Genome-wide validation of posttranscriptional variation in selection and disease

选择和疾病转录后变异的全基因组验证

基本信息

批准号：
9307917
负责人：
Dustin Shahab Griesemer
金额：
$ 4.9万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-08-15 至 2018-08-14
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9307917
关键词：
3&apos Untranslated Regions Alleles Biological Biological Assay Clustered Regularly Interspaced Short Palindromic Repeats Data Detection Development Diagnostic Diet Disease Ethnic group Follow-Up Studies Future Genetic Engineering Genetic Polymorphism Genetic Transcription Genetic Translation Genome Genome Scan Genomics Genotype Global Change Goals Hepatitis C Hypoxia Inborn Genetic Diseases Individual Infection prevention Infectious Agent Inherited Interferons Lead Light Link Literature Masks Mediating MicroRNAs Molecular Output Pathogenesis Pathway interactions Phenotype Play Polyribosomes Process Proteins RNA Interference Regulation Regulatory Element Reporter Role Scanning Signal Transduction Technology Testing Transcript Translations Untranslated Regions Validation Variant base career climate change clinically significant cohort dietary restriction differential expression ethnic diversity genome wide association study genome-wide high throughput screening human disease human genome sequencing insight interest mRNA Stability mRNA Transcript Degradation novel novel therapeutic intervention novel therapeutics personalized therapeutic pressure public health relevance response skills tool trait

项目摘要

DESCRIPTION (provided by applicant): An influx of genotype data from disease cohorts and diverse ethnic groups is markedly increasing the power of genome-wide scans for disease association and positive selection. These scans identify loci relevant to the pathogenesis of disease and survival in the face of historic threats such as infectious agents, climate change, and dietary limitations, setting the stage for the development of genotype-based diagnostics and personalized therapeutics to reverse inherited disease and protect against acquired disease. However, it is difficult to isolate disease-causing variants from nearby neutral variants to which they are closely linked. One potential solution is to assay all potentially causal variants for molecular function. However, it is infeasible to individually assay the thousands of variants potentially associated with disease, especially in light of the prediction that most variants responsible for selection and disease will be regulatory. We aim to elucidate novel variants underlying disease and adaptive phenotypes by developing a high-throughput screen for posttranscriptional regulatory function. To accomplish this goal, we will adapt the recently described Massively Parallel Reporter Assay (MPRA) to allow the quantification of allelic differences in expression and translation for thousands of variants in tandem. We will utilize this adapted MPRA to comprehensively assay loci implicated in disease and adaptation for variants with posttranscriptional function. Finally, after identifying variants with quantifiable effects on expression or translation, we will perform targeted follow-up studies to gain mechanistic insight into posttranscriptional processes underlying these traits. These aims will enable us to move from genome-wide scans for disease and selection to elucidation of posttranscriptional mechanisms that may be manipulated to devise novel therapeutic approaches.

描述（由适用提供）：来自疾病队列和大种族的基因型数据的影响明显增加了全基因组扫描对疾病关联和阳性选择的力量。这些扫描确定了面对历史威胁（例如传染性药物，气候变化和饮食局限性）的疾病发病机理和生存的区域，这为发展基于基因型的诊断和个性化治疗的发展奠定了基础，以反向遗传疾病并预防获得的疾病。但是，很难将引起疾病的变体与与之紧密联系的近乎中性变体分离。一种潜在的解决方案是主张分子功能的所有潜在因果变异。但是，单独主张可能与疾病相关的数千种变体是不可行的，尤其是鉴于预测大多数负责选择和疾病的变体都是调节性的。我们的目的是通过开发用于转录后调节功能的高通量屏幕来阐明潜在的疾病和适应性表型的新型变异。为了实现这一目标，我们将适应最近描述的大量平行报告基因测定法（MPRA），以允许数千种变体的表达和翻译等位基因差异的数量。我们将利用这个改编了MPRA，以全面分析植入疾病的地方，并适应具有转录后功能的变体。最后，在确定具有可量化影响的变体之后表达或翻译，我们将进行有针对性的后续研究，以获取对这些特征背后的转录后过程的机械洞察力。这些目标将使我们能够从全基因组的疾病扫描和选择转变为阐明后的后机制，这些机制可能被操纵以设计新的治疗方法。

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）

Genome-wide functional screen of 3'UTR variants uncovers causal variants for human disease and evolution.

DOI：
10.1016/j.cell.2021.08.025
发表时间：
2021-09-30
期刊：
Cell
影响因子：
64.5
作者：
Griesemer D;Xue JR;Reilly SK;Ulirsch JC;Kukreja K;Davis JR;Kanai M;Yang DK;Butts JC;Guney MH;Luban J;Montgomery SB;Finucane HK;Novina CD;Tewhey R;Sabeti PC
通讯作者：
Sabeti PC