Recovering Proteoforms from Cardiovascular Omics Datasets: A Multi-omics Secondary Analysis

从心血管组学数据集中恢复蛋白质形式：多组学二次分析

基本信息

批准号：
10084750
负责人：
Maggie Lam
金额：
$ 11.66万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-01-15 至 2022-12-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10084750
关键词：
Algorithms Alternative Splicing Amino Acid Sequence Amino Acid Sequence Databases Atrial Fibrillation Biochemical Bioinformatics Biological Biological Markers Cardiomyopathies Cardiovascular system Cell physiology Chemicals Code Coin Communities Computing Methodologies Custom Data Data Set Databases Diagnosis Disease Exons Funding Future Genes Genome Goals Heart Heart Diseases Heart Research Heart failure Human Knowledge Meta-Analysis Modification Molecular National Heart, Lung, and Blood Institute Pathologic Processes Pathology Pathway interactions Pilot Projects Population Post-Translational Modification Site Post-Translational Protein Processing Process Protein Isoforms Proteins Proteomics Public Domains RNA Splicing Regulation Research Research Activity Research Personnel Shotguns Techniques Tissue-Specific Gene Expression Tissues Variant computational pipelines cost effective data repository data resource data reuse differential expression experimental study improved insight molecular sequence database multiple omics novel protein expression protein function proteomic signature public repository repository secondary analysis therapeutic target tool transcriptome sequencing

项目摘要

PROJECT SUMMARY Large-scale omics techniques including proteomics and RNA-seq have become important tools to identify disease mechanisms and therapeutic targets. However, these experiments have largely not considered “proteoforms” - protein variants coded by the same gene such as through alternative splicing and post- translational modifications that can serve different cellular functions and whose distributions are often permuted in disease. In the heart in particular, alternative splicing is implicated in broad pathological processes in heart failure and cardiomyopathy, but at present we have a poor understanding of the expression status and molecular functions of many alternative splice isoform products at the protein level. Recently we have developed and optimized a computational pipeline which can integrate information from RNA-seq and proteomics data to recover lost protein isoform information from proteomics data. Our goal now is to perform a targeted secondary analysis of publicly available quantitative proteomics data on heart diseases that are housed in persistent data repositories. Specifically, Aim 1 will (i) identify and quantify alternative splice isoforms in heart failure and atrial fibrillation proteomics data, by using custom sequence databases constructed from RNA-seq data; and (ii) determine the intersections between AS isoforms with PTM sites at regulatory hotspots, with the aid of mass-tolerant open-search algorithms that can recover unexpected PTMs in proteomics data. By reanalyzing existing datasets with our pipeline we aim to extract isoform-level knowledge on existing data, which we are confident will have a strong likelihood to open unforeseen avenues into the research of heart diseases, and also add value to the existing rich data resources in our research community.

项目摘要包括蛋白质组学和RNA-seq在内的大规模的OMIC技术已成为识别的重要工具疾病机制和治疗靶标。但是，这些实验在很大程度上不考虑 “蛋白质成型” - 由相同基因编码的蛋白质变体，例如通过替代剪接和后翻译的修改可以服务于不同的蜂窝函数并且其分布经常是疾病排列。特别是心脏地带，在广泛的病理中暗示了替代剪接心力衰竭和心肌病的过程，但目前我们对许多替代剪接同工型产物在蛋白质水平上的表达状态和分子功能。最近，我们开发并优化了可以集成信息的计算管道从RNA-seq和蛋白质组学数据中恢复蛋白质组学数据中丢失的蛋白质同工型信息。我们的现在的目标是对公开可用的定量蛋白质组学数据进行有针对性的次要分析持续数据存储库中的心脏病。具体而言，目标1将（i）识别和量化通过使用自定义序列由RNA-Seq数据构建的数据库；（ii）确定AS同工型与借助大量耐受性开放式搜索算法，可以恢复的PTM位点蛋白质组学数据中意外的PTM。通过使用我们的管道重新分析现有数据集，我们旨在提取有关同工级知识现有数据，我们有信心将不可预见的途径开放到心脏病的研究，还为我们的研究社区中现有的丰富数据资源增加了价值。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart.

心脏中选择性剪接衍生蛋白质形式的组织使用偏好和本质无序区域重塑。

DOI：
10.1101/2023.10.08.561375
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Pandi,Boomathi;Brenman,Stella;Black,Alexander;Ng,DominicCM;Lau,Edward;Lam,MaggiePY
通讯作者：
Lam,MaggiePY

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot.