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Status |
Public on Oct 15, 2015 |
Title |
nanosGAL4_dsWhite_rep2_GROseq |
Sample type |
SRA |
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Source name |
adult fly ovaries
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Organism |
Drosophila melanogaster |
Characteristics |
age: 3-5 old antibody/beads: BrdU Antibody (IIB5) Agarose (santa cruz, sc-32323 AC) tissue: Ovary
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Treatment protocol |
Flies were fed with yeast paste. Germline specific knockdowns were done as described (Czech et al., 2013 Mol Cell).
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Growth protocol |
All fly stocks were maintained at 25°C on standard diet.
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Extracted molecule |
total RNA |
Extraction protocol |
Adult ovaries were dissected in cold PBS. Nuclei preparation and in vitro transcription run-on were done as described (Rozhkov et al., Genes and Dev., 2013) Libraries were prepared for sequencing using iCLIP protocols (Huppertz et al., 2014, Methods) GRO-Seq
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Library strategy |
OTHER |
Library source |
transcriptomic |
Library selection |
other |
Instrument model |
Illumina MiSeq |
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Description |
BrU labeled transcription run-on RNAs
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Data processing |
The GRO-seq data were mapped first to the transposon database using the Bowtie2 software package (version 2.0.0-beta17) (57). Due to the repetitive nature of transposon sequences, reads were allowed to map to up to 10 different canonical transposons, with read counts distributed evenly among all potential matches. For all samples, the percentage of reads that mapped exactly one time to the canonical transposon database was always more than the percentage of reads that aligned to multiple transposon sequences. To obtain an accurate estimate of the ‘‘library size’’ for each sample, we used all reads that failed to align to the transposon database and mapped just those sequences to the genome using the same alignment criteria (two mismatches per read, 10 total alignments). We then added together the total number of sequenced reads that were mappable to either the transposon or genome database and used this number as a normalization factor for all subsequent analyses, reporting all feature abundances as reads per million (RPM) mapped. To obtain accurate estimates of genomic features that might overlap partial transposon sequences, we remapped all reads to the genome using more stringent criteria (one mismatch per read, 10 total alignments) but still retaining the normalization factor obtained above as the global normalization factor. Feature abundances were obtained by annotating each alignment with a genomic feature using intersectBed from BedTools (version-2.10.1), dividing each alignment by the total number of matches as described above, summing the alignments with the BEDTools ‘‘groupBy,’’ and maintaining the strandedness of all reads. For differential expression analysis, we integrated the gene count table and the transposon count table together and fed to the DESeq package with parameters advisable for data sets with few replicates (2 or 3) (fit, “local’’; method, “pooled’’; and sharing Mode, ‘‘fit-only’’), 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.
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Submission date |
Jul 27, 2015 |
Last update date |
May 15, 2019 |
Contact name |
Yang Yu |
E-mail(s) |
yyu@cshl.edu
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Organization name |
Cold Spring Harbor Laboratory
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Lab |
Hannon Lab
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Street address |
One Bungtown Road
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City |
Cold Spring Harbor |
State/province |
NY |
ZIP/Postal code |
11724 |
Country |
USA |
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Platform ID |
GPL16479 |
Series (2) |
GSE71369 |
Panoramix enforces piRNA-dependent co-transcriptional silencing (GRO-Seq) |
GSE71374 |
Panoramix enforces piRNA-dependent co-transcriptional silencing |
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Relations |
BioSample |
SAMN03939063 |
SRA |
SRX1120708 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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