Delphine Lallias, Pierre Boudry, Isabelle Arzul, René Robert, Sylvie Lapègue. BfN workshop, Isle of Vilm, 15 th -16 th November 2012

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1 Delphine Lallias, Pierre Boudry, Isabelle Arzul, René Robert, Sylvie Lapègue BfN workshop, Isle of Vilm, 15 th -16 th November 2012

2 General role of genetics in restoration programmes Molecular genetic markers Assessment of genetic characteristics of wild stocks level of genetic variation population structure and level of connectivity genetics and reproductive success Marker-assisted selection: resistance to bonamiosis Technological advances: conditioning and seed production Insights into pathology aspects

3 General role of genetics in restoration Genetic tools can play an important role in assisting shellfish restoration projects: Can identify population structure, connectivity, existing genetic diversity and effective population size in natural stocks Would successful restocking into one area improve recruitment to other areas or do some areas have low inter-population connectivity? Can estimate the genetic diversity of shellfish used for restoration Attempt to restore populations with the highest possible genetic diversity Can be used to choose the source of broodstock for any re-population effort Local adaptation in sessile organisms is highly likely, so restoration efforts should use local populations Can be used to estimate / monitor the effectiveness of conservation effort: bay scallop Argopecten irradians (Wilbur et al. 2005) Eastern cupped oyster C. virginica (Milbury et al. 2004; Hare et al. 2006).

4 Genetic molecular markers: nuclear Inherited from both parents - Genotypes Microsatellites: short fragments of DNA made up of sequences repeated in tandem arrays of 2-6bp - length polymorphism primer F A T A T A T A T T A T A T A T A primer R flanking sequences microsatellite (AT) motif flanking sequences SNPs (Single Nucleotide Polymorphisms) - sequence polymorphism

5 Genetic molecular markers: mitochondrial Inherited from the female parent - Haplotypes Position 265: A/G Position 309: A/G (Danic-Tchaleu et al. 2011)

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7 European scale ANa ANc Geographic distribution of O. edulis ANd ASa ASb ASc ASd ANb ANe MEa MWb MEb MWc MWa BS Sampling sites Atlantic Mediterranean

8 Nuclear DNA (5 microsatellites) Mitochondrial DNA (12S-rRNA gene) ASa ANe ASc ASb F st = MEa ASc ANb ANc ASb ASa ANa ANd ANe MWb MWc Atlantic Mediterranean ANa ANb ANd MWa ASd ANc F st = MEb MWa ASd MWc MWb BS MEa 0.01 BS 0.1 MEb (Launey et al. 2002) (Diaz-Almela et al. 2004)

9 European scale 215 SNPs in 16 populations F st = 0.09 (Harrang et al., in prep)

10 Case study: introduction to Canada Nova Scotia O. edulis introduced 30 years ago to Nova Scotia (stocks: naturalized populations in Maine - ancestors originated in the Netherlands) Maine Genetic data (5 microsatellites) consistent with history of introduction (Vercaemer et al., 2006)

11 Genetics and reproductive success 1994: one cohort recruited over 15 days in Sète (South France) Quiberon Bay Comparison genetic diversity spat vs adults (4 microsatellites) Seasonal Alleles /locus: spat (13.75) adults (23) N b < 30 F st = (P<0.0001) Supports the hypothesis of sweepstakes reproductive success (Hedgecock et al., 2007) Comparison genetic diversity adults vs 4 cohorts (4 msats, 12S) High allelic richness (20-22) Msats: no significant differentiation 12S: significant F st (C1-Seasonal; C1-Adults) N e : 458 (msats) vs 29 (12S) Limited evidence of sweepstakes (Taris et al., 2009)

12 Genetics and reproductive success Very variable number of males per female (1 to > 40) 14 brooding females 80 larvae per female (4 msats) Variance in individual male contribution Paternity analysis (Lallias et al., 2010a)

13 Genetics and reproductive success 62 adults Experimental hatchery 6 successive spawns 80 larvae per spawn (4 msats) Total contribution of each progenitor was very variable For each temporal cohort, N b generally below 25 Parentage analysis (Lallias et al., 2010a)

14 Comparison wild / pond / hatchery 20 Allelic Richness Allelic richness (5 msats) Wild 1 Wild 2 Wild 3 Wild 4 Pond 1 Pond 2 Pond 3 Pond 4 Hatchery 1 hatchery 2 hatchery 3 Hatchery 4 Allelic richness Log 10 (N b ) Wild A=18.4 Pond A=14.1 Hatchery A=7.6 Loss of genetic diversity in hatchery populations Alternative managed reproduction methods can retain high genetic diversity in O. edulis (large scale ponds - Norway) Variance in reproductive success among potential breeders (high relatedness among hatchery progenies) Pedigree reconstruction (Lallias et al., 2010b)

15 Summary Population genetic structure of O. edulis wild stocks in Europe Weak but significant structure: Atlantic vs Mediterranean Finer resolution with new tools (SNPs) Possibility to track introductions of O. edulis in the world (e.g. Canada) Genetic markers can give insights into variance in reproductive success Comparison genetic diversity adults vs cohorts Parentage and paternity analyses (field and experimental hatchery) Can have implications in terms of genetic diversity levels Genetic markers can give insights into methods of production (comparison wild / pond / hatchery) Hatchery: significant loss of genetic diversity, very small N b Large scale pond-production systems could represent a valuable alternative to hatcheries (efficient in maintaining genetic diversity)

16 But... Restoration of flat oyster populations in Europe is complicated by the existence of bonamiosis which can cause very high mortalities in flat oyster populations. Restoration of oysters in bonamiosis-free regions: could take advantage of the potential high genetic diversity provided by large scale pond production. Restoration of oysters in bonamiosis areas: better strategy might be to use bonamiosis resistant strains from hatchery (Naciri-Graven et al. 1998) or small pond-culture (Culloty et al. 2004) need to improve hatchery and small pond production methods to gain the highest genetic diversity possible (Lallias et al., 2010b)

17 E8f88r E5f88r B4f303 E1f374 A1f154 A3f101r QTL 28.0 E10f44r 27.0 E1f211 E3f B8f97r E3f267 A11f288r B7f172 A8f63r A3f228r E10f89r E8f186 E11f130r A9f195r 83.3 E7f A10f39

18 Survival performances Comparison of survival in Quiberon Bay Figure 8: Survies comparées en baie de Quiberon 100% 90% 89,2% 50% 45% 80% 73,4% 40% Survie (%) Survival (%) 70% 60% 50% 40% 30% 20% 10% CN Sol R Sol CN Poche R Poche Bo R Poche Bo CN Sol Bo R Sol Bo CN Poche 39,8% 33,6% 35% 30% 25% 20% 15% 10% 5% Taux de Bonamia (%) Bonamia rate (%) 0% 0% juil.-02 oct.-02 janv.-03 mai-03 août-03 nov.-03 mars-04 juin-04 sept.-04 déc.-04

19 Find genetic markers associated with resistance or susceptibility to bonamiosis, with the ultimate objective to implement marker-assisted selection in O. edulis. A resistance B C susceptibility D - Instead of basing selection on performance of the potential breeder at 3 years old (survival/death) - Early selection based on genetic markers (A and B associated to resistance)

20 Several steps for the search of QTLs Identification of potential markers (test marker by marker): multistage testing strategy (Moen et al. 2004) Transmission disequilibrium test (TDT) Mendelian Segregation Test (MST) Survival analysis Probability of survival 1 0,8 0,6 0,4 0,2 E1f43 not banded banded Days Location of those markers in the genome (genetic mapping) QTL mapping approach (uses genetic map and the survival data)

21 G1_410_8 G2_410_8 G3_410_8 G4_410_8 G5_410_ C5f110 (+) B4f159 (+) D1f149 C5f213 A8f60 A12f D1f203() OeduU2 OeduC6 B8f245 E10f206 OeduJ12 B3f200 E8f110 R W Oe1/10 B8f LOD E1f43() R A5f49() E3f255() R A12f429() S C1f252 A3f186 B10f Oe3/44 A9f OeduG9 D5f125 B4f268 E2f163 E12f274 (-) A8f162 A8f120 B9f123 A10f141 A11f Oedu.HA Oe1/47 Oe3/37 B8f96 (-) B11f296 (-) E1f310 (-) E5f212 (-) Oedu.HA A11f82 E3f195() E8f61 B1f216() B4f125() E10f140() 16.7 E12f A12f222 A4f E1f98 (+) E5f157 R E12f245 C1f125 (-) 51.7 A10f A1f150 S W31 A3f73 R QTL A5f OeduO9 G6_410_8 G7_410_8 G8_410_8 G9_410_8 G10_410_ D1f328 R W31 B12f243 S E3f169 R W31 Oedu.HA7 A11f150 (+) B3f342 (+) E12f134 (+) E9f368 R W31 C1f99 S E1f294 (-) OeduT5 A11f340 (-) A12f127 (-) QTL2 0 1 LOD D5f155 A10f139 Oe2/71 D1f D1f271 (+) A10f276 (+) C5f268() E12f190() C1f376() E11f311() C1f67 D5f279 E1f330 C5f A1f261 (+) A4f81 (+) A5f316 E11f252 R resistant allele S susceptible allele B12f52 A5f225 A10f137 A12f A4f313 A11f179 (Lallias et al., 2009)

22 QTLs detection For characters expressing themselves late: bonamiosis resistance (QTLs and eqtls) (INTERREG IVB Seafare) For characters difficult to measure (reproductive effort): development of individual phenotyping, nondestructive by MRI (ANR Gametogene)

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24 Control of reproduction and improvement of seed production Flow-through systems Optimization of diet for broodstock conditioning and larvae Algal production

25 In progress : PERLE a multidisciplinary project to study O. edulis in the Rade of Brest Recruitment and larval dispersal Population genetics Diseases Growth and reproduction (DEB modelling) Seed production Hatchery technology

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27 Diseases can be a major constraint for restoration programme: - pathogens might be introduced through the introduction of animals from an infected population/stock - introduced animals might present high susceptibility to pathogens already present in the restoration zone.

28 Bonamia «Microcell» (2-3 µm) B. Chollet 1 µm B. Chollet

29 European distribution of Bonamia ostreae and B. exitiosa Bonamia ostreae Bonamia ostreae et B. exitiosa Bonamia exitiosa These results are based on surveillance programmes performed in some European countries and do not necessary reflect the real distribution of these parasites.

30 Marteilia Marteilia refringens cells (digestive gland imprint) Marteilia refringens in the epithelia of digestive gland (histological section) Pictures: Ifremer

31 European distribution of Marteilia refringens Data from Marc Engelsma Republic of Ireland, United Kingdom and Denmark have demonstrated freedom for marteiliosis for part or all of their coasts (in green). Pink spots represent locations where Marteilia regringens has been detected.

32 Conclusions Genetic aspects: assess population genetic structure and connectivity assess genetic diversity give insight into reproduction (variance in reproductive success) Pathology aspects: diseases can be a major constraint to restoration projects Bonamia ostreae and B. exitiosa; Marteilia refringens Possibility of using improved material in hatcheries optimised for the species: programme of selection to Bonamia marker-assisted selection

33 References Danic-Tchaleu G, Heurtebise S, Morga B, Lapègue S (2011) Complete mitochondrial DNA sequence of the European flat oyster Ostrea edulis confirms Ostreidae classification. BMC Research Notes, 4, 400. Diaz-Almela E, Boudry P, Launey S, Bonhomme F, Lapègue S (2004) Reduced female gene flow in the European flat oyster Ostrea edulis. Journal of Heredity, 95, Gaffney PM (2006) The role of genetics in shellfish restoration. Aquatic Living Resources, 19, Hare MP, Allen SK, Bloomer P et al. (2006) A genetic test for recruitment enhancement in Chesapeake Bay oysters, Crassostrea virginica, after population supplementation with a disease tolerant strain. Conservation Genetics, 7, Hedgecock D, Launey S, Pudovkin AI et al. (2007) Small effective number of parents (N b ) inferred for a naturally spawned cohort of juvenile European flat oysters Ostrea edulis Marine Biology, 150, Lallias D, Boudry P, Lapègue S, King JW, Beaumont AR (2010b) Strategies for the retention of high genetic variability in European flat oyster (Ostrea edulis) restoration programmes. Conservation Genetics, 11, Lallias D, Gomez-Raya L, Haley CS et al. (2009) Combining two-stage testing and interval mapping strategies to detect QTL for resistance to bonamiosis in the European flat oyster Ostrea edulis. Marine Biotechnology, 11, Lallias D, Taris N, Boudry P, Bonhomme F, Lapègue S (2010a) Variance in the reproductive success of flat oyster Ostrea edulis L. assessed by parentage analyses in natural and experimental conditions. Genetics Research, 92, Launey S, Ledu C, Boudry P, Bonhomme F, Naciri-Graven Y (2002) Geographic structure in the European flat oyster (Ostrea edulis L.) as revealed by Microsatellite polymorphism. Journal of Heredity, 93, Milbury C, Meritt D, Newell R, Gaffney P (2004) Mitochondrial DNA markers allow monitoring of oyster stock enhancement in the Chesapeake Bay. Marine Biology, 145, Taris N, Boudry P, Bonhomme F, Camara MD, Lapègue S (2009) Mitochondrial and nuclear DNA analysis of genetic heterogeneity among recruitment cohorts of the European flat oyster Ostrea edulis. Biological Bulletin, 217, Vercaemer B, Spence KR, Herbinger CM, Lapègue S, Kenchington EL (2006) Genetic diversity of the European oyster (Ostrea edulis L.) in Nova Scotia: Comparison with other parts of Canada, Maine and Europe and implications for broodstock management. Journal of Shellfish Research, 25, Wilbur AE, Seyoum S, Bert TM, Arnold WS (2005) A genetic assessment of bay scallop (Argopecten irradians) restoration efforts in Florida s Gulf of Mexico Coastal Waters (USA). Conservation Genetics, 6,