Unraveling the Expression Profiles of Long Noncoding RNAs in Rat Cardiac Hypertrophy and Functions of lncRNA BC088254 in Cardiac Hypertrophy Induced by Transverse Aortic Constriction

Cardiology ◽  
2016 ◽  
Vol 134 (2) ◽  
pp. 84-98 ◽  
Author(s):  
Xiaoying Li ◽  
Lei Zhang ◽  
Jiangjiu Liang
Keyword(s):  
Cardiac Hypertrophy ◽  
Myocardial Hypertrophy ◽  
Heart Diseases ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Transverse Aortic Constriction ◽  
Rt Pcr ◽  
Aortic Constriction

Long noncoding RNAs (lncRNAs), although initially considered as genomic transcription noise, have been demonstrated to play pivotal roles in multiple biological processes and are increasingly recognized as contributors to the pathology of cancer, neurodegenerative diseases, diabetes, heart diseases, and inflammation. However, studies on the roles of lncRNAs in angiocardiopathy, particularly in cardiac hypertrophy, are still preliminary. In our study, differentially expressed lncRNAs in rat cardiac hypertrophy induced by transverse aortic constriction (TAC) were identified by microarray analysis and validated using quantitative real-time polymerase chain reaction (RT-PCR). Briefly, we identified 6,969 lncRNAs, among which 80 lncRNAs were significantly upregulated and 172 lncRNAs were significantly downregulated. Quantitative RT-PCR was used to validate the differential expression of 5 lncRNAs in myocardial tissue RNA. Further, pathway analysis indicated that 25 pathways corresponded to upregulated transcripts and 20 pathways corresponded to downregulated transcripts. Third, by coexpression network analysis, we found a correlation between BC088254 and phb2 (prohibitin 2) and verified this expression by RT-PCR and Western blot. This is the first study to reveal differentially expressed lncRNAs in rat cardiac hypertrophy induced by TAC, indicating potential lncRNA mechanisms of action in myocardial hypertrophy. We also found that lncRNA BC088254 may have a certain role in myocardial hypertrophy induced by TAC and functional relevance between lncRNA BCO88254 and phb2, but the relationship between these two factors is unclear.

scholarly journals Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Liang Guo ◽  
Kai Xu ◽  
Hongbo Yan ◽  
Haifeng Feng ◽  
Linlin Chai ◽  
...  
Keyword(s):  
Microarray Analysis ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Diagnostic Biomarkers ◽  
Pathway Enrichment ◽  
Normal Tissues ◽  
Wide Range ◽  
Skin Scar

Background. Long noncoding RNAs (lncRNAs) play key roles in a wide range of biological processes and their deregulation results in human disease, including keloids. Earlobe keloid is a type of pathological skin scar, and the molecular pathogenesis of this disease remains largely unknown. Methods. In this study, microarray analysis was used to determine the expression profiles of lncRNAs and mRNAs between 3 pairs of earlobe keloid and normal specimens. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify the main functions of the differentially expressed genes and earlobe keloid-related pathways. Results. A total of 2068 lncRNAs and 1511 mRNAs were differentially expressed between earlobe keloid and normal tissues. Among them, 1290 lncRNAs and 1092 mRNAs were upregulated, and 778 lncRNAs and 419 mRNAs were downregulated. Pathway analysis revealed that 24 pathways were correlated to the upregulated transcripts, while 11 pathways were associated with the downregulated transcripts. Conclusion. We characterized the expression profiles of lncRNA and mRNA in earlobe keloids and suggest that lncRNAs may serve as diagnostic biomarkers for the therapy of earlobe keloid.

scholarly journals Characterization and validation of long noncoding RNAs as new candidates in prostate cancer

2020 ◽  
Author(s):  
Shengyang Ge ◽  
Yuanyuan Mi ◽  
Xiaojun Zhao ◽  
Qingfeng Hu ◽  
Yijun Guo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Expression Profiles ◽  
Survival Curve ◽  
Noncoding Rnas ◽  
Hazard Ratio ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
High Hazard Ratio ◽  
High Hazard

Abstract Background: Long noncoding RNAs (lncRNAs) have been proved to be an important regulator in gene expression. In almost all kinds of cancers, lncRNAs participated in the process of pathogenesis, invasion, and metastasis. Meanwhile, compared with the large amounts of patients, there is rare knowledge about the role of lncRNAs in prostate cancer (PCa). Material/Method: In this study, lncRNA expression profiles of prostate cancer were detected by Agilent microarray chip, 5 pairs of case and control specimens were involved in. Differentially expressed lncRNAs were screened out by volcano plot for constructing lncRNA-miRNA-mRNA central network. Then, the top ten up-regulated and down-regulated lncRNAs were validated by qRT-PCR in another 5 tumor specimens and 7 para-cancerous/benign contrasts. Furthermore, we searched for the survival curve of the top 10 upregulated and downregulated lncRNAs. Results: A total of 817 differentially expressed lncRNAs were filtered out by the criteria of fold change (FC) and t-test p < 0.05. Among them, 422 were upregulated, whereas 395 were downregulated in PCa tissues. Gene ontology and KEGG pathway analyses showed that many lncRNAs were implicated in carcinogenesis. lnc-MYL2-4:1 (FC = 0.00141, p = 0.01909) and NR_125857 (FC = 59.27658, p = 0.00128) had the highest magnitude of change. The subsequent qPCR confirmed the expression of NR_125857 was in accordance with the clinical samples. High expression of PCA3, PCAT14 and AP001610.9 led to high hazard ratio while low expression of RP11-279F6.2 led to high hazard ratio. Conclusions: Our study detected a relatively novel complicated map of lncRNAs in PCa, which may have the potential to investigate for diagnosis, treatment and follow-up in PCa. Our study revealed the expression of NR_125857 in human PCa tissues was most up-regulated. Further studies are needed to investigate to figure out the mechanisms in PCa.

scholarly journals Long Noncoding RNAs and Messenger RNAs Expression Profiles Potentially Regulated by ZBTB7A in Nasopharyngeal Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Fei Liu ◽  
Jiazhang Wei ◽  
Yanrong Hao ◽  
Fengzhu Tang ◽  
Wei Jiao ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Fatty Acid Synthase ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Messenger Rnas ◽  
Regulatory Pathways ◽  
Different Levels

Our previous studies showed that ZBTB7A played an important role in promoting nasopharyngeal carcinoma (NPC) progression. However, molecular mechanisms of different levels of ZBTB7A are still unclear. It is necessary to search molecular markers which are closely connected with ZBTB7A. We selected NPC sublines CNE2 with stably transfecting empty plasmid (negative control, NC) and short hair RNA (shRNA) plasmid targeting ZBTB7A as research objectives. Microarray was used to screen differentially expressed long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) via shRNA-CNE2 versus NC-CNE2. Quantitative PCR (qPCR) was used to validate lncRNAs and mRNAs from the sublines, chronic rhinitis, and NPC tissues. Bioinformatics was used to analyze regulatory pathways which were connected with ZBTB7A. The 1501 lncRNAs (long noncoding RNAs) and 1275 differentially expressed mRNAs were upregulated or downregulated over 2-fold. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the upregulated or downregulated carbohydrate and lipid metabolisms probably involved in carcinogenicity of shRNA-CNE2 (P-value cut-off was 0.05). In order to find the molecular mechanisms of ZBTB7A, we validated 12 differentially expressed lncRNAs and their nearby mRNAs by qPCR. Most of the differentially expressed mRNAs are closely connected with carbohydrate and lipid metabolisms in multiply cancers. Furthermore, part of them were validated in NPC and rhinitis tissues by qPCR. As a result, NR_047538, ENST00000442852, and fatty acid synthase (FASN) were closely associated with NPC. ZBTB7A had a positive association with NR_047538 and negative associations with ENST00000442852 and FASN. The results probably provide novel candidate biomarkers for NPC progression with different levels of ZBTB7A.

scholarly journals Characterization and validation of long noncoding RNAs as new candidates in prostate cancer

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Shengyang Ge ◽  
Yuanyuan Mi ◽  
Xiaojun Zhao ◽  
Qingfeng Hu ◽  
Yijun Guo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Expression Profiles ◽  
Survival Curve ◽  
Noncoding Rnas ◽  
Hazard Ratio ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
High Hazard Ratio ◽  
High Hazard

Abstract Background Long noncoding RNAs (lncRNAs) have been proved to be an important regulator in gene expression. In almost all kinds of cancers, lncRNAs participated in the process of pathogenesis, invasion, and metastasis. Meanwhile, compared with the large amounts of patients, there is rare knowledge about the role of lncRNAs in prostate cancer (PCa). Material/Method In this study, lncRNA expression profiles of prostate cancer were detected by Agilent microarray chip, 5 pairs of case and control specimens were involved in. Differentially expressed lncRNAs were screened out by volcano plot for constructing lncRNA-miRNA-mRNA central network. Then, the top ten up-regulated and down-regulated lncRNAs were validated by qRT-PCR in another 5 tumor specimens and 7 para-cancerous/benign contrasts. Furthermore, we searched for the survival curve of the top 10 upregulated and downregulated lncRNAs. Results A total of 817 differentially expressed lncRNAs were filtered out by the criteria of fold change (FC) and t-test p < 0.05. Among them, 422 were upregulated, whereas 395 were downregulated in PCa tissues. Gene ontology and KEGG pathway analyses showed that many lncRNAs were implicated in carcinogenesis. lnc-MYL2-4:1 (FC = 0.00141, p = 0.01909) and NR_125857 (FC = 59.27658, p = 0.00128) had the highest magnitude of change. The subsequent qPCR confirmed the expression of NR_125857 was in accordance with the clinical samples. High expression of PCA3, PCAT14 and AP001610.9 led to high hazard ratio while low expression of RP11-279F6.2 led to high hazard ratio. Conclusions Our study detected a relatively novel complicated map of lncRNAs in PCa, which may have the potential to investigate for diagnosis, treatment and follow-up in PCa. Our study revealed the expression of NR_125857 in human PCa tissues was most up-regulated. Further studies are needed to investigate to figure out the mechanisms in PCa.

scholarly journals A Novel Analysis of the Differentiated Expression of Long Noncoding RNAs Profiles in Human Prostate Cancer

2020 ◽  
Author(s):  
Chuanyu Sun ◽  
Shengyang Ge ◽  
Yuanyuan Mi ◽  
Qingfeng Hu ◽  
Yijun Guo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Biology ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
Clinical Value ◽  
Pathway Analyses ◽  
Almost All

Abstract Background: Long noncoding RNAs (lncRNAs) have crucial roles in cancer biology. Increasing numbers of evidences have indicated that lncRNAs play an important role in the pathogenesis, invasion, and metastasis in almost all kinds of cancers. But, compared with the large amounts of patients, there is rare reports that showed the differential expression of lncRNAs in prostate cancer. Methods: In this study, lncRNA expression profiles were screened in PCa, by using 5 pairs of clinical specimens in PCa and matched non-PCa tissues with lncRNA chip. To affirm further clinical value, we extended the samples consisting of another 5 tumor specimens and 7 para-cancerous/benign contrasts by qRT-PCR in top 10 up-regulated and down-regulated lncRNAs. Results: A total of 817 lncRNAs were differentially expressed between PCa tumor and para-cancerous tissues (Fold Change ≥2.0, p < 0.05): 422 were upregulated, whereas 395 were downregulated in PCa tissues. Gene ontology and KEGG pathway analyses showed that many lncRNAs were implicated in carcinogenesis. Among differentially expressed lncRNAs, lnc-MYL2-4:1 (FC = 0.00141, p = 0.01909) and NR_125857 (FC = 59.27658, p = 0.00128) had the highest magnitude of change. The subsequent qPCR confirmed the expression of NR_125857 accorded with the clinical samples.Conclusions: Our study detected a relatively novel complicated map of lncRNAs in PCa, which may have the potential to investigate for diagnosis, treatment and follow-up in PCa. Our study revealed the expression of NR_125857 in human PCa tissues was most up-regulated. Further study of these meaningful candidates are need to research deep mechanisms.

Microarray analysis of gene expression after transverse aortic constriction in mice

2004 ◽  
Vol 19 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Mingming Zhao ◽  
Amy Chow ◽  
Jennifer Powers ◽  
Giovanni Fajardo ◽  
Daniel Bernstein
Keyword(s):  
Gene Expression ◽  
Statistical Analysis ◽  
Cardiac Hypertrophy ◽  
Heart Function ◽  
Expression Profiles ◽  
Alternative Methods ◽  
Transverse Aortic Constriction ◽  
Aortic Constriction ◽  
Altered Expression ◽  
Qrt Pcr

Cardiac hypertrophy is a compensatory response initially beneficial to heart function but can ultimately lead to cardiac decompensation. It is an integrated process involving multiple cellular signaling pathways and their cross talk. Microarray GeneChip technology is a powerful new tool to identify gene expression profiles of cardiac hypertrophy. To identify well-characterized as well as novel adaptive mechanisms, we utilized a murine model of compensated pressure overload hypertrophy (transverse aortic constriction, TAC). At 48 h, 10 days, and 3 wk, hearts were harvested and total RNA hybridized to Affymetrix U74Av2 GeneChips, which contain a 12,488-gene/EST probe set. Verification of gene expression was performed by SYBR quantitative real-time RT-PCR (QRT-PCR) for selected genes. A rigorous evaluation of the adequacy of the control condition was also performed. For statistical analysis we generated a four-step filtering criteria. Our results show an upregulation of 38 genes (48 h), 269 genes (10 days), and 203 genes (3 wk) and downregulation of 15 genes (48 h), 160 genes (10 days), and 124 genes (3 wk). Transcripts differentially expressed after TAC were categorized into 12 functional groups and revealed the presence of several intriguing transcripts, e.g., cell proliferation-related Ki-67 and several apoptosis-related genes. Overall changes in QRT-PCR were in accordance with GeneChip data, with the highest correlation for genes with the largest up- or downregulation with TAC. Thus TAC results in altered expression of genes in several pathways regulating both cardiac structure and function. However, for in vivo gene microarray experiments, it is critical to define adequate controls, perform rigorous statistical analysis, and provide validation by alternative methods.

scholarly journals A novel analysis of the differentiated expression of long noncoding RNAs profiles in human prostate cancer

2020 ◽  
Author(s):  
Shengyang Ge ◽  
Yuanyuan Mi ◽  
Xiaojun Zhao ◽  
Qingfeng Hu ◽  
Yijun Guo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Expression Profiles ◽  
Survival Curve ◽  
Noncoding Rnas ◽  
Hazard Ratio ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
High Hazard Ratio ◽  
High Hazard

Abstract Background: Long noncoding RNAs (lncRNAs) have been proved to be an important regulator in gene expression. In almost all kinds of cancers, lncRNAs participated in the process of pathogenesis, invasion, and metastasis. Meanwhile, compared with the large amounts of patients, there is rare knowledge about the role of lncRNAs in prostate cancer (PCa).Material/Method: In this study, lncRNA expression profiles of prostate cancer were detected by Agilent microarray chip, 5 pairs of case and control specimens were involved in. Differentially expressed lncRNAs were screened out by volcano plot for constructing lncRNA-miRNA-mRNA central network. Then, the top ten up-regulated and down-regulated lncRNAs were validated by qRT-PCR in another 5 tumor specimens and 7 para-cancerous/benign contrasts. Furthermore, we searched for the survival curve of the top 10 upregulated and downregulated lncRNAs.Results: A total of 817 differentially expressed lncRNAs were filtered out by the criteria of fold change (FC) and t-test p < 0.05. Among them, 422 were upregulated, whereas 395 were downregulated in PCa tissues. Gene ontology and KEGG pathway analyses showed that many lncRNAs were implicated in carcinogenesis. lnc-MYL2-4:1 (FC = 0.00141, p = 0.01909) and NR_125857 (FC = 59.27658, p = 0.00128) had the highest magnitude of change. The subsequent qPCR confirmed the expression of NR_125857 was in accordance with the clinical samples. High expression of PCA3, PCAT14 and AP001610.9 led to high hazard ratio while low expression of RP11-279F6.2 led to high hazard ratio.Conclusions: Our study detected a relatively novel complicated map of lncRNAs in PCa, which may have the potential to investigate for diagnosis, treatment and follow-up in PCa. Our study revealed the expression of NR_125857 in human PCa tissues was most up-regulated. Further studies are needed to investigate to figure out the mechanisms in PCa.

Differential Expression of Long Noncoding RNAs and Their Function-Related mRNAs in the Peripheral Blood of Allergic Rhinitis Patients

2020 ◽  
Vol 34 (4) ◽  
pp. 508-518
Author(s):  
Yanyan Yang ◽  
Yu Zhang ◽  
Yujuan Yang ◽  
Jing Guo ◽  
Liping Yang ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Transcription Factor ◽  
Peripheral Blood ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Pcr Analysis ◽  
Qrt Pcr ◽  
Control Subjects

Background The mechanism of long noncoding RNAs (lncRNAs) involved in the development of allergic rhinitis (AR) remains unclear. Objective We investigated the mechanism by which differentially expressed lncRNAs contribute to pathogenesis of AR. Methods Expression profiles of lncRNAs and mRNAs were analyzed by microarray detection from the blood samples of 3 AR patients and 3 control subjects, and the main lncRNAs were verified by quantitative real-time polymerase chain reaction (qRT-PCR) in the peripheral blood of 16 AR patients and 18 control subjects. GO (Gene_Ontology), Pathway, and Disease analysis of differentially expressed lncRNAs and mRNAs, and transcription factor prediction analysis were performed to explore synergistic effect of differentially expressed lncRNAs and their function-related mRNAs on AR pathogenesis. Results Thirty-one lncRNAs were differentially expressed in the peripheral blood from AR patients, and 4 of the 5 most differentially expressed lncRNAs had significantly higher levels in AR patients than in control subjects by qRT-PCR analysis. A lncRNA-mRNA coexpression network analysis identified 16 pairs of positive correlations between the 4 lncRNAs and coexpressed mRNAs. GO, Pathway, and Disease analyses indicated that the 4 lncRNAs were correlated with 7 mRNAs enriched in terms of inflammation, immune response, and allergic diseases. Transcription factor prediction results suggested that Oct-1, AP-1, NF-kappaB, and c-Rel play key roles in the pathogenesis of AR mediated by lncRNAs. Conclusion Our results provide new insights into how lncRNAs and their function-related mRNAs might contribute to AR.

scholarly journals Genome-Wide Identification and Characterization of Long Noncoding RNAs Involved in Chinese Wheat Mosaic Virus Infection of Nicotiana benthamiana

Biology ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 232
Author(s):  
Weiran Zheng ◽  
Haichao Hu ◽  
Qisen Lu ◽  
Peng Jin ◽  
Linna Cai ◽  
...  
Keyword(s):  
Virus Infection ◽  
Mosaic Virus ◽  
Nicotiana Benthamiana ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Genome Wide ◽  
Chinese Wheat

Recent studies have shown that a large number of long noncoding RNAs (lncRNAs) can regulate various biological processes in animals and plants. Although lncRNAs have been identified in many plants, they have not been reported in the model plant Nicotiana benthamiana. Particularly, the role of lncRNAs in plant virus infection remains unknown. In this study, we identified lncRNAs in N. benthamiana response to Chinese wheat mosaic virus (CWMV) infection by RNA sequencing. A total of 1175 lncRNAs, including 65 differentially expressed lncRNAs, were identified during CWMV infection. We then analyzed the functions of some of these differentially expressed lncRNAs. Interestingly, one differentially expressed lncRNA, XLOC_006393, was found to participate in CWMV infection as a precursor to microRNAs in N. benthamiana. These results suggest that lncRNAs play an important role in the regulatory network of N. benthamiana in response to CWMV infection.

scholarly journals Identification of the specific long-noncoding RNAs involved in night-break mediated flowering retardation in Chenopodium quinoa

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Qi Wu ◽  
Yiming Luo ◽  
Xiaoyong Wu ◽  
Xue Bai ◽  
Xueling Ye ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Functional Characterization ◽  
Chenopodium Quinoa ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Rna Seq ◽  
Short Day ◽  
Homologous Genes ◽  
The Relationship ◽  
Encoding Genes

Abstract Background Night-break (NB) has been proven to repress flowering of short-day plants (SDPs). Long-noncoding RNAs (lncRNAs) play key roles in plant flowering. However, investigation of the relationship between lncRNAs and NB responses is still limited, especially in Chenopodium quinoa, an important short-day coarse cereal. Results In this study, we performed strand-specific RNA-seq of leaf samples collected from quinoa seedlings treated by SD and NB. A total of 4914 high-confidence lncRNAs were identified, out of which 91 lncRNAs showed specific responses to SD and NB. Based on the expression profiles, we identified 17 positive- and 7 negative-flowering lncRNAs. Co-expression network analysis indicated that 1653 mRNAs were the common targets of both types of flowering lncRNAs. By mapping these targets to the known flowering pathways in model plants, we found some pivotal flowering homologs, including 2 florigen encoding genes (FT (FLOWERING LOCUS T) and TSF (TWIN SISTER of FT) homologs), 3 circadian clock related genes (EARLY FLOWERING 3 (ELF3), LATE ELONGATED HYPOCOTYL (LHY) and ELONGATED HYPOCOTYL 5 (HY5) homologs), 2 photoreceptor genes (PHYTOCHROME A (PHYA) and CRYPTOCHROME1 (CRY1) homologs), 1 B-BOX type CONSTANS (CO) homolog and 1 RELATED TO ABI3/VP1 (RAV1) homolog, were specifically affected by NB and competed by the positive and negative-flowering lncRNAs. We speculated that these potential flowering lncRNAs may mediate quinoa NB responses by modifying the expression of the floral homologous genes. Conclusions Together, the findings in this study will deepen our understanding of the roles of lncRNAs in NB responses, and provide valuable information for functional characterization in future.

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