DOI: 10.5061/dryad.w9ghx3fx6
title: Data from: Among-population variation in telomere regulatory proteins and their potential role as hidden drivers of intraspecific variation in life history

description: Biologists aim to explain patterns of growth, reproduction, and ageing
 that characterize life histories, yet we are just beginning to understand
 the proximate mechanisms that generate this diversity. Existing research
 in this area has focused on telomeres but has generally overlooked the
 telomere’s most direct mediator, the shelterin protein complex. Shelterin
 proteins physically interact with the telomere to shape its shortening and
 repair. They also regulate metabolism and immune function, suggesting a
 potential role in life history variation in the wild. However, research on
 shelterin proteins is uncommon outside of biomolecular work. Intraspecific
 analyses can play an important role in resolving these unknowns because
 they reveal subtle variation in life history within and among populations.
 Here, we assessed ecogeographic variation in shelterin protein abundance
 across eight populations of tree swallow (Tachycineta bicolor) with
 previously documented variation in environmental and life history traits.
 Using blood gene expression of four shelterin proteins in 12-day old
 nestlings, we tested the hypothesis that shelterin protein gene expression
 varies latitudinally and in relation to both telomere length and life
 history. Shelterin protein gene expression differed among populations and
 tracked non-linear variation in latitude: nestlings from mid-latitudes
 expressed nearly double the shelterin mRNA on average than those at more
 northern and southern sites. However, telomere length was not
 significantly related to latitude. We next assessed whether telomere
 length and shelterin protein gene expression correlate with 12-day old
 body mass and wing length, two proxies of nestling growth linked to future
 fecundity and survival. We found that body mass and wing length correlated
 more strongly (and significantly) with shelterin protein gene expression
 than with telomere length. These results highlight telomere regulatory
 shelterin proteins as potential mediators of life history variation among
 populations. Together with existing research linking shelterin proteins
 and life history variation within populations, these ecogeographic
 patterns underscore the need for continued integration of ecology,
 evolution, and telomere biology, which together will advance understanding
 of the drivers of life history variation in nature. 
description: <strong><em>Study
 populations</em></strong>: Data were collected from 8
 populations in the eastern United States, spanning nearly 10 degrees of
 latitude (<strong>Table 1, Fig 2A</strong>): Ithaca, New York
 (42.28°N, 76.29°W); Amherst, Massachusetts (42.22°N, 72.31°W); Linesville,
 Pennsylvania (41.65°N, 80.43°W); Bloomington, Indiana (39.17°N, 86.53°W);
 Lexington, Kentucky (38.11°N, 84.49°W); Knoxville, Tennessee (35.90°N,
 83.96°W); Davidson, North Carolina (35.53°N, 80.88°W); and Santee, South
 Carolina (33.49°N, 80.36°W). These populations do not represent the entire
 breeding range of this species and in particular, do not extend to the
 northern edge in Canada and Alaska. All methods were approved by
 institutional IACUCs and conducted with appropriate state and federal
 permits. <strong><em>Sampling of
 nestlings</em></strong>: Nest boxes were monitored for hatch
 dates, but in cases where hatch dates were missed (e.g., due to weather or
 COVID-related staffing shortages), hatch dates were estimated using
 existing growth curves (McCarty, 2001; Wolf et al., 2021) and accounted
 for in all statistical analyses. Data from multiple populations shows that
 the average peak of postnatal growth occurs around 6-days old (McCarty,
 2001; Wolf et al., 2021). Growth then slows and plateaus near adult size
 by 12-days old, just as feather development accelerates. We targeted
 12-day old nestlings because they have just completed the rapid period of
 postnatal growth. Many studies therefore use morphological data at this
 critical time period as a proxy of nestling growth (Gebhardt-Henrich
 & Richner, 1998; Haywood & Perrins, 1992; Magrath, 1991;
 Martin et al., 2018; McCarty, 2001). Population variation in growth rates
 occurs primarily after peak growth but does not map neatly onto latitude,
 at least not in the northern (historical) range where previous research
 has been focused (Ardia, 2006; McCarty, 2001). We
 sampled nestlings at 12.03 ± 0.01-days old (hatch day = day 1, range = 10
 – 14 days). We sampled ~30 nests per population (<strong>Table
 1</strong>), though logistical constraints prevented collection of
 RNA in Kentucky. Upon arrival at each nest, we immediately collected whole
 blood from the brachial vein of 2-3 nestlings per nest (≤ 200 µl, below
 the maximum suggested volume based on body mass; Gaunt et al., 1997), and
 we avoided obvious runts with atypical growth. We collected blood in
 separate tubes for DNA and RNA analyses. We banded nestlings with a USGS
 band and weighed them to the nearest 0.1g. We also measured flattened wing
 length using a wing ruler. We stored blood on ice or dry ice in the field,
 and later stored it at -80°C. Due to limited budgets,
 we made the decision <em>a priori</em> to conduct laboratory
 analyses for a single nestling per nest. When possible, we selected the
 nestling with the median mass. If the median-massed nestling was not bled
 or failed to produce a sufficient blood sample, we selected the nestling
 with the closest mass to the median. In nests with even brood sizes, we
 randomly selected one of the two nestlings with median mass for telomere
 and gene expression analyses. In all states except Indiana, telomere
 length and gene expression data come from the same individual.
 <em> </em><strong><em>qPCR for Telomere
 length</em></strong><em>: </em>We extracted DNA
 from whole blood (following Wolf et al., 2022) and used primers
 <em>telc</em> and <em>telg </em>(adapted from
 Cawthon, 2009) to quantify telomere length relative to the single copy
 gene GAPDH. Samples were run in triplicate, and mean values were used to
 calculate the T/S ratio of telomere repeat copy number (T) to our single
 gene copy number (S) using the formula: 2<sup>-∆∆Ct</sup>,
 where ∆∆C<sub>t</sub> = (C<sub>t</sub>
 <sup>telomere</sup> – C<sub>t</sub>
 <sup>GAPDH</sup>) <sub>reference</sub> –
 (C<sub>t</sub> <sup>telomere</sup> –
 C<sub>t</sub> <sup>GAPDH</sup>)<sub>
 sample</sub>. The intraclass correlation coefficient (ICC) for
 intraplate repeatability was 0.951 ± 0.03 (95% CI = 0.944, 0.957) for
 GAPDH C<sub>t</sub> values and 0.926 ± 0.09 (95% CI = 0.916,
 0.935) for telomere C<sub>t</sub> values. The ICCs for
 interplate repeatability were 0.96 ± 0.03 (95% CI = 0.87, 0.98) for GAPDH
 Ct values, 0.89 ± 0.06 (95% CI = 0.73, 0.95) for telomere Ct values, and
 0.79 ± 0.10 (95% CI: 0.54 - 0.90) for the T/S ratio (based on
 2<sup>-∆Ct</sup> values). Plates (n = 13) were balanced by
 population, sex, relative date of sampling within each population, and
 brood size. <strong><em>Nestling Sexing
 Protocol</em></strong>: Nestlings were molecularly sexed using
 DNA following established methods (Griffiths et al., 1998; Wolf et al.,
 2022). <strong><em>Shelterin Protein Primer
 Design</em></strong>: Shelterin proteins are relatively
 conserved across taxa (de Lange, 2018; Myler et al., 2021) and earlier
 work has identified at least four shelterin proteins in the chicken (De
 Rycker et al., 2003; Konrad et al., 1999; Tan et al., 2003; Wei &
 Price, 2004). Our shelterin protein primer sets were developed using the
 tree swallow transcriptome (accession #GSE126210; Bentz et al., 2019).
 TRF2 exhibits multiple variants in passerines, and a BLAST search
 confirmed that our primer set targets TRF2 in closely related barn
 swallows (<em>Hirundo rustico</em>). TPP1 and POT1 each have a
 single transcript in adult tree swallows that is highly expressed across
 tissues, and BLAST searches confirmed that our primer sets targeted TPP1
 and POT1 genes, respectively, in multiple bird species. We also designed
 primers for RAP1 based on tree swallow transcripts of TRF2IP
 (TRF2-interacting protein), a common alias for RAP1. However, this study
 omits TRF1 due to negligible expression in nestling blood, and TIN2
 because we could not confidently identify the passerine sequence for TIN2.
 Thus, altogether we quantified gene expression for four key components of
 the shelterin complex: TRF2, RAP1, TPP1, and POT1 (primer sequences in
 <strong>Table S1</strong>).
 <strong><em>qPCR for Shelterin Protein Gene
 Expression</em></strong>: We extracted RNA using a
 phenol-chloroform-based Trizol method (Invitrogen, Carlsbad, CA) with
 PhaseLock tubes (5PRIME, #2302830). We synthesized cDNA using 1µg RNA and
 Superscript III reverse transcriptase (Invitrogen), treated with DNAase
 (Promega, Madison, WI) and RNase inhibitor (RNAsin N2111, Promega). For
 each gene of interest, we used the 2<sup>-∆∆Ct</sup> method of
 quantification (Livak & Schmittgen, 2001), in which expression is
 normalized to the geometric mean Ct of two reference genes for each sample
 (Vandesompele et al., 2002), and relative to a calibrator sample on each
 plate. Reference genes correct for technical variation in cDNA quantity
 across samples, and as such, must (i) be highly expressed, (ii) exhibit
 low variability among samples, and (iii) show no significant variation
 among biological categories of interest. Our reference genes were PPIA
 (peptidylprolyl isomerase A; Virgin & Rosvall, 2018) and MRPS25
 (Mitochondrial Ribosomal Protein S25; Woodruff et al., 2022). Preliminary
 work showed that New York samples exhibited markedly higher gene
 expression of these and a third reference gene (GAPDH). This violates
 assumption (iii) of the 2<sup>-∆∆CT</sup> method, and we
 therefore had to omit New York gene expression data. The remaining six
 populations exhibited limited among-population variation in reference gene
 expression (non-significant state differences or ≤ 0.5 Ct of the
 study-wide average). Samples were run in triplicate
 alongside No Template Controls (NTCs), using PerfeCta SYBR Green FastMix
 with low ROX (Quanta Biosciences, Gaithersburg MD) on 384-well plates
 using an ABI Quantstudio 5 machine with Quantstudio Design &
 Analysis software (v1.4.3, Thermo Fisher Scientific, Foster City, CA).
 Each well included 3µL of cDNA diluted 1:50 (or 3µL water, for NTCs) and
 primers diluted to 0.3µM in a total volume of 10µL. All reactions use the
 following thermal profile: 10 min at 95°, followed by 40 cycles of 30 s at
 95°, 1 min at 60°, and 30 s at 70°, with a final dissociation phase (1 min
 at 95°, 30 s at 55°, and 30 s at 95°) that confirmed single-product
 specificity for all samples. All samples fell within the bounds of the
 standard curve and reaction efficiencies were within 100 ± 15%. Each gene
 was run on 1.5 plates, balanced by population. Intraclass correlation
 coefficients for triplicates were 0.996 ± 0.01 (95% CI = 0.995, 0.997) for
 PPIA C<sub>t</sub> values, 0.994 ± 0.009 (95% CI = 0.993,
 0.996) for MRPS25 C<sub>t</sub> values, 0.975 ± 0.05 (95% CI =
 0.967, 0.982) for POT1 C<sub>t</sub> values, 0.940 ± 0.05 (95%
 CI = 0.923, 0.954) for TRF2 C<sub>t</sub> values, 0.975 ± 0.05
 (95% CI = 0.968, 0.981) for TRF2IP C<sub>t</sub> values, and
 0.996 ± 0.007 (95% CI = 0.995, 0.997) for TPP1 C<sub>t</sub>
 values.
description: # Among-population variation in telomere regulatory proteins and their
 potential role as hidden drivers of intraspecific variation in life
 history We assessed
 ecogeographic variation in shelterin protein abundance across eight
 populations of tree swallow (Tachycineta bicolor) with previously
 documented variation in environmental and life history traits. Using blood
 gene expression of four shelterin proteins in 12-day old nestlings, we
 tested the hypothesis that shelterin protein gene expression varies
 latitudinally and in relation to both telomere length and life history.
 This dataset includes the following information from nestlings sampled
 across eight populations: # siblings, age, molecular sex, morphology,
 relative telomere length, and relative gene expression for four shelterin
 protein genes. ## Description of the data and file structure In the excel
 file, each row corresponds to an individual nestling. Because of the
 nature of field work, each variable of interest does have missing data for
 some individuals. In addition, only a subset of nestlings were chosen for
 telomere length and shelterin protein gene expression analyses. Please see
 the "Notes" sheet on the excel data file for descriptions of the
 columns and variables.