Subcellular distribution of tail-anchored proteins in Arabidopsis

KRIECHBAUMER, Verena, SHAW, Rowena, MUKHERJEE, Joy, BOWSHER, Caroline G., HARRISON, Anne-Marie and ABELL, Benjamin (2009). Subcellular distribution of tail-anchored proteins in Arabidopsis. Traffic, 10 (12), 1753-1764.

Full text not available from this repository.
Link to published version:: 10.1111/j.1600-0854.2009.00991.x

Abstract

Tail-anchored (TA) proteins function in key cellular processes in eukaryotic cells, such as vesicle trafficking, protein translocation and regulation of transcription. They anchor to internal cell membranes by a C-terminal transmembrane domain, which also serves as a targeting sequence. Targeting occurs post-translationally, via pathways that are specific to the precursor, which makes TA proteins a model system for investigating post-translational protein targeting. Bioinformatics approaches have previously been used to identify potential TA proteins in yeast and humans, yet little is known about TA proteins in plants. The identification of plant TA proteins is important for extending the post-translational model system to plastids, in addition to general proteome characterization, and the identification of functional homologues characterized in other organisms. We identified 454 loci that potentially encode TA proteins in Arabidopsis, and combined published data with new localization experiments to assign localizations to 130 proteins, including 29 associated with plastids. By analysing the tail anchor sequences of characterized proteins, we have developed a tool for predicting localization and estimate that 138 TA proteins are localized to plastids.

Item Type: Article
Research Institute, Centre or Group: Biomedical Research Centre
Identification Number: 10.1111/j.1600-0854.2009.00991.x
Depositing User: Sarah Ward
Date Deposited: 12 May 2010 10:22
Last Modified: 09 Oct 2012 10:18
URI: http://shura.shu.ac.uk/id/eprint/1871

Actions (login required)

View Item

Downloads

Downloads per month over past year

View more statistics