INTRODUCTION
Telomeres are nucleoprotein structures that cap the ends of linear
chromosomes in most eukaryotes (Blackburn, 1991). Understanding the
causes of individual variation in telomere length (TL) is important
because this trait has been shown to predict variation in survival or
lifespan within and among species (Joeng, Song, Lee, & Lee, 2004; Bize,
Criscuolo, Metcalfe, Nasir, & Monaghan, 2009; Monaghan, 2010; Heidinger
et al., 2012; Tricola et al., 2018; Wilbourn et al., 2018; Pepke &
Eisenberg, 2021) and individual fitness in wild animals (Eastwood et
al., 2019). Telomeres shorten through life in many organisms (Dantzer &
Fletcher, 2015) due to cell division, oxidative stress, and other
factors (Jennings, Ozanne, & Hales, 2000; Reichert & Stier, 2017),
which can ultimately result in telomere dysfunction, genome instability,
and cell death (Nassour et al., 2019) and organismal senescence (Herbig,
Ferreira, Condel, Carey, & Sedivy, 2006). Individual TLs may act as
biomarkers or sensors of exposure to intrinsic and extrinsic stressors
(Houben, Moonen, van Schooten, & Hageman, 2008), and hence reflect
individual condition (Rollings et al., 2017), but the physiological
mechanisms underlying the ontogenetic variation in TL is not well known
(Monaghan, 2014; Erten & Kokko, 2020). Several studies have
investigated the potential of telomere dynamics (i.e. individual
differences in TL and telomere loss rate) in mediating life-history
trade-offs both across (Dantzer & Fletcher, 2015; Pepke & Eisenberg,
2020) and within relatively long-lived species (Monaghan, 2010; Spurgin
et al., 2018). However, despite being an ecologically important trait in
many species (Wilbourn et al., 2018), knowledge about the genetic
architecture of TL or its adaptive potential in wild populations remains
scarce (Dugdale & Richardson, 2018).
Quantifying the additive genetic variance of a trait is required to
understand mechanisms driving
adaptive evolution, i.e. the response to selection on a trait (Lande,
1979; Ellegren & Sheldon, 2008; Kruuk, Slate, & Wilson, 2008).
However, the magnitude of the heritability and mode of inheritance of TL
is not well-known in populations of wild animals, and few general
patterns have been described (Horn et al., 2011; Dugdale & Richardson,
2018; Bauch, Boonekamp, Korsten, Mulder, & Verhulst, 2019). Utilizing
long-term pedigree data, individual variation in early-life TL can be
decomposed into various genetic and environmental sources of variation
through a type of mixed-effect model
(‘animal model’),
which takes all relationships from
the pedigree into account (Kruuk, 2004; Wilson et al., 2010). Estimates
of TL heritabilities from studies using animal models (reviewed in
Dugdale & Richardson, 2018) have varied considerably across bird
species from h2 =0 (n =177, in wild
white-throated dippers, Cinclus cinclus , Becker et al., 2015) toh2 =0.99 (n =125, in captive zebra
finches, Taeniopygia guttata , Atema et al., 2015). While most
studies are characterized by relatively small sample sizes, recent
long-term studies on Seychelles warblers (Acrocephalus
sechellensis , n =1317, h2 =0.03-0.08,
Sparks et al., 2021) and common terns (Sterna hirundo ,n =387, h2 =0.46-0.63, Vedder et al.,
2021) also revealed contrasting estimates of TL heritabilities.
Epidemiological studies of humans have documented consistently high TL
heritabilities, ranging from h2 =0.34-0.82
(Broer et al., 2013). In humans, some studies reported strong paternal
inheritance (e.g. Njajou et al., 2007) or maternal inheritance (e.g.
Broer et al., 2013) or that there were no differences in parental mode
of inheritance (e.g. Eisenberg, 2014). In birds, several studies have
documented maternal effects on offspring telomere dynamics (Horn et al.,
2011; Asghar, Bensch, Tarka, Hansson, & Hasselquist, 2015; Reichert et
al., 2015; Heidinger et al., 2016), or effects of parental age at
conception on offspring TL (Eisenberg & Kuzawa, 2018). Reichert et al.
(2015) found a significant correlation between mother-offspring TL
measured at 10 days of age in king penguins (Aptenodytes
patagonicus ), but not when TL was measured at later ages
(>70 days). This may be because post-natal telomere loss
rate is strongly influenced by individual environmental circumstances
(Wilbourn et al., 2018; Chatelain, Drobniak, & Szulkin, 2020) and does
not always correlate strongly with chronological age (Boonekamp, Simons,
Hemerik, & Verhulst, 2013; Boonekamp, Mulder, Salomons, Dijkstra, &
Verhulst, 2014).
Telomeres shorten during growth and a negative phenotypic correlation
between TL and body size has been documented within several species
(Monaghan & Ozanne, 2018). This may indicate that there is a negative
genetic correlation between TL and size, which could act as an
evolutionary constraint on the response of TL to selection on body size
and contribute to the trade-off between growth and lifespan (Metcalfe &
Monaghan, 2003; Roff & Fairbairn, 2012). Thus, quantifying the genetic
correlation between TL and size enables us to determine whether TL can
evolve independently of body size. Pepke et al. (2021, submitted )
showed that artificial directional selection on body size affected TL in
the opposite direction. However, it is not known if there is a genetic
correlation between the two traits, in which case selection acting on TL
will affect body size. It is also possible that the negative phenotypic
correlation between TL and size has no genetic basis but is shaped by
environmental (co)variances (Hadfield, 2008; Kruuk et al., 2008).
TL is a complex phenotypic trait (Aviv, 2012; Hansen et al., 2016)
expect to be polygenic, i.e. affected by small effects of many genes
(Hill, 2010; Dugdale & Richardson, 2018). Accordingly, numerous
genome-wide association studies (GWAS), which tests associations of
single-nucleotide polymorphisms (SNPs) with specific traits, have
identified several loci correlated with TL in humans that map to genes
involved in telomere and telomerase maintenance, DNA damage repair,
cancer biology, and several nucleotide metabolism pathways (e.g.
Vasa-Nicotera et al., 2005; Andrew et al., 2006; Codd et al., 2010; Levy
et al., 2010; Mirabello et al., 2010; Jones et al., 2012; Mangino et
al., 2012; Soerensen et al., 2012; Codd et al., 2013; Deelen et al.,
2013; Liu et al., 2014; Mangino et al., 2015; Ojha et al., 2016; Delgado
et al., 2018; Zeiger et al., 2018; Coutts et al., 2019; Nersisyan et
al., 2019; Li et al., 2020). None of the GWA studies in humans
specifically tested the marker associations of early-life TL, which pose
a challenge to the interpretation of the results, as TL shortens through
life in humans (Blackburn, Epel, & Lin, 2015) and genes may have
different impacts at various life stages. Furthermore, large sample
sizes and dense sampling of genetic loci is needed to ensure high power
in GWA studies (Mackay, Stone, & Ayroles, 2009) and resolve any
pleiotropic effects (Prescott et al., 2011). The genes influencing TL in
humans that were identified through GWAS only explain a small proportion
of the inter-individual variation in TL (<2 %, Aviv, 2012;
Codd et al., 2013; Fyhrquist, Saijonmaa, & Strandberg, 2013). One GWAS
on TL of a non-human species (dairy cattle, Bos taurus ) was
recently performed (Ilska-Warner et al., 2019) supporting the polygenic
nature of early-life TL. However, domesticated species in captivity may
display TL dynamics that are not representative for natural populations
(Eisenberg, 2011; Pepke & Eisenberg, 2021). There is a paucity of GWAS
on TL performed in natural populations.
In this study, we aim to provide novel insights into the genetic
architecture of TL and the evolutionary mechanisms by which natural
selection can alter telomere ecology using data from a passerine bird.
We sampled TL of most individuals (n =2746) born within 20 cohorts
in two natural insular populations of wild house sparrows (Passer
domesticus ) at about the same age (11 days), in addition to individuals
at the same age in two insular populations that underwent artificial
selection on body size for 4 consecutive years (n =569, Kvalnes et
al., 2017; Pepke et al., 2021, submitted ). First, we estimate the
phenotypic correlations between TL and tarsus length (as a proxy for
body size, Araya-Ajoy et al., 2019) in house sparrow nestlings. Second,
we test for effects of parental age on offspring TL. Third, we estimate
heritability, environmental variances, and parental effects on
early-life TL, and test for genetic correlations between TL, body size,
and body condition in the natural populations (primary analyses). We
then use similar analyses in the artificially selected populations to
validate our results from the primary analyses. Finally, we use
high-density genome-wide Single Nucleotide Polymorphism (SNP) genotype
data (Lundregan et al., 2018) in a GWAS to identify genetic regions and
potential candidate genes underlying variation in early-life TL within
wild house sparrows (up ton =383).