Developing Proteogenomic Mapping for Human Genome Annotation

开发用于人类基因组注释的蛋白质组图谱

基本信息

批准号：
8321269
负责人：
Morgan Corinne GIDDINGS
金额：
$ 79.77万
依托单位：
BOISE STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-09-16 至 2013-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8321269
关键词：
Address Affect Algorithms Alternative Splicing Biochemical Cell physiology Cells Code Collaborations Communities Complex Computer software Custom DNA DNA Sequence Data Data Set Databases Development Disease Elements Exons Foundations Funding Gene Targeting Genes Genetic Transcription Genome Goals Grant Health Histocompatibility Testing Human Human Genome Imagery Information Management Investigation Isotope Labeling Knowledge Link Location Machine Learning Malignant Neoplasms Maps Mass Spectrum Analysis Measures Methods Mining Modeling Nature Paint Peptides Play Procedures Process Protein Analysis Proteins Proteomics Quality Control RNA RNA Splicing Regulation Regulatory Element Research Personnel Role Sampling Software Tools Source Specific qualifier value Speed Structure System Technology Time Tissues Transcript Translating Translations Variant base cell type design experience flexibility gene function genetic element genome sequencing high throughput analysis human disease improved new technology novel prevent software systems tandem mass spectrometry web interface

项目摘要

DESCRIPTION (provided by applicant): Genome sequencing efforts are producing ever greater quantities of raw DNA sequence, but the annotation process for locating and determining the function of genetic elements has not kept up. While many aspects of annotation are difficult, it is particularly challenging to determine which parts of a genome sequence encode proteins, and therefore how the processes leading to protein translation are regulated. Not only are technologies for examining proteins more limited than those for studying RNA transcription, in an extensive study of transcription by the Encyclopedia of DNA elements consortium, a picture of great complexity emerged. The project uncovered many novel exons, alternative splice forms, and novel regulatory elements. These results indicate that nearly 9/10ths of human genes undergo alternative splicing, and the average gene produces approximately 6 splice variants. Rather than solidify knowledge regarding the location and function of genes, these results question whether we accurately know what constitutes a gene, and how the products encoded by genes determine the function of cells. The results particularly obfuscate determination of which transcripts are selected for translation to protein, further complicating annotation efforts. To address that gap, our project will determine which transcripts encode proteins, and how these are affected in several tissue types and disease conditions. We will use large tandem mass spectrometry-based proteomic data sets, mapping the analyzed protein data directly to several available human genome sequences, along with sets of predicted transcripts produced by the N-SCAN and CONTRAST gene finders, to reveal which parts of transcripts are translated into proteins, and in which types of cells this translation occurs. To accomplish this, our project has three specific aims: 1) to develop high-accuracy methods and software for mapping proteomic data from mass spec analyzed proteins directly to the genome locus encoding them; 2) to develop an analysis pipeline software system using a novel rule-based information management approach; and 3) to apply these developments for the high-throughput analysis of large proteomic data sets, identifying the transcripts that encode proteins in distinct tissue types and disease conditions, and placing the results in a publicly accessible track in the UCSC genome browser. We believe this project will yield significant knowledge about the location and timing of protein translation in cells, which will potentiate further investigation of how misregulation of the path from transcription to translation leads to human disease conditions. PUBLIC HEALTH RELEVANCE: Sequencing of the human genome is complete, but figuring out where genes are located, how they function, and how they cause or prevent human diseases like cancer has only just begun. Genes act as blueprints for RNA and proteins, the workhorses of the cell. We are developing technologies to address the key challenges of determining which genes specify the building of which proteins and how this process is orchestrated to ultimately unravel how disease processes occur.

描述（由申请人提供）：基因组测序工作正在产生更多数量的原始DNA序列，但是定位和确定遗传元素功能的注释过程尚未保持。尽管注释的许多方面很困难，但确定基因组序列的哪些部分编码蛋白质以及如何调节导致蛋白质翻译的过程特别具有挑战性。在研究DNA元素财团百科全书的广泛转录研究中，不仅比研究RNA转录的技术更有限制，这是出现了很高复杂性的图片。该项目发现了许多新颖的外显子，替代剪接形式和新颖的调节元素。这些结果表明，将近9/10的人类基因经历替代剪接，平均基因产生了大约6个剪接变体。这些结果不是巩固有关基因位置和功能的知识，而是质疑我们是否准确知道什么构成基因，以及基因编码的产物如何决定细胞的功能。结果特别混淆了选择哪些转录本被选择为蛋白质，进一步使注释工作变得复杂。为了解决该差距，我们的项目将确定哪些转录本编码蛋白质，以及在几种组织类型和疾病状况中如何影响它们。我们将使用基于大的串联质谱法蛋白质组学数据集，将分析的蛋白质数据直接映射到几个可用的人基因组序列，以及由N-SCAN和对比基因发现器产生的一组预测转录物，以揭示转录物的哪些部分转化为蛋白质，以及在哪种类型的细胞中进行这种翻译。为此，我们的项目具有三个特定的目的：1）开发高准确的方法和软件，以将蛋白质分析的蛋白质分析的蛋白质组学数据直接映射到编码它们的基因组基因座； 2）使用基于新规则的信息管理方法开发分析管道软件系统； 3）将这些发展应用于大型蛋白质组学数据集的高通量分析，识别在不同的组织类型和疾病条件下编码蛋白质的转录本，并将结果置于UCSC基因组浏览器中的公开访问轨道中。我们认为，该项目将对细胞中蛋白质翻译的位置和时机产生重要的了解，这将增强进一步研究从转录到翻译的路径如何导致人类疾病状况的错误调节。公共卫生相关性：人类基因组的测序是完整的，但是弄清楚基因的位置，其功能以及它们如何引起或预防癌症等人类疾病才刚刚开始。基因充当RNA和蛋白质的蓝图，即细胞的工作马。我们正在开发技术，以解决确定哪些基因指定哪种蛋白质的构建以及该过程如何精心策划以最终揭示疾病过程的发生方式的关键挑战。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

On the process of becoming a great scientist.

DOI：
10.1371/journal.pcbi.0040033
发表时间：
2008-02
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Giddings MC
通讯作者：
Giddings MC

Ultra-Structure database design methodology for managing systems biology data and analyses.

DOI：
10.1186/1471-2105-10-254
发表时间：
2009-08-19
期刊：
BMC bioinformatics
影响因子：
3
作者：
Maier CW;Long JG;Hemminger BM;Giddings MC
通讯作者：
Giddings MC

Comparative genome analysis of ciprofloxacin-resistant Pseudomonas aeruginosa reveals genes within newly identified high variability regions associated with drug resistance development.

环丙沙星耐药铜绿假单胞菌的比较基因组分析揭示了新发现的与耐药性发展相关的高变异性区域内的基因。

DOI：
10.1089/mdr.2012.0258
发表时间：
2013
期刊：
Microbial drug resistance (Larchmont, N.Y.)
影响因子：
0
作者：
Su,Hsun-Cheng;Khatun,Jainab;Kanavy,DonaM;Giddings,MorganC
通讯作者：
Giddings,MorganC

Whole human genome proteogenomic mapping for ENCODE cell line data: identifying protein-coding regions.

DOI：
10.1186/1471-2164-14-141
发表时间：
2013-02-28
期刊：
BMC genomics
影响因子：
4.4
作者：
Khatun J;Yu Y;Wrobel JA;Risk BA;Gunawardena HP;Secrest A;Spitzer WJ;Xie L;Wang L;Chen X;Giddings MC
通讯作者：
Giddings MC