Introduction
Nuclear microsatellites became popular during the 1990’s as a powerful
tool to assess patterns of genetic variation in populations (Allendorf,
2017; Ellegren, 2004). While they are still widely used, the development
of Genotyping-by-Sequencing techniques, like RADseq (Baird et al., 2008;
Miller, Dunham, Amores, Cresko, & Johnson, 2007) and similar techniques
of genome complexity reduction (e.g. ddRAD, bestRAD), coupled with the
decreasing costs of massive parallel sequencing, have extended the reach
of massive single nucleotide polymorphism (SNP) genotyping to the study
of non-model organisms (Baird et al., 2008; Davey et al., 2011;
Peterson, Weber, Kay, Fisher, & Hoekstra, 2012; Allendorf, 2017;
Andrews, Good, Miller, Luikart, & Hohenlohe, 2016; Putman & Carbone,
2014). This has led to a discussion about the relative benefits of using
each type of marker in conservation and evolutionary biology (Allendorf,
2017; Hodel et al., 2017; Morin, Luikart, & Wayne, 2004; Puckett,
2017).
Mutation rates in microsatellites are several orders of magnitude higher
than those estimated for SNPs (Dallas, 1992; Ellegren, 2004; Lynch,
2010; Weber & Wong, 1993; Zhang & Hewitt, 2003). Combined with the
larger number of possible alleles for a single locus, microsatellites
provide immense levels of polymorphism, yielding high statistical power
in population genetic inference (Allendorf, 2017; Avise, 2004).
Microsatellites are very sensitive to sudden, or recent, demographical
processes, and are well suited to detect subtle population structure or
recent bottlenecks (Haasl & Payseur, 2011; Luikart & Cornuet, 1998;
Pereira, Teixeira, & Velo-Antón, 2018; Putman & Carbone, 2014).
However, high polymorphism is usually associated with homoplasy (Garza
& Freimer, 1996; Hedrick, 1999; Queney, Ferrand, Weiss, Mougel, &
Monnerot, 2001), and poses difficulties in fitting adequate evolutionary
models to heterogeneous mutation processes (Di Rienzo et al., 1994;
Ellegren, 2004; Valdes, Slatkin, & Freimer, 1993; Weber & Wong, 1993;
Webster, Smith, & Ellegren, 2002). This can lead to unreliable
estimates of divergence times (Kalinowski, 2002; Queney et al., 2001)
and underestimation of genetic differentiation between populations
caused by high intra-populational heterozygosity (Hedrick, 1999).
Furthermore, microsatellites are not well suited to reconstruct the
evolutionary history of lineages or species under certain demographic
scenarios, for instance during range expansions, when consecutive
founder events and allele surfing processes in newly formed populations
inflate genetic differentiation (Pereira et al., 2018). A microsatellite
locus contains from four to twelve times more information than a SNP
(Liu, Chen, Wang, Oh, & Zhao, 2005). However, current genotyping costs
for SNPs are relatively low, so the lower per-locus information of SNPs
is largely compensated by the sequencing of thousands of them at a
similar cost than the genotyping of a few microsatellites (Hodel et al.,
2016; Puckett, 2017). A large number of SNPs and their genome-wide
distribution secure a range of mutation rates that can, in principle,
provide sufficient information at different evolutionary scales, from
recent demographic processes within-species to interspecies phylogenies
(DeFaveri, Viitaniemi, Leder, & Merilä, 2013; Petersen et al., 2013).
The different molecular nature of SNPs and microsatellites is expected
to impact their resolution power at different evolutionary scales, with
microsatellites better reflecting recent demographic processes but
rapidly losing resolution above the species level, and SNPs providing
less information per locus but securing resolution of demographic
processes over a wider evolutionary window (DeFaveri et al., 2013;
Estoup, Jarne, & Cornuet, 2002; Haasl & Payseur, 2011). A review of
the recent literature shows that thousands of SNPs are generally more
powerful in detecting genetic structure than typical microsatellite
datasets (Elbers, Clostio, & Taylor, 2017; Hodel et al., 2017; Jeffries
et al., 2016; Malenfant, Coltman, & Davis, 2015; McCartney-Melstad, Vu,
& Shaffer, 2018; Puckett, 2017; Puckett & Eggert, 2016; Rašić,
Filipović, Weeks, & Hoffmann, 2014). The choice of marker (SNPsversus microsatellites) also seems to affect estimates of the
proportions of individual ancestries and the inferred optimal number of
clusters (Bradbury et al., 2015; Malenfant et al., 2015; Elbers et al.,
2017; Bohling et al., 2019). These studies have made important
contributions to our understanding of differences in patterns of genetic
diversity and structure using both types of markers. However, the lack
of comparable datasets, differences in the clustering methods used, and
the absence of metrics allowing direct comparisons across marker types
limit generalization of these results.
We present an explicit comparison of patterns of genetic structure and
diversity based on comparable datasets of microsatellites and SNPs in
two amphibian species: the Iberian tree frog, Hyla molleriBedriaga, 1889, and the Western Spadefoot, Pelobates cultripes(Cuvier, 1829). Both are nearly endemic to the Iberian Peninsula (with
some populations reaching southern France), and their range-wide
phylogeography has been previously investigated based on mitochondrial
and microsatellite datasets (Gutiérrez-Rodríguez, Barbosa, &
Martínez-Solano, 2017; Sánchez‐Montes, Recuero, Barbosa, &
Martínez‐Solano, 2019). These studies linked their contrasting
phylogeographic patterns with different demographic histories during the
Late Quaternary. Hyla molleri is present in Continental and
Atlantic Iberia, and its higher tolerance to colder conditions was
hypothesized to account for their inferred demographic stability since
the Last-Glacial Maximum (~ 21,000 years ago)
(Sánchez‐Montes et al., 2019). In contrast, P. cultripes is a
more thermophilous species present in southern and central Iberia, in
areas with a Mediterranean influence. This species seems to have
experienced important range contractions to southern glacial refugia
during colder times in the Pleistocene, resulting in a south-to-north
gradient of decreasing genetic diversity (Gutiérrez-Rodríguez et al.,
2017). The availability of comprehensive microsatellite datasets and the
contrasting demographic histories in a shared geographical area make
these two species good study systems for a robust comparative assessment
of patterns of genetic diversity and structure obtained with
microsatellites and SNPs.