Characterizing the full spectrum of genomic variation in biomedically-relevant primates

表征生物医学相关灵长类动物的全谱基因组变异

• 批准号: 10713954
• 负责人: Susanne P Pfeifer
• 金额: $ 39.25万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10713954
• 关键词: Behavioral Research; Biology; Biomedical Research; Catalogs; Code; Complex; Computing Methodologies; Data Set; Development; Disease; Etiology; Evolution; Frequencies; Gene Expression; Genes; Genetic Drift; Genetic Processes; Genetic Recombination; Genetic Variation; Genome; Genomics; Health; Heart; Heritability; Historical Demography; Human; Knowledge; Length; Modeling; Molecular; Mutation; Natural Selections; Nucleotides; Pathogenesis; Pattern; Phenotype; Play; Point Mutation; Population; Population Genetics; Primates; Process; Proteins; Research; Resolution; Role; Sampling; Shapes; Source; Structure; Technology; Variant; Work; clinical phenotype; genome-wide; genomic data; genomic variation; improved; insight; neglect; nonhuman primate; novel; single molecule

PROJECT SUMMARY Gaining a better understanding of the population genomic processes that shape observed genetic variation is at the heart of evolutionary biology. Over the past decades, much previous genomics work has focused on studying the causes and consequences of point mutations, utilizing single nucleotide variation to infer rates and patterns of recombination, population demographic history (modulating genetic drift), and natural selection. However, by failing to incorporate structural variants (insertions, deletions, duplications, translocations, and inversions with a length of ≥ 50 bp), the greatest source of heritable variation was often neglected, contributing to the 'missing heritability' problem faced in many studies of complex phenotypes. Owing to their size, structural variants frequently disrupt protein-coding genes and/or modify gene expression, thus their characterization is crucially important to elucidate factors related to health and disease. Several population- specific structural variant catalogues have recently started to emerge for human populations; yet, similar datasets remain limited for most non-human primates, despite their importance to evolutionary research (as outgroups to the human lineage) and extensive usage in biomedical and behavioral research. This neglect is largely owing to historical reasons, as short-read sequencing and limited sampling previously made a comprehensive quantification of genome-wide structural variation impossible. However, cutting-edge single- molecule long-read sequencing technologies now allow us to investigate the topic with considerable resolution. Over the next five years, the Pfeifer lab will combine the development of novel long-read genomics datasets with computational methods for evolutionary inference to: (i) comprehensively characterize the full spectrum of genomic variation (including the relative frequencies of different types of structural variants) in three biomedically-relevant primate species, (ii) conduct genomic-wide comparisons with hominoids to gain a better understanding of the diversity within and divergence between species, (iii) characterize the molecular and evolutionary processes determining the accrual, and dictating the fate, of structural variants, (iv) determine associations with previously characterized clinical phenotypes, as well as (v) investigate the interplay of (structural) mutation with another population genetic process that shapes genome structure, recombination. Taken together, this research will improve the utility of these species as models in biomedical research, provide new insights into the etiology of disease, and allow for a deeper understanding of the mode and tempo of evolutionary changes across the primate clade.

项目摘要 了解观察到的遗传变异的人群基因组过程的更好理解是 进化生物学的核心。在过去的几十年中，以前的许多基因组工作都集中在 研究点突变的原因和后果，使用单核苷酸变化来推断速率 重组，人口人群历史（调节遗传漂移）和自然选择的模式。 但是，通过未结合结构变体（插入，删除，重复，易位和 长度为≥50bp的倒置），最大的遗传变化来源通常被忽略，造成了贡献 在许多复杂表型的研究中，“缺失的遗传力”问题面临。由于它们的大小， 结构变体经常破坏蛋白质编码基因和/或修饰基因表达，因此 表征对于阐明与健康和疾病有关的因素至关重要。几个人口 特定的结构变体目录最近开始出现人类人群。但是，类似 数据集对大多数非人类素数仍然有限，dospite对进化研究的重要性（如 人类血统的群体和生物医学和行为研究中的广泛使用。这种忽视是 由于历史原因，很大程度上是由于简短的测序和有限的抽样，以前使 不可能综合数量的全基因组结构变异。但是，尖端的单人 分子长读测序技术现在使我们能够通过考虑分辨率调查主题。 在接下来的五年中，Pfeifer Lab将结合新型长阅读基因组数据集的开发 使用用于进化推断的计算方法：（i）全面表征 基因组变异（包括不同类型的结构变体的相对频率） （II）进行基因组范围的比较与类人类的生物治疗，以获得更好的比较，以获得更好的比较 了解物种内部多样性和差异，（iii）表征分子和 确定结构变体的准确性和命运的进化过程（iv）确定 与先前表征的临床表型的关联，以及（v）研究的相互作用 （结构性）突变与另一个人群遗传过程，该过程塑造了基因组结构，重组。 综上所述，这项研究将改善这些物种作为生物医学研究模型的实用性， 提供有关疾病病因的新见解，并可以更深入地了解该模式和节奏 灵长类动物进化枝的进化变化。