The changing mouse embryo transcriptome at whole tissue and single-cell resolution

Peng He, Brian A. Williams (), Diane Trout, Georgi K. Marinov, Henry Amrhein, Libera Berghella, Say-Tar Goh, Ingrid Plajzer-Frick, Veena Afzal, Len A. Pennacchio, Diane E. Dickel, Axel Visel, Bing Ren, Ross C. Hardison, Yu Zhang and Barbara J. Wold ()
Additional contact information
Peng He: California Institute of Technology
Brian A. Williams: California Institute of Technology
Diane Trout: California Institute of Technology
Georgi K. Marinov: Stanford University
Henry Amrhein: California Institute of Technology
Libera Berghella: California Institute of Technology
Say-Tar Goh: California Institute of Technology
Ingrid Plajzer-Frick: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory
Veena Afzal: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory
Len A. Pennacchio: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory
Diane E. Dickel: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory
Axel Visel: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory
Bing Ren: University of California, San Diego
Ross C. Hardison: Pennsylvania State University
Yu Zhang: Pennsylvania State University
Barbara J. Wold: California Institute of Technology

Nature, 2020, vol. 583, issue 7818, 760-767

Abstract: Abstract During mammalian embryogenesis, differential gene expression gradually builds the identity and complexity of each tissue and organ system1. Here we systematically quantified mouse polyA-RNA from day 10.5 of embryonic development to birth, sampling 17 tissues and organs. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets that were further characterized by the transcription factor motif codes of their promoters. We decomposed the tissue-level transcriptome using single-cell RNA-seq (sequencing of RNA reverse transcribed into cDNA) and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for one-third of differential gene expression and more than 40% of identified cell types. By integrating promoter sequence motifs with companion ENCODE epigenomic profiles, we identified a prominent promoter de-repression mechanism in neuronal expression clusters that was attributable to known and novel repressors. Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types that included progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell-type transcription factor networks and complementary sets of candidate enhancer elements by using single-cell RNA-seq to decompose integrative cis-element (IDEAS) models that were derived from whole-tissue epigenome chromatin data. These ENCODE reference data, computed network components and IDEAS chromatin segmentations are companion resources to the matching epigenomic developmental matrix, and are available for researchers to further mine and integrate.

Date: 2020
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DOI: 10.1038/s41586-020-2536-x

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