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

We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1α heterozygous and two Ire1α-null samples. The 26nt 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 Ire1α knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, 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. Identification of non-canonical spliced regions for mouse MEF samples (two Ire1α heterozygous and two Ire1α-null samples)

本研究开发了一种名为读段拆分游走（Read-Split-Walk, RSW）的生物信息学分析流程，并采用2份Ire1α杂合样本与2份Ire1α纯合敲除样本对该流程进行了性能评估。在杂合样本中，本研究的RSW流程可将Xbp1基因中26nt的非经典剪接位点鉴定为最高置信度命中结果，而在阴性对照的Ire1α敲除样本中则未检测到该位点。本研究将本流程得到的Xbp1分析结果，与采用比对工具BWA、STAR、Exonerate以及Unix系统"grep"命令得到的结果进行了对比。随后，本研究将RSW流程应用于人乳腺癌细胞系SKBR3的RNA测序（RNA-Seq）数据。RSW流程在17号染色体的108个基因中鉴定出大量非经典剪接区域，这些区域已被一项独立研究证实。针对小鼠胚胎成纤维细胞（MEF）样本（2份Ire1α杂合样本与2份Ire1α纯合敲除样本）的非经典剪接区域鉴定工作