SFD Transcriptomics 🐍

This Github repository contains scripts developed for the transcriptomic study of host response to snake fungal disease (ophidiomycosis) in different temperature conditions

Publication:

Mathur, S., Haynes, E., Allender, M. C., & Gibbs, H. L. (2024). Genetic mechanisms and biological processes underlying host response to ophidiomycosis (snake fungal disease) inferred from tissue‐specific transcriptome analyses. Molecular Ecology, 33(2), e17210. https://doi.org/10.1111/mec.17210

Folders

The directory structure of the repository is:

• Bash Scripts: Contains scripts for data analysis on OSC clusters.

Popgen : Scripts for population genomics of C.viridis genomes download from NCBI SRA database RNASeq : Scripts for RNASeq data processing and mapping

• RScripts: Contains scripts for statistical analysis and output data visualization in R.
• DataFies: Contains miscellenious datafiles used/generated for the study Bash Scripts

• RNASeq

1. adapter_removal.sh

To remove adapter and low base quality sequences from raw RNASeq reads using triommomatic.

2. fastqc.sh

To quality check filtered RNASeq reads

3. alignment.sh

To build reference genome database and map filtered RNAseq reads using hisat2

4. stringtie.sh

To assemble transcripts for each sample using C. viridis reference annotation file to guide assembly and merged sample transcripts

5. featureCounts.sh

To generate a transcript count matrix

• Popgen

1. adapter_removal.sh

To remove adapter and low base quality sequences from raw whole genome sequence reads using triommomatic.

2. alignment.sh

To align filtered genomic reads to reference genome. Script also sort, mark duplications, fix mate pair information, and get mapping stats.

3. base_recalibration.sh

To identify known variants from our dataset and recalibrate base quality scores for genomic reads for each sample

• RScripts

1. Differential gene expression (DGE) using DESeq2

DGE_liver.R : For liver samples DGE_kidney.R : For kidney samples DGE_skin.R : For skin samples

2. DGE_Compare.R

To compare DGE results for each tissue and extract differentially expressed genes (DEGs) due to fixed effects only

3. DGE_Contrast_Compare.R

To compare DGE results for each tissue and extract differentially expressed genes (DEGs) due to interaction between infection and temperature

4. Weighted gene co-expression network analysis (WGCNA)

WGCNA_liver.R : For liver samples WGCNA_kidney.R : For kidney samples WGCNA_skin.R : For skin samples

5. Compare_WGCNA.R

To compare WGCNA results for each tissue and extract genes within each module significantly associated with infection or the interaction between infection and temperature.

6. gene_list.R

To get the final gene lists from DGE and WGCNA analysis.