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      Transcriptome profiling of long noncoding RNAs and mRNAs in spinal cord of a rat model of paclitaxel-induced peripheral neuropathy identifies potential mechanisms mediating neuroinflammation and pain

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          Abstract

          Background

          Paclitaxel is a widely prescribed chemotherapy drug for treating solid tumors. However, paclitaxel-induced peripheral neuropathy (PIPN) is a common adverse effect during paclitaxel treatment, which results in sensory abnormalities and neuropathic pain among patients. Unfortunately, the mechanisms underlying PIPN still remain poorly understood. Long noncoding RNAs (lncRNAs) are novel and promising targets for chronic pain treatment, but their involvement in PIPN still remains unexplored.

          Methods

          We established a rat PIPN model by repetitive paclitaxel application. Immunostaining, RNA sequencing (RNA-Seq) and bioinformatics analysis were performed to study glia cell activation and explore lncRNA/mRNA expression profiles in spinal cord dorsal horn (SCDH) of PIPN model rats. qPCR and protein assay were used for further validation.

          Results

          PIPN model rats developed long-lasting mechanical and thermal pain hypersensitivities in hind paws, accompanied with astrocyte and microglia activation in SCDH. RNA-Seq identified a total of 814 differentially expressed mRNAs (DEmRNA) (including 467 upregulated and 347 downregulated) and 412 DElncRNAs (including 145 upregulated and 267 downregulated) in SCDH of PIPN model rats vs. control rats. Functional analysis of DEmRNAs and DElncRNAs identified that the most significantly enriched pathways include immune/inflammatory responses and neurotrophin signaling pathways, which are all important mechanisms mediating neuroinflammation, central sensitization, and chronic pain. We further compared our dataset with other published datasets of neuropathic pain and identified a core set of immune response-related genes extensively involved in PIPN and other neuropathic pain conditions. Lastly, a competing RNA network analysis of DElncRNAs and DEmRNAs was performed to identify potential regulatory networks of lncRNAs on mRNA through miRNA sponging.

          Conclusions

          Our study provided the transcriptome profiling of DElncRNAs and DEmRNAs and uncovered immune and inflammatory responses were predominant biological events in SCDH of the rat PIPN model. Thus, our study may help to identify promising genes or signaling pathways for PIPN therapeutics.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12974-021-02098-y.

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          Most cited references75

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              Fast gapped-read alignment with Bowtie 2.

              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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                Author and article information

                Contributors
                yuanyuanlizy@163.com
                1163566590@qq.com
                lby_0731@163.com
                15237832605@163.com
                wangjie121@hotmail.com
                2572875759@qq.com
                837324951@qq.com
                zjhxf1986@163.com
                fangjunfan0223@163.com
                635747467@qq.com
                liangyiwww@126.com
                jyl2182@163.com
                fangjianqiao7532@163.com
                boyi.liu@foxmail.com
                Journal
                J Neuroinflammation
                J Neuroinflammation
                Journal of Neuroinflammation
                BioMed Central (London )
                1742-2094
                18 February 2021
                18 February 2021
                2021
                : 18
                : 48
                Affiliations
                GRID grid.268505.c, ISNI 0000 0000 8744 8924, Department of Neurobiology and Acupuncture Research, The Third Clinical Medical College, , Zhejiang Chinese Medical University, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, ; 548 Binwen Road, Hangzhou, 310053 China
                Author information
                http://orcid.org/0000-0001-9870-4548
                Article
                2098
                10.1186/s12974-021-02098-y
                7890637
                33602238
                fb99c179-d88a-42b4-9588-8eee441daa3c
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 23 September 2020
                : 2 February 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81873365
                Award ID: 81603676
                Award Recipient :
                Funded by: Zhejiang Provincial Natural Science Funds for Distinguished Young Scholars
                Award ID: LR17H270001
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Neurosciences
                rna-seq,lncrna,paclitaxel,neuropathic pain,inflammation
                Neurosciences
                rna-seq, lncrna, paclitaxel, neuropathic pain, inflammation

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