NCBI Logo
GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
          Go
Series GSE66230 Query DataSets for GSE66230
Status Public on Oct 13, 2015
Title Subcellular whole transcriptome profiling reveals the RNA composition of motor axons
Organisms Homo sapiens; Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary Most RNAs within polarized cells such as neurons are sorted subcellularly in a coordinated manner. Despite advances in the development of methods for profiling polyadenylated RNAs from small amounts of input RNA, techniques for profiling coding and non-coding RNAs simultaneously are not well established. Here, we optimized a transcriptome profiling method based on double-random priming and applied it to serially diluted total RNA down to 10 pg. Read counts of expressed genes were robustly correlated between replicates, indicating that the method is both reproducible and scalable. Our transcriptome profiling method detected both coding and long non-coding RNAs sized >300 bases. Compared to total RNA-seq using a conventional approach, our protocol detected 70% more genes due to reduced capture of ribosomal RNAs. We used our method to analyze the RNA composition of compartmentalized motoneurons. The somatodendritic compartment was enriched for transcripts with post-synaptic functions as well as for certain nuclear non-coding RNAs such as 7SK. In axons, transcripts related to translation were enriched including the cytoplasmic non-coding RNA 7SL. Our profiling method can be applied to a wide range of investigations including perturbations of subcellular transcriptomes in neurodegenerative diseases, and investigations of microdissected tissue samples such as anatomically defined fiber tracts.
 
Overall design Total number of samples is 43
 
Contributor(s) Briese M, Saal L, Appenzeller S, Moradi M, Baluapuri A, Sendtner M
Citation(s) 26464439
Submission date Feb 23, 2015
Last update date Apr 12, 2023
Contact name Silke Appenzeller
E-mail(s) silke.appenzeller@uni-wuerzburg.de
Organization name University Wuerzburg
Street address Schweinfurter Str. 28
City W├╝rzburg
ZIP/Postal code 97076
Country Germany
 
Platforms (2)
GPL15520 Illumina MiSeq (Homo sapiens)
GPL16417 Illumina MiSeq (Mus musculus)
Samples (43)
GSM1617470 wt_ax_1
GSM1617471 wt_ax_2
GSM1617472 wt_ax_3
Relations
BioProject PRJNA276148
SRA SRP055447

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
GSE66230_RAW.tar 49.4 Mb (http)(custom) TAR (of CSV)
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