Computational approaches to delineate non-canonical splicing events

描述非规范剪接事件的计算方法

• 批准号: 10797919
• 负责人: Rendong Yang
• 金额: $ 6.02万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10797919
• 关键词: Algorithms; Alternative Splicing; Basic Science; Catalogs; Communities; Complex; Computational algorithm; Computer software; Data; Data Set; Dedications; Development; Disease; Event; Genes; Genetic; Genomic medicine; Genotype-Tissue Expression Project; Goals; Health; Introns; Modeling; Molecular; Multiomic Data; Pattern; Population; Prevalence; Proteins; RNA; RNA Splicing; Reporting; Research; Series; Site; Technology; The Cancer Genome Atlas; Transcript; Variant; Work; cell type; computer framework; exon skipping; genome sequencing; human disease; improved; innovation; novel; novel therapeutic intervention; open source; programs; proteogenomics; sequencing platform; tool; transcriptome; whole genome

Abstract: RNA splicing generates enormous variations at the RNA and protein levels to regulate cell-type- specific functions as well as being the cause for numerous diseases. Several classes of splicing patterns have been widely studied, such as exon skipping, intron retention and alternative splicing sites. Advances in sequencing technologies enable the discovery of previously unknown non-canonical splicing events. However, due to the lack of dedicated computational approaches, the prevalence and functional consequences of these non-canonical splicing events remain unexplored. The goal of our research program in the next five years is to develop novel and specialized computational algorithms for discovery and characterization of emerging splicing patterns that are currently understudied. We will focus on exitrons and non-linear- spliced transcripts in our proposed study, as these two non-canonical splicing models have been implicated in complex human diseases reported by recent studies. We will develop a series of algorithms to (1) comprehensively catalog these novel splicing patterns using short and long read sequencing platforms, (2) dissect the genetic basis of non-canonical splicing events with integrative analysis of deep transcriptome and whole-genome sequencing data, and (3) elucidate the functional impacts of novel forms of RNA splicing alternations using a proteogenomic strategy. Our proposed work is innovative in that we will build unique computational frameworks to detect and characterize novel non-canonical splicing events by integrating large multi-omics datasets (e.g. TCGA, GTEx and ENCODE). It is significant because it can be applied both in basic research to improve transcriptome annotation and potentially in genomic medicine to guide the development of novel therapeutic strategies for complex diseases.

文摘:

项目成果

ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data.

ScanExitronLR：长读长 RNA-seq 数据中退出子剪接事件的表征和定量。

• DOI: 10.1093/bioinformatics/btac626
• 发表时间: 2022
• 期刊: Bioinformatics (Oxford, England)
• 作者: Fry,Joshua;Li,Yangyang;Yang,Rendong
• 通讯作者: Yang,Rendong

PxBLAT: An Ergonomic and Efficient Python Binding Library for BLAT.

PxBLAT：一个符合人体工程学且高效的 BLAT Python 绑定库。

• DOI: 10.1101/2023.08.02.551686
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Li,Yangyang;Yang,Rendong
• 通讯作者: Yang,Rendong