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Identification and Functional Validation of Human Infertility Alleles

Identification and Functional Validation of Human Infertility Alleles
人类不育等位基因的鉴定和功能验证
批准号:
10224949
负责人:
John C Schimenti
金额:
$60.85万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
未结题
起止时间:
2015-09-01 至 2025-04-30
关键词:
AddressAffectAgeAllelesAmino AcidsAneuploidyBenignBiochemicalBiological AssayCRISPR/Cas technologyCodeCollectionComputational BiologyComputing MethodologiesCouplesDNA Sequence AlterationDNA sequencingDatabasesDefectDevelopmentDiagnosisDisease susceptibilityEmbryoEmbryo LossEmbryonic DevelopmentEnhancersExhibitsFertilityFertilizationFrequenciesFundingGametogenesisGenerationsGenesGeneticGenetic PolymorphismGenetic RecombinationGenetically Engineered MouseGenomeGenomic medicineGenomicsGenotype-Tissue Expression ProjectGerm CellsGoalsHealthHereditary DiseaseHeterogeneityHumanInfertilityLinkLitter SizeMLH1 geneMaintenanceMeiosisMethodologyMethodsMinorMismatch RepairModelingMusMutant Strains MiceMutationNatureNucleic Acid Regulatory SequencesOvarianPatientsPhenotypePlant RootsPopulationPregnancy lossPrivatizationProcessProteinsProteomicsRNARecurrenceRegulatory ElementReporterReproductionReproductive HealthResourcesSingle Nucleotide PolymorphismSumTechnologyTestingTimeTranscriptional RegulationTransgenic MiceTransgenic OrganismsUntranslated RNAValidationVariantWomen&aposs Healthaccurate diagnosisage relatedbasecell typechromosome missegregationcostde novo mutationexome sequencingexperiencegenetic disorder diagnosisgenetic pedigreegenetic variantgenome editinggenome sequencinggenome wide association studyhuman modelidiopathic infertilityimprovedin vitro Assayin vivoinnovationmouse modelmultidisciplinarynoveloffspringovarian reservepredictive modelingprimary ovarian insufficiencyprobandpromoterprotein functionprotein protein interactionreproductivesexsubfertilityvector

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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.
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Mechanisms underlying sex-dependent pregnancy outcomes caused by fetal and maternal genomic instability
  • 批准号:
    10391992
  • 项目类别:
  • 资助金额:
    $34.65万
  • 财政年份:
    2022
  • 负责人:
    John C Schimenti
  • 依托单位:
Mechanisms underlying sex-dependent pregnancy outcomes caused by fetal and maternal genomic instability
  • 批准号:
    10704495
  • 项目类别:
  • 资助金额:
    $34.63万
  • 财政年份:
    2022
  • 负责人:
    John C Schimenti
  • 依托单位:
Genetics and Proteomics of Mouse Egg Activation
  • 批准号:
    10366090
  • 项目类别:
  • 资助金额:
    $23.46万
  • 财政年份:
    2021
  • 负责人:
    John C Schimenti
  • 依托单位:
Genetics and Proteomics of Mouse Egg Activation
  • 批准号:
    10209649
  • 项目类别:
  • 资助金额:
    $19.45万
  • 财政年份:
    2021
  • 负责人:
    John C Schimenti
  • 依托单位:
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