Transcription Regulation

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Transcription Regulation

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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. - PowerPoint PPT Presentation

Transcript of Transcription Regulation

Page 1: Transcription Regulation

Transcription Regulation

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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.

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ChIP - chip

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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.

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Human binding sites continued…

• Computational approaches were used to identify potential binding sites.

• Only 2-35% of found binding sites exactly match consensus sequences.

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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.

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Genome-Wide Location and Function of DNA Binding

Proteins

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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.

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The Activators discussed

• Gal4 - gene expression under changes in carbon source.

• Ste12 - mating pheromone.

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Methods

Close-up of a scanned image of a microarray containing DNA fragments

representing 6361 intergenic regions of the yeast genome.

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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.

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• Three independent experiments were performed.

• Three Samples were analyzed individually.

• Average binding ratio and associated P value were calculated.

Experimental Design

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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 contributeto specificity in vivo.

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Genes whose promoter regions were bound by Gal4 and whose expression levels were induced at least

twofold by galactose.

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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.

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Galactose-induced exoression of FUR4, MTH1 and PCL10

Samples from wild-type and gal4- strains were taken before and after the addition of galactose.

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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.

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New functions for Gal4 – PCl10

• Cyclin associates with Pho85p and represses formation of glycogen.

• Reduces glycogenesis to maximize the energy obtained from galactose metbolism

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New functions for Gal4 – MTH1

• Encodes transcriptional repressor of HXT genes involved in hexose transport.

• Leads to reduced levels of glucose transporter expression.

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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.

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Ste12 - continued

• The genes can be divided into 2 classes:– Those bound by Ste12 both before and after pheromone exposure.

– Those bound by Ste12 only 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.

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Genome-wide location of Ste12 protein

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Role of Ste12 target genes in the yeast mating pathway

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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.

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Transcriptional regulatory code of an eukayotic genome

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Prolog

• Comparative genomics has been used to identify cis-regulatory sequences 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.

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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.

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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.

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Findings

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

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Yeast transcription regulatory map

• This map includes 3,533 interaction within 1,296 promotor regions.

• Describes transcription regulatory potential.

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Combining binding data and sequence conservation data

• 884-base-pair intergenic region upsteram to the gene BAP2.

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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.

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Yeast promoter architecture

• Simple promotor usually involved in common biological function.

• Repetetive promoter can permit a graded transcriptional response.

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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.

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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

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Mechanistic regulatory models

• Expansion of binding sites.

• Interaction with other regulators or possible environmentally dependant modifications.

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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.