2 resultados para qPCR

em University of Queensland eSpace - Australia


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Transgenic tobacco plants, carrying a Potato virus Y (PVY)-NIa hairpin sequence separated by a unique unrelated spacer sequence were specifically silenced and highly resistant to PVY infection. In such plants neither PVY-NIa nor spacer transgene transcripts were detectable by specific quantitative real time reverse transcriptase PCR (RT-qPCR) assays of similar relative efficiencies developed for direct comparative analysis. However, small interfering RNAs (siRNAs) specific for the PVY sequence of the transgene and none specific for the LNYV spacer sequence were detected. Following infection with Cucumber mosaic virus (CMV), which suppresses dsRNA-induced RNA silencing, transcript levels of PVY-NIa as well as spacer sequence increased manifold with the same time course. The cellular abundance of the single-stranded (ss) spacer sequence was consistently higher than that of PVY dsRNA in all cases. The results show that during RNA silencing and its suppression of a hairpin transcript in transgenic tobacco, the ssRNA spacer sequence is affected differently than the dsRNA. In PVY-silenced plants. the spacer is efficiently degraded by a mechanism not involving the accumulation of siRNAs, while following suppression of RNA silencing by CMV, the spacer appears protected from degradation. Crown Copyright (c) 2006 Published by Elsevier B.V. All rights reserved.

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Transcriptional regulatory networks govern cell differentiation and the cellular response to external stimuli. However, mammalian model systems have not yet been accessible for network analysis. Here, we present a genome-wide network analysis of the transcriptional regulation underlying the mouse macrophage response to bacterial lipopolysaccharide (LPS). Key to uncovering the network structure is our combination of time-series cap analysis of gene expression with in silico prediction of transcription factor binding sites. By integrating microarray and qPCR time-series expression data with a promoter analysis, we find dynamic subnetworks that describe how signaling pathways change dynamically during the progress of the macrophage LPS response, thus defining regulatory modules characteristic of the inflammatory response. In particular, our integrative analysis enabled us to suggest novel roles for the transcription factors ATF-3 and NRF-2 during the inflammatory response. We believe that our system approach presented here is applicable to understanding cellular differentiation in higher eukaryotes. (c) 2006 Elsevier Inc. All rights reserved.