Tran Martin, Askary Amjad, Elowitz Michael B
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA 90095, USA.
bioRxiv. 2023 Jun 7:2023.06.06.543925. doi: 10.1101/2023.06.06.543925.
In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells that produce specific sets of descendant cell types. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer progenitor states and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryo development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.
在多细胞生物中，必须以适当的比例产生和维持细胞类型。实现这一目标的一种方式是通过定向祖细胞，它们产生特定的后代细胞类型集。然而，在大多数情况下，细胞命运的定向是概率性的，这使得推断祖细胞状态并理解它们如何建立整体细胞类型比例变得困难。在这里，我们引入了谱系基序分析（LMA），这是一种递归识别谱系树上细胞命运统计上过度代表的模式作为定向祖细胞状态潜在特征的方法。将LMA应用于已发表的数据集揭示了斑马鱼、大鼠视网膜和小鼠早期胚胎发育中细胞命运定向的空间和时间组织。对脊椎动物物种的比较分析表明，谱系基序促进了视网膜细胞类型比例的适应性进化变异。因此，LMA通过将复杂的发育过程分解为更简单的基础模块，为这些过程提供了深入了解。
