4 research outputs found

    Additional file 5: of Read-Split-Run: an improved bioinformatics pipeline for identification of genome-wide non-canonical spliced regions using RNA-Seq data

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    Total number of spliced regions identified by RSR in the human ENCODE RNA-Seq dataset. This file includes all supplementary results for number of supporting reads, splice length, range of supporting reads (spliced regions) identified by RSR in the human ENCODE RNA-Seq dataset. (XLSX 1411 kb

    Epimedium sempervirens Nakai

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    原著和名: トキハイカリサウ科名: メギ科 = Berberidaceae採集地: 島根県 隠岐 島後 (隠岐 島後)採集日: 1976/5/9採集者: 萩庭丈壽整理番号: JH002351国立科学博物館整理番号: TNS-VS-95235

    Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data

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    <div><p>Setting</p><p>During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) <i>Ire1</i>α initiates removal of a 26 nt region from the mRNA encoding the transcription factor <i>Xbp1</i> via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported.</p><p>Objective</p><p>Our goal was to develop an approach to identify non-canonical, possibly very short, splicing regions using RNA-Seq data and apply it to ER stress-induced <i>Ire1</i>α heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional <i>Ire1</i>α targets.</p><p>Results</p><p>We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two <i>Ire1</i>α heterozygous and two <i>Ire1</i>α-null samples. The 26 nt non-canonical splice site in <i>Xbp1</i> was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control <i>Ire1</i>α knockout samples. We compared the <i>Xbp1</i> results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix “<i>grep</i>” command. We then applied our RSW pipeline to RNA-Seq data from the SKBR3 human breast cancer cell line. RSW reported a large number of non-canonical spliced regions for 108 genes in chromosome 17, which were identified by an independent study.</p><p>Conclusions</p><p>We conclude that our RSW pipeline is a practical approach for identifying non-canonical splice junction sites on a genome-wide level. We demonstrate that our pipeline can detect novel splice sites in RNA-Seq data generated under similar conditions for multiple species, in our case mouse and human.</p></div
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