Transcriptional regulation is pivotal to the specification of distinct cell types during embryonic development. However, it still lacks a systematic way to identify key transcription factors (TFs) orchestrating the temporal and tissue specificity of gene expression. Here, we integrated epigenomic and transcriptomic data to reveal key regulators from two cells to postnatal day 0 in mouse embryogenesis. We predicted three-dimensional chromatin interactions in 12 tissues across eight developmental stages, which facilitates linking TFs to their target genes for constructing transcriptional regulatory networks. To identify driver TFs, we developed a new algorithm, dubbed Taiji, to assess the global influence of each TF and systematically uncovered TFs critical for lineage-specific and stage-dependent tissue specification. We have also identified TF combinations that function in spatiotemporal order to form transcriptional waves regulating developmental progress. Furthermore, lacking stage-specific TF combinations suggests a distributed timing strategy to orchestrate the coordination between tissues during embryonic development.
Keyphrases
- transcription factor
- gene expression
- single cell
- genome wide identification
- dna binding
- genome wide
- dna methylation
- cell fate
- rna seq
- induced apoptosis
- machine learning
- bioinformatics analysis
- cell therapy
- deep learning
- electronic health record
- stem cells
- big data
- neural network
- oxidative stress
- dna damage
- signaling pathway