Discussion
Our study provides evidence that P. ochraceus may show genetic
variation for tolerance of or resilience to SSWS. By comparing allele
frequencies between symptomatic and asymptomatic individuals during an
outbreak, we detected significant differences across multiple genomic
regions, consistent with a polygenic basis for this phenotype. Based on
Fst analyses in individual SNP loci, three loci were detected to be
under selection in at least one of the three geographic populations
sampled. Multivariate analyses examining genome-wide changes revealed
differences between symptomatic and asymptomatic sea stars, and 10 of
these differences occurred in more than one population. Our study is the
second to detect a genomic signal consistent with selection caused by a
strong epizootic event of SSWS starting in 2013.
Schielbelhut et al. (2018) detected allelic shifts in healthy P.
ochraceus adults and juveniles before and after the SSWS outbreak in
California. They found three loci putatively under selection and
reported on 100 discriminatory haplotypes between time periods.
Interestingly, the 87 SNP loci we detected as most discriminatory in our
samples did not occur within 10 kb of those reported by Schielbelhut et
al. (2018). The nature of the sampling between studies, which differ in
time period, the health status of the sea stars, and geographic
location, likely contributes to differences in power to detect
associated genetic variants. For instance, elevated sea water
temperature can lead to additional stress responses to SSWS (Eisenlord
et al., 2016; Kohl et al., 2016). Differences in thermal stress between
the two regions may also cause different selective pressures. For
instance, daily deviation from annual sea water temperatures in Oregon
were more prevalent in 2013/2014 than in California (Miner et al.,
2018). Differences in allele frequencies between Schielbelhut’s and our
study could indicate the differences in synergistic selective pressures
from SSWS and temperature. Additionally, we analyzed our genetic data
for each subpopulation separately, detecting a signal of population
structure. Schielbelhut et al. (2018) did not detect significant
structure and performed a region-wide analysis. By accounting for
subpopulation structure, we were able to isolate more genes that would
have been confounded in a full population wide study.
While our DAPC analysis identified 85 outlier loci in total, we
proceeded conservatively by further requiring that different populations
shared neighboring loci (within 1 Mbp). The 10 clusters identified
harbor over 100 predicted protein-coding genes. With the current
dataset, we cannot identify regions more specifically, and hence many of
these genes are likely linked to relevant alleles. We argue that these
regions may have small but cumulative effects of adaptive genetic
variation associated with SSWS tolerance or resistance, which is
expected for a polygenic trait. This trait may require higher powered
studies for ascertaining causative loci with more precision (Gagnaire &
Gaggiotti, 2016). Nevertheless, these functional regions may serve as
candidates in future studies of response to SSWS challenges, such as
differential gene expression or monitoring of allele frequency changes.
In fact, differential gene expression between symptomatic and
asymptomatic individuals were related to innate immunity and tissue
remodeling (Fuess et al., 2015; Gudenkauf & Hewson, 2015; Ruiz‐Ramos et
al., 2020). Many of these genes are related to stress response,
defensive apoptosis and tissue degradation. Echinoderms have complex
immune system that allows for innate immunity through primitive immune
memory and cytokine-like systems (Mydlarz, Jones, & Harvell, 2006). In
addition, recent studies suggest that microbial activity on the
diffusive boundary layer between water and animal could reduce oxygen
uptake (Aquino et al., 2021), suggesting metabolic genes may be also
play important roles in this response. We did not see similar genes
specifically related to Ruiz-Ramos et al. (2020), suggesting other
mechanisms other than immunity could be important to SSWS resistance,
such as metabolic processes in response to hypoxic conditions (Aquino et
al., 2021). Genes with small effects found in our study may aid in
cellular processes related to SSWS resistance.
Assessing marine diseases is difficult due to large gaps in knowledge
regarding how pathogens disperse and propagate in marine systems
(MCCALLUM et al., 2004). The vast majority of our understanding of
wildlife diseases comes from terrestrial systems (Harvell et al., 2004).
In addition, there is higher taxonomic diversity of hosts and pathogens
in marine systems. The complexity of marine diseases is likely a culprit
as to why isolating the causation of SSWS remains to be unresolved
(Eisenlord et al., 2016). Mitigation techniques for addressing outbreaks
when a causative agent is unknown should run parallel with studies
attempting to determine the cause (Groner et al., 2016). With the rising
sea water temperatures resulting in the higher prevalence of marine
diseases (Harvell et al., 2002; Tracy, Pielmeier, Yoshioka, Heron, &
Harvell, 2019), we are likely to see similar scenarios of disease
outbreaks impacting marine species more frequently and having little
time to address management or conservation plans.
One method of addressing our lack of knowledge on SSWS and other disease
outbreaks is to determine whether there is a potential for the organism
of interest to adapt to the syndrome. For example, selectively rearing
disease-resistant oysters in hatcheries has been a useful tool in
avoiding disease outbreaks that are decimating the wild? populations
(Agnew et al., 2020; Dégremont, Garcia, & Allen, 2015). Selectively
breeding programs in both the eastern and Pacific oyster,Crassostrea virginica and Crassostrea gigas , has been a
useful tool in producing disease tolerant lines. Of course, not all
marine species are amenable for selective breeding. Assessing genomic
variation in natural populations can address whether these species have
the genetic makeup for adaptation to marine diseases on their own. Our
dataset is hence valuable in that captured phenotypic and genetic
variation during a period of high SSWS incidence.
Our study joins that of Schielbelhut et al. (2018) to show that P.
ochraceus has the potential to adapt to SSWS challenges. A number of
candidate genes were isolated that may aid in SSWS resistance, although
none of these appear to function via changes in gene expression
associated with SSWS infection. Assessing genetic variation to address
susceptibility and adaptative potential should continue to run parallel
with studies that try to determine the causative agent for SSWS and
other marine disease. These studies should also be done both in locally
as well as across geographic regions as we have seen variation in how
local populations respond differently.