Acknowledgements
We are indebted to Peter H. Becker for setting up the long-term
individual-based common tern study at the Banter See and to Götz
Wagenknecht and the many scientists, students and field assistants who
collected the data across the years. We express our gratitude to Johanna
Klughammer, Amelie Nemc and Christoph Bock for their advice on
sequencing strategy and for performing the RRBS sequencing. We also
thank Michaela Schwarz for help with DNA extraction, Kristian Ullrich
for his support in solving bioinformatics hurdles, and Melanie J.
Heckwolf and our epigenetic journal club for inspiring discussions on
DNA methylation. The study was performed under licenses of the city of
Wilhelmshaven and the Lower Saxony State Office for Consumer Protection
and Food Safety, Germany. This study was supported by the Max Planck
Society through a MPRG grant (MFFALIMN0001 to ML), a sequencing grant
(PSLIMN6000 to ML and SB), and the ”Norddeutscher Wissenschaftspreis
2018” (BSM, SB and ML).
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Data
accessibility
The common tern reference genome we developed (bSteHir1) is accessible
in NCBI (https://www.ncbi.nlm.nih.gov/bioproject/560234), as well
in Genome Ark (https://vgp.github.io/genomeark/Sterna_hirundo/).
All RRBS data will be deposited into the public database at ENA
https://www.ebi.ac.uk/ena. The final dataset and our R code will
be uploaded to Dryad upon acceptance of the manuscript.
Author
Contributions
SB collected the blood samples and life history data on the terns, ML
and SB designed the study and ML organized sequencing of the samples.
BSM analyzed the methylation data and performed the statistical analyses
with the help of MM. The reference genome was generated as part of the
Vertebrate Genome Project, coordinated by EDJ. OF coordinated the genome
assembly; BH and JM were responsible for sample processing and generated
the genome sequence data; CC, GF and MU-S for the genome assembly; WC,
JW and KH curated the final reference genome. BSM and SB wrote the
manuscript with input from ML, MM and EDJ. All authors commented on
drafts of the manuscript.
Tables and Figures
Table 1. Result of a Generalised Linear Mixed Model with
binomial error distribution testing whether variation in autosomal
methylation level is explained by sex (males as a reference category)
and the between- (average age) and within-individual (delta age)
components of age. Provided are parameter estimates and associated 95%
credible intervals (95% CI). Significant effects (p-value <
0.05 and 95% CI which do not overlap with zero) are presented in bold.