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

被引:0
|
作者
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
Barbara J. Wold
机构
[1] California Institute of Technology,Division of Biology and Biological Engineering
[2] Stanford University,Department of Genetics
[3] Environmental Genomics and Systems Biology Division,Comparative Biochemistry Program
[4] Lawrence Berkeley National Laboratory,School of Natural Sciences
[5] Department of Energy Joint Genome Institute,Department of Cellular and Molecular Medicine
[6] Lawrence Berkeley National Laboratory,Department of Biochemistry and Molecular Biology
[7] University of California,Department of Statistics
[8] Berkeley,undefined
[9] University of California,undefined
[10] Merced,undefined
[11] University of California,undefined
[12] San Diego,undefined
[13] Pennsylvania State University,undefined
[14] Pennsylvania State University,undefined
[15] European Bioinformatics Institute (EMBL-EBI),undefined
来源
Nature | 2020年 / 583卷
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摘要
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.
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页码:760 / 767
页数:7
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