High throughput sequencing of whole transcriptome and construct of ceRNA regulatory network in RD cells infected with enterovirus D68

Abstract Background With the advancement of sequencing technologies, a plethora of noncoding RNA (ncRNA) species have been widely discovered, including microRNAs (miRNAs), circular RNAs (circRNAs), and long ncRNAs (lncRNAs). However, the mechanism of these non-coding RNAs in diseases caused by enterovirus d68 (EV-D68) remains unclear. The goal of this research was to identify significantly altered circRNAs, lncRNAs, miRNAs, and mRNAs pathways in RD cells infected with EV-D68, analyze their target relationships, demonstrate the competing endogenous RNA (ceRNA) regulatory network, and evaluate their biological functions. Methods The total RNAs were sequenced by high-throughput sequencing technology, and differentially expressed genes between control and infection groups were screened using bioinformatics method. We discovered the targeting relationship between three ncRNAs and mRNA using bioinformatics methods, and then built a ceRNA regulatory network centered on miRNA. The biological functions of differentially expressed mRNAs (DEmRNAs) were discovered through GO and KEGG enrichment analysis. Create a protein interaction network (PPI) to seek for hub mRNAs and learn more about protein–protein interactions. The relative expression was verified using RT-qPCR. The effects of Fos and ARRDC3 on virus replication were confirmed using RT-qPCR, virus titer (TCID50/ml), Western blotting. Results 375 lncRNAs (154 upregulated and 221 downregulated), 33 circRNAs (32 upregulated and 1 downregulated), 96 miRNAs (49 upregulated and 47 downregulated), and 239 mRNAs (135 upregulated and 104 downregulated) were identified as differently in infected group compare to no-infected group. A single lncRNA or circRNA can be connected with numerous miRNAs, which subsequently coregulate additional mRNAs, according to the ceRNA regulatory network. The majority of DEmRNAs were shown to be connected to DNA binding, transcription regulation by RNA polymerase II, transcription factor, MAPK signaling pathways, Hippo signal pathway, and apoptosis pathway, according to GO and KEGG pathway enrichment analysis. The hub mRNAs with EGR1, Fos and Jun as the core were screened through PPI interaction network. We preliminarily demonstrated that the Fos and ARRDC3 genes can suppress EV-D68 viral replication in order to further verify the results of full transcriptome sequencing. Conclusion The results of whole transcriptome analysis after EV-D68 infection of RD cells were first reported in this study, and for the first time, a ceRNA regulation network containing miRNA at its center was established for the first time. The Fos and ARRDC3 genes were found to hinder viral in RD cells. This study establishes a novel insight host response during EV-D68 infection and further investigated potential drug targets.

Download Full-text

Identification and Analysis of lncRNAs by Whole-Transcriptome Sequencing in Porcine Preadipocytes Induced by BMP2

Cytogenetic and Genome Research ◽

10.1159/000501182 ◽

2019 ◽

Vol 158 (3) ◽

pp. 133-144

Author(s):

Sheng Li ◽

Chengzhen Chen ◽

Menglong Chai ◽

Jiawei Wang ◽

Bao Yuan ◽

...

Keyword(s):

Target Genes ◽

Metabolic Diseases ◽

Enrichment Analysis ◽

Fat Deposition ◽

Bone Morphogenetic Protein 2 ◽

Morphogenetic Protein ◽

Whole Transcriptome Sequencing ◽

Mirna Sponges ◽

Whole Transcriptome ◽

First Time

Bone morphogenetic protein 2 (BMP2) can mediate the signaling of R-Smads and regulate different biological functions, including adipocyte differentiation. Long noncoding RNAs (lncRNAs) can be involved in many important biological processes, including fat metabolism, as miRNA sponges. This study aimed to investigate the molecular mechanism of fat deposition and to provide useful information for the prevention and treatment of lipid-related diseases. lncRNA sequencing was performed to compare and analyze, for the first time, the expression of lncRNAs in BMP2-induced and non-BMP2-induced preadipocytes from Junmu1 pigs. In addition, functional annotation and enrichment analysis of differentially expressed lncRNA target genes were carried out. lncRNAs and mRNAs were compared and analyzed. lncRNAs were identified that may regulate adipogenesis and lipid metabolism. The results give a theoretical basis for further studies on fat deposition mechanisms and provide potential therapeutic targets for metabolic diseases.

Download Full-text

Whole-transcriptome RNA sequencing reveals the global molecular responses and ceRNA regulatory network of mRNAs, lncRNAs, miRNAs and circRNAs in response to copper toxicity in Ziyang Xiangcheng (Citrus junos Sieb. Ex Tanaka)

BMC Plant Biology ◽

10.1186/s12870-019-2087-1 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 4

Author(s):

Xing-Zheng Fu ◽

Xiao-Yong Zhang ◽

Jie-Ya Qiu ◽

Xue Zhou ◽

Meng Yuan ◽

...

Keyword(s):

Regulatory Network ◽

Copper Toxicity ◽

Enrichment Analysis ◽

Circular Rnas ◽

Potential Threat ◽

Cu Toxicity ◽

Citrus Junos ◽

Whole Transcriptome Sequencing ◽

Citrus Production ◽

Whole Transcriptome

Abstract Background Copper (Cu) toxicity has become a potential threat for citrus production, but little is known about related mechanisms. This study aims to uncover the global landscape of mRNAs, long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and microRNAs (miRNAs) in response to Cu toxicity so as to construct a regulatory network of competing endogenous RNAs (ceRNAs) and to provide valuable knowledge pertinent to Cu response in citrus. Results Tolerance of four commonly used rootstocks to Cu toxicity was evaluated, and ‘Ziyang Xiangcheng’ (Citrus junos) was found to be the most tolerant genotype. Then the roots and leaves sampled from ‘Ziyang Xiangcheng’ with or without Cu treatment were used for whole-transcriptome sequencing. In total, 5734 and 222 mRNAs, 164 and 5 lncRNAs, 45 and 17 circRNAs, and 147 and 130 miRNAs were identified to be differentially expressed (DE) in Cu-treated roots and leaves, respectively, in comparison with the control. Gene ontology enrichment analysis showed that most of the DEmRNAs and targets of DElncRNAs and DEmiRNAs were annotated to the categories of ‘oxidation-reduction’, ‘phosphorylation’, ‘membrane’, and ‘ion binding’. The ceRNA network was then constructed with the predicted pairs of DEmRNAs-DEmiRNAs and DElncRNAs-DEmiRNAs, which further revealed regulatory roles of these DERNAs in Cu toxicity. Conclusions A large number of mRNAs, lncRNAs, circRNAs, and miRNAs in ‘Ziyang Xiangcheng’ were altered in response to Cu toxicity, which may play crucial roles in mitigation of Cu toxicity through the ceRNA regulatory network in this Cu-tolerant rootstock.

Download Full-text

Three novel circRNAs upregulated in tissue and plasma from hepatocellular carcinoma patients and their regulatory network

Cancer Cell International ◽

10.1186/s12935-021-01762-w ◽

2021 ◽

Vol 21 (1) ◽

Cited By ~ 1

Author(s):

Lianghai Wang ◽

Lisha Zhou ◽

Jun Hou ◽

Jin Meng ◽

Ke Lin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regulatory Network ◽

Expression Profiles ◽

Interaction Network ◽

Enrichment Analysis ◽

Circular Rnas ◽

Pathway Enrichment Analysis ◽

Plasma Samples ◽

Hub Genes ◽

Protein Protein Interaction

Abstract Background The regulatory roles of circular RNAs (circRNAs) in tumorigenesis have attracted increasing attention. However, novel circRNAs with the potential to be used as serum/plasma biomarkers and their regulatory mechanism in the pathogenesis of hepatocellular carcinoma (HCC) remain explored. Methods CircRNA expression profiles of tumor tissues and plasma samples from HCC patients were compiled and jointly analyzed. CircRNA–miRNA–mRNA interactions were predicted by bioinformatics tools. The expression of interacting miRNAs and mRNA was verified in independent datasets. Survival analysis and pathway enrichment analysis were conducted on hub genes. Results We identified three significantly up-regulated circRNAs (hsa_circ_0009910, hsa_circ_0049783, and hsa_circ_0089172) both in HCC tissues and plasma samples. Two of them were validated to be indeed circular and could be excreted from hepatoma cells. We further revealed four miRNAs (hsa-miR-455-5p, hsa-miR-615-3p, hsa-miR-18a-3p, hsa-miR-4524a-3p) that targeting circRNAs and expressed in human HCC samples, and 95 mRNAs targeted by miRNAs and significantly up-regulated in two HCC cohorts. A protein-protein interaction network revealed 19 hub genes, 12 of them (MCM6, CCNB1, CDC20, NDC80, ZWINT, ASPM, CENPU, MCM3, MCM5, ECT2, CDC7, and DLGAP5) were associated with reduced survival in two HCC cohorts. KEGG, Reactome, and Wikipathway enrichment analysis indicated that the hub genes mainly functioned in DNA replication and cell cycle. Conclusions Our study uncovers three novel deregulated circRNAs in tumor and plasma from HCC patients and provides an insight into the pathogenesis from the circRNA–miRNA–mRNA regulatory network.

Download Full-text

The circular RNA expression profile in ovarian serous cystadenocarcinoma reveals a complex circRNA–miRNA regulatory network

BMC Medical Genomics ◽

10.1186/s12920-021-01132-5 ◽

2021 ◽

Vol 14 (S2) ◽

Author(s):

Minhui Zhuang ◽

Jian Zhao ◽

Jing Wu ◽

Shilong Fu ◽

Ping Han ◽

...

Keyword(s):

Potential Function ◽

Expression Profile ◽

Regulatory Network ◽

Noncoding Rna ◽

Interaction Network ◽

Enrichment Analysis ◽

Circular Rna ◽

Mirna Sponge ◽

Normal Tissues ◽

Serous Cystadenocarcinoma

Abstract Background Ovarian serous cystadenocarcinoma is one of the most serious gynecological malignancies. Circular RNA (circRNA) is a type of noncoding RNA with a covalently closed continuous loop structure. Abnormal circRNA expression might be associated with tumorigenesis because of its complex biological mechanisms by, for example, functioning as a microRNA (miRNA) sponge. However, the circRNA expression profile in ovarian serous cystadenocarcinoma and their associations with other RNAs have not yet been characterized. The main purpose of this study was to reveal the circRNA expression profile in ovarian serous cystadenocarcinoma. Methods We collected six specimens from three patients with ovarian serous cystadenocarcinoma and adjacent normal tissues. After RNA sequencing, we analyzed the expression of circRNAs with relevant mRNAs and miRNAs to characterize potential function. Results 15,092 unique circRNAs were identified in six specimens. Approximately 46% of these circRNAs were not recorded in public databases. We then reported 353 differentially expressed circRNAs with oncogenes and tumor-suppressor genes. Furthermore, a conjoint analysis with relevant mRNAs revealed consistent changes between circRNAs and their homologous mRNAs. Overall, construction of a circRNA–miRNA network suggested that 4 special circRNAs could be used as potential biomarkers. Conclusions Our study revealed the circRNA expression profile in the tissues of patients with ovarian serous cystadenocarcinoma. The differential expression of circRNAs was thought to be associated with ovarian serous cystadenocarcinoma in the enrichment analysis, and co-expression analysis with relevant mRNAs and miRNAs illustrated the latent regulatory network. We also constructed a complex circRNA–miRNA interaction network and then demonstrated the potential function of certain circRNAs to aid future diagnosis and treatment.

Download Full-text

Whole-transcriptome RNA sequencing reveals the global molecular responses and ceRNA regulatory network of mRNAs, lncRNAs, miRNAs and circRNAs in response to Cu toxicity in Ziyang xiangcheng (Citrus junos Sieb. ex Tanaka)

10.21203/rs.2.13386/v2 ◽

2019 ◽

Author(s):

xing-zheng fu ◽

Xiao-Yong Zhang ◽

Jie-Ya Qiu ◽

Xue Zhou ◽

Meng Yuan ◽

...

Keyword(s):

Regulatory Network ◽

Enrichment Analysis ◽

Circular Rnas ◽

Potential Threat ◽

Cu Toxicity ◽

Citrus Junos ◽

Whole Transcriptome Sequencing ◽

Competing Endogenous Rnas ◽

Citrus Production ◽

Whole Transcriptome

Abstract Background Copper (Cu) toxicity has become a potential threat for citrus production, but little is known about related mechanisms. This study aims to uncover the global landscape of mRNAs, long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and microRNAs (miRNAs) in response to Cu toxicity so as to construct a regulatory network of competing endogenous RNAs (ceRNAs) and to provide valuable knowledge pertinent to Cu response in citrus. Results Tolerance of four commonly used rootstocks to Cu toxicity was evaluated, and ‘Ziyang Xiangcheng’ (Citrus junos ) was found to be the most tolerant genotype. Then the roots and leaves sampled from ‘Ziyang Xiangcheng’ with or without Cu treatment were used for whole-transcriptome sequencing. In total, 5734 and 222 mRNAs, 164 and 5 lncRNAs, 45 and 17 circRNAs, and 147 and 130 miRNAs were identified to be differentially expressed (DE) in Cu-treated roots and leaves, respectively, in comparison with the control. Gene ontology enrichment analysis showed that most of the DEmRNAs and targets of DElncRNAs and DEmiRNAs were annotated to the categories of ‘oxidation-reduction’, ‘phosphorylation’, ‘membrane’, and ‘ion binding’. The ceRNA network was then constructed with the predicted pairs of DEmRNAs-DEmiRNAs and DElncRNAs-DEmiRNAs, which further revealed regulatory roles of these DERNAs in Cu toxicity. Conclusions A large number of mRNAs, lncRNAs, circRNAs, and miRNAs in ‘Ziyang Xiangcheng’ were altered in response to Cu toxicity, which may play crucial roles in mitigation of Cu toxicity through the ceRNA regulatory network in this Cu-tolerant rootstock.

Download Full-text

A transcriptomic profile of topping responsive non-coding RNAs in tobacco roots (Nicotiana tabacum)

BMC Genomics ◽

10.1186/s12864-019-6236-6 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 4

Author(s):

Xi Chen ◽

Shuo Sun ◽

Fangjie Liu ◽

Enhui Shen ◽

Lu Liu ◽

...

Keyword(s):

Nicotiana Tabacum ◽

High Throughput Sequencing ◽

Potential Role ◽

Interaction Network ◽

Differentially Expressed ◽

Circular Rnas ◽

Biological Functions ◽

Non Coding Rnas ◽

Nicotine Biosynthesis ◽

Tobacco Roots

Abstract Background Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long ncRNAs (lncRNAs) and circular RNAs (circRNAs), accomplish remarkable variety of biological functions. However, the composition of ncRNAs and their interactions with coding RNAs in modulating and controlling of cellular process in plants is largely unknown. Using a diverse group of high-throughput sequencing strategies, the mRNA, miRNA, lncRNA and circRNA compositions of tobacco (Nicotiana tabacum) roots determined and their alteration and potential biological functions in response to topping treatment analyzed. Results A total of 688 miRNAs, 7423 non-redundant lncRNAs and 12,414 circRNAs were identified, among which, some selected differentially expressed RNAs were verified by quantitative real-time PCR. Using the differentially expressed RNAs, a co-expression network was established that included all four types of RNAs. The number of circRNAs identified were higher than that of miRNAs and lncRNAs, but only two circRNAs were present in the co-expression network. LncRNAs appear to be the most active ncRNAs based on their numbers presented in the co-expression network, but none of them seems to be an eTM (endogenous Target Mimicry) of miRNAs. Integrated with analyses of sequence interaction, several mRNA-circRNA-miRNA interaction networks with a potential role in the regulation of nicotine biosynthesis were uncovered, including a QS-circQS-miR6024 interaction network. In this network miR6024 was significantly down-regulated, while the expression levels of its two targets, circQS and its host gene QS, were sharply increased following the topping treatment. Conclusions These results illustrated the transcriptomic profiles of tobacco roots, the organ responsible for nicotine biosynthesis. mRNAs always play the most important roles, while ncRNAs are also expressed extensively for topping treatment response, especially circRNAs are the most activated in the ncRNA pool. These studies also provided insights on the coordinated regulation module of coding and non-coding RNAs in a single plant biological sample. The findings reported here indicate that ncRNAs appear to form interaction complex for the regulation of stress response forming regulation networks with transcripts involved in nicotine biosynthesis in tobacco.

Download Full-text

Bioinformatics analysis of expression profiling by high throughput sequencing for identification of potential key genes among SARS-CoV-2/COVID 19

10.21203/rs.3.rs-122015/v2 ◽

2021 ◽

Author(s):

Basavaraj Mallikarjunayya Vastrad ◽

Chanabasayya Mallikarjunayya Vastrad

Keyword(s):

High Throughput ◽

Expression Profiling ◽

Regulatory Network ◽

Target Gene ◽

Molecular Mechanisms ◽

High Throughput Sequencing ◽

Enrichment Analysis ◽

Current Investigation ◽

Hub Genes ◽

Key Genes

Abstract Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is pandemic recently emerged and is rapidly spreading in humans. However, the precise molecular mechanisms of the advancement and progression of SARS-CoV-2 infection remain unclear. The current investigation attempted to identify and functionally analyze the differentially expressed genes (DEGs) between SARS-CoV-2 infection and mock by using comprehensive bioinformatics analyses. The GSE148729 expression profiling by high throughput sequencing was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the limma package in R software to identify DEGs. Pathway and gene ontology (GO) enrichment analysis of the up and down regulated genes were performed in ToppGene. The HIPPIE database was used to evaluate the interactions of up and down regulated genes and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the Network Analyzer plugin. Subsequently, extensive target prediction and network analyses methods were used to assess, target gene - miRNA regulatory network and target gene - TF regulatory network. Receiver operating characteristic (ROC) analysis was utilized for validation. A total of 928 DEGs (461 up regulated genes and 467 down regulated genes) were identified between SARS-CoV-2 infection and mock samples. The Pathway enrichment analysis results showed that these up and down regulated genes were significantly enriched in cytokine-cytokine receptor interaction, and ascorbate and aldarate metabolism. Several significant GO terms, including the response to biotic stimulus and oxoacid metabolic process, were identified as being closely associated with these up and down regulated genes. The top hub genes and target genes were screened and included JUN, FBXO6, PCLAF, CFTR, TXNIP, PMAIP1, BRI3BP, FAHD1, PROX1, CXCL11, SERHL2 and CFI. ROC curve analysis showed that messenger RNA levels of these ten genes (DDX58, IFITM2, IRF1, PML, SAMHD1, ACSS1, CYP2U1, DDC, PNMT and UGT2A3) exhibited better diagnostic efficiency for SARS-CoV-2 infection and mock. The current investigation identified a series of key genes and pathways that may be involved in the progression of SARS-CoV-2 infection, providing a new understanding of the underlying molecular mechanisms of SARS-CoV-2 infection.

Download Full-text

In Silico Protein Interaction Network Analysis of Virulence Proteins Associated with Invasive Aspergillosis for Drug Discovery

Current Topics in Medicinal Chemistry ◽

10.2174/1568026619666181120150633 ◽

2019 ◽

Vol 19 (2) ◽

pp. 146-155 ◽

Cited By ~ 1

Author(s):

Renu Chaudhary ◽

Meenakshi Balhara ◽

Deepak Kumar Jangir ◽

Mehak Dangi ◽

Mrridula Dangi ◽

...

Keyword(s):

Network Analysis ◽

Invasive Aspergillosis ◽

Protein Interaction ◽

Drug Target ◽

Interaction Network ◽

Enrichment Analysis ◽

Homology Model ◽

Ppi Network ◽

Virulence Proteins ◽

Hub Proteins

<P>Background: Protein-Protein interaction (PPI) network analysis of virulence proteins of Aspergillus fumigatus is a prevailing strategy to understand the mechanism behind the virulence of A. fumigatus. The identification of major hub proteins and targeting the hub protein as a new antifungal drug target will help in treating the invasive aspergillosis. </P><P> Materials & Method: In the present study, the PPI network of 96 virulence (drug target) proteins of A. fumigatus were investigated which resulted in 103 nodes and 430 edges. Topological enrichment analysis of the PPI network was also carried out by using STRING database and Network analyzer a cytoscape plugin app. The key enriched KEGG pathway and protein domains were analyzed by STRING.Conclusion:Manual curation of PPI data identified three proteins (PyrABCN-43, AroM-34, and Glt1- 34) of A. fumigatus possessing the highest interacting partners. Top 10% hub proteins were also identified from the network using cytohubba on the basis of seven algorithms, i.e. betweenness, radiality, closeness, degree, bottleneck, MCC and EPC. Homology model and the active pocket of top three hub proteins were also predicted.</P>

Download Full-text

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

Current Bioinformatics ◽

10.2174/1574893615666200207092410 ◽

2021 ◽

Vol 15 (8) ◽

pp. 927-936 ◽

Cited By ~ 3

Author(s):

Yan Peng ◽

Yuewu Liu ◽

Xinbo Chen

Keyword(s):

Drought Stress ◽

Target Genes ◽

Hot Spot ◽

Interaction Network ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Protein Protein Interaction ◽

Promising Tool ◽

Differentially Expressed Mirnas ◽

Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identiﬁed. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

Download Full-text

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

Current Bioinformatics ◽

10.2174/1574893615999200608125427 ◽

2020 ◽

Vol 15 ◽

Author(s):

Wei Han ◽

Dongchen Lu ◽

Chonggao Wang ◽

Mengdi Cui ◽

Kai Lu

Keyword(s):

Papillary Thyroid Carcinoma ◽

Thyroid Carcinoma ◽

Differential Expression Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Integrated Analysis ◽

Papillary Thyroid ◽

Gene Set Enrichment ◽

Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

Download Full-text