lncRNA Expression Profiles Research Articles

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.

Integrative transcriptomic profiling of ncRNAs and mRNAs in developing mouse lens.

In recent years, burgeoning research has underscored the pivotal role of non-coding RNA in orchestrating the growth, development, and pathogenesis of various diseases across organisms. However, despite these advances, our understanding of the specific contributions of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) to lens development remains notably limited. Clarifying the intricate gene regulatory networks is imperative for unraveling the molecular underpinnings of lens-related disorders. In this study, we aimed to address this gap by conducting a comprehensive analysis of the expression profiles of messenger RNAs (mRNAs), lncRNAs, and circRNAs at critical developmental time points of the mouse lens, encompassing both embryonic (E10.5, E12.5, and E16.5) and postnatal stages (P0.5, P10.5, and P60). Leveraging RNA-sequencing technology, we identified key transcripts pivotal to lens development. Our analysis revealed differentially expressed (DE) mRNAs, lncRNAs, and circRNAs across various developmental stages. Particularly noteworthy, there were 1831 co-differentially expressed (CO-DE) mRNAs, 150 CO-DE lncRNAs, and 13 CO-DE circRNAs identified during embryonic stages. Gene Ontology (GO) enrichment analysis unveiled associations primarily related to lens development, DNA conformational changes, and angiogenesis among DE mRNAs and lncRNAs. Furthermore, employing protein-protein interaction networks, mRNA-lncRNA co-expression networks, and circRNA-microRNA-mRNA networks, we predicted candidate key molecules implicated in lens development. Our findings underscore the pivotal roles of lncRNAs and circRNAs in this process, offering fresh insights into the pathogenesis of lens-related disorders and paving the way for future exploration in this field.

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.

LncRNA EIF3J-DT promotes chemoresistance in oral squamous cell carcinoma.

This study aimed to screen oral squamous cell carcinoma (OSCC) diagnostic and prognostic candidates and investigate the potential functions and mechanisms of candidates in the chemoresistance of OSCC cell lines. Differential expression profiling of lncRNA was performed in a large cohort of OSCC patients from the Cancer Genome Atlas database to identify OSCC diagnostic and prognostic candidates. Taxol resistance in OSCC cell lines was analyzed using MTT assay. OSCC cell lines transfected with EIF3J-DT pcDNA or siRNA were used to determine its regulatory effects on apoptosis, cell cycle distribution and autophagy using flow cytometry and western blot. We identified EIF3J-DT as a candidate for OSCC diagnosis and prognosis. The expression level of EIF3J-DT in OSCC cell lines correlates with taxol resistance. EIF3J-DT silencing attenuated taxol resistance, and EIF3J-DT overexpression enhanced taxol resistance in OSCC cell lines. Silencing of EIF3J-DT reduced taxol resistance by inducing apoptosis, cell cycle arrest, and ATG14-mediated autophagy inhibition in OSCC cell lines. We found that EIF3J-DT induced chemoresistance by regulating apoptosis, cell cycle, and autophagy in OSCC cell lines, which EIF3J-DT might provide a novel therapeutic approach for OSCC as well as a diagnostic and prognostic factor.

Systematic analysis of co-expression network and gene expression profile of differentially expressed lncRNA-mRNA one week after spinal cord injury

Spinal cord injury (SCI) is a severe event that occurs in the central nervous system (CNS). Long noncoding RNAs (lncRNAs) have already been proven to play key roles in different diseases of the CNS. Nevertheless, the roles of messenger RNAs (mRNAs) and lncRNAs one week after SCI remain to be elucidated. We established a rat model of SCI and examined the differential levels of mRNAs and lncRNAs, and then, the differentially expressed mRNAs (DE mRNAs) and lncRNAs (DE lncRNAs) were investigated. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DE lncRNAs and mRNAs were subsequently carried out to explore crucial biological processes and signaling pathways. Moreover, we constructed protein–protein interaction (PPI) networks, the STRING database, and identified the 10 high degree core nodes. We also established a co-expression network by calculating the correlation between lncRNA expression profile and mRNA expression profile. The identified DE lncRNAs and DE mRNAs may potentially be critical targets for the diagnosis and treatment of SCI in the future. Abbreviations: SCI: spinal cord injury; CNS: central nervous system; YLDs: years of life lived with disability; lncRNAs: long noncoding RNAs; mRNAs: messenger RNAs; DE: differentially expressed; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GSEA: gene set enrichment analysis; RIN: Renewable Identification Number; PCA: principal component analysis; PPI: protein–protein interaction; MF, molecular function; BP: biological process; CC: cellular component; MCODE: molecular complex detection

Curcumin alleviates Aflatoxin B1-triggered chicken liver necroptosis by targeting the LOC769044/miR-1679/STAT1 axis

Aflatoxin B1 (AFB1) is an unavoidable environmental toxin. The accumulation of AFB1 and its metabolites in the liver poses a threat to both human and animal health. Curcumin exhibits anti-oxidative, anti-tumor, and anti-inflammatory properties. There is no report on the mechanism regarding how curcumin relived liver necroptosis in chickens induced by AFB1 based on the regulatory network of ceRNA. To explore this, we performed transmission electron microscopy and sequenced lncRNA and mRNA in chicken livers treated with AFB1 and/or curcumin for 28 d in vivo. We observed substantial alterations in the lncRNA and mRNA expression profiles within the chicken liver, indicating that curcumin can mitigate AFB1-induced necroptosis both in vivo and in vitro. Further analysis, including the establishment of an lncRNA-miRNA-mRNA network and the utilization of a dual luciferase reporter assay, revealed that LOC769044 acts as a competing endogenous RNA (ceRNA) for miR-1679. In addition, STAT1 was identified as a direct target of miR-1679. Modulating miR-1679 levels through overexpression, and silencing LOC769044 and STAT1, effectively reversed the necroptotic effects induced by AFB1, a reversal that was also observed with curcumin supplementation. In conclusion, our data demonstrate that curcumin alleviates AFB1-induced liver necroptosis through the LOC769044/miR-1679/STAT1 signaling axis. This study suggests that LOC769044 may serve as a novel therapeutic target for managing AFB1-mediated liver toxicity.

Differential mRNA and lncRNA Expression Profiles Associated with Early Pregnancy Loss in ART Patients.

Early pregnancy loss (EPL) is the most common complication in assisted reproductive technology (ART). However, the precise causes for nearly 50% patients remain unexplained. In the current study, we aimed to discover the differentially expressed profiling of mRNAs and lncRNAs by RNA sequencing (RNA-seq). Human chorionic villi tissues were collected from patients with EPL and natural control (NC) group. RNA sequencing (RNA-seq) of these specimens was performed for transcriptome analysis. As a result, we identified a total of 141 mRNAs and 137 lncRNAs that were significantly differentially expressed between villi tissues from EPL and NC. Functional enrichment analyses indicated enrichment of differentially expressed genes involved in pathways were associated with growth hormone receptor binding, PI3K-Akt signaling pathway, Jak-STAT signaling pathway, transcriptional misregulation in cancer, metabolic pathways and Rap1 signaling pathway. Additionally, the co-expression networks (lncRNA-miRNA-mRNA) was constructed based on the correlation analysis between the differentially expressed RNAs.7 mRNAs and 6 lncRNAs were successfully technically validated with RT-PCR. In conclusion, our results suggest a direction for the further study of EPL-related mRNAs and lncRNAs and may ultimately assist in understanding the pathogenesis of EPL.

An exosomes-related lncRNA prognostic model correlates with the immune microenvironment and therapy response in lung adenocarcinoma

Recent research highlights the significance of exosomes and long noncoding RNAs (lncRNAs) in cancer progression and drug resistance, but their role in lung adenocarcinoma (LUAD) is not fully understood. We analyzed 121 exosome-related (ER) mRNAs from the ExoBCD database, along with mRNA and lncRNA expression profiles of TCGA-LUAD using “DESeq2”, “survival,” “ConsensusClusterPlus,” “GSVA,” “estimate,” “glmnet,” “clusterProfiler,” “rms,” and “pRRophetic” R packages. This comprehensive approach included univariate cox regression, unsupervised consensus clustering, GSEA, functional enrichment analysis, and prognostic model construction. Our study identified 134 differentially expressed ER-lncRNAs, with 19 linked to LUAD prognosis. These ER-lncRNAs delineated two patient subtypes, one with poorer outcomes. Additionally, 286 differentially expressed genes were related to these ER-lncRNAs, 261 of which also correlated with LUAD prognosis. We constructed an ER-lncRNA-related prognostic model and calculated an ER-lncRNA-related risk score (ERS), revealing that a higher ERS correlates with poor overall survival in both the Meta cohort and two validation cohorts. The ERS potentially serves as an independent prognostic factor, and the prognostic model demonstrates superior predictive power. Notably, significant differences in the immune landscape were observed between the high- and low-ERS groups. Drug sensitivity analysis indicated varying responses to common chemotherapy drugs based on ERS stratification, with the high-ERS group showing greater sensitivity, except to rapamycin and erlotinib. Experimental validation confirmed that thymidine kinase 1 enhances lung cancer invasion, metastasis, and cell cycle progression. Our study pioneers an ER-lncRNA-related prognostic model for LUAD, proposing that ERS-based risk stratification could inform personalized treatment strategies to improve patient outcomes.

Study of lncRNAs expression profile in the response to biological drugs in Psoriatic Arthritis: MEG3 could be a potential genomic biomarker of therapy efficacy

We aimed to identify an expression profile of lncRNAs potentially related to treatment response in Psoriatic arthritis (PsA) patients, to be used as potential genomic biomarkers predictors of drug treatment effectiveness. In addition, we evaluated a possible association between lncRNAs genetic variants and the response to therapy using the clinical parameter of Disease Activity Index. For the expression study, we collected 48 treated PsA patients, monitoring the treatment response for 12 months. We initially used PCR Array and, then, we validated the results with qRT-PCR. We also retrospectively genotyped 163 treated PsA patients. Firstly, we observed a significant difference in the expression level between Responder and non-Responder patients, of 4 lncRNAs in the group of PsA patients treated with TNFi and of 3 lncRNAs in the group of patients treated with IL17i. Then, we confirmed a significant decrease of MEG3 expression in non-Responder patients compared to Responders, also considering separately the single groups of patients treated with TNFi and IL17i. In addition, our results seem to highlight a potential dose-dependent effect of rs941576 (MEG3) variant allele on Disease Activity Index. Our study suggests a possible role of the lncRNA MEG3 in the treatment response to biological drugs.

Transcriptomic Profiles of Long Noncoding RNAs and Their Target Protein-Coding Genes Reveals Speciation Adaptation on the Qinghai-Xizang (Tibet) Plateau in Orinus.

Long noncoding RNAs (lncRNAs) are RNA molecules longer than 200 nt, which lack the ability to encode proteins and are involved in multifarious growth, development, and regulatory processes in plants and mammals. However, the environmental-regulated expression profiles of lncRNAs in Orinus that may associated with their adaptation on the Qinghai-Xizang (Tibet) Plateau (QTP) have never been characterized. Here, we utilized transcriptomic sequencing data of two Orinus species (O. thoroldii and O. kokonoricus) to identify 1624 lncRNAs, including 1119 intergenic lncRNAs, 200 antisense lncRNAs, five intronic lncRNAs, and 300 sense lncRNAs. In addition, the evolutionary relationships of Orinus lncRNAs showed limited sequence conservation among 39 species, which implied that Orinus-specific lncRNAs contribute to speciation adaptation evolution. Furthermore, considering the cis-regulation mechanism, from 286 differentially expressed lncRNAs (DElncRNAs) and their nearby protein coding genes (PCGs) between O. thoroldii and O. kokonoricus, 128 lncRNA-PCG pairs were obtained in O. thoroldii, whereas 92 lncRNA-PCG pairs were obtained in O. kokonoricus. In addition, a total of 19 lncRNA-PCG pairs in O. thoroldii and 14 lncRNA-PCG pairs in O. kokonoricus were found to participate in different biological processes, indicating that the different expression profiles of DElncRNAs between O. thoroldii and O. kokonoricus were associated with their adaptation at different elevations on the QTP. We also found several pairs of DElncRNA nearby transcription factors (TFs), indicating that these DElncRNAs regulate the expression of TFs to aid O. thoroldii in adapting to the environment. Therefore, this work systematically identified a series of lncRNAs in Orinus, laying the groundwork for further exploration into the biological function of Orinus in environmental adaptation.

Differences in the expression of long noncoding RNAs in peripheral blood mononuclear cells indicate potential biomarkers for rheumatoid arthritis

ObjectiveLong noncoding RNAs (lncRNAs) play an increasingly important role in various autoimmune diseases. We aimed to characterize the expression profiles of lncRNAs in peripheral blood mononuclear cells (PBMCs) from RA patients and to assess the potential of these lncRNAs as RA biomarkers. MethodsWhole-transcriptome sequencing was used to establish a lncRNA expression profile. A total of 155 RA patients, 145 healthy controls, 59 systemic lupus erythematosus (SLE) patients and 59 primary Sjögren’s syndrome (pSS) patients were recruited for this study. Four candidate lncRNAs (linc00152, lnc-ADM-1, ITSN1-2, and lnc-FTH1-7) were validated via qRT-PCR in independent samples, and their expression, association with RA clinical features and value as RA biomarkers were evaluated. ResultsLinc00152 and lnc-ADM-1 exhibited upregulated expression (p = 0.001, p = 0.014, respectively), while ITSN1-2 and lnc-FTH1-7 exhibited downregulated expression (both p < 0.001, respectively) in RA patients compared to controls. Lnc-ADM-1 and lnc-FTH1-7 expression correlated positively with the C4 level (p = 0.016 and p = 0.012, respectively). ITSN1-2 levels were negatively associated with CRP levels (p = 0.024). Linc00152, lnc-ADM-1, ITSN1-2, and lnc-FTH1-7 showed potential as RA biomarkers, with the four-lncRNA panel distinguishing RA patients from controls, SLE patients, or pSS patients (AUC = 0.886, 0.746, and 0.749, respectively). ConclusionThe altered expression of linc00152, lnc-ADM-1, ITSN1-2 and lnc-FTH1-7 in RA patients suggested that these genes may serve as potential biomarkers for RA and could be involved in its pathogenesis.

Identification and coregulation pattern analysis of long noncoding RNAs in the mouse brain after Angiostrongylus cantonensis infection

BackgroundAngiostrongyliasis is a highly dangerous infectious disease. Angiostrongylus cantonensis larvae migrate to the mouse brain and cause symptoms, such as brain swelling and bleeding. Noncoding RNAs (ncRNAs) are novel targets for the control of parasitic infections. However, the role of these molecules in A. cantonensis infection has not been fully clarified.MethodsIn total, 32 BALB/c mice were randomly divided into four groups, and the infection groups were inoculated with 40 A. cantonensis larvae by gavage. Hematoxylin and eosin (H&E) staining and RNA library construction were performed on brain tissues from infected mice. Differential expression of long noncoding RNAs (lncRNAs) and mRNAs in brain tissues was identified by high-throughput sequencing. The pathways and functions of the differentially expressed lncRNAs were determined by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The functions of the differentially expressed lncRNAs were further characterized by lncRNA‒microRNA (miRNA) target interactions. The potential host lncRNAs involved in larval infection of the brain were validated by quantitative real-time polymerase chain reaction (qRT‒PCR).ResultsThe pathological results showed that the degree of brain tissue damage increased with the duration of infection. The transcriptome results showed that 859 lncRNAs and 1895 mRNAs were differentially expressed compared with those in the control group, and several lncRNAs were highly expressed in the middle–late stages of mouse infection. GO and KEGG pathway analyses revealed that the differentially expressed target genes were enriched mainly in immune system processes and inflammatory response, among others, and several potential regulatory networks were constructed.ConclusionsThis study revealed the expression profiles of lncRNAs in the brains of mice after infection with A. cantonensis. The lncRNAs H19, F630028O10Rik, Lockd, AI662270, AU020206, and Mexis were shown to play important roles in the infection of mice with A. cantonensis infection.Graphical

LINC02257 regulates colorectal cancer liver metastases through JNK pathway

BackgroundLong noncoding RNAs (lncRNAs) have emerged as critical regulators of colorectal cancer (CRC) progression, but their roles and underlying mechanisms in colorectal cancer liver metastases (CRLMs) remain poorly understood. MethodsTo explore the expression patterns and functions of lncRNAs in CRLMs, we analyzed the expression profiles of lncRNAs in CRC tissues using the TCGA database and examined the expression patterns of lncRNAs in matched normal, CRC, and CRLM tissues using clinical samples. We further investigated the biological roles of LINC02257 in CRLM using in vitro and in vivo assays, and verified its therapeutic potential in a mouse model of CRLM. ResultsOur findings showed that LINC02257 was highly expressed in metastatic CRC tissues and its expression was negatively associated with overall survival. Functionally, LINC02257 promoted CRC cell growth, migration, metastasis, and inhibited cell apoptosis in vitro, and enhanced liver metastasis in vivo. Mechanistically, LINC02257 up-regulated phosphorylated c-Jun N-terminal kinase (JNK) to promote CRLM. ConclusionsOur study revealed that LINC02257 played a key role in the proliferation and metastasis of CRC cells through the LINC02257/JNK axis. Targeting this axis may represent a promising therapeutic strategy for the treatment of liver metastases in patients with CRC.

Whole-Transcriptome Sequencing of Knee Joint Cartilage from Kashin-Beck Disease and Osteoarthritis Patients.

The aim of this study was to provide a comprehensive understanding of similarities and differences in mRNAs, lncRNAs, and circRNAs within cartilage for Kashin-Beck disease (KBD) compared to osteoarthritis (OA). We conducted a comparison of the expression profiles of mRNAs, lncRNAs, and circRNAs via whole-transcriptome sequencing in eight KBD and ten OA individuals. To facilitate functional annotation-enriched analysis for differentially expressed (DE) genes, DE lncRNAs, and DE circRNAs, we employed bioinformatic analysis utilizing Gene Ontology (GO) and KEGG. Additionally, using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), we validated the expression levels of four cartilage-related genes in chondrocytes. We identified a total of 43 DE mRNAs, 1451 DE lncRNAs, and 305 DE circRNAs in KBD cartilage tissue compared to OA (q value < 0.05; |log2FC| > 1). We also performed competing endogenous RNA network analysis, which identified a total of 65 lncRNA-mRNA interactions and 4714 miRNA-circRNA interactions. In particular, we observed that circRNA12218 had binding sites for three miRNAs targeting ACAN, while circRNA12487 had binding sites for seven miRNAs targeting COL2A1. Our results add a novel set of genes and non-coding RNAs that could potentially serve as candidate diagnostic biomarkers or therapeutic targets for KBD patients.

Identification and bioinformatics analysis of lncRNAs in serum of patients with ankylosing spondylitis

ObjectivesThe aim of this study was to explore the long non-coding RNA (lncRNA) expression profiles in serum of patients with ankylosing spondylitis (AS). The role of these lncRNAs in this complex autoimmune situation needs to be evaluated.MethodsWe used high-throughput whole-transcriptome sequencing to generate sequencing data from three patients with AS and three normal controls (NC). Then, we performed bioinformatics analyses to identify the functional and biological processes associated with differentially expressed lncRNAs (DElncRNAs). We confirmed the validity of our RNA-seq data by assessing the expression of eight lncRNAs via quantitative reverse transcription polymerase chain reaction (qRT-PCR) in 20 AS and 20 NC samples. We measured the correlation between the expression levels of lncRNAs and patient clinical index values using the Spearman correlation test.ResultsWe identified 72 significantly upregulated and 73 significantly downregulated lncRNAs in AS patients compared to NC. qRT-PCR was performed to validate the expression of selected DElncRNAs; the results demonstrated that the expression levels of MALAT1:24, NBR2:9, lnc-DLK1-35:13, lnc-LARP1-1:1, lnc-AIPL1-1:7, and lnc-SLC12A7-1:16 were consistent with the sequencing analysis results. Enrichment analysis showed that DElncRNAs mainly participated in the immune and inflammatory responses pathways, such as regulation of protein ubiquitination, major histocompatibility complex class I-mediated antigen processing and presentation, MAPkinase activation, and interleukin-17 signaling pathways. In addition, a competing endogenous RNA network was constructed to determine the interaction among the lncRNAs, microRNAs, and mRNAs based on the confirmed lncRNAs (MALAT1:24 and NBR2:9). We further found the expression of MALAT1:24 and NBR2:9 to be positively correlated with disease severity.ConclusionTaken together, our study presents a comprehensive overview of lncRNAs in the serum of AS patients, thereby contributing novel perspectives on the underlying pathogenic mechanisms of this condition. In addition, our study predicted MALAT1 has the potential to be deeply involved in the pathogenesis of AS.

Whole transcriptome sequencing reveals key genes and ceRNA regulatory networks associated with pimpled eggs in hens

Eggshell is one of the most important indicators of egg quality, and due to low shell strength, pimple eggs (PE) are more susceptible to breakage, thus causing huge economic losses to the egg industry. At the current time, the molecular mechanisms that regulate the formation of pimple eggs are poorly understood. In this study, uterine tissues of PE-laying hens (n = 8) and normal egg (NE) -laying hens (n = 8) were analyzed by whole transcriptome sequencing, and a total of 619 differentially expressed mRNAs (DE mRNAs), 122 differentially expressed lncRNAs (DE lncRNAs) and 21 differentially expressed miRNAs (DE miRNAs) were obtained. Based on the targeting relationship among DE mRNAs, DE lncRNAs and DE miRNAs, we constructed a competitive endogenous RNA (ceRNA) network including 12 DEmiRNAs, 19 DElncRNAs and 128 DEmRNAs. Considering the large amount of information contained in the network, we constructed a smaller ceRNA network to better understand the complex mechanisms of pimple egg formation. The smaller ceRNA network network contains 7 DE lncRNAs (LOC107056551, LOC121109367, LOC121108909, LOC121108862, LOC112530033, LOC121113165, LOC107054145), 5 DE miRNAs (gga-miR-6568-3p, gga-miR-31-5p, gga-miR-18b-3p, gga-miR-1759-3p, gga-miR-12240-3p) and 7 DE mRNAs (CABP1, DNAJC5, HCN3, HPCA, IBSP, KCNT1, OTOP3), and these differentially expressed genes may play key regulatory roles in the formation of pimpled eggs in hens. This study provides the overall expression profiles of mRNAs, lncRNAs and miRNAs in the uterine tissues of hens, which provides a theoretical basis for further research on the molecular mechanisms of pimpled egg formation, and has potential applications in improving eggshell quality.

Profiling of long non-coding RNAs in hippocampal–entorhinal system subfields: impact of RN7SL1 on neuroimmune response modulation in Alzheimer’s disease

Alzheimer’s disease (AD) is recognized as the predominant cause of dementia, and neuroimmune processes play a pivotal role in its pathological progression. The involvement of long non-coding RNAs (lncRNAs) in AD has attracted widespread attention. Herein, transcriptomic analysis of 262 unique samples extracted from five hippocampal–entorhinal system subfields of individuals with AD pathology and without AD pathology revealed distinctive lncRNA expression profiles. Through differential expression and coexpression analyses, we identified 16 pivotal lncRNAs. Notably, RN7SL1 knockdown significantly modulated microglial responses upon oligomeric amyloid-β stimulation, resulting in a considerable decrease in proinflammatory cytokine production and subsequent neuronal damage. These findings highlight RN7SL1 as an essential neuroimmune-related lncRNA that could serve as a prospective target for AD diagnosis and treatment.

Correlation of Differentially Expressed lncRNAs with Intestinal Flora Imbalance, Small Intestinal Permeability, and Glucose Uptake in T2DM Mice.

Diabetes is a major global health concern. This study aimed to investigate the correlation between differentially expressed lncRNAs in mice with type 2 diabetes mellitus (T2DM) and alterations in the intestinal flora and intestinal pathology. A T2DM mouse model was constructed by feeding mice a high-fat diet. Serum fat metabolism-related indices and insulin levels were biochemically detected. Serum inflammatory factors (IL-1β, IL-6, TNF-α, IL-10) and endotoxin (LPS) were measured by ELISA. Histopathological changes in the small intestines of mice were observed by HE. The short-chain fatty acid (SCFA) content was analyzed using GC-MS. Analysis of altered intestinal flora in T2DM mice was performed using a 16sRNA sequencing assay. Differences in lncRNA expression profiles in small intestinal tissues were analyzed using RNA-seq assays. Spearman's correlation analysis was used to correlate the expression of candidate lncRNAs with changes in differential gut flora. Spearman's correlation analysis was used to analyze the correlation between the expression of candidate differentially expressed lncRNAs, small intestinal permeability, and glucose absorption. We found that serum levels of LPS, BUN, Scr, TC, TG, LDL-C, IL-1β, IL-6, and TNF-α were elevated and levels of HDL-C, insulin, and IL-10 were decreased in T2DM mice. The ileal enterochromes of T2DM mice were disorganized and broken, the number of enterochromes was reduced, the local epithelial cells were necrotic, and the plasma membrane layer was locally absent. In addition, the protein expression of ZO-1 and occludin was decreased, and the protein expression of SGLT-1 and GLUT-2 was elevated in the model group compared to the control group.The levels of Acetic acid, Propionic acid and Butyric acid were decreased and the levels of Isobutyric acid andIsovaleric acid were increased, the abundance of beneficial bacteria was decreased and the abundance of harmfulbacteria was increased in the feces of T2DM mice. RNA-seq identified nine differentially expressed lncRNAs (LINC00675, Gm33838, Gm11655, LOC6613926, LOC6613788, LOC6613791, LOC6613795, Arhgap27os3, and A330023F24Rik). In addition, we found significant correlations between differentially expressed lncRNAs and a variety of intestinal flora, as well as between small intestinal permeability and glucose absorption. A significant correlation was observed between differentially expressed lncRNAs in the intestinal tissues of T2DM mice and intestinal flora imbalance, small intestinal permeability, and glucose absorption.