eQTL mapping in response to osteoarthritis induction in differentiated skeletal cell types

项目摘要/摘要 骨关节炎(OA)是一种以软骨和底层骨骼退化为特征的关节疾病， 世界范围内残疾和经济负担的主要来源2，3。虽然已经取得了进展，但 认识到骨性关节炎是一种复杂的疾病4，启动和调节骨性关节炎发病的机制 发病机制尚不清楚。遗传标记5-19与生物力学等环境影响 压力20-24与关节健康有关，基因表达调控25-36的改变可能与 并加强这些因素在疾病进展中的作用。更好地描述基因在多大程度上 骨骼细胞的表达模式与潜在的基因类型有关，并会因生物力学的影响而改变 力量，我们将使用一大组分化的人类软骨细胞和成骨细胞来识别个体间 对机械胁迫处理的基因表达反应的变异。具体地说，在目标1中，我将区分 70例人诱导多能干细胞分化为软骨细胞和成骨细胞的实验研究 使用批量和单细胞数据在这些细胞类型中的基因表达。拟议的研究将包括 之前由70个完全测序的哈特人个体组成的IPSC面板，37，38，并将使用已建立的 软骨细胞和成骨细胞分化方案39。Drop-seq单细胞RNA-seq数据将收集在 添加大量RNA-SEQ数据，以便我可以表征基因表达和基因表达的个体间变异性 解释了不同样本之间细胞成分的差异。在目标2中，我将治疗分化的软骨细胞和 用生物力学应力确定成骨细胞反应表达的数量性状基因座(EQTL)。至 为此，我将使终末分化的软骨细胞和成骨细胞承受已建立的循环拉伸应变。 作为OA40-43体外模型的治疗。将使用批量RNA-seq来确定响应eQTL 数据，以及生物力学应力响应的稳健程度将使用单细胞数据进行估计。 最后，在目标3中，我将把生物力学应激反应eqtls与全基因组关联结合起来。 研究(Gwas)数据以确定与骨性关节炎风险和潜在分子相关的变异 机械装置。已经在主要是欧洲人的个体中发现了几种与骨性关节炎有关的基因 由于拟议研究中的细胞小组由同质群体组成，代表 欧洲人的遗传多样性很大，这是一个理想的比较样本集。我会确定疾病- 通过检测OAGWASHITS的丰富和评估共定位来确定我们的响应eQTL的相关性。 总体而言，这项研究将识别和表征种群中个体间的基因表达反应- 骨性关节炎的细胞培养模型。此外，这项工作将生产出最大的人类IPSC来源的面板 软骨细胞和成骨细胞，预计将对环境中的基因有实质性的了解 导致骨骼系统疾病表型的相互作用。

Project Summary/Abstract Osteoarthritis (OA) is a joint disease characterized by the degradation of cartilage and underlying bone, and it is a major source of disability1 and financial burden2,3 worldwide. While progress has been made towards recognizing OA as a complex disorder4, the mechanisms that initiate and mediate the onset of OA pathogenesis are still unclear. Genetic markers5–19 and environmental influences such as biomechanical stress20–24 have been associated with joint health, and alterations in gene expression regulation25–36 may connect and reinforce these factors’ involvement in disease progression. To better characterize the degree to which gene expression patterns in skeletal cells relate to underlying genotypes and are altered in response to biomechanical forces, we will use a large panel of differentiated human chondrocytes and osteoblasts to identify inter-individual variation in gene expression responses to mechanical stress treatments. Specifically, in Aim 1, I will differentiate chondrocytes and osteoblasts from 70 human induced pluripotent stem cells (iPSCs) and characterize gene expression in these cell types using bulk and single-cell data. The proposed study will include a previously characterized panel of iPSCs from 70 fully sequenced Hutterite individuals37,38 and will use established chondrocyte and osteoblast differentiation protocols39. Drop-seq single-cell RNA-seq data will be collected in addition to bulk RNA-seq data so that I can characterize inter-individual variability in gene expression and account for variation in cell composition across samples. In Aim 2, I will treat differentiated chondrocytes and osteoblasts with biomechanical stress to identify response expression quantitative trait loci (eQTLs). To do this, I will subject terminally differentiated chondrocytes and osteoblasts to established cyclic tensile strain treatments that serve as an in vitro model of OA40–43. Response eQTLs will be determined using bulk RNA-seq data, and the degree to which biomechanical stress response is robust will be estimated using single-cell data. Finally, in Aim 3, I will integrate biomechanical stress response eQTLs with genome-wide association study (GWAS) data to identify variants associated with OA risk and the underlying molecular mechanisms. Several genetic associations with OA have been identified in individuals of primarily European decent6,8–19. Since the panel of cells in the proposed study consists of a homogeneous population that represents much of European genetic diversity44, it is an ideal comparative sample set. I will determine the disease- relevance of our response eQTLs by testing for enrichment of OA GWAS hits and evaluating colocalization. Overall, this research will identify and characterize inter-individual gene expression responses in a population- scale cell culture model of OA. Further, this work will produce the largest panel of human iPSC-derived chondrocytes and osteoblasts and is expected to yield substantial insight into the gene-by-environment interactions that contribute to disease phenotypes in the skeletal system.