Abstract: This project will use the analysis of pluripotent stem cells and pre-implantation embryonic development as testbed questions to build and test quantitative evolutionary models for gene regulatory networks (GRNs). Pluripotency refers to the potential of an undifferentiated cell to differentiate into any of the three germ layers and give rise to any adult cell type. The general hypothesis of the project is that the pluripotent cell phenotype can be sustained by alternatively implemented (re-wired) GRNs across species. This hypothesis deduces that the knowledge of the re-wiring of GRNs will contribute to finding new routes and efficient methods for reprogramming somatic cells into a pluripotent state. This hypothesis will be addressed by developing methods for combining multi-modality data for GRN reconstruction and quantitative phylogenetic models for GRN evolution. These models will be applicable for identifying and analyzing GRNs in other species and other biological processes. This project will build a general probabilistic framework to enable joint analysis of genomic, epigenomic and transcriptomic data as well as inference of combinatorial and evolutionary rules that GRNs conform to and implement. Five research thrusts will be developed as follows. 1. Develop a probabilistic framework for GRN analysis. 2. Develop models for combinatorial interactions of TFs with a cis-regulatory module (CRM), and extend this model to incorporate epigenetic states of the CRM. 3. Develop probabilistic evolution models for identification of conserved and species- specific gene expression modules. 4. Develop an evolutionary model for analysis of re-wiring of GRNs. The co-evolution of the regulatory relationships of TF and target genes, CRMs and the expression levels of target genes will be modeled. 5. Identify the conserved and re-wired components of the GRNs that support the pluripotent cell identity mammals. Experimentally test these conserved and species-specific regulatory relationships in human and mouse embryonic stem cells. Public Health Relevance: This project will use the analysis of pluripotent stem cells and pre-implantation embryonic development as testbed questions to build and test quantitative evolutionary models for gene regulatory networks. This project will address how gene expression is regulated in pluripotent stem cells and how such gene regulatory networks evolve. Such information may lead to finding new and more efficient routes of cellular reprogramming, which is critical to the development of cell-based therapies for various diseases.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
NIH Director’s New Innovator Awards (DP2)
Project #
7DP2OD007417-02
Application #
8786708
Study Section
Special Emphasis Panel (ZGM1-NDIA-O (01))
Program Officer
Basavappa, Ravi
Project Start
2010-09-30
Project End
2015-06-30
Budget Start
2012-12-01
Budget End
2015-06-30
Support Year
2
Fiscal Year
2010
Total Cost
$1,982,949
Indirect Cost
Name
University of California San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Xiao, Shu; Lu, Jia; Sridhar, Bharat et al. (2017) SMARCAD1 Contributes to the Regulation of Naive Pluripotency by Interacting with Histone Citrullination. Cell Rep 18:3117-3128
Xiao, Shu; Cao, Xiaoyi; Zhong, Sheng (2014) Comparative epigenomics: defining and utilizing epigenomic variations across species, time-course, and individuals. Wiley Interdiscip Rev Syst Biol Med 6:345-52
Biase, Fernando H; Cao, Xiaoyi; Zhong, Sheng (2014) Cell fate inclination within 2-cell and 4-cell mouse embryos revealed by single-cell RNA sequencing. Genome Res 24:1787-96
Huang, Wei; Cao, Xiaoyi; Biase, Fernando H et al. (2014) Time-variant clustering model for understanding cell fate decisions. Proc Natl Acad Sci U S A 111:E4797-806
Shi, Yuyan; Zhong, Sheng (2014) From genomes to societies: a holistic view of determinants of human health. Curr Opin Biotechnol 28:134-42
Chen, Chieh-Chun; Xiao, Shu; Xie, Dan et al. (2013) Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions. PLoS Comput Biol 9:e1003367
Yu, Pengfei; Xiao, Shu; Xin, Xiaoyun et al. (2013) Spatiotemporal clustering of the epigenome reveals rules of dynamic gene regulation. Genome Res 23:352-64
Cao, Xiaoyi; Zhong, Sheng (2013) Enabling interspecies epigenomic comparison with CEpBrowser. Bioinformatics 29:1223-5
Xiao, Shu; Xie, Dan; Cao, Xiaoyi et al. (2012) Comparative epigenomic annotation of regulatory DNA. Cell 149:1381-92
Zelin, Elena; Zhang, Yang; Toogun, Oyetunji A et al. (2012) The p23 molecular chaperone and GCN5 acetylase jointly modulate protein-DNA dynamics and open chromatin status. Mol Cell 48:459-70

Showing the most recent 10 out of 12 publications