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Status |
Public on Dec 20, 2017 |
Title |
101(M) |
Sample type |
SRA |
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Source name |
101 (M-strain)
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Organism |
Drosophila virilis |
Characteristics |
tissue: Ovaries strain: 101 (M-strain) rna fraction: Gel extraction of small RNAs (21-29 nts)
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Extracted molecule |
total RNA |
Extraction protocol |
Total RNA was extracted from ovaries of 7-10 days old females using Extract RNA reagent (Evrogen, Russia). To prepare small RNA fraction for cloning, total RNA from ovaries (~ 25 µg) was separated, using 15% polyacrylamide gel electrophoresis containing 8 M Urea. After incubation in an ethidium bromide solution (0.5 µg/ml) gel fragments corresponding to the small RNA fraction were excised, using chemically synthesized RNA corresponding to 21 and 29 nts as size markers. Cloning of small RNA libraries was performed by Illumina TruSeq Small RNA prep kit (Illumina, USA) according to the manufacturer’s protocol.
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Library strategy |
ncRNA-Seq |
Library source |
transcriptomic |
Library selection |
size fractionation |
Instrument model |
Illumina NextSeq 500 |
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Description |
small RNAs (21-29 nts)
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Data processing |
As a result of deep-sequencing we obtained 5-14 million reads of small RNAs for each library. Pre-processing procedure included: 3’-adapter cropping, filtration of reads by length filtration (>18 nt) and quality (80% of nt have ≥ 20 Phred quality). Pre-processed reads were further subjected to subtraction of reads matching to all rRNA, tRNA, snRNA and miRNA sequences. The selected reads were mapped to the latest release of D. virilis genome by Bowtie (Langmead et al., 2009) with requiring of perfect match. In order to identify siRNAs and piRNAs, the sequenced reads were mapped to the canonical sequences of TEs obtained from combined libraries of annotated and computationally predicted D. virilis transposons and repeats sequences (Erwin et al., 2015). Length distribution and counting of siRNAs and piRNAs reads, nucleotide biases, ping-pong signatures, coverage of transposon sequence by piRNAs were analyzed with accordance to the well-described technique (Brennecke et al., 2007; Song et al., 2014) using custom scripts written in Python. genome build: droVir2 (Aug, 2005) Supplementary_files_format_and_content: Excel file with CPM
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Submission date |
Dec 19, 2017 |
Last update date |
Dec 20, 2017 |
Contact name |
Sergei Funikov |
E-mail(s) |
sergeyfunikov@gmail.com
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Phone |
+79645866708
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Organization name |
Engelhardt Insitute of Molecular Biology
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Street address |
Vavilov str. 32
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City |
Moscow |
State/province |
Moscow |
ZIP/Postal code |
119991 |
Country |
Russia |
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Platform ID |
GPL20240 |
Series (1) |
GSE108298 |
Stochastic gain of susceptibility suggests a novel mechanism of resistance to hybrid dysgenesis in Drosophila virilis |
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Relations |
BioSample |
SAMN08204650 |
SRA |
SRX3485181 |
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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