Illuminating the distribution of extreme evolutionary constraint in the human genome from fetal demise to severe developmental disorders
阐明人类基因组中从胎儿死亡到严重发育障碍的极端进化限制的分布
基本信息
- 批准号:10601318
- 负责人:
- 金额:$ 4.05万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-01-01 至 2025-12-31
- 项目状态:未结题
- 来源:
- 关键词:AtlasesAutomobile DrivingAutopsyBiologicalBirthCellsChildhoodChromatinClinicalCodeDataData SetDevelopmentDevelopmental ProcessDisciplineDiseaseDisease modelDoctor of PhilosophyEtiologyExhibitsFamily memberFellowshipFertilityFetal DeathFetusFirst Pregnancy TrimesterGene DosageGene FrequencyGeneral PopulationGenesGenetic Predisposition to DiseaseGenetic RiskGenetic TranscriptionGenetic VariationGenetic studyGenomeGenomic SegmentGenomicsHumanHuman DevelopmentHuman GenomeIndividualInheritedInstitutionInternationalLaboratoriesMaternal-fetal medicineMeasuresMentorsMentorshipMusMutationNatural SelectionsNeurodevelopmental DisorderOutcomeParentsPathway interactionsPatternPlayPoint MutationPopulationPositioning AttributePropertyPublishingRecurrenceRegulatory ElementResearchResearch SupportResourcesRisk FactorsRoleSamplingSourceStatistical ModelsStructural defectTestingTrainingUntranslated RNAVariantWorkbasecareercell typecohortcongenital anomalydevelopmental diseaseexomefetalfetal lossgene discoverygene functiongenetic architecturegenome sequencinggenome-widegenomic variationhands on researchinsertion/deletion mutationinsightlaboratory experienceloss of functionnovelprogramsprotein protein interactionpurgereproductivesexskill acquisitionstillbirthsymposiumtooltraining opportunitywhole genome
项目摘要
Abstract
Natural selection purges deleterious mutations from populations in genomic regions impacting survival or
reproductive capacity. Recent genetic studies of massive population cohorts have revealed a continuous
distribution across the human genome of this constraint on deleterious mutations. Large-scale association
studies have found mutations in strongly constrained genomic regions to be major risk factors in many childhood
developmental disorders (DDs), suggesting that highly constrained sequences are likely to play key roles in
development. However, genetic studies of fetal demise after the first trimester (FD), an extreme outcome of DDs,
have thus far been limited in scope and size. The establishment by my mentors of an international Fetal
Genomics Consortium to sequence 10,500 samples (3,500 FD cases and their family members) ascertained for
FD of suspected genetic etiology now offers an unprecedented opportunity to illuminate the most extreme
consequences of mutation across individual genes and dosage sensitive genomic segments critical for human
development. In this fellowship, I will integrate whole-genome sequencing and autopsy data from this cohort
together with data from previously established DD cohorts to discover and functionally characterize mutationally
intolerant loci in the human genome. I will first define patterns of genetic variation in FD across constraint metrics
(loss-of-function, missense, and noncoding) and genomic variation classes (point mutations, indels, structural
variants, and repeat expansions), and investigate biases in these patterns with respect to fetal sex and mutational
parent-of-origin. I will then adapt a statistical framework for disease association capable of integrating evidence
from all coding and noncoding variant classes with prioritization of constrained regions, which I will apply to
perform novel gene discovery in FD (Aim 1). I will leverage these findings to generate functional predictions of
mutationally intolerant loci by defining the biological networks of activity and the cell types in which they are likely
to operate early in development (Aim 2). Finally, I will test these functional hypotheses across DDs that do not
result in FD, including liveborn fetal structural abnormalities, neurodevelopmental disorders, and congenital
anomalies (Aim 3). In parallel with these research aims, an exceptional team of six mentors and advisors across
multiple disciplines, career stages, and institutions will provide didactic training, hands-on research support,
regular opportunities for presentation in seminars and conferences, and a variety of soft skill development
sessions that directly align with my career objectives during my PhD training. Collectively, the aims outlined in
this proposal will take advantage of unique tools and resources to yield novel insights into the etiology of the
extremes along the continuum of developmental anomalies and evolutionary constraint, and will serve as an
outstanding training opportunity for me in computational, statistical, and functional disease genomics.
摘要
自然选择从影响生存或死亡的基因组区域的群体中清除有害突变。
生殖能力最近对大规模人群队列的遗传学研究揭示了一种持续的
这种对有害突变的限制在整个人类基因组中的分布。大型协会
研究发现,在许多儿童中,基因组区域的突变是主要的危险因素。
发育障碍(DDs),这表明高度限制的序列可能在发育障碍中发挥关键作用。
发展然而,对前三个月(FD)后胎儿死亡的遗传研究,这是DD的一个极端结果,
到目前为止,在范围和规模上都是有限的。我的导师们建立了一个国际胎儿
基因组学联盟将对10,500个样本(3,500个FD病例及其家庭成员)进行测序,
疑似遗传病因的FD现在提供了一个前所未有的机会来阐明最极端的
个体基因突变的后果和对人类至关重要的剂量敏感基因组片段
发展在这个奖学金中,我将整合来自这个队列的全基因组测序和尸检数据,
与来自先前建立的DD队列的数据一起,以发现和功能性表征突变
人类基因组中的不耐受位点。我将首先定义FD中跨约束度量的遗传变异模式
(功能丧失、错义和非编码)和基因组变异类别(点突变、插入缺失、结构突变)。
变异和重复扩增),并调查这些模式中关于胎儿性别和突变的偏倚。
原始父母然后,我将采用一个能够整合证据的疾病关联统计框架
从所有编码和非编码变体类与约束区域的优先级,我将适用于
在FD中进行新基因发现(目标1)。我将利用这些发现来产生功能预测,
通过定义生物活性网络和它们可能存在的细胞类型,
在开发早期运行(目标2)。最后,我将在不具备这些功能的DD中测试这些功能假设。
导致FD,包括活产胎儿结构异常,神经发育障碍和先天性
异常(目标3)。在这些研究目标的同时,一个由六位导师和顾问组成的特殊团队,
多学科,职业阶段和机构将提供教学培训,动手研究支持,
定期在研讨会和会议上发言的机会,以及各种软技能的发展
这些课程与我在博士培训期间的职业目标直接相关。总的来说,
这项提案将利用独特的工具和资源,对糖尿病的病因学产生新的见解。
沿着发展异常和进化限制的连续性的极端,并将作为一个
在计算、统计和功能性疾病基因组学方面给了我一个极好的培训机会。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Lily Wang其他文献
Lily Wang的其他文献
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{{ truncateString('Lily Wang', 18)}}的其他基金
New computational tools for understanding and predicting AD via age-associated DNA methylation changes
通过与年龄相关的 DNA 甲基化变化来理解和预测 AD 的新计算工具
- 批准号:
10509428 - 财政年份:2022
- 资助金额:
$ 4.05万 - 项目类别:
New statistical strategies for comprehensive analysis of epigenomewide methylation data
表观基因组甲基化数据综合分析的新统计策略
- 批准号:
9763421 - 财政年份:2018
- 资助金额:
$ 4.05万 - 项目类别:
Integrative statistical models for pathway analysis of GWAS data
GWAS 数据路径分析的综合统计模型
- 批准号:
9187527 - 财政年份:2013
- 资助金额:
$ 4.05万 - 项目类别:
Integrative statistical models for pathway analysis of GWAS data
GWAS 数据路径分析的综合统计模型
- 批准号:
8241543 - 财政年份:2013
- 资助金额:
$ 4.05万 - 项目类别:
Integrative statistical models for pathway analysis of GWAS data
GWAS 数据路径分析的综合统计模型
- 批准号:
8654353 - 财政年份:2013
- 资助金额:
$ 4.05万 - 项目类别:
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS Data
通过 RNA-seq 和 GWAS 数据绘制复杂疾病的遗传结构
- 批准号:
8658841 - 财政年份:2012
- 资助金额:
$ 4.05万 - 项目类别:
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS Data
通过 RNA-seq 和 GWAS 数据绘制复杂疾病的遗传结构
- 批准号:
8217762 - 财政年份:2012
- 资助金额:
$ 4.05万 - 项目类别:
Understanding Genetic Basis of Dental Caries via Integrative Genomic Approaches
通过综合基因组方法了解龋齿的遗传基础
- 批准号:
8320126 - 财政年份:2011
- 资助金额:
$ 4.05万 - 项目类别:
Understanding Genetic Basis of Dental Caries via Integrative Genomic Approaches
通过综合基因组方法了解龋齿的遗传基础
- 批准号:
8176915 - 财政年份:2011
- 资助金额:
$ 4.05万 - 项目类别:
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