1. RESEARCH NOTE
De novo isolation of 17 microsatellite loci for flat periwinkles (Littorina fabalis and
L. obtusata) and their application for species discrimination and hybridization studies
Joa˜ o Carvalho1,2,3, Carolina Pereira1, Graciela Sotelo3, Diana Costa3,4,
Juan Galindo1 and Rui Faria3,5
1
Departamento de Bioquı´mica, Xene´tica e Inmunoloxı´a, Facultade de Bioloxı´a, Universidade de Vigo, Campus de Vigo, 36310 Vigo, Spain;
2
Departamento de Biologia Ambiental, Faculdade de Cieˆncias da Universidade de Lisboa, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal;
3
CIBIO, Centro de Investigac¸a˜o em Biodiversidade e Recursos Gene´ticos, InBIO, Laborato´rio Associado, Universidade do Porto, Campus Agra´rio de Vaira˜o, 4485-661
Vaira˜o, Portugal;
4
Departamento de Biologia, Faculdade de Cieˆncias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal; and
5
IBE, Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Pompeu Fabra University, Doctor Aiguader 88,
08003 Barcelona, Spain
Correspondence: R. Faria; e-mail: rui.faria@upf.edu
Intertidal gastropods of the genus Littorina have been gaining
recognition as models to investigate local adaptation and eco-
logical speciation (e.g. Johannesson, 2003; Butlin et al., 2014;
Galindo & Grahame, 2014). However, not all species have
received the same attention. The flat periwinkles, L. obtusata
(Linnaeus, 1758) and L. fabalis (Turton, 1825), exhibit import-
ant differences in ecology, morphology and life history traits
(Reid, 1996) yet remain relatively understudied. These sister
species, which started to diverge around 1 Ma (Tatarenkov,
1995), present a largely overlapping distribution along the
northeastern Atlantic from Iceland to the Iberian Peninsula
(Reid, 1996). At the local scale, L. obtusata is generally found in
the upper intertidal of less exposed shores and L. fabalis is pre-
dominant in the lower part of the intertidal range (Reid, 1996).
Within each species, particularly in L. fabalis, phenotypic vari-
ation (often referred to as ecotypes, see Johannesson, 2003) is
associated with selective pressures that vary at a microscale (e.g.
wave exposure, crab predation) (Rola´ n & Templado, 1987;
Rola´ n-Alvarez, Zapata & Alvarez, 1995; Kemppainen et al.,
2005). These observations suggest that habitat-related adapta-
tion could have played an important role in the diversification
of flat periwinkles both within and between species, offering
the opportunity to study the relevance of this mechanism in
driving progress along the speciation continuum (Seehausen
et al., 2014).
Gene flow is crucial to our understanding of speciation, because
hybridization between diverging populations, ecotypes or species
can reduce or promote reproductive isolation (e.g. through
reinforcement or adaptive introgression) (Abbott et al., 2013).
Shared mitochondrial haplotypes suggest that introgressive hybrid-
ization may have occurred between L. obtusata and L. fabalis,
although this hypothesis was not supported at the nuclear level
using microsatellites (Kemppainen et al., 2009). One reason for this
could be the limited availability of such nuclear markers in these
species. Microsatellite loci have proved suitable for identifying
hybridization in different taxa (e.g. Thielsch et al., 2012;
Vanhaecke et al., 2012). However, most microsatellites analysed in
flat periwinkles were primarily developed for other Littorina species
(e.g. L. saxatilis: Sokolov, Sokolova & Po¨ rtner, 2002; L. subrotundata:
Tie, Boulding & Naish, 2000; L. littorea: McInerney et al., 2009a).
Only a few of these loci amplify in both L. fabalis and L. obtusata
(Panova et al., 2008; McInerney et al., 2009b) and null alleles are
frequently detected (e.g. Panova et al., 2008; Kemppainen et al.,
2009), limiting their application.
The development of a cost-effective genetic approach to dis-
tinguish L. fabalis from L. obtusata (and their hybrids) is also
essential for intraspecific studies of differences between popula-
tions and ecotypes. For example, effective species discrimination
is necessary to ensure that L. obtusata is excluded from analyses
when attempting to characterize the divergence between L. fabalis
ecotypes. Although the two species are morphologically distinct,
many traits represent a phenotypic continuum without clear
boundaries (e.g. shell shape and size) (Reid, 1996). Diagnostic
differences are in fact restricted to adult genitalia (penis and
pallial oviduct) (Reid, 1996) and are difficult to assess for less
experienced researchers. Furthermore, the classification of males
and females relies on a single trait, and the genetic basis and
mode of inheritance (e.g. monogenic vs. polygenic; dominant vs.
co-dominant) of this may make it difficult to accurately identify
hybrid or introgressed individuals. To overcome these issues, we
used next-generation sequencing to develop a new panel of
microsatellites for L. fabalis that successfully cross-amplify in
L. obtusata, providing a useful resource for evolutionary and eco-
logical studies in flat periwinkles.
Microsatellite loci isolation was initially performed using 10
L. fabalis (eight females and two males) that were collected in
Canido (Galicia, northwestern Spain: 428110
46.0000
N, 88470
49.4800
W) during 2012. From each individual, genomic DNA
was extracted from headfoot tissue either with the EasySpin
Genomic DNA Tissue Kit (Citomed) or using a standard high-
salt protocol (Sambrook, Fritish & Maniatis, 1989). DNA from
the samples was then pooled in an equimolar concentration and
sent to GenoScreen (http://www.genoscreen.com/). Microsatellites
were identified using 454 GS-FLX sequencing (Roche Diagnostics)
# The Author 2015. Published by Oxford University Press on behalf of The Malacological Society of London, all rights reserved
Journal of The Malacological Society of London
Molluscan Studies
Journal of Molluscan Studies (2015) 1–5. doi:10.1093/mollus/eyv014
Journal of Molluscan Studies Advance Access published 18 April 2015
byguestonNovember23,2016http://mollus.oxfordjournals.org/Downloadedfrom
2. after enrichment for regions containing short tandem repeat
motifs as described by Malausa et al. (2011). Raw reads were
analysed with the QDD pipeline, which included quality
control, detection of tandem repeats and primer design
(Megle´ cz et al., 2010). This resulted in 410 candidate primer
pairs for microsatellite loci. A subset of 35 pairs (nine di-, nine
tri- and 17 tetra-nucleotide motifs) was then selected for amplifi-
cation tests. The forward primer of each marker was
fluorescence-labelled with 6-FAM (Stab Vida), HEX (Stab
Vida) or NED (Applied Biosystems) dyes. Loci were arranged
into four multiplex reactions according to various criteria:
similar annealing temperatures (from 58 to 62 8C), different
dyes and/or product sizes (between 90 and 316 bp), and low
probability of forming cross-dimers.
Thirty-five L. fabalis individuals (10 females and 25 males)
collected in Tira´ n (Galicia: 428160
1200
N, 88450
2300
W) in 2012, as
well as 35 L. obtusata individuals (10 females and 25 males) from
Rio de Moinhos (northern Portugal: 418340
00.4200
N, 88470
50.2900
W),
were used for amplification tests and subsequent genotyping.
Genomic DNA was extracted (from headfoot tissue) and quanti-
fied as described by Galindo, Mora´ n & Rola´ n-Alvarez (2009),
further adjusting the concentration of each sample to 20 ng/ml.
All 35 loci were first amplified in single reactions (i.e. not multi-
plexed) using four L. fabalis individuals to optimize PCR and geno-
typing conditions. Reactions were repeated using four L. obtusata
individuals to test cross-amplification. Loci with inconsistent or
absent amplification, with signatures of duplications and/or com-
plex peak patterns preventing objective genotyping were dis-
carded, as were all loci that resulted monomorphic in both
species. Loci passing these filters were then tested in different
multiplex combinations. This resulted in 17 loci (five di-, five
tri- and seven tetra-nucleotide motifs; GenBank accession
numbers: KP722159-KP722175), which were reorganized into
three multiplex reactions (Table 1) and amplified in the 70
samples from both species for genotyping. Each reaction con-
sisted of 20 ng of DNA, 4 ml of QIAGEN Multiplex kit, 0.2 mM
of each 6-FAM/HEX primer pair and 0.4 mM of each NED
primer pair in a final volume of 8 ml. PCR conditions comprised
an initial 15 min at 95 8C, followed by 30 cycles of 30 s at 94 8C,
90 s at 60 8C and 60 s at 72 8C, and a final 30 min at 60 8C.
One microlitre of a 1:20 dilution of each PCR product was
loaded along with 0.15 ml of GeneScan-400HD ROX size stand-
ard (Applied Biosystems) on an ABI 3730 sequencer (Applied
Biosystems). Capillary electrophoresis was outsourced to Stab
Vida (http://www.stabvida.com/) and genotype profiles were
evaluated in GeneMapper v. 3.7 (Applied Biosystems).
Hardy–Weinberg equilibrium (HWE) for each locus-population
pair and overall linkage disequilibrium (LD) between locus pairs
was evaluated in GENEPOP v. 4.2 (Rousset, 2008) using exact
probability tests with a Markov Chain (MC) algorithm under
the default parameters. The Bonferroni method (Rice, 1989)
was applied to correct for multiple tests. MICRO-CHECKER
v. 2.2.3 (Van Oosterhout et al., 2004) was further used to inspect
possible causes of HWE departures (e.g. null alleles, stuttering
and/or large allele dropout). The mean number of alleles per
locus (A), allele frequencies, nonbiased expected (He) and
observed (Hobs) heterozygosity for each locus-population pair
were estimated with GENETIX v. 4.05 (Belkhir et al., 1996) and
the differentiation between the two species was quantified by
FST (Weir & Cockerham, 1984) estimated in FSTAT v. 2.9.3.2
(Goudet, 1995).
STRUCTURE v. 2.3.4 (Falush, Stephens & Pritchard, 2007)
was used to assess the power of the developed markers, first to
distinguish the two species and second to identify different types
of hybrids between them. For the former, we analysed the multi-
locus genotypes of the 70 individuals from Tira´ n and Rio de
Moinhos (dataset 1, real data). As we detected no admixture
between the species sampled at these locations (Fig. 1A), we
used a simulation approach to test for hybrid detection.
Individuals from different classes of hybrids (F1 s, F2 s and
backcrosses with parental species—BF with L. fabalis and BO
with L. obtusata) were simulated using HYBRIDLAB v. 1.0
(Nielsen, Bach & Kotlicki, 2006). To generate F1s, the multilo-
cus genotypes of the individuals from Tira´ n and Rio de Moinhos
(real data) were treated as parental species (L. fabalis and L.
obtusata, respectively). F1 genotypes were generated by random-
ly drawing an allele from each parental species as a function of
their frequencies (Nielsen et al., 2006). To generate F2s, two dif-
ferent sets of simulated F1s were used as the two parental
species. To generate backcrosses, one simulated set of F1s and
Table 1. Primer information and GenBank accession numbers for 17 microsatellite loci in Littorina fabalis and L. obtusata.
Locus Dye Motif Forward primer (5′
–3′
) Reverse primer (5′
–3′
) GenBank acc. no.
Multiplex 1
FP1 HEX gttt CCCAGACAATGCAGCCTAC CGGTAACTGAGTTGTGCAGC KP722159
FP2 NED aaac ACATGGGATACGACTACCCG AGCCTAGCTGCTACGTCCAA KP722160
FP3 FAM caaa TTTGCATACACCCGTCTAACC GCTATTTCATTAAGCCGCCA KP722161
FP4 HEX gct TCACTTACCTCAAACCTTGCG CCACAGGCGGGGTGTAAG KP722162
FP5 NED ttg CGCTACGCCACTTCGTTTA AATCGGAGAACAAAACCACG KP722163
FP6 FAM gtt ACGCCCAGAATTGCCTAAAT GCTTGTTTATTGACAGGCAGC KP722164
Multiplex 2
FP7 HEX ctt TTGTCAAGAATGTTGGTTCCC ATCCGGAATCGACAAGTGAC KP722165
FP8 NED caa CAGCACAAGGCGGTTCAG TCCTATTTGAAGATGCGGTG KP722166
FP9 NED ca TTTTGTTAACACGTGGCAGTT TTGGTGAGTGCGTGCATTAT KP722167
FP10 FAM ac TGGTACGGACGAGGCTCTTA ATTGCTTGAATGCCCGTTAC KP722168
FP11 HEX ag CATACAATCCGTCCCTCTCC TACTCGAACAGGAACGAGGC KP722169
FP12 HEX atcc CACCCACCCCTATTACCCA GGGTTGATGGATGAGTGGAT KP722170
Multiplex 3
FP13 NED tgtt ACCGCACAGCTACACGAAG TCGTGTTTCATGATGCCCTAT KP722171
FP14 HEX tc TGTTGCTCTGCAGATTATGACA GATCGATGCCCTGACATAGC KP722172
FP15 NED agtc GTTTTGGTTGAATGTTGGGC GACAGAAAACAGAAACAACGAAA KP722173
FP16 FAM ac CTCATGCTGTTCCTGGTTGA TGCGTGGTTTAAATTGTTCTTG KP722174
FP17 FAM aaac TGAGACATGAAGCCTGTGCT AATACAATCTGGTGTCTGCGG KP722175
RESEARCH NOTE
2
byguestonNovember23,2016http://mollus.oxfordjournals.org/Downloadedfrom
3. one of the original (real) populations (Tira´ n to generate BF and
Rio de Moinhos to generate BO) were provided as parental
species. Finally, the real data (70 individuals from Tira´ n and
Rio de Moinhos) were combined with the simulated data (20
individuals of each hybrid class) in a second dataset (dataset 2,
Fig. 1B). We ran STRUCTURE on both datasets, using the 15
markers that amplified in both species (see below). In both
cases, the number of genetic clusters (K) ranged from 1 to 3 and
10 replicate runs were performed for each K, consisting of
1,000,000 iterations (with 100,000 as burn-in), assuming an ad-
mixture model, uncorrelated allele frequencies and without
prior population information. The results from the multiple
replicates for the K with the highest likelihood (K ¼ 2, according
to STRUCTURE HARVESTER; Earl & vonHoldt, 2012)
were combined using the Greedy algorithm in CLUMPP
v. 1.1.2 (Jakobsson & Rosenberg, 2007) and the output was
plotted using DISTRUCT v. 1.1 (Rosenberg, 2004).
Table 2 summarizes the information on the 17 microsatellite
loci developed in this study. Despite being primarily developed
for L. fabalis, only two loci (FP7 and FP13) failed to cross-
amplify in L. obtusata (Table 2). Overall, the total number of
alleles per locus ranged from three to 21 and was higher on
average in L. fabalis than in L. obtusata (5.88 vs. 3.35). Three loci
(FP3, FP14 and FP16) were monomorphic in L. fabalis, but not
in L. obtusata, whereas the opposite was observed for two other
loci (FP15 and FP17) (Table 2). At least four loci (FP7, FP8,
FP10 and FP12) presented alleles with unexpected sizes, suggest-
ing imperfect repetition motifs or indels within the amplified
fragment. Three out of 27 tests showed significant deviations
from HWE expectations (all in L. fabalis; Table 2), but only one
remained significant following Bonferroni correction (FP13,
FIS ¼ 0.474). MICRO-CHECKER indicated that HWE devi-
ation at this locus is likely due to the presence of null alleles, al-
though other factors cannot be excluded (e.g. Wahlund effect,
selection against hybrids, nonrandom mating, etc.). Ten out of
272 tests showed significant LD between pairs of loci, but none
remained significant after Bonferroni correction. Considering
only polymorphic loci, observed heterozygosity ranged from
0.03 to 0.97 (mean ¼ 0.61) in L. fabalis and from 0.03 to 0.83
(mean ¼ 0.47) in L. obtusata and similar averages were obtained in
Figure 1. Cluster membership for individuals identified by STRUCTURE for K ¼ 2. Results for two different datasets are presented. A. Dataset 1,
using real genotypic data from 70 individuals from Rio de Moinhos (Littorina obtusata) and Tira´ n (L. fabalis). B. Dataset 2, combining simulated data
(20 individuals from each of the four hybrid classes: F1, F2, BO and BF) with the same real data (L. obtusata and L. fabalis). Membership is represented
on the y-axis: 1 corresponds to 100% membership to one of the two genetic clusters (black bars, L. obtusata; grey bars, L. fabalis). Abbreviations: F1,
first generation hybrids (resulting from the cross between the two parental species); F2, second generation hybrids (resulting from the cross between
F1s); BO, individuals resulting from the backcross of F1s with L. obtusata; BF, individuals resulting from the backcross of F1s with L. fabalis.
Table 2. Characterization of 17 microsatellite loci in Littorina fabalis (F) and L. obtusata (O).
Locus N Allele size range (bp) A He Hobs HWE FST
F O F O F O Total F O F O F O
FP1 35 35 177–219 181–185 8 2 10 0.8261 0.0286 0.8286 0.0286 0.3177 – 0.4250
FP2 35 35 110–138 82–126 4 7 11 0.5097 0.7660 0.7714 0.4571 0.0752 0.8137 0.3610
FP3 30 35 208 204–208 1 2 3 0 0.2687 0 0.3143 – 0.5656 0.8310
FP4 35 35 237–243 237–243 2 2 4 0.5068 0.4969 0.2857 0.5143 0.0162* 1.0000 20.0030
FP5 35 35 176–233 176–192 15 5 20 0.9275 0.6642 0.9714 0.5714 0.2492 0.0585 0.1480
FP6 35 35 281–331 284–325 10 8 18 0.8609 0.7412 0.8000 0.7143 0.2208 0.7484 0.1700
FP7 33 0 144–161 – 7 0 7 0.7300 – 0.7576 – 0.5092 – –
FP8 35 35 231–267 239–248 7 6 13 0.4360 0.7946 0.3714 0.8286 0.0435* 0.8878 0.3790
FP9 35 35 75–99 79–89 7 2 9 0.5925 0.1093 0.6286 0.1143 0.7960 1.0000 0.6310
FP10 35 35 184–224 182–194 17 4 21 0.9048 0.4422 0.9714 0.5143 0.4878 1.0000 0.2980
FP11 35 34 238–266 248–268 6 10 16 0.7097 0.8521 0.7714 0.8235 0.5398 0.1109 0.2180
FP12 35 35 132–144 133–136 2 2 4 0.0286 0.3578 0.0286 0.4000 – 0.6513 0.8070
FP13 34 0 243–275 – 3 0 3 0.5535 – 0.2941 – 0.001#
– –
FP14 35 35 195 197–201 1 3 4 0 0.6282 0 0.7429 – 0.5873 0.6870
FP15 35 35 103–120 111 4 1 5 0.4443 0 0.4857 0 0.8102 – 0.1830
FP16 35 34 235 233–235 1 2 3 0 0.1633 0 0.1176 – 0.2136 0.9110
FP17 35 33 101–133 161 5 1 6 0.6219 0 0.5429 0 0.1808 – 0.6820
Abbreviations: N, number of genotyped individuals; A, number of alleles; He, nonbiased expected heterozygosity, Hobs, observed heterozygosity; HWE, P-values of
the exact test for Hardy–Weinberg equilibrium.
*P , 0.05; #
P , 0.01.
RESEARCH NOTE
3
byguestonNovember23,2016http://mollus.oxfordjournals.org/Downloadedfrom
4. terms of expected heterozygosity (Table 2). Genetic differentiation
(FST) between the two species ranged from 0 to 0.91 across dif-
ferent loci (overall FST ¼ 0.4758; Table 2).
Figure 1A demonstrates that these new microsatellites are able
to distinguish genetically between L. fabalis and L. obtusata. This
establishes their usefulness for species identification/confirmation
in both males and females (as well as in juveniles), even when
impractical or not possible to do so based on morphology.
Additionally, the power of these microsatellites to detect differ-
ent classes of hybrids between the two species is clearly shown in
Figure 1B, where the simulated hybrid genotypes are identified
correctly. No signatures of hybridization were found in samples
analysed here. Nonetheless, the observation, even if rare, of
interspecific mating pairs in the field (E. Rola´ n-Alvarez, person-
al communication), and the existence of mitochondrial DNA
haplotypes shared between L. fabalis and L. obtusata in Northern
Europe (Kemppainen et al., 2009) and in the Iberian Peninsula
(R. Faria, unpub.), suggests that it does occur. Our study has
identified microsatellite loci that can be used to assess the role of
hybridization in the diversification of flat periwinkles. Moreover,
given the high levels of polymorphism found, we expect that they
will also be informative for addressing the intraspecific evolution-
ary history of L. fabalis and L. obtusata. For example, they could
be applied in the assessment of parallel evolution (e.g. Panova,
Hollander & Johannesson, 2006), the characterization of mul-
tiple paternity effects on population genetic structure and vari-
ability (e.g. Panova et al., 2010; Rafajlovic´ et al., 2013) and the
study of local adaptation (e.g. Schmidt et al., 2007) among others.
To our knowledge, this is one of the largest panels of species-
specific microsatellite loci developed for a Littorina species, a re-
source that will likely contribute to the emergence of flat periwin-
kles as a model to explore the ecological aspects of diversification
along the speciation continuum.
ACKNOWLEDGEMENTS
We thank Teresa Muin˜ os Lago for her assistance in sample col-
lection and Mark Ravinet for the English revision of the manu-
script. This study was funded by FEDER funds through the
Operational Programme for Competitiveness Factors –
COMPETE and by National Funds through FCT – Foundation
for Science and Technology under the PTDC/BIA-EVF/113805/
2009 and FCOMP-01-0124-FEDER-014272. R.F. is financed by
FCT under the Programa Operacional Potencial Humano –
Quadro de Refereˆ ncia Estrate´ gico Nacional from the European
Social Fund and the Portuguese Ministe´ rio da Educac¸ a˜ o e
Cieˆ ncia through the postdoctoral fellowship SFRH/BPD/89313/
2012. J.G. is currently supported by a Xunta de Galicia postdoc-
toral fellowship (Modalidade B). C.P. was funded by the
Lifelong Learning Programme (Leonardo da Vinci) - 2012-1-
PT1-LEO02-11437.
REFERENCES
ABBOTT, R., ALBACH, D., ANSELL, S., ARNTZEN, J.W., BAIRD,
S.J.E., BIERNE, N., BOUGHMAN, J., BRELSFORD, A.,
BUERKLE, C.A., BUGGS, R., BUTLIN, R.K., DIECKMANN,
U., EROUKHMANOFF, F., GRILL, A., CAHAN, S.H.,
HERMANSEN, J.S., HEWITT, G., HUDSON, A.G., JIGGINS,
C., JONES, J., KELLER, B., MARCZEWSKI, T., MALLET, J.,
MARTINEZ-RODRIGUEZ, P., MO¨ ST, M., MULLEN, S.,
NICHOLS, R., NOLTE, A.W., PARISOD, C., PFENNIG, K.,
RICE, A.M., RITCHIE, M.G., SEIFERT, B., SMADJA, C.M.,
STELKENS, R., SZYMURA, J.M., VA¨ INO¨ LA¨ , R., WOLF,
J.B.W. & ZINNER, D. 2013. Hybridization and speciation. Journal
of Evolutionary Biology, 26: 229–246.
BELKHIR, K., BORSA, P., GOUDET, J., CHIKHI, L.,
RAUFASTE, N. & BONHOMME, F. 1996. GENETIX, logiciel
sous Windows TM pour la ge´ ne´ tique des populations, Version 4.03.
Available at: http://kimura.univ-montp2.fr/genetix/.
BUTLIN, R., SAURA, M., CHARRIER, G., JACKSON, B., ANDRE´ ,
C., CABALLERO, A., COYNE, J., GALINDO, J., GRAHAME, J.,
HOLLANDER, J., KEMPPAINEN, P., MARTI´ NEZ-FERNA´ NDEZ,
M., PANOVA, M., QUESADA, H., JOHANNESSON, K. &
ROLA´ N-ALVAREZ, E. 2014. Parallel evolution of local adaptation
and reproductive isolation in the face of gene flow. Evolution, 68:
935–949.
EARL, A. & VONHOLDT, B. 2012. STRUCTURE HARVESTER: a
website and program for visualizing STRUCTURE output and
implementing the Evanno method. Conservation Genetics Resources, 4:
359–361.
FALUSH, D., STEPHENS, M. & PRITCHARD, J. 2007. Inference of
population structure using multilocus genotype data: dominant
markers and null alleles. Molecular Ecology Notes, 7: 574–578.
GALINDO, J. & GRAHAME, J.W. 2014. Ecological speciation and
the intertidal snail Littorina saxatilis. Advances in Ecology, doi:10.1155/
2014/239251.
GALINDO, J., MORA´ N, P. & ROLA´ N-ALVAREZ, E. 2009.
Comparing geographical genetic differentiation between candidate
and noncandidate loci for adaptation strengthens support for
parallel ecological divergence in the marine snail Littorina saxatilis.
Molecular Ecology, 18: 919–930.
GOUDET, J. 1995. Fstat version 1.2: a computer program to calculate
F statistics. Journal of Heredity, 86: 485–486.
JAKOBSSON, M. & ROSENBERG, N. 2007. CLUMPP: a cluster
matching and permutation program for dealing with label switching
and multimodality in analysis of population structure. Bioinformatics,
23: 1801–1806.
JOHANNESSON, K. 2003. Evolution in Littorina: ecology matters.
Journal of Sea Research, 49: 107–117.
KEMPPAINEN, P., PANOVA, M., HOLLANDER, J. &
JOHANNESSON, K. 2009. Complete lack of mitochondrial
divergence between two species of NE Atlantic marine intertidal
gastropods. Journal of Evolutionary Biology, 22: 2000–2011.
KEMPPAINEN, P., VAN NES, S., CEDER, C. & JOHANNESSON,
K. 2005. Refuge function of marine algae complicates selection in an
intertidal snail. Oecologia, 143: 402–411.
MALAUSA, T., GILLES, A., MEGLE´ CZ, E., BLANQUART, H.,
DUTHOY, S., COSTEDOAT, C., DUBUT, V., PECH, N.,
CASTAGNONE-SERENO, P., DE´ LYE, C., FEAU, N., FREY, P.,
GAUTHIER, P., GUILLEMAUD, T., HAZARD, L., LE CORRE,
V., LUNG-ESCARMANT, B., MALE´ , G., FERREIRA, S. &
MARTIN, J.F. 2011. High-throughput microsatellite isolation
through 454 GS-FLX Titanium pyrosequencing of enriched DNA
libraries. Molecular Ecology Resources, 11: 638–644.
MCINERNEY, C.E., ALLCOCK, A.L., JOHNSON, M.P. & PRODO¨ HL,
P.A. 2009a. Characterization of polymorphic microsatellites for the
periwinkle gastropod, Littorina littorea (Linnaeus, 1758) and their cross-
amplification in four congeners. Conservation Genetics, 10: 1417–1420.
MCINERNEY, C.E., ALLCOCK, A.L., JOHNSON, M.P. & PRODO¨ HL,
P.A. 2009b. Characterization of polymorphic microsatellites for the
rough periwinkle gastropod, Littorina saxatilis (Olivi, 1792) and their
cross-amplification in four congeners. Conservation Genetics, 10: 1989–1992.
MEGLE´ CZ, E., COSTEDOAT, C., DUBUT, V., GILLES, A.,
MALAUSA, T., PECH, N. & MARTIN, J.F. 2010. QDD: a
user-friendly program to select microsatellite markers and design
primers from large sequencing projects. Bioinformatics, 26: 403–404.
NIELSEN, E.E., BACH, L.A. & KOTLICKI, P. 2006. HYBRIDLAB
(version 1.0): a program for generating simulated hybrids from
population samples. Molecular Ecology Notes, 6: 971–973.
PANOVA, M., BOSTRO¨ M, J., HOFVING, T., ARESKOUG, T.,
ERIKSSON, A., MEHLIG, B., MA¨ KINEN, T., ANDRE´ , C. &
JOHANNESSON, K. 2010. Extreme female promiscuity in a
non-social invertebrate species. PLoS One, 5: e9640.
PANOVA, M., HOLLANDER, J. & JOHANNESSON, K. 2006.
Site-specific genetic divergence in parallel hybrid zones suggests
nonallopatric evolution of reproductive barriers. Molecular Ecology,
15: 4021–4031.
RESEARCH NOTE
4
byguestonNovember23,2016http://mollus.oxfordjournals.org/Downloadedfrom
5. PANOVA, M., MA¨ KINEN, T., FOKIN, M., ANDRE´ , C. &
JOHANNESSON, K. 2008. Microsatellite cross-species amplification
in the genus Littorina and detection of null alleles in Littorina saxatilis.
Journal of Molluscan Studies, 74: 111–117.
RAFAJLOVIC´ , M., ERIKSSON, A., RIMARK, A., HINTZ-SALTIN,
S., CHARRIER, G., PANOVA, M., ANDRE´ , C., JOHANNESSON,
K. & MEHLIG, B. 2013. The effect of multiple paternity on genetic
diversity of small populations during and after colonisation. PLoS One,
8: e75587.
REID, D.G. 1996. Systematics and evolution of Littorina. Ray Society, London.
RICE, W.R. 1989. Analyzing tables of statistical tests. Evolution, 43:
223–225.
ROLA´ N, E. & TEMPLADO, J. 1987. Consideraciones sobre el complejo
Littorina obtusata-mariae (Mollusca, Gastropoda, Littorinidae) en el
noroeste de la penı´nsula Ibe´ rica. Thalassas, 5: 71–85.
ROLA´ N-ALVAREZ, E., ZAPATA, C. & ALVAREZ, G. 1995. Distinct
genetic subdivision in sympatric and sibling species of the genus
Littorina (Gastropoda: Littorinidae). Heredity, 75: 1–9.
ROSENBERG, N. 2004. DISTRUCT: a program for the graphical
display of population structure. Molecular Ecology Notes, 4: 137–138.
ROUSSET, F. 2008. Genepop’007: a complete re-implementation of the
genepop software for Windows and Linux. Molecular Ecology
Resources, 8: 103–106.
SAMBROOK, J., FRITSCH, E.F. & MANIATIS, T. 1989. Molecular
cloning: a laboratory manual. Cold Spring Harbor Press, New York.
SCHMIDT, P.S., PHIFER-RIXEY, M., TAYLOR, G.M. &
CHRISTNER, J. 2007. Genetic heterogeneity among intertidal
habitats in the flat periwinkle, Littorina obtusata. Molecular Ecology, 16:
2393–2404.
SEEHAUSEN, O., BUTLIN, R.K., KELLER, I., WAGNER, C.E.,
BOUGHMAN, J.W., HOHENLOHE, P.A., PEICHEL, C.L.,
SAETRE, G.P., BANK, C., BRA¨ NNSTRO¨ M, A., BRELSFORD,
A., CLARKSON, C.S., EROUKHMANOFF, F., FEDER, J.L.,
FISCHER, M.C., FOOTE, A.D., FRANCHINI, P., JIGGINS,
C.D., JONES, F.C., LINDHOLM, A.K., LUCEK, K., MAAN,
M.E., MARQUES, D.A., MARTIN, S.H., MATTHEWS, B.,
MEIER, J.I., MO¨ ST, M., NACHMAN, M.W., NONAKA, E.,
RENNISON, D.J., SCHWARZER, J., WATSON, E.T., WESTRAM,
A.M. & WIDMER, A. 2014. Genomics and the origin of species.
Nature Reviews Genetics, 15: 176–192.
SOKOLOV, E.P., SOKOLOVA, I.M. & PO¨ RTNER, H.O. 2002.
Polymorphic microsatellite DNA markers from the marine gastropod
Littorina saxatilis. Molecular Ecology Notes, 2: 27–29.
TATARENKOV, A.N. 1995. Genetic divergence between sibling
species Littorina mariae Sacchi & Rastelli and L. obtusata (L.)
(Mollusca: Gastropoda) from the White Sea. Ophelia, 40: 207–218.
THIELSCH, A., VO¨ LKER, E., KRAUS, R.H.S. & SCHWENK, K.
2012. Discrimination of hybrid classes using cross-species
amplification of microsatellite loci: methodological challenges and
solutions in Daphnia. Molecular Ecology Resources, 12: 697–705.
TIE, A.D., BOULDING, E.G. & NAISH, K.A. 2000. Polymorphic
microsatellite DNA markers for the marine gastropod Littorina
subrotundata. Molecular Ecology, 9: 108–110.
VANHAECKE, D., DE LEANIZ, C.G., GAJARDO, G., YOUNG, K.,
SANZANA, J., ORELLANA, G., FOWLER, D., HOWES, P.,
MONGZON-ARGUELLO, C. & CONSUEGRA, S. 2012. DNA
barcoding and microsatellites help species delimitation and hybrid
identification in endangered galaxiid fishes. PLoS One, 7: e32939.
VAN OOSTERHOUT, C., HUTCHINSON, W., WILLS, D. &
SHIPLEY, P. 2004. MICRO-CHECKER: software for identifying
and correcting genotyping errors in microsatellite data. Molecular
Ecology Notes, 4: 535–538.
WEIR, B.S. & COCKERHAM, C.C. 1984. Estimating F-statistics for
the analysis of population structure. Evolution, 38: 1358–1370.
RESEARCH NOTE
5
byguestonNovember23,2016http://mollus.oxfordjournals.org/Downloadedfrom