Environmental and genealogical effects on DNA methylation in a widespread apomictic dandelion lineage

The following repository contains raw sequenced reads, R scripts, reports and processed DNA methylation files presented in the article "Environmental and genealogical effects on DNA methylation in a widespread apomictic dandelion lineage". 2023. Journal of Evolutionary Biology.

The demultiplexed sequencing raw data was deposited at ENA: PRJEB56325. To reproduce the results presented in this article, you can visit epiTree and epiGBS pipeline.

Genetic marker

• SSR_Data.csv: genetic data set used to compare epigenetic variability.

epiGBS2 pipeline files:

• run0202_epiGBS-superpool_S34_L008_R{1,2}_001.nophix.fastq.gz: raw sequenced reads for 80 samples multiplexed, half of them gDNA were fragmented with a combination of Csp6I-NsiI and the other half with AseI-NsiI restriction enzymes.
• {AseI-NsiI,Csp6I-NsiI}_barcode.tsv: A barcode file used for demultiplexing and that contains the following information: Flowcell, Lane, Barcode_R1, Barcode_R2, Sample, ENZ_R1, ENZ_R2, Wobble_R1, Wobble_R2.

epiGBS2 pipeline output files:

• {AseI-NsiI,Csp6I-NsiI}_config.yaml: configuration files used to run epiGBS pipeline.
• {AseI-NsiI,Csp6I-NsiI}_consensus_cluster.renamed.fa: de novo epiGBS loci representing the consensus sequences obtained during the creation of the de novo reference sequence.
• {AseI-NsiI,Csp6I-NsiI}_report.html: a report file that summarize all stats from the epiGBS analysis.
• {AseI-NsiI,Csp6I-NsiI}_methylation.bed: main output file containing the methylation calling as a genome-wide methylation report for all sequenced cytosines.

Processed data:

• {AseI-NsiI,Csp6I-NsiI}_methylation.filtered: The filtered DNA methylation data. This data was obtained after filtering the raw DNA methylation data. Cytosines which had a 10X coverage or higher and which were present in 80% of all samples were kept for further analysis.
• {AseI-NsiI,Csp6I-NsiI}_mergedAnnot.csv: Files with gene, repeats and transposable elements annotation and non-classified genomic regions for each epiGBS fragment.

R scripts:

• commonFunctions.R: To improve the readability of scripts, this file contains all hiden function used in the following scripts.
• 00_mergeAnnotation.R: This script is used to merge gene, repeats and transposable elements annotation and detect non-classified genomic regions.
• 01_filterMethylation.R: This script contain the code to filter methylation.bed files and to keep cytosines with 10X as minimum, that are presented in 80% of all samples and discarding the top 1% with the highest sequence coverage.
• 02_characterizeOverallMethylation.R: This script contain the code to characterized overall methylation
• 03_distances.R: This script contain the code to calculate and visualize the pairwise epigenetic distances, as the average methylation difference across all cytosines between two samples.
• 04_differentialCytosineMethylationWithDSS.R: This script contain the code to calculate differences in DNA methylation between accessions or light treatments at each individual cytosine using the ‘DSS’ package. Resulting p-values were adjusted for multiple testing using False Discovery Rate control using a threshold of 0.05.
• 05_manhattanPlot.R: This script contain the code to generate the manhattan plots of epiGBS loci using ‘qqman’
• 06_dendrogram.R: This script contain the code to generate UPGMA dendrograms based on methylation levels using euclidean distance or on eight microsatellite loci using Nei distance.
• 07_DMC_description.R: This script contain the code to characterized DMC over different genomic regions.
• 08_mantelTest.R: This script contain the code to correlate CG methylation variation with SSR variation.