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PubMed2024

Effect of light on ascorbic acid biosynthesis and bioinformatics analysis of related genes in Chinese chives.

Ascorbic acid (AsA) is an essential nutritional component and powerful antioxidant in vegetables, and in plants, AsA levels are regulated by light. AsA levels in the leaves of Chinese chive (Allium tuberosum Rottler ex Spr), a popular vegetable, are poorly understood. Thus, this study was performed to assess the influence of light on AsA biosynthesis in chive and select related genes (AtuGGP1 and AtuGME1); in addition, bioinformatic analyses and gene expression level assays were performed. The biological information obtained for AtuGGP1 and AtuGME1 was analysed with several tools, including NCBI, DNAMAN, and MEGA11. After different light treatments were performed, the Chive AsA content and AtuGGP1 and AtuGME1 expression levels were determined. These results suggest that 1) compared with natural light, continuous darkness inhibited AsA synthesis in chives. 2) The amino acid sequences of AtuGGP1 and AtuGME1 are very similar to those of other plants. 3) The trends observed for the expression levels of AtuGGP1 and AtuGME1 were consistent with the AsA content observed in chives. Hence, we speculated that light controls AsA biosynthesis in chives by regulating AtuGGP1 and AtuGME1 expression. This study provided impactful and informative evidence regarding the functions of GGP and GME in chives.

Ascorbic Acid↗

PubMed2026

Exploring the Role of HSD17B2 in Colorectal Cancer Through Bioinformatic Analysis: Preliminary Insights for Prognostic Evaluation.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related mortality worldwide. Although screening has reduced CRC in older adults, cases in younger individuals are rising, highlighting the need for early biomarkers. Emerging research highlights the role of estrogen metabolism in CRC progression, with enzymes such as hydroxysteroid (17-beta) dehydrogenase (HSD17B) being increasingly implicated. In this study, we performed a bioinformatics analysis using publicly available datasets, including The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) cohort and two independent Gene Expression Omnibus (GEO) cohorts (GSE40967 and GSE41258), to investigate the role of HSD17B enzymes in CRC. Our results suggest that HSD17B2 is frequently downregulated in precancerous lesions and early-stage CRC, which may contribute to elevated estradiol levels and a tumor-promoting microenvironment. In advanced stages, higher HSD17B2 expression levels are associated with poorer survival outcomes in retrospective cohorts. Other HSD17B enzymes also exhibit significant expression changes, further complicating the hormonal landscape of CRC. In addition, estrone, traditionally considered a weaker estrogen, emerges as a potential driver of CRC progression. Our in-silico analyses indicate that HSD17B2 and HSD17B11 warrant further investigation as candidate biomarkers for distinguishing CRC from benign and precancerous conditions, with the combination showing strong discriminatory power in Receiver Operating Characteristic (ROC) analyses. Overall, these findings highlight the potential role of estrogen metabolism in CRC and suggest that HSD17B enzymes may hold value as candidate prognostic and diagnostic indicators, though their clinical utility remains hypothetical at this stage. Experimental and clinical validation is strictly required to confirm these in silico observations and to clarify their mechanisms in CRC.

Humans↗

PubMed2026

Bioinformatics and Quantitative Real-Time Polymerase Chain Reaction Analysis of SUCNR1 and GPR37L1 in Schizophrenia.

Schizophrenia is a severe, complex, and multifactorial mental disorder involving numerous genetic susceptibility elements, leading to substantial disability, morbidity, and mortality. Despite significant progress in understanding its pathophysiology and etiology, specific diagnostic biomarkers for schizophrenia remain elusive. This study aimed to identify candidate molecular markers associated with schizophrenia. An integrated bioinformatics analysis was performed on the public microarray dataset GSE54913. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the most significantly enriched GO terms were related to channel activity, including passive transmembrane transporter activity, ion channel activity, gated channel activity, and substrate-specific channel activity. The top five enriched KEGG pathways were insulin secretion, cAMP signaling pathway, nucleotide excision repair, TNF signaling pathway, and glutathione metabolism. Validation was conducted using quantitative real-time polymerase chain reaction (qRT-PCR) on an independent sample set from Wuhan Rongjun Youfu Hospital. The qRT-PCR results were largely consistent with the microarray analysis (Pearson r = 0.89, 95% CI: 0.66-0.97). Protein-protein interaction (PPI) network analysis identified two hub genes, SUCNR1 and GPR37L1, which were significantly associated with the GO term 'ion channel activity' and enriched in the KEGG pathway 'insulin secretion'. Furthermore, SUCNR1 expression showed a negative correlation with verbal memory scores (r = -0.54, P = 0.015), whereas GPR37L1 expression showed a positive correlation (r = 0.59, P = 0.0034). These findings suggest that altered SUCNR1 and GPR37L1 expression may be associated with schizophrenia and may represent candidate molecular markers for further investigation.

Humans↗

PubMed2026

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans↗

PubMed2026

Physiological sub-typing of cold and freezing injury in Triticum turgidum subspecies with bioinformatic and expression characterization of glutathione reductase.

BACKGROUND: This study examined how different subspecies of Triticum turgidum (T. durum, T. polonicum, T. turanicum) respond to cold and freezing, assessing their water status, stress responses, and antioxidant system, with particular focus on the structure and function of glutathione reductase (TtGR). METHODS: TtGR genes were first identified from the T. turgidum genome using publicly available genomic resources such as Ensembl Plants. Promoter regions (~2 kb upstream) were analyzed to identify cis-regulatory elements using PlantCARE. Gene classification was performed based on predicted subcellular localization and conserved domain features. Plants were subjected to cold acclimation and freezing treatments, and physiological, biochemical, and enzymatic parameters were measured. RESULTS: Bioinformatics analyses identified four TtGR genes in the T. turgidum genome. The genes in two groups: cytosolic (Class I) and chloroplastic (Class II). Gene structure analysis showed a conserved exon-intron organization, while motif analysis confirmed the presence of Nicotinamide Adenine Dinucleotide Phosphate (NADPH)-binding and redox-active domains across all TtGR proteins. Several regulatory sequences in the promoters are involved in cold (DRE), abscisic acid (ABRE), and stress (STRE) responses, indicating that TtGR genes are dynamically regulated in response to environmental changes. Physiological analyses showed that freezing treatment reduces leaf water content in all genotypes, leading to turgor loss, hydrogen peroxide (H2O2) accumulation, and increased malondealdehyte (MDA) levels. However, tolerance mechanisms addressing water stress and membrane damage differ among genotypes. At the biochemical level, activation of the antioxidant defense system occurs in all genotypes. T. turanicum displays strong defense by significantly increasing enzyme activities, ensuring that the ascorbate-glutathione cycle continues under stress. By contrast, T. polonicum, although showing increased overall enzyme activities, experiences a dramatic drop in glutathione reductase (GR) activity at freezing temperatures, which restricts reduced glutathione (GSH) regeneration and creates a functional bottleneck in the antioxidant cycle. T. durum fails to sustain enzyme activities over the stress period, leading to an intermediate-sensitive response. Thus, whereas T. turanicum effectively maintains antioxidant function during freezing, T. polonicum and T. durum exhibit less efficient stress responses, either through enzymatic bottlenecks or a lack of sustained defense. CONCLUSIONS: One of the most striking findings of this study is the observed dissociation between TtGR gene expression levels and enzyme activities. Low temperature limits the link between transcription and enzyme function. The primary determinant of low-temperature tolerance in T. turgidum subspecies is the sustainability of GR enzyme activity and GSH regeneration under freezing conditions.

Triticum↗

PubMed2025

Bioinformatic analyses and validated experiments reveal an aging hallmark gene set and protective miR of coronary artery disease.

To investigate how aging hallmarks exert roles in the age-related disease of coronary artery disease (CAD). R software and the GEO2R online tool identified differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMis) in CAD microarray datasets from the Gene Expression Omnibus. Genes common to target genes of DEMis, DEGs, and an aging gene list from Human Aging Genomic Resources were then identified and analyzed for protein-protein interactions and functional and pathway enrichment. An miR-mRNA network was constructed using Cytoscape. Receiver operating characteristic curve analysis assessed the diagnostic utility of DEMis in CAD. The expression of two DEMis from a CAD cohort was employed to validate the findings. An aging hallmark gene set, comprising 18 genes, was delineated, with the hub gene TP53 established through protein-protein interaction and microRNA-mRNA networks. Within the microRNA-mRNA network, two DEMis (hsa-miR-423-5p and hsa-miR-564) potentially regulated TP53, rendering them potential CAD biomarkers, as indicated by their area under the curves (AUC) surpassing 0.6. Validation experiments corroborated an AUC of 0.7002 for hsa-miR-423-5p and 0.7261 for hsa-miR-564, highlighting its protective association with CAD. Combining hsa-miR-423-5p, hsa-miR-564, total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), white blood cells (WBC) achieved an area under the receiver operating characteristics curve of 0.783. A CAD-associated gene set was identified, with TP53 as the central hub. Hsa-miR-564 emerged as a potential protective factor against CAD.

Humans↗

PubMed2026

Digital Kennison: A bioinformatics pipeline for rapid mapping of sequences to the Drosophila melanogaster Y chromosome.

The Drosophila melanogaster Y chromosome is currently known to contain 13 single-copy protein-coding genes, six of which are essential for male fertility, as well as several non-coding genes and abundant repetitive DNA. Localization of Y-linked sequences has traditionally relied on labor-intensive crosses using Kennison's translocation strains, which map Y-linked loci by generating flies deficient for each of the six Y-chromosome fertility regions (ks-1, ks-2, kl-1, kl-2, kl-3, and kl-5). Here we present Digital Kennison, a computational pipeline that recasts this classical mapping strategy as a sequence-based analysis. The pipeline queries eight genomic databases derived from Kennison's strains using BLAST and read coverage, assigning sequences to fertility regions or the centromeric region with a calibrated confidence score. We benchmarked the method on 60 Y-linked sequences spanning all seven regions, including single-copy protein-coding genes, Mst77Y family members, non-coding RNAs, and the centromere. Digital Kennison achieved 97% precision while resolving challenging cases, including boundary-spanning genes (PRY and Ppr-Y), fragmented Mst77Y copies, and FDY, which has a closely related autosomal paralog. Beyond validating known localizations, the pipeline localized the unmapped gene CG41561 to the kl-1region and reassigned the transcript CR40629-RC from the kl-2 region to kl-5. It also localized 7 of 16 recently transferred Y-linked sequences, including 4 with high confidence. Applied to 904 R6 scaffolds, Digital Kennison assigned 75% to fertility regions, including five currently annotated as autosomal-pericentromeric. Digital Kennison reduces sequence localization from weeks of genetic crosses to minutes of computation while preserving the power of classical translocation mapping.

Drosophila melanogaster↗

PubMed2024

Bioinformatics analysis of ferroptosis in frozen shoulder.

OBJECTIVES: Frozen shoulder is a common shoulder disease that significantly affects the patient's life and work. Ferroptosis is a new type of programmed cell death, which is involved in many diseases. However, there have been no studies reporting the relationship between frozen shoulders and ferroptosis. This study identified potential molecular markers of ferroptosis in frozen shoulders to provide more effective strategies for the treatment of frozen shoulders. METHODS: GSE238053 was downloaded from the Gene Expression Omnibus (GEO) dataset and intersected with ferroptosis genes to obtain differentially expressed genes (DEGs). The signaling pathways and biological functions of DEGs were performed by WebGestalt and Metascape. The interactions related to these DEGs and the key genes between frozen shoulders and ferroptosis was performed by STRING and Cytoscape. A frozen shoulders rat model was used to validate our predicted genes, Western Blot and qRT-PCR was used to assess the expression levels of our genes of interest. RESULTS: A total of 34 DEGs between GSE238053 and Ferroptosis Database were obtained, most of which were involved in the HIF-1 signaling pathway and inflammatory response. A protein-protein interaction network was obtained by Cytoscape and the key genes (IL-6, HMOX1 and TLR4) were screened by MCODE. Our results of Western Blot showed that the protein expression level of TLR4 and HMOX1 were elevated, and the protein level of IL-6 decreased in frozen shoulders rat model. The mRNA level after frozen shoulders showed that IL-6 was upregulated, whereas TLR4 and HMOX1were downregulated. CONCLUSIONS: The results demonstrated that ferroptosis may affect the pathological process of frozen shoulders through these signaling pathways and genes. The identification of IL-6, HMOX1 and TLR4 genes can provide new therapeutic targets for frozen shoulders.

Ferroptosis↗

PubMed2025

Bioinformatics analysis of miR-2861 and miR-5011-5p that function as potential tumor suppressors in colorectal carcinogenesis.

BACKGROUND: The study aimed to was to investigate the relationship between miR-2861, miR-5011-5p, and colorectal carcinogenesis. METHOD: In the present study, it was isolated RNA from both the tumor and non-tumor tissue of a total of 80 CRC patients and after synthesizing the cDNA, it was performed qRT-PCR to determine the expression levels of miR‑2861 and miR‑5011-5p. In addition, it was predicted that dysregulated miRNAs targets, pathways and functional gene annotations that may be important in colorectal carcinogenesis using KEGG pathway and GO analysis. RESULTS: The resulting data revealed that both expression levels of miR-2861 and miR-5011-5p were significantly decreased in tumor tissues compared with non-tumor tissues of CRC patients. The GO and KEGG pathway analysis showed that miR-2861 and miR-5011-5p may participate in multiple the biological process, cellular components, and molecular function subcategories such as mitotic cell cycle, regulation of small GTPase mediated signal transduction, cell death, and acid binding transcription factor activity. It was also revealed that target genes of miRNAs can be found in signaling pathways such as TGF-beta, Rap1, Ras, cAMP, Wnt, mTOR and, PI3K-Akt signaling pathways. CONCLUSION: These findings imply that miR-2861 and miR-5011-5p might function as tumor suppressors in the development of CRC.

MicroRNAs↗

PubMed2025

FOSB is a key factor in the genetic link between inflammatory bowel disease and acute myocardial infarction: multiple bioinformatics analyses and validation.

BACKGROUND: Inflammatory Bowel Disease (IBD), which includes Crohn's disease and ulcerative colitis, is associated with an increased risk of Acute Myocardial Infarction (AMI). The genetic mechanisms underlying this link are not well understood. METHODS: We downloaded IBD and AMI-related microarray datasets from the NCBI Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and analyzed using enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning techniques, including LASSO, random forest, and Boruta, were employed to screen for hub genes. These genes were validated through qRT-PCR and Western blotting. Single-cell sequencing was used to confirm findings. Additionally, potential therapeutic targets were identified using the Connectivity Map (CMap) database. RESULTS: Five key hub genes-THBD, FOSB, ADGPR3, IL1R2, and PLAUR-were identified as significantly involved in both IBD and AMI pathogenesis. A diagnostic model for AMI constructed using these hub genes demonstrated high predictive accuracy. Single-cell sequencing analysis and several potential drugs targeting these hub genes were identified, offering new therapeutic avenues. CONCLUSION: This study highlights the crucial role of FOSB and other hub genes in the comorbidity of IBD and AMI. The findings provide novel insights for early diagnosis and potential therapeutic strategies, emphasizing the importance of further investigation into these genetic links.

Humans↗

PubMed2025

Identifying potential novel biomarkers for varicocele: A bioinformatics approach to genomics analysis.

Introduction: Varicocele, characterized by the enlargement of scrotal veins, is a common contributor to male infertility, but its genetic underpinnings remain largely unknown. Aim: The goal of this study is to identify potential biomarkers associated with varicocele in order to better understand its molecular mechanisms. Materials and methods: Using the three primary databases, NCBI, DisGeNET, and OpenTarget, we analyzed gene variants and found 79 pertinent genes associated with varicocele. Protein-protein interaction analysis was performed using STRING and visualized with Cytoscape. Molecular Complex Detection (MCODE) and CytoHubba tools helped identify significant protein clusters. Results: The gene ontology analysis shows that there are 79 proteins involved in the inflammatory process, the regulation of gene expression, and cellular components that play a role in oxidative stress and angiogenesis. Our results revealed three key biomarkers: Interleukin-1 beta (IL1B), B-cell lymphoma 2 (BCL2), and matrix metalloproteinase-9 (MMP-9). These proteins are involved in critical processes, such as inflammation, oxidative stress, angiogenesis, and vascular damage, that are central to the pathophysiology of varicocele. Conclusion: The identification of IL1B, BCL2, and MMP-9 offers new insights into varicocele’s molecular mechanisms and suggests potential targets for diagnostic and therapeutic strategies, advancing personalized treatment approaches for fertility restoration.

Humans↗

PubMed2026

Bioinformatics Analysis and Experimental Validation of Key Genes Associated With Hypoxia and Ischemia in Myocardial Infarction.

BACKGROUND: This study aimed to screen and identify core hypoxia-ischemia-related genes associated with myocardial infarction (MI). METHOD: Two transcriptomic datasets, GSE97320 and GSE48060, were retrieved from the Gene Expression Omnibus (GEO) database. After data integration and batch effect elimination, differential expression analysis was performed to screen differentially expressed genes (DEGs), and the corresponding visualization analysis was conducted. Hypoxia-ischemia-related genes were acquired from the GeneCards database; hypoxia-ischemia related genes (HIRGs) were subsequently identified by intersecting the retrieved genes with screened DEGs. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were implemented to explore the biological functions and underlying signaling pathways of HIRGs. A combination of protein-protein interaction (PPI) network analysis and random forest (RF) algorithm was applied to screen hub genes from HIRGs. The external GEO dataset GSE66360 was utilized to validate the expression patterns of candidate hub genes. Furthermore, an acute myocardial infarction (AMI) mouse model was established, and quantitative real-time polymerase chain reaction (qPCR) was performed to detect the mRNA expression levels of hub genes in myocardial tissues for in vivo validation. RESULTS: A total of 633 DEGs and 308 hypoxia-ischemia-related genes were screened in the present study, among which 21 overlapping HIRGs were obtained. PLAUR and IL1B were finally identified as two hub genes from HIRGs based on PPI network and random forest algorithm. The qPCR results revealed that the expression levels of PLAUR and IL1B were significantly upregulated in the AMI group compared with the sham operation group (p < 0.05). CONCLUSION: The present findings demonstrated that PLAUR and IL1B serve as pivotal genes involved in the pathological hypoxia-ischemia process of AMI. These two genes may act as novel biomarkers and promising therapeutic targets for the recognition and clinical intervention of hypoxia-ischemia injury following AMI.

Myocardial Infarction↗

PubMed2025

Expression and prognosis of CXCL13 in uterine corpus endometrial carcinoma based on bioinformatics analysis.

OBJECTIVE: The biological significance of the chemokine ligand C-X-C motif chemokine ligand 13 (CXCL13) may play a significant role in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). This study aims to identify and verify CXCL13 with predictive value for prognosis in UCEC. METHODS: CXCL13 mRNA expression differences were analyzed using R software in three independent datasets: one each from The Cancer Genome Atlas (TCGA) and two from the Gene Expression Omnibus (GEO), namely GSE17025 and GSE106191. The correlation between CXCL13 expression and prognosis was evaluated by Kaplan-Meier analysis. Univariate and multivariate Cox analyses were utilized to construct a prognostic nomogram. Tumor Immune Estimation Resource (TIMER) and the Tumor and Immune System Interaction Database (TISIDB) were employed to assess the relationship between CXCL13 and tumor immune infiltration. Coexpressed genes with CXCL13 were identified by the Spearman correlation analysis. A CXCL13 protein-protein interaction (PPI) network was constructed with the STRING website tool and hub genes were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses were performed with the "clusterProfiler" R package. Gene set enrichment analysis (GSEA) was used to identify underlying biological mechanisms. A drug-gene interaction network was constructed in the Comparative Toxicogenomics Database (CTD). RESULTS: High CXCL13 mRNA expression were validated in UCEC in the above three independent datasets. High CXCL13 expression was associated with favorable prognosis in UCEC. A nomogram for predicting the 1-, 3-, and 5-year survival probability in UCEC was construct based on CXCL13 expression and other clinical parameters. The use of Spearman correlation indicated certain correlation between CXCL13 and immune cells and immune checkpoint (ICP) genes. Seven hub genes were upregulated in UCEC, namely CXCL9, IFNG, CXCL10, CXCL11, GBP5, CCL18, and GZMB. The expression and prognostic relevance of CXCL9, IFNG, GBP5, and GZMB were in accordance with CXCL13. The main biological processes enriched were cytokine-cytokine receptor interaction and chemokine signaling pathway. CONCLUSIONS: The above comprehensive analyses suggest that CXCL13 may serve as a potential prognostic biomarker for UCEC, specifically for early-stage UCEC.

CXCL13↗

PubMed2024

Bioinformatic approaches for accurate assessment of A-to-I editing in complete transcriptomes.

A-to-I RNA editing is an RNA modification that alters the RNA sequence relative to the its genomic blueprint. It is catalyzed by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes, and contributes to the complexity and diversification of the proteome. Advancement in the study of A-to-I RNA editing has been facilitated by computational approaches for accurate mapping and quantification of A-to-I RNA editing based on sequencing data. In this chapter we review some of the main computational approaches currently used, describe potential hurdles, challenges and pitfalls, and discuss possible ways to mitigate them.

RNA Editing↗

PubMed2026

ReGAIN: a bioinformatics platform for assessing probabilistic co-occurrence between resistance genes in bacterial pathogens.

MOTIVATION: Multidrug-resistant bacterial pathogens continue to rise globally, yet scalable methods are needed to infer how resistance determinants co-occur across pathogen populations and to quantify conditional dependencies underlying co-occurrence and shared genetic context. RESULTS: We present ReGAIN (Resistance Gene Association and Inference Network), an open-source platform that applies Bayesian network structure learning to infer probabilistic, conditional dependency relationships among antibiotic resistance, heavy metal tolerance, stress response, and virulence determinants in bacteria. In contrast to pairwise co-occurrence analyses, ReGAIN reports conditional probabilities, relative risks, and absolute risk differences with confidence intervals to prioritize candidate relationships for downstream prioritization. Applied across ESKAPEE pathogens, ReGAIN recapitulated established resistance gene relationships and identified additional candidate patterns consistent with co-selection and shared genetic context. Together, these results support scalable, reproducible population-wide analysis of resistance networks for surveillance, comparative genomics and epidemiology. AVAILABILITY: ReGAIN analyses are performed using Python v3.11.5 and R v4.4.1 and is available as open-source software through Bioconda at {https://anaconda.org/bioconda/regain-cli}. Source code and documentation can be found at {https://github.com/ERBringHorvath/regain_CLI}. All genomes used in this publication were downloaded from the National Center for Biotechnology Information database. Large supplementary tables and results data from the ESKAPEE pathogen example network analyses can be downloaded from https://figshare.com/articles/dataset/ReGAIN_command_line_software_and_supplemental_figures_/28959431.

Computational Biology↗

PubMed2026

Identification of putative causal associations between MicroRNAs and breast cancer via Mendelian randomization and bioinformatic analysis.

MicroRNAs (miRNAs) are implicated in breast cancer progression and prognosis. This study employed a Mendelian randomization (MR) framework to investigate causal relationships between plasma circulating miRNAs and breast cancer. miRNA expression quantitative trait loci were extracted from 2 independent cohorts. High-confidence miRNAs and their associated single-nucleotide polymorphisms were selected for 2-sample MR analyses using inverse-variance weighted and MR-Egger methods. Differential expression analysis and univariate Cox regression identified survival-associated genes in breast cancer, while enrichment analyses revealed pathways and biological processes linked to candidate targets. Pan-cancer analyses of miRNAs and targets were conducted via the ENCORI platform. Initial MR analyses in the discovery phase identified hsa-miR-100-5p, hsa-miR-125b-5p, and hsa-miR-339-5p as significantly associated with reduced breast cancer risk (P < .05), suggesting potential protective roles. A total of 1291 survival-associated differentially expressed genes were identified, with 39 overlapping targets implicated in miRNA-mediated breast cancer intervention. Enrichment analyses highlighted their involvement in cell cycle regulation and p53 signaling pathway. In the validation cohort, only hsa-miR-339-5p confirmed a protective effect on breast cancer risk, while hsa-miR-100-5p and hsa-miR-125b-5p did not reach significance. Pan-cancer profiling demonstrated aberrant miRNA expression across malignancies, prognostic relevance in multiple cancers, and significant negative correlations between miRNAs and target genes in breast tumors. Our findings provide novel insights into the causal roles of miRNAs in breast cancer pathogenesis and underscore their potential as noninvasive biomarkers and therapeutic targets. Future studies should prioritize functional validation and clinical translation of these miRNAs.

Humans↗

PubMed2026

A Novel Long Noncoding RNA-LNC000133 Associated With Steroid-Induced Osteonecrosis of the Femoral Head Promotes Osteoblast Differentiation Through Bone Marrow Mesenchymal Stem Cells-Derived Exosomes Pathway: A Bioinformatics Validation and Detailed Mechanistic Study.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a debilitating disease caused by glucocorticoid abuse, characterized by complex pathogenesis and unclear molecular mechanisms. Dysfunction of bone marrow mesenchymal stem cells (BMSCs) and their exosome-mediated signalling is a key contributor to SONFH, although the precise mechanisms remain to be elucidated. In this study, the differential expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) in exosomes derived from human BMSCs (hBMSCs) obtained from patients with SONFH compared to controls with femoral neck fractures were identified. Through next-generation sequencing, a novel lncRNA, LNC000133, associated with SONFH was discovered. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and competing endogenous RNA (ceRNA) network construction, the LNC000133/miR-362-5p/TGF-β3/SMAD3/BMP2 signalling axis was established. The definitive expression, localization and full-length sequence of LNC000133 in BMSCs were subsequently validated by Northern blot, quantitative real-time polymerase chain reaction (qRT-PCR), fluorescence in situ hybridization (FISH) and rapid amplification of cDNA ends (RACE). Most notably, mechanistic studies demonstrated that LNC000133-modified BMSCs-derived exosomes were efficiently taken up by osteoblasts, which promoted proliferation and osteogenic differentiation by targeting the miR-362-5p/TGF-β3/SMAD3/BMP2 signalling pathway.

Humans↗

PubMed2026

Detection of short tandem repeats in the cattle genome: a comparison of bioinformatic tools.

BACKGROUND: Short tandem repeats (STRs) are repetitive DNA sequences with 1–6 nucleotide repeat units, exhibiting high polymorphism due to varying repeat counts. STRs are more variable than SNPs and can cause genetic disorders. With population-scale cattle whole-genome sequencing data available, whole-genome STR identification has attracted new interest, but challenges remain due to the lack of standardized methods, sequencing data limitations, and the diversity of STR-calling tools. This study compared six STR-calling tools: HipSTR, GangSTR, and ExpansionHunter for short-read data, and Straglr, RepeatHMM, and LongTR for Oxford Nanopore (ONT) long-read data—using sequences from five Holstein cattle (two parent–offspring trios with a shared sire). This is the first cattle study to evaluate short- and long-read STR callers using both data types from the same animals. RESULTS: In short-read data, ExpansionHunter identified the highest number of polymorphic STRs (pSTRs) (327,690), followed by HipSTR (205,900) and GangSTR (110,680), with 93,023 loci detected by all three tools. In long-read data, LongTR detected 470,250 pSTRs, RepeatHMM 224,185, and Straglr 90,275, with only 33,253 loci shared among them. Mendelian consistency of STR genotypes in the trio offspring was high (> 0.8) for all short-read tools, with HipSTR and GangSTR highest at 0.98. LongTR was the only long-read tool with high consistency (0.88). Short-read tools also showed higher concordance in STR genotypes among themselves than was observed among long-read tools. However, long-read tools had a clear advantage in detecting large STRs. Relative to computational efficiency, HipSTR and GangSTR (short-reads), and LongTR (long-reads) required less memory and shorter runtimes than the other tools. CONCLUSIONS: Tool selection is critical for accurate whole-genome STR identification in cattle. For short-read data, HipSTR showed relatively high Mendelian consistency and concordance compared to the other tools, while ExpansionHunter was able to detect longer STRs but with lower Mendelian consistency. For long-read data, LongTR demonstrated higher consistency and computational efficiency relative to the other tools. Based on these results, HipSTR and LongTR are suggested as preferred options for short-read and ONT long-read datasets, respectively, in cattle STR analysis. These recommendations are based on the metrics observed in this study, and confirmatory analyses across additional breeds, larger sample sizes, and validated truth sets are encouraged.

Animals↗