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Identification and Functional Validation of Human Infertility Alleles

人类不育等位基因的鉴定和功能验证

基本信息

批准号：
8973021
负责人：
John C Schimenti
金额：
$ 59.96万
依托单位：
CORNELL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2020-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8973021
关键词：
Address Alleles Amino Acids Behavior Benign Biological Assay CDK2 gene Cell Count Chromosomes Clustered Regularly Interspaced Short Palindromic Repeats Computer Simulation DNA Sequence DNA Sequence Alteration Data Data Aggregation Databases Diagnosis Disease Fertility Frequencies Future Generations Gametogenesis Gene Frequency Generations Genes Genetic Genetic Polymorphism Genetically Engineered Mouse Genomics Germ Cells Goals Heterogeneity Histology Human In Vitro Infertility Knowledge Laboratories Medicine Meiosis Methods Minor Modeling Mus Mutation Oocytes Orthologous Gene Patients Phenotype Population Process Proteins Reproduction Resources Single Nucleotide Polymorphism Sperm Motility Technology Test Result Testing Ursidae Family Validation Variant Woman Work base clinically significant cost empowered exome sequencing functional genomics gene therapy genetic disorder diagnosis genetic linkage analysis genetic variant genome editing genome wide association study genome-wide improved in vitro Assay in vitro testing interdisciplinary approach knockout gene meetings men mouse model multidisciplinary mutant mutant mouse model personalized medicine protein function protein protein interaction public health relevance reproductive sex sperm morphology web site

项目摘要

DESCRIPTION (provided by applicant): It is thought that nearly half of infertility cases have a genetic basis. Despite extensive knowledge gained from gene knockouts in mice, the genetic causes for the vast majority of idiopathic human infertilities are unknown. Traditional methods for studying inheritance, such as GWAS or linkage analysis, have been confounded by heterogeneity of infertility phenotypes and hundreds of genes involved in reproduction. Finally, we do not know the proportion of cases in which genetically-based infertilities are caused by de novo mutations vs. inheritance of alleles segregating in the human population. This project proposes a new, comprehensive, and multidisciplinary approach to this problem that will screen and identify nonsynonymous single nucleotide polymorphisms (nsSNPs) that functionally disrupt gametogenesis. The complementary expertise of two laboratories - one which has developed massively parallel in silico and in vitro methods to predict and validate disease-causing nsSNPs, and the other a leader in discovery and characterization of infertility genes using mouse mutant models - will together be brought together to bear on the problem. The Specific Aims are to: 1) Use computational approaches and high-throughput in vitro assays to identify nsSNPs in human infertility genes that are likely to disrupt protein function. These alleles will be precisely modeed in mice using CRISPR/Cas genome editing. 2) Phenotype the mouse models to identify those SNPs which impact gametogenesis and fertility. Overall, ~125 mouse models corresponding to nsSNPs in >300 known reproduction genes will be made. Already, 2 of 5 nsSNPs tested caused infertility. Establishing a database of experimentally-validated benign and deleterious SNPs in reproduction genes will revolutionize and empower the human reproductive genetics field as we enter the era of personalized medicine by improving the identification of causative alleles in exome-sequenced patients.

描述（由申请人提供）：据认为，近一半的不孕症病例有遗传基础。尽管从小鼠基因敲除中获得了广泛的知识，但绝大多数特发性人类不孕症的遗传原因尚不清楚。研究遗传的传统方法，如GWAS或连锁分析，已经被不育表型的异质性和数百个涉及生殖的基因所混淆。最后，我们不知道人类群体中由从头突变与等位基因分离遗传引起的遗传性不孕病例的比例。该项目提出了一种新的，全面的，多学科的方法来解决这个问题，将筛选和识别非同义单核苷酸多态性（nsSNPs），功能上破坏配子发生。两个实验室的互补专业知识-其中一个已经开发了大规模并行的计算机和体外方法来预测和验证致病nsSNP，另一个是使用小鼠突变模型发现和表征不育基因的领导者-将一起承担这个问题。具体目标是：1）使用计算方法和高通量体外测定来鉴定可能破坏蛋白质功能的人类不育基因中的nsSNP。这些等位基因将使用CRISPR/Cas基因组编辑在小鼠中精确地进行修饰。2)对小鼠模型进行表型分析，以确定影响配子发生和生育力的SNP。总体而言，将制备约125个对应于>300个已知生殖基因中的nsSNP的小鼠模型。已经有5个nsSNP中的2个导致了不育。建立生殖基因中实验验证的良性和有害SNP的数据库将彻底改变和赋予人类生殖遗传学领域，因为我们通过改善外显子组测序患者中致病等位基因的鉴定进入个性化医疗时代。