Transcriptome-wide identification of differentially expressed genes and long non-coding RNAs in nitroglycerin-tolerant rat aorta

It is commonly observed that patients with bone fracture concomitant with traumatic brain injury (TBI) had significantly increased fracture healing, but the underlying mechanisms were not fully revealed. Long non-coding RNAs (lncRNAs) are known to play complicated roles in bone homeostasis, but their role in TBI accelerated fracture was rarely reported. The present study was designed to determine the role of lncRNAs in TBI accelerated fracture via transcriptome sequencing and further bioinformatics analyses. Blood samples from three fracture-only patients, three fracture concomitant with TBI patients, and three healthy controls were harvested and were subsequently subjected to transcriptome lncRNA sequencing. Differentially expressed genes were identified, and pathway enrichment was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. High-dimensional data visualization by self-organizing map (SOM) machine learning was applied to further interpret the data. An xCell method was then used to predict cellular behavior in all samples based on gene expression profiles, and an lncRNA–cell interaction network was generated. A total of 874 differentially expressed genes were identified, of which about 26% were lncRNAs. Those identified lncRNAs were mainly enriched on TBI-related and damage repair-related pathways. SOM analyses revealed that those differentially expressed lncRNAs could be divided into three major module implications and were mainly enriched on transcriptional regulation and immune-related signal pathways, which promote us to further explore cellular behaviors based on differentially expressed lncRNAs. We have predicted that basophils, CD8+ T effector memory cells, B cells, and naïve B cells were significantly downregulated, while microvascular endothelial cells were predicted to be significantly upregulated in the Fr/TBI group, was the lowest and highest, respectively. ENSG00000278905, ENSG00000240980, ENSG00000255670, and ENSG00000196634 were the most differentially expressed lncRNAs related to all changes of cellular behavior. The present study has revealed for the first time that several critical lncRNAs may participate in TBI accelerated fracture potentially via regulating cellular behaviors of basophils, cytotoxic T cells, B cells, and endothelial cells.

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Comparative Transcriptome Analysis Provides Insights into Differentially Expressed Genes and Long Non-Coding RNAs between Ovary and Testis of the Mud Crab (Scylla paramamosain)

Marine Biotechnology ◽

10.1007/s10126-017-9784-2 ◽

2017 ◽

Vol 20 (1) ◽

pp. 20-34 ◽

Cited By ~ 18

Author(s):

Xiaolong Yang ◽

Mhd Ikhwanuddin ◽

Xincang Li ◽

Fan Lin ◽

Qingyang Wu ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Transcriptome Analysis ◽

Differentially Expressed ◽

Scylla Paramamosain ◽

Comparative Transcriptome ◽

Mud Crab ◽

Comparative Transcriptome Analysis ◽

Non Coding Rnas

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Co-expressed differentially expressed genes and long non-coding RNAs involved in the celecoxib treatment of gastric cancer: An RNA sequencing analysis

Experimental and Therapeutic Medicine ◽

10.3892/etm.2016.3648 ◽

2016 ◽

Vol 12 (4) ◽

pp. 2455-2468 ◽

Cited By ~ 5

Author(s):

Bin Song ◽

Juan Du ◽

Ye Feng ◽

Yong-Jian Gao ◽

Ji-Sheng Zhao

Keyword(s):

Gastric Cancer ◽

Rna Sequencing ◽

Differentially Expressed Genes ◽

Differentially Expressed ◽

Sequencing Analysis ◽

Non Coding Rnas

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

10.2196/preprints.33186 ◽

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.

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Transcriptome-Wide Identification of Differentially Expressed Genes and Long Non-coding RNAs in Aluminum-Treated Rat Hippocampus

Neurotoxicity Research ◽

10.1007/s12640-018-9879-1 ◽

2018 ◽

Vol 34 (2) ◽

pp. 220-232 ◽

Cited By ~ 2

Author(s):

Yirong Xu ◽

Huifang Zhang ◽

Baolong Pan ◽

Shuhui Zhang ◽

Shan Wang ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Rat Hippocampus ◽

Differentially Expressed ◽

Non Coding Rnas

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Coding and non-coding RNAs transcribed at the RORA locus (ROR𝛂) are differentially expressed in the whole blood of sepsis patients.

10.31219/osf.io/cdv8y ◽

2020 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Expression Analysis ◽

Whole Blood ◽

Gene Expression Analysis ◽

Differentially Expressed ◽

Blood Gene Expression ◽

Non Coding Rna ◽

Non Coding Rnas ◽

Long Non Coding Rna

Sepsis is a leading cause of mortality (1). We mined published datasets from the whole blood of patients with sepsis to identify differentially expressed genes in the septic state (2, 3). We found changes in RORA expression as among the most significant quantitative differences in sepsis whole blood gene expression. Analysis of a separate dataset (4) demonstrated significant repression of a long non-coding RNA produced at the RORA locus in the blood of patients with sepsis.

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