# Maternally derived avian corticosterone affects offspring genome-wide DNA methylation in a passerine species

Anna Miltiadous, Damien Callahan, Antoine Dujon, Katherine Buchanan, Lee Rollins

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Anna Miltiadous, Damien Callahan, Antoine Dujon, Katherine Buchanan, Lee Rollins. Maternally derived avian corticosterone affects offspring genome-wide DNA methylation in a passerine species. Molecular Ecology, 2024, 33 (6), pp.e17283. 10.1111/mec.17283. hal-04934988

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# Maternally derived avian corticosterone affects offspring genome-wide DNA methylation in a passerine species

Anna Miltiadous<fnref n="1" /> ID

Damien L. Callahan<fnref n="2" /> ID

Antoine M. Dujon<fnref n="1" />,<fnref n="3" /> ID

Katherine L. Buchanan<fnref n="1" /> ID

Lee A. Rollins<fnref n="1" />,<fnref n="4" /> ID

**Correspondence**

Anna Miltiadous, School of Life and Environmental Sciences, Deakin University, Geelong, VIC, Australia.
Email: a.miltiadous@research.deakin.edu.au

**Funding information**

Centre of Excellence for Environmental Decisions, Australian Research Council, Grant/Award Number: DP130100417 and FT140100101; Australian Research Council (ARC), Discovery Project, Grant/Award Number: DP130100417; Australian Research Council (ARC), Future Fellowship, Grant/Award Number: FT140100101

Handling Editor: David Coltman

**Abstract**

Avian embryos develop in an egg composition which reflects both maternal condition and the recent environment of their mother. In birds, yolk corticosterone (CORT) influences development by impacting pre- and postnatal growth, as well as nestling stress responses and development. One possible mechanism through which maternal CORT may affect offspring development is via changes to offspring DNA methylation. We sought to investigate this, for the first time in birds, by quantifying the impact of manipulations to maternal CORT on offspring DNA methylation. We non-invasively manipulated plasma CORT concentrations of egg-laying female zebra finches (*Taeniopygia castanotis*) with an acute dose of CORT administered around the time of ovulation and collected their eggs. We then assessed DNA methylation in the resulting embryonic tissue and in their associated vitelline membrane blood vessels, during early development (5 days after lay), using two established methods – liquid chromatography-mass spectrometry (LC-MS) and methylation-sensitive amplification fragment length polymorphism (MS-AFLP). LC-MS analysis showed that global DNA methylation was lower in embryos from CORT-treated mothers, compared to control embryos. In contrast, blood vessel DNA from eggs from CORT-treated mothers showed global methylation increases, compared to control samples. There was a higher proportion of global DNA methylation in the embryonic DNA of second clutches, compared to first clutches. Locus-specific analyses using MS-AFLP did not reveal a treatment effect. Our results indicate that an acute elevation of maternal CORT around ovulation impacts DNA methylation patterns in their offspring. This could provide a mechanistic understanding of how a mother's experience can affect her offspring's phenotype.

**KEYWORDS**

epigenetics, glucocorticoid, hormones, maternal effects

<figure><img src="image_2.png" /></figure>

<footnote n="1">¹School of Life and Environmental Sciences, Deakin University, Geelong, Victoria, Australia</footnote>

<footnote n="2">²School of Life and Environmental Sciences, Deakin University, Burwood, Victoria, Australia</footnote>

<footnote n="3">³CREEC/CANECEV (CREES), MIVEGEC, IRD 224-CNRS 5290-Université de Montpellier, Montpellier, France</footnote>

<footnote n="4">⁴Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia</footnote>
# 1 | INTRODUCTION

Organismal phenotype is the product of the genes controlling the development of the organism, in interaction with its environment (Via & Lande, 1985). For a developing embryo, developmental trajectories are influenced by a sequence of regulated changes in gene expression, influenced by factors such as maternal diet (Bazer et al., 2004), maternal investment (Weaver et al., 2004), and embryonic perception of competition or predation in the postnatal environment (Gilbert, 2001; Mommer & Bell, 2014; Ruiz-Raya et al., 2023). Such prenatal phenotypic plasticity can potentially lead to fundamental shifts in postnatal development and behaviour, which in some cases may allow adaptive responses to the adult environment (Mariette & Buchanan, 2016; Noguera & Velando, 2019). However, despite increasing interest in the causes of prenatal plasticity, the mechanisms underlying phenotypic plasticity (Berghänel et al., 2017; Mousseau & Fox, 1998), both intra- and interspecifically (Groothuis et al., 2005), are still largely unclear.

One of the mechanisms that may underlie maternal alteration of offspring phenotype is via changes to the offspring epigenome. Epigenetic alterations are sometimes heritable and can affect the expression of genes, without altering the organism's underlying DNA sequence (Richards, 2006). There are a range of known epigenetic processes, including histone modifications and DNA methylation, which are sometimes associated with changes in gene expression (Bird, 2007). One of the most common, and most commonly studied, types of DNA methylation in animals involves the methylation of cytosines that are followed by guanine (CpG). CpG islands (regions of DNA rich in CpGs) are often found in gene promoter regions, and increases in DNA methylation in these regions are generally associated with decreased gene expression (Jones, 2012). Additionally, the associations between DNA methylation and gene expression are shown to be context-dependent with respect to developmental timing and can impact offspring developmental trajectories, with effects continuing into adulthood (Weaver et al., 2004, 2006).

An offspring's epigenome can be maternally and paternally influenced (separately or in interaction with one another); these effects may be intergenerational, affecting the immediate offspring, or transgenerational, affecting multiple subsequent generations (Youngson & Whitelaw, 2008). Yet, the mammalian model shows that dynamic changes in the patterns of gametic DNA methylation occur during embryonic development, including the removal (demethylation) of most parentally inherited DNA methylation patterns in the zygote, to allow for effective transcription and embryonic development (Zeng & Chen, 2019). While different taxa handle epigenetic reprogramming differently (Feng et al., 2010), currently little is known about demethylation events during avian embryonic development. Evidence suggests that embryonic DNA methylation reprogramming is likely similar to mammals, with evidence of two developmental periods during which epigenetic

changes, including demethylation of DNA, occur (Guerrero-Bosagna et al., 2018). Subsequent to the occurrence of epigenetic reprogramming necessary for development, DNA methylation patterns specific to the embryo are then established, and these patterns may be influenced by the developmental environment and/or include parental DNA methylation patterns that were not removed during reprogramming (Szyf, 2013). Additionally, DNA methylation patterns are tissue-specific (Herzog et al., 2021; Liang et al., 2011) and may be dependent on the developmental stage of the offspring at the time of sampling (Sun et al., 2021). Although DNA demethylation is clearly important for embryonic development, the intergenerational persistence of environmentally induced DNA methylation patterns provides a mechanistic pathway through which a mother's experience could affect her offspring's phenotype (e.g., Sarma et al., 2021). However, evidence for this phenomenon remains scarce in animals.

The factors influencing DNA methylation patterns are still emerging, but there is evidence in mammals that maternal plasma glucocorticoids (GCs) may impact offspring DNA methylation (Szyf, 2013). GCs are produced in the adrenal gland and are upregulated in response to stress (Romero, 2004; Sapolsky et al., 2000) via the hypothalamus-pituitary-adrenal (HPA) axis (Ahmed et al., 2014), mediating the physiological mechanisms that are imperative for maintaining homeostasis (Sapolsky et al., 2000). GCs are central to the vertebrate response to stressful experiences in the natural world, including mobilization of energy reserves and determining the physiological and behavioural response to acute and chronically stressful events (Romero & Wingfield, 2016). Embryos are exposed to maternal GCs through the maternal bloodstream, which remain relevant to mammalian embryos throughout pregnancy (Edwards & Boonstra, 2018), but for birds maternal GC (corticosterone; CORT) transfer to the egg occurs pre-laying (Almasi et al., 2012; Hayward & Wingfield, 2004; Miltiadous & Buchanan, 2021). Oviparous species, therefore, offer an excellent opportunity to address how prenatal exposure to maternal GCs influences development and the potential underlying mechanisms. In rats, elevated concentrations of maternal CORT drive epigenetic programming of HPA axis responsiveness in their offspring, leading to increased anxiety and reduced social play in juveniles and adults (Morley-Fletcher et al., 2003). A small number of studies in birds have shown that embryonic exposure to elevated maternal CORT influences postnatal HPA response, via modulation of the HPA axis (Love et al., 2013; Zimmer et al., 2017) and may heighten hatchling aggression (Ahmed et al., 2014) increasing individual competitiveness and, therefore, survival. However, while these limited examples of the intergenerational consequences of elevated maternally derived CORT demonstrate the potential for maternal state to exert long-term impacts on offspring phenotype, they do not address how elevated CORT may impact the epigenome of avian offspring.

Evidence from studies on mammals suggest that maternal GCs are likely to alter offspring phenotype (McGowan &
Matthews, 2018; Seckl, 2001) and, despite the potential that this may be mediated through changes to DNA methylation (Constantinof et al., 2019; Szyf et al., 2005), this remains largely untested in birds. This mechanistic pathway is entirely plausible; there is evidence that avian offspring DNA methylation changes can occur in response to environmental and maternal effects. Studies using chickens, a model species for the study of epigenetic effects in birds, have focused on environmental factors, including temperature and nutrition (Bednarczyk et al., 2021). This trend is also reflected in studies on passerine species, which have focused on DNA methylation effects in terms of the factors affecting the postnatal environment, such as urbanization (Watson et al., 2021), phenology (Saino et al., 2019), and brood size (Jimeno et al., 2019; Sepers et al., 2021), with some focus on intergenerational influences (Saino et al., 2019; Sheldon, Schrey, Andrew, et al., 2018). In an earlier study (Miltiadous & Buchanan, 2021) in zebra finches (Taeniopygia castanotis), we have shown that an acute dose of maternal CORT is transferred to the egg yolk deposited after ovulation, altering the developmental environment of the embryo. Using the same remote, maternal oral-dosing protocol in the current study, we sought to test whether maternal plasma CORT manipulation affected DNA methylation in offspring as a first step towards understanding the mechanisms through which a mother's experience might impact her offspring.

We used two approaches to quantify offspring DNA methylation: (1) liquid chromatography-mass spectrometry (LC-MS; Song et al., 2005) and (2) methylation-sensitive amplification fragment length polymorphism (MS-AFLP; Pérez-Figueroa, 2013). LC-MS characterizes global levels of cytosine methylation, but does not provide locus-specific information. Conversely, MS-AFLP does detect locus-specific changes to cytosine methylation, but only a small portion of the genome is assayed, and the loci are anonymous. Locus-specific changes to DNA methylation may be detected using MS-AFLP that are undetectable with LC-MS, because any effects identified using the latter would be diluted by the many loci across the genome showing no effect. However, because MS-AFLP only surveys a small portion of the genome, LC-MS should indicate more broadly whether global changes to DNA methylation are occurring in response to our manipulations, even if these effects were not detected in the loci captured by MS-AFLP. Although there are genome-wide locus-specific methods available (e.g., Whole-Genome Bisulfite Sequencing), such methods are costly and computationally intensive. We chose to use both LC-MS and MS-AFLP because they provide different types of information (gross changes versus specific changes), yet both are relatively rapid and inexpensive approaches to detect changes in DNA methylation, appropriate for an initial investigation into whether our maternal manipulation impacted offspring DNA methylation. For both techniques, we predicted a change in offspring methylation, but we had no a priori expectations about the direction of this change, which may differ depending on the location of a cytosine in the genome (e.g., Sarma et al., 2020).

## 2 | METHODS

### 2.1 | Animals and housing

At Deakin University, Geelong, Australia, we moved domesticated zebra finches (N=24 male and N=24 female) from an external aviary-held population to a single indoor room and housed in cages measuring 100×65×65 cm. Birds were sourced from various local breeders - genetic relatedness between individuals was not known. We kept the birds in same sex groups of four individuals for 2 weeks, to acclimatize to the 14:10 light-dark, 21°C conditions. We assigned individuals to pairs based on observation of free-choice pairing behaviours and transferred pairs to individual cages. We monitored the birds daily, and they were fed mixed seed (Golden Cob™ canary mix), ad libitum, supplemented daily with cucumber and egg. Each pair was supplied fresh drinking water, as well as water for bathing, nest boxes, and nesting material (straw bedding, shredding paper, and sterile chicken feathers). We weighed all birds at the time of pairing, and after all reproduction concluded.

We conducted our experiments with approval of the Deakin University Animal Ethics Committee (Project Reference Number: G16-2015), under the guidelines of the Australian Code for the care and use of animals for scientific purposes, 8th edition, 2013 (National Health and Medical Research Council).

### 2.2 | Corticosterone dosing

In order to test the impact of elevated maternal CORT on embryonic DNA methylation, we ran a balanced reverse-order repeated measured design, under which females were exposed to either an acute elevation of CORT or the control vehicle alone. We randomly selected a subset of N=12 females for the treatment group, and N=12 females for the control group. As per Miltiadous and Buchanan (2021), we non-invasively increased maternal plasma CORT concentrations daily, from pairing until clutch completion, by presenting 500 mg of seed, sprinkled with 50 µL peanut oil alone (control) or 0.0125 mg CORT dissolved in peanut oil (treatment). Our previous work has established that this dose, administered with this method, causes a biologically relevant rise in circulating CORT levels, which peaks at around 20 min after ingestion, whilst circulating levels return to baseline levels approximately an hour after ingestion (Miltiadous & Buchanan, 2021). This dose was therefore designed and administered to simulate an acutely stressful event, such as predatory encounter, at around the time of ovulation. During this feeding time, we separated the females from their mates by a grill partition to ensure individual dosing. We provided males with identical bowls and seeds at the same time to encourage their mate's interest in feeding. All individuals were food deprived from 3 h before lights off on the day before dosing, and the seed was presented within 1 h of lights on the following day. Feed bowls were collected after 5 min from presentation, and
it was observed that females ate all seeds within this time frame. In our pilot study, neither maternal mass nor any measures of reproductive output were found to be affected by this experimental dosing regimen (Miltiadous & Buchanan, 2021).

## 2.3 | Egg collection and processing

We supplied the pairs with nest boxes and nesting material on the day of pairing. The day nest construction commenced was recorded as nest initiation date. We collected eggs (N=176, from 22 pairs and 44 clutches) on the day of lay (replaced with a dummy egg) and placed them in an incubator (Octagon 20 Advance EX Incubator; Brinsea, Florida, USA) maintained at 37.5°C, 65% humidity. Eggs were incubated for 5 days development from day of lay, and then frozen at -20°C. The number of days between nest construction was commenced and the first egg was laid was recorded as lay latency (a measure of reproductive onset) for that clutch. Two days after clutch completion, we removed the dummy eggs, nest, nesting material, and nest box from the cage. Females were rested for a period of 2 weeks, before we returned the nesting material and nesting boxes to the pairs. Females were then subjected to the alternate treatment to their first clutch and allowed to produce a second clutch with the same mate from their first breeding bout. We weighed all the birds for a second time after the completion of their second clutch. Two pairs failed to produce any clutches of two eggs or more and were excluded from the study. As such, 22 pairs were included in the study and subjected to the treatments in a balanced, randomized order.

After initial defrosting, we dissected embryos and vitelline blood vessels from the frozen egg (Figure 1), carefully separated from both the albumen and yolk, and placed each tissue type into separate tubes containing 300 µL Cell Lysis Solution (Gentra Puregene Tissue Kit; QIAGEN). Samples were refrigerated at 4°C

until further processing. n=24 eggs were infertile (neither embryonic nor vitelline blood vessel development could be visually detected; control: n=10, treatment: n=13, damaged in incubator, treatment: n=1) and were, therefore, excluded from further analysis.

## 2.4 | DNA extraction

We purified DNA from the samples using the Gentra Puregene Tissue Kit (QIAGEN), following manufacturer's instructions. All DNA extracts were stored at 4°C until further processing. DNA concentrations were determined using a Qubit Fluorometer 3.0 and a Qubit dsDNA BR Assay Kit according to manufacturer instructions (Thermo Fisher Scientific).

Samples that provided a lower than detectable concentration of DNA were excluded from further analysis, resulting in a final sample size of N=129 embryos (control: n=68, from 20 clutches/pairs; treatment: n=61, from 18 clutches/pairs) and N=136 vitelline blood vessels (control: n=73, treatment: n=63). All 129 embryos had a corresponding vitelline blood vessel sample.

## 2.5 | Liquid chromatography-mass spectrometry

We hydrolyzed DNA samples and conducted LC-MS according to the protocol cited by Song et al. (2005) derived from Crain (1990), with some modifications to the LC-MS procedure as stated below.

Hydrolyzed DNA was prepared to a final concentration of 0.5 ng/µL and produced a calibration standard matrix with dG, 5mdC+dC, dA and T at equal concentrations of 10, 2, 1, 0.2, 0.1, 0.02, and 0.01 pmol, at eight different [5mdC]/[dG] ratios of 10, 5, 2.5, 1, 0.5, 1.25, 0.1, and 0.05%. Standards and samples were injected at 1µL volumes. All samples and standards were measured in the same run

<figure><img src="image_3.png" /><figcaption>FIGURE 1 Diagram of the zebra finch egg development at 5-day incubation (left). The embryo and vitelline membrane blood vessels were dissected from the frozen egg and separated for DNA methylation analyses (right).</figcaption></figure>
using the same column to limit any measuring differences due to re-
producibility errors. We confirmed that reproducibility errors were
not present by including randomly selected samples run as triplicate
repeats throughout the process.

In this assay, DNA methylation is expressed as [5mdC]/[dG] and was quantified using a calibration curve between the peak area ratio of 5mdC to dG (A<sub>5mdC</sub>/A<sub>dG</sub>) versus [5mdC]/[dG]. Individual sample values for [5mdC]/[dG] were extrapolated from a linear calibration equation that best represented the calibration curve relationship.

## 2.6 | Methylation-sensitive amplification fragment length polymorphism

We conducted MS-AFLP from the procedure described in Vos et al. (1995), with the addition of modifications listed in López et al. (2012). Specific adapters and primers used in this study can be found in Table S1. The labelled MS-AFLP products were analyzed using the GeneScan™ 500 LIZ™ size standard using capillary electrophoresis on an ABI PRISM 3130 (Applied Biosystems; California, USA) at the Australian Genome Research Facility Ltd. in Adelaide, South Australia.

We processed raw data using GeneMapper software V3 (Applied Biosystems, Foster City, CA). We restricted our analysis to fragments sized between 100 and 500 base pairs (bp) to reduce the impact of size homoplasy (López et al., 2012) and included in our downstream analyses only unambiguously distinct peaks with a fluorescence value of 200 or greater. We manually checked data to ensure that bins were correctly placed in GeneMapper, and that peak calling was consistent. The presence of DNA fragments in each sample, for each restriction enzyme, was converted to a binary absence (0) or presence (1) matrix, resulting in a total of 184 fragments used for downstream analyses.

## 2.7 | Statistical analyses

We analyzed our data in R (version 4.3.1; R Core Team, 2023), via RStudio (version 2023.06.2+561; RStudio Team, 2023). To ensure that we were reliably testing the effect of treatment group on embryonic and vitelline blood vessel DNA methylation, we included additional variables within the models that have previously been indicated in contributing to maternal CORT and/or DNA methylation differences. These variables included clutch size (Lindner et al., 2021; Sheldon, Schrey, Ragsdale, & Griffith, 2018), clutch number (first or second clutch laid, independent of treatment group; Romero & Wingfield, 2016), maternal condition (Nager et al., 1999; Newbrey & Reed, 2009; here as scaled mass index, calculated as in Peig & Green, 2009), egg mass (Henriksen et al., 2011), and lay latency (Eyck et al., 2020; Schoech et al., 2009). Egg number was included in the models to eliminate the potential carry-over effect of CORT dosing or DNA methylation (i.e., an increase or decrease with lay order).

To analyze the data obtained via LC-MS, we used Gaussian linear mixed effect models and the nlme package (Pinheiro et al., 2019). To investigate the relationships influencing embryonic DNA methylation ratios, we included embryo DNA methylation ratio in the model as the dependent variable and treatment group as the main explanatory fixed factor. Clutch number nested within maternal ID was included as random factors to account for repeated measures from females (i.e., to control for relatedness between familial groups and embryos). Clutch size, clutch number, and egg number were included as categorical fixed effects, while maternal condition, egg mass, and lay latency were included as continuous fixed effects. To investigate the relationships influencing vitelline blood vessel DNA methylation ratios, models were constructed as we did for the embryonic DNA methylation (including the same nested random factors), though with vitelline blood vessel DNA methylation ratio added to the model as the dependent variable, instead. Model selection was conducted as reported in Miltiadous and Buchanan (2021), from criteria outlined in Zuur et al. (2007) and Symonds and Moussalli (2011). Briefly, we used an iterative drop-one method to compare model-corrected Aikake Information Criterion (AICc) values and AICc weights (MuMln; Barton & Barton, 2015) calculated under the maximum likelihood method. During an iteration, a set of models was constructed, whereby each model in a set differed only by one excluded variable (e.g., in the first iteration of model selection, models in a set each subsisted of the full model with one differing variable excluded). Within a set, the model with the lowest AICc value indicated which variable to drop and became the starting model for the next iteration of model selection. This process was repeated until the exclusion of a variable did not lower the AICc value any further. In both cases, the best-fitting models had lower AICc values and higher model weights than their competing null models and were the most parsimonious model (fewest number of significant variables) in their top sets (ΔAICc ≤ 2). Here, we report the results of the best-fitting models, run under the restricted maximum likelihood method, as fitted means (i.e., effect sizes) with their associated standard errors (SE), t-values, *p*-values, and 95% confidence intervals (95% CI). The assumptions of normality and homoscedasticity of the residuals and the response variables for the top competing models were confirmed using Kolmogorov-Smirnov tests, with additional verification by the visual examination of residual plots and histograms.

To analyze the MS-AFLP data, we used the *msap* package (Pérez-Figueroa, 2013). Presence/absence of methylation was scored following López et al. (2012). As such, DNA methylation for each of the above conditions was compared between groups, including treatment group, family group, clutch number, and egg number. Interactions between treatment group and clutch number, treatment group and egg number, and clutch number and egg number were also investigated. The variance in DNA methylation between groups (and interaction effect groups) was analyzed with an AMOVA and further assessed using a pairwise *ΦST* value.
3 | RESULTS

3.1 | Liquid chromatography-mass spectrometry

Maternal dosing with CORT affected offspring genome-wide DNA methylation ratios for both the embryos and the associated vitelline blood vessels. Embryos from treatment group mothers had a significantly lower mean genome-wide 5mdC ratio (2.14±0.09 SE, t=-2.23, df=16, p=0.041; CI: 1.96-2.32; **Figure 2**) than embryos from control group mothers (2.36±0.09 SE; CI: 2.18-2.55). The opposite pattern was detected in the blood vessel tissue: vitelline blood vessels from treatment group mothers had a significantly higher mean genome-wide 5mdC ratio (2.68±0.08 SE, t=2.10, df=19, p=0.049; CI: 2.51-2.84; **Figure 3**) than vitelline blood vessels from control group mothers (2.44±0.08 SE; CI: 2.29-2.59).

Embryonic genome-wide 5mdC ratios differed with clutch num-
ber. Embryos from first clutches had a significantly lower mean
genome-wide 5mdC ratio (2.36±0.09 SE, t=3.08, df=16, p=0.007;
CI: 2.18-2.55; **Figure 4**) than embryos from second clutches
(2.68±0.09 SE, CI: 2.51-2.85). There was no interaction effect be-
tween treatment group and clutch number in embryonic genome-
wide 5mdC ratios (**Tables S2 and S3; Figure 5**).

There was no effect of clutch number on genome-wide 5mdC
ratios of vitelline blood vessels, which was eliminated as a contrib-
uting factor during model selection. No other variables that were
tested in the competing models, including clutch size, egg number,
maternal scaled mass, egg mass, or lay latency, were shown to have
a significant relationship with genome-wide 5mdC ratios for ei-
ther the embryos or the vitelline blood vessels, and these variables
were also eliminated as contributing factors during model selection
(Tables S2-S5).

<figure><img src="image_4.png" /><figcaption>**FIGURE 2** Genome-wide DNA methylation (5mdC) ratios for embryonic tissue samples from control females and treatment females. Black points show fitted means ± SE, accounting for repeated measures from mothers and clutches. Means denoted by a different letter indicate significant differences between groups. Raw data points are jittered.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**FIGURE 3** Genome-wide DNA methylation (5mdC) ratios for blood vessel tissue samples from eggs from control females and treatment females. Black points show fitted means ± SE, accounting for repeated measures from mothers and clutches. Means denoted by a different letter indicate significant differences between groups. Group data points are jittered.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**FIGURE 4** Genome-wide DNA methylation (5mdC) ratios for embryonic tissue samples from eggs from all females across first and second clutches. Black points show fitted mean ± SE, accounting for repeated measures from mothers and clutches. Means denoted by a different letter indicate significant differences between groups. Group data points are jittered.</figcaption></figure>

**3.2 | Methylation-sensitive amplification fragment length polymorphism**

The MS-AFLP analysis generated 184 methylation-sensitive epiloci,
and 60 of these were polymorphic (33% of assayed epiloci). There
was significant differentiation between DNA methylation of family
groups (ΦST=0.091, *p*<0.0001); however, in contrast to the LC-MS
results, there were no significant differences in DNA methylation be-
tween any of the other tested groupings, including treatment group
(ΦST=-0.003, *p*=0.572), clutch number (ΦST=-0.009, *p*=0.961),
egg number (ΦST=0.013, *p*=0.154), or interactions between
these variables (treatment group×clutch number: ΦST=-0.0002,
*p*=0.426; treatment group×egg number: ΦST=0.014, *p*=0.184;
clutch number×egg number: ΦST=-0.002, *p*=0.517).
<figure><img src="image_7.png" /><figcaption>FIGURE 5 Genome-wide DNA methylation (5mdC) ratios for embryonic tissue samples from eggs from all control and treatment group females across first and second clutches. Black points show fitted mean ± SE, accounting for repeated measures from mothers and clutches. Means denoted by a different letter indicate significant differences between groups. Group data points are jittered.</figcaption></figure>

4 | DISCUSSION

Recent experimental studies of early development in oviparous
species have described environment impacts on DNA methylation
(Sarma et al., 2021; Sheldon, Schrey, Ragsdale, & Griffith, 2018),
including exposure to maternal glucocorticoids in mammals
(Constantinof et al., 2019; Szyf et al., 2005). Here, we show for the
first time that biologically relevant elevation in maternal CORT di-
rectly or indirectly affects embryonic and vitelline membrane blood
vessel DNA methylation. In line with our prediction, embryos and
vitelline blood vessels from CORT-treated mothers showed differ-
ences in genome-wide DNA methylation, compared to embryos
from control mothers. Because we know from our previous research
that this manipulation raises maternal CORT, as well as yolk CORT in
eggs laid the following day, maternal CORT is implicated in directly
or indirectly altering the developmental programming of offspring.
However, the exact mechanism through which maternal CORT might
alter embryonic and vitelline blood vessel DNA methylation is not
clear and requires further study. Direct mediation would involve ma-
ternally deposited yolk CORT altering embryonic DNA methylation
patterns. However, indirect mechanisms are possible and may in-
volve post-ovulatory changes to egg composition due to alterations
in yolk deposition, including lipid content, carotenoid allocations, or
the involvement of other neuroendocrine messengers. In addition,
given CORT is involved in metabolic regulation, subtle changes to
maternal foraging patterns pre-laying cannot be entirely excluded as
a mediating factor. However, regardless of whether the effect is di-
rectly due to maternal CORT, or indirectly due to other consequen-
tial behavioural or physiological changes, our results indicate that
changes to maternal CORT concentrations prior to egg laying impact
embryonic and vitelline blood vessel DNA methylation patterns.

Our results suggest that, in response to a stressful event such
as a predatory encounter around the time of ovulation, mothers

have the capacity to change the DNA methylation profiles of their
offspring due to their physiological response, although whether
such effects are directly or indirectly mediated by yolk CORT re-
mains unclear. Such effects may offer a potential means of altering
the developmental trajectories of offspring (Lamka et al., 2022).
The effects of CORT on avian physiology are broadscale and
are known to affect many developmental processes (Landys
et al., 2006; Schoech et al., 2011). The ability of avian mothers
to transfer CORT to the developing embryo in the few days be-
fore ovulation and laying is very important, because this provides
mothers the opportunity to communicate aspects of the exter-
nal environment to their offspring (Almasi et al., 2012; Hayward
& Wingfield, 2004). In a species such as the zebra finch, where
the time difference between ovulation and fledging is very short
(i.e., 11–16 days between ovulation and hatching, and 17–18 days
to fledging thereafter; Zann, 1996), this can provide the offspring
information about the external environment that is still contextu-
ally relevant to their ongoing survival. Because maternally derived
CORT can direct the developmental trajectories of developing em-
bryos, it offers offspring rapid, adaptive developmental program-
ming for survival and reproduction in response to environmental
conditions (Sheriff et al., 2018; Sheriff & Love, 2013).

We have shown that changes to genome-wide DNA meth-
ylation patterns differ in embryos and their associated vitelline
membrane blood vessels in response to our CORT treatment.
DNA methylation was lower in embryos from CORT-treated
mothers than in the embryos from control group mothers, and
in contrast, DNA methylation was higher in the vitelline blood
vessels of eggs from CORT-treated mothers than in the eggs from
control group mothers. It is challenging to interpret the direction
and magnitude of the DNA methylation changes we have found.
First, DNA methylation patterns differ across tissue types as
well as across cell types within those tissues (Husby, 2020), and
CORT treatment has been shown to affect the direction of global
DNA methylation change differentially across tissues (Crudo
et al., 2012). Our two types of samples differ in both their func-
tion and complexity. Vitelline membrane blood vessels transport
nutrition to the developing embryo and waste from the embryo,
while 5-day-old developing embryos contain a wider range of tis-
sue and cell types, all of which are undergoing rapid developmen-
tal change. For these reasons, it is unsurprising that we detected
contrasting effects of the CORT treatment on DNA methylation
across sample types. Second, our methods do not allow us to ex-
amine locus-specific DNA methylation patterns, nor the location
of DNA methylation changes within genes. CORT treatment is
known to upregulate some genes and downregulate others (e.g., in
birds; Austin et al., 2021), and so if DNA methylation of promoter
regions is linked to gene expression (Bird, 2002), it would also
be expected that DNA methylation levels change differentially
across the genome in response to this treatment. Because the
location of DNA methylation is key to understanding its possible
impacts on function, and because this information is unavailable
to us, we are unable to explain differences in functional effects
of CORT treatment across tissue types. The impact of environ-
mental stressors on gene expression is well studied, in particular,
at the glucocorticoid receptor gene (NR3C1), as is the relation-
ship between levels of DNA methylation in the promoter region
of this gene and its expression. Even within this one gene, these
relationships appear to be contextual (Ruiz-Raya et al., 2023),
and exposure to environmental stressors increases NR3C1 DNA
methylation in some cytosines while decreasing in others (Sarma
et al., 2020). Despite these complexities, studies such as the one
we present here suggest that DNA methylation may be a plausible
mechanism linking the environment and an organism's phenotype
and indicate that further investigation into these relationships
is warranted. In addition, our findings make an excellent start-
ing point for further work to test the functional significance of
CORT-mediated DNA methylation changes to specific genes and
their developmental consequences.

We found that embryonic DNA methylation was increased
in the eggs from second clutches, compared to those from first
clutches. This increase is unlikely to be due to any carry-over ef-
fects of prior maternal exposure to CORT across clutches, because
we saw no significant interaction between treatment exposure and
clutch order. This result seems more likely to be due to changes in
egg composition across clutches, a phenomenon which is well doc-
umented. Songbirds lay multiple clutches in a season; egg compo-
sition, development, and fledging rates vary across clutches, with
productivity declining across successive clutches (Monaghan &
Nager, 1997; Sockman et al., 2006). Recent work in birds suggests
that DNA methylation differences between individuals are due to
a genetic basis and vary little due to the postnatal rearing environ-
ment (egg cross-fostering experiment; Sepers et al., 2023). However,
given that our study manipulates early developmental exposure to
CORT, the prenatal rearing environment may well be an important
factor in determining offspring DNA methylation differences. It is
important that future work quantifies both the timing of develop-
mental changes in embryonic DNA methylation patterns, as well as
their functional significance. This would add to the well-documented
age-related changes in DNA methylation patterns across species
(Horvath & Raj, 2018; Luo et al., 2018).

While the MS-AFLP results did not reflect those obtained via
LC-MS, this is unsurprising because these two methods measure
DNA methylation differently. MS-AFLP interrogates locus-specific
methylation patterns at a small number of sites across the genome
and thus may fail to capture relevant changes in DNA methylation
due to the relatively small number of loci that are assayed (López
et al., 2012). However, the MS-AFLP data differed between fami-
lies, indicating that our loci did have the power to detect differences
in DNA methylation but did not include loci that responded to our
treatments. LC-MS measures the proportion of genome-wide meth-
ylated cytosines (Song et al., 2005) but cannot provide informa-
tion about which specific loci are responding to treatments. When
changes are observed in genome-wide DNA methylation patterns
using either of these initial approaches, further locus-specific studies
can be used to target particular candidate genes, be conducted more

broadly across the genome, or even survey the complete methylome
(e.g., via Reduced Representation Bisulfite Sequencing or Whole-
Genome Bisulfite Sequencing; Deng et al., 2009; Gu et al., 2011).
It is also important to note that our findings provide a snapshot of
DNA methylation at only one particular developmental time be-
cause we extracted the embryos at 5-day incubation, approximately
a quarter of total incubation time for this species (Zann, 1996). Thus,
it would be important to further this work by investigating how ma-
ternal CORT affects DNA methylation across developmental stages.
Coupling such studies with gene expression analyses could enable
investigation of whether changes to DNA methylation affect off-
spring responses to stressful maternal conditions and identify af-
fected genes.

Our study has provided evidence that elevated avian maternal
CORT has the potential to drive rapid changes in offspring DNA
methylation, either directly or indirectly. We have shown that DNA
methylation differs between embryos and vitelline blood vessels
from CORT-treated mothers compared to those from control moth-
ers. Additionally, we have shown that the direction of DNA meth-
ylation change differs between the two tissue types, highlighting
the importance of studying such effects in a tissue-specific manner.
These intriguing results indicate that DNA methylation may be an
important component of the pathway through which mothers af-
fect their offspring. However, it is clear that more work is warranted
to determine where changes to DNA methylation have occurred in
the genome and whether these changes affect gene expression in
offspring. This information is needed to identify the mechanisms
through which mothers can potentially adaptively tailor their off-
spring phenotype to the anticipated environment in which they will
live.

AUTHOR CONTRIBUTIONS

AM, KLB, LAR designed the project. AM and DLC collected data. All authors were involved in data analysis and interpretation. AM wrote the initial manuscript draft and produced the figures. All authors contributed to editing the manuscript.

ACKNOWLEDGEMENTS

We thank the Deakin Waurn Ponds Campus animal care staff, par-
ticularly Dr. Rod Collins, for providing animal care. We would also like
to thank three anonymous reviewers for their valuable comments,
which have greatly strengthened our manuscript. Financial support
was provided by the Australian Research Council (ARC) Discovery
Project DP130100417 and Future Fellowship FT140100101 to
KLB; and, the Centre of Integrative Ecology, Deakin University to
AM. Open access publishing facilitated by Deakin University, as
part of the Wiley - Deakin University agreement via the Council of
Australian University Librarians.

DATA AVAILABILITY STATEMENT

Data Accessibility: The raw data used in this study have been de-
posited on the publicly accessible data repository Dryad and can be
found at this DOI: https://doi.org/10.5061/dryad.kprr4xhbk.
Benefits Generated: The sharing of our data on Dryad and the publication of our results at *Molecular Ecology* will create a wider benefit from this research.

## ORCID

Anna Miltiadous https://orcid.org/0000-0002-9481-2602

Damien L. Callahan https://orcid.org/0000-0002-6384-8717

Antoine M. Dujon https://orcid.org/0000-0002-1579-9156

Katherine L. Buchanan https://orcid.org/0000-0002-6648-5819

Lee A. Rollins https://orcid.org/0000-0002-3279-7005

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## SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

**How to cite this article:** Miltiadous, A., Callahan, D. L., Dujon, A. M., Buchanan, K. L., & Rollins, L. A. (2024). Maternally derived avian corticosterone affects offspring genome-wide DNA methylation in a passerine species. *Molecular Ecology*, **33**, e17283. https://doi.org/10.1111/mec.17283