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Securing genetic integrity in freshwater pearl mussel propagation and captive breeding


Securing genetic integrity is of key importance in conservation-oriented captive breeding programs releasing juveniles into the wild. This is particularly true for species such as the endangered freshwater pearl mussel (Margaritifera margaritifera) for which a number of captive breeding facilities has been established in Europe. The core objective of this study was to compare the genetic constitution of 29 cohorts of captive-bred freshwater pearl mussels from five different breeding facilities in Austria, France, Luxembourg and Germany, with their original 14 source populations from nine major European drainages, based on microsatellite markers. Captive-bred mussels represented 11 different genetic clusters, suggesting an important contribution of the breeding stations to securing the genetic diversity of the species. In almost all cases, the cultured offspring closely resembled the genetic constitution of the source mussels as revealed from the STRUCTURE analysis and the generally high assignment of offspring to the original source populations. The majority of captive-bred cohorts had an increased inbreeding coefficient and decreased genetic variability compared to their source populations as measured by AR and HO. Highest numbers of deformed juveniles coincided with very low levels of HO < 0.05. Since erosion of genetic diversity in captive breeding was mostly evident in individual year-cohorts, long-term breeding over multiple years can minimize such effects. The systematic selection of priority populations for conservation, effective breeding strategies avoiding effects of in- and outbreeding by genetically informed selection of parent individuals, and a network of collaboration among the different breeding facilities would be very useful to increase resilience and effectiveness.


Freshwater biodiversity is globally in decline, with freshwater mussels being among the most affected taxonomic groups1,2. One of the species that receives greatest attention is the freshwater pearl mussel (Margaritifera margaritifera) which simultaneously fulfills the criteria of indicator, keystone, flagship and umbrella species3. Freshwater pearl mussels can reach ages of more than 100 years and have an exceptional life cycle that involves a parasitic life stage on a fish host that can either be Atlantic salmon (Salmo salar), brown trout (Salmo trutta), or both in European populations4,5. Degradation of pearl mussel habitats, mostly related to siltation and colmation of interstitial spaces in the stream bed where juvenile pearl mussels burrow, have resulted in a lack of recruitment and severe declines of many pearl mussel populations throughout their European range6,7. Since restoration of stream beds requires consideration of entire catchments and the restoration of natural flow dynamics8, this approach is time-consuming and costly. At the same time, many pearl mussel populations are overaged and expected to die out in the near future. Since the first descriptions of the ongoing threats and population declines9, the downward trend of populations has even become worse7. This development has prompted the creation of a first European CEN standard for a single species10 as well as several captive breeding efforts in different countries11,12,13,14. Captive breeding of freshwater pearl mussel was first established in the Czech Republic by Jaroslav Hruška11 and is mostly based on induced release of glochidia larvae from parent mussels, a subsequent infestation and holding of fish hosts as well as collection and raising of dropped-off juveniles14.

Due to the strong conservation interest in freshwater pearl mussel, its genetic constitution has been studied in depth both throughout its European15,16,17,18,19,20,21,22 as well as its North American23 distributions, facilitating the consideration of priority populations for conservation in captive breeding. A wise selection of parents or an annual replacement of breeders can help secure the genetic diversity in captive breeding efforts. Still, there are multiple factors that may compromise the genetic constitution of captive-bred mussels compared to their parent populations. For instance, the selection of small numbers of parent mussels that are not representative for the genetic constitution of the entire population can already narrow the basis of genetic variability within the breeding program. During infestation of host fish, the compatibility of the used species and strains among mussel and fish as well as the age of the fish all can have effects on attachment rates, survival and growth5,24,25. Physiology of the host fish immune system related to temperature26, the effects of different loading densities of mussel larvae on swimming performance of the host27 as well as the duration of the parasitic phase28,29 and associated nutrient transfer from the host to the mussel30 all have a potential selective effect on the mussels during the parasitic phase. In the subsequent post-parasitic (i.e. juvenile) phase, stock origin and environmental conditions31, food quantity as well as water and sediment quality32,33,34, but also changing of culture systems and the cleaning regimes35 were found to affect survival and growth. Generally, mortalities are highest until the juveniles reach the first millimeter36.

In order to make the most of recent advances in freshwater mussel propagation and restoration37, consideration of genetic effects during the breeding process and objective evaluation of ongoing breeding activities is needed yet still lacking. In addition to the technical optimization of breeding facilities for freshwater mussels38, such information can be useful in identifying the most suitable captive breeding techniques for retaining a maximum of the genetic-evolutionary potential of mussels3. The core objective of this study thus was to analyze the genetic constitution of captive-bred freshwater pearl mussels from different European breeding facilities and compare their genetic diversity and differentiation with the original populations. These served as a source for the parent mussels and captive-bred juveniles have been, or are intended to be released into the same streams. Specifically, we hypothesized that (1) breeding efforts would be suitable to secure the genetic identity of the captive bred mussels as indicated by low genetic differentiation between original populations and captive-bred juveniles, (2) there would be no decrease of the genetic variability in pearl mussel during the captive breeding as evident from highly similar genetic diversity indices such as Ho and AR between original populations and captive-bred juveniles.

Material and methods

Study design

Our study design was based on the comparison of population genetic parameters of natural freshwater pearl mussel populations and corresponding cohorts of juveniles propagated at specialized breeding stations. We included five facilities from four European countries (Germany, Austria, Luxembourg, France) in our sampling regime. In these, freshwater pearl mussels were propagated from a total of 14 different source populations representing nine main drainage systems: Elbe (Weiße Elster, Wolfsbach/Zinnbach), Danube (Kleine Ohe, Naarn, Wolfertsrieder Bach), Rhine (Sûre), Maas (Rulles, Anlier), Loire (Le Sarthon), Orne (La Rouvre), Sienne (L’Airou), Blavet (Le Bonne Chère, Le Loc’h) and Aulne (L’Elez) (Table 1). Source Populations of the streams Sûre, Rulles and Anlier were located on Belgian territory and juveniles were reared in Luxembourg. For genetic analyses we used data of 382 adult specimens from respective source populations collected between 2003 and 201915,16,17 in their natural habitats (based on representative sample collection over multiple locations per stream) or directly from individuals of the broodstock held at the breeding station as practiced in Austria39,40. Genetic constitution of those mussels was compared to results of 897 propagated juveniles comprising 29 different cohorts which were selected from different age classes ranging from 0 + to ca. 16 years. They were collected either while being held at the breeding facility, or from gravel-filled cage-boxes submerged in the streams of intended release, or from already released and marked individuals.

Table 1 Population characteristics and population genetic summary statistics of Margaritifera margaritifera source populations and corresponding cohorts of propagated juveniles.

Sampling and DNA extraction

We collected 40–100 µL haemolymph from the foot tissue of adult individuals and juveniles exceeding 30 mm total shell length by following the methodology of Geist & Kuehn16. This sampling technique is not harmful for the mussels which were returned alive to their original sites immediately after sampling. Juveniles of cohorts between 0 + and 5 years of age and a total shell length between < 1 mm and ca. 1 cm were sampled using whole individuals due to their small size. Obvious deformations of juvenile mussels (e.g., irregular and compressed shell shapes and growth patterns) were additionally noted. Haemolymph was transferred into 1.7 mL Eppendorf tubes while juveniles were kept alive in containers filled with water. Both were cooled at 4 °C and subsequently transported to the laboratories of the Technical University of Munich, Germany. Samples were prepared for DNA extraction by centrifuging haemolymph at 14.000 g for 5 min and discarding the supernatant whereas juveniles were transferred to individual reaction tubes. To ensure efficient lysis of the tissue, the smallest individuals (~ 1 mm) were crushed inside the reaction tube using a metal probe, or one shell valve with adhering tissue was used. Genomic DNA was then isolated from cellular pellets and juveniles using the NucleoSpin Tissue Kit (Macherey–Nagel GmbH, Düren, Germany) according to the manufacturer’s protocol for tissue samples and eluted in 80 µL of BE buffer.

PCR and genotyping

DNA samples were genotyped at nine standard species-specific microsatellite markers (MarMa2671, MarMa3050, MarMa3621, MarMa4143, MarMa4322, MarMa4726, MarMa5167, MarMa5280 and MarMa5023) as described by Geist et al.15 and Geist & Kuehn16,17. Polymerase chain reactions (PCRs) were performed in a total volume of 12.5 µL containing 25 ng genomic DNA, 0.2 µM of each primer, 0.2 mM of each dNTP, 3 mM MgCl2 for eight Loci (2 mM MgCl2 for Locus 5280), 1 × FirePol® PCR buffer BD (0.8 M Tris–HCl, 0.2 M (NH4)SO4 and 0.5 U FirePol® Taq DNA polymerase (Solis Biodyne, Tartu, Estonia) under the cycling conditions described in Geist et al.15 and Geist & Kuehn16. Forward primers were end-labelled with Cy5 fluorescent dye and PCR products were separated on 5% denaturing 19:1 acrylamid:bisacrylamid gels on an ALFexpressII DNA analyser (Amersham Pharmacia Biotech) and allele lengths were scored using ALLELELINKS 1.02 software. To ensure consistent allele scoring between individual lanes and among gels, two internal size standards were included per lane42 as well as 11 size standards and one previously genotyped reference sample in two separate lanes.

Statistical analyses

Microsatellite allele frequencies, the mean number of alleles per locus (A), allelic richness (AR) as a standardized measure of the number of alleles corrected for sample size, expected and observed heterzygosities (HE, HO) and inbreeding coefficient (FIS) were calculated using Fstat v. 2.9.343. We used Genepop v. 4.7.344 to test genotypic distributions for conformance with Hardy–Weinberg expectations using the probability test45, to calculate pairwise FST values46 between source populations and offspring cohorts and to estimate the significance of genotypic differentiation between these populations pairs. All probability tests were based on the Markov chain47,48 method using 10,000 dememorization steps, 100 batches and 5000 iterations per batch. The number of distinct multilocus genotypes (MLG) was determined using the R-package Poppr v. 2.8.349. The R-package Adegenet v. 2.1.150 was used to determine mean individual inbreeding coefficients (Find) for each source population and offspring cohort by calculating for each individual the probability of being homozygous at a locus: p(h) = F + (1 − F) \(\sum\nolimits_{i} {p_{i}^{2} }\) and summing up log-likelihoods over all microsatellite loci to account for multilocus genotypes, where F refers to the probability of an individual to inherit two identical alleles from a single ancestor and pi refers to the frequency of allele i in a population. Additionally, we estimated relatedness between individuals within populations based on the F-value of the 2mod program51 which provides information on the probability that two genes share a common ancestor within a population and is correlated with effective population size. The Markov chain Monte Carlo (MCMC) simulation was run for 200,000 iterations and the initial 10% of the data were discarded to avoid dependence on starting conditions. We used Structure v. 2.3.4 software52 to determine and visualize the number of genetic clusters (K) present among source populations and to assign probabilities of cluster memberships to propagated individuals. We tested values of K ranging from 2 to 20 under the admixture model and assuming correlated allele frequencies using 20,000 burn-ins, 200,000 MCMC repetitions and 10 iterations per K to assess the convergence of ln P(X│K). The software package Clumpak v. 1.153 was used to infer the most likely number of K based on the ΔK method of Evanno et al.54. The implemented program Clumpp v. 1.155 was used to find the optimal individual alignments of replicated cluster analyses using the LargeKGreedy algorithm and 2000 random input orders which were then visualized using Distruct v. 1.156. Bayesian clustering techniques may produce biased results in terms of cluster recognition when working with unbalanced sample sizes57,58. We therefore validated Structure results using the multivariate approach of discriminant analysis of principal components (DAPC)59 implemented in the software package Adegenet v. 2.1.150 in R v. 3.6.260 which is less sensitive to uneven sampling58. DAPC first transforms the data using principal component analysis (PCA) and then performs a Discriminant Analysis (DA) on the retained principal components (PC). We retained 13 PCs which explained 85% of the total variation of the data set. Results of the DAPC were visualized by assigning the first three PCs to intensities of the color channels of the RGB system. Similar generated colors thus correspond to similar genetic constitutions of respective individuals or populations59.


Genetic integrity

The captive breeding efforts over the five investigated rearing facilities were found to represent a diversity of genetically differentiated clusters of freshwater pearl mussel. Overall, eleven genetic clusters were identified as the most probable outcome using the ΔK method (Table 2, Fig. S2). In almost all cases, the cultured offspring closely resembled the genetic constitution of the source mussels as revealed from the Structure analysis and the generally high assignment of offspring to the original source populations. In 13 out of 29 cases (45%), a 100% assignment to the original population was found, and in 25 out of the 29 cases (86%), more than 80% of individuals were correctly assigned (Table 2). Otherwise, low levels of assignment occurred in populations (BC, LO, RU and SU) that generally had extremely low values of genetic variability (Table 1) and where drift effects due to the limited availability of a small number of gravid broodstock mussels for the breeding were expected. The result of the DAPC is consistent with the findings of the Structure analyses and graphically illustrates the genetic differentiation between source and captive-bred mussels based on color codes of multilocus genotype frequencies of each individual sampled (Fig. 1).

Table 2 Assignment of 1300 Margaritifera margaritifera individuals to genetic clusters identified based on genotyping nine polymorphic microsatellite markers and individual membership coefficients derived from Structure and Clumpp software.
Figure 1

(A) Clustering of 1300 individuals of 14 Margaritifera margaritifera source populations and 29 corresponding cohorts of propagated juveniles based on discriminant analysis of principal components (DAPC) using the first 13 principal components and 3 discriminant functions. Individuals are depicted as dots, populations are represented by inertia ellipses and mean population color based on the DAPC; population codes according to Table 1. (B) Individual genetic constitution of 1300 Margaritifera margaritifera from 14 source populations and respective cohorts of propagated juveniles based on discriminant analysis of principal components (DAPC) using the first 13 principal components and 3 discriminant functions. The color of the dots corresponds to the results of the DAPC with similar colors indicating similar genetic constitution.

Most FST values between captive-bred mussels with their original populations from the wild were low to moderate, indicating high similarity in the alleles present and their frequencies in both groups (Table 1). This was for instance obvious with the Austrian NA-O1 and NA-O2 compared to NA-S, a culturing system where the parent mussels are permanently maintained in a flow-through system allowing for a near-natural glochidia attachment to host fish that are maintained in tanks fed by the flow-through systems. In some cases, very high FST values of up to 0.638 between single year cohorts of offspring compared to the original populations were evident (e.g., ST-S with ST-O1). In most cases, these pronounced differences were not consistently present over different year cohorts, especially in captive breeding situations where glochidia from gravid mussels are annually collected in the wild to infest host fish in the rearing facility and where these source mussels differ from year to year.

Genetic variability

Mean values of observed heterozygosity (HO) and allelic richness (AR) in source populations ranged from HO = 0.006 (EL) to HO = 0.460 (WB) and from AR = 1.1 (EL and RU) to AR = 2.9 (WB) while the global means of source populations (HO = 0.131, AR = 1.7) were slightly higher than that of juvenile cohorts (HO = 0.112, AR = 1.6). In most cohorts of propagated juveniles, remarkably low levels of these two diversity parameters were detected, but also in the majority of the source populations, especially the westernmost ones (Table 1). However, in comparison to the source populations both AR and HO decreased in over half of the juvenile cohorts (Fig. 2) while respective individual inbreeding coefficients tended to increase (Fig. S1). Another remarkable finding relates to the numbers of physically deformed juveniles. In all six cohorts with ≥ 3 deformed specimens (ST-O1, ST-O2, RO-O1, RO-O2, LO-O2, EL-O1), observed heterozygosities were below 0.05 (Tab. 1).

Figure 2

Change of allelic richness (AR) and observed heterozygosity (HO) of 29 captive bred Margaritifera margaritifera cohorts compared to corresponding source populations.


The value and usefulness of captive breeding in fish populations has been subject to a great controversy61 and the increasing number of captive breeding efforts in freshwater mussels37,38, particularly in freshwater pearl mussel11,12,13,14,35,36, makes it necessary to critically reflect on these measures. Our study provides a first analysis of 29 captive-bred annual cohorts of freshwater pearl mussel in comparison to the genetic constitution of populations from their original streams considering four different European countries. Breeding efforts were found to represent a broad, yet not complete spectrum of the genetic diversity of wild populations, and seem to be a valuable tool to at least partially secure the genetic and evolutionary potential of populations at the brink of extinction until efforts of habitat restoration succeed and populations manage to sufficiently recruit in the wild. The findings also illustrate the usefulness of genetic monitoring in captive breeding to identify alterations of the genetic constitution in terms of genetic identity as well as decreased genetic variability.

Most breeding stations are focused on local production of juveniles from nearby populations using local fish stocks. The findings of this study with eleven different genetic clusters represented in those breeding efforts suggest that this approach appears generally useful in considering the overall pronounced degree of genetic differentiation among European populations16 as well as the co-evolutionary genetic patterning of freshwater pearl mussel and its hosts17. A main challenge lies in the simultaneous rearing of multiple populations and year cohorts in the same rearing facility which always poses a certain risk of mixing different populations. Such confusion was also suspected in one of the rearing facilities in this study and the genetic analyses provided a powerful tool in validating and re-assigning the offspring to the correct source population in the wild. Even though this was a rare incident, it may be generally useful to ensure validation of the integrity of captive-bred mussels before they are being released into the wild, especially in situations when the source population is not yet extinct.

Currently, most breeding stations rely on different ways of collecting parent mussels or larvae from the wild versus completely maintaining a suite of parent mussels together with host fishes. Since the primary objective of those breeding stations is to produce juvenile mussels and since there are many time-critical constraints in terms of finding sufficient numbers of gravid females, handling of glochidia larvae and the infestation of host fish, there is typically no time for a documentation of the exact procedures and methods such as numbers of parent mussels and glochidia collected as well as on individual host fish infestations and other rearing commodities that all may also affect the genetic constitution of the offspring. These constraints, along with the very different genetic background of the pearl mussel source populations considered in this study prevent us from systematically linking certain genetic effects to specific attributes of the respective breeding method. Still, the findings of this study suggest that gathering such information as regularly practiced in many state and federal breeding stations in the US, would be very useful. If this cannot be realized, then at least females should be exchanged annually and progeny from a single female should not be used more than once at each reintroduction locality. Moreover, a realistic evaluation of the effects of any captive breeding on the genetic constitution of populations should not look at single cohorts but rather at the cumulative effects over time. Whilst the findings of this study revealed rather low genetic diversity and signs of inbreeding in some of the annual cohorts, pronounced differences were typically observed when comparing the findings for cohorts from different years. Such differences can be explained by different availabilities of gravid mussels (in some populations only single individuals in certain years) as well as different infestation, metamorphosis and rearing success. Variable levels of multiple paternity as previously observed in this species62,63 and the Louisiana Pearlshell, Margaritifera hembeli, may also play a role64. In any case, the results of this study allow drawing the consistent picture that maintaining rearing activities for specific populations over multiple years is most beneficial since it reduces the risk of genetic bottlenecks, drift and selection effects. This is particularly true for a long-lived species like Margaritifera margaritifera, where the reproductive period extends over more than 80 years65, allowing multiple generations of different age to jointly reproduce. Still, the extremely low genetic diversity values also observed in most of the source populations for captive breeding suggest that the actual efforts to rescue genetically outstanding populations by captive breeding should begin before an erosion of the genetic variability at small effective population sizes. In cases of populations which are already suffering from loss of genetic diversity, an individual-based selection of specimens for the collection of glochidia is recommended, focusing on individuals which best represent the remaining gene pool of the original population. Also, in any breeding effort it is useful to avoid possible selection and drift effects. In the case of freshwater pearl mussel, it is thus mandatory to use a full and diverse suit of fish hosts and avoid fish strains that only result in metamorphosis of few specimens4,5,24. This also includes using older than the commonly utilized 0 + fish which were shown to result in higher numbers of developing postparasitic juveniles under captive breeding situations25.

The age and size at which captive-bred juvenile pearl mussels should be released into the wild still remains controversial. The greater capability of adaptation31 as well as the lower risk of genetic erosion and die-offs in the rearing facility would suggest an early release. Colmated stream beds and other adverse habitat conditions to which older and larger mussels are much more resistant than young ones, as well as the absence of a decreased genetic variability of older cohorts compared to younger ones in this study (see e.g. BC-O1,2,3,4 and WE-O1, WE-O2 with ages of more than 10 years), along with the continuous improvements of survival in rearing facilities32,35,36,38,66 clearly suggest that stocking with such cohorts is also a feasible option.

Effective conservation of freshwater pearl mussel will likely depend on a combination of habitat restoration and effective captive breeding to rescue genetically unique populations over time. An integration of scientific findings into the ecology and conservation genetics of the species is thus likely to be most successful3. Given the well-established knowledge on the genetic constitution of freshwater pearl mussel throughout its European and North American distribution15,16,17,18,19,20,21,22,23 and the large and increasing number of breeding facilities for this species, a more systematic approach of evidence-based conservation and restoration67 can be recommended. Such an approach should also include systematic selection of priority populations for conservation, effective breeding strategies avoiding effects of in- and outbreeding by genetically informed selection of parent individuals, and a network of collaboration among the different facilities.

Data availability

The original data used for the study will be available from the Dryad Digital Repository.


  1. 1.

    Geist, J. Integrative freshwater ecology and biodiversity conservation. Ecol. Indic. 11, 1507–1516 (2011).

    Article  Google Scholar 

  2. 2.

    Lopes-Lima, M. et al. Conservation status of freshwater mussels in Europe: State of the art and future challenges. Biol. Rev. 92, 572–607 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Geist, J. Strategies for the conservation of endangered freshwater pearl mussels (Margaritifera margaritifera L.): A synthesis of conservation genetics and ecology. Hydrobiologia 644, 69–88 (2010).

    Article  Google Scholar 

  4. 4.

    Taeubert, J. E. & Geist, J. The relationship between the freshwater pearl mussel (Margaritifera margaritifera) and its hosts. Biol. Bull. 44, 67–73 (2017).

    Article  Google Scholar 

  5. 5.

    Salonen, J. K. et al. Atlantic salmon (Salmo salar) and brown trout (Salmo trutta) differ in their suitability as a host for the endangered freshwater pearl mussel (Margaritifera margaritifera) in northern Fennoscandian rivers. Freshw. Biol. 62, 1346–1358 (2017).

    Article  Google Scholar 

  6. 6.

    Geist, J. & Auerswald, K. Physicochemical stream bed characteristics and recruitment of the freshwater pearl mussel (Margaritifera margaritifera). Freshw. Biol. 52, 2299–2316 (2007).

    Article  Google Scholar 

  7. 7.

    Stoeckl, K., Denic, M. & Geist, J. Conservation status of two endangered freshwater mussel species in Bavaria, Germany: Habitat quality, threats, and implications for conservation management. Aquat. Conserv. 30, 647–661 (2020).

    Article  Google Scholar 

  8. 8.

    Auerswald, K. & Geist, J. Extent and cause of siltation in a headwater stream bed: Catchment and soil erosion is less important than internal stream processes. Land Degrad. Dev. 29, 737–748. (2018).

    Article  Google Scholar 

  9. 9.

    Bauer, G. Threats to the freshwater pearl mussel Margaritifera margaritifera L. in central Europe. Biol. Conserv. 45, 239–253 (1988).

    Article  Google Scholar 

  10. 10.

    Boon, P. J. et al. Developing a standard approach for monitoring freshwater pearl mussel (Margaritifera margaritifera) populations in European rivers. Aquat. Conserv. 29, 1365–1379 (2019).

    Article  Google Scholar 

  11. 11.

    Hruska, J. Nahrungsansprüche der Flußperlmuschel und deren halbnatürliche Aufzucht in der Tschechischen Republik (Dietary requirements and semi-natural rearing of freshwater pearl mussel in the Czech Republic). Heldia 4, 69–79 (1999).

    Google Scholar 

  12. 12.

    Preston, S. J., Keys, A. & Roberts, D. Culturing freshwater pearl mussel Margaritifera margaritifera: A breakthrough in the conservation of an endangered species. Aquat. Conserv. 17, 539–549. (2007).

    Article  Google Scholar 

  13. 13.

    Thomas, G. R., Taylor, J. & de Leaniz, C. G. Captive breeding of the endangered freshwater pearl mussel, Margaritifera margaritifera. Endanger. Species Res. 12, 1–9 (2010).

    Article  Google Scholar 

  14. 14.

    Gum, B., Lange, M. & Geist, J. A critical reflection on the success of rearing and culturing juvenile freshwater mussels with a focus on the endangered freshwater pearl mussel (Margaritifera margaritifera L.). Aquat. Conserv. 21, 743–751 (2011).

    Article  Google Scholar 

  15. 15.

    Geist, J., Rottmann, O., Schröder, W. & Kühn, R. Development of microsatellite markers for the endangered freshwater pearl mussel Margaritifera margaritifera L. (Bivalvia: Unionoidea). Mol. Ecol. Resour. 3, 444–446 (2003).

    CAS  Article  Google Scholar 

  16. 16.

    Geist, J. & Kühn, R. Genetic diversity and differentiation of central European freshwater pearl mussel (Margaritifera margaritifera L.) populations: Implications for conservation and management. Mol. Ecol. 14, 425–439 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Geist, J. & Kuehn, R. Host-parasite interactions in oligotrophic stream ecosystems: The roles of life history strategy and ecological niche. Mol. Ecol. 17, 997–1008 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Marchordom, A., Araujo, R., Erpenbeck, D. & Ramos, M. A. Phylogeography and conservation genetics of the endangered European Margaritiferidae (Bivalvia: Unionoidea). Biol. J. Linn. Soc. Lond. 78, 235–252 (2003).

    Article  Google Scholar 

  19. 19.

    Stoeckle, et al. Strong genetic differentiation and low genetic diversity of the freshwater pearl mussel (Margaritifera margaritifera L.) in the southwestern European distribution range. Conserv. Genet. 18, 147–157 (2017).

    Article  Google Scholar 

  20. 20.

    Karlsson, S., Larsen, B. M. & Hindar, K. Host-dependent genetic variation in freshwater pearl mussel (Margaritifera margaritifera L.). Hydrobiologia 735, 179–190 (2014).

    Article  Google Scholar 

  21. 21.

    Geist, J., Söderberg, H., Karlberg, A. & Kuehn, R. Drainage-independent genetic structure and high genetic diversity of endangered freshwater pearl mussels (Margaritifera margaritifera) in northern Europe. Conserv. Genet. 11, 1339–1350 (2010).

    Article  Google Scholar 

  22. 22.

    Geist, et al. Genetic structure of Irish freshwater pearl mussels (Margaritifera margaritifera and Margaritifera durrovensis): Validity of subspecies, roles of host fish, and conservation implications. Aquat. Conserv. 28, 923–933 (2018).

    Article  Google Scholar 

  23. 23.

    Zanatta, et al. High genetic diversity and low differentiation in North American Margaritifera margaritifera (Bivalvia: Unionida: Margaritiferidae). Biol. J. Linn. Soc. Lond. 123, 850–863 (2018).

    Article  Google Scholar 

  24. 24.

    Taeubert, J. E., Denic, M., Gum, B., Lange, M. & Geist, J. Suitability of different salmonid strains as hosts for the endangered freshwater pearl mussel (Margaritifera margaritifera). Aquat. Conserv. 20, 728–734 (2010).

    Article  Google Scholar 

  25. 25.

    Marwaha, et al. Host (Salmo trutta) age influences resistance to infestation by freshwater pearl mussel (Margaritifera margaritifera) glochidia. Parasitol. Res. 118, 1519–1532 (2019).

    PubMed  Article  Google Scholar 

  26. 26.

    Taeubert, J. E., Gum, B. & Geist, J. Variable development and excystment of freshwater pearl mussel (Margaritifera margaritifera L.) at constant temperature. Limnologica 43, 319–322 (2013).

    Article  Google Scholar 

  27. 27.

    Taeubert, J. E. & Geist, J. Critical swimming speed of brown trout (Salmo trutta) infested with freshwater pearl mussel (Margaritifera margaritifera) glochidia and implications for artificial breeding of an endangered mussel species. Parasitol. Res. 112, 1607–1613 (2013).

    PubMed  Article  Google Scholar 

  28. 28.

    Marwaha, J., Jensen, K. H., Jakobsen, P. J. & Geist, J. Duration of the parasitic phase determines subsequent performance in juvenile freshwater pearl mussels (Margaritifera margaritifera). Ecol. Evol. 7, 1375–1383 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Eybe, T., Thielen, F., Bohn, T. & Sures, B. Influence of the excystment time on the breeding success of juvenile freshwater pearl mussels (Margaritifera margaritifera). Aquat. Conserv. 25, 21–30 (2015).

    Article  Google Scholar 

  30. 30.

    Denic, M., Taeubert, J. E. & Geist, J. Trophic relationships between the larvae of two freshwater mussels and their fish hosts. Invertebr. Biol. 134, 129–135 (2015).

    Article  Google Scholar 

  31. 31.

    Denic, M. et al. Influence of stock origin and environmental conditions on the survival and growth of juvenile freshwater pearl mussels (Margaritifera margaritifera) in a cross-exposure experiment. Limnologica 50, 67–74 (2015).

    CAS  Article  Google Scholar 

  32. 32.

    Hyvärinen, H. S. H., Chowdhury, M. M. R. & Taskinen, J. Pulsed flow-through cultivation of Margaritifera margaritifera: Effects of water source and food quantity on the survival and growth of juveniles. Hydrobiologia. 3219–3229 (2021).

  33. 33.

    Hyvärinen, H., Saarinen-Valta, M., Mäenpää, E. & Taskinen, J. Effect of substrate particle size on burrowing of the juvenile freshwater pearl mussel Margaritifera margaritifera. Hydrobiologia (2021).

    Article  Google Scholar 

  34. 34.

    Taskinen, J. et al. Effect of pH, iron and aluminum on survival of early life history stages of the endangered freshwater pearl mussel, Margaritifera margaritifera. Toxicol. Environ. Chem. 93, 1764–1777 (2011).

    CAS  Article  Google Scholar 

  35. 35.

    Lavictoire, L., Moorkens, E., Ramsay, A. & Sweeting, R. Effects of substrate size and cleaning regime on growth and survival of captive-bred juvenile freshwater pearl mussels, Margaritifera margaritifera (Linnaeus, 1758). Hydrobiologia 766, 89–102 (2016).

    Article  Google Scholar 

  36. 36.

    Eybe, T., Thielen, F., Bohn, T. & Sures, B. The first millimetre: Rearing juvenile freshwater pearl mussels (Margaritifera margaritifera L.) in plastic boxes. Aquat. Conserv. 23, 964–975 (2013).

    Article  Google Scholar 

  37. 37.

    Strayer, D. L., Geist, J., Haag, W. R., Jackson, J. K. & Newbold, J. D. Essay: Making the most of recent advances in freshwater mussel propagation and restoration. Conserv. Sci. Pract. 1, e53. (2019).

    Article  Google Scholar 

  38. 38.

    Patterson, M. A. et al. Freshwater Mussel Propagation for Restoration (Cambridge University Press, 2018).

    Book  Google Scholar 

  39. 39.

    Gstöttenmayr, D., Scheder, C. & Gumpinger, C. Conservation de la mulette perlière d’eau douce en Autriche: un système d’élevage contrôlé en progrès. Penn ar Bed 222, 45–49 (2015).

    Google Scholar 

  40. 40.

    Gumpinger, C., Pichler-Scheder, C. & Huemer, D. Das oberösterreichische Artenschutzprojekt „Vision Flussperlmuschel“. Österreichs Fischerei 69, 259–273 (2016).

    Google Scholar 

  41. 41.

    Rice, W. R. Analyzing tables of statistical tests. Evolution 43, 223–225 (1989).

    PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    DeWoody, J. A. et al. Universal method for producing ROXlabeled size standards suitable for automated genotyping. Biotechniques 37, 348–352. (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Goudet, J. Fstat (Version 1.2): A computer program to calculate F-statistics. J. Hered. 86, 485–486 (1995).

  44. 44.

    Rousset, F. Genepop’007: A complete reimplementation of the Genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Haldane, J. B. S. An exact test for randomness of mating. J. Genet. 52, 631–635. (1954).

    Article  Google Scholar 

  46. 46.

    Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Guo, S. W. & Thompson, E. A. Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48, 361–372 (1992).

    CAS  PubMed  MATH  Article  PubMed Central  Google Scholar 

  48. 48.

    Raymond, M. & Rousset, F. An exact test for population differentiation. Evolution 49, 1280–1283 (1995).

    PubMed  Article  PubMed Central  Google Scholar 

  49. 49.

    Kamvar, Z. N., Tabima, J. F. & Grünwald, N. J. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2, e281. (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Jombart, T. Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Ciofi, C., Beaumont, M. A., Swingland, I. R. & Bruford, M. W. Genetic divergence and units for conservation in the Komodo dragon Varanus komodoensis. Proc. Royal Soc. B 266, 2269–2274 (1999).

    Article  Google Scholar 

  52. 52.

    Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. 53.

    Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. CLUMPAK: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software structure: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Jakobsson, M. & Rosenberg, N. A. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Rosenberg, N. A. DISTRUCT: A program for the graphical display of population structure. Mol. Ecol. Notes 4, 137–138 (2004).

    Article  Google Scholar 

  57. 57.

    Kalinowski, S. T. The computer program STRUCTURE does not reliably identify the main genetic clusters within species: Simulations and implications for human population structure. Heredity 106, 625–632 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  58. 58.

    Puechmaille, S. J. The program structure does not reliably recover the correct population structure when sampling is uneven: Subsampling and new estimators alleviate the problem. Mol. Ecol. Resour. 16, 608–627 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  59. 59.

    Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).

    PubMed  PubMed Central  Article  Google Scholar 

  60. 60.

    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: (2019).

  61. 61.

    Trushenski, J. T., Whelan, G. E. & Bowker, J. D. Why keep hatcheries? Weighing the economic cost and value of fish production for public use and public trust purposes. Fisheries 43, 285–293 (2018).

    Google Scholar 

  62. 62.

    Wacker, S., Larsen, B. M., Jakobsen, P. & Karlsson, S. High levels of multiple paternity in a spermcast mating freshwater mussel. Ecol. Evol. 8, 8126–8134 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  63. 63.

    Wacker, S., Larsen, B. M., Jakobsen, P. & Karlsson, S. Multiple paternity promotes genetic diversity in captive breeding of a freshwater mussel. Glob. Ecol. Conserv. 17, e00564. (2019).

    Article  Google Scholar 

  64. 64.

    Garrison, N. L., Johnson, P. D. & Whelan, N. V. Conservation genomics reveals low genetic diversity and multiple parentage in the threatened freshwater mussel, Margaritifera hembeli. Conserv. Genet. (2021).

    Article  Google Scholar 

  65. 65.

    Bauer, G. Reproductive strategy of the freshwater pearl mussel Margaritifera margaritifera. J. Anim. Ecol. 56, 691–704 (1987).

    Article  Google Scholar 

  66. 66.

    McMurray, S. E. & Roe, K. J. Perspectives on the controlled propagation, augmentation, and reintroduction of freshwater mussels (Mollusca: Bivalvia: Unionoida). Freshw. Mollusk Biol. Conserv. 20, 1–12 (2017).

    Article  Google Scholar 

  67. 67.

    Geist, J. Seven steps towards improving freshwater conservation. Aquat. Conserv. 25, 447–453 (2015).

    Article  Google Scholar 

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We thank Christine Seidel and Ewa Kluka for technical assistance with genotyping in the laboratory, as well as Clemens Gumpinger, Daniela Csar (Austria), Pierrick Dury, Marie Capoulade, Pierre-Yves Pasco (France), Grégory Motte (Belgium), Frankie Thielen (Luxembourg), Marco Denic, Michael Lange, Thomas Schiller and Felix Grunicke (Germany) for providing access to their captive-bred mussels and for their support of this study. Analyses of the German populations were financially jointly supported by the Federal Agency for Nature Conservation with funds of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety as well as the Federal Ministry of Education and Research (FKZ 01LC1313C).


Open Access funding enabled and organized by Projekt DEAL.

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The study was conceived by J.G., R.K. and H.B. Sampling was conducted by J.G. and H.B. The molecular genetic analysis was led by H.B., B.C.S. and R.K. The manuscript was primarily written by J.G., supported by H.B. and continuous input from all other authors. All authors read and approved the final manuscript.

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Correspondence to Juergen Geist.

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Geist, J., Bayerl, H., Stoeckle, B.C. et al. Securing genetic integrity in freshwater pearl mussel propagation and captive breeding. Sci Rep 11, 16019 (2021).

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