Computational Methods for Next-Generation Comparative Genomics

下一代比较基因组学的计算方法

• 批准号: 9102153
• 负责人: Jian Ma
• 金额: $ 32.94万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9102153
• 关键词: Address; Algorithmic Software; Algorithms; Biological; Biology; Biomedical Research; Chromosomes; Comparative Genomic Analysis; Complex; Computational Biology; Computing Methodologies; Data; Disease; Evolution; Foundations; Generations; Genome; Genomics; Goals; Health; Human; Human Biology; Human Genome; Knowledge; Methodology; Methods; Mission; Outcome; Pattern; Phenotype; Phylogenetic Analysis; Regulatory Element; Research; Research Personnel; Resolution; Sampling; Sequence Alignment; Sequence Analysis; Software Tools; Technology; Uncertainty; United States National Institutes of Health; Variant; Vertebrates; Work; base; comparative; comparative genomics; genome sequencing; genome-wide; human disease; improved; innovation; insight; markov model; next generation; next generation sequencing; novel; reconstruction; scaffold; trait; vertebrate genome; whole genome

Whole genome sequencing projects of human and other vertebrates have greatly advanced comparative genomics, which led to novel biological discoveries. Our long-term research goal is to use comparative genomics to elucidate the trajectory of vertebrate genome evolution and the origin of complex traits of different species. Such insights will in turn help us better understand the biology of the human genome. Advances in next-generation sequencing (NGS) technologies have provided us with unprecedented opportunities to tackle this problem. However, the large number of genomes being sequenced and the limitations of genome quality produced by NGS have underlined urgent needs for new computational methods to address several pressing challenges for the new generation of comparative genomic analysis. The objective in this particular application is to develop new computational methods to improve the accuracy of whole- genome comparisons for vertebrate genomes. We have two specific aims: (1) To develop a comparative assembly algorithm to improve vertebrate genomes assembled from NGS data; (2) To develop a probabilistic framework to improve the quality of multiple sequence alignments for vertebrate genomes. Our research plan is innovative because it provides novel algorithms and software tools to systematically improve the foundations for genome comparisons. The research is significant because the methods to be developed will allow researchers to more effectively utilize the new genome sequencing data. The proposed research will have sustained impact even with the increasing number of genomes and the advancement of sequencing technology. By improving the general methodology for next-generation comparative genomics, our work will have a high impact on large-scale genome projects such as G10K and ENCODE. As a result, this innovative project in computational biology will enable advancement in biomedical research.

人类和其他脊椎动物的全基因组测序项目取得了巨大进展 比较基因组学，带来了新的生物学发现。我们的长期研究目标是 使用比较基因组学来阐明脊椎动物基因组进化的轨迹和 不同物种复杂性状的起源。这些见解反过来将帮助我们更好地理解 人类基因组生物学。下一代测序 (NGS) 技术的进步 为我们解决这一问题提供了前所未有的机会。然而，大 正在测序的基因组数量以及 NGS 产生的基因组质量的局限性 强调了对新计算方法的迫切需求，以解决几个紧迫的问题 新一代比较基因组分析面临的挑战。本次活动的目的是 特殊的应用是开发新的计算方法来提高整体的准确性 脊椎动物基因组的基因组比较。我们有两个具体目标： (1) 开发 比较组装算法，用于改进从 NGS 数据组装的脊椎动物基因组； (2) 开发概率框架来提高多序列比对的质量 脊椎动物基因组。我们的研究计划是创新的，因为它提供了新颖的算法和 系统地改善基因组比较基础的软件工具。研究 意义重大，因为待开发的方法将使研究人员更有效地 利用新的基因组测序数据。拟议的研究将产生持续的影响，甚至 随着基因组数量的不断增加和测序技术的进步。经过 改进下一代比较基因组学的通用方法，我们的工作将 对 G10K 和 ENCODE 等大规模基因组项目影响很大。结果，这 计算生物学的创新项目将促进生物医学研究的进步。