Long non-coding RNAs are differentially expressed in dysferlinopathy (Preprint)

2021 ◽  
Author(s):  
Richa Singhal ◽  
Rachel Lukose ◽  
Gwenyth Carr ◽  
Afsoon Moktar ◽  
Eric C Rouchka ◽  
...  
Keyword(s):  
Network Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Disease Process ◽  
C2c12 Cells ◽  
Differentially Expressed ◽  
Aberrant Expression ◽  
Non Coding Rnas ◽  
Go Terms

BACKGROUND Long non-coding RNAs (lncRNAs) are non-coding RNA transcripts greater than 200 nucleotides in length and are known to play a role in regulating the transcription of genes involved in vital cellular functions. We hypothesized the disease process in dysferlinopathy is linked to an aberrant expression of lncRNAs and mRNAs. OBJECTIVE In this study, we compared the lncRNA and mRNA expression profiles between the normal and dysferlin deficient murine myoblasts (C2C12 cells). METHODS LncRNA and mRNA expression profiling were performed using a microarray. Several lncRNAs with differential expression were validated using quantitative real time polymerase chain reaction (qRT-PCR). Gene Ontology analysis was performed to understand the functional role of the differentially expressed mRNAs. Further bioinformatics analysis was used to explore the potential function, lncRNA-mRNA correlation and potential targets of the differentially expressed lncRNAs. RESULTS We found 3195 lncRNAs and 1966 mRNAs that are differentially expressed. The chromosomal distribution of the differentially expressed lncRNAs and mRNAs was unequal, with the chromosome 2 having the highest number of lncRNAs and chromosome 7 having the highest number of mRNAs that were differentially expressed. Pathway analysis of the differentially expressed genes indicated the involvement of several signaling pathways including PI3K-Akt, FoxO, Wnt, cAMP and Hippo. The differentially expressed genes were also enriched for the GO terms, developmental process and muscle system process. Network analysis identified 8 statistically significant (p<0.05) network objects from the upregulated lncRNAs and 3 statistically significant network objects from the downregulated lncRNAs. CONCLUSIONS Our results thus far imply that dysferlinopathy is associated with an aberrant expression of multiple lncRNAs many of which may have a specific function in the disease process. GO terms and Network Analysis suggest a muscle specific role for these lncRNAs. To elucidate the specific roles of these abnormally expressed non-coding RNAs, further studies engineering their expression are required.

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

scholarly journals Comprehensive Analysis of the Expression Profiles of Long Non-Coding RNAs with Associated ceRNA Network Involved in the Colon Cancer Staging and Progression

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Meini Wu ◽  
Wenliang Li ◽  
Fengchang Huang ◽  
Jing Sun ◽  
Kang ping Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Expression Profiles ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Stage Iii ◽  
Aberrant Expression ◽  
Normal Tissues ◽  
Cerna Network ◽  
Tumor Tissues ◽  
Non Coding Rnas

AbstractLong non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to compete with microRNAs (miRNAs) in cancer occurrence and development. However, the differential expression of RNAs and their ceRNA network during the development of colon cancer (CC) remains unclear. This study was aimed at comprehensive analysis of the lncRNAs and their ceRNA networks associated with CC. Whole transcriptome sequencing was performed on colorectal and adjacent normal tissues at different pathological stages. Forty-nine lncRNAs were differently expressed between the CC tissues and their adjacent normal tissues at all stages. Aberrant expression of lncRNA CDKN2B-AS1 and lncRNA MIR4435-2HG was confirmed by TCGA database. Moreover, 14 lncRNAs were differentially expressed between early and advance stages of the tumor tissues, and 117 miRNAs were specifically expressed in stage III & IV. Weighted gene co-expression network analysis of 17105 differently expressed mRNAs revealed that the mRNAs shown in module pink, midnight blue, black, and light cyan were related to TNM and pathological stage, and that these mRNAs were enriched in cancer related functions and pathways. As DElncRNA showed a trend of change similar to that of the DEmRNA and opposite to that of DEmiRNA, ceRNA network was constructed with 3 DEmiRNAs, 5 DElncRNAs, and 130 DEmRNAs. Real time PCR revealed that expression of MEG3 was decreased in the tumor tissues belonging to stage III and IV as compared to that in stage I. Moreover, hsa-miR-324-5p was upregulated, while FGFR3, PLCB4, and IKBKB were downregulated in the tumor tissues as compared to that in the adjacent normal tissues. Thus, this study revealed differentially expressed lncRNA between different stages of CC as well as suggested that lncRNA CDKN2B-AS1, MIR4435-2HG, and MEG3 may act as diagnostic biomarkers for the development of CC.

Identification of Differentially Expressed Genes and Signaling Pathways Related to Ovarian Endometriosis by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Kainan Lin ◽  
Zhenyan Pan ◽  
Renke He ◽  
Hanchu Wang ◽  
Kai Zhou ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Go Analysis ◽  
Pathway Enrichment

Abstract Purpose: Endometriosis was a common gynecological disease, however, the specific mechanism and the key molecules of endometriosis remained uncertain. This study aimed to single out key genes associated with poor prognosis, and further uncover underlying mechanisms.Methods: Data regarding mRNA expression profiles used in this study were retrieved from the Gene Expression Omnibus (GEO) database, a total of three mRNA expression profiles were included for subsequent analysis (GSE31515, GSE58178 and GSE120103). Then, we conducted Gene Ontology analysis (GO analysis), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) analysis by the software R.Results: A total of 304 differentially expressed genes (DEGs) between endometriosis tissues and normal endometrium tissues were identified in integrated analysis, including 185 up-regulated genes and 119 down-regulated genes. GO analysis reveals that the DEGs of endometriosis were closely associated with molecular origin of bacteria. KEGG pathway enrichment analysis indicates that the DEGs were mainly involved in AGE-RAGE signaling pathway in diabetic complications. In addition, PPI of these DEGs was visualized by Cytoscape platform with utilization of Search Tool for the Retrieval of Interacting Genes (STRING). PPI analysis identifies 10 potential DEGs-related protein targets, including CCND1, IL6, CCL2, COL1A2, PTGS2, VCAM1, COL3A1, ELN, SERPINE1, HSP90B1. Conclusion: In conclusion, the present study reveals that bacterial contamination, defect of female reproductive system development, retrograde menstruation and the AGE-RAGE signaling pathway may be involved in the development of endometriosis In addition, these identified DEGs may be of clinical significance for the diagnosis and treatment of the endometriosis.

scholarly journals Identification of key genes and pathways in endometriosis by integrated expression profiles analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10171
Author(s):  
Ding Cui ◽  
Yang Liu ◽  
Junyan Ma ◽  
Kaiqing Lin ◽  
Kaihong Xu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Western Blotting ◽  
Expression Profiles ◽  
Hippo Pathway ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Normal Endometrium

The purpose of this study was to integrate the existing expression profile data on endometriosis (EM)-related tissues in order to identify the differentially expressed genes. In this study, three series of raw expression data were downloaded from GEO database. Differentially expressed genes (DEGs) in three tissue types were screened. GO, KEGG pathway enrichment analysis, core differential genes (CDGs) protein–protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) were performed, finally, the dysregulation of Hippo pathway in ectopic endometrium (EC) was detected by Western blotting. A total of 1,811 DEGs between eutopic (EU) and normal endometrium (NE), 5,947 DEGs between EC and EU, and 3,192 DEGs between EC and NE datasets were identified. After screening, 394 CDGs were obtained, and 5 hub genes identified in the PPI network. CDGs enrichment and WGCNA network analysis revealed cell proliferation, differentiation, migration and other biological processes, Hippo and Wnt signaling pathways, and a variety of tumor-related pathways. Western blotting results showed that YAP/TAZ was upregulated, and MOB1, pMOB1, SAV1, LATS1 and LATS2 were downregulated in EC. Moreover, CDGs, especially the hub genes, are potential biomarkers and therapeutic targets. Finally, the Hippo pathway might play a key role in the development of endometriosis.

scholarly journals Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Huili Qiao ◽  
Jingya Wang ◽  
Yuanzhuo Wang ◽  
Juanjuan Yang ◽  
Bofan Wei ◽  
...  
Keyword(s):  
Bombyx Mori ◽  
Target Gene ◽  
Fat Body ◽  
Expression Profiles ◽  
Functional Characterization ◽  
Differentially Expressed ◽  
Post Injection ◽  
Biological Processes ◽  
Potential Target ◽  
Non Coding Rnas

Abstract Background 20-hydroxyecdysone (20E) plays important roles in insect molting and metamorphosis. 20E-induced autophagy has been detected during the larval–pupal transition in different insects. In Bombyx mori, autophagy is induced by 20E in the larval fat body. Long non-coding RNAs (lncRNAs) function in various biological processes in many organisms, including insects. Many lncRNAs have been reported to be potential for autophagy occurrence in mammals, but it has not been investigated in insects. Results RNA libraries from the fat body of B. mori dissected at 2 and 6 h post-injection with 20E were constructed and sequenced, and comprehensive analysis of lncRNAs and mRNAs was performed. A total of 1035 lncRNAs were identified, including 905 lincRNAs and 130 antisense lncRNAs. Compared with mRNAs, lncRNAs had longer transcript length and fewer exons. 132 lncRNAs were found differentially expressed at 2 h post injection, compared with 64 lncRNAs at 6 h post injection. Thirty differentially expressed lncRNAs were common at 2 and 6 h post-injection, and were hypothesized to be associated with the 20E response. Target gene analysis predicted 6493 lncRNA-mRNA cis pairs and 42,797 lncRNA-mRNA trans pairs. The expression profiles of LNC_000560 were highly consistent with its potential target genes, Atg4B, and RNAi of LNC_000560 significantly decreased the expression of LNC_000560 and Atg4B. These results indicated that LNC_000560 was potentially involved in the 20E-induced autophagy of the fat body by regulating Atg4B. Conclusions This study provides the genome-wide identification and functional characterization of lncRNAs associated with 20E-induced autophagy in the fat body of B. mori. LNC_000560 and its potential target gene were identified to be related to 20-regulated autophagy in B. mori. These results will be helpful for further studying the regulatory mechanisms of lncRNAs in autophagy and other biological processes in this insect model.

scholarly journals Integrative Analysis of miRNA and mRNA Expression Profiles in Mammary Glands of Holstein Cows Artificially Infected with Staphylococcus aureus

Pathogens ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 506
Author(s):  
Xiaolong Wang ◽  
Yongliang Fan ◽  
Yifan He ◽  
Ziyin Han ◽  
Zaicheng Gong ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Mrna Expression ◽  
Calcium Binding ◽  
Expression Profiles ◽  
Bovine Mastitis ◽  
Mammary Glands ◽  
Integrative Analysis ◽  
Differentially Expressed ◽  
Future Application ◽  
Collagen Type Iv

Staphylococcus aureus- induced mastitis is one of the most intractable problems for the dairy industry, which causes loss of milk yield and early slaughter of cows worldwide. Few studies have used a comprehensive approach based on the integrative analysis of miRNA and mRNA expression profiles to explore molecular mechanism in bovine mastitis caused by S. aureus. In this study, S. aureus (A1, B1 and C1) and sterile phosphate buffered saline (PBS) (A2, B2 and C2) were introduced to different udder quarters of three individual cows, and transcriptome sequencing and microarrays were utilized to detected miRNA and gene expression in mammary glands from the challenged and control groups. A total of 77 differentially expressed microRNAs (DE miRNAs) and 1625 differentially expressed genes (DEGs) were identified. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that multiple DEGs were enriched in significant terms and pathways associated with immunity and inflammation. Integrative analysis between DE miRNAs and DEGs proved that miR-664b, miR-23b-3p, miR-331-5p, miR-19b and miR-2431-3p were potential factors regulating the expression levels of CD14 Molecule (CD14), G protein subunit gamma 2 (GNG2), interleukin 17A (IL17A), collagen type IV alpha 1 chain (COL4A1), microtubule associated protein RP/EB family member 2 (MAPRE2), member of RAS oncogene family (RAP1B), LDOC1 regulator of NFKB signaling (LDOC1), low-density lipoprotein receptor (LDLR) and S100 calcium binding protein A9 (S100A9) in bovine mastitis caused by S. aureus. These findings could enhance the understanding of the underlying immune response in bovine mammary glands against S. aureus infection and provide a useful foundation for future application of the miRNA–mRNA-based genetic regulatory network in the breeding cows resistant to S. aureus.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

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