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从随机引入标记的分布估计细胞谱系。

Estimating cell lineage from distributions of randomly introduced markers.

作者信息

Mochizuki A

机构信息

Department of Biology, Faculty of Science, Kyushu University, Fukuoka 812-8581, Japan.

出版信息

J Theor Biol. 1999 Mar 21;197(2):227-45. doi: 10.1006/jtbi.1998.0870.

Abstract

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.

摘要

通过引入一种遗传或化学标记来分析多细胞生物的细胞谱系,该标记可从一个细胞遗传至其 daughter 细胞,并且即使经过数次细胞分裂也可检测到。为构建完整的细胞谱系,需要识别处于不同发育阶段的所有细胞,然后必须将细胞内标记引入每个细胞。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记分布来估计细胞谱系的新方法,这些标记是在早期阶段随机引入的。假设如下:(1)胚胎之间的细胞谱系是不变的;(2)每次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(或树形拓扑结构)识别为与观察到的细胞标记分布兼容所需标记插入最少的模式。该方法本质上与进化生物学中广泛用于祖先系统发育重建的简约原则相同。当细胞总数较少时,我们可以生成所有可能的细胞谱系,并计算每个候选谱系的最小标记插入数,然后选择所需标记插入最少的细胞谱系。如果细胞数量很大,我们可以使用聚类方法,其中标记标签相关性最高的一对细胞依次合并。计算机模拟证实了聚类方法在估计正确细胞谱系方面的效率。最后,将聚类方法应用于根据实验数据重建海鞘的细胞谱系。

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