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| Status |
Public on Sep 13, 2021 |
| Title |
STL_293T_KCl_1 |
| Sample type |
SRA |
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| Source name |
Human embryonic kidney 293T cells
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| Organism |
Homo sapiens |
| Characteristics |
cell line: WT 293T
s4u feed status: Yes
rna population: short, capped RNA
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| Treatment protocol |
S2 cells were treated with 42 µM 20-hydroxyecdysone or DMSO for 30 minutes, 500 nM flavopiridol or DMSO for 40 minutes, 10 µM triptolide or DMSO for 10 minutes, and/or 1mM s4U for 1.5, 3, 5, 7.5, 10, or 120 minutes. 293T cells were treated with 80 mM KCl for 1 hour and/or 1mM s4U for 5 minutes. In all cases the s4U labeling was the last 5 minutes of drug/stress treatment.
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| Growth protocol |
293T were grown in Dulbecco’s Modified Essential Media supplemented with 10% fetal bovine serum (Gibco) and Pen/Strep (50 U/ml). S2 cells were grown in Dulbecco’s Modified Essential Media supplemented with 10% fetal bovine serum (Gibco) and Pen/Strep (50 U/ml). 293T cell cultures were maintained at 37℃. S2 cell cultures were maintained at 27℃.
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| Extracted molecule |
total RNA |
| Extraction protocol |
RNA was harvested with Trizol reagent, followed by chloroform extraction and isopropanol precipitation. For transient-transciptome-TimeLapse-seq (TT-TL-seq) genomic DNA was depleted using Turbo DNAse, followed by cleanup with RNAclean beads. RNA for transient-transciptome-TimeLapse-seq RNA was enriched with MTS-biotin and treated with oxidative-nucleophilic-aromatic-substitution chemistry as described in Schofield et al. Nature Methods 2018. For Start-TimeLapse-seq, total RNA was treated with oxidative-nucleophilic-aromatic-substitution chemistry as described in Schofield et al. Nature Methods 2018 using mCPBA as the oxidant and short capped RNA was enriched as described in Nechaev et al. Science 2010.
TT-TL-seq libraries were generated following standard protocols using the SMARTer Stranded Total RNA-Seq Kit-Pico Input Mammalian, V2 (Takara Bio USA, cat. 634413). STL-seq libraries were generated with custom oligos following methods described in Nechaev et al. Science 2010.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
Reads filtered for number of T-to-C mutations (0-5+) and strandedness (min/pos)
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| Data processing |
Reads were filtered for unique sequences using FastUniq (this step excluded for STL-seq)
Reads were trimmed using cutadapt (--minimum-length=20)
For TT-TL-seq, reads were aligned to the GRCh38 genome using HISAT2 aligned with default parameters and --mp 4,2 . For STL-seq reads were aligned with Bismark and Bowtie2 with default parameters and --local.
Reads were processed using Picard tools, including FixMateInformation, SortSam and BuildBamIndex
Reads were filtered for those that aligned uniquely (flag: 83/163, 99/147), with MAPQ ≥ 2, and without insertions.
HTSeq-count was used to identify mapped reads in UCSC transcripts (union mode)
T-to-C mutations were identified using Rsamtools and a custom R script (available on Bitbucket). Only mutations at positions with a base quality score of greater than 40 that were at least three nt from the end of the read were counted. Reads were excluded where there were greater than five T-to-C mutations and these mutations did not account for at least one third of the observed mutations (NM tag).
SNP sites were filtered from our data in two ways: 1, bcftools was used to identify T-to-C SNP sites in control samples, and these sites were excluded from analysis; 2, sites exhibiting high T-to-C mutation rates in non-s4U treated controls were excluded from analysis.
To examine the distribution of reads with each minimum number of T-to-C mutations, bam files were filtered using Picard tools.
STAR aligner was used to make genome-coverage tracks (inputAlignmentsFromBam mode, outWigType bedGraph), and tracks were normalized using DESeq2 (estimateSizeFactors).
Tracks were converted to binary format using IGVtools (toTDF).
Genome_build: GRCh38 or dm6
Supplementary_files_format_and_content: bedgraph
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| Submission date |
Feb 04, 2021 |
| Last update date |
Sep 13, 2021 |
| Contact name |
Matthew Simon |
| E-mail(s) |
matthew.simon@yale.edu
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| Organization name |
Yale University
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| Department |
MBB
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| Lab |
Simon Lab
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| Street address |
West Campus, 100 West Campus Drive, Ste MIC312A
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| City |
Orange |
| State/province |
CT |
| ZIP/Postal code |
06477 |
| Country |
USA |
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| Platform ID |
GPL24676 |
| Series (1) |
| GSE166202 |
STL-seq reveals distinct pause release and termination kinetics for promoter-proximal paused RNA polymerase II transcripts |
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| Relations |
| BioSample |
SAMN17799077 |
| SRA |
SRX10030807 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM5065799_STL_293T_KCl_1.TC.0.min.bedGraph.gz |
7.2 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.0.pos.bedGraph.gz |
7.2 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.1.min.bedGraph.gz |
2.6 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.1.pos.bedGraph.gz |
2.6 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.2.min.bedGraph.gz |
1.1 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.2.pos.bedGraph.gz |
1.1 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.3.min.bedGraph.gz |
688.2 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.3.pos.bedGraph.gz |
680.2 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.4.min.bedGraph.gz |
520.0 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.4.pos.bedGraph.gz |
513.9 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.5.min.bedGraph.gz |
399.5 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM5065799_STL_293T_KCl_1.TC.5.pos.bedGraph.gz |
392.0 Kb |
(ftp)(http) |
BEDGRAPH |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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