Computational Methods for Next-Generation Comparative Genomics

下一代比较基因组学的计算方法

• 批准号: 8697559
• 负责人: Jian Ma
• 金额: $ 32.16万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 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 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8697559
• 关键词: Address; 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; Phylogenetic Analysis; Reading; Regulatory Element; Research; Research Personnel; Resolution; Sampling; Sequence Alignment; Sequence Analysis; Software Tools; Solutions; Technology; Uncertainty; Variant; Vertebrates; Work; base; comparative; comparative genomics; genome sequencing; human disease; improved; innovation; insight; markov model; next generation; next generation sequencing; novel; reconstruction; scaffold; trait; vertebrate 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整个基因组测序项目都非常先进 比较基因组学，导致了新的生物学发现。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 不同物种的复杂特征的起源。这种见解又将帮助我们更好地了解 人类基因组的生物学。下一代测序（NGS）技术的进步 为我们提供了解决这个问题的前所未有的机会。但是，大 测序的基因组数量以及NGS产生的基因组质量的局限性 已经强调了对新计算方法的紧急需求，以解决几种压力 新一代比较基因组分析的挑战。目的 特定的应用是开发新的计算方法，以提高整体的准确性 脊椎动物基因组的基因组比较。我们有两个具体的目标：（1）开发一个 比较组装算法以改善从NGS数据组装的脊椎动物基因组； （2） 开发一个概率框架，以提高多个序列一致性的质量 脊椎动物基因组。我们的研究计划具有创新性，因为它提供了新颖的算法和 软件工具可以系统地改善基础以进行基因组比较。研究 之所以重要，是因为要开发的方法将使研究人员更有效 利用新的基因组测序数据。拟议的研究甚至将持续影响 随着基因组数量的增加和测序技术的发展。经过 改善下一代比较基因组学的一般方法，我们的工作将有 对G10K和Encode等大型基因组项目的高影响。结果，这个 计算生物学的创新项目将使生物医学研究的进步。