Ribosome profiling: ribo-seq timecourse
We provide:
- Translation rates and efficiencies on updated Ensembl annotations,
- Genomic profiles for downstream analysis (see GeneAbacus-Python)
- Tracks for genome browsers.
Citing
This dataset combines data from multiple publications:
- Bazzini, Johnstone et al. Identification of small ORFs in vertebrates using ribosome footprinting and evolutionary conservation. EMBO 2014 (Pubmed ID: 24705786)
- Lee, Bonneau et al. Nanog, Pou5f1 and SoxB1 activate zygotic gene expression during the maternal-to-zygotic transition. Nature 2013 (Pubmed ID: 24056933
- Beaudoin, Novoa et al. Analyses of mRNA structure dynamics identify embryonic gene regulatory programs. NSMB 2018 (Pubmed ID: 30061596)
- Johnstone et al. Upstream ORFs are prevalent translational repressors in vertebrates. EMBO 2016 (Pubmed ID: 26896445)
- Chan et al. Brd4 and P300 Confer Transcriptional Competency during Zygotic Genome Activation. Dev Cell 2019 (Pubmed ID: 31211993)
Publication for each sample (i.e. what sample is cited in what manuscript) is available here and in the table below.
Samples available
| Sample | Column/File name | Translation efficiency denominator (RPKM table) | Publication |
|---|---|---|---|
| Ribo-seq 0hpf (Ribo-) | rpf_0h_chx_rm | Chan et al. Dev Cell 2019 | |
| Ribo-seq 2hpf | rpf_2h | mrna_r0_2h | Lee, Bonneau et al. Nature 2013 |
| Ribo-seq 5hpf | rpf_5h | mrna_r0_5h | Bazzini, Johnstone et al. EMBO 2014 |
| Ribo-seq 12hpf | rpf_12h | mrna_r0_12h | Bazzini, Johnstone et al. EMBO 2014 |
| Ribo-seq 24hpf | rpf_24h | mrna_r0_24h | Bazzini, Johnstone et al. EMBO 2014 |
| Ribo-seq 48hpf | rpf_48h | mrna_r0_48h | Bazzini, Johnstone et al. EMBO 2014 |
| Ribo-seq 2hpf +Pateamine A | rpf_2h_pata | mrna_2h_pata | Beaudoin, Novoa et al. NSMB 2018 |
| Ribo-seq 2hpf +Pateamine A (Control) | rpf_2h_ctrl_pata | mrna_2h_ctrl_pata | Beaudoin, Novoa et al. NSMB 2018 |
| mRNA-seq RiboZero 2hpf | mrna_r0_2h | Lee, Bonneau et al. Nature 2013 | |
| mRNA-seq RiboZero 5hpf | mrna_r0_5h | Johnstone et al. EMBO 2016 | |
| mRNA-seq RiboZero 12hpf | mrna_r0_12h | Johnstone et al. EMBO 2016 | |
| mRNA-seq RiboZero 24hpf | mrna_r0_24h | Johnstone et al. EMBO 2016 | |
| mRNA-seq RiboZero 48hpf | mrna_r0_48h | Johnstone et al. EMBO 2016 | |
| mRNA-seq 2hpf +Pateamine A | mrna_2h_pata | Beaudoin, Novoa et al. NSMB 2018 | |
| mRNA-seq 2hpf +Pateamine A (Control) | mrna_2h_ctrl_pata | Beaudoin, Novoa et al. NSMB 2018 |
- Reads were mapped to GRCz11.
- Genes annotations from Ensembl 104.
RPKM/count tables
- Tables include reads matching up to 5 loci in the zebrafish genome.
- RPKM and counts computed using GeneAbacus.
| File | Description | Type |
|---|---|---|
| rpf_mrna_giraldez_rpkm_5_ensembl104_v9.csv.xz | Main table combining all of our published Ribo-seq data | RPKM (up to 5 matches) |
| rpf_mrna_giraldez_count_5_ensembl104_v9.csv.xz | Main table combining all of our published Ribo-seq data | Count (up to 5 matches) |
| rpf_mrna_giraldez_publications_ensembl104_v9.csv.xz | Citations and SRA IDs |
- How to decompress
*.csv.xzfiles?- All files were compressed using XZ. You can obtain a copy at https://tukaani.org/xz if your system doesn’t provide it already.
- To decompress the files
xz -d file.csv.xz. - The Python Data Analysis Library pandas decompresses XZ files transparently.
Genomic profiles
- Profiles computed using GeneAbacus (in profile binary format).
See GeneAbacus-Python to import these profiles into your analysis. Use zebrafish GRCz11 danrer_genome_all_ensembl_grcz11_chrom_length.tab tabulated file to import.
To visualize Ribo-seq and mRNA-seq data on an mRNA, follow this notebook to create multi-frame coverage plot:
Raw data
Raw data is available for download at SRA. Please refer to rpf_mrna_giraldez_publications_v9.csv.xz to get the SRR references to download.