权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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：
10616671
负责人：
John C Schimenti
金额：
$ 60.85万
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 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10616671
关键词：
Address Affect Age Alleles Amino Acids Aneuploidy Benign Biochemical Biological Assay CRISPR/Cas technology Code Collection Computational Biology Computing Methodologies Couples DNA Sequence Alteration DNA sequencing Databases Defect Development Diagnosis Disease susceptibility Embryo Embryo Loss Embryonic Development Enhancers Exhibits Fertility Fertilization Frequencies Funding Gametogenesis Generations Genes Genetic Genetic Crossing Over Genetic Polymorphism Genetic Recombination Genetic Transcription Genetically Engineered Mouse Genome Genomic medicine Genomics Genotype-Tissue Expression Project Germ Cells Goals Health Hereditary Disease Heterogeneity Human Infertility Link Litter Size MLH1 gene Maintenance Meiosis Methodology Methods Minor Mismatch Repair Modeling Mus Mutant Strains Mice Mutation Nature Nucleic Acid Regulatory Sequences Ovarian Patients Persons Phenotype Population Pregnancy loss Privatization Probability Process Productivity Proteins Proteomics RNA Recurrence Regulatory Element Reporter Genes Reproduction Reproductive Health Resources Single Nucleotide Polymorphism Technology Testing Time Transcriptional Regulation Transgenic Mice Transgenic Organisms Untranslated RNA Validation Variant Women&apos s Health accurate diagnosis age related candidate selection cell type chromosome missegregation cost de novo mutation detection method exome sequencing experience genetic disorder diagnosis genetic pedigree genetic variant genome editing genome sequencing genome wide association study human model idiopathic infertility improved in vitro Assay in vivo innovation mouse model multidisciplinary novel offspring ovarian reserve personalized genomics primary ovarian insufficiency proband promoter protein function protein protein interaction reproductive segregation sex subfertility vector

项目摘要

Abstract Approximately 10% of people in the U.S. suffer from infertility, about half of whom are thought to have a genetic basis. However, the underlying causes remain undetermined in the great majority of patients. Traditional methods for identifying inherited disease loci, such as GWAS, have been confounded by heterogeneity of infertility phenotypes and the large numbers of genes involved in reproduction. Nevertheless, there are probably numerous “infertility” alleles segregating in populations, affecting diverse processes at all stages of gamete development. Our goal is to identify these alleles, their nature, and their in vivo impacts to reproduction. Under previous funding, we used a radically different approach to the problem that involved prediction and modeling of human coding variants biochemically and in mice. Here, we propose to employ innovative strategies for identifying and characterizing infertility variants (particularly SNPs) that segregate as minor alleles in populations. A multidisciplinary team with expertise in high-throughput genomics, reproductive genetics, proteomics, computational biology, and transcriptional regulation has been assembled to identify both protein-coding and regulatory variants affecting “fertility” genes. The Specific Aims are to: 1) Use computational approaches and high-throughput in vitro assays to identify nonsynonymous SNPs in human reproduction genes that are likely to disrupt protein function. These alleles will be precisely modeled in mice using CRISPR/Cas9 genome editing, and thoroughly phenotyped to inform patient diagnosis. 2) Exploit subfertile mouse models of human variants, exhibiting decreased chiasmata, to understand mechanisms of premature ovarian insufficiency (POI) and recurrent pregnancy loss. 3) Identify human germ cell regulatory variants via indentification of active (eRNA-transcribing) enhancers using ChRO-seq technology, followed by mouse transgenic assays. We will also identify eQTL residing in gametogenesis promoters by exploiting GTEx, high-throughput vector-building technology, and expression assays. Successful execution of this project would constitute the most comprehensive study ever conducted to identify and validate both coding and non-coding genetic variants in human populations that contribute to infertility in both sexes. Since the variants are carried by millions of people collectively, this project can have a major and lasting impact on the field of reproductive genetics in the precision genomics era.

摘要在美国，大约10%的人患有不孕症，其中大约一半被认为患有不孕症。遗传基础然而，在绝大多数患者中，根本原因仍不确定。用于鉴定遗传性疾病基因座的传统方法，如GWAS，已经被以下因素混淆：不育表型的异质性和大量的基因参与生殖。然而，尽管如此，种群中可能存在大量“不育”等位基因分离，影响不同的过程配子发育的阶段。我们的目标是识别这些等位基因、它们的性质以及它们的体内影响，生殖在以前的资助下，我们使用了一种完全不同的方法来解决这个问题，生物化学和小鼠中的人类编码变体的预测和建模。在这里，我们建议雇用用于识别和表征不育变体（特别是SNP）的创新策略，群体中的次要等位基因。一个多学科的团队，在高通量基因组学，生殖遗传学、蛋白质组学、计算生物学和转录调控已经组装起来，影响“生育力”基因的蛋白质编码和调节变体。具体目标是：（1）使用计算方法和高通量体外测定以鉴定人类中的非同义SNP 可能破坏蛋白质功能的生殖基因。这些等位基因将在小鼠中精确建模使用CRISPR/Cas9基因组编辑，并进行彻底的表型分析，以告知患者诊断。2)利用低生育力小鼠模型的人类变异，表现出减少交叉，以了解机制，卵巢功能不全（POI）和反复流产。3)鉴定人生殖细胞调节因子通过使用ChRO-seq技术鉴定活性（eRNA转录）增强子，小鼠转基因测定。我们还将通过利用GTEx鉴定位于配子发生启动子中的eQTL，高通量载体构建技术和表达测定。该项目的成功实施将是迄今为止进行的最全面的研究，识别和验证人群中的编码和非编码遗传变异，两性不育。由于变种是由数以百万计的人集体携带，这个项目可以有一个在精确基因组学时代对生殖遗传学领域产生了重大而持久的影响。