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Collaborative Research: Statistical Methods for RNA-seq Based Transcriptomic Analysis of Macrophage Function in Spinal Cord Injury

合作研究：基于RNA-seq的脊髓损伤中巨噬细胞功能转录组学分析的统计方法

基本信息

批准号：
1662139
负责人：
Jianqing Fan
金额：
$ 80万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2023-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1662139&HistoricalAwards=false
关键词：
Collaborative Research Statistical Methods RNA

项目摘要

Spinal cord injury causes functional impairment via the primary mechanical injury, followed by subsequent secondary injury mechanisms at cellular levels. Most research has focused on understanding the mechanisms of secondary injury since it corresponds to functional deficits. Inflammation is a principal mediator of the secondary injury cascade, with macrophages contributing profoundly to the secondary injury. Macrophages, one of the most important type of immune cells, migrate towards the injured spinal cord and engulf myelin debris that is generated at injury onset to form myelin-laden macrophages. In this project, the investigators will utilize RNA sequencing, a powerful method for analyzing global gene expression levels, and develop new statistical approaches to address biological questions related to how myelin-laden macrophages amplify inflammatory response and promote secondary injury. These studies will help researchers understand molecular mechanisms for spinal cord injury and shed new light on the treatment by targeting myelin-laden macrophages. This project aims to answer important questions regarding the mechanisms of secondary injury through the integration of new statistical methods and cutting-edge biological techniques. The central hypothesis is that myelin-laden macrophages in the injured spinal cord promote a local pathologic process and distal organ dysfunction. Specifically, the investigators will determine their molecular patterns and functions, study whether myelin-laden macrophages released extracellular vesicles (exosomes) carry microRNAs from myelin debris to recipient cells and then regulate their functions, and investigate whether these exosomes can enter the bloodstream and contribute to systemic inflammatory response syndrome and distal organ dysfunction. New statistical tools will be developed to analyze large datasets of microRNA sequencing and mRNA sequencing from multiple cell types and time points. In particular, novel robust statistical techniques are proposed to answer the following important questions: how to uniformly and robustly estimate large-scale gene expressions; how to compare them reliably across multiple phenotypes and measured across different platforms; how to accurately identify microRNAs' mRNA targets via sparse regression; how to use quantitative tools for studies of molecular mechanisms and comparisons of gene expression networks; how to control false discovery rate under general dependence; how to perform robust variable selection; how to estimate the size of spurious correlations. The proposed methods will be applied to newly collected, as well as existing data to answer the biological questions related to spinal cord injury. The project will integrate research and education by involving undergraduates, graduate students and postdoctoral fellows, creating new datasets, and developing publicly available software. Students from underrepresented groups will be trained as part of this project. The results will be disseminated broadly through presentations at seminars, conferences, and professional association meetings.

脊髓损伤通过原发性机械损伤引起功能障碍，随后是细胞水平的继发性损伤机制。大多数研究都集中在了解继发性损伤的机制，因为它对应于功能缺陷。炎症是二次损伤级联反应的主要介质，巨噬细胞对二次损伤有深远的影响。巨噬细胞是最重要的免疫细胞类型之一，其向损伤的脊髓迁移并吞噬在损伤开始时产生的髓鞘碎片以形成载有髓鞘的巨噬细胞。在这个项目中，研究人员将利用RNA测序，这是一种分析全球基因表达水平的强大方法，并开发新的统计方法来解决与髓鞘巨噬细胞如何放大炎症反应和促进继发性损伤有关的生物学问题。这些研究将帮助研究人员了解脊髓损伤的分子机制，并通过靶向富含髓鞘的巨噬细胞来阐明治疗方法。该项目旨在通过整合新的统计方法和尖端生物技术来回答有关继发性损伤机制的重要问题。中心假设是，在受损的脊髓中的髓鞘负载的巨噬细胞促进局部病理过程和远端器官功能障碍。具体来说，研究人员将确定它们的分子模式和功能，研究充满髓鞘的巨噬细胞释放的细胞外囊泡（exosomes）是否将microRNA从髓鞘碎片携带到受体细胞，然后调节它们的功能，并研究这些exosomes是否可以进入血液并导致全身炎症反应综合征和远端器官功能障碍。将开发新的统计工具来分析来自多种细胞类型和时间点的microRNA测序和mRNA测序的大型数据集。特别是，提出了新的鲁棒统计技术来回答以下重要问题：如何统一和鲁棒地估计大规模基因表达;如何在多个表型和不同平台上可靠地比较它们;如何通过稀疏回归准确地识别microRNA的mRNA靶标;如何使用定量工具研究分子机制和比较基因表达网络;如何在一般相关下控制错误发现率;如何进行稳健的变量选择;如何估计伪相关的大小。所提出的方法将应用于新收集的数据以及现有的数据，以回答与脊髓损伤相关的生物学问题。该项目将通过让本科生、研究生和博士后研究员参与，创建新的数据集，并开发公开可用的软件，来整合研究和教育。作为该项目的一部分，将对代表性不足群体的学生进行培训。研究结果将通过在研讨会、会议和专业协会会议上的介绍广泛传播。