Perturb-seq platform to establish the regulatory network underlying heart maturation. Results: Our current study has generated a postnatal murine heart atlas with 67,000 nuclei from postnatal heart. Temporal analysis of the cardiomyocyte transcriptome dynamics identifies Ankrd1+ cardiomyocyte as a transient state between proliferative and matured cardiomyocytes. We constructed a regulatory network consisting of 35 known and novel regulators for cardiomyocyte maturation. Our analysis of postnatal cardiomyocyte interactome elucidated signaling pathways’ stage-specific contribution to cardiomyocyte maturation. With the spatial transcriptomic data, we further identified signaling pathways that played unique roles in the maturation of chamber-specific cardiomyocytes. Using fixed RNA in vivo Perturb-seq established in this study, we have validated 21 novel regulators of postnatal cardiomyocyte maturation out of 53 candidate regulators from previous temporal and spatial analyses. Conclusions: We have not only created a single-cell-resolution temporal and spatial atlas during postnatal heart development but also established an in vivo Perturb-seq platform to allow the functional interrogation of key regulatory genes in a physiologically relevant context. Importantly, the proposed working model unlocks new possibilities for research, no longer limiting to a single gene or pathway, but allowing for the exploration of a network of genes. This high-resolution, high-throughput in vivo mapping and screening platform has the potential to revolutionize the way we study organogenesis and disease progression in the heart.

Abstract 4142799: Central role of LIM domain binding 3 (LDB3) protein in Tetralogy of Fallot assessed by single-nuclei multiome profiling of paediatric right ventricular samples

Background and aims: Tetralogy of Fallot (TOF; EC: 1565/2019) is the most common cyanotic congenital heart defect with a world-wide incidence of 0.02–0.04%. The pathophysiological mechanisms driven by variable genetic background are poorly understood. We applied the single-nuclei multiome profiling, composed of ATAC and RNA-seq from the same nuclei, of right ventricular samples of children with TOF. The final aim was to define cell types and characterize gene regulation states in different cell clusters including activation and maturation. Methods: Right ventricular samples were prospectively gathered during routinely performed cardiac surgery for TOF correction (EC: 1565/2019). In total, six paediatric patient samples were processed, and on average ~1,500 nuclei were sequenced per sample. Data was analysed using Scanpy to cluster and annotate cells, pycisTopic to identify cell stats and cis-regulatory topics, and SCENIC+ for enhancer-driven gene Regulatory network (eRegulon) construction. Results: Through manual annotation, using published markers, we identified cell types including cardiomyocyte, fibroblast, endothelial, pericyte, immune and neuronal cells. From this, we observed cell type specific expression, with overexpression of decorin in fibroblasts, PTPRC in immune cells, and neurexin genes in neuronal cells found. Differential expression analysis highlighted patient specific patterns of expression, of which gene set enrichment showed enrichment for genes associated with actomyosin structure organisation, dilated cardiomyopathy and cardiac muscle contraction. Integration of the gene expression data with the ATAC-seq data, across all patients, allowed for the construction of eRegulons networks. In detail, in the cardiomyocyte-annotated clusters, we identified enrichment of MEF2, MEIS2 and EPAS1 family enhancers with a central role of LIM domain binding 3 protein (LDB3, associated with cytoskeletal actin and muscle alpha-actin binding) (Fig. 1). Conclusion: Single nuclei multiome profiling of paediatric right ventricular TOF samples identified several patient specific patterns of expression and regulatory networks, related to the development of cyanotic congenital heart disease, and sheds light to the potential drivers of TOF.

Investigating the differential structural organization and gene expression regulatory networks of lamin A Ig fold domain mutants of muscular dystrophy.

Lamins form a proteinaceous meshwork as a major structural component of the nucleus. Lamins, along with their interactors, act as determinants for chromatin organization throughout the nucleus. The major dominant missense mutations responsible for autosomal dominant forms of muscular dystrophies reside in the Ig fold domain of lamin A. However, how lamin A contributes to the distribution of heterochromatin and balances euchromatin, and how it relocates epigenetic marks to shape chromatin states, remains poorly defined, making it difficult to draw conclusions about the prognosis of lamin A-mediated muscular dystrophies. In the first part of this report, we identified the in vitro organization of full-length lamin A proteins due to two well-documented Ig LMNA mutations, R453W and W514R. We further demonstrated that both lamin A/C mutant cells predominantly expressed nucleoplasmic aggregates. Labeling specific markers of epigenetics allowed correlation of lamin A mutations with epigenetic mechanisms. In addition to manipulating epigenetic mechanisms, our proteomic studies traced diverse expressions of transcription regulators, RNA synthesis and processing proteins, protein translation components, and posttranslational modifications. These data suggest severe perturbations in targeting other proteins to the nucleus.

In silico and functional analysis identifies key gene networks and novel gene candidates in obesity-linked human visceral fat.

Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk, and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene regulatory networks in human visceral obesity have been lacking. We analyzed gene regulatory networks in human visceral adipose tissue (VAT) from 48 and 11 Chinese patients with and without obesity, respectively, using gene coexpression and gene regulatory network construction from RNA-sequencing data. We also conducted RNA interference-based functional tests on selected genes for effects on adipocyte differentiation. A scale-free gene coexpression network was constructed from 360 differentially expressed genes between VAT samples from patients with and without obesity (absolute log fold change > 1, false discovery rate [FDR] < 0.05), with edge probability > 0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. A total of 15 subnetworks (communities) displayed altered connectivity patterns between obesity and nonobesity networks. Genes in proinflammatory pathways showed increased network connectivity in VAT samples with obesity, whereas the oxidative phosphorylation pathway displayed reduced connectivity (enrichment FDR < 0.05). Functional screening via RNA interference identified genes such as SOX30, SIRPB1, and OSBPL3 as potential network-derived candidates influencing adipocyte differentiation. This approach highlights the network architecture in human obesity, identifies novel candidate genes, and generates new hypotheses regarding network-assisted gene regulation in VAT.

Single-cell transcriptomics reveals IRF7 regulation of the tumor microenvironment in isocitrate dehydrogenase wild-type glioma.

Mutations in isocitrate dehydrogenase (IDH) are important markers of glioma prognosis. However, few studies have examined the gene expression regulatory network (GRN) in IDH-mutant and wild-type gliomas. In this study, single-cell RNA sequencing and spatial transcriptome sequencing were used to analyze the GRN of cell subsets in patients with IDH-mutant and wild-type gliomas. Through gene transcriptional regulation analysis, we identified the M4 module, whose transcription factor activity is highly expressed in IDH wild-type gliomas compared to IDH-mutants. Enrichment analysis revealed that these genes were predominantly expressed in microglia and macrophages, with significant enrichment in interferon-related signaling pathways. Interferon regulatory factor 7 (IRF7), a transcription factor within this pathway, showed the highest percentage of enrichment and was primarily localized in the core region of wild-type IDH tumors. A machine-learning prognostic model identified novel subgroups within the wild-type IDH population. Additionally, IRF7 was shown to promote the proliferation and migration of T98G and U251 cells in vitro, and its knockdown affected glioma cell proliferation in vivo. This study systematically established the regulatory mechanism of IDH transcriptional activity in gliomas at the single-cell level and drew a corresponding cell map. The study presents a transcriptional regulatory activity map for IDH wild-type gliomas, involving single-cell RNA sequencing and spatial transcriptomics to identify gene regulatory networks, machine learning models for IDH subtyping, and experimental validation, highlighting the role of IRF7 in glioma progression.

Elucidating the Mechanisms of Astragalus Membranaceus in Colorectal Cancer Patients through Bioinformatics Analysis.

Astragalus membranaceus has shown positive clinical efficacy in treating colorectal cancer (CRC). This study aimed to identify the key active components of Astragalus and determine effective targets of these components in CRC patients. We identified active components of Astragalus membranaceus and differentially expressed genes in traditional Chinese medicine systems pharmacology database and The Cancer Genome Atlas. Additionally, the enrichment analysis of differential target genes (DTGs) was performed using the R-package clusterProfiler. Immunocyte correlation analysis and non-coding regulatory network construction were performed for biomarkers using Spearman's method and NetworkAnalyst. Finally, molecular docking of biomarkers and their corresponding molecule drugs was done with Autodock Vina software. We identified 20 active components of Astragalus membranaceus and 1 403 target genes through screening. A total of 2 300 differentially expressed genes, and 3 035 hub genes in CRC were screened. The integration of the target genes with the significantly differentially expressed genes and Hub genes identified resulted in a total of 86 DTGs. Subsequently, the results showed 828 enriched GO biological processes, 184 enriched GO molecular functions, 59 enriched GO cellular components, and 46 enriched KEGG pathways. We also obtained a total of 143 PPI pairs involving 67 nodes. Additionally, we constructed 45 mRNA-TF pairs, 101 miRNA-mRNA pairs, and 200 miRNA- mRNA-TF triplets. Finally, molecular docking was performed for the active component quercetin with F2 and UGT1A1 and formic acid with FGA, AHSG, and KNG1. This study identified the active components of Astragalus membranaceus and their corresponding targets in CRC. These findings provide robust evidence for precision drug therapy in patients with CRC.

Single cell multi-omics analysis unveils a distinct mechanism of exercise-mediated cardioprotection in ischemic cardiomyopathy

Abstract Background Exercise is pivotal in heart disease prevention, with proven cardioprotective effects in clinical trials. However, its precise molecular mechanisms remain elusive. Recent advancements in single-cell omics have revealed cellular heterogeneity within heart tissues, offering a deeper understanding of the pathophysiology of cardiac diseases. Purpose To investigate the exercise-induced physiological changes in heart tissue at the single-cell level and elucidate the molecular mechanisms underlying its cardioprotective effect on ischemic cardiomyopathy. Methods Murine myocardial infarction (MI) model was established by ligating the left ascending coronary artery, and a six-week voluntary wheel running exercise regimen was implemented to investigate the effect of aerobic exercise on ischemic cardiomyopathy. Integrated multi-omics analyses of single-cell DNA methylation profiling, single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq) and single-nucleus RNA sequencing (snRNA-seq) were conducted to clarify the molecular mechanism of exercise-mediated cardioprotection at single-cell resolution. Overexpression and short hairpin RNA-mediated knockdown of gene X were conducted for murine MI model using cardiomyocyte-specific Myo-AAV2a vector. snRNA-seq of heart tissues from heart failure patients was performed to validate the clinical significance of the expression of gene X in cardiomyocytes. Results Exercise attenuates pathological cardiac remodeling, inducing physiological hypertrophy in non-infarcted areas while suppressing pathological remodeling of cardiomyocytes in infarct border zones. Single-cell epigenetic analysis unveiled intricate molecular mechanisms underlying exercise-induced transcriptome changes, providing insights into the gene regulatory networks modulated by exercise in the heart. In addition, integrated with snRNA-seq, we identified exercise-specific cardiomyocyte clusters, highlighting the substantial role of gene X in the molecular mechanism of exercise. Functional studies confirmed the essential role of gene X in exercise-induced cardioprotection, as its overexpression suppressed the adverse remodeling after MI and knockdown abolished the beneficial effects of exercise. Furthermore, snRNA-seq of heart failure patients revealed that higher expression of gene X was associated with ventricular reverse remodeling and favorable clinical outcomes, underscoring its significance in the pathophysiology of patients with heart failure. Conclusion Our study elucidates exercise-specific gene expression regulation networks in ischemic cardiomyopathy by unraveling the cellular heterogeneity and molecular changes associated with exercise. We identified gene X as a central player in exercise-mediated cardioprotection and further confirmed its significance in clinical settings, providing a potential therapeutic target for heart failure.

In-depth investigation of the complex pathophysiological mechanisms between diabetes and ischemic stroke through gene expression and regulatory network analysis

This study explores the intricate relationship between diabetes and ischemic stroke (IS) through gene expression analysis and regulatory network investigation to identify potential biomarkers and therapeutic targets. Using datasets from the Gene Expression Omnibus (GEO) database, differential gene analysis was conducted on GSE43950 (diabetes) and GSE16561 (IS), revealing overlapping differentially expressed genes (DEGs). Functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, and hub gene identification were performed, followed by validation in independent datasets (GSE156035 and GSE58294). The analysis identified 307 upregulated and 156 downregulated overlapping DEGs with significant enrichment in GO and KEGG pathways. Key hub genes (TLR2, TLR4, HDAC1, ITGAM) were identified through a PPI network (257 nodes, 456 interactions), with their roles in immune and inflammatory responses highlighted through GeneMANIA analysis. TRRUST-based transcription factor enrichment analysis revealed regulatory links involving RELA, SPI1, STAT3, and SP1. Differential expression analysis confirmed that RELA and SPI1 were upregulated in diabetes, while SPI1, STAT3, and SP1 were linked to IS. These transcription factors are involved in regulating immunity and inflammation, providing insights into the molecular mechanisms underlying diabetes-IS comorbidity. This bioinformatics-driven approach offers new understanding of the gene interactions and pathways involved, paving the way for potential therapeutic targets.

Population-wide DNA methylation polymorphisms at single-nucleotide resolution in 207 cotton accessions reveal epigenomic contributions to complex traits

DNA methylation plays multiple regulatory roles in crop development. However, the relationships of methylation polymorphisms with genetic polymorphisms, gene expression, and phenotypic variation in natural crop populations remain largely unknown. Here, we surveyed high-quality methylomes, transcriptomes, and genomes obtained from the 20-days-post-anthesis (DPA) cotton fibers of 207 accessions and extended the classical framework of population genetics to epigenetics. Over 287 million single methylation polymorphisms (SMPs) were identified, 100 times more than the number of single nucleotide polymorphisms (SNPs). These SMPs were significantly enriched in intragenic regions while depleted in transposable elements. Association analysis further identified a total of 5,426,782 cis-methylation quantitative trait loci (cis-meQTLs), 5078 cis-expression quantitative trait methylation (cis-eQTMs), and 9157 expression quantitative trait loci (eQTLs). Notably, 36.39% of cis-eQTM genes were not associated with genetic variation, indicating that a large number of SMPs associated with gene expression variation are independent of SNPs. In addition, out of the 1715 epigenetic loci associated with yield and fiber quality traits, only 36 (2.10%) were shared with genome-wide association study (GWAS) loci. The construction of multi-omics regulatory networks revealed 43 cis-eQTM genes potentially involved in fiber development, which cannot be identified by GWAS alone. Among these genes, the role of one encoding CBL-interacting protein kinase 10 in fiber length regulation was successfully validated through gene editing. Taken together, our findings prove that DNA methylation data can serve as an additional resource for breeding purposes and can offer opportunities to enhance and expedite the crop improvement process.

Assessing Alcohol Genes Targets in Mouse Liver

Background: Alcohol is a risk factor for liver diseases. There is a correlation between alcohol consumption and fatty liver disease. Experiences have shown gene expression alteration in the liver following alcohol consumption. Since the molecular mechanism of connection between alcohol consumption and fatty liver disease needs a clear perspective, this study aims to explore the significant genes that are targeted by alcohol in the liver of mice.Methods: Gene expression profiles of mice livers fed with alcohol were retrieved from the Gene Expression Omnibus (GEO) database and compared with the control samples. Data are pre-evaluated with the GEO2R program, and the significant differentially expressed genes (DEGs) are analyzed via gene expression evaluations and regulatory network assessment. Results: Among the 25619 dysregulated genes, 78 significant DEGs were pointed out. Gene expression analysis showed that most extremely dysregulated genes are up-regulated and belong to the cytochrome P450 genes family. Finally, cytochrome P450 and glutathione S-transferase genes family, as well as hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroid delta-isomerase 4, were introduced as the critical targeted genes.Conclusion: In conclusion, detoxification of xenobiotics, cellular metabolism and homeostasis, the pathogenesis of some liver diseases, synthesis of several prostaglandins and steroid hormones, and inflammation fibrosis in the liver are possibly associated with alcohol consumption.

Bioinformatics analysis of effective biomarkers and immune infiltration in type 2 diabetes with cognitive impairment and aging

With the increasing prevalence of diabetes mellitus worldwide, type 2 diabetes mellitus (T2D) combined with cognitive impairment and aging has become one of the common and important complications of diabetes mellitus, which seriously affects the quality of life of the patients, and imposes a heavy burden on the patients’ families and the society. Currently, there are no special measures for the treatment of cognitive impairment and aging in type 2 diabetes mellitus. Therefore, the search for potential biological markers of type 2 diabetes mellitus combined with cognitive impairment and aging is of great significance for future precisive treatment. We downloaded three gene expression datasets from the GEO database: GSE161355 (related to T2D with cognitive impairment and aging), GSE122063, and GSE5281 (related to Alzheimer’s disease). Differentially expressed genes (DEGs) were identified, followed by gene set enrichment analysis (GSEA). A protein-protein interaction (PPI) network was constructed using the STRING database, and the top 15 hub genes were identified using the CytoHubba plugin in Cytoscape. Core genes were ultimately determined using three machine learning methods: LASSO regression, Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Linear Discriminant Analysis (LDA). The diagnostic performance of these genes was assessed using ROC curve analysis and validated in an independent dataset (GSE5281). Regulatory genes related to ferroptosis were screened from the FerrDb database, and their biological functions were further explored through GO and KEGG enrichment analyses. Finally, the CIBERSORT algorithm was used to analyze immune cell infiltration, and the correlation between core genes and immune cell infiltration levels was calculated, leading to the construction of an mRNA-miRNA regulatory network. In the GSE161355 and GSE122063 datasets, 217 common DEGs were identified. GSEA analysis revealed their enrichment in the PI3K-PLC-TRK signaling pathway, TP53 regulation of metabolic genes pathway, Notch signaling pathway, among others. PPI network analysis identified 15 candidate core genes, and further selection using LASSO, LDA, and SVM-RFE machine learning algorithms resulted in 6 core genes: BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1. ROC curve analysis indicated that these genes had good diagnostic performance in the GSE161355 dataset, with TP53 and IL1B achieving an AUC of 0.9, indicating the highest predictive accuracy. BCL6, HSP90AA1, CRYAB, and DNAJB1 also had AUCs greater than 0.8, demonstrating moderate predictive accuracy. Validation in the independent dataset GSE5281 showed that these core genes also had good diagnostic performance in Alzheimer’s disease samples (AUC > 0.6). Ferroptosis-related analysis revealed that IL1B and TP53 play significant roles in apoptosis and immune response. Immune cell infiltration analysis showed that IL1B is significantly positively correlated with infiltration levels of monocytes and NK cells, while TP53 is significantly negatively correlated with infiltration levels of follicular helper T cells. The construction of the miRNA-mRNA regulatory network suggested that miR-150a-5p might play a key role in the regulation of T2D-associated cognitive impairment and aging by TP53. This study, by integrating bioinformatics and machine learning methods, identified BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1 as potential diagnostic biomarkers for T2D with cognitive impairment and aging, with a particular emphasis on the significance of TP53 and IL1B in immune cell infiltration. These findings not only enhance our understanding of the molecular mechanisms linking type 2 diabetes to cognitive impairment and aging, providing new targets for early diagnosis and treatment, but also offer new directions and targets for basic research.