CAREER: Computational Methods for Analyzing Large-Scale Genomic Changes in Mammalian Genomes

该项目将开发新的组合和概率算法，以揭开在进化背景下跨物种发生的相互交织的大规模基因组变化。主要的研究方向是开发新的祖先基因组重建算法，在一个统一的框架内处理不同分辨率的重排、复制和大插入和大删除。这些方法将被应用于大量的全基因组序列数据，这些数据已经成为可用的，以阐明哺乳动物基因组中大规模基因组操作的详细历史。有了重建的历史，科学家将能够解释大规模的基因组变化，并评估它们对任何谱系的表型影响，包括人类谱系。PI使用基于与当前基因组一致的断点图的简约原理来考虑祖先基因组的问题。考虑两个以上的基因组，这些问题在计算上几乎都很难处理。该方法的重点是在基因组之间建立更好的同步性块，并以分层的方法使用这些块来开发新的重建算法，然后将其细化为更小的块，并处理不完整的谱系排序。这些新的软件工具和资源将非常有用，以揭示哺乳动物形式和能力的非凡多样性。此外，来自该项目的见解将被应用于改进基于下一代高通量DNA测序读数的基因组组装方法。这些模型和算法还将用于研究受大规模基因组变化影响的特定基因组区域，例如复杂的基因簇和癌症基因组中包含基因组不稳定的区域。该项目将开发用于比较基因组学研究的开源软件工具，使世界各地的其他科学家能够使用这些工具。此外，该项目的成果将通过在线网站传播。研究中的可视化工具将提供关于基因组进化的科学教育，以增加公众对科学成果的可及性。作为他职业计划的一部分，教育部分与研究计划紧密结合。教育目标包括开发新的生物信息学课程；培训研究生具备后基因组时代所需的跨学科专业知识，并通过合作为他们提供有意义的国际研究经验；让本科生参与研究项目；参加伊利诺伊大学的G.A.M.E.S.夏令营，以激励大学前女孩在科学和工程领域发展事业。

This project will develop new combinatorial and probabilistic algorithms that will unravel the interwoven large-scale genomic changes that have occurred across species in an evolutionary context. The main research thrust is to develop new ancestral genome reconstruction algorithms that handle rearrangements, duplications, and large insertions and deletions at different resolutions in a single unified framework. These methods will be applied to the large number of whole-genome sequence data that have become available to elucidate detailed history of large-scale genomic operations in mammalian genomes. With the reconstructed history, scientists will be able to explain the large-scale genomic changes and assess their phenotypic impact on any lineage, including the human lineage. The PI considers the problem of ancestral genomes using a parsimony principle based on breakpoint graphs that are consistent with current genomes. For considering more than two genomes, these problems are nearly all computationally intractable. The approach focuses on building better synteny blocks between genomes and using these blocks in a hierarchical method to develop new reconstruction algorithms that are then refined to smaller blocks and dealing with incomplete lineage sorting. These new software tools and resources will be extremely useful to shed new light on the extraordinary diversity of mammalian forms and capabilities. In addition, the insights from this project will be applied to improve genome assembly methodologies based on next-generation high-throughput DNA sequencing reads. The models and algorithms will also be used to investigate specific genomic regions influenced by large-scale genomic changes, such as complex gene clusters and regions that harbor genome instability in cancer genomes. The project will develop open-source software tools for comparative genomics research, making them accessible to other scientists around the world. In addition, the outcome of the project will be disseminated through online website. Visualization tools from the research will provide scientific education on genome evolution to increase the accessibility of scientific results to the general public.As part of his CAREER plan, the education components are closely integrated with the research program. The educational objectives include the development of new bioinformatics courses; training graduate students with interdisciplinary expertise necessary for the post-genomic era and providing them with meaningful international research experience through collaboration; getting undergraduate students involved in research projects; and participating in the G.A.M.E.S. camp at the University of Illinois to inspire pre-college girls to develop careers in science and engineering.