rsbrennan / tonsa_reciprocal

#Acartia tonsa reciprocal transplant

This repository hold scripts for the analysis of a reciprocal transplant of Acartia tonsa following a ~20 generation selection experiment.

These RNAseq data were sequenced on 2 lanes of a Novaseq by Novogene. Data were received by us on 2018-07-24.

Data availability

Raw sequence data is available at NCBI BioProject PRJNA555881

Gene expression data are included in this repository in DGE_data/, both normalized (by librarysize) and not normalized.

All other summaries etc. are included as supplemental files with the manuscript.

Please get in touch about any data issues.

Scripts

Below are scripts to run the full analysis for the manuscript. A short description accompanies each.

Data processing

• Check data quality: 01_fastqc.sh
• Trim fastq files: 02_trim_AAAA.sh; 02_trim_HHHH.sh;02_trim_HHAA.sh;02_trim_AAHH.sh
• Re-run fastqc: 03_fastqc_posttrim.sh

Aligning, read counts, variant calling

• create index for salmon: 04_salmon_index.sh
• Quantify each sample: 05_salmon.sh
• Generate supertranscript reference to align: 06_supertranscript.sh
• Align to the supertranscript: 07_align.sh
• call variants using varscan: 08_varscan_all.sh
  • note that this is very liberal in the calls. Need to filter.
• Filter variants from varscan: 09_filter_variants.R

Analysis

• calulate pi and look at the loss:
  • 10a_popoolation.sh, 10b_popoolation_pi.R
• run the DAPC: 11_dapc.R
• Run the CMH, output allele freq changes: 12_snp_analysis.R
• Generate the correlation scatter plot for DGE and AF for the supplemental: 13_scatter_plot.R
• GO analysis
  • formatted output for DGE is from 13_scatter_plot.R: "~/reciprocal_t/analysis/GO_enrich/dge_f1.txt"
  • 14b_go_assign_snps.py, 14b_go_assign_dge.py produces dge_F1_GOterms.out snp_GOterms.out, for each generation.
  • 14c_GO_format.shthere are some weird formatting issues (some quotes?) that were just easier to fix with bash
  • 14d_GO_Enrich.R and 14d_GO_Enrich_SNP.R run the actual GO enrichment for expression and snps, respectively
  • 14e_go_enrich_deltapi.md run go enrichment for the change in pi

Figures:

• Fig. 2: combination of Fig_pca.R and 14d_GO_Enrich.R
• Fig. 3: plasticity_analysis.R
• Fig. 4: 11_dapc.R
• Fig. 5: 10b_popoolation_pi.R
• Fig. 6: 15_Phenotype_data_analysis.R

Supplemental:

• Fig. S1: Fig_S1.R
• Fig. S2: indiv_gene_fig.md
• Fig. S3: indiv_gene_fig.md
• Fig. S4: 13_scatter_plot.R
• Fig. S5: snp_validation.md
• Fig. S6: 13_scatter_plot.R
• Fig. S7: 09_filter_variants.R
• Fig. S8: venn.R
• Fig. S9: 14d_GO_Enrich.R
• Fig. S10: 14d_GO_Enrich.R