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      Transcriptome Analysis of Rat Lungs Exposed to Moxa Smoke after Acute Toxicity Testing

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          Abstract

          The increasing use of moxibustion has led to a debate concerning the safety of this treatment in human patients. Inhalation of cigarette smoke induces lung inflammation and granulomas, the proliferation of alveolar epithelial cells, and other toxic effects; therefore, it is important to assess the influence of inhaled moxa smoke on the lungs. In the present study, a novel poisoning cabinet was designed and used to assess the acute toxicity of moxa smoke in rats. We evaluated pathological changes in rat lung tissue and analyzed differentially expressed genes (DEGs) using RNA-seq and transcriptomic analyses. Our results show that the maximum tolerable dose of moxa smoke was 290.036 g/m³ and LC 50 was 537.65 g/m³. Compared with that of the control group, the degree of inflammatory cell infiltration in the lung tissues of group A rats (all dead group) was increased, while that in group E rats (all live group) remained unchanged. GO and KEGG enrichment analyses showed that the DEGs implicated in cell components, binding, and cancer were significantly enriched in the experimental groups compared with the profile of the control group. The expressions of MAFF, HSPA1B, HSPA1A, AOC1, and MX2 determined using quantitative real-time PCR were similar to those determined using RNA-seq, confirming the reliability of RNA-seq data. Overall, our results provide a basis for future evaluations of moxibustion safety and the development of moxibustion-based technology.

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          Most cited references47

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          TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

          TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
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            mRNA-Seq whole-transcriptome analysis of a single cell.

            Next-generation sequencing technology is a powerful tool for transcriptome analysis. However, under certain conditions, only a small amount of material is available, which requires more sensitive techniques that can preferably be used at the single-cell level. Here we describe a single-cell digital gene expression profiling assay. Using our mRNA-Seq assay with only a single mouse blastomere, we detected the expression of 75% (5,270) more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads. Moreover, 8-19% of the genes with multiple known transcript isoforms expressed at least two isoforms in the same blastomere or oocyte, which unambiguously demonstrated the complexity of the transcript variants at whole-genome scale in individual cells. Finally, for Dicer1(-/-) and Ago2(-/-) (Eif2c2(-/-)) oocytes, we found that 1,696 and 1,553 genes, respectively, were abnormally upregulated compared to wild-type controls, with 619 genes in common.
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              DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.

              High-throughput RNA sequencing (RNA-seq) is rapidly emerging as a major quantitative transcriptome profiling platform. Here, we present DEGseq, an R package to identify differentially expressed genes or isoforms for RNA-seq data from different samples. In this package, we integrated three existing methods, and introduced two novel methods based on MA-plot to detect and visualize gene expression difference. The R package and a quick-start vignette is available at http://bioinfo.au.tsinghua.edu.cn/software/degseq
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                Author and article information

                Contributors
                Journal
                Evid Based Complement Alternat Med
                Evid Based Complement Alternat Med
                ECAM
                Evidence-based Complementary and Alternative Medicine : eCAM
                Hindawi
                1741-427X
                1741-4288
                2021
                18 December 2021
                18 December 2021
                : 2021
                : 5107441
                Affiliations
                1Jiangxi Province Key Laboratory of TCM Etiopathogenesis, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi 330004, China
                2Research Center for Differentiation and Development of TCM Basic Theory, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi 330004, China
                Author notes

                Academic Editor: Swee Keong Yeap

                Author information
                https://orcid.org/0000-0001-5254-6505
                https://orcid.org/0000-0002-6190-704X
                https://orcid.org/0000-0002-5871-6971
                Article
                10.1155/2021/5107441
                8710166
                34961819
                d142b8ea-1856-47d8-9389-35fcf3072f06
                Copyright © 2021 Xiaoyu Xu et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 October 2021
                : 30 November 2021
                Funding
                Funded by: Jiangxi National Traditional Medicine Modern Technology And Industrial Development Collaborative Innovation Center Gan Gao Zi [2013]
                Award ID: 109
                Categories
                Research Article

                Complementary & Alternative medicine
                Complementary & Alternative medicine

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