Computational Methods for Next-Generation Comparative Genomics

人类和其他脊椎动物的全基因组测序计划已经取得了很大进展 比较基因组学，这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， 不同物种复杂性状的起源。这些见解将反过来帮助我们更好地理解 人类基因组生物学下一代测序（NGS）技术的进展 为我们解决这个问题提供了前所未有的机会。然而，大 测序的基因组数量和NGS产生的基因组质量的局限性 强调迫切需要新的计算方法来解决几个紧迫的问题 新一代比较基因组分析的挑战。在这方面的目标 特别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。我们有两个具体目标：（1）发展一个 比较组装算法，以改善从NGS数据组装的脊椎动物基因组;（2） 建立一个概率框架，以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， 软件工具，以系统地改善基因组比较的基础。研究 是重要的，因为要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。这项研究将产生持续的影响， 随着基因组数量的增加和测序技术的进步。通过 改进下一代比较基因组学的一般方法，我们的工作将有 对G10 K和ENCODE等大规模基因组计划产生重大影响。结果这个 计算生物学创新项目将促进生物医学研究的发展。

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.