Dataset Information

Isolation of cellular promoters by using a retrovirus promoter trap.

ABSTRACT: A retrovirus vector has been used to isolate transcriptional promoters from mammalian cells. The virus contains a selectable gene encoding histidinol dehydrogenase (his) in the U3 region of the 3' long terminal repeat (LTR). When the virus is passaged, duplication of LTRs places his sequences just 30 nucleotides from the adjacent cellular DNA. As a result, selection for histidinol resistance generates cell clones in which his is expressed on transcripts initiating in the flanking cellular DNA. Upstream cellular sequences, cloned after amplification by polymerase chain reaction, hybridized to RNA from uninfected cells, indicating that the adjacent promoters were transcriptionally active prior to virus integration. Two cloned transcribed flanking sequences also contained highly active transcriptional promoters, as estimated by their ability to activate expression of a linked reporter gene. Thus, U3His vectors provide a rapid and efficient means to isolate promoters active in different cell types. Moreover, by selecting for cell clones containing proviruses integrated in expressed genes, the virus may make an effective insertional mutagen.

SUBMITTER: von Melchner H

PROVIDER: S-EPMC53977 | biostudies-other | 1990 May

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Isolation of cellular promoters by using a retrovirus promoter trap.

von Melchner H H Reddy S S Ruley H E HE

Proceedings of the National Academy of Sciences of the United States of America 19900501 10

A retrovirus vector has been used to isolate transcriptional promoters from mammalian cells. The virus contains a selectable gene encoding histidinol dehydrogenase (his) in the U3 region of the 3' long terminal repeat (LTR). When the virus is passaged, duplication of LTRs places his sequences just 30 nucleotides from the adjacent cellular DNA. As a result, selection for histidinol resistance generates cell clones in which his is expressed on transcripts initiating in the flanking cellular DNA. U ...[more]

PMID: 2339116

Similar Datasets

Project description:BackgroundA complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and algorithms for predicting transcriptional regulatory mechanisms from sequence, gene expression, and binding data. However, most of these studies involved the use of yeast which has much simpler regulatory networks than human and has many genome wide binding data and gene expression data under diverse conditions. Studies of genome wide transcriptional networks of human genomes currently lag behind those of yeast.ResultsWe report herein a new method that combines gene expression data analysis with promoter analysis to infer transcriptional regulatory elements of human genes. The Z scores from the application of gene set analysis with gene sets of transcription factor binding sites (TFBSs) were successfully used to represent the activity of TFBSs in a given microarray data set. A significant correlation between the Z scores of gene sets of TFBSs and individual genes across multiple conditions permitted successful identification of many known human transcriptional regulatory elements of genes as well as the prediction of numerous putative TFBSs of many genes which will constitute a good starting point for further experiments. Using Z scores of gene sets of TFBSs produced better predictions than the use of mRNA levels of a transcription factor itself, suggesting that the Z scores of gene sets of TFBSs better represent diverse mechanisms for changing the activity of transcription factors in the cell. In addition, cis-regulatory modules, combinations of co-acting TFBSs, were readily identified by our analysis.ConclusionBy a strategic combination of gene set level analysis of gene expression data sets and promoter analysis, we were able to identify and predict many transcriptional regulatory elements of human genes. We conclude that this approach will aid in decoding some of the important transcriptional regulatory elements of human genes.

Dataset Information

Isolation of cellular promoters by using a retrovirus promoter trap.

Publications

Isolation of cellular promoters by using a retrovirus promoter trap.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets