High-Throughput Native Context Mapping and Modeling of Regulatory DNA

监管 DNA 的高通量本地上下文映射和建模

基本信息

批准号：
9350382
负责人：
David K Gifford
金额：
$ 63.04万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-09 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9350382
关键词：
B-Cell Development Back Base Pairing Benchmarking Beta Cell Binding Biological Assay Biological Process Catalogs Cell physiology Cells Cellular biology Chromatin Chromosomes Clustered Regularly Interspaced Short Palindromic Repeats Computer Simulation Computing Methodologies DNA Data Dependence Developmental Gene Elements Enhancers Ensure Foundations Gene Expression Genes Genome Genomic Segment Genomics Genotype Goals Guide RNA Health Histones Human Human Genome In Situ Individual Length Letters Libraries Measures Methods Modeling Mutate Mutation Non-Insulin-Dependent Diabetes Mellitus Nucleic Acid Regulatory Sequences Oligonucleotides Performance Phenotype Predictive Factor Regulation Regulator Genes Regulatory Element Reporter Resolution Scanning System Testing Training Untranslated RNA Variant Viral Work base cell type experimental study gene function genome editing genome wide association study genomic variation high throughput screening homologous recombination improved loss of function novel predictive modeling repaired success transcriptome transcriptome sequencing whole genome

项目摘要

Project Summary We propose to systematically investigate and characterize sequence elements that are necessary for genome function in their native context in contrast to existing high- throughput assays of genome function that detect sequence elements that are sufficient for function. We will accomplish this goal with three specific aims. We will develop a novel Multiplexed Editing Regulatory Assay (MERA) to test the effect of thousands of targeted mutations in native regulatory regions in a single experiment (Aim 1). We will use MERA to characterize the regulation of key developmental genes, the function of selected regulatory elements, and the gene expression effects of SNPs that are discovered in GWAS studies (Aim 2). Using these data we will build a model that will allow us to predict the bases that comprise the necessary genome and estimate the effect of non-coding genotype on gene expression (Aim 3). Through our new experimental and computational method we will help lay the groundwork for a novel paradigm in revealing the effect of human variation at base pair resolution.

项目摘要我们建议系统地研究并表征基因组功能在其本地背景下所必需的，与现有的高检测到足够的序列元素的基因组功能的吞吐量测定用于功能。我们将以三个特定的目标来实现这一目标。我们将发展一个新型的多重编辑调节测定（MERA）测试数千在单个实验中，天然调节区域的靶向突变（AIM 1）。我们将使用Mera来表征关键发育基因的调节，该基因的功能选定的调节元素以及SNP的基因表达效应在GWAS研究中发现（AIM 2）。使用这些数据，我们将构建一个模型，将允许我们预测构成必要基因组的基础并估计非编码基因型对基因表达的影响（AIM 3）。通过我们的新实验和计算方法，我们将帮助为新颖的基础奠定基础在揭示基本对分辨率下人类变异的影响方面的范式。