Covid-19 Gene Expression Work Group (Private project)

Hackathon team: gene expression analysis for Covid-19 Virtual Biohackathon (vBH)

Link to vBH Github

https://github.com/virtual-biohackathons/covid-19-bh20

Official Gene Expression Work Group Page (Public page)

https://github.com/virtual-biohackathons/covid-19-bh20/wiki/GeneExpression

Main Objective

We want to perform RNAseq-based analyses on published datasets in order to better understand the interaction between human host and virus.

Fig.1 - We want to focus on already known (such as ACE2 and TMPRSS2) but also on new candidate genes that may play a punctual or a general role in the interaction between host and virus. To this end, we will perform extensive RNAseq analyses as described in the workflow section below

Deliverables

Biological: Perform a global RNA-Seq analysis with SARS-CoV-2 infected datasets to search for new candidate genes for testing experimentally

Methodological: Create a packaged reproducible pipeline in Docker to help scientists to easily treat their RNA-Seq data and for us if any new dataset comes out

Tasks

Workflow

0. Check literature to select interesting genes/datasets to study
1. Downloading RNAseqs from SRA/GEO
2. Pipeline to clean reads
3. Map against viral genome (+ viral DBs)
4. Map against human genome (genes and isoforms pipelines)
5. Check shared reads between both genomes
6. Map reads against transposable elements
7. Check the existence of chimeric reads
8. Perform differential expression analysis on genes, transcripts and TEs
9. Functional enrichment analysis
10. SNP/Splicing on risk factor datasets for selected genes

Software Used during this project

Command line tools

• FastQC (https://github.com/s-andrews/FastQC)
• Fastq-screen (https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen/)
• trimmomatic (http://www.usadellab.org/cms/?page=trimmomatic)
• STAR (https://github.com/alexdobin/STAR)
• Bowtie2 (http://bowtie-bio.sourceforge.net/bowtie2/index.shtml)
• TEtools (https://github.com/l-modolo/TEtools)
• TEtranscripts (http://hammelllab.labsites.cshl.edu/software)
• LIONS (www.github.com/ababaian/LIONS)
• samtools / picard (http://samtools.sourceforge.net/; https://broadinstitute.github.io/picard/)
• featureCounts (http://subread.sourceforge.net)
• MultiQC (https://github.com/ewels/MultiQC)
• KissSplice (http://kissplice.prabi.fr/)

R packages

Direct install

ggplot2

install.packages("ggplot2")

BiocManager install

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

DESEq2

BiocManager::install("DESeq2")

EdgeR

BiocManager::install("EdgeR")

Limma-Voom

BiocManager::install("limma")

Devtools install

install.packages("devtools")

SARTools

library(devtools)
install_github("PF2-pasteur-fr/SARTools", build_opts="--no-resave-data")

Code repositories

Data-sources

Virus infection studies

• SARS-MERS: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56192
• COVID: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147507
• Murine coronavirus (M-CoV): https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-4111/

Increased risk factors studies

References