Investigating the role of structural variation in hominin evolution.

项目摘要 沿着环境的差异，遗传变异是表型多样性的最终来源 和物种之间。由于传统短读测序技术的局限性， 人类遗传学和进化集中在单核苷酸变异（SNV）和短插入， 删除。最近长读段测序技术的发展已经开始揭示 以及更大的插入、缺失和重排的表型影响，统称为结构性影响。 变体（SV）。然而，长读段测序方法对于大规模应用仍然是不切实际的，这是由于 它们的高成本和低产量。因此，SV在人类进化中的作用仍然知之甚少。 这些挑战激发了创新计算方法的发展，这些方法将联合收割机 使用具有短读段测序的规模和全局多样性的长读段发现SV的准确性 数据集。为了进一步了解SV如何影响人类的适应性和基因组功能， 研究项目将： 1.通过利用基于图的SV基因分型方法识别局部适应性SV。这种方法 能够对在不同的短读段数据集中用长读段发现的SV进行准确的基因分型， 人类种群。用这种方法产生的群体范围的基因型将允许 发现SV上历史正选择的特征。 2.发现现代人，尼安德特人，和 Denisovan谱系使用图基因分型和无标记方法。将SV放置在其 比较进化背景将揭示不同的变异，可能是重要功能的基础。 区别这些人类群体的差异。 3.通过结合长读段和短读段RNA定量SV的功能基因组影响 不同人类个体的测序。这些数据将揭示SV如何介导 表型差异通过影响基因表达和剪接。 这项研究将在强大的遗传学和基因组学培训环境中进行，并将联合收割机 进化论，计算基因组学，以及我的赞助商，合作者的长期测序专业知识和资源， 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， 软件工具的开发和功能基因组数据分析。同时，制度环境 也将促进我在沟通，教学，指导和领导技能的培训， 成为人类遗传学领域领先研究者的必备条件

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.