Tarkkonen Kati, Hieta Reija, Kytölä Ville, Nykter Matti, Kiviranta Riku
Institute of Biomedicine, University of Turku, Turku, Finland.
GeneVia Technologies, Tampere, Finland.
Gene. 2017 Aug 30;626:119-131. doi: 10.1016/j.gene.2017.05.028. Epub 2017 May 11.
Fast progress of the next generation sequencing (NGS) technology has allowed global transcriptional profiling and genome-wide mapping of transcription factor binding sites in various cellular contexts. However, limited number of replicates and high amount of data processing may weaken the significance of the findings. Comparative analyses of independent data sets acquired in the different laboratories would greatly increase the validity of the data. Runx2 is the key transcription factor regulating osteoblast differentiation and bone formation. We performed a comparative analysis of three published Runx2 data sets of chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) analysis in osteoblasts from mouse and human origin. Moreover, we assessed the similarity of the corresponding transcription data of these studies available online. The ChIP-seq data analysis confirmed general features of Runx2 binding, including location at genic vs intergenic regions and abundant Runx2 binding on promoters of the highly expressed genes. We also found high frequency of Runx2 DNA binding without a consensus Runx2 motif at the binding site. Importantly, mouse and human Runx2 showed moderately similar binding patterns in terms of peak-associated closest genes and their associated genomic ontology (GO) pathways. Accordingly, the gene expression profiles were highly similar and osteoblastic phenotype was prominent in the differentiated stage in both species. In conclusion, ChIP-seq method shows good reproducibility in the context of mature osteoblasts, and mouse and human osteoblast models resemble each other closely in Runx2 binding and in gene expression profiles, supporting the use of these models as adequate tools in studying osteoblast differentiation.
下一代测序(NGS)技术的快速发展使得在各种细胞环境中能够进行全基因组转录谱分析和转录因子结合位点的全基因组定位。然而,重复样本数量有限以及大量的数据处理可能会削弱研究结果的显著性。对在不同实验室获得的独立数据集进行比较分析将大大提高数据的有效性。Runx2是调节成骨细胞分化和骨形成的关键转录因子。我们对已发表的三个关于Runx2的数据集进行了比较分析,这些数据集来自对小鼠和人类来源的成骨细胞进行的染色质免疫沉淀测序(ChIP-seq)分析。此外,我们评估了这些研究在网上可获得的相应转录数据的相似性。ChIP-seq数据分析证实了Runx2结合的一般特征,包括在基因区域与基因间区域的定位以及在高表达基因启动子上丰富的Runx2结合。我们还发现在结合位点处Runx2 DNA结合频率很高,但没有一致的Runx2基序。重要的是,就与峰相关的最接近基因及其相关的基因组本体(GO)途径而言,小鼠和人类的Runx2显示出适度相似的结合模式。因此,基因表达谱高度相似,并且在两个物种的分化阶段成骨细胞表型都很突出。总之,ChIP-seq方法在成熟成骨细胞的背景下显示出良好的可重复性,并且小鼠和人类成骨细胞模型在Runx2结合和基因表达谱方面彼此非常相似,这支持将这些模型用作研究成骨细胞分化的合适工具。