GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
Series GSE66135 Query DataSets for GSE66135
Status Public on Jun 30, 2015
Title Allele-selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-coding and Noncoding RNAs, and RNA Isoforms
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Non-coding RNA profiling by high throughput sequencing
Genome variation profiling by high throughput sequencing
Summary Purpose: mRNA translation into protein is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants has yet to be systematically studied. Using high-throughput sequencing (RNA-seq), we have measured cellular levels of mRNAs and ncRNAs, and their isoforms, in lymphoblast cell lines (LCL) and in polysomal fractions, the latter shown to yield strong correlations of mRNAs with expressed protein levels. Analysis of allelic RNA ratios at heterozygous SNPs served to reveal genetic factors in ribosomal loading.
Methods: RNA-seq was performed on cytosolic extracts and polysomal fractions (3 ribosomes or more) from three lymphoblastoid cell lines. As each RNA fraction was amplified (NuGen kit), and relative contributions from various RNA classes differed between cytosol and polysomes, the fraction of any given RNA species loaded onto polysomes was difficult to quantitate. Therefore, we focused on relative recovery of the various RNA classes and rank order of single RNAs compared to total RNA.
Results: RNA-seq of coding and non-coding RNAs (including microRNAs) in three LCLs revealed significant differences in polysomal loading of individual RNAs and isoforms, and between RNA classes. Moreover, correlated distribution between protein-coding and non-coding RNAs suggests possible interactions between them. Allele-selective RNA recruitment revealed strong genetic influence on polysomal loading for multiple RNAs. Allelic effects can be attributed to generation of different RNA isoforms before polysomal loading or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Several variants and genes identified by this approach are also associated with RNA expression and clinical phenotypes in various databases.
Conclusions: These results provide a novel approach using complete transcriptome RNA-seq to study polysomal RNA recruitment and regulatory variants affecting protein translation.
Overall design cells from 3 samples were grown to 5x105 cells/mL density in T75 tissue culture flask and harvested, total RNA and polysome bound RNA was sequenced by Ion Proton
Contributor(s) Webb A, Mascarenhas R, Pietrzak M
Citation(s) 26331722
Submission date Feb 20, 2015
Last update date May 15, 2019
Contact name Amy Hite
Organization name The Ohio State University
Department Biomedical Informatics
Street address 1800 Cannon Drive 250 Lincoln Tower
City Columbus
State/province OH - Ohio
ZIP/Postal code 43210
Country USA
Platforms (1)
GPL17303 Ion Torrent Proton (Homo sapiens)
Samples (6)
GSM1614895 LCL14_Total
GSM1614896 LCL14_Polysome
GSM1614897 LCL19_Total
BioProject PRJNA276073
SRA SRP055413

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE66135_RAW.tar 72.4 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap