1. Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements
- Author
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Florian Buettner, Jasmin Fisher, Berthold Göttgens, Fabian J. Theis, Andrew J. Lilly, Steven Woodhouse, Evangelia Diamanti, Yosuke Tanaka, Wajid Jawaid, Iain C. Macaulay, Victoria Moignard, Laleh Haghverdi, Shin-Ichi Nishikawa, Nir Piterman, Valerie Kouskoff, and Adam C. Wilkinson
- Subjects
Male ,Mesoderm ,Transcription, Genetic ,Molecular Sequence Data ,Biomedical Engineering ,Gene regulatory network ,Diffusion map ,Bioengineering ,Computational biology ,Biology ,Applied Microbiology and Biotechnology ,Article ,Diffusion ,medicine ,Animals ,Computer Simulation ,Gene Regulatory Networks ,Hox gene ,Network model ,Genetics ,Regulation of gene expression ,Mice, Inbred ICR ,Blood Cells ,Base Sequence ,Models, Genetic ,Gene Expression Profiling ,Gastrulation ,Embryonic stem cell ,Gene expression profiling ,medicine.anatomical_structure ,Gene Expression Regulation ,Molecular Medicine ,Female ,Single-Cell Analysis ,Biotechnology - Abstract
Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.
- Published
- 2015