Transcriptomics

Dataset Information

0

Membrane-associated transcripts in Arabidopsis; their isolation...


ABSTRACT: Membrane-associated, integral membrane and secreted proteins are of key importance in many cellular processes. For most of the 28 952 predicted proteins in Arabidopsis, the actual subcellular localisation has not been demonstrated experimentally. So far, their potential membrane-association has been deduced from algorithms that predict transmembrane domains and signal peptides. However, the comprehensiveness and accuracy of these algorithms is still limited. The majority of membrane-associated and secreted proteins is synthesised on membrane-bound polysomes. Therefore, the isolation and characterisation of mRNA associated with membrane-bound polysomes offers an experimental tool for the genome-wide identification of these proteins. Here we describe an efficient method to isolate mRNA from membrane-bound polysomes and report on the validation of the method to enrich for transcripts encoding membrane-associated and secreted proteins. The sensitivity and reproducibility of the isolation method was investigated by DNA microarray analysis. Pearson correlations between transcript levels obtained from three replicate isolations showed that the method is highly reproducible. A significant enrichment for mRNAs encoding proteins containing predicted transmembrane domains and signal peptides was observed in the membrane-bound polysomal fraction. In this fraction, 301 transcripts were classified by gene ontologies as ‘cellular component unknown’, and potentially encode previously unrecognised secreted or membrane-associated proteins. Keywords: mRNA localisation, mRNA fractionation, predict protein localisation

ORGANISM(S): Arabidopsis thaliana

PROVIDER: GSE4023 | GEO | 2006/03/17

SECONDARY ACCESSION(S): PRJNA95125

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2010-07-01 | E-GEOD-4023 | biostudies-arrayexpress
2005-08-24 | E-GEOD-3180 | biostudies-arrayexpress
2019-04-18 | GSE118873 | GEO
2005-08-24 | GSE3180 | GEO
2024-03-28 | GSE247682 | GEO
2004-12-01 | GSE1400 | GEO
2007-07-29 | E-GEOD-1400 | biostudies-arrayexpress
2017-12-31 | GSE99826 | GEO
| PRJNA85165 | ENA
2016-08-03 | E-GEOD-74393 | biostudies-arrayexpress