|
| Status |
Public on Oct 15, 2015 |
| Title |
CG9754_het_rep1_RNAseq |
| Sample type |
SRA |
| |
|
| Source name |
adult fly ovaries
|
| Organism |
Drosophila melanogaster |
| Characteristics |
age: 3-5 old
tissue: Ovary
|
| Treatment protocol |
Flies were fed with yeast paste. Germline specific knockdowns were done as described (Czech et al., 2013 Mol Cell). CRISPR/Cas9 mediated generation of CG9754 mutants were done as described (Port et al., 2014 PNAS).
|
| Growth protocol |
All fly stocks were maintained at 25°C on standard diet.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was prepared with Trizol reagent (Invitrogen)
Transcriptome libraries were prepared according (Armour et al. 2009, Nat Methods) using not-so-random priming (NSR). 1 ug total RNA was revere transcribed using SuperScript III enzyme with first-strand NSR primer. RNA template was removed with RNase H (Invitrogen) Then cDNA was mixed with exo− Klenow fragment (NEB) second-strand NSR primer to synthesize the second strand. For PCR amplification, purified second-strand synthesis reaction were mixed with ExpandPLUS enzyme (Roche) and PE-P5-SBS3 and PE-P7-SBS8 primers. Products were run on a 2% low-melt agarose gel, and the 200–500 bp. range were purified.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina MiSeq |
| |
|
| Description |
NSR RNAseq
|
| Data processing |
The RNA-seq data were mapped using the STAR software package (version 2.3.0) with allowing up to 100 multi-alignment per read to get reads mapped to transposons.
Feature abundance estimations and the differential analysis were conducted using the TEtranscripts software package (http://hammelllab.labsites.cshl.edu/software/) . TEtranscripts distributes multi-mapped reads evenly among all potential matches at the initial step and using Expectation-Maximization approach to optimize the distribution of multi-mapped reads. TEtranscripts computes the gene abundances and transposon abundances at the same time, and integrates the gene count table and transposon count table into one count table and input to the DESeq package for the differential analsyis.
We used the DESeq package with suggested parameters as described above, accepting only changes greater than twofold, with adjusted p-values < 0.05 and counts per feature >20.
Genome_build: dm3/2006
Supplementary_files_format_and_content: results of DESeq analysis for transposons or genes which are deferentially expressed under the indicated experimental conditions include fold change in raw counts normalized according to DESeq protocol (Anders and Huber 2010, Genome Biol 11:R106) and p-values.
|
| |
|
| Submission date |
Jul 27, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Yang Yu |
| E-mail(s) |
yyu@cshl.edu
|
| Organization name |
Cold Spring Harbor Laboratory
|
| Lab |
Hannon Lab
|
| Street address |
One Bungtown Road
|
| City |
Cold Spring Harbor |
| State/province |
NY |
| ZIP/Postal code |
11724 |
| Country |
USA |
| |
|
| Platform ID |
GPL16479 |
| Series (2) |
| GSE71371 |
Panoramix enforces piRNA-dependent co-transcriptional silencing (RNA-Seq) |
| GSE71374 |
Panoramix enforces piRNA-dependent co-transcriptional silencing |
|
| Relations |
| Reanalyzed by |
GSM3276490 |
| BioSample |
SAMN03939087 |
| SRA |
SRX1120731 |
