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\begin{document}

\title{Parental age does not influence offspring telomeres during early life in
common gulls (Larus canus)}



\author[1]{Tuul Sepp}%
\author[1]{Richard Meitern}%
\author[2]{Britt Heidinger}%
\author[3]{Kristina Noreikiene}%
\author[3]{Kalev Rattiste}%
\author[1]{Peeter Hõrak}%
\author[1]{Lauri Saks}%
\author[1]{Janek Urvik}%
\author[4]{Mathieu Giraudeau}%
\affil[1]{University of Tartu}%
\affil[2]{North Dakota State University}%
\affil[3]{Estonian University of Life Sciences}%
\affil[4]{CNRS}%


\vspace{-1em}



  
  \date{June 02, 2024}


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\selectlanguage{english}
\begin{abstract}
Parental age can affect offspring telomere length through heritable and
epigenetic-like effects, but at what stage during development these
effects are established is not well known. To address this, we conducted
a cross-fostering experiment in common gulls (Larus canus) that enabled
us distinguish between pre- and post-natal parental age effects on
offspring telomere length. Whole clutches were exchanged after clutch
completion within and between parental age classes (young and old) and
blood samples were collected from chicks at hatching and during the
fastest growth phase (11 days later) to measure telomeres. Neither the
ages of the natal nor the foster parents' predicted the telomere length
or the change in telomere lengths of their chicks. Telomere length was
repeatable within chicks, but increased across development
(repeatability = 0.55, Intraclass Correlation Coefficient within
sampling events 0.934). Telomere length and the change in telomere
length were not predicted by post-natal growth rate. Taken together,
these findings suggest that in common gulls, telomere length during
early in life is not influenced by parental age or growth rate, which
may indicate that protective mechanisms buffer telomeres from external
conditions during development in this relatively long-lived species.%
\end{abstract}%



\sloppy


\textbf{Keywords}

Ageing, seabirds, telomere length, telomere dynamics, maternal effects,
qPCR

\textbf{Introduction}

Parental age often has long-term effects on offspring phenotype in
humans (Carlaske, Tynelius, van den Berg, \& Smith, 2019) and wild
animals (Bowers, Sakaluk, \& Thompson, 2017). In some cases, parental
age has a positive long-term effects on offspring (Bradley \& Safran,
2014), possibly because older parents are more experienced breeders than
younger parents and/or because reproductive investment increases with
age as future reproductive opportunities decline (e.g., terminal
investment) (Clutton-Brock, 1984). Alternatively, parental age may have
negative long-term effects on offspring if older parents experience
senescent declines in condition and/or reproductive function relative to
younger parents (Bock, Jarvis, Corey, Stone, \& Gribble, 2019; Maklakov
\& Chapman, 2019; Velarde \& Menon, 2016). Regardless, the mechanisms
that underlie these long-term effects of parental age on offspring
phenotype are not well understood, although several candidate mechanisms
have been proposed, including, for example, epigenetic factors (Bock et
al. 2019).

One of the mechanism that has been proposed may mediate
trans-generational effects of parental on offspring fitness could be
offspring telomere length (TL). Telomeres are highly conserved,
repetitive, non-coding sequences of DNA that form protective caps at the
ends of chromosomes, thereby enhancing genome stability (Blackburn,
2005). While some evidence suggests that TL is largely inherited
(Blackburn, 2005), it is also known that TL and telomere dynamics are
affected by a complex interaction of genetic effects and environmental
factors during an organism's life (Dugdale \& Richardson, 2018;
Monaghan, 2010). While telomeres typically shorten with age in somatic
cells, elongation of telomeres has also been described, mainly as a
result of the activity of the enzyme telomerase, which can extend
telomeres via the addition of terminal telomeric repeats (Cong, Wright,
\& Shay, 2002), and which is variably active in different cell types and
at different life stages (Gomes et al. 2011). The effect of parental age
on the length of offspring telomeres is currently an intensively studied
(e.g. Bauch, Boonekamp, Korsten, Mulder,\& Verhulst, 2019; Criscuolo,
Zahn,\& Bize, 2017; Heidinger et al. 2016; Froy et al. 2017; Noguera \&
Velando, 2020). Costs and benefits associated with maintaining the
length of telomeres are particularly interesting when considering the
adaptive role of telomeres in the evolution of life histories, as it is
suggested that telomeres play a proximate causal role in current--future
life-history trade-offs (Young, 2018). Optimal life-history strategies
are both inherited and shaped by environmental effects (Stearns, 1992),
and accordingly, telomere dynamics are a plausible physiological
mechanisms related to life-histories (Giraudeau, Angelier, \& Sepp,
2019).

While studies are accumulating that show parental age effects on
offspring telomeres, it is still unknown when these effects are
occuring. There are three potential routes through which parental age
could impact offspring telomeres (Haussmann \& Heidinger 2015; Heidinger
\& Young, 2020). First, age-associated changes in parental gametes may
affect the telomere length of offsprings. Parental age may negatively
influence offspring telomere length if older parents produce gametes
with shorter telomeres (shown for example in mice, \emph{Mus musculus} ,
de Frutos et al. 2015), however, studies in humans have also shown that
older fathers may have offspring with longer telomeres (Broer et al.
2013; Unryn, Cook, \& Riabowol, 2005), due to active telomerase in sperm
cells (Kimura et al., 2008). Such inconsistences among studies, but also
within species, could stem from differences in life-history strategies,
likely via mechanisms related to spermatogonial stem cell telomere
retention with increasing age, or selective attrition/survival of
spermatogonia (Kimura et al. 2008; Eisenberg \& Kuzawa 2018). Studies in
humans have mostly found a link between paternal age and offspring
telomere length, however, the effect of maternal age has been shown to
be even stronger for some species (e.g. great reed
warbler\emph{Acrocephalus arundinaceus} , Asghar, Bensch, Tarka,
Hansson, \& Hasselquist, 2015). While maternal reproductive cells
develop at a very early age, after which they are retained throughout
life without further cell divisions, association between mother age and
offspring telomere length could be explained by other mechanisms, for
example age- and/or condition-dependent telomerase activity in the
ovaries (Asghar et al. 2015a; Kinugawa, Murakami, Okamura, \& Yajima,
2000). Second possible route is through pre-natal effects, for example
age-associated changes in the amounts of glucocorticoid or androgen
hormones transferred from the mother to the developing embryo with
increasing age of the mother (Haussmann \& Heidinger, 2015; Heidinger \&
Young, 2020; Stier, Metcalfe, \& Monaghan 2019). This could in turn
activate the production of reactive oxygen species (ROS), as well as
decrease telomerase activity in the offspring (Haussmann \& Heidinger,
2015), potentially leading to telomere erosion. While there are now a
number of studies linking pre-natal stress to offspring telomeres
(reviewed for example, in Dantzer et al. 2020; Haussmann \& Heidinger;
2015, Heidinger \& Young, 2020), none have included parental age in this
equation. Third route are post-natal effects, as age-related variation
in parental care and the characteristics of the post-birth environment
could also be important mediators of offspring telomere dynamic
(Tarry-Adkins et al. 2009). For example, more experienced parents may
provide better care (Beamonte-Barrientos, Velando, Drummond, \& Torres,
2010), but older parents may also become less capable of providing a
high quality environment due to senescence effects (Torres, Drummond, \&
Velando, 2011). The quality of the parental care during the growth phase
may hasten or reduce telomere shortening (Criscuolo et al., 2017) with
long-lasting effects on the aging rate and life-history trajectories of
the organisms (Young 2018).

Distinguishing between the role of genetic/pre-natal and post-natal
effects on telomere length and telomere dynamics in natural populations
early in life is difficult, but potentially most important from an
evolutionary and ecological perspective (Dugdale \& Richardson, 2018).
Birds are a promising model system for this kind of study, as the embryo
development takes place within a sealed system, the egg, limiting the
physiological maternal effects with the moment of egg laying.
Cross-fostering experiments are a useful tool, as they allow to tease
apart effects that are epigenetic and/or due to pre-natal egg effects,
from effects occuring during incubation and/or chick feeding. However,
to the best of our knowledge, there are only two studies that have used
cross-fostering approach to separate the genetic and environmental
effects of parental age on offspring telomere length. In alpine swifts
(\emph{Apus melba} ), foster mother's age negatively affected offspring
telomere length (Criscuolo et al., 2017). Bauch \emph{et al} . (2019)
showed that paternal age effect on offspring telomere length is
independent of paternal care after conception in jackdaws (\emph{Corvus
monedula} ). However, neither of these studies took repeated measures,
which are necessary to assess the change in TL and to separate
phenotypic variance into individual and residual variance components to
calculate repeatability (Stoffel, Nakagawa, \& Schielzeth, 2017). In a
recent cross-fostering study of king penguins (\emph{Aptenodytes
patagonicus} ), repeated measures of TL were taken, indicating that
chick telomere length was positively related to foster mothers' TL at
both 10 and 105 days after hatching, however, this study did not include
information about parental age (Viblanc et al 2020). Our study combines
both of these approaches, applying a cross-fostering manipulation
between differently aged parents with repeated measures of offspring
telomere length in a wild population of long-lived birds. We
cross-fostered whole clutches of common gull (\emph{Larus canus} ) eggs
shortly after laying within and between age classes of young and old
parents, and assessed telomere length and dynamics during the chick
fastest growth phase. We predicted that if there are pre-natal,
epigenetic-like effects of parental age on offspring telomeres, there
will be a relationship between the age of the natal parent and offspring
telomeres, but if post-natal, environmental effects mediate the link
between parental age and offspring telomere length, there will be a
relationship between the age of the foster parent and offspring
telomeres.

\textbf{Materials and methods}

\textbf{1. Field methods.}

We conducted the study between the end of May -- early June 2017 on a
free-living, known-age breeding population of common gulls located on
Kakrarahu islet in Matsalu National Park on the west coast of Estonia
(58\selectlanguage{ngerman}°46' N, 23°26' E)\textsuperscript{34}. Based on studies of offspring
recruitment rate, reproductive success in common gulls increases to the
10th breeding year (12-13 years of age) and decreases thereafter
(Rattiste, 2004). It is known that they undergo senescence in a number
of physiological functions (Rattiste et al. 2015; Sepp et al. 2017;
Urvik, Rattiste, Giraudeau, Okuliarová, Hõrak \& Sepp, 2018). In
addition, this species is characterized by bi-parental care and a low
frequency of extra-pair mating ((Bukacinska, Bukacinski, Epplen,, Sauer,
\& Lubjuhn, 1998), making it possible to study the effects of age of the
parent of both sexes, and the age-dependent quality of parental care.
All of the birds included in the study were banded as chicks and their
exact age was therefore known. Common gulls typically lay clutches of
three eggs.

A total of 40 clutch nests were included in the experiment. Nests and
experimental groups were chosen based on the age of the mother, but the
father's age was also known. Common gulls mates assortatively with
respect to age and the ages of the parents were highly positively
correlated (Spearman r=0.74, p\textless{}0.0001) Half of the breeders
(\emph{n} = 20 females) were young, on their 1st-3rd breeding event (age
exactly 5 years). Another half (\emph{n} = 20 females) were middle-aged
or older (15-30 years old, average age 18 ± 3.37 (SD) years). In total,
19 males were 5-7 years old (average age 5.52 ± 0.80 (SD) years) and
were grouped as ``young'', 21 males were 10+ years (average age 16.29 ±
5.58 (SD) years) old and were grouped as ``old''. Distribution of the
ages of parent birds are shown in figures S4-S7.

We cross-fostered whole clutches right after the clutch was completed
both within and between maternal age classes (Table 1), so all of the
chicks included in this experiment hatched in foster-parent's nests.
Half of the clutches were cross-fostered within age classes and half
were cross-fostered between age classes. The 72 chicks that were
successfully caught for second sampling were included in the study.
Within two days from hatching, we collected the first blood sample
(10-30 \selectlanguage{greek}µ\selectlanguage{english}L taken, from brachial vein) for telomere measurement (average
age 0.61\selectlanguage{ngerman}±0.09 (SE) days) and individually marked the chicks for
identification. Chick head size (the distance from the tip of the bill
to the back of the head) was measured with a calliper to the nearest 0.1
mm. The day of the second blood sample varied between chicks, due to
difficulties in trapping precocial chicks. We captured the chicks near
their nests and collected a second blood sample between the 8th and 20th
day after hatching (with one exception of a 5-days old chick). Average
age at second blood sampling was 10.62 days (±0.35 SE). Blood samples
were kept on ice in an insulated box while on the islet, and stored at
-20°C until the end of the field work period, when they were transferred
to -80ºC and held there until analysed. The experimental protocol was
approved by the Ministry of Rural Affairs of the Republic of Estonia
(licence no. 106, issued 24.05.2017) and was performed in accordance
with relevant Estonian and European guidelines and regulations.

\textbf{2. Telomere measurement methods}

DNA was extracted from whole blood samples using Macherey Nagel
Nucleospin Blood kits following the manufacturer's protocol. Avian red
blood cells are nucleated and are well suited for longitudinal telomere
analysis (Nussey et al. 2014). DNA concentration and purity were
assessed with a Nanodrop 8000 (Thermo Scientific). Relative telomere
length was measured using qPCR (quantitative polymerase chain reaction)
on an Mx3000P (Stratagene) as described in Cawthon (2002) and modified
for use in common gulls (Rattiste et al., 2015). The relative telomere
length (T/S) of the samples was calculated as the ratio of the telomere
repeat copy number (T) to that of a single copy control gene (S),
relative to the reference sample. Glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) was used as the single copy control gene. We used
the following gull specific GAPDH forward and reverse primers
(Integrated DNA Technologies): 5'-CGGAGCACCGCTTACAATTT-3' and 5'-
GCATCTCCCCACTTGATGTTG-3' respectively. Amplified samples were run on a
3\% agarose gel to verify that the amplification was a single product,
which yielded a single band at 77 bp as expected. We used the following
telomere primers (Quanta Bio, with final concentration of 200 nM): TEL
1b: 5'-CGGTTTGTTTGGGTTTGGGTTTGGGTT-3' and TEL 2b:
5'-GGCTTGCCTTACCCTTACCCTTACCCT-3. The qPCR reactions for GAPDH and
telomeres were run on separate plates. All reactions used 20 ng of DNA
in a final volume of 25 \selectlanguage{greek}µ\selectlanguage{english}l containing 12.5 \selectlanguage{greek}µ\selectlanguage{english}l of SYBER green Master Mix,
0.25 \selectlanguage{greek}µ\selectlanguage{english}l forward and reverse primer, 6 \selectlanguage{greek}µ\selectlanguage{english}l water, and 6 \selectlanguage{greek}µ\selectlanguage{english}l of DNA sample.
A negative control of water was run on each plate. All samples were run
in duplicate, and average values were used to determine the T/S ratio.
Treatment groups were distributed approximately equally between plates.
Replicates of each sample, and the first and second sample for each bird
were run on the same plate. In order to assess the efficiencies of each
plate, samples were run against a standard curve of 40, 20, 10, 5, and
2.5 ng produced by serially diluting a reference sample. In all cases,
plate efficiencies were in the accepted range (i.e. 100+/-15\%) and all
of the samples fell within the bounds of the standard curve. Average
plate efficiencies and standard errors for GAPDH and telomere plates
were 102.34 \selectlanguage{ngerman}± 3.00, and 98.94 ± 3.00, respectively. The average
intra-plate variation of the Ct values was 0.82\% for the telomere
assays and 0.19\% for the GAPDH assays, and the inter-plate CV-s of the
Ct values for telomere and GAPDH assays were 0.64\% and 0.34\%,
respectively. The same individual was also included on every plate and
the coefficient of variation of the T/S ratio across plates was 8.12\%.
A subset of samples (45) was ran twice for assessing measurement
accuracy. Average Intraclass Correlation Coefficient (ICC) in this
subset was 0.934 (95\% CI 0.879 ± 0.964), p \textless{} 0.0001, for
single measurements ICC = 0.876 (95\% CI 0.785 ± 0.930) p \textless{}
0.0001.

\textbf{3. Statistical methods}

To test for an effect of parental age on chicks' telomere erosion and
telomere measurements at first and second sampling, we used repeated
measures mixed models and the R package lmerTest (Kuznetsova, Brockhoff
\& Christensen, 2017). Chick nested in the respective nest was included
as a random effect in our analysis. Models included age groups (young or
old) of either mother and foster mother or father and foster father as
categorical predictors, to emphasize our study design and questions.
Similar models were also run with age as a continuous factor (Table S1).
Separate models were run for mother's and father's age effect, since the
age of parents was strongly correlated and could not be entered in the
same models. Both models with and without interaction (Tables 1 and S2)
with sampling occasion (first or second) were run. Interval between
sampling varied between individuals, but this was not included in these
models as it was not related to telomere length (Figure S8, Table S6, p
= 0.805). Parental age effect models were run for head size as a
dependent variable (Tables S4-S5). In these models, chick age was
included as a predictive factor since it correlated significantly with
head size. Markov Chain Monte Carlo (MCMC) multivariate generalised
linear mixed models where used for assessing the continuous effects of
parental age (hatch year) on telomere length and telomere length
dynamics. Repeatabilites were calculated using R package rptR (Stoffel
et al., 2017). Heritabilities were obtained using one-way ANOVA from the
full sib design and (for the models including parental age and treatment
effects) using generalised linear mixed models for the repeated measures
design (R package MCMCglmm) (Hadfield 2010, de Villemereuil, Morrissey,
Nakagawa \& Schielzeth, 2018; Kuznetsova \& Hadfield, 2010). The models
were run for both telomere measurements (first and second) as well as
change as a dependent variable. The models included parent nest as
random effect and the same fixed effects as the repeated measures mixed
model for the effect of telomere length change. Both repeatability and
heritability measures are reported together with 95\% coefficient
intervals (CI). The distribution of the traits was normal or close to
normal distribution (Figures S1-S3), accordingly, models were ran with
untransformed values. Power analyses were conducted based on Monte Carlo
simulations (Green \& MacLeod, 2015) (Table S3). The R code for
different steps in the statistical analyses is accessible from the
supplementary material.

\textbf{Results}

There were no significant effects of the ages of the natal or foster
parents on offspring telomeres at hatching or the change in offspring
telomere length from hatching to the end of post-natal development
(Figure 1, see Tables 2 and S2 for results with age groups, young vs
old, and Tables 3 and S1 for results with parental age as a continuous
factor). When we entered the parental age squared in the models, it did
not change this result (Tables S7-S9). Telomere length was individually
repeatable between the first and second sampling, separated by on
average 11 days (repeatability r = 0.55, CI= 0.368 to 0.69, p
\textless{} 0.0001, Figure 2). Chick telomere length between the first
and second telomere measurements increased rather than decreased (the
estimated change in relative telomere length was 0.08 ± 0.05, p=0.003,
Table 2; when one outlier chick with highest increase in telomere length
was removed, the results stayed similar, estimated change 0.06 ± 0.04, p
= 0.005). The rate of growth during post-natal development was not
significantly related to the change in telomere length (measured as
change of head size, r \textless{} 0.0001; p = 0.97, Figure 3). Chick
growth rate was not related to the age of the parents and foster parents
(all parental effect p-values \textgreater{} 0.31, Tables S4-S5). The
power for detecting potential effects of parental age on telomere length
and telomere shortening in our sample is reported in Table S3. The study
set up also allowed us to assess wide-sense heritability of telomere
length, although these results must be taken with caution, since we did
not use a split nest cross-fostering design. Chick telomere length at
both first (h\textsuperscript{2}=0.27 CI=0.05 to 0.50) and second
(h\textsuperscript{2}=0.30 CI=0.08 to 0.54) measurement as well as the
change of telomere length (calculated as telomere length 2 - telomere
length 1, h\textsuperscript{2}=0.14 CI=0.03 to 0.29) were heritable.

\textbf{Discussion}

Parental age often has long-term consequences for offspring phenotype
and fitness, but the mechanisms that mediate these effects remain
insufficiently studied. Previous research suggests that telomeres may be
an important mechanism mediating these effects, but the routes by which
these effects occur are not well understood. The cross-fostering
experiment used here allowed us to distinguish whether any effects of
parental age on offspring telomeres occur as a result of epigenetic like
and/or pre-natal effects vs. post-natal effects. Previous research in
this colony of common gulls has demonstrated that offspring fitness
decreases with increasing parental age: recruitment rate decreases in
common gulls after the 10th breeding year (12-13 years of age)
(Rattiste, 2004), and older gulls allocate less nutrients to their eggs
(Urvik et al., 2018). However, despite these demonstrated effects of
parental age on offspring fitness in this species, we did not find any
evidence of the effect of parental age on offspring telomeres at
hatching or the change in telomere length during post-natal development.

Although parental age has been shown to have both negative and positive
effects on offspring telomere length (Table 4), this has not been found
in all studies. For example, no effect of parental age on offspring
telomere length was found in a study of Soay sheep (\emph{Ovis aries} )
despite a large sample size (Froy et al., 2017). Although bird studies
have generally found a negative effect of parental age on offspring
telomeres (see for example studies in alpine swifts, (Criscuolo et al.,
2017), and European shags \emph{Phalacrocorax aristotelis} , (Heidinger
et al., 2016), this is not a universal pattern (for example, older great
reed warbles \emph{Acrocephalus arundinaceus} produced offspring with
longer telomeres, (Asghar et al., 2015b). Also in humans the effect of
paternal age is positive rather than negative, as older fathers sire
offspring with longer telomeres (Broer et al., 2013). A review article
summarizing these results concluded that while there is no clear pattern
across species, this is unlikely to be explained by statistical noise or
publication bias (Eisenberg, 2014), but rather linked to the specific
biology of each species. There are also several additional factors that
could contribute to these mixed results: whether the study is
experimental or correlative, at what age the offspring are sampled, and
whether it is a longitudinal versus cross-sectional study of parental
age. Accordingly, we cannot rule out that a longitudinal set-up would
have revealed an effect of parental age on offspring telomere results
also in our study system, as the cross-sectional design could have
obscures the within individual patterns. Another possibility is that the
link between parental age and offspirng telomere length in this species
was too weak to be revealed from our sample size, despite relatively
good test power (Table S3). In this case, and also in the case of a
missing link, it is possible that telomere length in common gulls is
indeed relatively buffered from environmental influence.

Telomere length was repeatable across the chick rearing period in our
study, indicating a possible increase during post-natal development, and
not being related to chick growth rate. Telomeres were longer at the
second sampling, when chicks were approximately 11 days old. This period
covered the fastest growth period of gull chicks. While telomeres
shorten during growth in most studied adult vertebrates (which, as of
now, mainly include mammals and some bird species), some vertebrates
show increased telomerase activity during development (reviewed by
Larsson, Rattiste, \& Lilleleht, 1997, Monaghan \& Haussmann, 2006). It
has even been suggested that in free-living long-lived organisms,
evolution should favour mechanisms that maintain the longest possible
telomeres at the end of the most active growth period (Chan, \&
Blackburn, 2004). Studies in the wild have shown that telomeres elongate
in at least some life stages in Seychelles warblers (\emph{Acrocephalus
sechellensis} (Spurgin et al., 2018)), edible dormouse (\emph{Glis
glis}(Hoelzl et al., 2016)), Soay sheep (Fairlie et al., 2016),
Magellanic penguins (\emph{Spheniscus magellanicus} (Cerchiara et al.,
2017)), and Atlantic salmon (\emph{Salmo salar} (McLennan et al.,
2018)). However, when looking at the few studies on species more closely
related to common gulls, telomere shortening during the early growth
period has been reported. For example, in lesser black\selectlanguage{english}-backed gull
(\emph{Larus fuscus} ), telomeres shortened from hatching to ten-days
old (Foote et al., 2011), and in black-tailed gull chicks (\emph{Larus
crassirostris} ), telomere attrition was shown for chicks growing with
siblings in the nest (but not singleton chicks (Mizutani, Niizuma, \&
Yoda, 2016)). The latter study suggests that, in favourable growing
conditions, telomere attrition might be prevented. However, more results
on closely related species are needed to confirm the possibility of
telomere lengthening during early growth in gulls. Growth rate was
independent of telomere length or telomere dynamics (Figure 3). In
general, a trade-off between rapid growth and telomere maintenance is
expected, due to increased number of cell divisions required to attain
larger size, and/or increased loss of telomere length during each cell
division as a consequence of the conditions required for fast growth
(e.g. higher metabolic rate and ROS production reviewed by Monaghan \&
Ozanne (2018)). The current study adds to the increasing number of
studies suggesting a different pattern in long-lived seabirds (Mizutani
et al., 2016; Young et al., 2017). Seabirds are distinguished from most
other species by a long time period between the end of relatively fast
somatic growth and the beginning of reproduction (stretching several
years). More studies applying comparable methodological approaches are
needed for a comparative study, including patterns of growth and
life-history strategies of different species to determine if this
phenomenon of delayed reproduction is causally linked with the lack of
an association between fast growth and telomere shortening in seabirds.

In conclusion, our results suggest that the age of the parents at the
time of offspring conception does not influence offspring telomere
length or the change in telomere length in common gulls. An important
area of future research is to identify other mechanisms that mediate the
long-term effects of parental age on offspring and to better understand
the factors that contribute to the variation in the influence of
parental age on offspring telomeres across species.

\textbf{Acknowledgements}

We thank Jeffrey Kittilson for help with telomere measurements. We also
thank Mari-Ann Lind, Ulvi Karu and other field assistants. We thank two
anonymous reviewers who gave valuable suggestions for improving the
manuscript.

\textbf{Funding}

This work was supported by the Estonian Research Council (IUT21-1,
IUT34-8, PUT653, PSG458), Marie Sklodowska-Curie grant agreement no.
701747 to TS, and Mobilitas Pluss from European Regional Development
Fund (MOBJD344 to KN).

\textbf{Compliance with ethical standards}

The experimental protocol was approved by the Ministry of Rural Affairs
of the Republic of Estonia (licence no. 106, issued 24.05.2017) and was
performed in accordance with relevant Estonian and European guidelines
and regulations.

\textbf{Conflict of interests}

The authors declare no competing interests.

\textbf{Authors' contribution}

TS, MG, PH and KN conceived the ideas and designed methodology; JU, KR,
RM and LS collected the data; KR provided demographic data; TS, BH and
MG analysed the samples; PH, RM and TS performed statistical analyses.
All authors contributed critically to the drafts and gave final approval
for publication.

\textbf{Data accessibility}

Data available from the Dryad Digital Repository (TBA)

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\textbf{Tables and figures}

Table 1. Cross-fostering experiment sample sizes. A total of 72 chicks
from 40 nests were included in the experiment.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Parent gender & Manipulation & Number of nests & Number of
chicks\tabularnewline
\midrule
\endhead
Female & Young to young & 10 & 12\tabularnewline
& Old to old & 10 & 18\tabularnewline
& Young to old & 10 & 26\tabularnewline
& Old to young & 10 & 16\tabularnewline
Male & Young to young & 8 & 14\tabularnewline
& Old to old & 12 & 18\tabularnewline
& Young to old & 11 & 24\tabularnewline
& Old to young & 9 & 16\tabularnewline
\bottomrule
\end{longtable}

Table 2. Repeated measures mixed model of telomere length dynamics
(separate models for mother and father age groups). Final models without
non-significant interactions are presented in supplementary materials
(Table S2).\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\emph{Predictor} & \emph{Estimates} & \emph{CI} & \emph{p} &
\emph{Estimates} & \emph{CI} & \emph{p}\tabularnewline
\midrule
\endhead
second - first measurement & 0.11 & 0.02~--~0.20 & \textbf{0.025} & 0.09
& -0.01~--~0.18 & 0.070\tabularnewline
mother age group & 0.04 & -0.09~--~0.17 & 0.547 & & &\tabularnewline
foster mother age group & 0.12 & -0.02~--~0.25 & 0.092 & &
&\tabularnewline
time * mother age group & -0.03 & -0.14~--~0.08 & 0.597 & &
&\tabularnewline
time * foster mother age group & -0.03 & -0.14~--~0.08 & 0.552 & &
&\tabularnewline
father age group & & & & 0.09 & -0.04~--~0.22 & 0.168\tabularnewline
foster father age group & & & & 0.09 & -0.04~--~0.21 &
0.194\tabularnewline
time * father age group & & & & -0.02 & -0.12~--~0.09 &
0.738\tabularnewline
time * foster father age group & & & & 0.01 & -0.10~--~0.11 &
0.900\tabularnewline
\textbf{Random Effects} & \textbf{Random Effects} & \textbf{Random
Effects} & \textbf{Random Effects} & \textbf{Random Effects} &
\textbf{Random Effects} & \textbf{Random Effects}\tabularnewline
\selectlanguage{greek}σ\selectlanguage{english}\textsuperscript{2} & 0.03 & 0.03 & 0.03 & 0.03 & 0.03 &
0.03\tabularnewline
\selectlanguage{greek}τ\selectlanguage{english}\textsubscript{00} & 0.02~\textsubscript{chick\_ID:parent\_nest} &
0.02~\textsubscript{chick\_ID:parent\_nest} &
0.02~\textsubscript{chick\_ID:parent\_nest} &
0.02~\textsubscript{chick\_ID:parent\_nest} &
0.02~\textsubscript{chick\_ID:parent\_nest} &
0.02~\textsubscript{chick\_ID:parent\_nest}\tabularnewline
& 0.02~\textsubscript{parent\_nest} & 0.02~\textsubscript{parent\_nest}
& 0.02~\textsubscript{parent\_nest} & 0.01~\textsubscript{parent\_nest}
& 0.01~\textsubscript{parent\_nest} &
0.01~\textsubscript{parent\_nest}\tabularnewline
ICC & 0.58 & 0.58 & 0.58 & 0.57 & 0.57 & 0.57\tabularnewline
N & 72~\textsubscript{chick\_ID} & 72~\textsubscript{chick\_ID} &
72~\textsubscript{chick\_ID} & 72~\textsubscript{chick\_ID} &
72~\textsubscript{chick\_ID} &
72~\textsubscript{chick\_ID}\tabularnewline
& 40~\textsubscript{parent\_nest} & 40~\textsubscript{parent\_nest} &
40~\textsubscript{parent\_nest} & 40~\textsubscript{parent\_nest} &
40~\textsubscript{parent\_nest} &
40~\textsubscript{parent\_nest}\tabularnewline
Observations & 144 & 144 & 144 & 144 & 144 & 144\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{greek}σ\selectlanguage{english}2 - within-group (residual) variance, \selectlanguage{greek}τ\selectlanguage{english}00 - between-group-variance, ICC
- intraclass-correlation (variance partition coefficient).

Table 3. Markov Chain Monte Carlo (MCMC) multivariate generalised linear
mixed models of parental age (hatch year) effects on telomere length and
telomere length dynamics.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& Mother's hatch year & Foster mother's hatch year & Random effect
(parent nest) & Father's hatch year & Foster father's hatch year &
Random effect (parent nest)\tabularnewline
\midrule
\endhead
\textbf{Telomere length at hatching} & \textbf{Telomere length at
hatching} & \textbf{Telomere length at hatching} & \textbf{Telomere
length at hatching} & \textbf{Telomere length at hatching} &
\textbf{Telomere length at hatching} & \textbf{Telomere length at
hatching}\tabularnewline
Mean (95\% CI) & 0.004 (-0.005-0.012) & 0.007 (-0.001-0.015) & 0.016
(0.003-0.032) & 0.006 (-0.003-0.015 & 0.006 (-0.004-0.016) & 0.016
(0.003-0.032)\tabularnewline
pMCMC & 0.41 & 0.10 & & 0.23 & 0.25 &\tabularnewline
\textbf{Telomere length at second trapping} & \textbf{Telomere length at
second trapping} & \textbf{Telomere length at second trapping} &
\textbf{Telomere length at second trapping} & \textbf{Telomere length at
second trapping} & \textbf{Telomere length at second trapping} &
\textbf{Telomere length at second trapping}\tabularnewline
Mean (95\% CI) & 0.001 (-0.010-0.014) & 0.003 (-0.007-0.014) & 0.021
(0.004-0.043) & 0.009 (-0.002-0.020) & 0.009 (-0.003-0.020) & 0.019
(0.004-0.039)\tabularnewline
pMCMC & 0.85 & 0.56 & & 0.11 & 0.16 &\tabularnewline
\textbf{Change of telomere length} & \textbf{Change of telomere length}
& \textbf{Change of telomere length} & \textbf{Change of telomere
length} & \textbf{Change of telomere length} & \textbf{Change of
telomere length} & \textbf{Change of telomere length}\tabularnewline
Mean (95\% CI) & -0.003 (-0.013-0.006) & -0.005 (-0.014-0.005) & 0.011
(0.002-0.023) & -0.031 (-0.174-0.103) & 0.001 (-0.01-0.012) & 0.011
(0.002-0.023)\tabularnewline
pMCMC & 0.50 & 0.33 & & 0.65 & 0.093 &\tabularnewline
\bottomrule
\end{longtable}

CI-confidence interval.

Table 4. Overview of studies in non-human vertebrates (excluding also
laboratory rodents) investigating the effect of parental age on
offspring telomere length. For a review on human studies, please see
Froy et al. \textsuperscript{28}. Extended version of the table
including study design and offspring developmental stage available in
Supplementary Materials (Table S10).\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Class}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Species}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Sample size}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Studied parental effects}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Telomere method}\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
\textbf{Parental age effect (- / +)}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Teleost fish\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Atlantic salmon (\emph{Salmo salar})\textsuperscript{67}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
84 HSF\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Complex P\textsubscript{fry} (+)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Atlantic salmon (\emph{Salmo salar})\textsuperscript{68}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
60 HSF\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Complex P\textsubscript{fry} (-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reptiles\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Sand lizard (\emph{Lacerta agilis})\textsuperscript{12}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
N\textsubscript{sons}=12\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
P\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
TRF (TL in bp)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
P\textsubscript{sons}(-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Birds\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Great reed warbler (\emph{Acrocephalus
arundinaceus})\textsubscript{18}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=139 N\textsubscript{broods}=46\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M (+)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
European shag (\emph{Phalacrocorax
aristotelis})\textsuperscript{27}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=311 N\textsubscript{broods}=134\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL) and \selectlanguage{greek}Δ\selectlanguage{english}RTL\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \selectlanguage{greek}\textsubscript{ΔRTLoffspring}\selectlanguage{english} (-) P \selectlanguage{greek}\textsubscript{ΔRTLoffspring}\selectlanguage{english}
(-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Alpine swift (\emph{Apus melba})\textsuperscript{13}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=95 N\textsubscript{broods}=54\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P biological and foster\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
P\textsubscript{biological} (-) M\textsubscript{foster} (-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Zebra finch (\emph{Taeniopygia guttata})\textsuperscript{42}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=139 N\textsubscript{HSbroods}=64\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
P (-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
~Black-browed albatross (\emph{Thalassarche
melanophrys})\textsuperscript{69}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
N\textsubscript{ind}=51\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Mean M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
TRF (TL in bp)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Par (+)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Common tern (\emph{Sterna hirundo})\textsuperscript{70}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
N=142\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
TRF (TL in bp)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
P (-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Jackdaw (\emph{Corvus monedula})\textsuperscript{10}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=715 N\textsubscript{nests}=298
N\textsubscript{ind}=61 N\textsubscript{nests}=31\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P biological and foster\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
TRF (TL in bp)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
P\textsubscript{biol} (-)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Common gull (\emph{Larus canus})\textsuperscript{Curr. study}\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
N\textsubscript{ind}=72 N\textsubscript{nests}=40\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
qPCR (RTL and \selectlanguage{greek}Δ\selectlanguage{english}RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
No effect\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Mammals\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Soay sheep (\emph{Ovis aries})\textsuperscript{28}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
N\textsubscript{ind}=318\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
M \& P\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
No effect\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Chimpanzee (\emph{Pan troglodytes})\textsuperscript{71}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
N\textsubscript{ind}=40\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
P\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
qPCR (RTL)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
P (+)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Abbreviations: TL - telomere length, RTL - relative telomere length, TRF
- terminal restriction fragment, HSF - half sib families, ind -
individuals, P - paternal age effect, M - maternal age effect, Par -
parental age effect, (-) negative association, (+) positive association

Figure 1. Parents' and foster parents' age group did not affect
offspring telomere length (A-B) and telomere dynamics (C-F). Mother's
and father's age groups coincided for most, but not all chicks. Columns
denote group means, whiskers are standard errors.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 2. Telomere length was individually repeatable between first
(avg. 0.61 days after hatching) and second blood sampling (avg. 10.62
days after hatching). X=Y line is depicted to illustrate the direction
of individual increase of telomere length.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 3. Relative telomere length dynamics between the first and second
sampling (average time difference 10.62 days) were not related to chick
growth rate (change of head size). Since head size and telomere length
were measured at the same time points for individual birds, time is not
included as a factor here.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure1/Figure1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure2/Figure2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure3/Figure3}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

