Barbujani UCLA

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Barbujani UCLA

  1. 1. Nuragic Sardinians are still among us, and the Etruscans too. Two genealogical studies Guido Barbujani Dip. Biologia ed Evoluzione Università di Ferrara [email_address] UCLA, April 8, 2009
  2. 2. 1. The Etruscans do not resemble most modern Tuscans
  3. 3. A bit of history Etruscan a non-Indo-European language Documented from the end of VIII century BC Etruscan cities independent states Common culture and language, but never a political unit Maximum territory expansion: VI century BC Military defeats, Roman assimilation in the II century BC Dionysius of Halicarnassus: the Etruscans an Italic population Herodotus: the Etruscans seamen from Lydia, escaping famine
  4. 4. Adria (17, 5), Volterra (6, 3), Castelfranco di Sotto (2, 1), Castelluccio di Pienza (1, 1), Magliano and Marsiliana (25, 6) Tarquinia (18, 5), Capua (8, 6) 80 bone samples from 8 Etruscan necropoleis 27 individuals, 22 different haplotypes, h =0.946 Tuscans: 49 individuals from Francalacci et al. (1996)
  5. 5. Shared sequences between the Etruscans and modern populations 2 3 3 3 5 2 1 3 1 5 2 2 2 3 3 1 3 7 4 2 2 2 4
  6. 6. Genetic distances (F st x 1000) between the Etruscans and modern populations 36 80 90 70 48 74 118 55 50 37 47 41 76 60 51 57 261 69 65 41 62 73 71
  7. 7. 2. Testing hypotheses by serial coalescent simulation
  8. 8. Reconstructing (proceeding backwards in time) the maternal genealogy of a sample Two possibilities: either each individual has a different mom Or two individuals have the same mom (coalesence) Coalescence probability a function of population size N and sample size n
  9. 9. Past Present N = 10 N constant
  10. 10. Genealogies N = 10 N constant n = 6 9 generations MRCA
  11. 11. Mutation
  12. 12. Mutation ( sequences are arbitrary, their differences are not) 1 00000 00001 00010 00101 10101 1 2 3 3 4 5 01010
  13. 13. Il Modello: Serial Simcoal Serial coalescence Anderson C.N.K., Ramakrishnan U., Chan Y.L. e Hadly E.A. (2005) Bioinformatics INPUT Population size Population genealogy Population growth rate Migration matrix Mutation model and rate Sample sizes and ages OUTPUT N haplotypes Haplotype diversity Nucleotide diversity Mismatch distribution Haplotype sharing N=20 Modern sample (n=5) 0 100 Time (generations) Ancient sample (n=2)
  14. 14. Observed population statistics Consistency criterion: overlap between the 95% confidence intervals of observed and simulated statistics 0.028 0.024 F st 0.14 0.09 Haplotype sharing 4.50 5.03 3.91 Avg. mismatch 0.012 0.014 0.011 Nucleotide diversity 0.960 0.949 0.946 Haplotype diversity 60 40 22 Haplotype n 86 49 27 Sample size Murlo Tuscans Etruscans
  15. 15. median observed value simulated values The posterior probability (two-tailed) of a simulated statistic is represented by the gray area in the graph Two ways to combine the results: 1 estimate a joint posterior probability for all statistics; 2. count the number of statistics with P<0.05.
  16. 16. Simulation parameters <ul><li>Population sizes: Etruscans: 292,000  12 = 25,000 </li></ul><ul><li> Tuscans: 3,500,000  12 = 300,000 </li></ul><ul><li>Growth rate: Nt=N 0 e rt  r=1/100 ln 300,000/25,000 = 0.025 </li></ul><ul><li>Mutation rate: </li></ul><ul><li>1 mutation per million years per nucleotide </li></ul><ul><li> 360 nucleotides,  25 years per generation,  2  0.0045 </li></ul><ul><li>360 nucleotides </li></ul><ul><li>Transition bias: 0.94 </li></ul>
  17. 17. Etruscans and Tuscans a single population? Nf=25,000 Nf=25,000 r = 0 Model 1: Small population, constant size 0 100 Generations Tuscans Etruscans <ul><li>Allele sharing: 4.2% (1.4-8.1) OK </li></ul><ul><li>Hapl. diversity: </li></ul><ul><li>- Etruscans: > Obs. </li></ul><ul><li>- Tuscans: > Obs. </li></ul>
  18. 18. Etruscans and Tuscans a single population? Nf=300,000 Nf=25,000 r = -0.025 Model 3: Expanding population 0 100 Generations Tuscans Etruscans <ul><li>Allele sharing: 5.0% (1.3-9.1) OK </li></ul><ul><li>Hapl. diversity: </li></ul><ul><li>- Etruscans: > Obs. </li></ul><ul><li>- Tuscans: > Obs </li></ul>
  19. 19. Only models in which modern Tuscans and Etruscans belong to distinct genealogies are consistent with the data (  2 <31)
  20. 20. Interpretations, doubts <ul><li>Unless mutation rate is much higher than currently believed, the Etruscans left very few modern mitochondrial descendants in Tuscany (Belle et al. 2006) </li></ul><ul><li>Did they all go extinct? </li></ul><ul><li>Was the sample studied only representative of a social elite? </li></ul><ul><li>Did massive immigration dilute a component of Etruscan origin in the Tuscans’ mtDNA gene pool? </li></ul>Postmortem DNA modifications and/or technical problems affected the Etruscan mtDNA sequences (Achilli et al. 2007)
  21. 21. The similarity between the modern Tuscans and the Near East/Turkey suggests that the Etruscans came from there (Achilli et al. 2007)
  22. 22. No evidence of sequence errors in the Etruscan dataset
  23. 23. 61 tooth samples from Middle-Age Tuscany Guimaraes et al., submitted Joint analysis of 11 Etruscan sequences 27 Medieval sequences (900-1300 A.D.), from 6 cemeteries 322 (Achilli et al.) and 49 (Francalacci et al.) modern Tuscan sequences Murlo, Volterra, Casentino
  24. 24. Only the model in which medieval Tuscans and Etruscans belong to the same genealogy and modern Tuscans don’t is consistent with the data (Guimaraes et al., submitted) Model 1 0 C E M Model 4 C E M Model 2 C E M Model 3 C E M Model 5 C E M Model 6 E M C Model 7 E M C
  25. 25. 3. Or maybe the Etruscans are still among us, hiding somewhere?
  26. 26. Excoffier et al. (2005) Genetics 169:1727-1738 Estimating parameters and comparing models by ABC (Approximate Bayesian Computations)
  27. 27. Parameters: priors and posterior distributions 10 000 – 50 000 N e Medieval Tuscans 4000 – 21 000 N e Etruscans 100 – 2000 N e at split 10 000 – 100 000 N e Generation 27 100 – 10 000 N e Generation 26 101 – 1500 T estimated (bottleneck) 0.0003 – 0.0075 μ 50 000 – 500 000 | 10 000 – 70 000 N e Modern Tuscans Priors Parameters
  28. 28. Mod 1 Casentino Murlo Volterra SR = Straightforward rejection; LR = Logistic regression Mod 2 Mod 3 E M C 27 26 a1 a2 E M 27 26 a1 a2 Mod 1 0.000 0.010 0.990 100 SR 0.000 0.028 0.972 50000 RL Mod 3 Mod 2 Mod 1 Thresh. Method 0 1 0 100 0.SR 0.000 1 0.000 50000 RL Mod 3 Mod 2 Mod 1 Thresh. Method 0 1 0 100 SR 0.000 1 0.000 50000 RL Mod 3 Mod 2 Mod 1 Thresh. Method C E M 27 26
  29. 29. Parameters: priors and posterior distributions 10 000 – 50 000 N e Medieval Tuscans 100 – 2000 N e at split 10 000 – 100 000 N e Generation 27 100 – 10 000 N e Generation 26 101 – 1500 T estimated (bottleneck) 0.0003 – 0.0075 μ 10 000 – 70 000 N e Modern Tuscans from Casentino valley 20 000 – 200 000 N e Modern Tuscans Priors Parameters
  30. 30. SR = Straightforward rejection; LR = Logistic regression Ca E M Mu Vo E M Mu Vo Ca E M Mu Vo Ca A B C D Ca Mu Vo E M 27 26 a1 a2 27 26 27 26 a1 a2 a1 a2 a1 a2 27 26 0.000 0.966 0.011 0.023 100 SR 0 1 0 0 100 RL 0.056 0.912 0.003 0.000 50000 RL D C B A Thresh. Method
  31. 31. 4. Nuragic Sardinians resemble some, but not all, modern Sardinians
  32. 32. A genetic map of Europe (Menozzi, Piazza, Cavalli-Sforza 1978)
  33. 33. 53 tooth samples from 6 nuragic sites
  34. 34. Elimination of samples that do not comply with the strictest quality standards
  35. 35. 10 different sequences in 23 nuragic individuals h, haplotype diversity=0.83 Etruscans: 0.95 Tuscans: 0.96 Basques: 0.96 Greeks: 0.98 Sicilians: 0.96 Ogliastra 0.78 Gallura 0.93
  36. 36. Shared sequences among Nuragic people and other modern and ancient populations North Africa: 13.9 4 Near East: 10.7 6 Europe: 18.3 8 Iberians: 29.4 2 Etruscans: 22.2 4 Gallura: 18.5 1 Ogliastra: 54.6 4
  37. 37. Six models describing the genealogical relationships among Nuragic people and modern Sardinians Ogliastra 126 126 Ogliastra Gallura Gallura Gallura Ogliastra Ogliastra Model 2 Model 1 Model 3 0 0 Model 4 Model 5 Model 6 Gallura Gallura Gallura Ogliastra Ogliastra Latium Latium Latium
  38. 38. Parameters: priors and posterior distributions 0.06 - 1.3 per million years per site μ 1000 T split (Sardinia vs. Latium) 127 – 1000 [1, 2, 4, 5] or 1- 125 [3, 6] T split (Ogliastra vs. Gallura) 0 – 0.01 Migration rate from Latium 400 000 N e Latium 100 – 6 000 N e Ogliastra, Gallura at split 100 – 6 000 N e split 1000 – 40 000 N e Gallura 500 – 20 000 N e Ogliastra Priors Parameters
  39. 39. Observed summary statistics describing genetic variation in the Sardinia study Ogliastra / Gallura = 0.095 Gallura / Bronze Age = 0.100 Ogliastra / Bronze Age = 0.400 Haplotype sharing 0.0218 F st -2.02 -1.66 -0.97 -1.64 Tajima’s D 0.95 0.97 0.79 0.83 Haplotype diversity 4.07 4.42 2.49 1.39 Mean pairwise difference 45 31 22 10 N of segregating sites 36 21 26 10 Haplotype number Latium Gallura Ogliastra Bronze Age
  40. 40. Posterior probabilities of the models, with and without immigration (best 50 000 simulations) 0.983 0.002 0.015 0.813 0.081 0.106 Model 4 beats Model 1 >77% of times Model 2 Model 1 Model 3 Model 4 Model 5 Model 6
  41. 41. What happened in Italy between the Bronze-Age and now? Many things. Major demographic changes in the last few centuries documented by mtDNA in the Netherlands (Manni et al. 2002), in the British Isles (T ö pf et al. 2007) and in Iceland (Helgason et al. 2008), but not in the Iberian peninsula (Sampietro et al. 2005). Relatively recent immigration may have deeply changed the genetic structure of the population in part of Tuscany and in Gallura, but not Casentino and Ogliastra In studies of admixture, genealogical continuity between past and present is no longer an inevitable assumption, but rather a testable hypothesis (only at the mtDNA level, at present).
  42. 42. David Caramelli Giorgio Bertorelle Andrea Benazzo, Silvia Ghirotto Loredana Castrì Elise Belle Many thanks to Enza Colonna Stefano Mona Silvia Guimaraes Erica Fumagalli

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