This SuperSeries is composed of the SubSeries listed below.
Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.
No sample metadata fields
View SamplesGenome-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.
Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.
No sample metadata fields
View SamplesGenome-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.
Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.
No sample metadata fields
View SamplesOFD1 is a centrosomal/basal body protein codified by a transcript that when mutated results in OFD type I (OFDI) syndrome, a pleiotropic disorders associated with ciliary dysfunction. We demonstrate that components of the Preinitiation complex of translation (PIC) colocalize to the centrosome and interact with OFD1. We showed that OFD1 functionally controls the protein synthesis machinery, modulating the translation of specific mRNAs in the kidney. Our results indicate a new role for a centrosomal/basal body protein. The dataset contains the microarray data on total and polysomal RNA from control and Ofd1-IND mutant kidneys at P8.
No associated publication
Specimen part, Subject
View SamplesGenome-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.
Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.
No sample metadata fields
View SamplesTotal RNA samples from Vax2 knockout mouse eyes (at least two biological replicates) were profiled by gene expression. As control we used total RNA from wild type eyes. The analysis was carried out at five different developmental stages: E10.5, E12.5, E16.5, P8, and P60.
Vax2 regulates retinoic acid distribution and cone opsin expression in the vertebrate eye.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
MicroRNA target prediction by expression analysis of host genes.
No sample metadata fields
View SamplesTotal RNA samples from three biological replicates in which the hsa-mir-26b was overexpressed in HeLa cells were profiled by gene expression. As negative control, we used total RNA samples from HeLa cells transfected with cel-mir-67
MicroRNA target prediction by expression analysis of host genes.
No sample metadata fields
View SamplesTotal RNA samples from three biological replicates in which the hsa-mir-98 was overexpressed in HeLa cells were profiled by gene expression. As negative control, we used total RNA samples from HeLa cells transfected with cel-mir-67
MicroRNA target prediction by expression analysis of host genes.
No sample metadata fields
View SamplesPBMC from house dust mite (HDM) sensitized atopics with or without asthma (or nonallergic controls) were cultured in the presence or absence of HDM extract for 24 hours.
Differential gene network analysis for the identification of asthma-associated therapeutic targets in allergen-specific T-helper memory responses.
Specimen part, Disease stage, Subject
View Samples