Investigating the role of structural variation in hominin evolution.

研究结构变异在古人类进化中的作用。

基本信息

批准号：
10464600
负责人：
Stephanie M Yan
金额：
$ 4.68万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-16 至 2024-09-15
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10464600
关键词：
Address Affect Base Pairing Biology Code Collaborations Communication Computing Methodologies DNA DNA Sequence Rearrangement Data Data Analyses Data Set Development Educational process of instructing Environment Epigenetic Process European Evolution Exhibits Gene Expression Gene Expression Regulation Genetic Genetic Transcription Genetic Variation Genetic study Genome Genome Scan Genomic Segment Genomics Genotype Goals Graph Habitats Haplotypes Human Human Genetics Human Genome Hybrids Immunoglobulins Individual Investigation Knowledge Leadership Length Mediating Mentorship Methods Modernization Modification Molecular Mutation Phenotype Play Pongidae Population Prevalence RNA RNA Splicing Research Research Personnel Research Project Grants Resources Role Sampling Single Nucleotide Polymorphism Software Tools Source Spliced Genes Technology Training Transcript Variant Work base causal variant comparative cost fitness functional genomics genetic evolution genetic variant human disease human genomics improved innovation insertion/deletion mutation insight model development novel skills transcriptome sequencing

项目摘要

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.

项目概要除了环境差异外，遗传变异是生物体内表型多样性的最终来源。以及物种之间。由于传统短读长测序技术的局限性，大多数研究人类遗传学和进化主要关注单核苷酸变异（SNV）和短插入删除。长读长测序技术的最新发展已经开始揭示出其普遍性更大的插入、删除和重排对表型的影响，统称为结构变体（SV）。然而，长读长测序方法对于大规模应用仍然不切实际，因为它们的成本高且吞吐量低。因此，SV 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，这些方法结合了使用长读长发现 SV 的准确性以及短读长测序的规模和全局多样性数据集。为了加深对 SV 如何影响人类健康和基因组功能的了解，该提议研究项目将： 1. 利用基于图形的 SV 基因分型方法来识别局部自适应 SV。这种做法能够对来自不同短读长数据集中的长读长发现的 SV 进行准确的基因分型人口。用这种方法产生的人群范围的基因型将允许发现 SV 历史正选择的特征。 2. 发现现代人类、尼安德特人和现代人共有或独有的 SV 使用图基因分型和免比对方法进行丹尼索瓦人谱系。将 SV 放置在其比较进化背景将揭示可能构成重要功能的不同变异区分这些古人类群体的差异。 3. 通过结合长读长和短读长 RNA 来量化 SV 的功能基因组影响对不同人类个体进行测序。这些数据将揭示 SV 如何进行调解的见解通过对基因表达和剪接的影响产生表型差异。这项研究将在强大的遗传学和基因组学培训环境中进行，并将结合我的赞助商、合作者的进化、计算基因组学和长读测序专业知识和资源赞助者、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，制度环境还将促进我在沟通、教学、指导和领导技能方面的培训对于成为人类遗传学领域的领先研究人员至关重要。