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ETHNOPHARMACOLOGICAL RELEVANCE: Ganoderma lucidum (G. lucidum) has been widely used as adjuvant of anti-tumor therapy for variety tumors. The bioactive ingredients of G. lucidum mainly include triterpenes, such as Ganoderic acid A, Ganoderic acid B, Ganoderenic acid A, Ganoderenic acid B, Ganoderenic acid D, and Ganoderic acid X. However, the effects and underlying mechanisms of G. lucidum are often challenging in hepatocellular carcinoma (HCC) treatment. AIM OF THE STUDY: To explore the potential role and mechanism of enhancer-associated lncRNAs (en-lncRNAs) in G. lucidum treated HCC through the in vivo and in vitro experiments. MATERIALS AND METHODS: Hepa1-6-bearing C57 BL/6 mice model were established to evaluate the therapeutic efficacy of G. lucidum treated HCC. Ki67 and TUNEL staining were used to detect the tumor cell proliferation and apoptosis in vivo. The Mouse lncRNA 4*180K array was implemented to identify the differentially expressed (DE) lncRNAs and mRNAs of G. lucidum treated tumor mice. The constructed lncRNA-mRNA co-expression network and bioinformatics analysis were used to selected core en-lncRNAs and its neighboring genes. The UPLC-MS method was used to identify the triterpenes of G. lucidum, and the in vitro experiments were used to verify which triterpene monomers regulated en-lncRNAs in tumor cells. Finally, a stable knockdown/overexpression cell lines were used to confirm the relationship between en-lncRNA and neighboring gene. RESULTS: Ki67 and TUNEL staining demonstrated G. lucidum significantly inhibited tumor growth, suppressed cell proliferation and induced apoptosis in vivo. Transcriptomic analysis revealed the existence of 126 DE lncRNAs high correlated with 454 co-expressed mRNAs in G. lucidum treated tumor mice. Based on lncRNA-mRNA network and qRT-PCR validation, 6 core lncRNAs were selected and considered high correlated with G. lucidum treatment. Bioinformatics analysis revealed FR036820 and FR121302 might act as enhancers, and qRT-PCR results suggested FR121302 might enhance Popdc2 mRNA level in HCC. Furthermore, 6 main triterpene monomers of G. lucidum were identified by UPLC-MS method, and in vitro experiments showed FR121302 and Popdc2 were significantly suppressed by Ganoderenic acid A and Ganoderenic acid B, respectively. The knock/overexpression results demonstrated that FR121302 activating and enhancing Popdc2 expression levels, and Ganoderenic acid A and Ganoderenic acid B dramatically suppressed FR121302 and decreased Popdc2 level in Hepa1-6 cells. CONCLUSIONS: Enhancer-associated lncRNA plays a crucial role as an enhancer during hepatocarcinogenesis, and triterpenes of G. lucidum significantly inhibited tumor cell proliferation and induced apoptosis by regulating en-lncRNAs. Our study demonstrated Ganoderenic acid A and Ganoderenic acid B suppressed en-lncRNA FR121302 may be one of the critical strategies of G. lucidum inhibit hepatocellular carcinoma growth.
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Apoptosis , Carcinoma Hepatocelular , Proliferación Celular , Neoplasias Hepáticas , Ratones Endogámicos C57BL , ARN Largo no Codificante , Reishi , Triterpenos , Animales , Triterpenos/farmacología , Triterpenos/aislamiento & purificación , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Carcinoma Hepatocelular/tratamiento farmacológico , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/genética , Reishi/química , Apoptosis/efectos de los fármacos , Proliferación Celular/efectos de los fármacos , Ratones , Línea Celular Tumoral , Masculino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Humanos , Antineoplásicos Fitogénicos/farmacología , Antineoplásicos Fitogénicos/aislamiento & purificaciónRESUMEN
Pork is an important high-value protein source that fulfills the nutritional requirements for normal growth development, repair, and metabolism. Tryptophan (Trp), a crucial amino acid for piglet growth performance and muscle development, has an essential yet unclear regulatory mechanism. To investigate the biological basis of Trp regulation of piglet muscle development and identify the related regulatory pathways, we studied 20 weaned piglets. The piglets were divided into control (CON, 0.14% Trp) and high Trp (HT, 0.35% Trp) groups. They were fed with different Trp concentrations for 28 days, after which we collected the longissimus dorsi (LD) muscle for histomorphometric analysis and RNA extraction. Our results showed that the HT diet significantly increased the average daily weight gain, myocyte number, and muscle fiber density in weaned piglets. We then analyzed the differentially expressed (DE) genes in the LD muscle through RNA sequencing (RNA-seq). We identified 253 lncRNAs and 1055 mRNAs mainly involved in myoblast proliferation and myofiber formation, particularly through the FoxO and AMPK signaling pathways and metabolism. Further analysis of the DE lncRNA targeting relationship and construction of a protein-protein interaction (PPI) network resulted in the discovery of a novel lncRNA, XLOC_021675 or FRPMD, and elucidated its role in regulating piglet muscle development. Finally, we confirmed the RNA-seq results by reverse transcription polymerase chain reaction (RT-PCR). This study provides valuable insights into the regulatory mechanism of lncRNA-mediated Trp regulation of muscle development in weaned piglets offering a theoretical basis for optimizing piglet dietary ratios and enhancing pork production.
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Prolonged alcohol consumption can disturb the expression of both coding and noncoding genes in the brain. These dysregulated genes may co-express in modules and interact within networks, consequently influencing the susceptibility to developing alcohol use disorder (AUD). In the present study, we performed an RNA-seq analysis of the expression of both long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in 192 postmortem tissue samples collected from eight brain regions (amygdala, caudate nucleus, cerebellum, hippocampus, nucleus accumbens, prefrontal cortex, putamen, and ventral tegmental area) of 12 AUD and 12 control subjects of European ancestry. Applying the limma-voom method, we detected a total of 57 lncRNAs and 51 mRNAs exhibiting significant differential expression (Padj < 0.05 and fold-change ≥2) across at least one of the eight brain regions investigated. Machine learning analysis further confirmed the potential of these top genes in predicting AUD. Through Weighted Gene Co-expression Network Analysis (WGCNA), we identified distinct lncRNA-mRNA co-expression modules associated with AUD in each of the eight brain regions. Additionally, lncRNA-mRNA co-expression networks were constructed for each brain region using Cytoscape to reveal gene regulatory interactions implicated in AUD. Hub genes within these networks were found to be enriched in several key KEGG pathways, including Axon Guidance, MAPK Signaling, p53 Signaling, Adherens Junction, and Neurodegeneration. Our results underscore the significance of networks involving AUD-associated lncRNAs and mRNAs in modulating neuroplasticity in response to alcohol exposure. Further elucidating these molecular mechanisms holds promise for the development of targeted therapeutic interventions for AUD.
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Mitochondrial permeability transition (MPT)-driven necrosis (MPTDN) was a regulated variant of cell death triggered by specific stimuli. It played a crucial role in the development of organisms and the pathogenesis of diseases, and may provide new strategies for treating various diseases. However, there was limited research on the mechanisms of MPTDN in cervical cancer (CESC) at present. In this study, Weighted Gene Co-expression Network Analysis (WGCNA) was performed on differentially expressed genes in CESC. The module MEyellow, which showed the highest correlation with the phenotype, was selected for in-depth analysis. It was found that the genes in the MEyellow module may be associated with the tumor immune microenvironment (TIME). Through COX univariate regression and LASSO regression analysis, 6 key genes were identified. These genes were further investigated from multiple perspectives, including their independent diagnostic value, prognostic value, specific regulatory mechanisms in the tumor immune microenvironment, drug sensitivity analysis, and somatic mutation analysis. This study provided a comprehensive exploration of the mechanisms of action of these 6 key genes in CESC patients. And qRT-PCR validation was also conducted. Through COX univariate regression and LASSO coefficient screening of the MEyellow module, 6 key genes were identified: CHRM3-AS2, AC096734.1, BISPR, LINC02446, LINC00944, and DGUOK-AS1. Evaluation of the independent diagnostic value of these 6 key genes revealed that they can serve as independent diagnostic biomarkers. Through correlation analysis among these 6 genes, a potential regulatory mechanism among them was identified. Therefore, a risk prognostic model was established based on the collective action of these 6 genes, and the model showed good performance in predicting the survival period of CESC patients. By studying the relationship between these 6 key genes and the tumor microenvironment of CESC patients from multiple angles, it was found that these 6 genes are key regulatory factors in the tumor immune microenvironment of CESC patients. Additionally, 16 drugs that are associated with these 6 key genes were identified, and 8 small molecule drugs were predicted based on the lncRNA-mRNA network. The 6 key genes can serve as independent biomarkers for diagnosis, and the Risk score of these genes when acting together can be used as an indicator for predicting the clinical survival period of CESC patients. Additionally, these 6 key genes were closely related to the tumor immune microenvironment of CESC patients and were the important regulatory factors in the tumor immune microenvironment of CESC patients.
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Regulación Neoplásica de la Expresión Génica , Necrosis , ARN Largo no Codificante , Microambiente Tumoral , Neoplasias del Cuello Uterino , Humanos , Microambiente Tumoral/inmunología , Microambiente Tumoral/genética , Neoplasias del Cuello Uterino/genética , Neoplasias del Cuello Uterino/patología , Neoplasias del Cuello Uterino/inmunología , Femenino , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Pronóstico , Mitocondrias/metabolismo , Mitocondrias/genética , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Redes Reguladoras de Genes , Perfilación de la Expresión GénicaRESUMEN
Hepatocellular carcinoma (HCC), a prevalent malignancy worldwide, poses significant challenges in terms of prognosis, necessitating innovative therapeutic approaches. Ferroptosis offers notable advantages over apoptosis, holding promise as a novel therapeutic approach for HCC complexities. Moreover, while the interaction between long non-coding RNAs (lncRNAs) and mRNAs is pivotal in various physiological and pathological processes, their involvement in ferroptosis remains relatively unexplored. In this study, we constructed a ferroptosis-related lncRNA-mRNA correlation network in HCC using Pearson correlation analysis. Notably, the SLC7A11-AS1/SLC7A11 pair, exhibiting high correlation, was identified. Bioinformatics analysis revealed a significant correlation between the expression levels of this pair and key clinical characteristics of HCC patients, including gender, pathology, Ishak scores and tumour size. And poor prognosis was associated with high expression of this pair. Functional experiments demonstrated that SLC7A11-AS1, by binding to the 3'UTR region of SLC7A11 mRNA, enhanced its stability, thereby promoting HCC cell growth and resistance to erastin- induced ferroptosis. Additionally, in vivo studies confirmed that SLC7A11-AS1 knockdown potentiated the inhibitory effects of erastin on tumour growth. Overall, our findings suggest that targeting the SLC7A11-AS1/SLC7A11 pair holds promise as a potential therapeutic strategy for HCC patients.
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Sistema de Transporte de Aminoácidos y+ , Carcinoma Hepatocelular , Ferroptosis , Regulación Neoplásica de la Expresión Génica , Neoplasias Hepáticas , ARN Largo no Codificante , Ferroptosis/genética , Humanos , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Carcinoma Hepatocelular/metabolismo , Carcinoma Hepatocelular/tratamiento farmacológico , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/metabolismo , Neoplasias Hepáticas/tratamiento farmacológico , Sistema de Transporte de Aminoácidos y+/genética , Sistema de Transporte de Aminoácidos y+/metabolismo , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Animales , Línea Celular Tumoral , Masculino , Femenino , Ratones , Pronóstico , Proliferación Celular/genética , Ratones Desnudos , Persona de Mediana Edad , ARN Mensajero/genética , ARN Mensajero/metabolismo , Piperazinas/farmacologíaRESUMEN
We investigated mRNA-lncRNA co-expression patterns in a cellular model system of non-small cell lung cancer (NSCLC) sensitive and resistant to the epithelial growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) erlotinib/gefitinib. The aim of this study was to unveil insights into the complex mechanisms of NSCLC targeted therapy resistance and epithelial-to-mesenchymal transition (EMT). Genome-wide RNA expression was quantified for weighted gene co-expression network analysis (WGCNA) to correlate the expression levels of mRNAs and lncRNAs. Functional enrichment analysis and identification of lncRNAs were conducted on modules associated with the EGFR-TKI response and/or intermediate EMT phenotypes. We constructed lncRNA-mRNA co-expression networks and identified key modules and their enriched biological functions. Processes enriched in the selected modules included RHO (A, B, C) GTPase and regulatory signaling pathways, apoptosis, inflammatory and interleukin signaling pathways, cell adhesion, cell migration, cell and extracellular matrix organization, metabolism, and lipid metabolism. Interestingly, several lncRNAs, already shown to be dysregulated in cancer, are connected to a small number of mRNAs, and several lncRNAs are interlinked with each other in the co-expression network.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , ARN Largo no Codificante , Humanos , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/genética , ARN Largo no Codificante/genética , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/genética , Receptores ErbB/genéticaRESUMEN
BACKGROUND: Diabetic cardiomyopathy (DCM) is becoming a very well-known clinical entity and leads to increased heart failure in diabetic patients. Long non-coding RNAs (LncRNAs) play an important role in the pathogenesis of DCM. In the present study, the expression profiles of lncRNAs and mRNAs were illuminated in myocardium from DCM mice, with purpose of exploring probable pathological processes of DCM involved by differentially expressed genes in order to provide a new direction for the future researches of DCM. RESULTS: The results showed that a total of 93 differentially expressed lncRNA transcripts and 881 mRNA transcripts were aberrantly expressed in db/db mice compared with the controls. The top 6 differentially expressed lncRNAs like up-regulated Hmga1b, Gm8909, Gm50252 and down-regulated Msantd4, 4933413J09Rik, Gm41414 have not yet been reported in DCM. The lncRNAs-mRNAs co-expression network analysis showed that LncRNA 2610507I01Rik, 2310015A16Rik, Gm10503, A930015D03Rik and Gm48483 were the most relevant to differentially expressed mRNAs. CONCLUSION: Our results showed that db/db DCM mice exist differentially expressed lncRNAs and mRNAs in hearts. These differentially expressed lncRNAs may be involved in the pathological process of cardiomyocyte apoptosis and fibrosis in DCM.
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Diabetes Mellitus , Cardiomiopatías Diabéticas , ARN Largo no Codificante , Humanos , Ratones , Animales , ARN Largo no Codificante/genética , Cardiomiopatías Diabéticas/genética , Cardiomiopatías Diabéticas/metabolismo , Cardiomiopatías Diabéticas/patología , Perfilación de la Expresión Génica/métodos , Miocardio/metabolismo , Biología Computacional , ARN Mensajero/genética , Redes Reguladoras de Genes , Diabetes Mellitus/metabolismo , Diabetes Mellitus/patologíaRESUMEN
BACKGROUND: Cell differentiation agent II (CDA-II) exhibits potent anti-proliferative and apoptosis-inducing properties against a variety of cancer cells. However, its mechanism of action in chronic myeloid leukemia (CML) remains unclear. METHODS: Cell counting Kit 8 (CCK-8) and flow cytometry were used to investigate the effects of CDA-II on the biological characteristics of K562 cells. Gene (mRNA and lncRNA) expression profiles were analyzed by bioinformatics to screen differentially expressed genes and to perform enrichment analysis. The Pearson correlation coefficients of lncRNAs and mRNAs were calculated using gene expression values, and a lncRNA/mRNA co-expression network was constructed. The MCODE and cytoHubba plugins were used to analyze the co-expression network. RESULTS: The Results, derived from CCK-8 and flow cytometry, indicated that CDA-II exerts dual effects on K562 cells: it inhibits their proliferation and induces apoptosis. From bioinformatics analysis, we identified 316 mRNAs and 32 lncRNAs. These mRNAs were predominantly related to the meiotic cell cycle, DNA methylation, transporter complex and peptidase regulator activity, complement and coagulation cascades, protein digestion and absorption, and cell adhesion molecule signaling pathways. The co-expression network comprised of 163 lncRNA/mRNA interaction pairs. Notably, our analysis results implicated clustered histone gene families and five lncRNAs in the biological effects of CDA-II on K562 cells. CONCLUSION: This study highlights the hub gene and lncRNA/mRNA co-expression network as crucial elements in the context of CDA-II treatment of CML. This insight not only enriches our understanding of CDA-II's mechanism of action but also might provide valuable clues for subsequent experimental studies of CDA-II, and potentially contribute to the discovery of new therapeutic targets for CML.
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Leucemia Mielógena Crónica BCR-ABL Positiva , Péptidos , Fenilacetatos , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Perfilación de la Expresión Génica , Leucemia Mielógena Crónica BCR-ABL Positiva/tratamiento farmacológico , Leucemia Mielógena Crónica BCR-ABL Positiva/genética , ARN Mensajero/metabolismo , Redes Reguladoras de GenesRESUMEN
BACKGROUND: Avian pathogenic E. coli (APEC) can cause localized or systemic infections, collectively known as avian colibacillosis, resulting in huge economic losses to poultry industry globally per year. In addition, increasing evidence indicates that long non-coding RNAs (lncRNAs) play a critical role in regulating host inflammation in response to bacterial infection. However, the role of lncRNAs in the host response to APEC infection remains unclear. RESULTS: Here, we found 816 differentially expressed (DE) lncRNAs and 1,798 DE mRNAs in APEC infected chicken macrophages by RNAseq. The identified DE lncRNA-mRNAs were involved in Toll like receptor signaling pathway, VEGF signaling pathway, fatty acid metabolism, phosphatidylinositol signaling system, and other types of O-glycan biosynthesis. Furthermore, we found the novel lncRNA TCONS_00007391 as an important immune regulator in APEC infection was able to regulate the inflammatory response by directly targeting CD86. CONCLUSION: These findings provided a better understanding of host response to APEC infection and also offered the potential drug targets for therapy development against APEC infection.
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Infecciones por Escherichia coli , Enfermedades de las Aves de Corral , ARN Largo no Codificante , Animales , Escherichia coli/genética , Pollos/genética , Pollos/microbiología , ARN Largo no Codificante/genética , ARN Mensajero/genética , Infecciones por Escherichia coli/microbiología , Infecciones por Escherichia coli/veterinaria , Macrófagos , Enfermedades de las Aves de Corral/genética , Enfermedades de las Aves de Corral/microbiologíaRESUMEN
BACKGROUND: To compare the expression levels of long non-coding RNA (lncRNA) and messenger RNA (mRNA) in pre-receptive endometrium between patients with Polycystic Ovary Syndrome (PCOS)and normal ovulation undergoing in vitro fertilization-embryo transfer (IVF-ET). METHODS: Endometrial tissues were collected with endometrial vacuum curette in pre-receptive phase (3 days after oocytes retrieval) from PCOS and control groups. LncRNAs and mRNAs of endometrium were identified via RNA sequencing and alignments. A subset of 9 differentially expressed lncRNAs and 11 mRNAs were validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)in 22 PCOS patients and 18 ovulation patients. The function of mRNAs with differential expression patterns were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: We found out 687 up-regulated and 680 down-regulated mRNAs, as well as 345 up-regulated and 63 down-regulated lncRNAs in the PCOS patients in contrast to normal ovulation patients. qRT-PCR was used to detect the expression of 11 mRNAs, and validated that the expression of these 6 mRNAs CXCR4, RABL6, OPN3, SYBU, IDH1, NOP10 were significantly elevated among PCOS patients, and the expression of ZEB1 was significantly decreased. qRT-PCR was performed to detect the expression of 9 lncRNAs, and validated that the expression of these 7 lncRNAs IDH1-AS1, PCAT14, FTX, DANCR, PRKCQ-AS1, SNHG8, TPT1-AS1 were significantly enhanced among PCOS patients. Bioinformatics analysis showed that differentially expressed genes (DEGs) involved KEGG pathway were tyrosine metabolism, PI3K-Akt pathway, metabolic pathway, Jak-STAT pathway, pyruvate metabolism, protein processing in endoplasmic reticulum, oxidative phosphorylation and proteasome. The up-regulation of GO classification was involved in ATP metabolic process, oxidative phosphorylation, RNA catabolic process, and down-regulation of GO classification was response to corticosteroid, steroid hormone, and T cell activation. CONCLUSION: Our results determined the characteristics and expression profile of endometrial lncRNAs and mRNAs in PCOS patients in pre-receptive phase, which is the day 3 after oocytes retrival. The possible pathways and related genes of endometrial receptivity disorders were found, and those lncRNAs may be developed as a predictive biomarker of endometrium in pre-receptive phase.
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Síndrome del Ovario Poliquístico , ARN Largo no Codificante , Humanos , Femenino , ARN Mensajero/metabolismo , ARN Largo no Codificante/metabolismo , Síndrome del Ovario Poliquístico/genética , Quinasas Janus/genética , Quinasas Janus/metabolismo , Fosfatidilinositol 3-Quinasas/genética , Transducción de Señal , Factores de Transcripción STAT/genética , Factores de Transcripción STAT/metabolismo , Perfilación de la Expresión Génica , Transferencia de Embrión , Endometrio/metabolismo , Fertilización In Vitro , Redes Reguladoras de Genes , Opsinas de Bastones/genética , Opsinas de Bastones/metabolismoRESUMEN
Background: Sepsis was a high mortality and great harm systemic inflammatory response syndrome caused by infection. lncRNAs were potential prognostic marker and therapeutic target. Therefore, we expect to screen and analyze lncRNAs with potential prognostic markers in sepsis. Methods: Transcriptome sequencing and limma was used to screen dysregulated RNAs. Key RNAs were screened by correlation analysis, lncRNA-mRNA co-expression and weighted gene co-expression network analysis. Immune infiltration, gene set enrichment analysis and gene set variation analysis were used to analyze the immune correlation. Kaplan-Meier curve, receiver operator characteristic curve, Cox regression analysis and nomogram were used to analyze the correlation between key RNAs and prognosis. Sepsis model was established by lipopolysaccharide-induced HUVECs injury, and then cell viability and migration ability were detected by cell counting kit-8 and wound healing assay. The levels of apoptosis-related proteins and inflammatory cytokines were detected by RT-qPCR and Western blot. Reactive Oxygen Species and superoxide dismutase were detected by commercial kit. Results: Fourteen key differentially expressed lncRNAs and 663 key differentially expressed genes were obtained. And these lncRNAs were closely related to immune cells, especially T cell activation, immune response and inflammation. Subsequently, Subsequently, lncRNA PRKCQ-AS1 was identified as the regulator for further investigation in sepsis. RT-qPCR results showed that PRKCQ-AS1 expression was up-regulated in clinical samples and sepsis model cells, which was an independent prognostic factor in sepsis patients. Immune correlation analysis showed that PRKCQ-AS1 was involved in the immune response and inflammatory process of sepsis. Cell function tests confirmed that PRKCQ-AS1 could inhibit sepsis model cells viability and promote cell apoptosis, inflammatory damage and oxidative stress. Conclusion: We constructed immune-related lncRNA-mRNA regulatory networks in the progression of sepsis and confirmed that PRKCQ-AS1 is an important prognostic factor affecting the progression of sepsis and is involved in immune response.
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Long non-coding RNAs play crucial role in the tumorigenesis of lung adenocarcinoma (LUAD). However, the function of a large number of lncRNAs in LUAD has not been investigated yet. Weighted gene correlation network analysis (WGCNA) was applied to construct the co-expression module in the TCGA-LUAD cohort. Protein-protein interaction (PPI) network was used to explore the relationship of genes in the key module. The function of the key module on the prognosis in LUAD was analyzed using GO and KEGG analysis. Finally, we constructed the mRNA-lncRNA co-expression network in the key module to identify the hub lncRNAs that play crucial role in the prognosis in LUAD. The most highly expressed 2500 mRNAs and 2500 lncRNAs in the TCGA-LUAD cohort were clustered into 21 modules. After analyzing the correlation between the module and prognostic clinical traits, the Tan module, consisting of 130 genes, was selected as the key module on the prognosis in LUAD. And then, we found that genes in the key module were majorly enriched in ten multiple signaling pathways. Subsequently, we constructed the mRNA-lncRNA co-expression network based on the genes in the key module. Finally, we identified three lncRNAs and nineteen mRNAs that could be the promising prognostic biomarkers for LUAD. We identified three lncRNAs (MIR99AHG, ADAMTS9-AS2, and AC037459.2) and nineteen mRNAs as potential prognostic biomarkers in LUAD, which provided new insight for prognosis monitoring and therapy development in LUAD.
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Adenocarcinoma , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Redes Reguladoras de Genes , Pronóstico , Regulación Neoplásica de la Expresión Génica , ARN Mensajero/genética , ARN Mensajero/metabolismo , Biomarcadores , Pulmón/metabolismo , Adenocarcinoma/genéticaRESUMEN
Long non-coding RNAs (lncRNAs) play a significant role in various biological processes. Hence, it is utmost important to elucidate their functions in order to understand the molecular mechanism of a complex biological system. This versatile RNA molecule has diverse modes of interaction, one of which constitutes lncRNA-mRNA interaction. Hence, identifying its target mRNA is essential to understand the function of an lncRNA explicitly. Existing lncRNA target prediction tools mainly adopt thermodynamics approach. Large execution time and inability to perform real-time prediction limit their usage. Further, lack of negative training dataset has been a hindrance in the path of developing machine learning (ML) based lncRNA target prediction tools. In this work, we have developed a ML-based lncRNA-mRNA target prediction model- 'LncRTPred'. Here we have addressed the existing problems by generating reliable negative dataset and creating robust ML models. We have identified the non-interacting lncRNA and mRNAs from the unlabelled dataset using BLAT. It is further filtered to get a reliable set of outliers. LncRTPred provides a cumulative_model_score as the final output against each query. In terms of prediction accuracy, LncRTPred outperforms other popular target prediction protocols like LncTar. Further, we have tested its performance against experimentally validated disease-specific lncRNA-mRNA interactions. Overall, performance of LncRTPred is heavily dependent on the size of the training dataset, which is highly reflected by the difference in its performance for human and mouse species. Its performance for human species shows better as compared to that for mouse when applied on an unknown data due to smaller size of the training dataset in case of mouse compared to that of human. Availability of increased number of lncRNA-mRNA interaction data for mouse will improve the performance of LncRTPred in future. Both webserver and standalone versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred/index.html. Github Link: https://github.com/zglabDIB/LncRTPred.
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ARN Largo no Codificante , Humanos , Animales , Ratones , ARN Largo no Codificante/genética , ARN Mensajero/genética , Biología Computacional/métodosRESUMEN
Post-injury adaptation (PIA) is a simple and convenient method to promote bone healing, but its mechanism is unclear. This study was to discuss the role of fracture site tissue exosomes lncRNAs-mRNAs networks on PIA promoting bone mesenchymal stem cells (BMSCs) proliferation and migration. Firstly, the effects of PIA accelerating BMSCs proliferation and migration were confirmed by rat fracture model and bone fracture environment in vitro. Besides, the fracture site tissue exosomes were isolated and authenticated. Then the tissue exosomes were the key factor in PIA promoting BMSCs proliferation and migration authenticated by in vitro and in vivo experiments. The high throughput sequencing and RT-PCR were used to analyze the tissue exosomes lncRNAs-mRNAs networks. It was found that PIA treatment upregulated 118 lncRNAs, 295 mRNAs, and downregulated 111 lncRNAs, 2706 mRNAs in tissue exosomes. A total 12,211 genes were the target genes. Akt1, Actb and Uba52 were the hub mRNAs in tissue exosomes. In additions, tissue-derived exosomes of PIA treated rats upregulated 49 genes, 3 lncRNAs and downregulated 28 genes, 1 lncRNA in BMSCs. Kif11 was the hub gene. Overall, PIA promoted BMSCs proliferation and migration in the early stage of fracture healing, which was closely related to the fracture site tissue exosomes. Akt1, Actb and Uba52 were the hub mRNAs in the exosomes. Besides, Kif11 might be the key gene in BMSC regulated by tissue-derived exosomes of PIA treated rats.
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Exosomas , Fracturas Óseas , Células Madre Mesenquimatosas , ARN Largo no Codificante , Ratas , Animales , ARN Largo no Codificante/genética , Osteogénesis/genética , ARN Mensajero/genética , Fracturas Óseas/genética , Células Madre Mesenquimatosas/fisiología , Proliferación CelularRESUMEN
Long noncoding RNAs (lncRNAs) play essential roles in numerous biological processes in plants, such as regulating the gene expression. However, only a few studies have looked into their potential functions in xylem development. High-throughput sequencing of P. euramericana 'Zhonglin46' developing and mature xylem was performed in this study. Through sequencing analysis, 14,028 putative lncRNA transcripts were identified, including 4525 differentially expressed lncRNAs (DELs). Additional research revealed that in mature xylem, a total of 2320 DELs were upregulated and 2205 were downregulated compared to developing xylem. Meanwhile, there were a total of 8122 differentially expressed mRNAs (DEMs) that were upregulated and 16,424 that were downregulated in mature xylem compared with developing xylem. The cis- and trans-target genes of DELs were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, which indicated that these DELs participate in controlling the phenylpropanoid and lignin biosynthesis pathway as well as the starch and sucrose metabolism pathway. Among the cis-regulated DELs, LNC_006291, LNC_006292, and LNC_006532 all participate in regulating multiple HCT gene family membranes. As targets, POPTR_001G045900v3 (CCR2) and POPTR_018G063500v3 (SUS) both have only one cis-regulatory lncRNA, referred to as LNC_000057 and LNC_006212, respectively. Moreover, LNC_004484 and two DELs named LNC_008014 and LNC_010781 were revealed to be important nodes in the co-expression network of trans-lncRNAs and mRNAs associated to the lignin biosynthesis pathway and cellulose and xylan biosynthetic pathways, respectively. Finally, quantitative real-time PCR (qRT-PCR) was used to confirme 34 pairs of lncRNA-mRNA. Taken together, these findings may help to clarify the regulatory role that lncRNAs play in xylem development and wood formation.
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Populus , ARN Largo no Codificante , ARN Mensajero/genética , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Populus/genética , Lignina , Xilema/genética , Xilema/metabolismo , Redes Reguladoras de Genes , Perfilación de la Expresión GénicaRESUMEN
Long non-coding RNAs (lncRNAs) are transcripts of more than 200 nucleotides (nt) in length, with minimal or no protein-coding capacity. Increasing evidence indicates that lncRNAs play important roles in the regulation of gene expression including in the biosynthesis of secondary metabolites. Salvia miltiorrhiza Bunge is an important medicinal plant in China. Diterpenoid tanshinones are one of the main active components of S. miltiorrhiza. To better understand the role of lncRNAs in regulating diterpenoid biosynthesis in S. miltiorrhiza, we integrated analysis of lncRNAs, mRNAs, and transcription factors (TFs) to identify network modules underlying diterpenoid biosynthesis based on transcriptomic data. In transcriptomic data, we obtained 6,651 candidate lncRNAs, 46 diterpenoid biosynthetic pathway genes, and 11 TFs involved in diterpenoid biosynthesis. Combining the co-expression and genomic location analysis, we obtained 23 candidate lncRNA-mRNA/TF pairs that were both co-expressed and co-located. To further observe the expression patterns of these 23 candidate gene pairs, we analyzed the time-series expression of S. miltiorrhiza induced by methyl jasmonate (MeJA). The results showed that 19 genes were differentially expressed at least a time-point, and four lncRNAs, two mRNAs, and two TFs formed three lncRNA-mRNA and/or TF network modules. This study revealed the relationship among lncRNAs, mRNAs, and TFs and provided new insight into the regulation of the biosynthetic pathway of S. miltiorrhiza diterpenoids.
Asunto(s)
Diterpenos , ARN Largo no Codificante , Salvia miltiorrhiza , ARN Largo no Codificante/genética , Salvia miltiorrhiza/genética , ARN Mensajero/genética , Factores de Transcripción/genética , Diterpenos/metabolismoRESUMEN
Protein-translated mRNA analysis has been extensively used to determine the function of various traits in animals. The non-coding RNA (ncRNA), which was known to be non-functional because it was not encoded as a protein, was re-examined as it was studied to actually function. One of the ncRNAs, long non-coding RNA (lncRNA), is known to have a function of regulating mRNA expression, and its importance is emerging. Therefore, lncRNAs are currently being used to understand the traits of various animals as well as human diseases. However, studies on lncRNA annotation and its functions are still lacking in most animals except humans and mice. lncRNAs have unique characteristics of lncRNAs and interact with mRNA through various mechanisms. In order to make lncRNA annotations in animals in the future, it is essential to understand the characteristics of lncRNAs and the mechanisms by which lncRNAs function. In addition, this will allow lncRNAs to be used for a wider variety of traits in a wider range of animals, and it is expected that integrated analysis using other biological information will be possible.
RESUMEN
A high oleic acid content is considered an essential characteristic in the breeding of high-quality rapeseed in China. Long-chain non-coding RNA (lncRNA) molecules play an important role in the plant's growth and its response to stress. To better understand the role of lncRNAs in regulating plant reproductive development, we analyzed whole-transcriptome and physiological data to characterize the dynamic changes in lncRNA expression during the four representative times of seed development of high- and low-oleic-acid rapeseed in three regions. We identified 21 and 14 lncRNA and mRNA modules, respectively. These modules were divided into three types related to region, development stages, and material. Next, we analyzed the key modules related to the oil content and the oleic acid, linoleic acid, and linolenic acid contents with physiological data and constructed the key functional network analysis on this basis. Genes related to lipid metabolism, such as 3-ketoacyl-CoA synthase 16 (KCS16) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), were present in the co-expression network, suggesting that the effect of these genes on lipid metabolism might be embodied by the expression of these lncRNAs. Our results provide a fresh insight into region-, development-stage-, and material-biased changes in lncRNA expression in the seeds of Brassica napus. Some of these lncRNAs may participate in the regulatory network of lipid accumulation and metabolism, together with regulated genes. These results may help elucidate the regulatory system of lncRNAs in the lipid metabolism of high-oleic-acid rapeseed seeds.
Asunto(s)
Brassica napus , Brassica rapa , ARN Largo no Codificante , Brassica napus/genética , Brassica napus/metabolismo , Ácido Oléico/metabolismo , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Aceites de Plantas/metabolismo , Metabolismo de los Lípidos/genética , Fitomejoramiento , Brassica rapa/genética , Brassica rapa/metabolismo , Semillas/metabolismoRESUMEN
Long noncoding RNAs (lncRNAs) participate in a wide range of biological processes, but lncRNAs in plants remain largely unknown; in particular, we lack a systematic identification of plant lncRNAs involved in hormone responses. To explore the molecular mechanism of the response of poplar to salicylic acid (SA), the changes in protective enzymes, which are closely related to plant resistance induced by exogenous SA, were studied, and the expression of mRNA and lncRNA were determined by high-throughput RNA sequencing. The results showed that the activities of phenylalanine ammonia lyase (PAL) and polyphenol oxidase (PPO), in the leaves of Populus × euramericana, were significantly increased by exogenous SA application. High-throughput RNA sequencing showed that 26,366 genes and 5690 lncRNAs were detected under the different treatment conditions: SA and H2O application. Among these, 606 genes and 49 lncRNAs were differentially expressed. According to target prediction, lncRNAs and target genes involved in light response, stress response, plant disease resistance, and growth and development, were differentially expressed in SA-treated leaves. Interaction analysis showed that lncRNA-mRNA interactions, following exogenous SA, were involved in the response of poplar leaves to the external environment. Our study provides a comprehensive view of Populus × euramericana lncRNAs and offers insights into the potential functions and regulatory interactions of SA-responsive lncRNAs, thus forming the foundation for future functional analysis of SA-responsive lncRNAs in Populus × euramericana.
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Long non-coding RNAs (lncRNAs) are crucial players regulating many biological processes in plants. However, limited knowledge is available regarding their roles in kiwifruit ripening and softening. In this study, using lncRNA-seq technology, 591 differentially expressed (DE) lncRNAs (DELs) and 3107 DE genes (DEGs) were identified from kiwifruit stored at 4 °C for 1, 2, and 3 weeks in comparison with non-treated control fruits. Of note, 645 DEGs were predicted to be targets of DELs (DEGTLs), including some DE protein-coding genes (such as ß-amylase and pectinesterase). DEGTL-based GO enrichment analysis revealed that these genes were significantly enriched in cell wall modification and pectinesterase activity in 1 W vs. CK and 3 W vs. CK, which might be closely related to the fruit softening during low-temperature storage. Moreover, KEGG enrichment analysis revealed that DEGTLs were significantly associated with starch and sucrose metabolism. Our study revealed that lncRNAs play critical regulatory roles in kiwifruit ripening and softening under low-temperature storage, mainly by mediating the expression of starch and sucrose metabolism and cell wall modification related genes.