Cooperative Binding of Heat Shock Factor to the Yeast \u3ci\u3eHSP82\u3c/i\u3e Promoter In Vivo and In Vitro

revious work has shown that heat shock factor (HSF) plays a central role in remodeling the chromatin structure of the yeastHSP82 promoter via constitutive interactions with its high-affinity binding site, heat shock element 1 (HSE1). The HSF-HSE1 interaction is also critical for stimulating both basal (noninduced) and induced transcription. By contrast, the function of the adjacent, inducibly occupied HSE2 and -3 is unknown. In this study, we examined the consequences of mutations in HSE1, HSE2, and HSE3 on HSF binding and transactivation. We provide evidence that in vivo, HSF binds to these three sites cooperatively. This cooperativity is seen both before and after heat shock, is required for full inducibility, and can be recapitulated in vitro on both linear and supercoiled templates. Quantitative in vitro footprinting reveals that occupancy of HSE2 and -3 by Saccharomyces cerevisiae HSF (ScHSF) is enhanced ∼100-fold through cooperative interactions with the HSF-HSE1 complex. HSE1 point mutants, whose basal transcription is virtually abolished, are functionally compensated by cooperative interactions with HSE2 and -3 following heat shock, resulting in robust inducibility. Using a competition binding assay, we show that the affinity of recombinant HSF for the full-length HSP82promoter is reduced nearly an order of magnitude by a single-point mutation within HSE1, paralleling the effect of these mutations on noninduced transcript levels. We propose that the remodeled chromatin phenotype previously shown for HSE1 point mutants (and lost in HSE1 deletion mutants) stems from the retention of productive, cooperative interactions between HSF and its target binding sites

Differential analysis for high density tiling microarray data

Background: High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results: We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion: The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003 it is most significant at the 5' end of genes, at a p-value < 10^{-13}. The prototype R code has been made available as supplementary material [see Additional file 1]

Differential analysis for high density tiling microarray data

<p>Abstract</p> <p>Background</p> <p>High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The <it>ab initio </it>probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an <it>in-vivo </it>system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program.</p> <p>Results</p> <p>We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias.</p> <p>Conclusion</p> <p>The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10^-13. The prototype R code has been made available as supplementary material [see Additional file <supplr sid="S1">1</supplr>].</p> <suppl id="S1"> <title> <p>Additional file 1</p> </title> <text> <p>gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples.</p> </text> <file name="1471-2105-8-359-S1.zip"> <p>Click here for file</p> </file> </suppl

Cooperative Binding of Heat Shock Factor to the Yeast HSP82 Promoter In Vivo and In Vitro

Previous work has shown that heat shock factor (HSF) plays a central role in remodeling the chromatin structure of the yeast HSP82 promoter via constitutive interactions with its high-affinity binding site, heat shock element 1 (HSE1). The HSF-HSE1 interaction is also critical for stimulating both basal (noninduced) and induced transcription. By contrast, the function of the adjacent, inducibly occupied HSE2 and -3 is unknown. In this study, we examined the consequences of mutations in HSE1, HSE2, and HSE3 on HSF binding and transactivation. We provide evidence that in vivo, HSF binds to these three sites cooperatively. This cooperativity is seen both before and after heat shock, is required for full inducibility, and can be recapitulated in vitro on both linear and supercoiled templates. Quantitative in vitro footprinting reveals that occupancy of HSE2 and -3 by Saccharomyces cerevisiae HSF (ScHSF) is enhanced ∼100-fold through cooperative interactions with the HSF-HSE1 complex. HSE1 point mutants, whose basal transcription is virtually abolished, are functionally compensated by cooperative interactions with HSE2 and -3 following heat shock, resulting in robust inducibility. Using a competition binding assay, we show that the affinity of recombinant HSF for the full-length HSP82 promoter is reduced nearly an order of magnitude by a single-point mutation within HSE1, paralleling the effect of these mutations on noninduced transcript levels. We propose that the remodeled chromatin phenotype previously shown for HSE1 point mutants (and lost in HSE1 deletion mutants) stems from the retention of productive, cooperative interactions between HSF and its target binding sites

A representative density profile of the d-statistic for change in H3K27T histone modification between 0 and 2 hours of retinoic acid treatment for the ENCODE region on chromosome 1

<p><b>Copyright information:</b></p><p>Taken from "Differential analysis for high density tiling microarray data"</p><p>http://www.biomedcentral.com/1471-2105/8/359</p><p>BMC Bioinformatics 2007;8():359-359.</p><p>Published online 24 Sep 2007</p><p>PMCID:PMC2231405.</p><p></p> The curves of different colors illustrate differential change for the H3K27T modification in exonic (green), intronic (black) and intergenic (blue) regions. The shift into the negative territory for the d-statistic for all classes of regions suggest is a consistent downward trend for this modification between 0 and 2 hours

The histogram summarizes the differential expression profiles in each ENCODE region on each chromosome

<p><b>Copyright information:</b></p><p>Taken from "Differential analysis for high density tiling microarray data"</p><p>http://www.biomedcentral.com/1471-2105/8/359</p><p>BMC Bioinformatics 2007;8():359-359.</p><p>Published online 24 Sep 2007</p><p>PMCID:PMC2231405.</p><p></p> Chromosome region specific differential expression is observed across the time-points – 30 percent change on chromosome 8 to no detectable change on chromosome 10. Globally, the highest fraction of differential expression when summarized across all transfrag is observed between 8–32 hours (53.8 percent),. The most statistically significant (FDR ≤12 percent) changes are also observed between 8–32 hours

D-statistic versus FDR relationship at putative TREs, across the time-series (IGB view)

<p><b>Copyright information:</b></p><p>Taken from "Differential analysis for high density tiling microarray data"</p><p>http://www.biomedcentral.com/1471-2105/8/359</p><p>BMC Bioinformatics 2007;8():359-359.</p><p>Published online 24 Sep 2007</p><p>PMCID:PMC2231405.</p><p></p> Examples of enrichment fragments are observed within and upstream of the second intron of the HIC gene (pink). The upstream fragment is possibly un-annotated (UA), in so far as no RefSeq annotation is available. The top four tracks represent the HisH4 p-value graphs at 0 (red), 2 (light-blue), 8 (dark-blue) and 32 (green) hours, scaled appropriately for comparison; the subsequent tracks represent the d-statistic (top) and FDR (bottom) pair for the 0–2 (red), 2–8 (cyan) and 8–32 (blue) hour time intervals. The horizontal lines associated with the FDR data refer to the 5 percent threshold in each case

Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function