1. Introduction
Effects of climate change are projected to become more intense during
the 21st century (IPCC, 2014; Caldeira & Wickett, 2003). Tropical coral
reefs have been most negatively affected by the rapid climate change,
resulting in worldwide coral reef decline (Parmesan, 2006; Heron et al.,
2016). Consequently, corals must adapt to their changing environments,
or face declines and ultimately extinction.
Thermal adaptation has been documented in various coral populations
throughout the Indo-Pacific, but it is uncertain whether these disparate
populations adapt to other novel environmental stressors in similar
manner (Palumbi et al., 2014). If the same genes are under selection by
different stressors, evolution of resistance to one stressor would
promote the resistance to other stressors, speeding up the adaptation to
long-term climate change. It is also possible that the same genes are
used in adaptation to different stressors but differentially selected
upon, which would imply a tradeoff where some adaptations exclude
others. Such genetic tradeoffs could slow down or even entirely prevent
long-term adaptation to multiple stressors. Lastly, if different genes
are used for adaptation to different stressors, this would imply
independent evolution and that these adaptations can occur at the same
time, neither helping nor hindering each other.
Previous studies investigating how coral responds to multiple
environmental stressors, simultaneously, have done so by exposing
different coral genotypes to various stressors and then measuring the
coral’s response to each stressor or combination of stressors. The
experimental design of Mueller et al., 2018 found that Acropora
cervicornis resistance to white-band disease and high-water
temperatures had no tradeoffs, and that these responses evolved
independently. The elevated temperature, increasedp CO2, and bacterial challenge treatments used in
Wright et al., 2019 found that Acropora millepora ’s responses to
these treatments had no tradeoffs, and that coral’s survival under one
treatment indicated its potential to withstand the other treatments. The
physiological responses of Acropora cervicornis to raised
temperatures and acidification in Mueller et al., 2021 revealed no
tradeoffs between the responses, and that the phenotypic responses had
significant variation among the coral genotypes. These previous studies
broadened the scope of research on how climate change affects coral
reefs to include the effects of multiple environmental stressors, rather
than individual, and their interactions (Pendleton et al., 2016).
However, coral’s response pathways and outcomes when faced with these
multiple climate changes, as well as others, still needs to be addressed
(Pendleton et al., 2016). Here, we aim to address this problem by
investigating the evolutionary pathways of coral’s adaptive response to
various environmental stressors, and ultimately determine if these
pathways are the same, independent, or trade off each other.
We reanalyzed transcriptomic reads from four studies comparing corals
across four environmental gradients (Figure 1): differentially heated
tidal pools (Rose et al., 2017), proximity to CO2 seep
(Kenkel et al., 2017), different symbionts (Barfield et al., 2018), and
latitudinal gradient (Dixon et al., 2014). We have quantified not only
gene expression differences between contrasts, which was the original
goal of all these studies, but also genetic divergence based on the same
transcriptomic reads. We hypothesized that coral’s divergence and gene
expression responses to daily heat stress, less heat-tolerant type of
algal symbionts, and warmer location in the latitudinal gradient should
show at least some parallelism, both at the level of genetic divergence
and gene expression, as all these are expected to involve thermal
adaptation. Even more obvious should be the similarity between the two
cases of adaptation and/or acclimatization to a high CO2environment, at Dobu and Upa-Upasina. At the same time, we expected that
CO2 adaptation would be either independent, or trading
off the thermal adaptation. It is important to note that the tradeoff
could be detected only for gene expression data, i.e., opposite
regulation of the same genes (Figure 1). Tradeoff detection was not
possible for genetic divergence since the test statistic,F ST, does not capture the direction of
evolutionary change. Finally, we examined the overlap between
differentially expressed and genetically diverging genes, to look for
evidence that the regulatory differences had genetic basis.
Figure 1. Experimental design of the study. (a) Environmental
stressors, showing stressed and non-stressed contrast, selected for
study. (b) Contrast’s non-stressed and stressed populations were used to
compute the per gene genetic divergence (F ST) and
gene expression. (c) To compare directions of adaptive responses to
these stressors, a principal coordinate analysis (PCoA) and principal
component analysis (PCA) was used for F ST (with
Bray-Curtis distance measure) and log-fold change, respectively. (d)
Possible outcomes of the PCoA or PCA include adaptive response vectors
aligning themselves together to reflect parallel evolution, aligning
themselves orthogonally (i.e., 90°) to reflect independent evolution, or
aligning themselves 180° apart to reflect tradeoffs between the
responses (possible for gene expression analysis).