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Louis Bernatchez

Towards genome enabled conservation of salmonid fishes. Université LAVAL. Louis Bernatchez. Genomics and Conservation of Aquatic Resources. What is conservation genetics?. Conservation genetics is the application of genetics to preserve species as dynamic entities capable

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Louis Bernatchez

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  1. Towards genome enabled conservation of salmonid fishes Université LAVAL Louis Bernatchez Genomics and Conservation of Aquatic Resources

  2. What is conservation genetics? Conservation genetics is the application of genetics to preserve species as dynamic entitiescapable of coping with environmental change. Frankham et al. 2002

  3. What is conservation genetics? Conservation genetics is the application of genetics to preserve species as dynamic entitiescapable of coping with environmental change. Frankham et al. 2002 Past (Species diversity) Bowen B.W., J. Roman. 2005. Conservation Biology.

  4. What is conservation genetics? Conservation genetics is the application of genetics to preserve species as dynamic entitiescapable of coping with environmental change. Frankham et al. 2002 Present (Genetic integrity) Past (Species diversity) Bowen B.W., J. Roman. 2005. Conservation Biology.

  5. What is conservation genetics? Conservation genetics is the application of genetics to preserve species as dynamic entitiescapable of coping with environmental change. Frankham et al. 2002 Present (Genetic integrity) Past (Species diversity) Future Evolutionary potential (depends on human impacts) Bowen B.W., J. Roman. 2005. Conservation Biology.

  6. Two fundamental roles of molecular data in conservation genetics Inventorial : Documenting patterns

  7. Two fundamental roles of molecular data in conservation genetics Inventorial : Documenting patterns Evolutionary potential Local adaptation

  8. Two fundamental roles of molecular data in conservation genetics Mechanistic : Deciphering processes

  9. Two fundamental roles of molecular data in conservation genetics Mechanistic : Deciphering processes Evolutionary potential Local adaptation

  10. The promises of GENOMICS

  11. The promises of GENOMICS • Scaling up genome coverage • for any non-model species: • Improve estimates of population genetic • and evolutionary parameters.

  12. The promises of GENOMICS • Scaling up genome coverage • for any non-model species: • Improve estimates of population genetic • and evolutionary parameters. • II. Markers « that counts » (SNP) and • integrative approach (all the « …ics »): • Elucidate the functional significance • of molecular variation.

  13. The promises of GENOMICS III. Get to the « real stuff » for conservation genetics : Finding causal relationships between genetic variation, phenotypes and the environment to predict future dynamics of selectively important variation and potential for adaptation to new conditions.

  14. The promises of GENOMICS What genotyping methods to use?... With SNP development Without SNP development RRL RADseq GBS

  15. The promises of GENOMICS What genotyping methods to use?...

  16. Towards genome enabled conservation of salmonid fishes • Outline: • - Illustrate from our own work how genomics • can contribute to improve our knowledge • in 3 general topics of direct relevance to • conservation genetics: • - Genomic basis of ecological speciation • - Scale of local adaptation • - Introgressive hybridization and stocking • Discuss some pros- and cons- of different • genotyping strategies.

  17. I. The unfolding of genomic divergence during ecological speciation in whitefish. Pierre-Alexandre Gagnaire

  18. Whitefish are more interesting and as • tasty as salmon !..... Pierre-Alexandre Gagnaire

  19. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001)

  20. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001) 1. Direct selection acting on a few genomic regions.

  21. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001) 1. Direct selection acting on a few genomic regions. 2. Differentiation accumulates around targets of selection by divergence hitchhiking (DH)

  22. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001) 1. Direct selection acting on a few genomic regions. 2. Differentiation accumulates around targets of selection by divergence hitchhiking (DH) 3. Genetic divergence eased by genome hitchhiking (GH) : global reduction of gene flow caused by selection

  23. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001) 1. Direct selection acting on a few genomic regions. 2. Differentiation accumulates around targets of selection by divergence hitchhiking (DH) 3. Genetic divergence eased by genome hitchhiking (GH) : global reduction of gene flow caused by selection. 4. Complete reproductive isolation. Exchange of new advantageous mutations impossible.

  24. The unfolding of genomic divergence during ecological speciation The genic view of speciation (Wu 2001) 1. Direct selection acting on a few genomic regions. 2. Differentiation accumulates around targets of selection by divergence hitchhiking (DH). 3. Genetic divergence eased by genome hitchhiking (GH) : global reduction of gene flow caused by selection. 4. Complete reproductive isolation. Exchange of new advantageous mutations impossible. • More ecologically diverged populations should have more and larger genomic regions (DH) and be more genetically differentiated overall (GH)

  25. Phenotypic gradient parallels ecological gradient Gradient of phenotypic variation Landscape (biotic and abiotic) with higher potential for intra-population competition and more potential for distinct trophic niches associated with increased phenotypic divergence Lu & Bernatchez 1999 ; Landry et al. 2007; 2010. The unfolding of genomic divergence during ecological speciation

  26. The unfolding of genomic divergence during ecological speciation Objectives: . RAD genotype-by-sequencing approach to: 1 . Test the hypothesis that gradient of phenotypic and ecological divergence correlates with overall genetic divergence (GH). 2. Test the hypothesis that DH can drive the divergence of large (many cM) genomic regions. 3. Test whether divergence concentrated on a few regions or widely spread.

  27. Consensus sex-averaged map length: 3118 cM Average size of LG : 78 cM 4887 mappable SNPs genotyped in 102 progeny from one backcross 40/40 linkage groups identified Density: 1.56 marker per cM (or 122 markers per LG) The unfolding of genomic divergence during ecological speciation SNP discovery and genetic mapping using sequenced RAD Tags

  28. Témiscouata Fst = 0.008 East L. Fst = 0.029 Webster L. Fst = 0.049 Indian P. Fst = 0.105 Cliff L. Fst = 0.216 The unfolding of genomic divergence during ecological speciation Mapping position (cM) (40 chromosomes)

  29. Cliff Indian Webster East Témiscouta 0 0.6 1.2 1.8 2.4 3.0 The unfolding of genomic divergence during ecological speciation R2 = 0.849 Fst Phenotypic divergence

  30. The unfolding of genomic divergence during ecological speciation . Sliding window analysis: Fst of 90% quantile SNP vs. chromosomal distance from outlier regions

  31. Témiscouata East Size of regions of divergence (cM) Webster Indian Cliff Chromosomes The unfolding of genomic divergence during ecological speciation

  32. The unfolding of genomic divergence during ecological speciation 1 . Continuum of overall genetic divergence between dwarf and normal whitefish which correlates with adaptive phenotypic divergence. Intensity of selection imposed by biotic and abiotic landscape drives the extent of Global hitchhiking (GH). 2 . Divergence hitchhiking can drive the divergence of “large” genomic regions (at least up to 10cM). 3 . Divergence is widely spread over chromosomes but chromosome-specific effect and partially parallel only. Parallel phenotypic evolution not accompanied by strong genomic parallelism.

  33. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Vincent Bourret

  34. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition • Local adaptation in the wild • Documented in a wide range of species • Heterogeneous environmental conditions • How local is local adaptation • Geographical level ? • Genomic level ? Understand the evolution of the genome under environmental selective pressure

  35. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition

  36. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Genomics Landscape Environmental differentiation Physical barriers Determinants of population connectivity • Neutral and adaptive divergence in HD • Functional inferences • Genomic localization • Define neutral connectivity • Associate adaptive and environmental divergence • Extent of local adaptation • Key biological functions • and genomic regions

  37. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Using µsats • Regional structure • 7 regions • 2 X differentiation

  38. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Objectives: • Using the 7k SNP Infinium chip (CIGENE) to: • Define regional structure • Identify markers potentially under selection • Associate genetic and ecological differences • Identify biological functions and • localize genomic regions involved • in local adaptation

  39. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition • Materials • 25 individuals/pop • 26 populations • 7 regions represented • 3824 neutral SNPs Labrador Anticosti Lower North Shore Southern Quebec PC2 Quebec City Ungava Higher North Shore PC1 • Results • Regional clustering • Confirms µsat clusters PC3

  40. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Hierarchical Fdist • Genome scan (p < 0.01) • 84 divergent SNPs • Mean FCT = 0.07 AMOVA - Strong regional differences Neutral & Adaptive Analysis of MOlecularVAriance (AMOVA)

  41. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition • Environmental parameters • Reduce collinearity of variables via PCA • 49 variables reduced to 10 factors • Factor 1 = Climatic (Temperature) • Factor 2 = Climatic (Rain) • Factor 3 = River characteristics • Factor 4 = Geology • Regional variation Geology 11.3% River properties 12.8% Climatic (Temperature) 33.8%

  42. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition Redundancy analysis (RDA) Strong regional components driven by different genetic and environmental variables 6 factors out of 10 are significantly correlated with outliers SNP frequencies Identify SNPs strongly correlated with different environmental variables Climatic (T°) River prop. Climatic (Rain) Geology (F7) Geology

  43. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition • Global annotation (Blast2Go) • 1615 annotated sequences • Diversity of functions and processes • Outliers Enrichment analysis • For p < 0.05 outliers GO-terms over representation • SNPs associated with immune system protein (Syndecan) Immune system diversity (MHC class IIß) was shown to differ among regions (Dionne et al. 2007)

  44. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition 7 5 Chromosomal distribution of divergent loci 3 1 FCT Log10 p-value 7 5 3 1 Distance in cM

  45. II. Conservation Genomics and Adaptive Divergence of Atlantic Salmon (Salmo salar) In High Definition • Confirm regional structure : Reveals regional level of local adaptation • Identify markers potentially under selection Few, but distributed over the genome, representing many biological functions. • Associate genetic and ecological differences Regional population genomic structure correlates with environmental landscape structure • Correlations between environmental parameters and specific biological functions Temperature. vs immune related genes

  46. III. Evaluating genetic impacts of stocking on brook charr by means of SNP population genomics Fabien Lamaze

  47. III. Evaluating genetic impacts of stocking on brook charr by means of SNP population genomics

  48. III. Evaluating genetic impacts of stocking on brook charr by means of SNP population genomics

  49. III. Evaluating genetic impacts of stocking on brook charr by means of SNP population genomics

  50. III. Evaluating genetic impacts of stocking on brook charr by means of SNP population genomics Coding genes SNP development from cDNA pyrosequencing

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