All cells constantly adjust their gene expression programs in response to environmental and genetic perturbations. The changes in gene expression are mediated by a complex regulatory network, of which transcriptional regulation is a major component. Cellular transcription networks regulate essentially all biological processes, from development to cancer and aging. The goal of the proposed research is to develop novel theoretical and experimental approaches to systematically analyze the structure, function, and evolution of transcription networks, using yeast as a model organism. Building on the significant progress we have made in the previous granting period, we will continue our efforts to reconstruct yeast transcription networks at a genomic scale. To understand the physiological importance of the network structure, we will quantitatively analyze the growth phenotypes of the deletion mutants of all the transcription factors in the genome under a variety of conditions, and connect global gene expression program to the fitness of the cell. We will expand the scope of our study to incorporate genome- wide nucleosome positioning information, to better understand the relationship between nucleosome positioning and transcriptional regulation. We will systematically perform comparative analysis of transcriptional circuits in different yeast species, in order to derive basic principles governing their evolution. Together these systems-level studies will reveal the basic functional and evolutionary constraints and design principles of transcription networks beyond the yeast system. In addition, specific knowledge of transcriptional regulation in yeast can be transferred to higher eukaryotes including humans, since many biological processes are highly conserved.

Public Health Relevance

Cellular transcription networks regulate essentially all biological processes, including development, cancer and aging. Mis-regulation of these processes leads to human diseases. A global understanding of the structure, function and evolution of the transcription networks in yeast will likely lead to general principles applicable to humans and have a significant impact on human health.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Sledjeski, Darren D
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
Schools of Medicine
San Francisco
United States
Zip Code
Xie, Zhengwei; Jay, Kyle A; Smith, Dana L et al. (2015) Early telomerase inactivation accelerates aging independently of telomere length. Cell 160:928-939
Zuleta, Ignacio A; Aranda-Díaz, Andrés; Li, Hao et al. (2014) Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry. Nat Methods 11:443-8
Nelson, Christopher S; Fuller, Chris K; Fordyce, Polly M et al. (2013) Microfluidic affinity and ChIP-seq analyses converge on a conserved FOXP2-binding motif in chimp and human, which enables the detection of evolutionarily novel targets. Nucleic Acids Res 41:5991-6004
He, Xin; Fuller, Chris K; Song, Yi et al. (2013) Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS. Am J Hum Genet 92:667-80
Huang, Vera; Zheng, Jiashun; Qi, Zhongxia et al. (2013) Ago1 Interacts with RNA polymerase II and binds to the promoters of actively transcribed genes in human cancer cells. PLoS Genet 9:e1003821
Xie, Zhengwei; Zhang, Yi; Zou, Ke et al. (2012) Molecular phenotyping of aging in single yeast cells using a novel microfluidic device. Aging Cell 11:599-606
Rafelski, Susanne M; Viana, Matheus P; Zhang, Yi et al. (2012) Mitochondrial network size scaling in budding yeast. Science 338:822-4
Chubukov, Victor; Zuleta, Ignacio A; Li, Hao (2012) Regulatory architecture determines optimal regulation of gene expression in metabolic pathways. Proc Natl Acad Sci U S A 109:5127-32
Zhang, Yi; Luo, Chunxiong; Zou, Ke et al. (2012) Single cell analysis of yeast replicative aging using a new generation of microfluidic device. PLoS One 7:e48275
Zheng, Jiashun; Benschop, Joris J; Shales, Michael et al. (2010) Epistatic relationships reveal the functional organization of yeast transcription factors. Mol Syst Biol 6:420

Showing the most recent 10 out of 24 publications