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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：
10385752
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/10385752
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 Polymorphism Genetic Recombination 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 Plant Roots Population Pregnancy loss Privatization Process Proteins Proteomics RNA Recurrence Regulatory Element Reporter Reproduction Reproductive Health Resources Single Nucleotide Polymorphism Sum Technology Testing Time Transcriptional Regulation Transgenic Mice Transgenic Organisms Untranslated RNA Validation Variant Women&apos s Health accurate diagnosis age related base cell type chromosome missegregation cost de novo mutation 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 predictive modeling primary ovarian insufficiency proband promoter protein function protein protein interaction reproductive 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