Lineages of embryonic stem cells show non-Markovian state transitions.
Lineages of embryonic stem cells show non-Markovian state transitions.
复制标题
胚胎干细胞的谱系表现出非马尔可夫状态转换。
DOI：
10.1016/j.isci.2021.102879
复制
发表时间：
2021-08-20
期刊：
影响因子：
5.8
通讯作者：
Garg S
中科院分区：
文献类型：
--
作者：
Udomlumleart T;Hu S;Garg S
多能胚胎干细胞（ESCs）通过一系列发育状态的转变，构成了成年脊椎动物的细胞类型。这些状态可以通过标记基因（如Nanog和Sox2）的表达水平来定义。在文化中，ESCs在状态之间可逆地转换。然而，ESCs是否保留其先前状态的记忆或在无记忆（马尔可夫）过程中过渡仍然相对未知。在这里，我们展示了一些高度动态的esc谱系不表现出马尔可夫性质：它们以前的状态和亲缘关系影响未来的选择。出乎意料的是，与马尔可夫模型的预测相反，谱系在不同状态之间的分布随着时间的推移是恒定的。此外，高度动态的ESC谱系在维甲酸分化后显示出扭曲的细胞命运分布。总之，这些数据表明ESC谱系是控制未来细胞状态的重要变量，对干细胞的功能和发育有影响。胚胎干细胞在Nanog和Sox2定义状态之间切换的动力学在数天到数周的时间内，谱系水平的动力学是非马尔可夫的。一部分谱系在状态之间显示出很高的转换率。干细胞研究；发育生物学;胚胎学;系统与计算生物学
Pluripotent embryonic stem cells (ESCs) constitute the cell types of the adult vertebrate through a series of developmental state transitions. These states can be defined by expression levels of marker genes, such as Nanog and Sox2. In culture, ESCs reversibly transition between states. However, whether ESCs retain memory of their previous states or transition in a memoryless (Markovian) process remains relatively unknown. Here, we show some highly dynamic lineages of ESCs do not exhibit the Markovian property: their previous states and kin relations influence future choices. Unexpectedly, the distribution of lineages across their composition between states is constant over time, contrasting with the predictions of a Markov model. Additionally, highly dynamic ESC lineages show skewed cell fate distributions after retinoic acid differentiation. Together, these data suggest ESC lineage is an important variable governing future cell states, with implications for stem cell function and development. Dynamics of embryonic stem cells switching between Nanog and Sox2 defined states Lineage-level dynamics are non-Markov over a time period of days to weeks A subset of lineages shows high transition rate between states These lineages skew cell fate under retinoic acid differentiation Cell biology; Stem cells research; Developmental biology; Embryology; Systems and computational biology
登录
查看更多内容
影响因子：
16.6
作者：
Semrau S;Goldmann JE;Soumillon M;Mikkelsen TS;Jaenisch R;van Oudenaarden A
通讯作者：
van Oudenaarden A
影响因子：
14.8
作者：
Niakan, Kathy K.;Schrode, Nadine;Cho, Lily T. Y.;Hadjantonakis, Anna-Katerina
通讯作者：
Hadjantonakis, Anna-Katerina
影响因子：
5.7
作者：
Boije H;MacDonald RB;Harris WA
通讯作者：
Harris WA
影响因子：
64.8
作者：
Claveria, Cristina;Giovinazzo, Giovanna;Torres, Miguel
通讯作者：
Torres, Miguel
影响因子：
3.4
作者：
TILL, JE;MCCULLOCH, EA
通讯作者：
MCCULLOCH, EA