Skip to content

A cell fate map of mammalian embryogenesis

The MELA dataset reconstructs lineage trees across more than 1.5 million cells from 16 mouse embryos, staged at half-day intervals from E7.5 to E10.0, and pairs them with deep transcriptional profiling to chart how cell fate is determined during gastrulation and early organogenesis.

UMAP of the MELA single-cell transcriptomic atlas, colored by cell type
>1.5M
cells profiled
16
mouse embryos
E7.5–E10.0
staged in half-day steps
~75%
of cell divisions resolved
Reconstructed lineage trees across MELA mouse embryos

Reconstructed lineage trees resolving ~75% of cell divisions across 16 embryos.

The project

A quantitative framework for cell fate specification

A comprehensive cell fate map of mammalian embryogenesis has long been out of reach because of the scale, cellular diversity, and non-deterministic nature of development in utero. Using PEtracer to continuously install heritable genetic marks as cells divide, we reconstruct lineage trees that resolve roughly 75% of cell divisions.

Pairing these trees with deep transcriptional profiling, we quantify fate biases, restriction timing, progenitor pool sizes, and lineage relationships across the embryo — revealing strikingly reproducible lineage architecture across replicate embryos despite the regulative flexibility of mammalian development. The result is a lineage-resolved reference for generating and contextualizing developmental hypotheses at organismal scale.

What you'll find here

Cite this work

Colgan WN, Koblan LW, Villagrana J, Hou T-CJ, Wang M, Gowri G, Chandler W, Sepulveda LA, Ciftci D, Smolyar K, Young A, Wittler L, Markoulaki S, Loh KM, Zhuang X, Yosef N, Smith ZD, Weissman JS. Comprehensive Lineage Tracing Maps the Landscape of Cell Fate Decisions in Mouse Embryogenesis. bioRxiv (2026).

doi: 10.64898/2026.05.07.722278

Data & citation →

Funding

The generation of this data was supported by the CZ Biohub Billion Cells Project, the Howard Hughes Medical Institute, and an NIH Center of Excellence in Genomic Science (CEGS) award.