miRNA and mRNA Expression Profiles Reveal Insight into Chitosan-Mediated Regulation of Plant Growth

2018 ◽  
Vol 66 (15) ◽  
pp. 3810-3822 ◽  
Author(s):  
Xiaoqian Zhang ◽  
Kecheng Li ◽  
Ronge Xing ◽  
Song Liu ◽  
Xiaolin Chen ◽  
...  
Keyword(s):  
Plant Growth ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Insight Into

scholarly journals Unique MicroRNA and mRNA Interactions in EGFR-Mutated Lung Adenocarcinoma

2018 ◽  
Vol 7 (11) ◽  
pp. 419 ◽  
Author(s):  
Sophia Subat ◽  
Kentaro Inamura ◽  
Hironori Ninomiya ◽  
Hiroko Nagano ◽  
Sakae Okumura ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mrna Expression ◽  
Regulatory Network ◽  
Egfr Mutation ◽  
Expression Profiles ◽  
Integrative Analysis ◽  
Future Research ◽  
Mutation Status ◽  
Egfr Mutated ◽  
Insight Into

The EGFR gene was one of the first molecules to be selected for targeted gene therapy. EGFR-mutated lung adenocarcinoma, which is responsive to EGFR inhibitors, is characterized by a distinct oncogenic pathway in which unique microRNA (miRNA)–mRNA interactions have been observed. However, little information is available about the miRNA–mRNA regulatory network involved. Both miRNA and mRNA expression profiles were investigated using microarrays in 155 surgically resected specimens of lung adenocarcinoma with a known EGFR mutation status (52 mutated and 103 wild-type cases). An integrative analysis of the data was performed to identify the unique miRNA–mRNA regulatory network in EGFR-mutated lung adenocarcinoma. Expression profiling of miRNAs and mRNAs yielded characteristic miRNA/mRNA signatures (19 miRNAs/431 mRNAs) in EGFR-mutated lung adenocarcinoma. Five of the 19 miRNAs were previously listed as EGFR-mutation-specific miRNAs (i.e., miR-532-3p, miR-500a-3p, miR-224-5p, miR-502-3p, and miR-532-5p). An integrative analysis of miRNA and mRNA expression revealed a refined list of putative miRNA–mRNA interactions, of which 63 were potentially involved in EGFR-mutated tumors. Network structural analysis provided a comprehensive view of the complex miRNA–mRNA interactions in EGFR-mutated lung adenocarcinoma, including DUSP4 and MUC4 axes. Overall, this observational study provides insight into the unique miRNA–mRNA regulatory network present in EGFR-mutated tumors. Our findings, if validated, would inform future research examining the interplay of miRNAs and mRNAs in EGFR-mutated lung adenocarcinoma.

scholarly journals Expression imbalance map: a new visualization method for detection of mRNA expression imbalance regions

2003 ◽  
Vol 13 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Makoto Kano ◽  
Kunihiro Nishimura ◽  
Shumpei Ishikawa ◽  
Shuichi Tsutsumi ◽  
Koichi Hirota ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Expression Profiles ◽  
Genomic Structure ◽  
Comparative Genomic ◽  
Visualization Method ◽  
Expression Data ◽  
Microarray Expression ◽  
Insight Into ◽  
Arbitrary Selection ◽  
Selection Of

We describe the development of a new visualization method, called the expression imbalance map (EIM), for detecting mRNA expression imbalance regions, reflecting genomic losses and gains at a much higher resolution than conventional technologies such as comparative genomic hybridization (CGH). Simple spatial mapping of the microarray expression profiles on chromosomal location provides little information about genomic structure, because mRNA expression levels do not completely reflect genomic copy number and some microarray probes would be of low quality. The EIM, which does not employ arbitrary selection of thresholds in conjunction with hypergeometric distribution-based algorithm, has a high tolerance of these complex factors. The EIM could detect regionally underexpressed or overexpressed genes (called, here, an expression imbalance region) in lung cancer specimens from their gene expression data of oligonucleotide microarray. Many known as well as potential loci with frequent genomic losses or gains were detected as expression imbalance regions by the EIM. Therefore, the EIM should provide the user with further insight into genomic structure through mRNA expression.

scholarly journals Molecular Comparison of Imatinib-Naïve and Resistant Gastrointestinal Stromal Tumors: Differentially Expressed microRNAs and mRNAs

Cancers ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 882 ◽  
Author(s):  
Amirnasr ◽  
Gits ◽  
van Kuijk ◽  
Smid ◽  
Vriends ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Cellular Proliferation ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Imatinib Resistance ◽  
Network Analyses ◽  
Biochemical Pathways ◽  
Imatinib Resistant ◽  
Differentially Expressed Mirnas ◽  
Insight Into

Despite the success of imatinib in advanced gastrointestinal stromal tumor (GIST) patients, 50% of the patients experience resistance within two years of treatment underscoring the need to get better insight into the mechanisms conferring imatinib resistance. Here the microRNA and mRNA expression profiles in primary (imatinib-naïve) and imatinib-resistant GIST were examined. Fifty-three GIST samples harboring primary KIT mutations (exon 9; n = 11/exon 11; n = 41/exon 17; n = 1) and comprising imatinib-naïve (IM-n) (n = 33) and imatinib-resistant (IM-r) (n = 20) tumors, were analyzed. The microRNA expression profiles were determined and from a subset (IM-n, n = 14; IM-r, n = 15) the mRNA expression profile was established. Ingenuity pathway analyses were used to unravel biochemical pathways and gene networks in IM-r GIST. Thirty-five differentially expressed miRNAs between IM-n and IM-r GIST samples were identified. Additionally, miRNAs distinguished IM-r samples with and without secondary KIT mutations. Furthermore 352 aberrantly expressed genes were found in IM-r samples. Pathway and network analyses revealed an association of differentially expressed genes with cell cycle progression and cellular proliferation, thereby implicating genes and pathways involved in imatinib resistance in GIST. Differentially expressed miRNAs and mRNAs between IM-n and IM-r GIST were identified. Bioinformatic analyses provided insight into the genes and biochemical pathways involved in imatinib-resistance and highlighted key genes that may be putative treatment targets.

scholarly journals Comparison of lncRNA and mRNA expression in mouse brains infected by a wild-type and a lab-attenuated Rabies lyssavirus

2020 ◽  
Author(s):  
Baokun Sui ◽  
Dong Chen ◽  
Wei Liu ◽  
Bin Tian ◽  
Lei Lv ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Clinical Symptoms ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Wild Type ◽  
Fresh Insight ◽  
Neuron Injury ◽  
Insight Into ◽  
Generation Sequencing

Rabies is a lethal disease caused by Rabies lyssavirus, commonly known as rabies virus (RABV), and results in nearly 100 % death once clinical symptoms occur in human and animals. Long non-coding RNAs (lncRNAs) have been reported to be associated with viral infection. But the role of lncRNAs involved in RABV infection is still elusive. In this study, we performed global transcriptome analysis of both of lncRNA and mRNA expression profiles in wild-type (WT) and lab-attenuated RABV-infected mouse brains by using next-generation sequencing. The differentially expressed lncRNAs and mRNAs were analysed by using the edgeR package. We identified 1422 differentially expressed lncRNAs and 4475 differentially expressed mRNAs by comparing WT and lab-attenuated RABV-infected brains. Then we predicted the enriched biological pathways by the Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) database based on the differentially expressed lncRNAs and mRNAs. Our analysis revealed the relationships between lncRNAs and RABV-infection-associated immune response and ion transport-related pathways, which provide a fresh insight into the potential role of lncRNA in immune evasion and neuron injury induced by WT RABV.

scholarly journals Integrated analysis of tobacco miRNA and mRNA expression profiles under PVY infection provids insight into tobacco-PVY interactions

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Yushuang Guo ◽  
Meng-ao Jia ◽  
Yumei Yang ◽  
Linlin Zhan ◽  
Xiaofei Cheng ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Insight Into

scholarly journals LncRNA and mRNA Expression Profiles in Methylprednisolone Stimulated Neural Stem Cells

2021 ◽  
Vol 15 ◽  
Author(s):  
Yong Tang ◽  
Zhongyu Xie ◽  
Mengjun Ma ◽  
Kaidi Duan ◽  
Yuxi Li ◽  
...  
Keyword(s):  
Stem Cells ◽  
Neural Stem Cells ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Akt Signaling Pathway ◽  
External Stimulation ◽  
Cord Injury ◽  
And Migration ◽  
Insight Into

Spinal cord injury (SCI) is a devastating neurological disorder that affects thousands of individuals each year. Previously, our study in non-human primates with SCI demonstrated that methylprednisolone (MP) resulted in the dysfunction of neural stem cells (NSCs), which may help to explain the controversial roles of MP in SCI. However, the detailed mechanism is still unclear. In this manuscript, we investigated the LncRNA and mRNA expression profiles of NSCs treated with MP. A total of 63 differentially expressed LncRNAs and 174 differentially expressed mRNAs were identified. Gene ontology (GO) analysis showed that differentially expressed mRNAs were highly associated with terms related to regulation of external stimulation, secretion, and migration. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results indicated that the PI3K–Akt signaling pathway contributed to the functions of MP treated NSCs. Besides, 3899 co-expression pairs were constructed among the differentially expressed LncRNA and mRNA, among which five predicted target mRNAs with the differentially expressed LncRNAs were identified. These results provide greater insight into the precise mechanisms of MP mediating NSC dysfunction in SCI.

Integrated analysis of non-coding RNA and mRNA expression profiles of 2 pig breeds differing in muscle traits

2017 ◽  
Vol 95 (3) ◽  
pp. 1092 ◽  
Author(s):  
J. Sun ◽  
M. Xie ◽  
Z. Huang ◽  
H. Li ◽  
T. chen ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Pig Breeds ◽  
Non Coding Rna
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