Investigating the role of structural variation in hominin evolution.

项目总结 除了环境的差异，遗传变异也是 以及物种之间的差异。由于传统短读测序技术的局限性，大多数研究在 人类的遗传和进化一直专注于单核苷酸变异(SNV)和短插入和 删除。最近长读测序技术的发展已经开始揭示这种普遍存在的情况 以及更大的插入、删除和重排的表型影响，统称为结构 变种(SVS)。然而，长读测序方法对于大规模应用来说仍然是不切实际的，因为 它们的高成本和低吞吐量。因此，SVS在人类进化中的作用仍然知之甚少。 这些挑战推动了创新计算方法的发展，这些方法结合了 利用短读测序的规模和全局多样性使用长读数发现SV的准确性 数据集。为了促进对SVS如何影响人类健康和基因组功能的了解，这项研究提出了 研究项目将： 1.利用基于图形的方法进行SV基因分型，识别局部适应性SV。这种方法 能够对从不同来源的短读数据集中通过长读数据发现的SVS进行准确的基因分型 人类人口。用这种方法产生的全人群的基因型别将允许 在支持向量机上发现历史正向选择特征。 2.发现现代人、尼安德特人和 丹尼索瓦血统使用图形基因分型和无比对方法。将SV放置在他们的 比较的进化背景将揭示可能构成重要功能的不同变体 区别这些原始人群体的差异。 3.通过结合长读和短读RNA来量化SVS的功能基因组影响 对不同的人类个体进行排序。这些数据将揭示SVS可能如何进行调解 通过对基因表达和剪接的影响来实现表型差异。 这项研究将在强大的遗传学和基因组学培训环境中进行，并将结合 进化论，计算基因组学，以及我的赞助商-- 赞助商和合作者。我的项目将为我提供进化建模方面的科学培训， 开发软件工具和功能基因组数据分析。同时，制度环境 还将促进我在沟通、教学、指导和领导技能方面的培训，这些技能 对成为人类遗传学领域的领军研究人员至关重要。

PROJECT SUMMARY Along with differences in the environment, genetic variation is the ultimate source of phenotypic diversity within and between species. Due to the limitations of traditional short-read sequencing technologies, most research in human genetics and evolution has focused on single-nucleotide variants (SNVs) and short insertions and deletions. The recent development of long-read sequencing technologies has begun to reveal the prevalence and phenotypic impacts of larger insertions, deletions, and rearrangements, collectively termed structural variants (SVs). However, long-read sequencing methods remain impractical for large-scale application due to their high cost and low throughput. Consequently, the role of SVs in human evolution is still poorly understood. These challenges motivate the development of innovative computational approaches that combine the accuracy of SV discovery using long reads with the scale and global diversity of short-read sequencing datasets. To advance knowledge of how SVs impact fitness and genome function in humans, this proposed research project will: 1. Identify locally adaptive SVs by leveraging graph-based methods for SV genotyping. This approach enables accurate genotyping of SVs discovered with long reads in short-read datasets from diverse human populations. The population-wide genotypes generated with this method will allow for the discovery of signatures of historical positive selection on SVs. 2. Discover SVs that are shared among or exclusive to the modern human, Neanderthal, and Denisovan lineages using both graph genotyping and alignment-free methods. Placing SVs in their comparative evolutionary contexts will reveal divergent variants that may underlie important functional differences that distinguished these hominin groups. 3. Quantify the functional genomic impacts of SVs by combining long-read and short-read RNA sequencing of diverse human individuals. This data will reveal insights into how SVs may mediate phenotypic differences through effects on gene expression and splicing. This research will be conducted in a strong genetics and genomics training environment, and will combine the evolution, computational genomics, and long-read sequencing expertise and resources of my sponsor, co- sponsor, and collaborator. My project will provide me with scientific training in evolutionary modeling, development of software tools, and functional genomic data analysis. Meanwhile, the institutional environment will also facilitate my training in the communication, teaching, mentorship, and leadership skills that are essential for becoming a leading researcher in human genetics.