Dissecting and reconstructing the molecular roadmaps of cellular reprogramming to iPSCs in single-cell resolution

以单细胞分辨率剖析和重建 iPSC 细胞重编程的分子路线图

基本信息

  • 批准号:
    10535468
  • 负责人:
  • 金额:
    $ 23.58万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

Project Summary Understanding the molecular programs that guide cell fate conversion will provide a foundation for the development of tools to convert cell fate and eventually facilitate the generation of therapeutically relevant cell types. Experimental approaches to understand such mechanisms have typically involved studying bulk populations. These experiments are severely limited because they can only measure averaged effects. Recently, large-scale profiling of single cells has opened new prospects for systematically dissecting the processes underlying cell fate conversion. However, proper analysis of large-scale single cell data remains a challenge. To combat this, we developed experimental and computational approaches to study scRNA-seq data from 65,781 cells collected at 10 time points over 16 days during the reprogramming of fibroblasts to iPSCs by Oct4, Sox2, Klf4, and cMyc. In my K99/R00 proposal, I hypothesize that dissecting complex reprogramming processes in single-cell resolution will help us understand the mechanisms of reprogramming for iPSCs, identify novel reprogramming factors that can enhance reprogramming efficiency and generate high- quality iPSCs that can be used in clinical settings. I propose to 1) characterize the role of candidate reprograming factors (K99); 2) validate the reprogramming trajectory predicted from single-cell RNA- seq data by lineage tracing (K99); 3) investigate the reprogramming process through comparison of different cocktails (K99/R00); 4) develop new methods to enhance cell fate conversion (R00). Together, the proposed aims will have a broad impact on the journey to understand developmental processes and provide rich resources for the scientific community. In the long term, these studies may reveal novel strategies to generate therapeutically relevant cells. To succeed in these proposed aims, I will need additional training in computational analysis and stem cell research, supported by my co-mentors Dr. Eric Lander (genetics and genomics) and Dr. Rudolf Jaenisch (stem cells and genome engineering) as well as an Advisory Committee including Dr. Aviv Regev (computational biology and single-cell techniques), Dr. Feng Zhang (genome engineering). My career development plan integrates practical training in computational and experimental tools as well as trainings in communication, management, mentorship, grant writing, etc. The Broad Institute is an ideal environment, providing all of the facilities needed for the proposed research and a rich interdisciplinary environment. With these additional skills gained through support by the NIH K99/R00 Pathway to Independence Award, I will be qualified to execute these goals to make great strides at the interface of stem cell research and single-cell techniques.
项目总结

项目成果

期刊论文数量(1)
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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Jian Shu其他文献

Jian Shu的其他文献

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{{ truncateString('Jian Shu', 18)}}的其他基金

Scale up single-cell technologies to map pain-associated genes and cells across the lifespan
扩大单细胞技术的规模,绘制整个生命周期中与疼痛相关的基因和细胞图谱
  • 批准号:
    10580155
  • 财政年份:
    2022
  • 资助金额:
    $ 23.58万
  • 项目类别:
Dissecting and reconstructing the molecular roadmaps of cellular reprogramming to iPSCs in single-cell resolution
以单细胞分辨率剖析和重建 iPSC 细胞重编程的分子路线图
  • 批准号:
    10320077
  • 财政年份:
    2021
  • 资助金额:
    $ 23.58万
  • 项目类别:
Dissecting and reconstructing the molecular roadmaps of cellular reprogramming to iPSCs in single-cell resolution
以单细胞分辨率剖析和重建 iPSC 细胞重编程的分子路线图
  • 批准号:
    10301498
  • 财政年份:
    2021
  • 资助金额:
    $ 23.58万
  • 项目类别:
Dissecting and reconstructing the molecular roadmaps of cellular reprogramming to iPSCs in single-cell resolution
以单细胞分辨率剖析和重建 iPSC 细胞重编程的分子路线图
  • 批准号:
    9765363
  • 财政年份:
    2018
  • 资助金额:
    $ 23.58万
  • 项目类别:

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