Evolutionary Bioinformatics of Human Mutations

人类突变的进化生物信息学

• 批准号: 7988546
• 负责人: Sudhir Kumar
• 金额: $ 38.13万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2013-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7988546
• 关键词: Acute; Address; Adoption; Affect; Anatomy; Bioinformatics; Biological; Biomedical Research; Communities; Complex; Computer Simulation; Computer software; DNA Sequence; Data; Data Set; Databases; Decision Support Systems; Development; Diagnosis; Diagnostic; Disease; Failure; Frequencies; Functional RNA; Gene Mutation; Genetic Polymorphism; Genome; Genomics; Human; Human Genome; Individual; Investigation; Linux; Measures; Medicine; Methods; Molecular; Mutate; Mutation; Mutation Analysis; Nature; Operating System; Pattern; Plug-in; Point Mutation; Population; Population Analysis; Positioning Attribute; Property; Publications; Recording of previous events; Research; Research Infrastructure; Research Personnel; Running; Scientist; Sequence Alignment; Software Design; Software Tools; Solutions; Somatic Cell; Source Code; Techniques; Time; Training and Education; Translating; Variant; Visual; Work; base; biological research; computerized tools; cost; direct application; experience; fundamental research; innovation; knowledge base; mutant; novel; population survey; programs; research and development; software development; sound; success; tool; user-friendly

DESCRIPTION (provided by applicant): An enduring impediment in translating genomic advances into biomedical solutions has been the lack of tools and techniques that enable biologists to [a] efficiently leverage the multitude of publically- available genome variation data in their research endeavors, and [b] effectively harness the long-term (inter-specific) evolutionary histories of mutant positions in diagnosing functional effects of novel mutations. This need has become more acute with the discovery of unprecedented numbers of novel mutations in personal genomes and population surveys. Therefore, we propose an integrated research and development project to address this need. First, we plan to develop unique, user-friendly, and robust software to investigate human mutations in the context of Long-Term Evolutionary (LTE) patterns on a genomic scale; LTE patterns are revealed by inter-specific comparisons at a position, and they provide sound baseline hypotheses for analyzing the nature of mutations and frequencies of contemporary variations. The proposed myPEG (Population Evolutionary Genomics) software will contain tools for automated data assembly and integration from primary genome alignment browsers and mutation databases (e.g., UCSC, 1000Genomes, dbSNP). myPEG will enable users to conduct integrative analysis across taxonomic scales via its cross-platform WebTop display and analysis framework that will seamlessly integrate species and population sequence alignments and analyses in traditional and novel ways. myPEG's approach to software design and development will be biologist- centric in which we emulate, rather than reinvent, biologists' favorite work practices. These software developments will be informed by the proposed fundamental research to develop direct applications of macro-evolutionary patterns to the diagnosis of mutations associated with disease (e.g., Mendelian, complex, and somatic-cell mutations), and the successes of their computational predictions using in silico tools. The proposed investigations will yield similarities and differences in evolutionary anatomies of disease-associated and other mutations (including population SNPs) as well as those of the success rates of all major in silico tools currently used for diagnosing functional effects of novel mutations. These discoveries will form the basis for developing a decision support system to choose the best in silico method for the type of mutation and purpose (type of disease), such that the Reliability of in silico Inference (RoI) is the highest. myPEG will contain this decision support system, along with facilities for prototyping and conducting high-throughput iterative analysis of large numbers of mutations. myPEG will run on all major platforms (Windows, Linux, and MacOS), will be useable as a plug-in into analysis pipelines natively in these operating systems, and will be available at no cost (including the source code) to all users, including those in research, education, and training.

描述（由申请人提供）： 将基因组发展转化为生物医学解决方案的持久障碍是缺乏工具和技术，使生物学家能够[A]有效利用其研究努力中的多种公开可用的基因组变异数据，而[b]有效地利用长期（特定间）进化的历史悠久的诊断效果的突变性效应。随着个人基因组和人口调查中空前数量的新突变，这种需求变得更加急剧。因此，我们提出了一个综合的研发项目来满足这一需求。首先，我们计划开发独特的，用户友好且健壮的软件，以在基因组规模上长期进化（LTE）模式的背景下研究人类突变； LTE模式通过特定于位置的特定比较来揭示，它们提供了声音基线假设，用于分析突变和当代变化的频率的性质。提出的MYPEG（人群进化基因组学）软件将包含用于自动数据组件的工具，以及主要基因组比对浏览器和突变数据库（例如UCSC，1000 genomes，dbsnp）的集成。 MYPEG将使用户能够通过其跨平台WebTop显示和分析框架进行跨分类学量表进行综合分析，从而将物种和种群序列对齐和分析以传统和新颖的方式无缝整合。 MyPEG的软件设计和开发方法将以生物学家为中心，在该方法中，我们模仿生物学家最喜欢的工作实践而不是重塑生物学。这些软件开发将由拟议的基础研究告知，以开发宏观进化模式的直接应用，以诊断与疾病相关的突变（例如Mendelian，Complex和Sompatic-Cell突变）及其在计算机工具中使用其计算预测的成功。拟议的研究将产生与疾病相关和其他突变（包括种群SNP）的进化解剖结构以及所有专业的成功率的相似性和差异，目前用于诊断新型突变功能效应的硅酸盐工具的成功率。这些发现将构成开发决策支持系统的基础，以选择用于突变和目的类型（疾病类型）的最佳硅方法，以便在计算机推理（ROI）中的可靠性最高。 MyPEG将包含此决策支持系统，以及用于原型制作和进行大量突变的高通量迭代分析的设施。 MYPEG将在所有主要平台（Windows，Linux和MacOS）上运行，可作为这些操作系统本地分析管道的插件使用，并将免费提供给所有用户，包括研究，教育和培训的所有用户。