Supporting Files for: Genome-wide hydroxymethylation profiles in liver of female Nile tilapia with distinct growth performance

This dataset is related to the scientific publication: \"Genome-wide hydroxymethylation profiles in liver of female Nile tilapia with distinct growth performance\". Abstract of related publication: The mechanisms underlying the fast genome evolution that occurs during animal domestication are poorly understood. Here, we present a genome-wide epigenetic dataset that quantifies DNA hydroxymethylation at single nucleotide resolution among full-sib Nile tilapia (Oreochromis niloticus) with distinct growth performance. In total, we obtained 355 million, 75 bp reads from 5 large- and 5 small-sized fish on an Illumina NextSeq500 platform. We identified several growth-related genes to be differentially hydroxymethylated, especially within gene bodies and promoters. Previously, we proposed that DNA hydroxymethylation greatly affects the earliest responses to adaptation and potentially drives genome evolution through its targeted enrichment and elevated nucleotide transversion rates. This dataset can be analysed in various contexts (e.g., epigenetics, evolution and growth) and compared to other epigenomic datasets in the future, namely DNA methylation and histone modifications. With forthcoming advancements in genome research, this hydroxymethylation dataset will also contribute to better understand the epigenetic regulation of key genomic features, such as cis-regulatory and transposable elements. Supplementary files 1a, 1b and 1c: show the DhmCs in gene bodies (1a), intergenic regions (1b) and uncharacterized genes (1c). Statistical analysis revealed 2,677 differentially hydroxymethylated cytosines (DhmCs; q<0.05). Supplementary File 2: list of genes involved in growth and metabolic functions which had higher DNA hydroxymethylation levels in large- than in small-sized individuals. Supplementary Files 3 and 4: description and source code of software trim_galore v0.4.4 and bowtie v0.12.8 in CPP format (combined in one pdf file) Supplementary Files 5 and 6: have been submitted to https://github.com/IoannisKonstantinidis/RRHP_Code. Supplementary File 7: this compressed file contains all the necessary files for the visualization of the DNA hydroxymethylation dataset in IGV. The README file contains instructions to visualize the data.