Browse
Submit Data
Databases
API
Help

Dataset Information

54 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Toward a functional annotation of the human genome using artificial transcription factors.

ABSTRACT: We have developed a novel, high-throughput approach to collecting randomly perturbed gene-expression profiles from the human genome.A human 293 cell library that stably expresses randomly chosen zinc-finger transcription factors was constructed, and the expression profile of each cell line was obtained using cDNA microarray technology.Gene expression profiles from a total of 132 cell lines were collected and analyzed by (1) a simple clustering method based on expression-profile similarity, and (2) the shortest-path analysis method. These analyses identified a number of gene groups, and further investigation revealed that the genes that were grouped together had close biological relationships. The artificial transcription factor-based random genome perturbation method thus provides a novel functional genomic tool for annotation and classification of genes in the human genome and those of many other organisms.

SUBMITTER: Lee DK

PROVIDER: S-EPMC403813 | biostudies-literature | 2003 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Toward a functional annotation of the human genome using artificial transcription factors.

Lee Dong-ki DK Park Jin Woo JW Kim Youn-Jae YJ Kim Jiwon J Lee Yangsoon Y Kim Jeonglim J Kim Jin-Soo JS

Genome research 20031201 12

We have developed a novel, high-throughput approach to collecting randomly perturbed gene-expression profiles from the human genome.A human 293 cell library that stably expresses randomly chosen zinc-finger transcription factors was constructed, and the expression profile of each cell line was obtained using cDNA microarray technology.Gene expression profiles from a total of 132 cell lines were collected and analyzed by (1) a simple clustering method based on expression-profile similarity, and ( ...[more]

PMID: 14656973

Similar Datasets

Toward a functional annotation of the human genome using artificial transcription factors

Project description:Toward a functional annotation of the human genome using artificial transcription factors. Keywords: other

2003-12-12 | GSE677 | GEO

Toward a functional annotation of the human genome using artificial transcription factors

Project description:Toward a functional annotation of the human genome using artificial transcription factors.

2010-06-05 | E-GEOD-677 | biostudies-arrayexpress

Enhancement of Arabidopsis growth characteristics using genome interrogation with artificial transcription factors.

Project description:The rapidly growing world population has a greatly increasing demand for plant biomass, thus creating a great interest in the development of methods to enhance the growth and biomass accumulation of crop species. In this study, we used zinc finger artificial transcription factor (ZF-ATF)-mediated genome interrogation to manipulate the growth characteristics and biomass of Arabidopsis plants. We describe the construction of two collections of Arabidopsis lines expressing fusions of three zinc fingers (3F) to the transcriptional repressor motif EAR (3F-EAR) or the transcriptional activator VP16 (3F-VP16), and the characterization of their growth characteristics. In total, six different 3F-ATF lines with a consistent increase in rosette surface area (RSA) of up to 55% were isolated. For two lines we demonstrated that 3F-ATF constructs function as dominant in trans acting causative agents for an increase in RSA and biomass, and for five larger plant lines we have investigated 3F-ATF induced transcriptomic changes. Our results indicate that genome interrogation can be used as a powerful tool for the manipulation of plant growth and biomass and that it might supply novel cues for the discovery of genes and pathways involved in these properties.

| S-EPMC5373528 | biostudies-literature

Genome-wide functional perturbation of human microsatellite repeats using engineered zinc finger transcription factors.

Project description:Repeat elements can be dysregulated at a genome-wide scale in human diseases. For example, in Ewing sarcoma, hundreds of inert GGAA repeats can be converted into active enhancers when bound by EWS-FLI1. Here we show that fusions between EWS and GGAA-repeat-targeted engineered zinc finger arrays (ZFAs) can function at least as efficiently as EWS-FLI1 for converting hundreds of GGAA repeats into active enhancers in a Ewing sarcoma precursor cell model. Furthermore, a fusion of a KRAB domain to a ZFA can silence GGAA microsatellite enhancers genome wide in Ewing sarcoma cells, thereby reducing expression of EWS-FLI1-activated genes. Remarkably, this KRAB-ZFA fusion showed selective toxicity against Ewing sarcoma cells compared with non-Ewing cancer cells, consistent with its Ewing sarcoma-specific impact on the transcriptome. These findings demonstrate the value of ZFAs for functional annotation of repeats and illustrate how aberrant microsatellite activities might be regulated for potential therapeutic applications.

| S-EPMC9374162 | biostudies-literature

Systematic target function annotation of human transcription factors.

Project description:BACKGROUND:Transcription factors (TFs), the key players in transcriptional regulation, have attracted great experimental attention, yet the functions of most human TFs remain poorly understood. Recent capabilities in genome-wide protein binding profiling have stimulated systematic studies of the hierarchical organization of human gene regulatory network and DNA-binding specificity of TFs, shedding light on combinatorial gene regulation. We show here that these data also enable a systematic annotation of the biological functions and functional diversity of TFs. RESULT:We compiled a human gene regulatory network for 384 TFs covering the 146,096 TF-target gene (TF-TG) relationships, extracted from over 850 ChIP-seq experiments as well as the literature. By integrating this network of TF-TF and TF-TG relationships with 3715 functional concepts from six sources of gene function annotations, we obtained over 9000 confident functional annotations for 279 TFs. We observe extensive connectivity between TFs and Mendelian diseases, GWAS phenotypes, and pharmacogenetic pathways. Further, we show that TFs link apparently unrelated functions, even when the two functions do not share common genes. Finally, we analyze the pleiotropic functions of TFs and suggest that the increased number of upstream regulators contributes to the functional pleiotropy of TFs. CONCLUSION:Our computational approach is complementary to focused experimental studies on TF functions, and the resulting knowledge can guide experimental design for the discovery of unknown roles of TFs in human disease and drug response.

| S-EPMC5795274 | biostudies-literature

Comparative annotation of functional regions in the human genome using epigenomic data.

Project description:Epigenetic regulation is dynamic and cell-type dependent. The recently available epigenomic data in multiple cell types provide an unprecedented opportunity for a comparative study of epigenetic landscape. We developed a machine-learning method called ChroModule to annotate the epigenetic states in eight ENCyclopedia Of DNA Elements cell types. The trained model successfully captured the characteristic histone-modification patterns associated with regulatory elements, such as promoters and enhancers, and showed superior performance on identifying enhancers compared with the state-of-art methods. In addition, given the fixed number of epigenetic states in the model, ChroModule allows straightforward illustration of epigenetic variability in multiple cell types. Using this feature, we found that invariable and variable epigenetic states across cell types correspond to housekeeping functions and stimulus response, respectively. Especially, we observed that enhancers, but not the other regulatory elements, dictate cell specificity, as similar cell types share common enhancers, and cell-type-specific enhancers are often bound by transcription factors playing critical roles in that cell type. More interestingly, we found some genomic regions are dormant in cell type but primed to become active in other cell types. These observations highlight the usefulness of ChroModule in comparative analysis and interpretation of multiple epigenomes.

| S-EPMC3632130 | biostudies-literature

Genome-wide functional perturbation of human microsatellite repeats using engineered zinc finger transcription factors

Project description:Genome-wide functional perturbation of human microsatellite repeats using engineered zinc finger transcription factors

2022-06-30 | GSE163886 | GEO

Phenotypic engineering by reprogramming gene transcription using novel artificial transcription factors in Escherichia coli.

Project description:Now that many genomes have been sequenced and the products of newly identified genes have been annotated, the next goal is to engineer the desired phenotypes in organisms of interest. For the phenotypic engineering of microorganisms, we have developed novel artificial transcription factors (ATFs) capable of reprogramming innate gene expression circuits in Escherichia coli. These ATFs are composed of zinc finger (ZF) DNA-binding proteins, with distinct specificities, fused to an E. coli cyclic AMP receptor protein (CRP). By randomly assembling 40 different types of ZFs, we have constructed more than 6.4 x 10(4) ATFs that consist of 3 ZF DNA-binding domains and a CRP effector domain. Using these ATFs, we induced various phenotypic changes in E. coli and selected for industrially important traits, such as resistance to heat shock, osmotic pressure and cold shock. Genes associated with the heat-shock resistance phenotype were then characterized. These results and the general applicability of this platform clearly indicate that novel ATFs are powerful tools for the phenotypic engineering of microorganisms and can facilitate microbial functional genomic studies.

| S-EPMC2532725 | biostudies-literature

Reprogramming cell fate with a genome-scale library of artificial transcription factors.

Project description:Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.

| S-EPMC5187731 | biostudies-literature

Whole-genome annotation by using evidence integration in functional-linkage networks.

Project description:The advent of high-throughput biology has catalyzed a remarkable improvement in our ability to identify new genes. A large fraction of newly discovered genes have an unknown functional role, particularly when they are specific to a particular lineage or organism. These genes, currently labeled "hypothetical," might support important biological cell functions and could potentially serve as targets for medical, diagnostic, or pharmacogenomic studies. An important challenge to the scientific community is to associate these newly predicted genes with a biological function that can be validated by experimental screens. In the absence of sequence or structural homology to known genes, we must rely on advanced biotechnological methods, such as DNA chips and protein-protein interaction screens as well as computational techniques to assign putative functions to these genes. In this article, we propose an effective methodology for combining biological evidence obtained in several high-throughput experimental screens and integrating this evidence in a way that provides consistent functional assignments to hypothetical genes. We use the visualization method of propagation diagrams to illustrate the flow of functional evidence that supports the functional assignments produced by the algorithm. Our results contain a number of predictions and furnish strong evidence that integration of functional information is indeed a promising direction for improving the accuracy and robustness of functional genomics.

| S-EPMC365715 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data