Computational Approaches for Structural Variation Studies in Genomes

描述(申请人提供)：结构变异，包括大块DNA序列的重复、插入、缺失、倒置和易位，已被证明与各种人类疾病有关。这些变异也经常出现在癌症的躯体改变中。识别和描述基因组序列中的结构变异是一项具有挑战性的任务。我们建议开发计算方法，以实现对正常和疾病基因组结构变异的全面研究。在目标1中，我们使用一种新的几何和概率方法开发了一个通用计算框架，用于跨多个样本和测量平台对结构变体进行分类和比较。在目标2中，我们设计算法以最大限度地发挥新兴的单分子测序技术的有效性，以检测和组装复杂的结构变体和重排的转录本。在目标3中，我们开发了重建癌症基因组组织的算法，并研究了结构变异如何在体细胞进化过程中改变基因组组织。最后，在目标4中，我们研究了人类基因组倒位多态的群体遗传学，包括它们对单倍型区块结构的影响，以及在选择下的倒位是否留下了独特的遗传特征。我们将与几位生物医学研究人员合作，将这些方法应用于来自人类、癌症、小鼠和病原体基因组的数据。拟议研究的成功完成将有助于未来研究结构变异在人类和癌症遗传学中的作用。

DESCRIPTION (provided by applicant): Structural variants, including duplications, insertions, deletions, inversions, and translocations of large blocks of DNA sequence, have been shown to be associated with various human diseases. These variants also frequently occur as somatic alterations in cancer. Identifying and characterizing structural variants in a genome sequence is a challenging task. We propose to develop computational methods to enable comprehensive studies of structural variation in normal and diseased genomes. In Aim 1 we develop a general computational framework for classification and comparison of structural variants across multiple samples and measurement platforms using a novel geometric and probabilistic approach. In Aim 2 we design algorithms to maximize the effectiveness of emerging single-molecule sequencing technologies for detecting and assembling complex structural variants and rearranged transcripts. In Aim 3 we develop algorithms to reconstruct the organization of cancer genomes and investigate how structural variants alter genome organization during somatic evolution. Finally, in Aim 4, we study the population genetics of inversion polymorphisms in the human genome, including their effects on haplotype block structure and whether inversions under selection leave distinctive genetic signatures. We will apply these approaches to data from human, cancer, mouse, and pathogen genomes in collaboration with several biomedical researchers. Successful completion of the proposed studies will facilitate future research of the role of structural variation in human and cancer genetics.