Linking GWAS variants to function with single-cell pooled CRISPR screens

将 GWAS 变体与单细胞 CRISPR 筛选结合起来发挥作用

基本信息

  • 批准号:
    10571493
  • 负责人:
  • 金额:
    $ 10.56万
  • 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:
    2023-02-16 至 2025-01-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY/ABSTRACT Genome-wide association studies (GWAS) have identified thousands of common and rare genetic variants associated with complex traits and common diseases. Most variants map to the 98% of the genome that is noncoding, with their target genes or function largely unknown. This is the variant-to-function problem (V2F), and solving it remains a major hurdle in human genetics research. To help solve V2F, I propose to develop modular workflows combining GWAS variant prioritization methods and pooled single-cell CRISPR screens for target gene identification. I have developed an integrative approach combining highly polygenic blood trait GWASs and pooled single-cell CRISPR inhibition (CRISPRi) screens in a human erythroid progenitor cell model (K562), to identify target genes: Systematic Targeting and Inhibition of Noncoding GWAS loci with single-cell sequencing (STING-seq). STING-seq can functionally dissect multiple GWAS loci in a massively parallel fashion, identifying target genes in cis as well as trans-regulatory networks. Here, I will develop STING-seq further and examine its generalizability for other GWAS traits and their cell models. First, I will expand STING-seq with precise variant insertion, developing base editing STING-seq (Bee-STING) for high-throughput measurements of GWAS variant effects on target genes and regulatory networks. Second, I will develop modular workflows for GWAS variant prioritization for STING-seq, targeting sets of variants with distinct selection criteria to increase STING-seq’s target gene and regulatory network discovery rate. Third, I will focus STING-seq on new GWAS traits and cell models to examine its generalizability, first piloting STING-seq for another highly polygenic complex trait, bone mineral density, with a human osteoblast cell model (hFOB). In the long-term, these aims will help solve V2F for human genetics research, as their continued development and application will improve our understanding of how GWAS variants causally influence complex traits and common diseases. I have a comprehensive training plan in place with my primary mentors, Dr. Neville Sanjana (genome engineering) and Dr. Tuuli Lappalainen (gene regulation), my mentorship committee members, Dr. David Knowles (machine learning), Dr. Aravinda Chakravarti (human genetics), Dr. Charles Farber (bone biology), and my collaborator Dr. Eugene Katsevich (statistical methods). This plan will continue my training in dissecting GWAS variant function with multiple computational and experimental approaches, along with additional training in grant writing, mentoring students, teaching courses, and presenting at research conferences. The full mentorship committee will direct me to pertinent literature, offer advice on my research program, and provide guidance as I navigate the academic job market. The New York Genome Center is the ideal training location for me, given its cutting-edge facilities, plentiful opportunities for career and intellectual development, and collaborative research environment. Upon completion of this training program, I will be well-positioned to lead my own interdisciplinary research lab and become a leader in the fields of human complex traits genetics and genome engineering.
项目摘要/摘要 全基因组关联研究已经确定了数千种常见和罕见的遗传变异。 与复杂的特征和常见疾病有关。大多数变异映射到98%的基因组,即 非编码,其目标基因或功能基本未知。这是变量到函数的问题(V2F),以及 解决这个问题仍然是人类遗传学研究中的一个主要障碍。为了帮助解决V2F,我建议开发模块化的 将GWAS不同的优先排序方法和目标的池化单单元CRISPR屏幕相结合的工作流 基因鉴定。我已经开发出一种综合方法,将高度多基因的血液性状GWASs和 联合单细胞CRISPR抑制(CRISPRi)在人红系祖细胞模型(K562)中的筛选,以 识别靶基因:用单细胞测序系统靶向和抑制非编码GWA基因座 (STING-SEQ)。STING-SEQ可以以大规模并行的方式在功能上剖析多个GWAS基因座,识别 顺式调节基因和跨调控网络中的靶基因。在这里,我将进一步开发SING-SEQ,并研究其 其他GWAs性状及其细胞模型的概括性。首先,我将用精确的变量来扩展SING-SEQ 插入、形成碱基编辑序列(BEE-STING),用于高通量测量GWA变异体 对靶基因和调控网络的影响。其次,我将为GWAS变体开发模块化的工作流 确定SING-SEQ的优先顺序,以具有不同选择标准的变种集合为目标,以增加SING-SEQ 靶基因和调控网络发现率。第三,我将把重点放在新的GWAS特征和细胞上 检验其普适性的模型,首先对另一种高度多基因的复杂性状--骨骼--进行试验 矿物质密度,与人类成骨细胞模型(HFOB)。从长远来看,这些目标将有助于解决V2F 人类遗传学的研究,随着它们的不断发展和应用,将提高我们对 GWA型变异对复杂性状和常见疾病有因果影响。我有一个全面的训练计划 与我的主要导师,内维尔·桑贾纳博士(基因组工程学)和图利·拉帕莱宁博士(基因 法规),我的导师委员会成员,David Knowles博士(机器学习),Aravinda博士 Chakravarti博士(人类遗传学)、Charles Farber博士(骨骼生物学)和我的合作者Eugene Katsevich博士 (统计方法)。这项计划将继续我的训练,解剖具有多个 计算和实验方法,以及额外的拨款编写培训,指导学生, 教授课程,并在研究会议上发表演讲。整个指导委员会将指导我 相关文献,就我的研究计划提供建议,并在我从事学术工作时提供指导 市场。纽约基因组中心是我理想的培训地点,因为它拥有尖端的设施, 丰富的职业和智力发展机会,以及协作研究环境。vt.在.的基础上 完成这一培训计划后,我将能够领导自己的跨学科研究实验室,并 成为人类复杂性状遗传学和基因组工程领域的领导者。

项目成果

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