UCLA IDDRC: Functional Genomics and Genetics Core

加州大学洛杉矶分校 IDDRC：功能基因组学和遗传学核心

基本信息

批准号：
10085983
负责人：
Michael Gandal
金额：
$ 10.5万
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：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10085983
关键词：
ATAC-seq Animal Model Atlases Automobile Driving Basic Science Bioinformatics Biological Assay Brain Cell Nucleus Cell model Cells Chromatin Clinical Collaborations Computerized Medical Record Data Data Analyses Data Set Data Storage and Retrieval Database Management Systems Databases Development Environment Epigenetic Process Equipment and supply inventories Experimental Designs Experimental Models Explosion Foundations Funding Gene Expression Gene Expression Profiling Genes Genetic Genetic study Genome Genomic approach Genomics Genotype Goals High Performance Computing Human Informatics Infrastructure Institution Intellectual and Developmental Disabilities Research Centers Investigation Journals Knowledge Laboratories Lead Medical Genetics Methods Methylation Modernization Nature Network-based Neurons Neurosciences Online Systems Paper Pathway Analysis Patients Phenotype Postdoctoral Fellow Pregnancy Privatization Process Protocols documentation Publications Publishing Quantitative Trait Loci RNA Splicing Recording of previous events Regulatory Element Research Research Design Research Personnel Resolution Resource Informatics Resources Running Science Services Solid Students Study models Technology Training Translational Research United States National Institutes of Health Untranslated RNA Update Validation Walkers Work analysis pipeline analytical method base cohort computing resources data access data mining data sharing design exome sequencing experience experimental analysis experimental study fetal functional genomics genetic approach genome-wide genomic data innovation multiple datasets neurogenesis neuroimaging new technology next generation sequencing polygenic risk score single cell analysis single-cell RNA sequencing student training tool transcriptome sequencing translational genetics translational study web-based tool

项目摘要

CORE C: Abstract The Genetics, Genomics, and Informatics Core (GGIC) focuses on the application of genome- level analyses in neuroscientific investigation, both at the sequence (genetic), gene expression and epigenetic (genomics) levels. The explosion of next-generation sequencing (NGS)-based methods has made advanced computational expertise and infrastructure needed for all sequencing-based applications. The proposed Core aims at providing support for basic and advanced genetics and genomics experiments in both patient cohorts for translational studies and experimental models for basic research. Modern genetic and genomic approaches rely on sequencing technology and require substantial bioinformatics expertise and access to solid computational resources. This Core leverages a proven history of expertise, as well as support and collaboration with other investigators in the Gandal and Geschwind groups with regards to computational and informatics resources funded by NIH and private foundations. Based on this proven track record, the Core will provide IDDRC investigators with the necessary expertise and infrastructure to perform high-throughput, genome-wide genetic and genomic studies. State-of- the-art analytical methods will be used to analyze NGS, gene expression, chromatin accessibility (e.g., ATAC-seq), methylation, and single cell/nucleus scRNA-seq data, and the resulting datasets will be posted onto a database accessible to IDDRC investigators, facilitating data sharing and collaborative analyses. Over the past 15 years, UCLA computational biologists and statisticians have lead the field of integrative data analysis (Geschwind and Konopka, 2009) and network-based methods (Oldham et al., 2008; Parikshak et al., 2013; Zhang and Horvath, 2005). Further, over the past 5 years, IDDRC investigators have published pioneering work interrogating the functional genomic landscape of human brain development, including the first comprehensive atlas of single-cell gene expression in the mid-gestation human brain (Polioudakis et al., 2019), high-resolution mapping of non-coding regulatory elements driving human neurogenesis with ATAC-seq (de La Torre Ubieta et al, 2018), and large-scale expression and splicing quantitative trait loci (QTL) profiling in fetal brain (Walker et al., 2019). Expertise in the development and implementation of these methods (including single-cell analysis, network methods, and integrative approaches) will be made directly available to IDDRC investigators.

核心 C：摘要遗传学、基因组学和信息学核心（GGIC）专注于基因组学的应用神经科学研究中的水平分析，包括序列（遗传）、基因表达和表观遗传（基因组学）水平。基于下一代测序 (NGS) 的爆炸式增长方法已经为所有人提供了所需的先进计算专业知识和基础设施基于测序的应用。拟议的核心旨在为基本和在两个患者队列中进行先进的遗传学和基因组学实验，以进行转化研究和基础研究的实验模型。现代遗传学和基因组方法依赖于测序技术，需要大量的生物信息学专业知识和可靠的信息计算资源。该核心利用了久经考验的专业知识以及支持以及与 Gandal 和 Geschwind 小组的其他研究人员在以下方面的合作：由 NIH 和私人基金会资助的计算和信息学资源。基于此良好的记录，核心将为 IDDRC 调查人员提供必要的专业知识和进行高通量、全基因组遗传和基因组研究的基础设施。状态- 最先进的分析方法将用于分析NGS、基因表达、染色质可及性（例如，ATAC-seq）、甲基化和单细胞/核 scRNA-seq 数据，以及所得结果数据集将发布到 IDDRC 调查人员可访问的数据库中，以方便数据处理共享和协作分析。在过去的 15 年里，加州大学洛杉矶分校的计算生物学家和统计学家在综合数据分析领域处于领先地位（Geschwind 和 Konopka，2009 年）基于网络的方法（Oldham 等人，2008；Parikshak 等人，2013；Zhang 和 Horvath，2005）。此外，在过去 5 年里，IDDRC 调查人员发表了开创性的著作，审问人类大脑发育的功能基因组景观，包括第一个全面的妊娠中期人脑单细胞基因表达图谱（Polioudakis et al., 2019），驱动人类神经发生的非编码调控元件的高分辨率图谱 ATAC-seq (de La Torre Ubieta et al, 2018)，以及大规模表达和剪接定量胎儿大脑中的性状基因座 (QTL) 分析 (Walker et al., 2019)。开发和开发方面的专业知识这些方法的实施（包括单细胞分析、网络方法和综合方法）方法）将直接提供给 IDDRC 调查人员。