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      Neuropsychiatric Disease and Treatment (submit here)

      This international, peer-reviewed Open Access journal by Dove Medical Press focuses on all aspects of neuropsychiatric and neurological disorders. Sign up for email alerts here.

      63,741 Monthly downloads/views I 2.989 Impact Factor I 4.5 CiteScore I 1.09 Source Normalized Impact per Paper (SNIP) I 0.744 Scimago Journal & Country Rank (SJR)

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      Circular RNA circPHC3 Promotes Cell Death and Apoptosis in Human BMECs After Oxygen Glucose Deprivation via miR-455-5p/TRAF3 Axis in vitro

      research-article
      Author(s): 1 , 1 , 1 , 1
      Publication date (Electronic):
      Journal: Neuropsychiatric Disease and Treatment
      Publisher: Dove
      Keywords: ischemic stroke, circPHC3, TRAF3, miR-455-5p

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          Abstract

          Objective

          Brain microvascular endothelial cells (BMECs) are involved in brain vascular dysfunction in ischemic stroke. Abnormal expression of circular RNAs regulate physiological and pathophysiological processes in the central nervous system. The aim of the present study was to investigate profile circRNAs in human BMECs after oxygen glucose deprivation (OGD), which was an in vitro model of ischemic stroke, and find promising biomarkers in ischemic stroke.

          Methods

          RNA sequencing (RNA-seq) technology was conducted to analyze the differential expression of circRNAs between BMECs after OGD and non-OGD treated BMECs. RT-qPCR, cell proliferation, cell apoptosis and dual-luciferase assay, and so on, were used to investigate the functions and molecular mechanisms of hsa_circ_0001360 (named circPHC3 in this study) in ischemic stroke.

          Results

          CircPHC3 was highly expressed in human BMECs after OGD. Knockdown of circPHC3 inhibited cell death and apoptosis in human BMECs treated with OGD. Mechanistically, circPHC3 acted as miR-455-5p sponge to activate TRAF3 to promote cell death and apoptosis in human BMECs after OGD.

          Conclusion

          In short, circPHC3 promotes cell death and apoptosis in ischemic stroke in vitro model, which might be a novel molecular target for acute cerebrovascular protection.

          Most cited references28

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          STAR: ultrafast universal RNA-seq aligner.

          Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)
          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Fast gapped-read alignment with Bowtie 2.

            Ben Langmead, Steven L Salzberg (2022)
            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

              Bo Li, Colin Dewey (2011)
              Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Neuropsychiatr Dis Treat
                Journal ID (iso-abbrev): Neuropsychiatr Dis Treat
                Journal ID (publisher-id): ndt
                Journal ID (pmc): neurodist
                Title: Neuropsychiatric Disease and Treatment
                Publisher: Dove
                ISSN (Print): 1176-6328
                ISSN (Electronic): 1178-2021
                Publication date (Electronic): 22 January 2021
                Publication date Collection: 2021
                Volume: 17
                Pages: 147-156
                Affiliations
                [1 ]Department of Neurology, Peking University Shenzhen Hospital , Shenzhen 518000, Guangdong Province, People’s Republic of China
                Author notes
                Correspondence: Jun Wu Email junwu_2000@126.com
                Article
                Publisher ID: 288669
                DOI: 10.2147/NDT.S288669
                PMC ID: 7837587
                PubMed ID: 33519202
                SO-VID: b41e0ed6-5ae1-406f-b662-a825e5ededd7
                Copyright © © 2021 Xu et al.
                License:

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                Date received : 25 October 2020
                Date accepted : 29 December 2020
                Page count
                Figures: 4, Tables: 1, References: 28, Pages: 10
                Categories
                Subject: Original Research

                ScienceOpen disciplines: Neurology
                Keywords: ischemic stroke,circphc3,traf3,mir-455-5p
                Data availability:
                ScienceOpen disciplines: Neurology
                Keywords: ischemic stroke, circphc3, traf3, mir-455-5p

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