A gateway-compatible yeast one-hybrid system

Bart Deplancke
2004
Article

Résumé

Since the advent of microarrays, vast amounts of gene expression data have been generated. However, these microarray data fail to reveal the transcription regulatory mechanisms that underlie differential gene expression, because the identity of the responsible transcription factors (TFs) often cannot be directly inferred from such data sets. Regulatory TFs activate or repress transcription of their target genes by binding to cis-regulatory elements that are frequently located in a gene's promoter. To understand the mechanisms underlying differential gene expression, it is necessary to identify physical interactions between regulatory TFs and their target genes. We developed a Gateway-compatible yeast one-hybrid (Y1H) system that enables the rapid, large-scale identification of protein-DNA interactions using both small (i.e., DNA elements of interest) and large (i.e., gene promoters) DNA fragments. We used four well-characterized Caenorhabditis elegans promoters as DNA baits to test the functionality of this Y1H system. We could detect approximately 40% of previously reported TF-promoter interactions. By performing screens using two complementary libraries, we found novel potentially interacting TFs for each promoter. We recapitulated several of the Y1H-based protein-DNA interactions using luciferase reporter assays in mammalian cells. Taken together, the Gateway-compatible Y1H system will allow the high-throughput identification of protein-DNA interactions and may be a valuable tool to decipher transcription regulatory networks.

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https://infoscience.epfl.ch/record/125659?ln=fr

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Bart Deplancke
2004
Article

Résumé

Official source

https://infoscience.epfl.ch/record/125659?ln=fr

À propos de ce résultat

Concepts associés (19)

Concepts associés

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Publications associées (106)

Publications associées

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Genomic Context and KRAB/KAP1-mediated Transcriptional Repression

Sylvain Meylan

Chromatin structure and its impact on transcriptional activity represent one of the major revolutions in the biomedical field over the passed decade. The implications concern as much fundamental as clinically-oriented research; diseases and therapeutical strategies are being approached from a new point of view (Mackay et al., 2008; Richman et al., 2009). The current work dissects the different susceptibilities of genes in the human genome and how these react to the changes in chromatin landscape upon the recruitment of a transcriptional corepressor. The KRAB-Zinc finger proteins are the largest family of transcriptional repressors in the human genome. These repressors use the KRAB domain as a docking site for KAP-1 which in turn recruits a macromolecular chromatin-remodelling complex leading to heterochromatin formation. Yet current knowledge of their impact on gene regulation is limited. By artificially recruiting a KRAB-repressor in the context of genes, our lab has previously shown that this repression can act over several tens of kilobases (Groner et al., 2010). Specifically, transcriptional silencing depends on the spreading of repressive marks to the upstream promoter. However, such spreading to the trapped promoter is not systematic, suggesting potential counter-acting influences. To identify the determinants of repression, we designed a high-throughput approach of our experimental system to accumulate thousands of KRAB docking sites for which the trapped promoter is regulable and docking sites for which the promoter is immune to repression. Firstly, our data indicate that KRAB/KAP-1-repression can act efficiently over distances of 20 kb albeit in a very variable fashion, but is limited beyond that. Second, propagation of repression in the transcribed regions was favoured in most open chromatin. Third, we observed that the broader context of genes sustaining repression was that of most euchromatic regions, recapitulating the genetic context of natural targets of KAP1 repression. On the other hand, we have no evidence that barrier elements such as CTCF counteract this KRAB-mediated repression within genes. Finally, work on cases where repression acts over distances greater than 40 kb hints at the regulation of enhancers by our KRAB repressor rather than promoter. In conclusion, this work broadens the knowledge in the emerging field of gene regulation and provides further insight on the complexity of chromatin architecture and its meaning at a functional level.

EPFL2010

Chargement

Relationship between estrogen receptor alpha location and gene induction reveals the importance of downstream sites and cofactors

Mauro Delorenzi, Felix Naef

BACKGROUND: To understand cancer-related modifications to transcriptional programs requires detailed knowledge about the activation of signal-transduction pathways and gene expression programs. To investigate the mechanisms of target gene regulation by human estrogen receptor alpha (hERalpha), we combine extensive location and expression datasets with genomic sequence analysis. In particular, we study the influence of patterns of DNA occupancy by hERalpha on expression phenotypes. RESULTS: We find that strong ChIP-chip sites co-localize with strong hERalpha consensus sites and detect nucleotide bias near hERalpha sites. The localization of ChIP-chip sites relative to annotated genes shows that weak sites are enriched near transcription start sites, while stronger sites show no positional bias. Assessing the relationship between binding configurations and expression phenotypes, we find binding sites downstream of the transcription start site (TSS) to be equally good or better predictors of hERalpha-mediated expression as upstream sites. The study of FOX and SP1 cofactor sites near hERalpha ChIP sites shows that induced genes frequently have FOX or SP1 sites. Finally we integrate these multiple datasets to define a high confidence set of primary hERalpha target genes. CONCLUSION: Our results support the model of long-range interactions of hERalpha with the promoter-bound cofactor SP1 residing at the promoter of hERalpha target genes. FOX motifs co-occur with hERalpha motifs along responsive genes. Importantly we show that the spatial arrangement of sites near the start sites and within the full transcript is important in determining response to estrogen signaling.

BioMed Central2009

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Excess fat mass in obese individuals, which is characterized by an increase of white adipocyte cell size and number, significantly raises the risk of developing metabolic syndrome symptoms as well as cancer. A detailed understanding of the transcriptional mechanisms mediating white adipocyte differentiation (i.e., adipogenesis) is required to counteract the growing obesity epidemics. In this thesis, we have implemented two combinatory approaches to detect new protein-DNA interactions in the mouse, one of which targets the adipogenic gene regulatory network (GRN) that underlies the white adipocyte differentiation process. As a first approach to shed light on GRNs, we have developed and validated a powerful approach that combines a high-throughput yeast one-hybrid-based (Y1H) system to detect transcription factors (TFs)-DNA element interactions, together with a novel microfluidics-based technique, enabling the identification and characterization of individual binding sites for detected TFs within the respective regulatory sequences at unprecedented throughput and resolution. Using well-described regulatory elements as well as an uncharacterized enhancer which can play also a role in adipogenesis, we show that our approach in a first phase uncovers many known as well as novel TF-DNA interactions, of which a large proportion were independently validated. In addition, we further demonstrate how our approach can be used in a second phase to characterize detected interactions by enabling the generation of a relative DNA occupancy landscape over the length of the respective DNA element. Furthermore, we provide evidence that this system enables the detection of novel interactions that may have in vivo relevance. Given the strict requirements for direct and well-characterized protein-DNA interaction data to generate and model gene regulatory networks, the presented two-tiered approach should be of great value to enhance our understanding of the regulatory principles underlying mouse gene expression. To identify transcription factors involved in white adipocyte differentiation, we overexpressed TFs in preadipocytes and quantified their effect on differentiation. To this end, we have created a mouse open-reading frame resource consisting of more than 750 fully sequence-verified TF clones. We transferred these TF clones to a Tet-On lentiviral vector and used them to infect white preadipocytes. Based on microscopy-assisted quantification of lipids after induction of differentiation, we identified putatively novel TF candidates that strongly enhanced differentiation based on the increased lipid accumulation, indicating a potential role in adipogenesis. Gene expression and ChIP-seq experiments have been performed for the three top candidates (ZEB1, ZFP30 and ZFP277) to further study their function within the adipogenic regulatory network. To assess whether the effect of these TFs on adipogenesis could be reproduced in vivo, murine adipose stromal-vascular fraction containing adipocyte precursor cells were implanted into mice fed a high-fat diet, after each of the three TF candidates were knockdown or overexpressed in these cells. This experiment and the RNA-seq analyses are currently being processed while this thesis is being written. Furthermore, due to the absence of quantitative real-time PCR (qPCR) primer designing tools that would allow for gene-specific expression profiling in a high-throughput fashion, we design a user-friendly platform: GETPrime. This platform uniquely combines and automates several features critical to optimal qPCR primer design for all annotated Homo sapiens, Mus musculus, Caenorhabditis elegans, Drosophila melanogaster and Danio rerio genes in the Ensembl database. GETPrime primers have been extensively validated experimentally, demonstrating their high quality as well as high transcript specificity in complex samples.

EPFL2013

Chargement

Genomic Context and KRAB/KAP1-mediated Transcriptional Repression

Sylvain Meylan

EPFL2010

EPFL2013