Simulated infection induced changes in DNA methylation differ between introduced and native house sparrow (Passer domesticus)

As DNA methylation can change within individuals over time and regulate gene expression, it is important in many aspects of avian biology. It likely plays a critical role in the response of individuals to various stressors, such as infection, environmental change, and the myriad of novel conditions associated with introductions. Here, we use epiRADseq to investigate changes in DNA methylation within-individual birds over eight hours in response to simulated infection. We contrast house sparrows from introduced locations with individuals from native locations, comparing the number of genomic locations that change, their magnitude of change, and the variance among individuals of the change. We detected that introduced individuals change their DNA methylation at more genomic locations, with greater magnitude, and higher variance, compared to native individuals. Together, these findings support a critical role of DNA methylation in an individual’s response to infection, which introduces individuals likely to adopt an “invader phenotype,” differentiating their response from native individuals, and that the overall pattern of change in DNA methylation is congruent with epigenetic buffering.

Methods
We used epiRADseq to screen variation in DNA methylation among house sparrows on the Ion Torrent PGM platform. We followed a genotype-by-sequencing (GBS) protocol developed for the Ion Torrent platform, substituting the DNA methylation-sensitive restriction enzyme HpaII for MspI to construct the epiRADseq library. After restriction digestion, we ligated Ion Torrent IonXpress barcoded adaptors and y-adapters. We ran emulsion polymerase chain reactions following the manufacturers protocols of the Ion PGM-Hi-Q-View OT2-200 kit on the Ion Express OneTouch2 platform. We sequenced resultant fragments following manufacturers protocols of the Ion PGM-Hi-Q-View Sequencing 200 Kit using an Ion 316v2 BC Chips. We demultiplexed runs and conducted quality control with Torrent Suite version 4.4.3. We retained bases above the AQ20 confidence threshold. We trimmed sequences to 100 bp targeting the higher quality sequence at the 5’ end. We performed a de novo assembly and constructed a pseudo-reference using Geneious Prime v. 2022.1.1. We mapped individual sequences with BWA Galaxy Version 0.7.17.4. We used featureCounts Galaxy Version 1.6.4+galaxy1 to determine read counts of fragments within 100 bp bins spanning the pseudo-reference. We present all count files, all significant count files post edgeR analysis, and summary information for each individual.