Population genetics of sponges in marine lakes
The use of thousands of RADseq-based SNPs provided the resolution
necessary to reveal genetic patterns of Suberites diversicolorthat had not previously been captured at finer spatial scales. We
observed clear clustering for the marine lake locations per lake. The
lagoon populations Bay and to a lesser extend DAR showed to hold a basal
position in the phylogenetic tree and in PCAs. They also showed links to
most other populations in the migration network. The presence of
ancestral polymorphisms in the marine lake populations could explain
this pattern. The observation of finding more structure when using
higher numbers of genetic markers has been shown in other marine
organisms as well (Bradbury et al. , 2015; Maas et al. ,
2018; Lemopoulos et al. , 2019; D’Aloia et al. , 2020; Sundeet al. , 2020; Timm, 2020). In a comparison among three
high-throughput genotyping approaches, the RADseq generated markers were
found to be the most sensitive and robust in detecting fine-scaled
structure (D’Aloia et al. , 2020). The discrepancy in observed
genetic structure based on a higher number of markers as compared to
single markers is important in interpreting results from other studies
for sessile marine organisms using low resolution markers.
While traditional, low-resolution markers have been useful in exposing
morphologically cryptic sponge species, they have often failed to detect
within-species diversity (as reviewed in Oppen et al., 2002;
Pérez-Portela & Riesgo, 2018; Uriz & Turon, 2012; Wörheide et al.,
2005). Using the high resolution of RAdseq generated markers allowed us
to see clear clustering per lake even on very small spatial scales
1-10km. The scale at which we find strong structure is smaller compared
to studies using microsatellites in the sponges Crambe crambe(Duran et al. , 2004), Scopalina lophyropoda (Blanquer and
Uriz, 2010), Spongia lamella (Noyer and Becerro, 2012;
Pérez-Portela, Noyer and Becerro, 2015), Stylissa carteri (Gileset al. , 2015), Cliona delitrix (Chaves-Fonnegra et
al. , 2015), Xestospongia muta (Richards et al. , 2016),Paraleucilla magna (Guardiola, Frotscher and Uriz, 2016),
Plenaster cragi (Taboada et al. , 2018) and Petrosia
ficiformis (Riesgo et al. , 2019). Even studies using higher
resolution markers also little structure at small spatial scales, with
Brown et al. (2017) detecting little structuring forAphrocallistes vastus in British Colombia at scales
<275km and Leiva et al. (2019) finding panmixia at
scales >900km for Dendrilla antarctica . It could be
that these are highly connected populations, possibly through rafting or
sperm-mediated gene flow (Maldonado, 2006; DeBiasse, Nelson and
Hellberg, 2014). Yet it is also possible that the number of SNPs from
Brown et al. (2017) and Leiva et al. (2019) (67 and 529,
respectively) was too low to detect subtle structure at small scales.
Alternatively, the filtering strategy of these studies possibly was not
rigorous enough to eliminate sufficient or all microbial contamination,
possibly clouding patterns.
We assessed the effects of several drivers of population diversity and
structure. First, we tested to what extent marine genetic
differentiation conforms to the decay of population similarity with
geographical distance resulting in a pattern of isolation‐by‐distance
(Wright, 1943) using only Lineage B. We found strong population
structure with clustering per lake, yet no pattern of
isolation‐by‐distance was observed. This is remarkable, since we sampled
at geographical distances of 1km - 1,400km. We also did not detect a
pattern of isolation-by-environment, despite the great environmental
variability among lakes (temperature: 29 - 32.4 °C, salinity: 24 - 33.4
ppt). Previous studies using a low number of markers did find a pattern
of isolation-by-distance for sponges (Duran et al. , 2004;
Blanquer and Uriz, 2010; Noyer and Becerro, 2012; Pérez-Portela, Noyer
and Becerro, 2015), which is usually expected for species with
restricted dispersal abilities (Wörheide, Solé-Cava and Hooper, 2005;
Maldonado, 2006). Other studies report an influence of oceanographic
currents (Chaves-Fonnegra et al. , 2015; Richards et al. ,
2016; Riesgo et al. , 2019), or environmental heterogeneity
(temperature and productivity) (Giles et al. , 2015) on sponges.
Our results indicate that mechanisms other than only dispersal
limitation by geographical distance or local environments are important
in structuring S. diversicolor populations. In addition, the
permeability of the landscape barrier surrounding the marine lakes,
determining the degree of water flowing in and out of the lakes, did not
seem to influence the population structure or diversity. PerhapsS. diversicolor populations are truly isolated per lake as their
low dispersal ability restricts effective gene flow. Then, populations
can become differentiated through genetic drift or via local adaptation
to environmental parameters that we have not recorded (Frankham, Briscoe
and Ballou, 2002). Alternatively, founder effects and subsequent
priority effects could explain the pattern (Orsini et al. , 2013;
Fukami, 2015; De Meester et al. , 2016).
Priority effects were previously discussed as potential drivers of
structure in marine lake organisms by Maas et al. (2018) and de
Leeuw et al. (2020). Depending on spatial scale Maas et
al. (2018) found an effect of geographic distance and connectivity
influencing mussel population structure. They argued that despite
founder events stochastically driving alleles to fixation in small
populations, ongoing dispersal would overwhelm this effect (Mayr, 1963;
Waters, Fraser and Hewitt, 2013). Mussels have extensive pelagic larval
duration periods, and Maas et al. (2018) hence argued that
priority effects mediated by local adaptation could facilitate the
observed patterns of population structure (Orsini et al. , 2013;
Fukami, 2015; De Meester et al. , 2016). Sponges, in contrast,
generally have poor dispersal abilities (Maldonado, 2006). As the
current study does not find an effect of connection to the sea in
structuring populations, stochastic fixation of alleles due to genetic
drift may be the cause of each population being distinct. Including more
lakes with replicates of local environments and/or connection to the sea
may further elucidate drivers of sponge differentiation in fragmented
habitats.