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Sample GSM4804530

Query DataSets for GSM4804530

Status

Public on Aug 20, 2021

Title

SC_arp5del_R1_rep2

Sample type

SRA

Source name

S. cerevisiae

Organism

Saccharomyces cerevisiae

Characteristics

experiment: PRO-seq
genotype: arp5[delta]

Growth protocol

All cells were grown to mid-log phase at 30°C in yeast peptone dextrose (YPD).

Extracted molecule

total RNA

Extraction protocol

Nuclear run-on reactions and RNA extractions were performed based on the published protocol (Mahat et al., 2016) with minor modifications according to the previous study (Booth et al., 2018; Hou et al., 2019).
Library was generated followed by the published PRO-seq or PRO-cap protocol (Mahat et al., 2016) from RNA fragmentation by base hydrolysis to full-scale PCR amplification with few differences of reagent. DNA libraries of ~100bp to 350bp were selected by agarose gel extraction (Zymo Research, D4007) according to the manufacturer’s protocol.

Library strategy

OTHER

Library source

transcriptomic

Library selection

other

Instrument model

HiSeq X Ten

Description

Detecting active RNA polymerase
SC_arp5d_Norm_plus.bw
SC_arp5d_Norm_minus.bw

Data processing

Sequence alignment and data processing were performed based on the publicly available alignment pipelines on GitHub used in the previous study (Booth et al., 2018; only Read 1 (R1) was used for analysis) with minor modifications.
Raw sequencing reads were processed using FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/) in the following orders: Adaptor sequences (5’-TGGAATTCTCGGGTGCCAAGG-3’) were removed, reads length was trimmed to a maximum length of 36 bp and, for PRO-seq, reads were then reverse-complemented.
The reads mapped to rRNA sequences were depleted using SortMeRNA (Kopylova et al., 2012)
The reads that were not mapped to rRNA sequences were uniquely aligned to a genome using Bowtie allowing for two mismatches (Langmead et al., 2009).
The processed reads of yeast samples that were generated with the spike-in approach were mapped to a combined genome consisting of S. cerevisiae (sacCer3) and S. pombe (SpombeASMv2) and unique reads from each genome were parsed for downstream analysis. The processed reads of mESCs were mapped to the M. musculus mm10 genome.
Genome_build: S. cereivisae (sacCer3), S. pombe (SpombeASMv2) and M. musculus (mm10)
Supplementary_files_format_and_content: The coverage of the aligned reads was generated using genomecov function of BEDtools (Quinlan and Hall, 2010). Only the most 3’ nucleotide of each read was calculated for PRO-seq and only the most 5’ nucleotide of each read was calculated for PRO-cap. For the spike-in control, the recorded coverage in the bedGraph file was normalized to the relative number of uniquely mapped spike-in counts, and these normalized reads were counted in reads per million mapped reads (RPM) considering the sequencing depth of experimental reads. For mESCs data, which was generated without the spike-in control, the reads were presented in RPM. BedGraph files were converted to BigWig files by bedGraphToBigWig (Kent et al., 2010) and the downstream analysis was processed based on the publicly available custom R scripts on GitHub, as previously reported (Booth et al., 2018).

Submission date

Sep 27, 2020

Last update date

Sep 25, 2021

Contact name

Youngseo Cheon

E-mail(s)

cheonyseo@kaist.ac.kr

Organization name

Korea Advanced Institute of Science and Technology

Street address

291 Daehak-ro, Yuseong-gu