Leveraging genetic variation to dissect gene regulatory networks of reprogramming to pluripotency

利用遗传变异剖析重编程为多能性的基因调控网络

基本信息

批准号：
10473738
负责人：
Chongyuan Luo
金额：
$ 135.13万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
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：
2021-09-01 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10473738
关键词：
ATAC-seq Affect Alleles Architecture Binding Biological Biological Assay CRISPR interference Candidate Disease Gene Cell Differentiation process Cell Line Cell Nucleus Cells Cellular Morphology ChIP-seq Chromatin Clustered Regularly Interspaced Short Palindromic Repeats Computer Models Consensus Cytosine DNA Methylation Data Data Set Disease model Drug Screening Due Process Enhancers Event Fibroblasts Gene Expression Gene Expression Regulation Genes Genetic Genetic Engineering Genetic Transcription Genetic Variation Genome Genomics Goals Heterogeneity Human Human Genetics Human Genome In Situ Individual Joints Knowledge Maintenance Maps Measurement Mediating Methods Methylation Modeling Molecular Molecular Conformation Mouse Strains Multiomic Data Nature Patients Phenotype Population Population Genetics Process Quantitative Trait Loci RNA RNA methylation Regenerative Medicine Regulation Regulator Genes Regulatory Element Resolution Resources Role Series Site Somatic Cell Specificity Statistical Methods System Testing Therapeutic Time Untranslated RNA Variant Work base c-myc Genes causal variant cell type embryonic stem cell epigenome epigenomics experimental study gene interaction gene regulatory network genetic variant genome sequencing genomic data histone modification induced pluripotent stem cell innovation insight molecular phenotype multiple omics novel pluripotency predictive modeling programs repaired single-cell RNA sequencing stem cells transcription factor transcriptional reprogramming transcriptome transcriptomics whole genome

项目摘要

PROJECT SUMMARY The reprogramming of somatic human cells to induced pluripotent stem cells (iPSCs) by only four transcription factors (TFs) Oct4, Sox2, Klf4, and cMyc (OSKM) is one of the most striking remodelings of gene regulatory networks. The remarkable ability of OSKM to reprogram diverse somatic cell types into iPSCs that are functionally indistinguishable from embryonic stem cells indicates that OSKM leverages a fundamental mechanism for network remodeling that may be generally applicable to all cell fate transitions. Previous studies of reprogramming have identified the crucial role of cooperative TF binding in repressing somatic programs and activating pluripotent ones. However, associating TF binding dynamics and epigenomic remodeling with key bifurcation events during reprogramming is confounded by the highly heterogeneous nature of the reprogramming process and the lack of knowledge regarding how the transition from somatic to pluripotent regulatory programs occurs in individual cells. In this project, we aim to model the regulatory network underlying the cell fate change of reprogramming using three types of single-cell multi-omic profiles generated from critical time points during reprogramming. We will interrogate the network leveraging natural perturbation of reprogramming and pluripotency by genetic variants. Genetic variation is well known to modulate the regulatory network of pluripotency and contributes to the variability of cellular phenotypes and differentiation capacity of iPSC lines. We will generate population-scale single-cell joint profiling of RNA and DNA methylation (snmCT- seq), joint profiling of RNA and chromatin accessibility (scRNA + ATAC-seq) and single-nucleus joint profiling of chromatin conformation and DNA methylation (sn-m3C-seq), allowing the cell-type-specific determination of transcriptome, chromatin accessibility and methylation states at regulatory elements, as well as enhancer-gene looping to connect non-coding variants to their regulatory target. To integrate OSKM binding with the single-cell transcriptomic and epigenomic dynamics, we will determine the allele-specific binding of TFs and histone modifications using a pooled-alleles ChIP-seq strategy. We will use Dynamic Regulatory Events Miner (DREM) to construct predictive models by integrating transcription factor-gene interaction information with time- and pseudotime-series genomics data. To determine the genetic regulation of the reprogramming network, we will apply the novel statistical method FastGxE to distinguish cell-type-specific from the shared genetic component of gene expression regulation, to enhance the sensitivity for identifying cell-type-specific quantitative trait loci (QTLs). To test the regulatory network, we will experimentally determine the function of network hub genes and non-coding variants using high-throughput CRISPR interference and precise variant replacement experiments. Our proposed project integrates diverse approaches including single-cell multi-omics, computational modeling, and genetic engineering, and will likely provide new insights into the mechanism by which TFs remodel regulatory networks of cell type identity and serve as a model for similar analyses in other systems.

项目摘要仅通过四个转录将体细胞重编程为诱导多能干细胞（IPSC）的重新编程因素（TFS）OCT4，SOX2，KLF4和CMYC（OSKM）是基因调节的最引人注目的重塑之一网络。 OSKM能够将各种体细胞类型重新编程为IPSC的显着能力在功能上与胚胎干细胞无法区分，表明OSKM利用了基本网络重塑的机制通常适用于所有细胞命运过渡。先前的研究重编程已经确定了合作TF结合在压制躯体程序和激活多能。但是，将TF结合动力学和表观基因组重塑与键关联重新编程期间的分叉事件与高度异质性质混淆重新编程过程以及缺乏有关如何从躯体到多能的过渡的知识调节程序发生在单个细胞中。在这个项目中，我们旨在对基础监管网络进行建模细胞命运使用从关键产生的三种类型的单细胞多摩变轮廓进行重新编程的变化重新编程期间的时间点。我们将询问利用自然扰动的网络通过遗传变异的重新编程和多能性。众所周知，遗传变异可以调节调节多能性网络，并有助于细胞表型的变异性和分化能力 IPSC线。我们将产生RNA和DNA甲基化的种群尺度单细胞关节分析（SNMCT- SEQ），RNA和染色质可及性（SCRNA + ATAC-SEQ）的关节分析和单核关节分析染色质构象和DNA甲基化（SN-M3C-Seq），允许细胞类型的特异性测定调节元素处的转录组，染色质可及性和甲基化状态以及增强子基因循环以将非编码变体连接到其调节目标。将OSKM结合与单细胞结合转录组和表观基因组动力学，我们将确定TFS和组蛋白的等位基因特异性结合使用合并的芯片序列策略进行修改。我们将使用动态调节活动矿工（DREM）通过将转录因子 - 基因相互作用信息与时间和时间和时间和时间和时间整合在一起来构建预测模型伪系列基因组学数据。为了确定重编程网络的遗传调节，我们将应用新颖的统计方法FastGXE将细胞类型特异性与共享遗传成分区分开基因表达调控的，以增强识别细胞类型特异性定量特征基因座的灵敏度（QTL）。为了测试监管网络，我们将通过实验确定网络中心基因的功能和使用高通量CRISPR干扰和精确变体替换实验的非编码变体。我们提议的项目整合了各种方法和基因工程，并可能会提供有关TFS重塑调节的机制的新见解细胞类型身份的网络，并作为其他系统中类似分析的模型。