Integrated miRNA and mRNA Expression Profiles Reveal Differentially Expressed miR-222a as an Antiviral Factor Against Duck Hepatitis A Virus Type 1 Infection.
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ABSTRACT:
SUBMITTER: Sui N
PROVIDER: S-EPMC8761743 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAlthough dilated cardiomyopathy (DCM) is a prevalent form of cardiomyopathy, the molecular mechanisms underlying its pathogenesis and progression remain poorly understood. It is possible to identify and validate DCM-associated genes, pathways, and miRNAs using bioinformatics analysis coupled with clinical validation methods.MethodsOur analysis was performed using 3 mRNA datasets and 1 miRNA database. We employed several approaches, including gene ontology (GO) analysis, KEGG pathway enrichment analysis, protein-protein interaction networks analysis, and analysis of hub genes to identify critical genes and pathways linked to DCM. We constructed a regulatory network for DCM that involves interactions between miRNAs and mRNAs. We also validated the differently expressed miRNAs in clinical samples (87 DCM ，83 Normal) using qRT-PCR.The miRNAs' clinical value was evaluated by receiver operating characteristic curves (ROCs).Results78 differentially expressed genes (DEGs) and 170 differentially expressed miRNAs (DEMs) were associated with DCM. The top five GO annotations were collagen-containing extracellular matrix, cell substrate adhesion, negative regulation of cell differentiation, and inflammatory response. The most enriched KEGG pathways were the Neurotrophin signaling pathway, Thyroid hormone signaling pathway, Wnt signaling pathway, and Axon guidance. In the PPI network, we identified 10 hub genes, and in the miRNA-mRNA regulatory network, we identified 8 hub genes and 15 miRNAs. In the clinical validation, we found 13 miRNAs with an AUC value greater than 0.9.ConclusionOur research offers novel insights into the underlying mechanisms of DCM and has implications for identifying potential targets for diagnosis and treatment of this condition.
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Project description:Several studies have investigated miRNA and mRNA co-expression to identify regulatory networks at the transcriptional level. A typical finding of these studies is the presence of both negative and positive miRNA-mRNA correlations. Negative correlations are consistent with the expected, faster degradation of target mRNAs, whereas positive correlations denote the existence of feed-forward regulations mediated by transcription factors. Both mechanisms have been characterized at the molecular level, although comprehensive methods to represent miRNA-mRNA correlations are lacking. At present, genome-wide studies are able to assess the expression of more than 1000 mature miRNAs and more than 35,000 well-characterized human genes. Even if studies are generally restricted to a small subset of genes differentially expressed in specific diseases or experimental conditions, the number of potential correlations remains very high, and needs robust multivariate methods to be conveniently summarized by a small set of data.Nonparametric Kendall correlations were calculated between miRNAs and mRNAs differentially expressed in livers of patients with acute liver failure (ALF) using normal livers as controls. Spurious correlations due to the histopathological composition of samples were removed by partial correlations. Correlations were then transformed into distances and processed by multidimensional scaling (MDS) to map the miRNA and mRNA relationships. These showed: (a) a prominent displacement of miRNA and mRNA clusters in ALF livers, as compared to control livers, indicative of gene expression dysregulation; (b) a clustering of mRNAs consistent with their functional annotations [CYP450, transcription factors, complement, proliferation, HLA class II, monocytes/macrophages, T cells, T-NK cells and B cells], as well as a clustering of miRNAs with the same seed sequence; and (c) a tendency of miRNAs and mRNAs to populate distinct regions of the MDS plot. MDS also allowed to visualize the network of miRNA-mRNA target pairs.Different features of miRNA and mRNA relationships can be represented as thematic maps within the framework of MDS obtained from pairwise correlations. The symmetric distribution of positive and negative correlations between miRNA and mRNA expression suggests that miRNAs are involved in a complex bidirectional molecular network, including, but not limited to, the inhibitory regulation of miRNA targets.
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Project description:MicroRNAs (miRNAs) regulate post-transcription gene expression by targeting genes and play crucial roles in diverse biological processes involving body color formation. However, miRNAs and miRNA-targets underlying shell color polymorphism remain largely unknown in mollusca. Using four shell colors full-sib families of the Pacific oyster Crassostrea gigas, we systematically identified miRNAs and miRNA-targets in the mantles, which organ could produce white, golden, black or partially pigmented shell. RNA sequencing and analysis identified a total of 53 known miRNA and 91 novel miRNAs, 47 of which were detected to differentially express among six pairwise groups. By integrating miRNA and mRNA expression profiles, a total of 870 genes were predicted as targets of differentially expressed miRNAs, mainly involving in biomineralization and pigmentation through functional enrichment. Furthermore, a total of four miRNAs and their target mRNAs were predicted to involve in synthesis of melanin, carotenoid or tetrapyrrole. Of them, lgi-miR-317 and its targets peroxidase and lncRNA TCONS_00951105 are implicated in acting as the competing endogenous RNA to regulate melanogenesis. Our studies revealed the systematic characterization of miRNAs profiles expressed in oyster mantle, which might facilitate understanding the intricate molecular regulation of shell color polymorphism and provide new insights into breeding research in oyster.
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Project description:Increasing amounts of evidence indicate that noncoding RNAs (ncRNAs) have important roles in various biological processes. Here, miRNA, lncRNA, and mRNA expression profiles were analyzed in human HepG2 and L02 cells using high-throughput technologies. An integrative method was developed to identify possible functional relationships between different RNA molecules. The dominant deregulated miRNAs were prone to be downregulated in tumor cells, and the most abnormal mRNAs and lncRNAs were always upregulated. However, the genome-wide analysis of differentially expressed RNA species did not show significant bias between up- and downregulated populations. miRNA-mRNA interaction was performed based on their regulatory relationships, and miRNA-lncRNA and mRNA-lncRNA interactions were thoroughly surveyed and identified based on their locational distributions and sequence correlations. Aberrantly expressed miRNAs were further analyzed based on their multiple isomiRs. IsomiR repertoires and expression patterns were varied across miRNA loci. Several specific miRNA loci showed differences between tumor and normal cells, especially with respect to abnormally expressed miRNA species. These findings suggest that isomiR repertoires and expression patterns might contribute to tumorigenesis through different biological roles. Systematic and integrative analysis of different RNA molecules with potential cross-talk may make great contributions to the unveiling of the complex mechanisms underlying tumorigenesis.
| S-EPMC4086520 | biostudies-literature
Project description:Background The development of the ovaries is an important factor that affects egg production performance in geese. Ovarian development is regulated by genes that are expressed dynamically and stage-specifically. The transcriptome profile analysis on ovarian tissues of goose at different egg laying stages could provide an important basis for screening and identifying key genes regulating ovarian development. Results In this study, 4 ovary tissues at each breeding period of pre-laying (PP), laying (LP), and ceased-laying period (CP), respectively, with significant morphology difference, were used for RNA extraction and mRNAs, lncRNAs, and miRNAs comparison in Yili geese. CeRNA regulatory network was constructed for key genes screening. A total of 337, 1136, and 525 differentially expressed DE mRNAs, 466, 925, and 742 DE lncRNAs and 258, 1131 and 909 DE miRNAs were identified between PP and LP, between CP and LP, and between CP and PP groups, respectively. Functional enrichment analysis showed that the differentially expressed mRNAs and non-coding RNA target genes were mainly involved in the cell process, cytokine-cytokine receptor interaction, phagosome, calcium signaling pathway, steroid biosynthesis and ECM-receptor interaction. Differential genes and non-coding RNAs, PDGFRB, ERBB4, LHCGR, MSTRG.129094.34, MSTRG.3524.1 and gga-miR-145–5p, related to reproduction and ovarian development were highly enriched. Furthermore, lncRNA-miRNA-mRNA regulatory networks related to ovary development were constructed. Conclusions Our study found dramatic transcriptomic differences in ovaries of Yili geese at different egg-laying stages, and a differential lncRNA-miRNA-mRNA regulatory network related to cell proliferation, differentiation and apoptosis and involved in stromal follicle development were established and preliminarily validated, which could be regarded as a key regulatory pathway of ovarian development in Yili geese. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08774-4.
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Project description:BackgroundDuck is an economically important poultry and animal model for human viral hepatitis B. However, the molecular mechanisms underlying host-virus interaction remain unclear because of limited information on the duck genome. This study aims to characterize the duck normal liver transcriptome and to identify the differentially expressed transcripts at 24 h after duck hepatitis A virus genotype C (DHAV-C) infection using Illumina-Solexa sequencing.ResultsAfter removal of low-quality sequences and assembly, a total of 52,757 unigenes was obtained from the normal liver group. Further blast analysis showed that 18,918 unigenes successfully matched the known genes in the database. GO analysis revealed that 25,116 unigenes took part in 61 categories of biological processes, cellular components, and molecular functions. Among the 25 clusters of orthologous group categories (COG), the cluster for "General function prediction only" represented the largest group, followed by "Transcription" and "Replication, recombination, and repair." KEGG analysis showed that 17,628 unigenes were involved in 301 pathways. Through comparison of normal and infected transcriptome data, we identified 20 significantly differentially expressed unigenes, which were further confirmed by real-time polymerase chain reaction. Of the 20 unigenes, nine matched the known genes in the database, including three up-regulated genes (virus replicase polyprotein, LRRC3B, and PCK1) and six down-regulated genes (CRP, AICL-like 2, L1CAM, CYB26A1, CHAC1, and ADAM32). The remaining 11 novel unigenes that did not match any known genes in the database may provide a basis for the discovery of new transcripts associated with infection.ConclusionThis study provided a gene expression pattern for normal duck liver and for the previously unrecognized changes in gene transcription that are altered during DHAV-C infection. Our data revealed useful information for future studies on the duck genome and provided new insights into the molecular mechanism of host-DHAV-C interaction.
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Project description:Neuroinflammation contributes to many neurologic disorders including Alzheimer's disease, multiple sclerosis, and stroke. Microglia is brain resident myeloid cells and have emerged as a key driver of the neuroinflammatory responses. MicroRNAs (miRNAs) provide a novel layer of gene regulation and play a critical role in regulating the inflammatory response of peripheral macrophages. However, little is known about the miRNA in inflammatory activation of microglia. To elucidate the role that miRNAs have on microglial phenotypes under classical (M1) or alternative (M2) activation under lipopolysaccharide ('M1'-skewing) and interleukin-4 ('M2a'-skewing) stimulation conditions, we performed microarray expression profiling and bioinformatics analysis of both mRNA and miRNA using primary cultured murine microglia. miR-689, miR-124, and miR-155 were the most strongly associated miRNAs predicted to mediate pro-inflammatory pathways and M1-like activation phenotype. miR-155, the most strongly up-regulated miRNA, regulates the signal transducer and activator of transcription 3 signaling pathway enabling the late phase response to M1-skewing stimulation. Reduced expression in miR-689 and miR-124 are associated with dis-inhibition of many canonical inflammatory pathways. miR-124, miR-711, miR-145 are the strongly associated miRNAs predicted to mediate anti-inflammatory pathways and M2-like activation phenotype. Reductions in miR-711 and miR-124 may regulate inflammatory signaling pathways and peroxisome proliferator-activated receptor-gamma pathway. miR-145 potentially regulate peripheral monocyte/macrophage differentiation and faciliate the M2-skewing phenotype. Overall, through combined miRNA and mRNA expression profiling and bioinformatics analysis we have identified six miRNAs and their putative roles in M1 and M2-skewing of microglial activation through different signaling pathways.
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Project description:Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.
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Project description:Aim: To comprehensively profile the landscape of the mRNA N6-methyladenosine (m6A) modification in human colorectal cancer (CRC). Methods: Methylated RNA immunoprecipitation sequencing (MeRIP-seq) was explored to compare the difference in mRNA N6-methyladenosine (m6A) methylation between CRC tissues and adjacent normal control (NC) tissue. RNA-sequencing (RNA-seq) was performed to transcribe differentially expressed mRNAs. Conjoint analysis of MeRIP-seq and RNA-seq data was conducted to predict RNA-binding proteins (RBPs). Results: MeRIP-seq identified 1110 differentially m6A methylated sites (DMMSs) and 980 differentially m6A methylated genes (DMMGs) in CRC, with 50.13% of all modified genes showing unique m6A-modified peaks in CRC. RNA-seq showed 915 upregulated genes and 1463 downregulated genes in CRC. QRT-PCR verified the RNA-seq results by detecting the expression of some mRNAs. Conjoint analysis of MeRIP-seq and RNA-seq identified 400 differentially m6A methylated and expressed genes (DEGs), and pathway analysis detected that DMMGs and DEGs were closely related to cancer. After analyzing these DMMGs and DEGs through the GEPIA database, we found that the expression of B3GNT6, DKC1, SRPK1, and RIMKLB were associated with prognosis, and the expression of B3GNT6 and RIMKLB were associated with clinical stage. 17 RBPs were identified based on the DMMGs and DEGs, among which FXR1, FXR2, FMR1, IGF2BP2, IGF2BP3, and SRSF1 were obviously highly expressed in CRC, and FMR1, IGF2BP2, and IGF2BP3 were closely related to methylation, and might be involved in the development of CRC. Conclusion: This study comprehensively profiled m6A modification of mRNAs in CRC, which revealed possible mechanisms of m6A-mediated gene expression regulation.
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Project description:p53 is the most frequently mutated gene in human cancers, with over half of all tumors harboring mutation at this locus. R248 and R249 (corresponding to porcine R241 and R242), are among the hotspot mutations frequently mutated in liver, lung, breast, and some other cancers. In this study, p53 gene was knocked out or point-edited (R241 and R242 were converted to 241W and 242S) in porcine fetal fibroblast (PFF) cells via CRISPR-Cas9 technique. High throughput sequencing of miRNA and mRNA uncovered a total of 225 differentially expressed miRNAs (DEMs) and 738 differentially expressed genes (DEGs) in the p53 knockout (p53-KO) cells, and a total of 211 DEMs and 722 DEGs in the point-modified (p53-241W242S) cells. Totally 28 annotated DEMs were found to overlap between p53-KO/p53-WT and p53-241W242S/p53-WT miRNAs datasets, of which miR-34 c, miR-218, miR-205, miR-105-1, miR-105-2, miR-206, miR-224 and miR-429 play important roles in p53 regulatory network. Among the top 10 DEGs in p53-KO and p53-241W242S cells, most genes were reported to be involved in tumors, cell proliferation or cell migration. p53-KO and p53-241W242S cells showed a significantly higher (P < 0.01) proliferation rate compared with p53-WT cells. In conclusion, genetic modifications of p53 gene significantly affect the expression levels of a large number of genes and miRNAs in the PFF cells. The p53-edited PFF cells could be used as non-tumor cell models for investigating the p53 signaling network, and as donor cells for somatic nuclear transfer, with the aim to develop porcine models with the corresponding p53 mutations.Abbreviations: CRISPR-Cas9: Clustered regularly interspaced short palindromic repeats-associated protein 9; PFF: porcine fetal fibroblasts; SCNT: somatic cell nuclear transfer; RNA sequencing: small RNA sequencing and mRNA sequencing; DEGs: differentially expressed mRNAs; DEMs: differentially expressed miRNAs.
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