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Transcription Regulation

Transcription Regulation. Facts & History. Transcription factors binding sites are small (6-9 bp) and highly degenerate. Chromatin immunoprecipitation and microarray main methods. Originally established in yeast’s DNA array containing 6000 intergenic regions.

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Transcription Regulation

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  1. Transcription Regulation

  2. Facts & History • Transcription factors binding sites are small (6-9 bp) and highly degenerate. • Chromatin immunoprecipitation and microarray main methods. • Originally established in yeast’s DNA array containing 6000 intergenic regions. • Nowadays ChIP-chip extended to use to map binding sides along entire human chromosomes.

  3. ChIP - chip

  4. Human binding sites • Not only in the immediate vicinity of the transcription start site. • Appear at distal sites and within genes. • 9-27% within the first 1kb upstream. • 25% 10kb upstream. • 40% within introns. • 36% at the 3’ end. Possible antisense transcription regulation.

  5. Human binding sites continued… • Computational approaches were used to identify potential binding sites. • Only 2-35% of found binding sites exactly match consensus sequences.

  6. Why Yeast? • 16 chromosomes ranging in size from 200 to 2,200 kb. • total genome size of approximately 13,000kb. • most yeast genes do not contain introns. • There is little 'junk' DNA in the intergenic regions. • Binding sites are usually loctaed 1kb upstream.

  7. Genome-Wide Location and Function of DNA Binding Proteins

  8. Binding sites roles • Transcription activators recruit chromatin modifying compexes and transcription apparatus. • DNA binding status of transcription activators is affected by the cell cycle status and enviromental changes. • Regulation of chromosme replication, condensation, cohesion and other aspects of DNA maintenance.

  9. The Activators discussed • Gal4 - gene expression under changes in carbon source. • Ste12 - mating pheromone.

  10. Methods Close-up of a scanned image of a microarray containing DNA fragments representing 6361 intergenic regions of the yeast genome.

  11. P value – Confidence to estimate binding Analysis of Cy3- and Cy5- labeled DNA amplifed from 1 ng of yeast genomic DNA using a single-array error model. 99.8% of genes within the error range.

  12. Experimental Design • Three independent experiments were performed. • Three Samples were analyzed individually. • Average binding ratio and associated P value were calculated.

  13. Gal4 • Activates genes necessery for galactose metabolism. • Among the best characterized transcriptional activators. • 10 genes to be bound by Gal4 were found (P value ≤ 0.001). • 7 previously known to be regulated and new 3: MTH1, PCL10 and FUR4. • Gal4 consensus binding sequence (CGGN11CCG) can be found at many sites where binding is not detected. • Additional factors such as chromatin structure contribute to specificity in vivo.

  14. Genes whose promoter regions were bound by Gal4 and whose expression levels were induced at least twofold by galactose.

  15. Confirmation of microarray data for each gene Strains with (+) and without (-) myc tagged Gal4 were grown in galactos. Amplification of unenriched DNA (I) and IP-enriched DNA(P) ARN1 was used as negative control.

  16. Galactose-induced exoression of FUR4, MTH1 and PCL10 Samples from wild-type and gal4- strainswere taken before and after the addition of galactose.

  17. New functions for Gal4 – FUR4 Encodes uracil permease Reflects a need to increase intracellular pools of pyrimadines to permit efficient UDP addition to galactose catalyzed by Gal7.

  18. New functions for Gal4 – PCl10 Cyclin associates with Pho85p and represses formation of glycogen. Reduces glycogenesis to maximize the energy obtained from galactose metbolism

  19. New functions for Gal4 – MTH1 Encodes transcriptional repressor of HXT genes involved in hexose transport. Leads to reduced levels of glucose transporter expression.

  20. Ste12 • Functions in the response of haploid yeast to mating pheromones. • 200 genes are transcriptionally Ste12-dependent, not all of them directly. • The genome wide binding of Ste12 before and after pheromone treatment was determined in 3 independent experiments. • It shows that 29 pheromone-induced genes are regulated directly by Ste12. • 11 were already known to participate in various steps of the mating process.

  21. Ste12 - continued • The genes can be divided into 2 classes: • Those bound by Ste12both before and after pheromone exposure. • Those bound by Ste12only after pheromone exposure • The genes induced after pheromone exposure by a mechanism converts inactive DNA-bound Ste12 protein to an active transcriptional activator. Probably by removing repressors. • Those induced before and after pheromone exposure show limited binding of Ste12 before exposure. Indication of possible presence of additional regulatory elements.

  22. Genome-wide location of Ste12 protein

  23. Role of Ste12 target genes in the yeast mating pathway

  24. Summary & Conclusion • ChIP-chip can identify the global set of genes whose expression is controlled by transcriptional activators in vivo. • New functional modules were discovered. • Inablilty to distinguish direct from indirect effects on genes.

  25. Transcriptional regulatory code of an eukayotic genome

  26. Prolog • Comparative genomics has been used to identify cis-regulatorysequences within the yeast genome on the basis phylogenetic conservation. • It does not reveal whether transcription regulators occupy these binding sites. • An Initial map of yeast transcription regulatory code was constructed. • Sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species were found.

  27. Methods • Genome-wide location analysis was used to determine occupancy of 203 DNA-binding transcription regulators. • Done in rich media conditions for all regulators. • For 84 regulators in at least 1 of 12 other environmental conditions. • 11,000 unique interactions between regulators and promoter regions were identified in high confidence ( p ≤ 0.0001). • Six motif discovery methods were used to discover 68,279 DNA sequences motifs for the 147 regulators that bound more than 10 probes. • Clustering and stringent statistical tests were used to identify highly significant motifs for each of 116 regulators.

  28. Methods - continued • Additional criteria including requirement for conservation among 3 of 4 related yeast species was used to determine high confidence motifs for 65 regulators.

  29. Findings • For 21 of the regulators there was no prior specificity information.

  30. Yeast transcription regulatory map • This map includes 3,533 interaction within 1,296 promotor regions. • Describes transcription regulatory potential.

  31. Combining binding data and sequence conservation data • 884-base-pair intergenic region upsteram to the gene BAP2.

  32. Regular binding site distribution • Binding sites are not uniformly distributed over the promoter regions. • Almost no binding sites 100bp upsteam. • 74% of the binding sites between 100 and 500bp upstream. • A property that reduces the potential for inappropriate activation of nearby genes.

  33. Yeast promoter architecture • Simple promotor usually involved in common biological function. • Repetetive promoter can permit a graded transcriptional response.

  34. Yeast promoter architecture • This gene might be subject to combinatorial regulation. • Promotors that can execute differential responses to varied growth conditions. • The promotors possibly interact physically or have related functions at multiple genes.

  35. Mechanistic regulatory models Binding is necessary but not sufficient for activation A ligand can turn negative regulation into positive regulation. Activation or repression of other regulators is needed in additon to DNA binding. Condition specific binding

  36. Mechanistic regulatory models Expansion of binding sites. Interaction with other regulators or possible environmentally dependant modifications.

  37. Summary & Conclusion • Mapping the DNA sequence bound by specific regulators in various conditions revealed regulatory potential in the genome. • A framework for modeling the regulatory mechanisms was created. • The methods described can be used to map the sequences that control gene expression in higher eukaryotes.

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