DOI: 10.5061/dryad.qjq2bvqf0
title: High social status males experience accelerated epigenetic aging in wild baboons

description: Aging, for virtually all life, is inescapable. However, within
 populations, biological aging rates vary. Understanding sources of
 variation in this process is central to understanding the biodemography of
 natural populations. We constructed a DNA methylation-based age predictor
 for an intensively studied wild baboon population in Kenya. Consistent
 with findings in humans, the resulting “epigenetic clock” closely tracks
 chronological age, but individuals are predicted to be somewhat older or
 younger than their known ages. Surprisingly, these deviations are not
 explained by the strongest predictors of lifespan in this population,
 early adversity and social integration. Instead, they are best predicted
 by male dominance rank: high-ranking males are predicted to be older than
 their true ages, and epigenetic age tracks changes in rank over time. Our
 results argue that achieving high rank for male baboons—the best predictor
 of reproductive success—imposes costs consistent with a “live fast, die
 young” life history strategy.
description: DNA methylation data were generated from blood-extracted DNA
 collected from known individuals in the Amboseli study population.  RRBS
 libraries were constructed via Msp1 digestion of~200 ng baboon DNA plus
 0.2 ng unmethylated lambda phage DNA per sample as input . Samples were
 sequenced to a mean depth of 17.8 million reads on either the Illumina
 HiSeq 2000 or HiSeq 4000 platform. Sequence reads were trimmed with Trim
 Galore to remove adapters and low quality sequence (Phred score &lt;
 20). Trimmed reads were mapped with BSMAP to the baboon genome (Panu2.0)
 allowing a 10% mismatch rate to account for the degenerate composition of
 bisulfite-converted DNA. We used the mapped reads to count the number of
 methylated and total reads per CpG site, per sample. CpG sites were
 filtered to retain sites with a mean methylation level between 0.1 and 0.9
 (i.e., to exclude constitutively hyper- or hypo-methylated sites) and mean
 coverage ≥5x. We also excluded any CpG sites with missing data for ≥ 5% of
 individuals in the sample. After filtering, we retained N = 458,504 CpG
 sites for downstream analysis. Included here are the effective total CT
 counts and methylated counts for all 277 samples (from 245 unique
 individuals) across each of these 458,504 CpG sites. 
description: total_read_counts Number of reads mapped to
 a given location in the genome for a given sample. Sites included in this
 dataset represent the set of filtered sites we analyzed to produce our
 main results. Note that these values are the "effective CT
 count" values output from BSMAP, which attempts to correct for
 potential SNPs at measured CpG sites. In a small number of cases
 (&lt;.1%), this measure results in an "effective CT count"
 value that is less than the methylated counts. Depending on the downstream
 handling of methylation values, and desired used of these data, these
 cases can be excluded, ignored, or one can simply set the "effective
 CT count"=methylated count, for those small subsets of
 sites.  methylated_read_counts
 Number of methylated reads mapped to a given location in the
 genome for a given sample. Sites included in this dataset represent the
 set of filtered sites we analyzed to produce our main results. The row and
 column dimensions of the methylated_read_count table matches the
 total_read_count table, such that corresponding values for the same CpG
 site and sample can be found in the same table cell.
 counts_tables_columns A file noting which
 sample appears in which column of the methylated and total read counts
 tables. The individual identifiers in this file are consistent with the
 identifiers in Table S1. Note that multiple samples from the same
 individuals can be identified via the Anonymous ID # (i.e. AMB_140 and
 AMB_140B came from the same individual sampled at different
 dates).