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\begin{document}

\title{Sex-specific effects of inbreeding in juvenile brown trout}



\author[1]{Jonas Bylemans}%
\author[1]{Lucas Marques da Cunha}%
\author[1]{Sonia Sarmiento Cabello}%
\author[1]{David Nusbaumer}%
\author[1]{Anshu Uppal}%
\author[1]{Claus Wedekind}%
\affil[1]{University of Lausanne}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Inbreeding depression, i.e., the reduction of health and vigour in
individuals with high inbreeding coefficients, is expected to increase
with environmental, social, or physiological stress. Differences in the
strength of sexual selection are therefore predicted to usually lead to
higher inbreeding depression in males than in females. However,
sex-specific differences in life history may reverse that pattern during
certain developmental stages. In salmonids, for example, female
juveniles start developing their gonads earlier than males who instead
grow faster during that time. We tested whether the sexes are
differently affected by inbreeding during that time. To study the
effects of inbreeding coefficients that may be typical for natural
populations of brown trout (Salmo trutta), and also to control for
potentially confounding maternal or paternal effects, we sampled males
and females from the wild, used their gametes in a block-wise breeding
design to produce 60 full-sib families, released the offspring as
yolk-sac larvae into the wild, caught them back 6 months later,
identified their genetic sex, and used microsatellites to assign them to
their parents. We calculated the average inbreeding coefficient per
family based on a panel of \textgreater{}1 million SNPs. Juvenile growth
could be predicted from these inbreeding coefficients and the genetic
sex: Females grew slower with increasing inbreeding coefficient, while
no such link could be found in males. This sex-specific inbreeding
depression led to the overall pattern that females grew on average
slower than males during the time of gonad formation.%
\end{abstract}%



\sloppy


\textbf{Sex-specific effects of inbreeding in juvenile brown trout}

Jonas Bylemans\textsuperscript{1,2\#}, Lucas Marques da
Cunha\textsuperscript{1\#}, Sonia Sarmiento Cabello\textsuperscript{1},
David Nusbaumer\textsuperscript{1}, Anshu Uppal\textsuperscript{1},
Claus Wedekind\textsuperscript{1*}

\# Shared first authors

* Corresponding author; claus.wedekind@unil.ch

\textsuperscript{1} Department of Ecology and Evolution, Biophore,
University of Lausanne, 1015, Lausanne, Switzerland

\textsuperscript{2} University of Savoie Mont Blanc, INRAE, CARRTEL,
74200 Thonon-les-Bains, France

\textbf{Abstract}

Inbreeding depression, i.e., the reduction of health and vigour in
individuals with high inbreeding coefficients, is expected to increase
with environmental, social, or physiological stress. Differences in the
strength of sexual selection are therefore predicted to usually lead to
higher inbreeding depression in males than in females. However,
sex-specific differences in life history may reverse that pattern during
certain developmental stages. In salmonids, for example, female
juveniles start developing their gonads earlier than males who instead
grow faster during that time. We tested whether the sexes are
differently affected by inbreeding during that time. To study the
effects of inbreeding coefficients that may be typical for natural
populations of brown trout (Salmo trutta), and also to control for
potentially confounding maternal or paternal effects, we sampled males
and females from the wild, used their gametes in a block-wise breeding
design to produce 60 full-sib families, released the offspring as
yolk-sac larvae into the wild, caught them back 6 months later,
identified their genetic sex, and used microsatellites to assign them to
their parents. We calculated the average inbreeding coefficient per
family based on a panel of \textgreater{}1 million SNPs. Juvenile growth
could be predicted from these inbreeding coefficients and the genetic
sex: Females grew slower with increasing inbreeding coefficient, while
no such link could be found in males. This sex-specific inbreeding
depression led to the overall pattern that females grew on average
slower than males during the time of gonad formation.

\textbf{Introduction}

Inbreeding can lead to inbreeding depression, i.e., to a reduction in
health and vigour, because of the expression of deleterious recessive
alleles and a general reduction of heterozygote advantages (Charlesworth
\& Willis 2009). Males and females can be differently affected by
inbreeding, for example because of sex-specific differences in the
strength of sexual selection (Ebel \& Phillips 2016; Vega-Trejo \emph{et
al.} 2022). A general prediction is that males suffer more from
inbreeding than females because the strength of sexual selection is
usually higher for males (Janicke \emph{et al.} 2013; Noel \emph{et
al.}2019). Heterogamety has been discussed as a possible alternative
explanation for sex-specific inbreeding depression, but its relevance is
still unclear (Connallon \emph{et al.} 2022; Vega-Trejo \emph{et
al.}2022). Little is known about other possible reasons for sex-specific
effects of inbreeding such as differences in early life history
(Vega-Trejo \emph{et al.} 2022).

Most salmonid fish reach sexual maturity at the age of 2 or later,
usually with no obvious sexual dimorphism before. However, the sexes
differ in many aspects from very early stages on. Sex-specific gene
expression could be observed in grayling embryos (\emph{Thymallus
thymallus} ) (Maitre \emph{et al.} 2017; Selmoni \emph{et al.} 2019) and
around hatching in rainbow trout (\emph{Onchorhynchus mykiss} )
(Guiguen\emph{et al.} 2019). Embryos can even show sex-specific stress
tolerance (Moran \emph{et al.} 2016; Nusbaumer \emph{et al.} 2021). Sex
differences could also be found during the early juvenile stages, i.e.,
within the first few months when gonad formation starts. In grayling,
genetic females start gonad formation earlier than males who instead
grow faster during that time (Maitre \emph{et al.} 2017). These sex
differences peak around the first summer, possibly making female
juveniles more susceptible to heat stress during summer and thereby
explaining the observed link between climate warming and male-biased sex
ratios among adults (Wedekind \emph{et al.} 2013). Analogous sex
differences in the timing of gonad formation could be observed in brown
trout: females start gonad formation earlier than males, and
captive-born males grow larger than captive-born females after their
first months in the wild (Palejowski \emph{et al.} 2022).

Inbreeding in wild populations is often a consequence of adaptive
responses to local conditions, especially in salmonids (Wang \emph{et
al.} 2002). It has been shown to influence early life-history traits
(Kincaid 1976; Naish \emph{et al.} 2013), disease resistance
(Arkush\emph{et al.} 2002), and reproductive traits (Naish \emph{et al.}
2013; Waters \emph{et al.} 2020; Paul \emph{et al.} 2021) in diverse
salmonid species, but other studies did not find significant and
consistent negative effects of inbreeding (Houde \emph{et al.} 2011;
Johnson\emph{et al.} 2015). Inbreeding effects in salmonid species can
be influenced by environmental context (Gallardo \& Neira 2005) or
temporal and regional genomic effects (Paul \emph{et al.} 2021). Not
much is known about sex-specific effects of inbreeding in salmonids, but
a recent meta-analysis on other taxa (mostly insects) highlighted the
potential sex-specific effects of inbreeding and concluded that they may
mostly be due to difference in the strength of sexual selection while
heterogamety seem to play no significant role (Vega-Trejo \emph{et
al.}2022). The role of sex-specific life histories, however, remains
unclear.

Here we focus on juvenile brown trout around a time when the sexes
differ in gonad formation and the physiological stress that may be
associated to this, i.e., around the end of their first summer. To study
ecologically relevant inbreeding coefficients while experimentally
controlling for potentially confounding maternal and paternal effects,
we sampled adult males and females from the wild and use their gametes
for \emph{in vitro} fertilizations in full-factorial breeding blocks.
The resulting 60 full-sib families differed in their mean inbreeding
coefficients that were, however, mostly low as expected for the study
population. We released the larvae into the wild and sampled them 6
months later. Here we (i) compare these captive bred juveniles that had
been stocked into the wild with the wild-born of the same cohort, and
(ii) test whether there are sex-specific effects of inbreeding on
fitness-relevant traits.

\textbf{Methods}

Adult brown trout were caught from the \emph{Rotache} stream (a rather
pristine tributary of the Aare river, Marques da Cunha \emph{et
al.}2019) shortly before the spawning season. The eggs of 12 females
were stripped and fertilized with milt of 10 males in two full-factorial
breeding blocks (6 x 5 each) to produce in total 60 full-sib families as
described in Wilkins et al. (2017). Fin clips were stored in 70 \%
ethanol at -20 \selectlanguage{ngerman}°C.

After egg hardening and sampling eggs for parallel laboratory studies on
embryo stress tolerance (Wilkins \emph{et al.} 2017; Marques da
Cunha\emph{et al.} 2018), a total of 1,925 eggs (mean±SD number per
full-sib family = 32.1±14.8) were incubated under routine hatchery
conditions at the cantonal \emph{Fischereistützpunkt Reutigen} at
constant temperature of 8.5°C and stocked into the \emph{Mühlibach}
streamlet (a tributary to the \emph{Rotache} ; 46.804459°N, 7.690544°E)
at a late yolk-sac stage in early March.

About 6 months after release into the wild (i.e., in late August),
electrofishing was used along the \emph{Mühlibach} streamlet to catch as
many brown trout as possible (N\textsubscript{total} = 518). The fish
were narcoticized (0.075 g/L tricaine methanoesulfonate buffered with
0.15 g/L NaHCO3) and photographed on a weighting scale to later extract
fork length and body weight. Fin clips were collected and stored in 70
\% ethanol. After handling, all fish were returned to the wild.

Fin clips of adult breeders and a random subset of juveniles from the
wild (N = 376) were used for microsatellite genotyping and genetic
sexing. DNA was extracted using the BioSprint\textsuperscript{®} 96
workstation following the manufacturer's protocol (Qiagen GmbH, Hilden,
Germany). DNA was quantified using a HS dsDNA assay on a
Qubit\textsuperscript{®} 2.0 Fluorometer (Life Technologies, Carlsbad,
CA, USA) and concentrations of up to 20 ng/\selectlanguage{greek}µ\selectlanguage{english}L were sent
to\emph{Ecogenics GmbH} (Balgach, Switzerland) for genotyping at 13
microsatellite loci and genetic sex determination using the protocol
described in Palejowski et al. (2022). Parental assignment of the
juveniles was based on the full-likelihood approach implemented in
Colony v2.0.6.5 (Jones and Wang, 2010) with a threshold of 0.98.

For all but two breeders (one dam and one sire) high quality DNA
extracts or tissue samples could be used for whole genome resequencing
to calculate the kinship coefficients for each breeding pair. Samples
were sent to the NGS Platform at the University of Bern (Switzerland)
for library construction using the Illumina TruSeq DNA PCR-Free Library
Prep Kit (Illumina Inc., San Diego, CA, USA) after mechanical shearing
of the DNA. Electrophoresis bases size selection (150bp fragments) was
used prior to library quantification, quality control and paired-end
sequencing using a NovaSeq 6000 S4 flow cell (Illumina Inc., San Diego,
CA, USA). Adult samples from the current study were combined with
samples from a parallel study to achieve an estimated coverage of 15x.
The quality of raw sequence reads was assessed using FastQC v0.11.9
(Andrews 2010). Trimmomatic v0.39 (Bolger \emph{et al.} 2014) was
subsequently used to remove adaptor sequences and remove low-quality
reads (i.e. HEADCROP:6 LEADING:3 TRAILING:3 MINLEN:70 CROP:140).
High-quality reads were aligned to the indexed reference genome of brown
trout (Hansen \emph{et al.} 2021) with BWA v0.7.17 (Li, 2013) and the
obtained BAM files were further processed using Samtools v1.12
(Li\emph{et al.} 2009) and Picard version 2.24.0 (``Picard Tools - By
Broad Institute,'' n.d.). BAM files were cleaned by soft-clipping
beyond-end-of reference alignment and setting MAPQ to 0 for unmapped
reads, alignments were sorted by leftmost coordinates, mate coordinates
were filled and duplicated alignments were marked. The resulting clean,
coordinate-sorted BAM files were indexed and ordered along the reference
genome and variants were called using the HaplotypeCaller function of
GATK v4.2.0.0 (McKenna \emph{et al.} 2010). Variants were subsequently
hard filtered according to GATK best practices recommendations (i.e.
QD\textless{}2.0, QUAL\textless{}30, SOR\textgreater{}3.0,
FS\textgreater{}60.0, MQ\textless{}40.0, MQRankSum\textless{}-12.5,
ReadPosRankSum\textless{}-8.0) (Depristo et al., 2011; Van der Auwera \&
O'Connor, 2020). Further filtering was performed to remove indels and
SNPs with a sequencing depth \textless{}10 and \textgreater{}30, a minor
allele frequency \textless{}0.01, outside of Hardy-Weinberg equilibrium
(p\textless{}10\textsuperscript{-8}) and showing signs of strong linkage
disequilibrium (r2 \textgreater{} 0.6). Only SNPs present in at least
90\% of individuals were retained and the R package Hierfstat (Goudet
2005) was used to obtain marker-based estimates of kinship between all
parental breeding pairs using a panel of 1,058,625 SNPs (Goudet \emph{et
al.} 2018).

Statistical analyses were done in JMP Pro17 and R 4.0.2 (R Development
Core Team 2015). The Akaike information criterion (AIC) were used to
describe the fit of different distribution models on juvenile sizes.
Standard F-tests were used to compare means when visual examination of
the distributions suggested similar variances. Welch's F tests were used
when this model assumption seemed violated. Likelihood ratio tests were
used to compare frequencies. Linear mixed-effect models were used to
evaluate the combined effects of sex and kinship on growth indicators.
Non-parametric Spearman correlation coefficients r\textsubscript{s} were
used to test for correlations between parental inbreeding coefficients,
kinship coefficients, and family sex ratios.

\textbf{3. Results}

Figure 1a shows the bimodal size distribution of the 518 juveniles that
could be caught from the wild. As expected, the random sample of 375
juveniles that was genotyped for parental assignment did not
significantly differ in body lengths from the non-genotyped fish
(Welch's F = 1.7, p = 0.19). In total 301 (80.3\%) of these 375
wild-caught juveniles could be assigned to 56 of the 60 experimental sib
groups. Their average (\selectlanguage{ngerman}± SD) body lengths and weights were 95.6 ± 10.6
mm and 11.3 ± 3.9 g, respectively, and were always below the 125 mm that
the Bayesian mixture model had identified as upper size for 0+ fish
(Fig. 1b). All but one of them could be genetically sexed. The overall
male ratio was 48.3\% and not significantly biased (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}
= 0.33, p = 0.56).

The Bayesian model identified 57 of the remaining 74 genotyped fish as
wild-born 0+ juveniles and the larger ones as 1+ or older (Fig. 1b). The
wild-born 0+ were on average 17.6 mm smaller than the experimentally
bred 0+ (Fig. 1b; F = 122.5, p \textless{} 0.001). Among the
experimentally bred 0+, males were on average 2.6 mm larger than females
(F = 4.4, p = 0.03; Fig. 1b). Among the wild-born 0+, males were on
average 3.0 mm larger than females, which was in this smaller sample not
statistically significant (F = 1.6, p = 0.21). However, the wild-born 0+
had a male-based sex ratio (63.2\% males) that was not observed in the
experimentally bred 0+ (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} = 4.3, p = 0.04; Fig. 1c).

We obtained 47 kinship coefficients (mean \selectlanguage{ngerman}± SD = -0.0003 ± 0.04). One
full-sib family with a kinship coefficient of 0.226 was classified as
outlier (because »3 SDs away from the mean, following the three-sigma
rule) and excluded from all further analyses, leaving 251 genetically
sexed juveniles of 46 full-sib families for the final analyses. The
kinship coefficients of these sib groups could partly be predicted by
the parental inbreeding coefficients: Higher parental inbreeding
coefficients led to higher average kinship coefficients among their
offspring (r\textsubscript{s} = 0.61, n = 20, p = 0.004; Supplementary
Figure S1).

The body sizes of female juveniles declined with increased kinship
coefficients, while the body sizes of male juveniles did not seem to be
affected (Figure 2; Table 1; Supplementary Figure S2; Supplementary
Table S1). Juvenile body size also varied among maternal but not
paternal sib groups (Table 1).

The recapture rates per full-sib family, i.e., the mean number of
recovered juveniles per number of released larvae, varied between 0.0
and 0.68 and were not correlated with the kinship coefficients
(r\textsubscript{s} = 0.13, n= 48, p = 0.38) nor with the inbreeding
coefficients of the dams (r\textsubscript{s} = 0.39, n= 11, p = 0.23) or
the sires (r\textsubscript{s} = 0.05, n= 9, p = 0.90).

The number of recovered juveniles per experimental sib group that was
represented in our sample varied from 1 to 17 (mean = 5.3, SD = 3.1),
i.e., sex ratios per individual family could mostly not be determined
due to low N. However, the number of recovered juveniles per dam varied
from 5 and 52 (mean = 24.3, SD = 10.6). Family sex ratio differed among
the maternal sib groups (\selectlanguage{greek}χ \selectlanguage{english}\textsuperscript{2} = 22.5, d.f. = 11, p =
0.02) but could not be predicted by maternal inbreeding coefficients
(r\textsubscript{s} = -0.19, p = 0.57) nor the average kinship per
maternal sib group (r\textsubscript{s} = 0.30, p = 0.37). The number of
recovered juveniles per sire varied from 17 to 51 (mean = 29.2, SD =
10.6). Family sex ratio did not differ among the paternal sib groups
(\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} = 10.8, d.f. = 9, p = 0.29) and was not correlated
with paternal inbreeding coefficients (r\textsubscript{s} = 0.65, p =
0.06) or average kinship per paternal sib group (r\textsubscript{s} =
0.37, p = 0.33).

\textbf{4. Discussion}

Using molecular markers, we could identify captive-bred juveniles of 56
experimentally produced families and compare them to wild-born juveniles
of the same cohort. The captive-bred 0+ dominated in number (by a factor
5.3), had a significantly more balanced sex ratio, and were on average
larger than wild-born 0+. The reason for these differences remains
unclear but could be linked, for example, to different stress levels
during embryogenesis, the timing of stocking relative to the timing of
emergence of wild-born, or size differences at the time when exogenous
feeding starts. Given these many possible reasons, it may even be a
general rule that captive-bred and wild-born fish of the same cohort
differ in growth and survival because of differences in early life
history (Palejowski \emph{et al.} 2022).

We used a panel of \textgreater{} 1 million SNPs to calculate the
kinship coefficients of 47 parental combinations that resulted from our
experimental breeding. These 47 kinship coefficients (minus one outlier)
may well reflect the average inbreeding coefficient per experimental
full-sib family in a population that does not seem to suffer from
elevated levels of inbreeding, as concluded from measurements of hybrid
vigour that included our study population (Clark \emph{et al.} 2013;
Stelkens \emph{et al.} 2014) in crosses of populations that are
genetically distinct (Stelkens \emph{et al.} 2012). Nevertheless, the
variation in kinship coefficients that we observed could be used to
predict female growth in the wild. Females grew slower with increasing
inbreeding coefficients. No such effects could be observed among males.
We conclude that the susceptibility to inbreeding depression is
sex-specific at this juvenile stage.

We sampled the juveniles about 6 months after release into the wild.
Sexual maturity and first breeding are expected at the end of their
second or third year of life. Therefore, the sex-specific effects of
inbreeding that we observed cannot be explained by the sex-specific
stress that is expected during the mating season. Moreover, because sex
chromosomes of brown trout are largely homomorphic (Guiguen \emph{et
al.} 2019), as is typical for lower vertebrates (Beukeboom \& Perrin
2014), they are not expected to contribute significantly to sex-specific
inbreeding depression (Vega-Trejo \emph{et al.} 2022). The effects we
found here are therefore best explained by sex differences in life
histories. In the case of brown trout, these sex differences are rather
cryptic. Little is known about sex differences in morphometry or
behaviour at such early life-history stages even though the brown trout
is a common and well-studied species. However, recent studies on brown
trout and grayling revealed that the sexes differ in the timing of gonad
development. Females generally develop their gonads earlier than males
while males in turn grow faster than females during that time
(Maitre\emph{et al.} 2017; Palejowski \emph{et al.} 2022). The size
difference that was found before in other populations (Palejowski
\emph{et al.}2022) could be confirmed in the present study but was
overall small (around 3\%). This difference was linked to the variance
in kinship coefficients and may even be caused by the variance in
kinship coefficients because the sex difference in size was not apparent
in families with small inbreeding coefficients. We therefore predict
that increased inbreeding within a population will accentuate the sex
difference in growth.

The overall sex ratio in our re-captured sample was about equal, and
there was no significant effect of inbreeding on recapture rates for the
different families. Based on the rate of experimentally produced fish
among the sampled ones (80.3\%), the total number of fish that could be
sampled, and the number of fertilized eggs that were used for this
study, the overall mortality of the experimentally produced fish over
their first 9 months of their life was 78.4\% or less if some fish had
escaped sampling. Because embryo mortality was low in a parallel study
on the same families (Wilkins \emph{et al.} 2017), the mortality in the
present study reflects the acute stress during stocking and/or the
selection during the fish's first spring and summer in the wild.
Somewhat comparable levels of mortality during these first months have
been observed in nearby populations of brown trout (Palejowski \emph{et
al.} 2022), i.e., the level of selection in our study system seems not
extra-ordinary.

As is typical for studies on wild populations, quantifying likely
effects of emigration remained difficult. In our study system, upstream
emigration was not possible. Downstream emigration into the larger
stream (Rotache) was possible. However, if migration happens in this
species, it typically starts at later developmental stages and is then
often sex-biased, with females being more likely to migrate than males
(Forseth \emph{et al.} 1999; Nevoux \emph{et al.} 2019). The most
parsimonious explanation for the observed overall equal sex ratio in the
captive-born fish, and the non-significant correlations between
recapture rates and inbreeding, is therefore that there was no
sex-specific mortality and no sex-specific emigration, and that
inbreeding depression only affected growth but did not lead to increased
mortality in the hatchery-produce fish. The pattern was different in the
wild-born 0+ who grew smaller than the hatchery-produced 0+ and had a
male-bias sex ratio, suggesting that wild-born females suffered from a
higher mortality than wild-born males during their first spring and
summer. It is possible that a combination of sex-specific inbreeding and
larger hatchery-born competitors led to sex-specific mortality among the
wild-born.

Inbreeding coefficients can show significant heritability in small and
structured populations (Neff \& Pitcher 2008; Nietlisbach \emph{et
al.}2016). This prediction is supported by the significant correlation
that we found between parental inbreeding coefficients and the average
kinship coefficients, i.e., the expected inbreeding coefficients of
their offspring. If parental inbreeding coefficients predict offspring
inbreeding coefficients, and if inbreeding depression during the
spawning season affects intra- and inter-sexual selection (i.e., giving
inbred individuals a selective advantage), natural spawning would be
expected to reduce the average inbreeding coefficient of the next
generation. However, the one extreme kinship coefficient that we
recorded would not be avoid through effects of inbreeding on health and
vigour because the parents of this sib group had average and very
similar inbreeding coefficients, suggesting that they could have been
brother and sister that would not be able to avoid each other without
some form in kin recognition.

Our experimental breeding also allowed to test for general maternal and
paternal effects on juvenile growth. We found significant maternal but
not paternal effects, suggesting that juvenile growth is affected by
maternal environmental effects such as egg size and egg content. The
absence of significant paternal effects is either due to limited
statistical power or suggests that heritability of growth is small when
measured in juveniles recaptured from the wild. Paternal effects on
offspring growth are, however, frequently observed in brown trout larvae
when studied under controlled laboratory conditions, revealing
significant heritability of growth in this species (Marques da
Cunha\emph{et al.} 2019; Nusbaumer \emph{et al.} 2019). The limited
number of recaptured juveniles per each of the 60 full-sib families did
not allow to test for possible effects of dam x sire interactions on
growth.

In conclusion, inbreeding did not significantly affect mortality of
juvenile brown trout that had been stocked into the wild as larvae.
However, female growth during their first spring and summer in the wild
was reduced with increasing inbreeding coefficients. No such effect
could be observed in males who even could grew on average about 3\%
larger than females during that time. Inbreeding depression is hence
sex-specific around the time of gonad formation and long before intra-
or inter-sexual selection are expected to cause sex-specific
(male-biased) inbreeding depression.

\textbf{Data availability statement}

All data used here will be made available upon acceptance of the
manuscript.

\textbf{Author statement}

JB, LMC, and CW designed and supervised the study. LMC, DN, AU \& CW did
the experimental breeding. LMC, DN \& AU sampled the juveniles from the
wild and LMC determined their growth. JB \& LMC were responsible for the
parental assignments and the genetic sexing. JB \& SSC performed
bio-informatic analysis. JB \& CW performed the statistical analyses and
wrote the manuscript. All authors revised and approved the final
manuscript for publication.

\textbf{Declaration of competing interest}

The authors declare that they have no competing financial interests or
personal relationships that could influence the work reported in this
paper.

\textbf{Ethics statement}

The sampling and handling of wild adults, the experimental breeding, the
raising of offspring, the stocking into the wild, and sampling and
handling of juveniles caught from the wild were approved by the fishery
inspectorate and the veterinary office of the Bern canton (permit
BE118/14).

\textbf{Acknowledgements}

We thank T. B\selectlanguage{ngerman}ösch, B. Bracher, U. Gutmann, C. de Guttry, M. Escher, J.
Kast, A. Knutti, C. Küng, E. Longange, E. Pereira-Alvarez, L. Wilkins,
and the members of the \emph{Pachtverein Rotache} for assistance and/or
discussion. The study was funded by the Swiss National Science
Foundation (31003A\_159579 \& 31003A\_182265).

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\textbf{Table 1.} Linear mixed model (REML, unbounded variance
components) on juvenile length and weight when predicted by sex and mean
kinship coefficient per family. Parental identities were included as
random factors. Significant p-values are highlighted in bold.\selectlanguage{english}
\begin{longtable}[]{@{}llllllllll@{}}
\toprule
& & Body length & Body length & Body length & Body length & & Body
weight & Body weight & Body weight\tabularnewline
\midrule
\endhead
Effects & d.f. & F & Variance component & p & & F & F & Variance
component & p\tabularnewline
Fixed effects: & Fixed effects: & & & & & & & &\tabularnewline
Sex & 1 & 5.4 & & \textbf{0.02} & & 9.1 & 9.1 & &
\textbf{0.003}\tabularnewline
Kinship & 1 & 0.3 & & 0.58 & & 0.2 & 0.2 & & 0.66\tabularnewline
Sex x kinship & 1 & 8.3 & & \textbf{0.004} & & 8.8 & 8.8 & &
\textbf{0.003}\tabularnewline
Random effects: & & & & & & & & &\tabularnewline
Dam\textsuperscript{1} & & & 27.3\selectlanguage{ngerman}±14.0 & \textbf{0.05} & & & & 3.6\selectlanguage{ngerman}±1.9 &
\textbf{0.05}\tabularnewline
Sire\textsuperscript{1} & & & 3.1\selectlanguage{ngerman}±3.3 & 0.35 & & & & 0.4\selectlanguage{ngerman}±0.5 &
0.34\tabularnewline
Residual & & & 83.4\selectlanguage{ngerman}±7.7 & & & & & 10.5\selectlanguage{ngerman}±1.0 &\tabularnewline
\bottomrule
\end{longtable}

\textsuperscript{1}REML unbounded variance components \selectlanguage{ngerman}± standard error,
Wald p-values\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} Sizes of trout sampled from the wild. (A) Size
distribution of all trout (N = 518) with the bimodal normal distribution
(green line; AIC = 4278.3) that fit the data better than a normal
distribution (AIC = 4465.1). (B) Sizes of trout that were genetically
sexed and assigned to one of the experimental families or to the
non-experimental ones (blue = male, red = female). The hatched line
indicates the largest size of 0+ fish based on a Bayesian mixture model
(Supplementary Material) and that is supported by the genetic
assignments of known 0+. (C) Sex ratio (\% males) among captive-bred and
wild-born that were identified as 0+. The dotted line indicates the 50\%
male ratio. See text for statistics.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2.} Body length of wild-caught juvenile brown trout in
relation to the kinship coefficient in males (blue dots and regression
line) and females (red). Female but not male size declines with
increased kinship coefficients (Table 1; this is also the case if
kinship coefficients \textgreater{} 0.03 are excluded, see Supplementary
Figure S1 \& Table S1).

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

