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| Status |
Public on Sep 18, 2020 |
| Title |
mouse106_liver_30sec_RiboSeq |
| Sample type |
SRA |
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| Source name |
liver
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| Organism |
Mus musculus |
| Characteristics |
age: 72 weeks old mouse
strain: C57BL6
inhibitors: harringtonine 30 sec cycloheximide
injection route: tail-vein
internal animal id: 106
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| Extracted molecule |
total RNA |
| Extraction protocol |
Frozen tissue was lysed a glass-Teflon Dounce homogenizer: 20 mM Tris-HCl pH 7.5, 100 mM KCl, 5 mM MgCl2, 5 mM CaCl2, 1 mM DTT, 1% Triton-X100, 0.1 mg/ml cycloheximide. The lysate was incubated with 4:1 mixture of ribonucleases T1 and S7 for 30 min at room temperature with gentle agitation. Lysate fractionation was performed by ultracentrifugation for 3 h at 35.000 rpm in an SW41 rotor (Beckman, Optima L-20K) at 4⁰ C in 10-50% sucrose, 20 mM Tris-HCl pH 7.5, 100 mM KCl, 10 mM MgCl2, 1 mM DTT, 0.1 mg/ml cycloheximide. After the centrifugation, gradients were passed through a UV detector (Bio-Rad) and the absorption at 254 nm was recorded. The fraction containing monosomes was collected in a single tube. The volume of the sample was brought to 50 ul by concentrating it using 100 kDa filters (Amicon Ultra, Millipore). Then, the sample was diluted to 500 ul with a buffer containing 10 mM Tris-HCl pH 7.5, 2 mM EDTA, 1% SDS. RNA was extracted by hot acid phenol (Ambion) and precipitated by the glycogen-ethanol method (1/10 volume of 3 M sodium acetate, 1/100 volume of glycogen, 2.5 volumes of pure ethanol, 1-hour incubation at -20 followed by centrifugation). RNA was loaded on a 15% polyacrylamide TBE-urea gel and the band containing ribosomal footprints around 28-30 nucleotides was cut.
DNA adapter (rApp-AGATCGGAAGAGCACACGTCT- ddC) was ligated to the 3' end of RNA footprint. Illumina flanking sequences were added through reverse transcription and consequent Circligation technique.
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| Library strategy |
OTHER |
| Library source |
transcriptomic |
| Library selection |
other |
| Instrument model |
Illumina HiSeq 2500 |
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| Description |
ribosome footprints
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| Data processing |
Library strategy: Ribo-seq
To remove illumina adapter from Ribo-seq libraries run "cutadapt -u 1 -m 23 -a AGATCGGAAGAGCACACGTCT --discard-untrimmed -o output.fastq input.fastq"
mRNA-seq sequences were aligned with TopHat 2.1.0 using following settings: tophat --transcriptome-index --no-discordant --no-mixed --no-novel-juncs
The NCBI mouse genome build GRCm38.p3 and the Mus musculus Annotation Release 105 were used as a reference. When aligning mRNA-seq and ribosome profiling reads for expression and translation efficiency estimation we used the following strategy. Only full chromosomes were left and all non-chromosomal and mitochondrial records removed. Furthermore, only RefSeq and BestRefSeq records were left in the transcriptome annotation, while Gnomon predictions were discarded along with pseudogenes. Read count per gene was accessed by HTseq-count software
To plot time-dependent ribosome occupancy, we employed a different strategy. First, using a gene bank (gbk) file, which comes in a package with the genome assembly and annotation, we extracted RefSeq and BestRefSeq records for every gene including CDS, 5’-UTR and 3’-UTR lengths and sequences. Among them, we identified the longest isoform for every gene, prioritized as CDS > 5’UTR > 3’UTR. 5’-UTRs were trimmed by 100 nucleotides. If either or UTRs were shorter than 100 nucleotides, we filled it with up to 100 based on genomic coordinates. The full list of sequences is collected in the mRNA_100.fna file. To prepare a list of non-redundant genes, we run blast of all vs. all (blastall -p blastn -m 8 -b 500 -v 500 -e 0.001). Gene pairs that are too similar at the level of nucleotide sequence were excluded. In addition to the e-score, we enforced a requirement of the high-homology stretch being at least 50 nt long, and if it was longer, the similarity had to be at least 90% to treat these genes as homologous and redundant. A total of 13,685 genes passed every threshold. This reference set ensured unambiguous alignment of ribosome footprints. Resulting sequences are collected in the mRNA_100unique.fna file.
Custom Perl and R scripts were used to calculate the footprint coverage profiles of individual genes.
Genome_build: GRCm38
Supplementary_files_format_and_content: read counts contain raw read count of individual genes; footprint coverage contains gene coverage profiles
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| Submission date |
Sep 18, 2020 |
| Last update date |
Sep 20, 2020 |
| Contact name |
Maxim Gerashchenko |
| E-mail(s) |
mgerashchenko@bwh.harvard.edu
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| Organization name |
Brigham and Women's Hospital
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| Department |
Medicine
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| Street address |
77 Louis Pasteur Ave, NRB 435
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| City |
Boston |
| State/province |
Massachusetts |
| ZIP/Postal code |
02115 |
| Country |
USA |
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| Platform ID |
GPL17021 |
| Series (1) |
| GSE112223 |
Translation elongation rate varies among organs and decreases with age |
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| Relations |
| BioSample |
SAMN16212674 |
| SRA |
SRX9152002 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM4795532_mouse106_liver_30sec_RiboSeq.coverage.txt.gz |
1.3 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Processed data provided as supplementary file |
| Raw data are available in SRA |
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