Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, India.
Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, India.
Comput Biol Chem. 2020 Apr;85:107239. doi: 10.1016/j.compbiolchem.2020.107239. Epub 2020 Feb 21.
Insight into the key genes of pluripotency in human and their interrelationships is necessary for understanding the underlying mechanism of pluripotency and hence their successful application in regenerative medicine. The recent advances in transcriptomics technologies have created new opportunities to decipher the genes involved in pluripotency, genetic network that governs the unique properties of embryonic stem cells and lineage differentiation mechanisms in a deeper scale. There are a large number of experimental studies on human embryonic stem cells (hESCs) being routinely conducted for unfolding the underlying biology of embryogenesis and their clinical prospects. However, the outcome of these studies often lacks consensus due to differences in samples, experimental techniques and/or analysis protocols. A universal stemness gene list is still lacking. Thus, we aim to identify the pluripotency-associated genes and their interaction network. In this quest, we compared transcriptomic profiles of pluripotent and non-pluripotent samples from diverse cell lines/types generated through RNA-sequencing (RNA-seq). We used a uniform pipeline for the analysis of raw RNA-seq data in order to reduce the amount of variation. Our analysis revealed a consensus set of 498 pluripotency-associated genes and 432 genes as potential pluripotent cell differentiation markers. Furthermore, we predicted 32 genes as "pluripotency critical genes". These pluripotency critical genes formed a tightly bound co-expression network with small-world architecture. Gene ontology (GO) and pathway enrichment analysis, StemChecker and literature survey confirmed the involvement of the genes in the induction and maintenance of pluripotency, though more experimental studies are required for understanding their molecular mechanisms in human.
深入了解人类多能性的关键基因及其相互关系,对于理解多能性的潜在机制及其在再生医学中的成功应用是必要的。转录组学技术的最新进展为解析多能性相关基因、调控胚胎干细胞独特特性的遗传网络以及更深层次的谱系分化机制提供了新的机会。目前有大量关于人类胚胎干细胞(hESC)的实验研究正在进行,旨在揭示胚胎发生的基础生物学及其临床前景。然而,由于样本、实验技术和/或分析方案的差异,这些研究的结果往往缺乏共识。目前仍然缺乏一个普遍的干性基因列表。因此,我们旨在确定多能性相关基因及其相互作用网络。在这项研究中,我们通过 RNA 测序(RNA-seq)比较了来自不同细胞系/类型的多能性和非多能性样本的转录组谱。我们使用统一的管道来分析原始的 RNA-seq 数据,以减少变异量。我们的分析揭示了一个由 498 个多能性相关基因和 432 个基因组成的共识集,这些基因可能是多能性细胞分化的标记物。此外,我们预测了 32 个基因作为“多能性关键基因”。这些多能性关键基因形成了一个紧密结合的共表达网络,具有小世界结构。基因本体论(GO)和途径富集分析、StemChecker 和文献调查证实了这些基因参与了多能性的诱导和维持,但为了理解它们在人类中的分子机制,还需要更多的实验研究。