1. Uncovering the mesendoderm gene regulatory network through multi-omic data integration
- Author
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Ira L. Blitz, Rebekah M. Charney, Margaret B. Fish, Camden Jansen, Kitt D. Paraiso, Jeff Jiajing Zhou, Aaron M. Zorn, Yuuri Yasuoka, Gert Jan C. Veenstra, Ali Mortazavi, M. Wlizla, Jin Sun Cho, Ann Rose Bright, Ken W.Y. Cho, Norihiro Sudou, and Masanori Taira
- Subjects
Transcription, Genetic ,Computer science ,Cellular differentiation ,Xenopus ,Medical Physiology ,Gene regulatory network ,computer.software_genre ,Mesoderm ,Transcriptional regulation ,Developmental ,Gene Regulatory Networks ,biology ,Endoderm ,Vertebrate ,Gene Expression Regulation, Developmental ,Genomics ,ATAC-seq ,Chromatin ,ChIP-seq ,Stem Cell Research - Nonembryonic - Non-Human ,Molecular Developmental Biology ,Transcription ,Data integration ,Protein Binding ,Biotechnology ,Cell signaling ,Pediatric Research Initiative ,1.1 Normal biological development and functioning ,Computational biology ,Cell fate determination ,General Biochemistry, Genetics and Molecular Biology ,linked self-organizing maps ,Genetic ,Underpinning research ,biology.animal ,cis-regulatory modules ,Consensus Sequence ,Genetics ,Animals ,endoderm ,Transcription factor ,multi-omic ,Embryogenesis ,Gastrulation ,Human Genome ,DNA ,biology.organism_classification ,Stem Cell Research ,Gene Expression Regulation ,RNA ,Generic health relevance ,Biochemistry and Cell Biology ,RNA-seq ,computer ,Transcription Factors - Abstract
SummaryMesendodermal specification is one of the earliest events in embryogenesis, where cells first acquire distinct identities. Cell differentiation is a highly regulated process that involves the function of numerous transcription factors (TFs) and signaling molecules, which can be described with gene regulatory networks (GRNs). Cell differentiation GRNs are difficult to build because existing mechanistic methods are low-throughput, and high-throughput methods tend to be non-mechanistic. Additionally, integrating highly dimensional data comprised of more than two data types is challenging. Here, we use linked self-organizing maps to combine ChIP-seq/ATAC-seq with temporal, spatial and perturbation RNA-seq data fromXenopus tropicalismesendoderm development to build a high resolution genome scale mechanistic GRN. We recovered both known and previously unsuspected TF-DNA/TF-TF interactions and validated through reporter assays. Our analysis provides new insights into transcriptional regulation of early cell fate decisions and provides a general approach to building GRNs using highly-dimensional multi-omic data sets.HighlightsBuilt a generally applicable pipeline to creating GRNs using highly-dimensional multi-omic data setsPredicted new TF-DNA/TF-TF interactions during mesendoderm developmentGenerate the first genome scale GRN for vertebrate mesendoderm and expanded the core mesendodermal developmental network with high fidelityDeveloped a resource to visualize hundreds of RNA-seq and ChIP-seq data using 2D SOM metaclusters.
- Published
- 2022