Why were differences in methylating enzyme expression opposite of
our hypothesis?
In the present study, we detected a significant effect of native versus
non-native population status on the expression of all three genes. As
with the trend in Senegal, older (native) populations expressedmore DNMT1 and DNMT3 as well as TET2 than non-native birds. What
are reasonable explanations for this pattern, so strong but reverse of
expectations? There might be some insight to gain by comparing the most
important other drivers of gene expression among the factors we
considered (Fig. 1). After tissue, temperature predictability and
genetic group were the strongest predictors of expression with
native/non-native status significant but a fraction as informative. We
cannot explain the effect of genetic group because we had no a
priori reason to expect this factor to be so important. This predictor
captures the evolutionary history of populations and thus could
represent more of a phylogenetic than functional difference.
The very strong effect of temperature predictability, by contrast, is
intriguing because it resembles the directionality of the difference we
saw for native/non-native status here and in Senegal: birds from sites
where plasticity should be more favorable (i.e., the youngest
populations) expressed less of the enzymes that regulate
methylation. Our expectation was that if DNMT1/3 and TET2 expression
were mediators of reversible plasticity (Wu and Zhang 2010, Bogan and Yi
2024), expression of these genes should be highest where conditions are
less predictable (McCaw et al. 2020). Even the genetic group effect
could be an echo of temperature predictability: despite our ambitious
sampling effort, we only collected tissues from 9 countries. More
importantly, sparrows from Israel, Senegal and Vietnam are also members
of genetic group 2, the most predictable sites we studied (Table 1). Our
current country set prevents us from disentangling genetic history and
temperature predictability. Nonetheless, we suspect that temperature
predictability is the driving force here. Genetic group 1 includes birds
from Spain, one of the more predictable climates, but also birds from
the Netherlands and Norway, the least predictable climates, and
native/non-native status either relates to introduction history alone or
is also partly entangled with temperature predictability.
Another potentially useful way of updating our hypotheses given our
results involve kinds of plasticity that might be fostered by
methylation. Our initial hypothesis was based on
environmentally-sensitive, reversible plasticity. Our results may
reflect, though, the dispositions of populations to realize canalized,
developmental plasticities to predictable cues over development, not
plasticity activated and suppressed to match current conditions (Vogt
2017a, Vogt 2017b). In support, there was a consistent effect of
latitude on expression of all three genes. Latitudinal effects might
reflect a tendency for DNMT/TET expression to track photoperiod-related
seasonality (Stevenson 2018), which increases towards the poles.
Seasonality as a predictable form of environmental variation is quite
distinct from Colwell’s indexes, which capture climaticunpredictability . Perhaps DNMT/TET expression is more important
for plastic responses to predictable than unpredictable environmental
change (McCaw et al. 2020, Lynch et al. 2016). There could also be an
upper limit on the rate at which environmental variation can be
transduced into DNMT expression, then methylation, and ultimately
reversible plasticity (Snell-Rood et al. 2018). DNA methylation plays a
role in the regulation of several seasonal plasticities (Fishman and
Tauber 2024) from the neuroendocrine coordination of biorhythms to the
recrudescence of reproductive tissues (Sharma et al. 2018). We expected
that DNMT expression differences play some role in reversible
plasticity, too, but the consistent effects of latitude on expression
could suggest that DNMT and TET2 expression levels might instead be set
permanently in early development (i.e., epigenetically programmed). By
measuring gene expression in only adult birds, we could be capturing the
roles these enzymes played in coordinating what would become rhythmic
changes in phenotypes in consistently periodic environments (Friston
2010). Measurements in immature animals could have produced very
different patterns.
We find this possibility (i.e., the patterns we observed largely being
due to the age of the birds we studied) worthy of future study but
unsatisfying. First, latitude effects on expression were very small
compared to other forces. If seasonality is so important, its effects
would probably have been of comparable strength to the other factors.
Second, DNMT and TET2 expression (Lynch et al. 2016) and resultant
methylation (Sheldon et al. 2020) can in fact be quite dynamic in many
vertebrates (see also Schrey et al., this issue). Expression of all
three enzymes can change over months, weeks, days, and even hours
(Alvarado et al. 2015, Stevenson 2017). To our knowledge, no one has yet
evaluated how quickly expression of these enzymes can change in adult
house sparrows, but there is no reason to believe that this species
would be unlike others. Finally, DNMTs in other species can in fact play
roles over the timescales and contexts that underpin our hypotheses (Luo
et al. 2012). For instance, in domesticated chickens, strain differences
in resistance to Marek’s disease virus were related to DNMT expression;
exposure to a novel and lethal environmental stimulus (i.e., the virus)
led different individuals to distinctly respond to and cope with the
stimulus via plasticity over a fairly short time scale. If broadly
applicable, these results suggest that appreciable within-individual
variation in the expression of these DNMT/TET is achievable. Indeed,
inter-cell type variation in expression of these genes is well-known,
and it is partly for this reason we measured expression in three
tissues. One thing to mention as well is that we gave all birds in our
study a small dose of lipopolysaccharide (LPS) to induce an immune
response that is the subject of other projects. We could not study
untreated birds for ethical and practical reasons, but it is possible
that birds not treated with LPS could have shown different patterns.
A final surprising result that warrants attention and might even be
related to the unexpected outcomes we observed among populations are the
strong within-individual and among-population correlations in gene
expression (Fig. 2). We did not expect such strong relationships among
genes given their unique functions, yet these results suggest that the
persistence, creation and erasure rates of methyl marks across tissues
within individuals are probably similar among birds and across sites.
Such strong covariation suggests that these genes might evolve and/or
operate as a unit among individuals and populations, which could
constrain expression variation consistently, despite the utility of
plasticity for unpredictability in some sites.