Dataset Information

Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

ABSTRACT: SETTING:During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1? initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 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. OBJECTIVE: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 Ire1? heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional Ire1? targets. RESULTS:We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1? heterozygous and two Ire1?-null samples. The 26 nt non-canonical splice site in Xbp1 was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control Ire1? knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix "grep" 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. CONCLUSIONS: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.

SUBMITTER: Bai Y

PROVIDER: S-EPMC4084626 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

Bai Yongsheng Y Hassler Justin J Ziyar Ahdad A Li Philip P Wright Zachary Z Menon Rajasree R Omenn Gilbert S GS Cavalcoli James D JD Kaufman Randal J RJ Sartor Maureen A MA

PloS one 20140703 7

<h4>Setting</h4>During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 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 splicin ...[more]

PMID: 24991935

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Project description:Most existing tools for detecting next-generation sequencing-based splicing events focus on generic splicing events. Consequently, special types of non-canonical splicing events of short mRNA regions (IRE1? targeted) have not yet been thoroughly addressed at a genome-wide level using bioinformatics approaches in conjunction with next-generation technologies. During endoplasmic reticulum (ER) stress, the gene encoding the RNase Ire1? is known to splice out a short 26 nt region from the mRNA of the transcription factor Xbp1 non-canonically within the cytosol. This causes an open reading frame-shift that induces expression of many downstream genes in reaction to ER stress as part of the unfolded protein response (UPR). We previously published an algorithm termed "Read-Split-Walk" (RSW) to identify non-canonical splicing regions using RNA-Seq data and applied it to ER stress-induced Ire1? heterozygote and knockout mouse embryonic fibroblast cell lines. In this study, we have developed an improved algorithm "Read-Split-Run" (RSR) for detecting genome-wide Ire1?-targeted genes with non-canonical spliced regions at a faster speed. We applied the RSR algorithm using different combinations of several parameters to the previously RSW tested mouse embryonic fibroblast cells (MEF) and the human Encyclopedia of DNA Elements (ENCODE) RNA-Seq data. We also compared the performance of RSR with two other alternative splicing events identification tools (TopHat (Trapnell et al., Bioinformatics 25:1105-1111, 2009) and Alt Event Finder (Zhou et al., BMC Genomics 13:S10, 2012)) utilizing the context of the spliced Xbp1 mRNA as a positive control in the data sets we identified it to be the top cleavage target present in Ire1? (+/-) but absent in Ire1? (-/-) MEF samples and this comparison was also extended to human ENCODE RNA-Seq data.Proof of principle came in our results by the fact that the 26 nt non-conventional splice site in Xbp1 was detected as the top hit by our new RSR algorithm in heterozygote (Het) samples from both Thapsigargin (Tg) and Dithiothreitol (Dtt) treated experiments but absent in the negative control Ire1? knock-out (KO) samples. Applying different combinations of parameters to the mouse MEF RNA-Seq data, we suggest a General Linear Model (GLM) for both Tg and Dtt treated experiments. We also ran RSR for a human ENCODE RNA-Seq dataset and identified 32,597 spliced regions for regular chromosomes. TopHat (Trapnell et al., Bioinformatics 25:1105-1111, 2009) and Alt Event Finder (Zhou et al., BMC Genomics 13:S10, 2012) identified 237,155 spliced junctions and 9,129 exon skipping events (excluding chr14), respectively. Our Read-Split-Run algorithm also outperformed others in the context of ranking Xbp1 gene as the top cleavage target present in Ire1? (+/-) but absent in Ire1? (-/-) MEF samples. The RSR package including source codes is available at http://bioinf1.indstate.edu/RSR and its pipeline source codes are also freely available at https://github.com/xuric/read-split-run for academic use.Our new RSR algorithm has the capability of processing massive amounts of human ENCODE RNA-Seq data for identifying novel splice junction sites at a genome-wide level in a much more efficient manner when compared to the previous RSW algorithm. Our proposed model can also predict the number of spliced regions under any combinations of parameters. Our pipeline can detect novel spliced sites for other species using RNA-Seq data generated under similar conditions.

Project description:BackgroundIt is generally thought that most canonical or non-canonical splicing events involving U2- and U12 spliceosomes occur within nuclear pre-mRNAs. However, the question of whether at least some U12-type splicing occurs in the cytoplasm is still unclear. In recent years next-generation sequencing technologies have revolutionized the field. The "Read-Split-Walk" (RSW) and "Read-Split-Run" (RSR) methods were developed to identify genome-wide non-canonical spliced regions including special events occurring in cytoplasm. As the significant amount of genome/transcriptome data such as, Encyclopedia of DNA Elements (ENCODE) project, have been generated, we have advanced a newer more memory-efficient version of the algorithm, "Read-Split-Fly" (RSF), which can detect non-canonical spliced regions with higher sensitivity and improved speed. The RSF algorithm also outputs the spliced sequences for further downstream biological function analysis.ResultsWe used open access ENCODE project RNA-Seq data to search spliced intron sequences against the U12-type spliced intron sequence database to examine whether some events could occur as potential signatures of U12-type splicing. The check was performed by searching spliced sequences against 5'ss and 3'ss sequences from the well-known orthologous U12-type spliceosomal intron database U12DB. Preliminary results of searching 70 ENCODE samples indicated that the presence of 5'ss with U12-type signature is more frequent than U2-type and prevalent in non-canonical junctions reported by RSF. The selected spliced sequences have also been further studied using miRBase to elucidate their functionality. Preliminary results from 70 samples of ENCODE datasets show that several miRNAs are prevalent in studied ENCODE samples. Two of these are associated with many diseases as suggested in the literature. Specifically, hsa-miR-1273 and hsa-miR-548 are associated with many diseases and cancers.ConclusionsOur RSF pipeline is able to detect many possible junctions (especially those with a high RPKM) with very high overall accuracy and relative high accuracy for novel junctions. We have incorporated useful parameter features into the pipeline such as, handling variable-length read data, and searching spliced sequences for splicing signatures and miRNA events. We suggest RSF, a tool for identifying novel splicing events, is applicable to study a range of diseases across biological systems under different experimental conditions.

Dataset Information

Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

Publications

Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

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