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首页> 外文期刊>Journal of Theoretical Biology >Estimating Cell Lineage from Distributions of Randomly Introduced Markers
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Estimating Cell Lineage from Distributions of Randomly Introduced Markers

机译：从随机引入的标记分布估计细胞谱系

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Cell lineage of a multicellular organism has been analysed by introducing a genetic or chemical marker that is inherited from a cell to its daughter cells and is detectable even after several cell divisions. To construct a complete cell lineage, all the cells at different developmental stages need to be identified, and then the intracellular marker must be introduced to each cell. In this paper, I study a new method of estimating cell lineage based on distributions of intercellular markers observed at a single stage, which are introduced randomly at earlier stages. Assumptions are: (1) cell lineage is invariant between embryos; (2) a small number of cells are marked in each experiment; and (3) the total number of replicate experiments is sufficiently large. Then we identify the most likely cell lineage pattern (or tree topology) as the one that requires the least marker insertions to be compatible with the observed distributions of cell markers. This method is essentially the same as the principle of persimony widely used for ancestral phylogeny reconstruction in evolutionary biology. When the total number of cells is small, we can generate all the possible cell lineages and calculate the minimum number of marker insertions for each candidate, and then choose the cell lineage that requires the least marker insertions. If the number of cells is large, we can use clustering method in which a pair of cells with the highest correlation in marker labelling are merged sequentially. The efficiency of the clustering method in estimating the correct cell lineage is confirmed by computer simulations. Finally, the clustering method is applied to reconstruct the cell lineage of ascidian from experimental data.
机译：通过将遗传或化学标记引入多细胞生物的细胞谱系，该遗传或化学标记是从细胞遗传到其子细胞，即使经过几次细胞分裂也可以检测到。为了构建完整的细胞谱系，需要鉴定处于不同发育阶段的所有细胞，然后将细胞内标记物引入每个细胞。在本文中，我研究了一种基于在单个阶段观察到的细胞间标志物分布的估计细胞谱系的新方法，该方法是在早期阶段随机引入的。假设是：（1）细胞谱系在胚胎之间是不变的; （2）在每个实验中标记少量细胞; （3）重复实验的总数足够大。然后，我们将最可能的细胞谱系模式（或树形拓扑）识别为需要最少的标记插入才能与观察到的细胞标记分布兼容的模式。该方法与进化生物学中广泛用于祖先系统发育重建的柿子原理基本相同。当细胞总数很小时，我们可以生成所有可能的细胞谱系，并计算每个候选者的最小标记插入数，然后选择需要最少标记插入的细胞谱系。如果细胞数量很大，可以使用聚类方法，其中标记标记相关性最高的一对细胞顺序合并。计算机模拟证实了聚类方法在估计正确细胞谱系中的效率。最后，采用聚类方法从实验数据重建海鞘细胞谱系。

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