https://doi.org/10.5061/dryad.qjq2bvqs2

Description of the data and file structure

House sparrows were collected from four locations in their native range: Israel (n = 6), Norway (n = 6), Spain (n = 6), and Vietnam (n = 6), and three locations in their introduced range: Australia (n = 3), Canada (n = 6), Senegal (n = 6; Table 1). Upon capture, we took a 50 µl blood sample from the brachial vein of each bird. Immediately after this, we injected each bird with 100 µl of 1 mg/ml-1 lipopolysaccharide in sterile saline subcutaneously over the breast muscle. Post injection, we housed birds individually in wire songbird cages with food and water ad libitum. Eight hours post-injection, we took an additional 10 µl of blood from the brachial vein. We extracted DNA samples ending with paired 0- and 8-hour samples for each individual.

We used epiRADseq to screen variation in DNA methylation among house sparrows on the Ion Torrent PGM platform. We followed a genotype-by-sequencing 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 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. W e 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 used edgeR, Galaxy Version 3.24.1+galaxy1, to detect differently methylated regions, between the 0- and 8-hour samples, with a False Discovery Rate of 0.05. We first compared all samples between 0- and 8-hour; we then repeated the comparison separately for native and introduced individuals. For every house sparrow, we calculated the change in DNA methylation between the 0- and 8-hour sample for all bins with significant differences as identified by the EdgeR analyses. We standardized each count for each bin by sequencing depth as (observed count for bin x / total read count) x 1,000.

Files and variables

File: HOSP_0vs8hr_READ_COUNTS.xlsx

Description:  contains summary data on read count depth for each individual in the study. Individuals are given a unique identifier that has collection location, 00 or 08 hour, and designator.

Variables

• Read count number for each individual

File: HOSP_DNAme_0vs8hr_ALL_DATA.xlsx

Description: contains count data to 100bp bins for each individual in the study. Individuals are given a unique identifier that has collection location, 00 or 08 hour, and designator. All mapped loci are presented.

Variables

• Feature count for each of the 100bp bins assigned to the pseudo reference for each individual

File: HOSP_0vs8hr_Significant_Loci_Only.xlsx

Description: contains count data to 100bp bins for each individual in the study. Individuals are given a unique identifier that has collection location, 00 or 08 hour, and designator. Only loci identified as containing significant differences are presented.

Variables

• Feature count for only the significant bin of the 100bp bins assigned to the pseudo reference for each individual

File: Additional_data_for_GLMM_and_ANOVA_analysis.csv

Table 1: Correlation of Fixed Effects in a Generalized Linear Mixed Model (GLMM)

This table shows the pairwise correlation coefficients between fixed effects included in a GLMM analysis. Understanding these correlations helps assess potential collinearity between predictor variables, which can affect model interpretation and stability.

Table 2: Tukey HSD Post-Hoc Test for Differences in DNA Methylation Among Countries

This table shows the results of Tukey’s Honestly Significant Difference (HSD) test, a post-hoc pairwise comparison method used after an ANOVA to determine which group means are significantly different from each other.

Variables:

Difference: The estimated mean difference in DNA methylation levels between the two countries.

Lower/Upper: The bounds of the 95% confidence interval for the mean difference.

Adjusted p-value: p-values corrected for multiple comparisons (Tukey adjustment).

File: Description_of_code_used_in_the_RStudio_analysis.txt

A GLMM (Gamma, log link) was used to model absolute DNA methylation change as a function of sex and native/invasive status with random intercepts for country; ANOVA followed by Tukey HSD tested for mean differences in methylation change across countries.

Code/software

• File above, Description of code used in the Studio analysis.tx, contains code used for GLMM model, ANOVA, and Tukey multiple comparisons of means analyses.

• All files viewable in Microsoft Excel