mRNA Expression Profiles Research Articles

Analysis of long noncoding RNA and mRNA profiling in peripheral blood mononuclear cells of human immunized with rabies virus vaccine by RNA sequencing

BackgroundThe rabies virus (RABV) continues to be the deadly cause of rabies and to be a hazard to international health. The specific epigenetic modifications in the host response to RABV vaccination have not been fully elucidated. While long noncoding RNAs (lncRNAs) are known to play crucial roles in viral infection control, their specific expression profiles in humans vaccinated against RABV have not been clearly defined. MethodsThis study investigated the lncRNAs and mRNAs expression profiles in four volunteers vaccinated with the RABV vaccine using high-throughput RNA sequencing. ResultsWe have discovered 33 lncRNAs and 427 mRNAs that exhibited differential expression after RABV vaccination. The functional annotation, utilizing gene ontology and Kyoto Encyclopedia of Genes and Genomes pathways, revealed that these lncRNAs are involved in signaling pathways that enhance host immune response to RABV vaccination. ConclusionsOur findings indicate that these lncRNAs, via influencing host immune response, could be explored as potential therapeutic targets in treatments against RABV infection. To the best of our knowledge, it is the first time to report the transcriptome landscape of lncRNAs in human immunized with RABV vaccine.

Exploring the underlying molecular mechanisms of acute myocardial infarction after SARS-CoV-2 infection

An increase in acute myocardial infarction (AMI)-related deaths has been reported during the COVID-19 pandemic. Despite evidence suggesting the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and AMI, the underlying mechanisms remain unclear. Here, we integrated mRNA and microRNA expression profiles related to SARS-CoV-2 infection and AMI from public databases. We then performed transcriptomic analysis using bioinformatics and systems biology approaches to explore the potential molecular mechanisms of SARS-CoV-2 infection affects AMI. First, twenty-one common differentially expressed genes (DEGs) were identified from SARS-CoV-2 infection and AMI patients in endothelial cells datasets and then we performed functional analysis to predict the roles of these DEGs. The functional analysis emphasized that the endothelial cell response to cytokine stimulus due to excessive inflammation was essential in these two diseases. Importantly, the tumor necrosis factor and interleukin-17 signaling pathways appeared to be integral factors in this mechanism. Interestingly, most of these common genes were also upregulated in transcriptomic datasets of SARS-CoV-2-infected cardiomyocytes, suggesting that these genes may be shared in cardiac- and vascular-related injuries. We subsequently built a protein-protein interaction network and extracted hub genes and essential modules from this network. At the transcriptional and post-transcriptional levels, regulatory networks with common DEGs were also constructed, and some key regulator signatures were further identified and validated. In summary, our research revealed that a highly activated inflammatory response in patients with COVID-19 might be a crucial factor for susceptibility to AMI and we identified some candidate genes and regulators that could be used as biomarkers or potential therapeutic targets.

Heterogenous Gene Expression of Bicellular and Tricellular Tight Junction-Sealing Components in the Human Intestinal Tract.

A major site for the absorption of orally administered drugs is the intestinal tract, where the mucosal epithelium functions as a barrier separating the inside body from the outer environment. The intercellular spaces between adjacent epithelial cells are sealed by bicellular and tricellular tight junctions (TJs). Although one strategy for enhancing intestinal drug absorption is to modulate these TJs, comprehensive gene (mRNA) expression analysis of the TJs components has never been fully carried out in humans. In this study, we used human biopsy samples of normal-appearing mucosa showing no endoscopically visible inflammation collected from the duodenum, jejunum, ileum, colon, and rectum to examine the mRNA expression profiles of TJ components, including occludin and tricellulin and members of the claudin family, zonula occludens family, junctional adhesion molecule (JAM) family, and angulin family. Levels of claudin-3, -4, -7, -8, and -23 expression became more elevated in each segment along the intestinal tract from the upper segments to the lower segments, as did levels of angulin-1 and -2 expression. In contrast, expression of claudin-2 and -15 was decreased in the large intestine compared to the small intestine. Levels of occludin, tricellulin, and JAM-B and -C expression were unchanged throughout the intestine. Considering their segment specificity, claudin-8, claudin-15, and angulin-2 appear to be targets for the development of permeation enhancers in the rectum, small intestine, and large intestine, respectively. These data on heterogenous expression profiles of intestinal TJ components will be useful for the development of safe and efficient intestinal permeation enhancers.

Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

BackgroundVariations exist in the response of patients with Crohn’s disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD.MethodsThe GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset.ResultsA total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers.ConclusionsTh1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients.Trial registration: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.clinicaltrials.gov.

Identifying miRNA Signatures Associated with Pancreatic Islet Dysfunction in a FOXA2-Deficient iPSC Model.

The pathogenesis of diabetes involves complex changes in the expression profiles of mRNA and non-coding RNAs within pancreatic islet cells. Recent progress in induced pluripotent stem cell (iPSC) technology have allowed the modeling of diabetes-associated genes. Our recent study using FOXA2-deficient human iPSC models has highlighted an essential role for FOXA2 in the development of human pancreas. Here, we aimed to provide further insights on the role of microRNAs (miRNAs) by studying the miRNA-mRNA regulatory networks in iPSC-derived islets lacking the FOXA2 gene. Consistent with our previous findings, the absence of FOXA2 significantly downregulated the expression of islet hormones, INS, and GCG, alongside other key developmental genes in pancreatic islets. Concordantly, RNA-Seq analysis showed significant downregulation of genes related to pancreatic development and upregulation of genes associated with nervous system development and lipid metabolic pathways. Furthermore, the absence of FOXA2 in iPSC-derived pancreatic islets resulted in significant alterations in miRNA expression, with 61 miRNAs upregulated and 99 downregulated. The upregulated miRNAs targeted crucial genes involved in diabetes and pancreatic islet cell development. In contrary, the absence of FOXA2 in islets showed a network of downregulated miRNAs targeting genes related to nervous system development and lipid metabolism. These findings highlight the impact of FOXA2 absence on pancreatic islet development and suggesting intricate miRNA-mRNA regulatory networks affecting pancreatic islet cell development.

Comparative transcriptomic study on the ovarian cancer between chicken and human

The laying hen is the spontaneous model of ovarian tumor. A comprehensive comparison based on RNA-seq from hens and women may shed light on the molecular mechanisms of ovarian cancer. We performed next-generation sequencing of microRNA and mRNA expression profiles in 9 chicken ovarian cancers and 4 normal ovaries, which has been deposited in GSE246604. Together with 6 public datasets (GSE21706, GSE40376, GSE18520, GSE27651, GSE66957, TCGA-OV), we conducted a comparative transcriptomics study between chicken and human. In the present study, miR-451, miR-2188-5p, and miR-10b-5p were differentially expressed in normal ovaries, early- and late-stage ovarian cancers. We also disclosed 499 up-regulated genes and 1,061 down-regulated genes in chicken ovarian cancer. The molecular signals from 9 cancer hallmarks, 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 369 Gene Ontology (GO) pathways exhibited abnormalities in ovarian cancer compared to normal ovaries via Gene Set Enrichment Analysis (GSEA). In the comparative analysis across species, we have uncovered the conservation of 5 KEGG and 76 GO pathways between chicken and human including the mismatch repair and ECM receptor interaction pathways. Moreover, a total of 174 genes contributed to the core enrichment for these KEGG and GO pathways were identified. Among these genes, the 22 genes were found to be associated with overall survival in patients with ovarian cancer. In general, we revealed the microRNA profiles of ovarian cancers in hens and updated the mRNA profiles previously derived from microarrays. And we also disclosed the molecular pathways and core genes of ovarian cancer shared between hens and women, which informs model animal studies and gene-targeted drug development.

Dendritic Cell-Related Immune Marker CD1C for Predicting Prognosis and Immunotherapy Opportunities of Lung Adenocarcinoma Patients.

Lung adenocarcinoma (LUAD) is the most frequent type of lung cancer with a high mortality rate. Here, we aim to explore novel immune-related biomarkers for LUAD patients. Datasets, mRNA expression profiles, and clinical data concerned with LUAD were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), respectively. Differential expression analysis was performed to obtain differentially expressed genes (DEGs). Based on DEGs, we conducted functional enrichment analyses. Subsequently, Kaplan‑Meier (KM) was performed to analyze survival differences among different groups. Furthermore, immune cell infiltration proportion was calculated by CIBERSORT and TIMER. The relationship between gene and immune response was analyzed using Tumor Immune System Interactions (TISIDB) database. Finally, Pearson correlation analysis was performed between CD1C and six immune checkpoints. We identified dendritic cells (DCs)-related expression profiles from four LUAD samples. DCs' immune marker CD1C in LUAD was selected by univariate Cox regression analysis. Low CD1C expression patients had a poor prognosis. A total of 332 DEGs were identified in high and low CD1C expression groups, which primarily enriched in 348 GO terms and 30 KEGG pathways. There were significant differences in the infiltration proportion of 17 immune cells between high and low CD1C expression groups. Most immunomodulators, chemokines, and chemokine receptors were positively associated with CD1C expression. Six immune checkpoints were also positively correlated with CD1C expression. DCs related immunomarker CD1C probably plays a pivotal part in prognosis and immunotherapy of LUAD via a joint analysis of single-cell and bulk sequencing data.

Establishment and validation of a novel disulfidptosis-related immune checkpoint gene signature in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal tumors and is associated with a unfavorable prognosis. Disulfidptosis is a recently identified form of cell death mediated by disulfide bonds. Numerous studies have highlighted the significance of immune checkpoint genes (ICGs) in ccRCC. Nevertheless, the involvement of disulfidptosis-related immune checkpoint genes (DRICGs) in ccRCC remains poorly understood.MethodsThe mRNA expression profiles and clinicopathological data of ccRCC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The associations between disulfidptosis-related genes (DRGs) and immune checkpoint genes (ICGs) were assessed to identify DRICGs. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were conducted to construct a risk signature.ResultsA total of 39 differentially expressed immune-related candidate genes were identified. A prognostic signature was constructed utilizing nine DRICGs (CD276, CD80, CD86, HLA-E, LAG3, PDCD1LG2, PVR, TIGIT, and TNFRSF4) and validated using GEO data. The risk model functioned as an independent prognostic indicator for ccRCC, while the associated nomogram provided a reliable scoring system for ccRCC. Gene set enrichment analysis indicated enrichment of phospholipase D, antigen processing and presentation, and ascorbate and aldarate metabolism-related signaling pathways in the high-risk group. Furthermore, the DRICGs exhibited correlations with the infiltration of various immune cells. It is noteworthy that patients with ccRCC categorized into distinct risk groups based on this model displayed varying sensitivities to potential therapeutic agents.ConclusionsThe novel DRICG-based risk signature is a reliable indicator for the prognosis of ccRCC patients. Moreover, it also aids in drug selection and correlates with the tumour immune microenvironment in ccRCC.

BACH1 impairs hepatocyte regeneration after hepatectomy with repeated ischemia/reperfusion by reprogramming energy metabolism and exacerbating oxidative stress

BTB and CNC homology 1 (BACH1) regulates biological processes, including energy metabolism and oxidative stress. Insufficient liver regeneration after hepatectomy remains an issue for surgeons. The Pringle maneuver is widely used during hepatectomy and induces ischemia/reperfusion (I/R) injury in hepatocytes. A rat model of two-thirds partial hepatectomy with repeated I/R treatment was used to simulate clinical hepatectomy with Pringle maneuver. Delayed recovery of liver function after hepatectomy with the repeated Pringle maneuver in clinic and impaired liver regeneration in rat model were observed. Highly elevated lactate levels, along with reduced mitochondrial complex III and IV activities in liver tissues, indicated that the glycolytic phenotype was promoted after hepatectomy with repeated I/R. mRNA expression profile analysis of glycolysis-related genes in clinical samples and further verification experiments in rat models showed that high BACH1 expression levels correlated with the glycolytic phenotype after hepatectomy with repeated I/R. BACH1 overexpression restricted the proliferative potential of hepatocytes stimulated with HGF. High PDK1 expression and high lactate levels, together with low mitochondrial complex III and IV activities and reduced ATP concentrations, were detected in BACH1-overexpressing hepatocytes with HGF stimulation. Moreover, HO-1 expression was downregulated, and oxidative stress was exacerbated in the BACH1-overexpressing hepatocytes with HGF stimulation. Cell experiments involving repeated hypoxia/reoxygenation revealed that reactive oxygen species accumulation triggered the TGF-β1/BACH1 axis in hepatocytes. Finally, inhibiting BACH1 with the inhibitor hemin effectively restored the liver regenerative ability after hepatectomy with repeated I/R. These results provide a potential therapeutic strategy for impaired liver regeneration after repeated I/R injury.

Integrated physiological, whole transcriptomic and functional analysis reveals the regulatory mechanism in the liver of rainbow trout (Oncorhynchus mykiss) in response to short-term and chronic hypoxia stress

The frequency of fish encountering hypoxia has risen dramatically as global warming and water pollution intensify, posing a serious threat to survival. Rainbow trout (Oncorhynchus mykiss), which is an economically important fish worldwide, belongs to a typical hypoxia-sensitive fish. However, little is known about the differences in response mechanisms employed by rainbow trout to short-term and chronic hypoxia stress and the roles of non-coding RNAs (ncRNAs) in the response of rainbow trout to hypoxia stress. In this study, we systematically analyzed the changes of liver biochemical parameters in rainbow trout exposed to moderate hypoxic conditions (DO: 4.5 ± 0.1 mg/L) for different durations (4, 8, 12, 24 h and 1 month) and 24 h reoxygenation, and histologic and transcriptome profiles (lncRNA, miRNA and mRNA) under hypoxia stress for 12 h (Tm12L) and 1 month (TmlL) compared with control (normoxia, DO: 8.5 ± 0.1 mg/L), and target and regulatory relationships between LOC110520201, miR-2188-y and superoxide dismutase 1 (sod1) were verified by dual-luciferase reporter, overexpression and silencing assays. Histological observations revealed that liver showed no pathological changes in TmlL. Integrating biochemical parameters and mRNA expression profiles, we found that exposure to short-term hypoxia stress resulted in enhanced immune response, aerobic and anaerobic glycolysis and lipid metabolism. In TmlL, increased anaerobic glycolysis and decreased aerobic glycolysis were observed, and antioxidant and immune capacity has returned to normal. Additionally, several key hypoxia-related genes (epo, vegfc, epor, sod1, ppara, foxo1a, gk, dusp1, nlrc3 and nlrp3) and ceRNA regulatory networks were identified from 2711 differentially expressed (DE) mRNAs, 575 DElncRNAs and 395 DEmiRNAs, including LOC110520201-miR-2188-y-sod1, LOC110533332-miR-144-y-vegfc, LOC110526066-miR-465-x-ppara and LOC110535032-miR-743-y-nlrp3. The analysis of expression patterns in rainbow trout liver and liver cells treated with hypoxia suggested that changes in LOC110520201, miR-2188-y and sod1 showed a ceRNA regulatory relationship. Further experiments demonstrated that sod1 was a target of miR-2188-y, and LOC110520201 silencing increased the expression of miR-2188-y and inhibited sod1 expression. These results facilitate our understanding of the molecular mechanisms of hypoxia response in rainbow trout and provide genetic resources for breeding hypoxia-tolerant varieties.

Identification of a signature of histone modifiers in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.

Association of genetic variations of 3′-UTR in clopidogrel pharmacokinetic-relevant genes with clopidogrel response in Han Chinese patients with coronary artery disease

Dual antiplatelet therapy with aspirin and clopidogrel has reduced ischemic vascular events significantly. Genetic influence, especially those in clopidogrel pharmacokinetic-relevant genes partially accounts for interindividual pharmacodynamic variability of clopidogrel. However, most studies have concentrated on the genetic variations in introns, exons, or promoters of the candidate genes, and the association between genetic variations in 3′-UTR in clopidogrel pharmacokinetic-relevant genes and clopidogrel response is unknown. In our study, ten different algorithms were applied to pick potential miRNAs targeting the clopidogrel pharmacokinetic-relevant genes. Furthermore, the correlation between miRNA expression profiles and mRNA expression of corresponding clopidogrel pharmacokinetic-relevant genes was analyzed. Through comprehensive analysis, including bioinformatics prediction and correlation analysis of miRNA and mRNA expression profiles, miR-218–5p and miR-506–5p were supposed to regulate the expression of PON1 via binding with its 3′-UTR. Moreover, PON1 rs854551 and rs854552 were located in miRNA recognizing sequences and may serve as potential miRSNPs possibly affecting PON1 expression. The rs854552 polymorphism was genotyped and platelet reactivity index (PRI) indicative of clopidogrel response was measured in 341 Chinese coronary artery disease (CAD) patients 24 h after administration of 300 mg clopidogrel. Our results showed that PON1 rs854552 had a significant influence on PRI in CAD patients, especially in patients with CYP2C19 extensive metabolic phenotype. In conclusion, PON1 rs854552 polymorphisms may affect clopidogrel response. Bioinformatics prediction followed by functional validation could aid in decoding the contribution of unexplained variations in the 3′-UTR in drug-metabolizing enzymes on clopidogrel response.

Revolutionary multi-omics analysis revealing prognostic signature of thyroid cancer and subsequent in vitro validation of SNAI1 in mediating thyroid cancer progression through EMT

Thyroid carcinoma (TC), the most commonly diagnosed malignancy of the endocrine system, has witnessed a significant rise in incidence over the past few decades. The integration of scRNA-seq with other sequencing approaches offers researchers a distinct perspective to explore mechanisms underlying TC progression. Therefore, it is crucial to develop a prognostic model for TC patients by utilizing a multi-omics approach. We acquired and processed transcriptomic data from the TCGA-THCA dataset, including mRNA expression profiles, lncRNA expression profiles, miRNA expression profiles, methylation chip data, gene mutation data, and clinical data. We constructed a tumor-related risk model using machine learning methods and developed a consensus machine learning-driven signature (CMLS) for accurate and stable prediction of TC patient outcomes. 2 strains of undifferentiated TC cell lines and 1 strain of PTC cell line were utilized for in vitro validation. mRNA, protein levels of hub genes, epithelial-mesenchymal transition (EMT)-associated phenotypes were detected by a series of in vitro experiments. We identified 3 molecular subtypes of TC based on integrated multi-omics clustering algorithms, which were associated with overall survival and displayed distinct molecular features. We developed a CMLS based on 28 hub genes to predict patient outcomes, and demonstrated that CMLS outperformed other prognostic models. TC patients of relatively lower CMLS score had significantly higher levels of T cells, B cells, and macrophages, indicating an immune-activated state. Fibroblasts were predominantly enriched in the high CMLS group, along with markers associated with immune suppression and evasion. We identified several drugs that could be suitable for patients with high CMLS, including Staurosporine_1034, Rapamycin_1084, gemcitabine, and topotecan. SNAI1 was elevated in both undifferentiated TC cell lines, comparing to PTC cells. Knockdown of SNAI1 reduced the cell proliferation and EMT phenotypes of undifferentiated TC cells. Our findings highlight the importance of multi-omics analysis in understanding the molecular subtypes and immune characteristics of TC, and provide a novel prognostic model and potential therapeutic targets for this disease. Moreover, we identified SNAI1 in mediating TC progression through EMT in vitro.

Comparison of the classifiers based on mRNA, microRNA and lncRNA expression and DNA methylation profiles for the tumor origin detection.

Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles. Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites. We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction. In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.

Selection for high and low antibody responses to sheep red blood cells influences cytokine and chemokine expression in chicken peripheral blood leukocytes and splenic tissue

White Leghorn chickens from a common founder population have been divergently selected for high (HAS) or low (LAS) antibody responses to sheep red blood cells (SRBC) for 49 generations resulting in 2 diverse lines for this trait. Much has been studied in these two lines; however, the impact of these selection pressures on cytokine and chemokine expression is not fully understood. The purpose of this study is to determine if selection for antibody response to SRBC impacts cytokine and chemokine expression in peripheral blood leukocytes (PBL) and spleen from HAS and LAS chickens. Total RNA was isolated from PBL and spleen after which mRNA expression of cytokines (IL4, IL6, IL10, TGF-β4) and chemokines (CXCL8, CCL4) were determined by quantitative real-time RT-PCR (qRT-PCR). The data were analyzed using Student's t test comparing HAS and LAS (P < 0.05) and are reported as corrected 40-CT. PBL and spleen samples were analyzed separately. With respect to PBL, expression of IL6 was higher (P < 0.05) in PBL isolated from LAS chickens compared to those from the HAS line whereas there were no differences (P > 0.05) in IL4, IL10, CXCL8, CCL4, or TGF-β4. The cytokine and chemokine mRNA expression profiles were different in the spleen between the two lines. IL4 and CXCL8 expression were higher (P < 0.05) in spleen samples from HAS chickens than LAS. The expression of IL6, IL10, CCL4, or TGF-β4 in the spleens did not differ (P > 0.05) between the lines. The data indicate that selection for specific antibody responses to SRBC impacts the cytokine and chemokine expression profile in PBL and spleens but in different ways in HAS and LAS. These studies provide insight into the influence that selection pressures for antibody responses have on different immune response components, specifically cytokines and chemokines typically involved in the innate response.

Comparative Analysis of mRNA and lncRNA Expression Profiles in Testicular Tissue of Sexually Immature and Sexually Mature Mongolian Horses.

Testicular development and spermatogenesis are tightly regulated by both coding and non-coding genes, with mRNA and lncRNA playing crucial roles in post-transcriptional gene expression regulation. However, there are significant differences in regulatory mechanisms before and after sexual maturity. Nevertheless, the mRNAs and lncRNAs in the testes of Mongolian horses have not been systematically identified. In this study, we first identified the testicular tissues of sexually immature and sexually mature Mongolian horses at the tissue and protein levels, and comprehensively analyzed the expression profiles of mRNA and lncRNA in the testes of 1-year-old (12 months, n = 3) and 10-year-old (n = 3) Mongolian horses using RNA sequencing technology. Through gene expression analysis, we identified 16,582 mRNAs and 2128 unknown lncRNAs that are commonly expressed in both sexually immature and sexually mature Mongolian horses. Meanwhile, 9217 mRNAs (p < 0.05) and 2191 unknown lncRNAs (p < 0.05) were identified as differentially expressed between the two stages, which were further validated by real-time fluorescent quantitative PCR and analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The analysis results showed that genes in the sexually immature stage were mainly enriched in terms related to cellular infrastructure, while genes in the sexually mature stage were enriched in terms associated with hormones, metabolism, and spermatogenesis. In summary, the findings of this study provide valuable resources for a deeper understanding of the molecular mechanisms underlying testicular development and spermatogenesis in Mongolian horses and offer new perspectives for future related research.

Comprehensive analysis of the expression profiles of mRNA, lncRNA, circRNA, and miRNA in primary hair follicles of coarse sheep fetal skin

BackgroundThe Qinghai Tibetan sheep, a local breed renowned for its long hair, has experienced significant deterioration in wool characteristics due to the absence of systematic breeding practices. Therefore, it is imperative to investigate the molecular mechanisms underlying follicle development in order to genetically enhance wool-related traits and safeguard the sustainable utilization of valuable germplasm resources. However, our understanding of the regulatory roles played by coding and non-coding RNAs in hair follicle development remains largely elusive.ResultsA total of 20,874 mRNAs, 25,831 circRNAs, 4087 lncRNAs, and 794 miRNAs were annotated. Among them, we identified 58 DE lncRNAs, 325 DE circRNAs, 924 DE mRNAs, and 228 DE miRNAs during the development of medullary primary hair follicle development. GO and KEGG functional enrichment analyses revealed that the JAK-STAT, TGF-β, Hedgehog, PPAR, cGMP-PKG signaling pathway play crucial roles in regulating fibroblast and epithelial development during skin and hair follicle induction. Furthermore, the interactive network analysis additionally identified several crucial mRNA, circRNA, and lncRNA molecules associated with the process of primary hair follicle development. Ultimately, by investigating DEmir’s role in the ceRNA regulatory network mechanism, we identified 113 circRNA–miRNA pairs and 14 miRNA–mRNA pairs, including IGF2BP1-miR-23-x-novel-circ-01998-MSTRG.7111.3, DPT-miR-370-y-novel-circ-005802-MSTRG.14857.1 and TSPEAR-oar-miR-370-3p-novel-circ-005802- MSTRG.10527.1.ConclusionsOur study offers novel insights into the distinct expression patterns of various transcription types during hair follicle morphogenesis, establishing a solid foundation for unraveling the molecular mechanisms that drive hair development and providing a scientific basis for selectively breeding desirable wool-related traits in this specific breed.

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Assessment of immunomodulatory effects of five commonly used parabens on human THP-1 derived macrophages: Implications for ecological and human health impacts

Parabens are widely used as broad-spectrum anti-microbials and preservatives in food, cosmetics, pharmaceuticals, and personal care products. Studies suggest that the utilization of parabens has substantially increased over the past years, particularly during the global pandemic of coronavirus disease 2019 (COVID-19). Although parabens are generally recognized as safe by the U.S. FDA, some concerns have been raised regarding the potential health effects of parabens associated with immunotoxicity. Herein, we comprehensively investigated several key characteristics of immunotoxicants of five commonly used parabens (methyl-, ethyl-, propyl-, butyl-, and benzyl parabens) in human THP-1 derived macrophages, which are effector cells serving as a first line of host defense against pathogens and tumor immunosurveillance. The results indicate parabens, at concentrations found in humans and biota, significantly dampened macrophage chemotaxis and secretion of major pro-inflammatory cytokines (TNF-α and IL-6) and anti-inflammatory cytokine (IL-10), corroborating the mRNA expression profile. Furthermore, some parabens were found to markedly alter macrophage adhesion and cell surface expression of costimulatory molecules, CD80+ and CD86+, and significantly increase macrophage phagocytosis. Collectively, these findings heighten awareness of potential immunotoxicity posed by paraben exposure at biologically relevant concentrations, providing implications for human health and ecological risks associated with immune dysfunctions.

Growth behavior and mRNA expression profiling during growth of IPEC-J2 cells

ObjectiveThe IPEC-J2 cell line is used as an in vitro small intestine model for swine, but it is also used as a model for the human intestine, presenting a relatively unique setting. By combining electric cell-substrate impedance sensing, with next-generation-sequencing technology, we showed that mRNA gene expression profiles and related pathways can depend on the growth phase of IPEC-J2 cells. Our investigative approach welcomes scientists to reproduce or modify our protocols and endorses putting their gene expression data in the context of the respective growth phase of the cells.ResultsThree time points are presented: (TP1) 1 h after medium change (= 6 h after seeding of cells), (TP2) the time point of the first derivative maximum of the cell growth curve, and a third point at the beginning of the plateau phase (TP3). Significantly outstanding at TP1 compared to TP2 was upregulated PLEKHN1, further FOSB and DEGS2 were significantly downregulated at TP2 compared to TP3. Any provided data can be used to improve next-generation experiments with IPEC-J2 cells.