ABSTRACT: Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering” algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Keywords: time course, p63, keratinocytes
Project description:Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineeringâ algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Experiment Overall Design: Transient transfection of primary keratinocytes with Trp63-specific small interfering RNA oligonucleotides. Cell were collected 48h after transfection.
Project description:Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineeringâ algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Experiment Overall Design: Primary keratinocytes were infected with an EMPTY retrovirus and treated with with Tamoxifen, cells were collected every 20 minutes up to 1 hours, and every hour up to 4 hours.
Project description:Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineeringâ?? algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Experiment Overall Design: Primary keratinocytes were infected with a retrovirus carryng the DNp63alpha isform fused to the Estrogene receptor domain Upon induction with Tamoxifen, cells were collected every 20 minutes up to 4 hours.
Project description:Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering” algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Keywords: time course, p63, keratinocytes
Project description:Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering” algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites. Keywords: siRNA
2008-03-01 | GSE10564 | GEO
Project description:Identification of targets of transcription factor Trp63: primary keratinocytes
Project description:This SuperSeries is composed of the following subset Series:; GSE10562: Induction of ERDNp63a via Tamoxifen in primary keratinocytes; GSE10563: Primary keratinocytes treated with Tamoxifen; GSE10564: Silencing of p63 (trp63) in primary keratinocytes via siRNA oligo transfection. Experiment Overall Design: Refer to individual Series
Project description:The discovery of direct downstream targets of transcription factors (TFs) is necessary for understanding the genetic mechanisms underlying complex, highly regulated processes such as development. In this report, we have used a combinatorial strategy to conduct a genome-wide search for novel direct targets of Eyeless (Ey), a key transcription factor controlling early eye development in Drosophila. Like many other TFs, little is known for Ey direct downstream targets. To date, only one gene, sine oculis (so), has been identified as Ey direct targets in Drosophila. Therefore, it is crucial to identify additional targets in order to gain a better understanding of ey function. To overcome the lack of high quality consensus binding site sequences, phylogenetic shadowing of Ey binding sites in so was used to construct a position weight matrix (PWM) of the Ey protein. This PWM was then used for in silico prediction of potential binding sites in the Drosophila melanogaster genome. To reduce the false positive rate, conservation of these potential binding sites was assessed by comparing the genomic sequences from seven Drosophila species. In parallel, microarray analysis of wild-type versus ectopic ey-expressing tissue, followed by microarray-based epistasis experiments in an atonal (ato) mutant background, identified 188 genes induced by ey. Intersection of in silico predicted conserved Ey binding sites with the candidate gene list produced through expression profiling yields a list of 20 putative ey-induced, eye-enriched, ato-independent, direct targets of Ey, including so. The accuracy of this list of genes was confirmed using both in vitro and in vivo methods. Initial analysis reveals three genes, eyes absent, shifted, and Optix, as novel direct targets of Ey. These results suggest that the integrated strategy of computational biology, genomics, and genetics is a powerful approach that can be applied to systematically identify direct downstream targets for any transcription factor genome-wide.
Project description:A relatively small number of proneural transcription factors specify a multitude of neural progenitor populations in the developing mammalian brain. Despite their importance, little is known about their targets, cellular processes they regulate, or what genomic sites they occupy in vivo. We used an integrated experimental and computational approach, combining RNA-seq, Histone-seq, and Atoh1 ChIP-seq in cerebellar tissue, to identify over 600 targets of Atoh1, an important developmental transcription factor. We validated 10% of these targets and found that Atoh1 directly regulates genes involved not only in early proliferation but also later differentiation, migration, cell adhesion, metabolism, and cytoskeletal organization by recognizing a novel 10 nucleotide Atoh1 E-Box associated motif (AtEAM). This Atoh1 “targetome” is not only a resource for studies aimed at understanding the molecular mechanisms involved in cerebellar development, but our integrated approach provides a framework for future in vivo studies of transcription factors and their targetomes. Examination of RNA-seq WT and null expression data (2 reps each), 2 different histone modifications (2 rep each) and IgG control, and Atoh1 DNA-binding (2 reps each) and control in the developing cerebellum
Project description:A relatively small number of proneural transcription factors specify a multitude of neural progenitor populations in the developing mammalian brain. Despite their importance, little is known about their targets, cellular processes they regulate, or what genomic sites they occupy in vivo. We used an integrated experimental and computational approach, combining RNA-seq, Histone-seq, and Atoh1 ChIP-seq in cerebellar tissue, to identify over 600 targets of Atoh1, an important developmental transcription factor. We validated 10% of these targets and found that Atoh1 directly regulates genes involved not only in early proliferation but also later differentiation, migration, cell adhesion, metabolism, and cytoskeletal organization by recognizing a novel 10 nucleotide Atoh1 E-Box associated motif (AtEAM). This Atoh1 “targetome” is not only a resource for studies aimed at understanding the molecular mechanisms involved in cerebellar development, but our integrated approach provides a framework for future in vivo studies of transcription factors and their targetomes.