|
| Status |
Public on Apr 29, 2022 |
| Title |
T-dVMV-RIG-1 [T-dVMV-RIG-1_ACAGTG] |
| Sample type |
SRA |
| |
|
| Source name |
INPUT RNA extracted on RIG-I protein
|
| Organisms |
Homo sapiens; Measles morbillivirus |
| Characteristics |
cell line background: HEK293
genotype/variation: RIG-I protein tagged 1-STrEP tag
infection: measles virus (deltaV)
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Before RNA-seq analysis of total and RLR-bound RNA from virus- and mock-infected cells, depletion of ribosomal RNA was done using the riboZero reagents included in the TruSeq stranded total RNA library prep kit (#20020596, Illumina). NGS libraries were generated following the manufacturer’s protocol. The indexed samples were multiplexed per 4 or 6 and sequenced on a HiSeq2500 sequencer (Illumina) to produce single-ends 65 bases reads, bearing strand specificity.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2500 |
| |
|
| Description |
T-dVMV-RIG-1_ACAGTG_L007
|
| Data processing |
Reads were cleaned of adapter sequences and low-quality sequences using cutadapt version 1.11.Only sequences at least 25 nt in length were considered for further analysis
Bowtie version 1.2.2 (parameters --chunkmbs 400 -m 1) was used for alignment on the reference genome.
Genes were counted using featureCounts version 1.4.6-p3 from the Subreads package (parameters: -t gene -g ID -s 1).
To compute coverage on viruses, Bowtie version 1.2.2 14 , with default parameters, was used for alignment on the reference genomes. Only first base of each read are used as input of genomeCoverageBed from Bedtools 15 . Minus and plus strand coverage are separated by a simple awk command.
For statistical analysis of NGS data, count data were analyzed using R version 3.5.1 and the Bioconductor package DESeq2 version 1.20.0 16 . The normalization and dispersion estimation were performed with DESeq2 using the default parameters and statistical tests for differential expression were performed applying the independent filtering algorithm. For each virus, a generalized linear model including the replicate, beads and protein factors as well as the beads x protein interaction was set in order to test for the differential expression between the biological conditions. For each pairwise comparison, raw p-values were adjusted for multiple testing according to the Benjamini and Hochberg (BH) procedure 17 and genes with an adjusted p-value lower than 0.05 were considered differentially expressed.
Supplementary_files_format_and_content: DESeq2 output
|
| |
|
| Submission date |
Jul 25, 2019 |
| Last update date |
Apr 29, 2022 |
| Contact name |
Rachel Legendre |
| E-mail(s) |
rachel.legendre@pasteur.fr
|
| Organization name |
Institut Pasteur
|
| Department |
Research and Resource Center for Scientific Informatics
|
| Lab |
Hub of Bioinformatics and Biostatistics
|
| Street address |
28, rue du docteur Roux
|
| City |
Paris |
| ZIP/Postal code |
75724 |
| Country |
France |
| |
|
| Platform ID |
GPL26959 |
| Series (2) |
| GSE134859 |
Viral Mimicry by Endogenous Y-RNAs Contributes to Antiviral Immunity [MVseq2] |
| GSE134861 |
Viral Mimicry by Endogenous Y-RNAs Contributes to Antiviral Immunity |
|
| Relations |
| BioSample |
SAMN12361477 |
| SRA |
SRX6589577 |
