Génétique des populations dans                                      l’espace et dans le temps:                            ...
POPULATION AND CONSERVATION GENETICS                       POPULATION GENETIC DATA                     Y chromosome       ...
Problématiques• Impact de la fragmentation de l’habitat sur la diversité  intra-spécifique :   – Diversité génétique et ta...
The Kinabatangan                 Sulu SeaFloodplain                               1 cm = 5                               k...
The Data– 279 samples collected with 32 twice (hair + faeces)– 247 individuals (176 nests and 71 faeces) extracted  and am...
Size       Model of Beaumont 1999 and Storz et Beaumont, 2002                            Linear           Exponential     ...
Model of Beaumont 1999    Microsatellite        Data                               Storz and Beaumont, 2002Linear         ...
Population size change
Time since the population size change                           FE:   Forest exploitation                           F:    ...
Conclusions (at the time)1.   Strong signal for a bottleneck2.   The signal is robust to the mutation model3.   The signal...
Habitat Fragmentation (and loss) in Daraina                    44 000 ha of fragmented forest      Loky River             ...
Habitat Fragmentation (and loss ?) in Daraina                        44 000 ha of fragmented forest                       ...
Habitat Fragmentation (and loss) in Daraina                              Faeces from 230 individuals                      ...
Habitat Fragmentation (and loss) in DarainaRôle de la rivière Manakolana:        * structure la diversité        * ancienn...
Habitat fragmentation and loss             time             time
GENETIC DIVERSITY      Past                                          NEW                                          MUTATION...
GENETIC DIVERSITYPast      Ne = 1000                                                     Ne = 100PresentPresent   Ne = 100...
GENETIC DIVERSITY                                        EQUILIBRIUM (N1 pre-bottleneck)                          HETEROZY...
GENETIC DIVERSITY Past                                    Population size change :                                        ...
Habitat fragmentation and loss             time             time
Effect of population structure on bottleneck signals•   Models of population structure (100 demes in all simulations)     ...
Effect of population structure on bottleneck signals                        Can we separate population structure          ...
Conclusions  1. Population structure can mimic bottleneck signals  2. The signal is particularly strong when      1. Genet...
Habitat fragmentation and loss              time      or population structure              time            or both ?      ...
Vers de nouveaux outils de simulation (1)SPLATCHE-like: L. Excoffier et Cie                                            R. ...
Layer 1                              cell                    K: carrying capacity                    F: friction          ...
Vers de nouveaux outils de simulation (2)                                                 SG1         SG2     MATRIX (ngro...
1 MALE, 1 FEMALE                 1 DOMINANT M/F     n MALES,nm=1; nf=1; ndm=1; ndf=1         n NON-DOMINANT F/M m FEMALES ...
CONCLUSIONS• La génétique du paysage a tendance à ignorer le temps• Les méthodes d’inférence en génétique des populations ...
JE VOUS REMERCIE POUR VOTRE ATTENTION                       Anna Rozzi
Brigitte Crouau-Roy Univ. Paul Sabatier, Toulouse, FranceLounes Chikhi         CNRS and Univ. Paul Sabatier, Toulouse, Fra...
Chikhi grenoble bioinfo_biodiv_juin_2011
Chikhi grenoble bioinfo_biodiv_juin_2011
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Chikhi grenoble bioinfo_biodiv_juin_2011

  1. 1. Génétique des populations dans l’espace et dans le temps: reconstruire l’histoire démographique des populations Laboratoire Evolution et Diversité Biologique, CNRS, Toulouse Population and Conservation Genetics Group, IGC, Portugal Biodiversité et Informatique, Grenoble, 28 Juin 2011Photos: E. Quéméré, F. Jan, B. Goossens
  2. 2. POPULATION AND CONSERVATION GENETICS POPULATION GENETIC DATA Y chromosome mitochondrial DNA ---CAGTCAGTCAGT---CONSERVATION GENETICS HUMAN PAST DEMOGRAPHYHabitat Fragmentation Neolithic TransitionPopulation Decline Admixture in Human PopulationsAdmixture in Domesticates G T G G T T G G G G G NEW METHODS / SOFTWARE
  3. 3. Problématiques• Impact de la fragmentation de l’habitat sur la diversité intra-spécifique : – Diversité génétique et tailles des fragments – Distance géographique entre fragments sur la différenciation génétique – Barrières au flux géniques (routes, rivières, fleuves, villages, etc.) ? – Déterminer, quantifier et dater d’éventuels événements démographiques (goulots d’étranglements, expansions, mélanges) ayant influencé la diversité actuelle – Importance relative de la fragmentation d’origine anthropique et des phénomènes naturels – Importance de la structure spatiale, des expansions et contractions spatiales, de la structure sociale
  4. 4. The Kinabatangan Sulu SeaFloodplain 1 cm = 5 km Agricultural lands (mostly oil palm plantations) Lower Kinabatangan Wildlife Sanctuary Virgin Jungle Reserves Kinabatangan River Main road (Sandakan – Lahad Datu) Villages
  5. 5. The Data– 279 samples collected with 32 twice (hair + faeces)– 247 individuals (176 nests and 71 faeces) extracted and amplified– 200 individuals genotyped for 14 microsatellite loci divided into 9 samples (S1 to S9)– 14*200 = 2800 genotypes (7 missing = 0.25%)– 2 di and 12 tetra loci.
  6. 6. Size Model of Beaumont 1999 and Storz et Beaumont, 2002 Linear Exponential N1 > N0 ? Parameters: N0 : current size N1 : ancestral size ta: nb of generations since the pop started to increase or decreaseN0 Reparameterize: r = N0/N1 tf = ta/ N0  = 2 N0  N1 < N0 ? Sampling ta (in generations) Past Present Time
  7. 7. Model of Beaumont 1999 Microsatellite Data Storz and Beaumont, 2002Linear Exponential Microsatellite Data r = N0/N1 tf = ta/ N0 Exponential  = 2 N0  N 0, N 1, t a, 
  8. 8. Population size change
  9. 9. Time since the population size change FE: Forest exploitation F: Farmers HG: Hunter-gatherers thin line: S1 thick line : S2
  10. 10. Conclusions (at the time)1. Strong signal for a bottleneck2. The signal is robust to the mutation model3. The signal is robust to a linear or exponential decrease (assuming a specific mutation model)4. The population decrease is very important5. The population decrease is very recent: recent anthropogenic changes
  11. 11. Habitat Fragmentation (and loss) in Daraina 44 000 ha of fragmented forest Loky River Indian Ocean Manambato River Golden-crowned sifaka Propithecus tattersalli Erwan Quéméré
  12. 12. Habitat Fragmentation (and loss ?) in Daraina 44 000 ha of fragmented forest Océan IndienPictures: E. Quéméré
  13. 13. Habitat Fragmentation (and loss) in Daraina Faeces from 230 individuals (105 social groups) 13 microsatellites Questions: 1. Role of the road as a barrier to gene flow 2. Role of savanna / grasslands 3. Role of the Manankolana river
  14. 14. Habitat Fragmentation (and loss) in DarainaRôle de la rivière Manakolana: * structure la diversité * ancienne barrière ? * lieu de peuplements humains ? * etc.
  15. 15. Habitat fragmentation and loss time time
  16. 16. GENETIC DIVERSITY Past NEW MUTATIONS POPULATION TIME SIZE (FINITE) LOSS OF MUTATIONS Present MUTATIONSGENETIC DIVERSITY GENETIC DRIFT
  17. 17. GENETIC DIVERSITYPast Ne = 1000 Ne = 100PresentPresent Ne = 100 Ne = 1000 Ne = 500Present GENETIC DIVERSITY Different demographic histories can produce similar or counter-intuitive results
  18. 18. GENETIC DIVERSITY EQUILIBRIUM (N1 pre-bottleneck) HETEROZYGOSITY: function(nA, freq.)NUMBER OF ALLELES EQUILIBRIUM (N0 post-bottleneck) TIME DIFFERENT TEMPORAL DYNAMICS OF THE TWO MEASURES
  19. 19. GENETIC DIVERSITY Past Population size change : recognizable signatureTIME A B ... NPresent PROBLEM : STRUCTURED POPULATIONS GENERATE A SIMILAR SIGNATURE TRUE AND FALSE SIGNATURES: WHO SHOULD YOU BELIEVE?...
  20. 20. Habitat fragmentation and loss time time
  21. 21. Effect of population structure on bottleneck signals• Models of population structure (100 demes in all simulations) Stepping-stone – n-island model (100 islands) – Stepping-stone (10 x 10) (toroidal) n-island• Parameters used – Stepwise mutation model assumed to simulate data – FST values used { 0.01 ; 0.05 ; 0.1 ; 0.25 } Differentiation – θ values used { 1; 10 } – Number of loci { 5 ; 20 } Diversity – 50 individuals sampled (100 genes) (mutation and pop size)• Sampling schemes : – n-islands model: samples from 1, 2, 10 and 50 demes – Stepping stone model: samples from 1, 2 neighbouring and 2 distant demes• 10 independent data sets for each parameter set (except 20 loci and 10 demes)
  22. 22. Effect of population structure on bottleneck signals Can we separate population structure from population crash? Bottleneck signals
  23. 23. Conclusions 1. Population structure can mimic bottleneck signals 2. The signal is particularly strong when 1. Genetic differentiation is high (gene flow is limited) 2. Genetic diversity is high 3. The number of loci used is large 3. The effect is less important when more than one population is sampled Need to develop methods that can separate these two kinds of scenarios (structure versus bottleneck)ad hoc ways to minimize the genetic structure effect is to spread sampling (one individual per “population”)
  24. 24. Habitat fragmentation and loss time or population structure time or both ? time
  25. 25. Vers de nouveaux outils de simulation (1)SPLATCHE-like: L. Excoffier et Cie R. Rasteiro P-A Bouttier V. Sousa
  26. 26. Layer 1 cell K: carrying capacity F: friction m: migration rate r: growth rate γ: admixture Genetic parameters: mutation rates,Layer 2 sequence length, etc
  27. 27. Vers de nouveaux outils de simulation (2) SG1 SG2 MATRIX (ngroups*ngroups) popstructure.txt S1 S2 S3 S4 S5 S1 0 1 0 1 1 S2 1 0 1 1 1 SG5 SG4 S3 0 1 0 1 1 S4 1 1 1 0 1 S4 1 1 1 1 0 SG3• SG1 is connected to pops 2, 4, 5•SG3 is connected to pops 2, 4, 5•SG2, SG4, SG5 are connected to all other SG’s E. Quéméré – C. Vanpé – B. Parreira
  28. 28. 1 MALE, 1 FEMALE 1 DOMINANT M/F n MALES,nm=1; nf=1; ndm=1; ndf=1 n NON-DOMINANT F/M m FEMALES nm=1; nf=n; ndm=1; ndf=0 nm=n; nf=m; ndm=0; ndf=0 nm=n; nf=1; ndm=0; ndf=1 Dominance = priority in reproduction
  29. 29. CONCLUSIONS• La génétique du paysage a tendance à ignorer le temps• Les méthodes d’inférence en génétique des populations ont tendance à ignorer l’espace• Comment intégrer ces deux notions ?• Madagascar est un lieu privilégié pour cela: colonisation humaine récente
  30. 30. JE VOUS REMERCIE POUR VOTRE ATTENTION Anna Rozzi
  31. 31. Brigitte Crouau-Roy Univ. Paul Sabatier, Toulouse, FranceLounes Chikhi CNRS and Univ. Paul Sabatier, Toulouse, France Instituto Gulbenkian de Ciência, Oeiras, PortugalBárbara Parreira, Rita Rasteiro, Vitor Sousa Inst. Gulbenkian de Ciência, Oeiras,PortugalPierre Luisi, Pierre-Antoine Bouttier INSA, Toulouse, FranceBenoît Goossens Cardiff Univ., UK – Sabah Wildlife Dept, MalaysiaMark Beaumont: Reading Univ., UKErwan Quéméré: Univ. Paul Sabatier,Toulouse, FrancePedro Fernandes: Bioinformatics Unit, IGC

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