Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding of proteins with alpha helical domains
Authors/Creators
- 1. Biozentrum, University of Basel, Basel, Switzerland
- 2. Biozentrum, University of Basel, Basel, Switzerland; Institute of Human Genetics, Polish Academy of Sciences, 60-479 Poznan, Poland
- 3. Cryo-EM Knowledge Hub (CEMK), ETH Zürich, Switzerland
- 4. Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Basel, Switzerland
- 5. Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Basel, Switzerland; Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Switzerland
Description
Supplementary materials for the paper "Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding of proteins with alpha helical domains".
Analysis of public RNA-seq data
The files named "RPL39L_public_rna_seq*" are related to the analysis of public RNA-seq data reflected in Figure 1 and S1 of the manuscript.
To run the jupyter notebook with the analysis, create a local conda environment using a provided .yml file:
conda env create -f RPL39L_public_rna_seq_env.ymlUntar the archive with all the necessary data:
tar -xvzf RPL39L_public_rna_seq.tar.gzIn your juputer lab or hub, or standard notebooks instance, open the file "RPL39L_public_rna_seq.ipynb", select the environment "rpl39l", and run the analysis. The instructions for installation of the jupyter lab can be found here: https://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html
Analysis of Ribo-seq data from WT and RPL39L-KO mESC
Extract the archive "RPL39L_Ribo_seq.tar.gz" with the following command:
tar -xvzf RPL39L_Ribo_seq.tar.gzThe analysis is executed in two steps, represented by independent Snakemake-based workflows. To run the workflows, please install the Snakemake following the instructions from here: https://snakemake.readthedocs.io/en/stable/getting_started/installation.html
Step 1: preparation of the enriched mouse genome annotation
The directory "prepare_annotation" contains the Snakemake workflow for preparation of custom mouse annotation. Navigate there and run the bash script "run_snakefile.sh"
Step 2: analysis of the ribo-seq data
The directory "process_data" contains the Snakemake workflow for running the analysis. Please go the subdirectory "./samples/Rpl39l_Samples/", put the riboseq .fastq files from the associated SRA study there, and run the bash script "rename.sh".
After that, navigate back to the directory "process_data" and run the bash script "run_snakefile.sh".