Discussion
In this study, we present the first analysis of population structure in European sardine across a large part of its distribution range using whole‐genome sequencing data. A number of mechanisms have been suggested to explain how population structure can evolve in an environment without any complete physical barrier to gene flow, including local adaptation, habitat discontinuity, different habitat preferences and behavior, sexual selection, oceanographic currents , isolation by distance and limited dispersal capabilities (Bremer et al., 2005; Díaz-Jaimes et al., 2010; Faria et al., 2021; Kumar & Kumar, 2018; Patarnello et al., 2007).
Altogether, the assessment of nuclear genome sequences by means of individual ancestry information, principal component analysis (Figure 1B and Figure 1C) and differentiation (FST) among populations from different geographic regions (Figure 2), supports that the European sardine comprises three main stocks: “West” that includes individuals from Azores and Madeira (part of the Macaronesian region in the Atlantic), “Central” that corresponds to Iberia (the center of the sampling distribution), and “East” that gathers the Mediterranean samples and those from the Canary Islands. The observed genetic differentiation between Mediterranean and Atlantic populations (except the Canary Islands) is in agreement with previous phenotypic and genetic studies based on mtDNA (Andreu, 1969; Atarhouch et al., 2006; Parrish et al., 1989), suggesting the existence of a phylogeographic break between the South of Portugal and Mediterranean populations. The Almeria-Oran Front is likely to be responsible for reduction in gene flow between populations in each side, as previously observed in sardine (Ramon & Castro, 1997) and other species (Pita et al., 2014; Ouagajjou & Presa, 2015), as the Spanish Mediterranean populations have only a small proportion of ancestry associated with the Central cluster (Figure 1B). Instead, the shared pattern of ancestry of the individuals from the Alboran Sea and the Gulf of Cadiz indicates that the Strait of Gibraltar is not such a strong barrier as previously suggested (Jeema et al., 2015; Alemany & Alvarez, 1993; Ramon & Castro, 1997).
The population from the Canary Islands has a Mediterranean ancestry, and its divergence from the Western group has also been suggested by Kasapidis et al (2011) using microsatellite data, which further revealed a high differentiation between Azores/Madeira and the other Atlantic populations. Notably, populations from these two archipelagos cluster together genetically, despite Madeira being geographically closer to Canary Islands and almost at the same distance to Iberia as it is to Azores. This strongly suggests a barrier to gene flow between the region formed by these two archipelagos and the other populations analyzed in this study, including Canary Islands and Iberia. This genetic division can be caused by currents, isolation by distance and lack of suitable habitat between these regions, local adaptation to different environmental conditions or other reasons. The fact that we did not observe a pattern consistent with isolation by distance and that we excluded markers putatively under selection argue against the latter. Nonetheless, this needs further investigation.
The higher differentiation of sardine populations from Azores and Madeira is also clear in the mitogenome tree (Figure 3). Although two other main clades are observed, they are formed by haplotypes from individuals with a very different nuclear-based ancestry. Thus, it is not easy to objectively pinpoint the geographic origin of these mtDNA clades.
Discordance between differentially inherited markers can simply result from stochastic patterns of lineage sorting, but it can also be indicative of introgression (Lavretsky et al., 2014). Patterns suggesting admixture between the three genetic clusters were also observed with the nuclear data in all populations except Madeira. Given the lower effective population size of mtDNA when compared to nuclear DNA, we would expect to see it more sorted within each region. The fact that haplotypes from the main clades in the mitochondrial tree are present across almost the entire distribution could eventually favor introgression over incomplete lineage sorting.
An important piece of information that can help us to disentangle the role of gene flow versus shared ancestral polymorphism is the geographic pattern of differentiation. Genetic differentiation is lower between closer geographic populations within the East and Center clusters (Figure 2). Furthermore, we observed that the proportion of individuals with pure nuclear ancestry is higher in populations that are geographically more distant from populations with a different ancestry, suggesting that at least some of the patterns observed with nuclear and mtDNA genomes can indeed be created by gene flow between populations from these genetic clusters. Although this needs to be further confirmed using model-based approaches, if true, it provides additional support that the barriers involved in the differentiation between these three genetic clusters are only partial. Furthermore, the ancestry patterns observed between populations from the Central and Eastern clusters could suggest bidirectional gene flow between populations from Iberia and Mediterranean populations outside Iberia, which is also supported by the more even distribution of the two main mitochondrial haplotypes between these regions.
Western cluster ancestry is also observed in populations from the Center, Canaries’ Island and mainly in the Western Mediterranean populations. Although these patterns are compatible with admixture, gene flow between populations from the Eastern and Western clades are more difficult to explain. This discordance between molecular markers can also reflect the fact that regional populations of sardines seem to undergo periodic extinctions and recolonizations (Grant & Bowen, 1998). A recolonization of the Mediterranean from a refugium in the West African coast, as it has been suggested for anchovies (Magoulas et al., 2006), a species that shares several traits with sardines (Checkley et al., 2017), could potentially explain the admixed ancestry of the Canary Islands and the Eastern cluster (Figure 2).
Finally, we found that genomic regions corresponding to the top outliers of genetic differentiation are located in areas of low recombination (Figure 3), suggesting that genetic architecture can be contributing in some extent to the observed pattern of population structure. Interestingly, one of these regions include genes related to otolith formation, and otolith shapes have been found to divide the Atlantic and Mediterranean sardines (Jeema et al., 2015).
Conclusions
Our main results provide evidence for three main genetic clusters of sardine populations across the analyzed specimens, suggesting at least two important barriers to gene flow. Although these do not seem complete, with gene flow possibly occurring between the three main phylogeographic regions identified, they seem to be strong enough to maintain populations genetically differentiated following their own evolutionary trajectory. Our results thus offer an important baseline for further studies trying to identify the nature of these and other possible barriers between sardine populations, which can be compared with the phylogeographic patterns of other organisms with a similar distribution. Finally, the differentiation patterns reported here together with the genetic resources generated for this commercially important species, offers information of strategic importance for transnational stock management of this highly exploited species towards sustainable fisheries.
Acknowledgments
All figures were edited in Inkscape (
http://www.inkscape.org/). Thanks to Alessandro Laio, Amélia Fonseca, Ludovic Dickel, Patrícia Campos, Sara Rocha, Yorgos Athanasidis and Sabour Brahim, for supplying tissue samples. We would also like to thank Anders Albrechtsen, Katherine Richardson, Lounes Chikhi, Jonas Meisner, Jørgen Bendtsen, Rasmus Heller, Ricardo Pereira, and Stephen Sabatino for advice. The authors gratefully acknowledge the following for funding their research: Villum Fonden Young Investigator Grant VKR023446 (R.D.F.); Fundação para a Ciência e a Tecnologia (FCT), Portugal, Scientific Employment Stimulus Initiative, grants CEECIND/00627/2017 to E.F and CEECIND/01799/2017 to P.F.C.. R.D.F. thanks the VILLUM FONDEN for the Center for Global Mountain Biodiversity (grant no 25925). M.P. and I.R. thank the Axencia Galega de Innovación (GAIN), Xunta de Galicia, Spain, for its funding of the AQUACOV and MERVEX Research Groups (grants IN607B 2018/14 and IN607-A 2018/4) and IMPRESS project supported by Spanish MICINN through grant RTI2018-099868-B-I00. R. F. is currently funded by FEDER through the Operational Competitiveness Factors Program (COMPETE) and by FCT (project “Hybrabbid”, grants PTDC/BIA-EVL/30628/2017 and POCI-01-0145-FEDER-030628). E.F. research was funded by the project The Sea and the Shore, Architecture and Marine Biology: The Impact of Sea Life on the Built Environment Project No. POCI-01-0145-FEDER-029537, co-financed by COMPETE 2020, Portugal 2020 and the European Union through the European Regional Development Fund (ERDF). L.F.C.C research was funded by: project VALORMAR (reference nr. 24517), supported by COMPETE2020, LISBOA2020, ALGARVE2020, PORTUGAL2020, through ERDF; strategic funding UIDB/04423/2020 through FCT and ERDF, in the framework of the programme PT2020. We thank the scientific and technical staff and the crew of the PELACUS0315 and SARLINK oceanographic surveys conducted by the Instituto Español de Oceanografía. Alboran Sea samples were collected during the SARLINK oceanographic survey. Samples from Galicia, Cantabrian Sea and Bay of Biscay were collected during the PELACUS 0315 Oceanographic survey, funded by the EU through the European Maritime and Fisheries Fund (EMFF) within the National Program of collection, management and use of data in the fisheries sector and support for scientific advice regarding the Common Fisheries Policy.
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Author contributions
R.D.F. and L.F.C. designed the study; F.T., M.N., S.A., M.P., I.R., P.C., A.J-R., M.T.G.S. organized and executed the sample collection; P.F.C., A.R-I. and E.F. performed the laboratory work; R.D.F. analyzed the data with contributions from G.B., L.B., R.F., A.M.M.; R.D.F., P.F.C., E.F. and L.F.C. wrote the manuscript with contributions from all authors. All authors have read and approved the manuscript.