ABI Innovation: A Novel Framework for Detecting Genomic Structural Variation

基因组结构变异已被确定为广泛的系统发育谱中表型多样性的重要贡献者，包括人类，脊椎动物，线虫，昆虫和植物。这些变异是包含DNA重排的染色体的大多态区域。虽然有许多工具可以从测序数据中检测这些变异，但它们无法准确地解析具有高重复内容的区域或具有复杂结构的变异。该项目解决了当前方法的算法限制，并开发了能够识别这些复杂和重复变体的工具。它还开发了一个计算平台，以促进研究社区其他成员开发先进工具。理解基因组变异所扮演的角色是当今社会面临的主要科学挑战和机遇之一。这些变异检测的改进将在广泛的生物学领域产生影响，包括群体遗传学、进化发育生物学和植物基因组学。它还将使人们更好地了解癌症等毁灭性疾病背后的机制，在这些疾病中，复杂和重复的因素已被证明发挥着重要作用。为了培养这一重要领域的未来领导者，该项目将开发研究生和本科生课程，以培养未来的科学家和工程师，并推进生物学和计算机科学的合作前沿。将大力努力通过招收代表性不足群体的学生来促进多样性。

Genomic structural variation has been identified as a significant contributor to phenotype diversity across a wide phylogenetic spectrum, including humans, vertebrates, nematodes, insects, and plants. These variants are large polymorphic regions of chromosomes that contain rearrangement of DNA. While numerous tools exist for detecting these variants from sequencing data, they are not able to accurately resolve regions with a high repetitive content or variants with a complex structure. This project addresses the algorithmic limitations of current approaches and develops tools to enable the identification of these complex and repetitive variants. It also develops a computational platform to facilitate the development of advanced tools by other members of the research community. Understanding the role that genomic variation plays is one of the major scientific challenges and opportunities facing society today. The improved detection of these variants will have an impact across a wide range of biological areas, including population genetics, evolutionary developmental biology, and plant genomics. It will also lead to better understanding of the mechanisms behind devastating diseases such as cancer, where complex and repetitive elements have been shown to play an important role. To educate future leaders in this important field, the project will develop graduate and undergraduate classes to train future generations of scientists and engineers and to advance the collaborative frontiers of biology and computer science. Strong efforts will be made to promote diversity through recruitment of students from under-represented groups.