Functionally relevant mapping of human GWAS SNPs on model organisms

人类 GWAS SNP 在模式生物上的功能相关图谱

基本信息

批准号：
10056966
负责人：
Sunduz Keles
金额：
$ 40.05万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
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：
2020-08-06 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10056966
关键词：
Address Animal Model Binding Sites Biological CRISPR/Cas technology Cells ChIP-seq Characteristics Chromatin Collaborations Computer Analysis Computer software Data Development Disease Engineering Event Exhibits Genes Genome Genome engineering Genomics Hematology Human Human Genome Joints Lifting Ligation Link Location Maps Mediating Metabolic syndrome Methodology Methods Modeling Molecular Mus Neurologic Non-Insulin-Dependent Diabetes Mellitus Obesity Pattern Process Publications Quantitative Trait Loci Regulatory Element Research Personnel Resources Single Nucleotide Polymorphism Statistical Models System Time Tissues Untranslated RNA Validation Variant analytical tool autism spectrum disorder base cell type chromosome conformation capture clinical phenotype comparative comparative genomics epigenome epigenomics experimental study follow-up genome editing genome wide association study genomic locus human disease human model innovation molecular phenotype mouse genome mouse model novel open source promoter risk variant simulation trait transcription factor transcriptome

项目摘要

Project Summary A large fraction of trait/disease-associated loci from genome-wide association studies (GWAS) is intronic or intergenic. A major barrier to elucidating the variants responsible for a given human trait/disease is the lack of understanding of the function of noncoding genome. While there have been major developments in analytical tools that exploit GWAS and large-scale epigenome resources to elucidate cell/tissue types and epigenomic events relevant for the GWAS loci, comparative genomics methods through mouse engineering approaches are critically lacking. This is a clear hindrance for leveraging large-scale and well-powered model organism eQTL and QTL studies such as the ones from diversity outbred mice to understand mechanisms underlying human diseases. Current practice of moving between human and model organism genomes solely pertains a sequence similarity-based mapping. However, this approach leads to 60-70% of the SNPs not mapping, and a significant fraction mapping to multiple locations. This project addresses key difficulties towards this end by developing a biologically relevant and statistically rigorous method, liftSNP, that goes beyond sequence similarity and incorporates epigenome and higher order regulatory grammar into mapping of human GWAS SNPs to model organism genomes. liftSNP will be developed and evaluated on GWAS SNPs from three diverse disease systems (hematologic/developmental; obesity, metabolic syndrome, T2D; neurological/autism). The results of these large-scale applications will be made available through atSNP Search and will enable researchers to lift over their GWAS SNP harboring genomic loci to mouse genome in a functionally relevant manner. The aims will be accomplished through a combination of methodological development, theoretical analysis, data-driven simulation, computational analysis, and experimental validation. Statistical resources generated from this project will be disseminated as open-source software. Collectively, these aims will significantly enhance our comparative genomics interpretation of GWAS results.

项目概要大部分性状/疾病相关位点来自全基因组关联研究 (GWAS) 是内含子或基因间的。阐明负责的变体的主要障碍对于特定的人类特征/疾病，缺乏对非编码功能的理解基因组。虽然利用分析工具取得了重大进展 GWAS 和大规模表观基因组资源，用于阐明细胞/组织类型和与 GWAS 位点相关的表观基因组事件，通过比较基因组学方法小鼠工程方法严重缺乏。这是一个明显的障碍利用大规模且功能强大的模式生物 eQTL 和 QTL 研究，例如因为来自多样性的小鼠远交来了解人类的潜在机制疾病。当前在人类和模式生物基因组之间移动的实践仅涉及基于序列相似性的映射。然而，这种方法导致 60-70% 的 SNP 未映射，并且很大一部分映射到多个地点。该项目通过开发一个生物学相关且统计严谨的方法 liftSNP，超越了序列相似性并结合表观基因组和高阶调控语法将人类 GWAS SNP 映射到模型生物基因组。提升SNP将是对来自三种不同疾病系统的 GWAS SNP 进行开发和评估（血液/发育；肥胖、代谢综合征、T2D；神经/自闭症）。这些大规模应用的结果将通过 atSNP 提供搜索将使研究人员能够克服其含有基因组位点的 GWAS SNP 以功能相关的方式修改小鼠基因组。目标一定会实现通过方法论开发、理论分析、数据驱动的结合模拟、计算分析和实验验证。统计资源该项目产生的成果将作为开源软件进行传播。总的来说，这些目标将显着增强我们对 GWAS 的比较基因组学解释结果。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Gene by environment interaction mouse model reveals a functional role for 5-hydroxymethylcytosine in neurodevelopmental disorders.

DOI：
10.1101/gr.276137.121
发表时间：
2022-03
期刊：
Genome research
影响因子：
7
作者：
Papale LA;Madrid A;Zhang Q;Chen K;Sak L;Keleş S;Alisch RS
通讯作者：
Alisch RS

INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants.

DOI：
10.1186/s13059-021-02450-8
发表时间：
2021-08-23
期刊：
Genome biology
影响因子：
12.3
作者：
Dong C;Simonett SP;Shin S;Stapleton DS;Schueler KL;Churchill GA;Lu L;Liu X;Jin F;Li Y;Attie AD;Keller MP;Keleş S
通讯作者：
Keleş S

scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data.

scGAD：用于 scHi-C 数据探索性分析的单细胞基因关联域评分。