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多变量荟萃分析揭示了不同人类原始样多能状态的全局转录组特征。

Multivariate meta-analysis reveals global transcriptomic signatures underlying distinct human naive-like pluripotent states.

机构信息

Intramural IT and Bioinformatics Program, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.

NIH Stem Cell Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.

出版信息

PLoS One. 2021 May 13;16(5):e0251461. doi: 10.1371/journal.pone.0251461. eCollection 2021.

Abstract

The ground or naive pluripotent state of human pluripotent stem cells (hPSCs), which was initially established in mouse embryonic stem cells (mESCs), is an emerging and tentative concept. To verify this vital concept in hPSCs, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. This robust bioinformatics approach has significantly improved the predictive values of our meta-analysis. Accordingly, we revealed various similarities or dissimilarities between some naive-like hPSCs (NLPs) generated from different laboratories. Our analysis confirms some previous studies and provides new evidence concerning the existence of three distinct naive-like pluripotent states. Moreover, our study offers global transcriptomic markers that define diverse pluripotent states under various hPSC growth protocols.

摘要

人类多能干细胞(hPSCs)的原始或幼稚多能状态最初是在小鼠胚胎干细胞(mESCs)中建立的,这是一个新兴的、试探性的概念。为了在 hPSCs 中验证这一重要概念,我们通过百分位数归一化、主成分分析(PCA)、t 分布随机邻嵌入(t-SNE)和 SC3 共识聚类的联合分析能力,对主要的 hPSC 数据集进行了多元荟萃分析。这种强大的生物信息学方法显著提高了我们荟萃分析的预测值。因此,我们揭示了来自不同实验室的一些类似原始的 hPSCs(NLPs)之间的各种相似性或差异性。我们的分析证实了一些先前的研究,并提供了关于存在三种不同的原始样多能状态的新证据。此外,我们的研究提供了全局转录组标记,这些标记定义了不同的多能状态,这些状态在不同的 hPSC 生长方案下存在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a20c/8118304/ab7bfaccb990/pone.0251461.g001.jpg

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