Discovering human divergent activity-regulated elements using comparative, computational, and functional approaches

使用比较、计算和功能方法发现人类不同活动调节的元素

基本信息

批准号：
10779701
负责人：
KATHERINE S. POLLARD
金额：
$ 83.21万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-15 至 2028-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10779701
关键词：
Address Atlases Autopsy Behavioral Biological Assay Biological Models Brain CRISPR interference Chromatin Cognitive Computer Models Computing Methodologies Data Data Set Development Diploidy Disease Elements Enhancers Evolution Gene Expression Gene Expression Regulation Genes Genetic Genetic Variation Genetic study Genome Genomics Human In Vitro Induced pluripotent stem cell derived neurons Life Experience Link Location Macaca Macaca mulatta Machine Learning Mediator Methods Modeling Molecular Mutation Neurodevelopmental Disorder Neuronal Plasticity Neurons Pan Genus Pattern Phase Phenotype Phylogeny Physiological Prevalence Primates Property Regulator Genes Regulatory Element Reporter Resources Sequence Analysis Slice Statistical Data Interpretation Stimulus Training Variant cognitive ability comparative convolutional neural network developmental plasticity experience flexibility genome-wide innovation machine learning model nervous system disorder nonhuman primate response sequence learning single-cell RNA sequencing species difference stem cells

项目摘要

PROJECT SUMMARY New experiences elicit distinct patterns of brain activity, leading to the changes in gene expression, neuronal properties, and connectivity that underlie brain plasticity. In humans, the period of enhanced plasticity during brain development is particularly protracted compared to other species. However, the mechanisms and extent to which human neurons have changed to support increased plasticity remain unknown. Furthermore, although prolonged developmental plasticity may support increased cognitive capabilities and behavioral flexibility, it may also increase vulnerability to neurodevelopmental disorders. Neuronal plasticity depends on activity-regulated changes in gene expression that are controlled by activity-responsive genomic regulatory elements. Although we and others have identified regulatory elements as prominent substrates of human-specific evolutionary change, recent atlases of postmortem human and non-human primate brains overlook such dynamic stimulus- responsive regulatory elements. Without training on context-dependent data, current computational models that infer regulatory function based on sequence fail to predict activity-dependent regulatory elements. We hypothesize that there have been genetic changes in human divergent activity-regulated elements (hDAREs) and that we can discover these human-specific genetic underpinnings of plasticity using genome-wide approaches. We will use experimental and computational methods to predict and compare the activity-regulated responses of human neurons versus neurons from rhesus macaque and chimpanzee. We have developed innovative model systems that will allow us to stimulate physiological activity states in previously inaccessible primate neurons, machine learning models to predict regulatory function based on sequence, and massively parallel reporter assays and CRISPRi assays that will allow us to assess the function of candidate hDAREs. Through the successful completion of these studies, we will determine which genomic elements and genetic changes underlie activity-dependent responses in human neurons and the extent to which changes in these elements represent a major substrate of evolutionary selection in the human lineage. This will lay the groundwork for further phenotypic characterization of cellular plasticity mechanisms in the developing human brain. Additionally, these datasets will provide a valuable resource for dissecting genetic mechanisms of neurodevelopmental disorders.

项目概要新的经历会引发不同的大脑活动模式，从而导致基因表达、神经元的变化大脑可塑性的属性和连接性。在人类中，可塑性增强的时期与其他物种相比，大脑发育特别漫长。然而，机制和程度人类神经元发生哪些变化以支持增强的可塑性仍然未知。此外，虽然长期的发育可塑性可能支持认知能力和行为灵活性的提高，它可能也增加了神经发育障碍的脆弱性。神经元可塑性取决于活动调节由活性响应基因组调控元件控制的基因表达变化。虽然我们和其他人已经确定调控元件是人类特异性进化的重要底物变化，最近的人类和非人类灵长类动物死后大脑图谱忽略了这种动态刺激- 反应灵敏的监管要素。如果没有对上下文相关数据进行训练，当前的计算模型根据序列推断调节功能无法预测活性依赖性调节元件。我们假设人类不同活性调节元件（hDARE）发生了遗传变化我们可以利用全基因组发现这些人类特有的可塑性遗传基础接近。我们将使用实验和计算方法来预测和比较活动调节人类神经元与恒河猴和黑猩猩神经元的反应。我们开发了创新的模型系统将使我们能够刺激以前无法达到的生理活动状态灵长类神经元，基于序列预测调节功能的机器学习模型，以及大规模平行报告基因检测和 CRISPRi 检测将使我们能够评估候选 hDARE 的功能。通过成功完成这些研究，我们将确定哪些基因组元素和遗传人类神经元活动依赖性反应的变化以及这些变化的程度元素代表了人类谱系进化选择的主要基础。这将奠定基础用于进一步表征人类大脑发育中细胞可塑性机制的表型特征。此外，这些数据集将为剖析遗传机制提供宝贵的资源。神经发育障碍。