Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.
Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.
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DOI：
10.1002/stem.1612
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发表时间：
2014-05
期刊：
影响因子：
5.2
通讯作者：
Hibbs, Matthew A.
中科院分区：
文献类型：
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作者：
Dowell, Karen G.;Simons, Allen K.;Bai, Hao;Kell, Braden;Wang, Zack Z.;Yun, Kyuson;Hibbs, Matthew A.
关键词：
胚胎干细胞（Embryonic stem cells，ESCs）具有自我更新和分化为多种细胞系的能力，是生物医学和发育生物学研究的重要模型。人类和小鼠胚胎干细胞有许多共同的特征，但也有不同的方面，包括支持自我更新的信号通路和细胞周期控制的根本差异。在这里，我们使用贝叶斯网络机器学习来探索人类ESC自我更新的分子基础，以整合细胞类型特异性的高通量数据用于基因功能发现。我们将来自83项人类研究（在1100种条件下收集的约180万个数据点）和62项小鼠研究（在1085种条件下收集的约240万个数据点）的高通量ESC数据整合到专注于ESC自我更新的单独的人类和小鼠预测网络中，以分析蛋白质编码基因直系同源物之间共享和不同的功能关系。计算评估表明，这些网络是高度准确的，文献验证证实了它们的生物相关性，RT-PCR验证支持我们的预测。我们的研究结果反映了已知与两个物种的自我更新和多能性密切相关的关键调控基因的重要性（例如POU 5 F1、SOX 2和NANOG），确定物种之间的代谢差异（例如苏氨酸代谢），阐明人类和小鼠ESC发育信号通路之间的差异（例如，小鼠中LIF激活的JAK/STAT;人类中NODAL/ACTIVIN-A激活的FGF），并揭示了许多预测与每个物种中自我更新功能相关的新基因和途径。这些交互式网络可在www.StemSight.org上在线获得，供干细胞研究人员开发新的假设，发现涉及稀疏注释基因的潜在机制，并优先考虑实验验证的感兴趣基因。
Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1100 conditions) and 62 mouse studies (~2.4 million data points collected under 1085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and RT-PCR validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g. POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g. threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g. LIF-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated FGF in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation.
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影响因子：
4.3
作者：
Hibbs MA;Myers CL;Huttenhower C;Hess DC;Li K;Caudy AA;Troyanskaya OG
通讯作者：
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影响因子：
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作者：
Dowell KG;Simons AK;Wang ZZ;Yun K;Hibbs MA
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影响因子：
4
作者：
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通讯作者：
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影响因子：
1.2
作者：
Bai, Hao;Chen, Kang;Gao, Yong-Xing;Arzigian, Melanie;Xie, Yin-Liang;Malcosky, Christopher;Yang, Yong-Guang;Wu, Wen-Shu;Wang, Zack Z.
通讯作者：
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DOI：
10.1038/nrg3473
发表时间：
2013-06
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
通讯作者：
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