Analysis of Combinatorial cis-Regulation in Synthetic and Genomic Promoters

Transcription factor binding sites are being discovered at a rapid pace. It is now necessary to turn attention towards understanding how these sites work in combination to influence gene expression. Quantitative models that accurately predict gene expression from promoter sequence will be a crucial part of solving this problem. Here we present such a model, based on the analysis of synthetic promoter libraries in yeast (Saccharomyces cerevisiae). Thermodynamic models based only on the equilibrium binding of transcription factors to DNA and to each other captured a large fraction of the variation in expression in every library. Thermodynamic analysis of these libraries uncovered several phenomena in our system, including cooperativity and the effects of weak binding sites. When applied to the S. cerevisiae genome, a model of repression by Mig1 (which was trained on synthetic promoters) predicts a number of Mig1-regulated genes that lack significant Mig1-binding sites in their promoters. The success of the thermodynamic approach suggests that the information encoded by combinations of cis-regulatory sites is interpreted primarily through simple protein–DNA and protein–protein interactions, with complicated biochemical reactions—such as nucleosome modifications—being downstream events. Quantitative analyses of synthetic promoter libraries will be an important tool in unravelling the rules underlying combinatorial cis-regulation.

[1]  M. A. Shea,et al.  The OR control system of bacteriophage lambda. A physical-chemical model for gene regulation. , 1985, Journal of molecular biology.

[2]  H. Ronne,et al.  Yeast MIG1 repressor is related to the mammalian early growth response and Wilms' tumour finger proteins. , 1990, The EMBO journal.

[3]  M. Ptashne,et al.  Transcriptional activation by recruitment , 1997, Nature.

[4]  J. Boeke,et al.  Designer deletion strains derived from Saccharomyces cerevisiae S288C: A useful set of strains and plasmids for PCR‐mediated gene disruption and other applications , 1998, Yeast.

[5]  P. Brown,et al.  Characterization of three related glucose repressors and genes they regulate in Saccharomyces cerevisiae. , 1998, Genetics.

[6]  Gary D. Stormo,et al.  Identifying DNA and protein patterns with statistically significant alignments of multiple sequences , 1999, Bioinform..

[7]  H. Bussemaker,et al.  Regulatory element detection using correlation with expression , 2001, Nature Genetics.

[8]  M. Ptashne,et al.  Genes and Signals , 2001 .

[9]  Alexander E. Kel,et al.  TRANSFAC®: transcriptional regulation, from patterns to profiles , 2003, Nucleic Acids Res..

[10]  L. Fulton,et al.  Finding Functional Features in Saccharomyces Genomes by Phylogenetic Footprinting , 2003, Science.

[11]  Nicolas E. Buchler,et al.  On schemes of combinatorial transcription logic , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Mark Johnston,et al.  Regulatory Network Connecting Two Glucose Signal Transduction Pathways in Saccharomyces cerevisiae , 2004, Eukaryotic Cell.

[13]  Michael Q. Zhang,et al.  Interacting models of cooperative gene regulation. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Nicola J. Rinaldi,et al.  Transcriptional regulatory code of a eukaryotic genome , 2004, Nature.

[15]  Michael A. Beer,et al.  Predicting Gene Expression from Sequence , 2004, Cell.

[16]  Amos Tanay,et al.  Extensive low-affinity transcriptional interactions in the yeast genome. , 2006, Genome research.

[17]  Pooja Jain,et al.  The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae , 2005, Nucleic Acids Res..

[18]  M. Levine,et al.  Computational Models for Neurogenic Gene Expression in the Drosophila Embryo , 2006, Current Biology.

[19]  Eric D. Siggia,et al.  Gene Expression From Random Libraries of Yeast Promoters , 2006, Genetics.

[20]  M. Elowitz,et al.  Programming gene expression with combinatorial promoters , 2007, Molecular systems biology.

[21]  J. Collins,et al.  Combinatorial promoter design for engineering noisy gene expression , 2007, Proceedings of the National Academy of Sciences.

[22]  R. Schiestl,et al.  Large-scale high-efficiency yeast transformation using the LiAc/SS carrier DNA/PEG method , 2007, Nature Protocols.

[23]  Patrick J. Killion,et al.  Genetic reconstruction of a functional transcriptional regulatory network , 2007, Nature Genetics.

[24]  Alexandre P. Francisco,et al.  YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae , 2007, Nucleic Acids Res..

[25]  E. Segal,et al.  Predicting expression patterns from regulatory sequence in Drosophila segmentation , 2008, Nature.