Soreq Lilach, Guffanti Alessandro, Salomonis Nathan, Simchovitz Alon, Israel Zvi, Bergman Hagai, Soreq Hermona
Department of Medical Neurobiology, IMRIC, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Department of Biological Chemistry, The Life Sciences Institute, The Hebrew University of Jerusalem, Jerusalem, Israel; Genomnia srl, Lainate, Milan, Italy.
PLoS Comput Biol. 2014 Mar 20;10(3):e1003517. doi: 10.1371/journal.pcbi.1003517. eCollection 2014 Mar.
The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinson's disease (PD) patients' leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5'-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases.
人类寿命的不断延长伴随着神经退行性疾病发病率的增加,这就需要开发廉价的基于血液的诊断方法。通过RNA测序分析血细胞转录本是识别新型生物标志物的有力手段,这种方法正迅速变得普遍。然而,目前缺乏发现新外显子、连接和剪接事件,以及通过RNA测序数据分析和跨RNA测序平台精确且灵敏地评估差异剪接的工具。在此,我们展示了一种全新且全面的用于全转录组RNA测序分析的计算工作流程,使用软件AltAnalyze的更新版本,以识别已知和新型的高可信度可变剪接事件,并将它们与蛋白质结构域和微小RNA结合注释整合起来。我们将这种新颖的工作流程应用于帕金森病(PD)患者在深部脑刺激(DBS)治疗前后白细胞的RNA测序数据,并与健康对照进行比较。疾病介导的变化包括可变启动子和N端使用减少、5'端变异以及互斥外显子。PD调控的FUS和HNRNP A/B包括朊病毒样结构域调控区域。我们还在此展示了一种通过RNA测序数据识别和分析长链非编码RNA(lncRNA)的工作流程。我们在检测到的6000多个白细胞lncRNA中,发现13个lncRNA的表达降低以及PD诱导的选择性变化,其中4个在DBS后发生反向改变。这些包括U1剪接体lncRNA和RP11 - 462G22.1,它们各自与众多微小RNA具有序列互补性。对PD患者和未受影响对照大脑的RNA测序分析揭示了超过7000个在大脑中表达的lncRNA,其中3495个在白细胞中共同表达,包括U1,其在白细胞和大脑中均有增加。此外,qRT - PCR验证证实了与对照相比,PD患者白细胞以及杏仁核和黑质这两个脑区中这些共同增加的情况。这种新颖的工作流程允许对RNA测序数据集进行深入的多层次检查,并为理解PD和其他神经退行性疾病中的疾病转录组修饰提供了一个全面的新资源。