Lineage motifs: developmental modules for control of cell type proportions (post-revision)

Description

In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells or extrinsic interactions that produce specific patterns of descendant cell types on lineage trees. 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 or extrinsic interactions. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in retina and early embryonic 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.

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This dataset contains the data, code, and scripts to reproduce the results in the manuscript, "Lineage motifs: developmental modules for control of cell type proportions." Within this resource, data and scripts are organized by figure. All code is written in Python, with analysis scripts provided as Jupyter notebooks.