Raw read files for RNA-seq and Whole Genome Bisulfite Sequencing (WGBS) data can be found in the ENA with accession numbers PRJEB77425 and PRJEB77426 respectively.
All scripts for the RNA-seq analysis are found in the RNA-seq folder.
- Trim: fastp.pl
- Pseudoalignment & quantification with kallisto: kallisto.pl
- Import quantifications and summarise at gene level: import_kallisto_quantifications.R
- Identify differentially expressed genes (DEGs) in met1 mutants: DESeq_analysis_MET1_vs_AABBDD.R
- Plot the number of DEGs in each of the met1 mutants: number_of_DEGs_plot.R (produces Figures 4A-B)
- Plot particularly interesting genes: plot_genes_of_interest.R (produces Figure 4C)
- Gene Ontology enrichment for DEGs in Aabbdd mutant: GO_enrichment_MET1_vs_AABBDD.R, requires file to convert v1.0 gene IDs to v1.1, available here, and file with GO terms, available here (only in preprint, not final version of manuscript)
For analysing the expression of transposable elements:
- Creat genome index with hisat2: hisat2_index.sh
- Map RNA-seq reads to the whole genome with hisat2: hisat2_mapping.pl
- Sort bam files with the mapped reads: samtools_sort.pl
- Index the sorted bam files: samtools_index.pl
- Count reads uniquely mapping to complete TE positions: htseq_count.pl
- Combine counts from all samples into one file: combine_TE_counts.R
- Identify differentially expressed transposons (DETs): DESeq2_TEs_met1_vs_AABBDD.R (produces Figure 4B)
All scripts for the WGBS analysis are found in the WGBS folder.
- Trim: fastp.pl
- Create bisulfite-converted reference: bismark_index.sh, requires IWGSC v1.0 genome, available here
- Map to bisulfite-converted reference: bismark.pl
- Extract methylation data and produce CX_report: bismark_methylation_extraction.pl
- Split CX_report files into separate chromosomes: filter_all_chromosomes.sh
- Split CX_report files by sequence context and convert to bigwig files: CXreport_to_bigwig.R run via CXreport_to_bigwig.sh
- Merge bigwig files for all chromosomes, separate for each sequence context: merge_bigwigs_CG.sh, merge_bigwigs_CHG.sh, and merge_bigwigs_CHH.sh
- Convert gene and transposon gff3 files to gtf files and filter for chromosome of interest: gff_to_gtf_genes_all.sh and gff_to_gtf_TE_all.sh, requires IWGSC v1.1 HC genes gff3 file, available here and IWGSC Transposable Elements gff3 file, available here
- Plot average methylation across genes and TEs: computeMatrix_all_genes.sh, computeMatrix_all_TEs.sh, and plotProfile_all.sh (produces Figures 3B-C and Supplementary Figure 4)
- Produce methylation profile plots: plot_all_chrom.R run via plot_all_chrom.sh (produces Figures 3D-F and Supplementary Figures 6-12)
- Plot absolute difference in methylation between WT and met1 mutants: plot_all_chrom_difference.R run via plot_all_chrom_difference.sh (produces Supplementary Figure 5)
- Plot methylation profile plots for all single and double mutants: plot_all_chrom_singles.R run via plot_all_chrom_singles.sh, and plot_all_chrom_doubles.R run via plot_all_chrom_doubles.sh (produces Supplementary Figure 13)
- Call CG-DMRs: call_DMRs_all_chrom.R run via call_DMRs.sh
- Combine DMRs from all chromosomes, plot number of DMRs, and density of DMRs in chromosome regions: combine_all_DMRs.R (produces Figures 3G-H and Supplementary Figure 14-15)
- Convert DMR files into bed files: DMRs_to_bed.R
- Filter gff file with genes and add 1kb up- and downstream: gff_to_genes1kb.R, requires IWGSC v1.1 HC genes gff3 file, available here
- Find overlap between genes and DMRs: DMRs_intersect_genes.sh
- Plot number of genes overlapping DMRs and identify overlap with DEGs: DMR_gene_overlap.R (produces Figures 4D)
- Filter gff file with TEs: TEgff_to_completeTE.R, requires IWGSC Transposable Elements gff3 file, available here
- Find overlap between TEs and DMRs: DMRs_intersect_TEs.sh
- Plot the number of TEs overlapping DMRs: DMR_TE_overlap.R (produces Figure 4E)
- Find overlap between DETs and DMRs: DMR_DET_overlap.R (produces Figure 4F, Supplementary Figure 16)