Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of Wheat-Phytase transgenic plants vs a non-transgenic control line at three different developmental stages of the seed

ABSTRACT: A transgenic wheat line was compared for gene expression patterns to a non-transgenic control line at three different developmental stages of the seed. The three successive developmental stages were also compared for each of the two lines. Thus, a factorial experiment with three developmental stages and two genotypes. In total 8 hybridizations were performed.

ORGANISM(S): Triticum aestivum

SUBMITTER: Preben Bach Holm

PROVIDER: E-MEXP-368 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat.

Gregersen Per L PL Brinch-Pedersen Henrik H Holm Preben B PB

Transgenic research 20051201 6

Global, comparative gene expression analysis is potentially a very powerful tool in the safety assessment of transgenic plants since it allows for the detection of differences in gene expression patterns between a transgenic line and the mother variety. In the present study, we compared the gene expression profile in developing seeds of wild type wheat and wheat transformed for endosperm-specific expression of an Aspergillus fumigatus phytase. High-level expression of the phytase gene was ensure ...[more]

PMID: 16315094

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Project description:Missense mutations in the TP53 gene are frequent genetic alterations in human tumor tissue and cell lines. In contrast to wild-type p53, the mutant p53 (mutp53) protein has lost the transcriptional activity towards pro-apoptotic and growth arrest genes, but retained the property to interact with DNA in a structure-specific fashion. Expression of mutp53 is advantageous for tumor cells, however the molecular mechanism of mutp53 action is still not known. We used the glioblastoma-derived U-251 MG human cell line to analyze DNA binding of mutant p53 (R273H mutation) on a Nimblegen custom 135k tiling array and to correlate mutp53 binding regions with the epigenetic state and occupation by other transcription factors (ETS1 and SP1). We found that mutp53-binding regions are G/C-rich and are located around transcriptional start sites (TSS) of many protein-coding genes, which in most cases are active, but are not always regulated upon transient mutp53 depletion. We propose a model which does not only rely on interactions of mutp53 with diverse transcriptional regulators at active promoters, but primarily is based on a DNA binding activity of mutp53. We designed a Nimblegen custom 135k tiling array that covers a large set of putative and known p53 (wild-type and mutant) target genes in the human genome. For analysis of the epigenetic state of genes covered by the tiling array in control and mutant p53-depleted U251 cells we focused on changes in active histone marks, H3K4me3 and H3K9Ac, and RNA polymerase II recruitment and processivity. H3K4me3 and H3K9Ac marks are enriched in active promoter regions and the phosphorylation of serine 5 (S5-P) and serine 2 (S2-P) in the CTD of RNA polymerase II have been described to define initiated and elongating complexes, respectively. We performed the ChIP-chip experiments for H3K4me3, H3K9Ac, RNA polymerase II (S5-P) and RNA polymerase II (S2-P) from U251 cells transfected with p53-specific siRNA or control siRNA (2 biological replicates each). To analyze binding of mutant p53 to the genes covered by the tiling array we performed mutant p53 ChIP-chip experiments in 4 biological replicates of. In addition, we analyzed the distribution of SP1 and ETS1 binding sites in 3 biological replicates.

Dataset Information

Transcription profiling of Wheat-Phytase transgenic plants vs a non-transgenic control line at three different developmental stages of the seed

Publications

A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat.

Similar Datasets

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