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MPAW Estimation of divergence times Fabia U. Battistuzzi [email_address]
Two dimensions of evolution Lineage Relations Time frame Evolutionary Rate
Molecular clocks – brief overview Time Sequence Change X Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st  protein clock
Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st  protein clock Neutral theory Rate tests
Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st  protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Ancestor Descendant slower faster
Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st  protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Local rates slower faster
Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st  protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Local rates Autocorrelated clocks Uncorrelated clocks
What can we do with molecular clocks? ,[object Object],[object Object],[object Object],[object Object],Eastern fox squirrel ( Sciurus niger ) lacks phylogeographic structure: recent range expansion and phenotypic differentiation
Molecular clock packages available ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Molecular clock packages available ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Calibration priors Minimum only Maximum only Minimum-Maximum time lognormal : 95% probability uniform time exponential time normal time
Calibration priors Minimum only Maximum only Minimum-Maximum time : 95% probability time exponential time normal time Hedges and Kumar, Trends in Genetics (2004)
BEAUTI & BEAST ,[object Object],[object Object]
Phylogeny specification <newick id=&quot;startingTree&quot;> (((((Ssc:0.65,Bta:0.65):0.16,((Cfa:0.46,Fca:0.46):0.28,Eca:0.74):0.07):0.11,(((Rno:0.20,Mmu:0.20):0.65,Ocu:0.85):0.05,(((Hsa:0.05,Ptr:0.05):0.05,Ppy:0.10):0.13,Mml:0.23):0.67):0.02):0.81,Tvu1:1.73):1.37,Gga:3.10); </newick>
Strict clock & Relaxed clock Priors
Operators ,[object Object]
Generations ,[object Object]
Beast running…
A fuzzy caterpillar
MCMCTree seqfile = exampleseqs.phy treefile =  example.tre outfile = exampleseqs_3.out (((((Ssc,Bta),((Cfa,Fca)' B(0.45,0.47) ',Eca)),(((Rno,Mmu),Ocu),(((Hsa,Ptr),Ppy)' B(0.09,0.11) ',Mml))),Tvu1),Gga);
MCMCTree seqfile = exampleseqs.phy treefile =  example.tre outfile = exampleseqs_3.out (((((Ssc,Bta),((Cfa,Fca)‘ L(0.35,0.1,0.5,0.025) ',Eca)),(((Rno,Mmu),Ocu),(((Hsa,Ptr),Ppy),Mml))),Tvu1),Gga); p L p L t L p c
MCMCTree seqfile = exampleseqs.phy treefile = example.tre outfile = exampleseqs_3.out ndata = 1 usedata = 3  * 0: no data; 1:seq like; 2:use in.BV; 3: out.BV clock = 3  * 1: global clock;  2: independent rates; 3: correlated rates RootAge = < 3.0  * safe constraint on root age, used if no fossil for root. Ancestor Descendant slower faster slower faster Ancestor Descendant uncorrelated autocorrelated
MCMCTree model = 4  * 0:JC69, 1:K80, 2:F81, 3:F84, 4:HKY85 alpha = 0  * alpha for gamma rates at sites ncatG = 5  * No. categories in discrete gamma cleandata = 0  * remove sites with ambiguity data (1:yes, 0:no)? BDparas = 2 2 0.1  * birth, death, sampling kappa_gamma = 6 2  * gamma prior for kappa alpha_gamma = 1 1  * gamma prior for alpha rgene_gamma = 1 7.13  * gamma prior for overall rates for genes sigma2_gamma = 1 1.15  * gamma prior for sigma^2 (for clock=2 or 3) rgene : prior on rate parameter;  Sigma2 : prior on rate heterogeneity;
TimeTrees 300 250 200 150 100 50 0 Time (millions of years)
TimeTrees Ssc Bta Cfa Fca Eca Rno Mmu Ocu Hsa Ptr Ppy Mml Tvu1 Gga 0 50 100 150 200 Time (millions of years)
TimeTrees Ssc Bta Cfa Fca Eca Rno Mmu Ocu Hsa Ptr Ppy Mml Tvu1 Gga 0 50 100 150 200 Time (millions of years)
BEAST
MCMCTree autocorrelation uncorrelation
MultiDivTime
95% Credibility intervals TT TT Success Failure Model Match Model Violation
Things to remember ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Questions ?

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Estimation of divergence times

  • 1. MPAW Estimation of divergence times Fabia U. Battistuzzi [email_address]
  • 2. Two dimensions of evolution Lineage Relations Time frame Evolutionary Rate
  • 3. Molecular clocks – brief overview Time Sequence Change X Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st protein clock
  • 4. Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st protein clock Neutral theory Rate tests
  • 5. Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Ancestor Descendant slower faster
  • 6. Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Local rates slower faster
  • 7. Molecular clocks – brief overview Kumar, Nature Reviews Genetics (2005) 1962 1968 1972 1976 1984 1989 1997 2006 1 st protein clock Neutral theory Deut.-Prot. divergence Rate tests Rate Autocorrelation Local rates Autocorrelated clocks Uncorrelated clocks
  • 8.
  • 9.
  • 10.
  • 11. Calibration priors Minimum only Maximum only Minimum-Maximum time lognormal : 95% probability uniform time exponential time normal time
  • 12. Calibration priors Minimum only Maximum only Minimum-Maximum time : 95% probability time exponential time normal time Hedges and Kumar, Trends in Genetics (2004)
  • 13.
  • 14. Phylogeny specification <newick id=&quot;startingTree&quot;> (((((Ssc:0.65,Bta:0.65):0.16,((Cfa:0.46,Fca:0.46):0.28,Eca:0.74):0.07):0.11,(((Rno:0.20,Mmu:0.20):0.65,Ocu:0.85):0.05,(((Hsa:0.05,Ptr:0.05):0.05,Ppy:0.10):0.13,Mml:0.23):0.67):0.02):0.81,Tvu1:1.73):1.37,Gga:3.10); </newick>
  • 15. Strict clock & Relaxed clock Priors
  • 16.
  • 17.
  • 20. MCMCTree seqfile = exampleseqs.phy treefile = example.tre outfile = exampleseqs_3.out (((((Ssc,Bta),((Cfa,Fca)' B(0.45,0.47) ',Eca)),(((Rno,Mmu),Ocu),(((Hsa,Ptr),Ppy)' B(0.09,0.11) ',Mml))),Tvu1),Gga);
  • 21. MCMCTree seqfile = exampleseqs.phy treefile = example.tre outfile = exampleseqs_3.out (((((Ssc,Bta),((Cfa,Fca)‘ L(0.35,0.1,0.5,0.025) ',Eca)),(((Rno,Mmu),Ocu),(((Hsa,Ptr),Ppy),Mml))),Tvu1),Gga); p L p L t L p c
  • 22. MCMCTree seqfile = exampleseqs.phy treefile = example.tre outfile = exampleseqs_3.out ndata = 1 usedata = 3 * 0: no data; 1:seq like; 2:use in.BV; 3: out.BV clock = 3 * 1: global clock; 2: independent rates; 3: correlated rates RootAge = < 3.0 * safe constraint on root age, used if no fossil for root. Ancestor Descendant slower faster slower faster Ancestor Descendant uncorrelated autocorrelated
  • 23. MCMCTree model = 4 * 0:JC69, 1:K80, 2:F81, 3:F84, 4:HKY85 alpha = 0 * alpha for gamma rates at sites ncatG = 5 * No. categories in discrete gamma cleandata = 0 * remove sites with ambiguity data (1:yes, 0:no)? BDparas = 2 2 0.1 * birth, death, sampling kappa_gamma = 6 2 * gamma prior for kappa alpha_gamma = 1 1 * gamma prior for alpha rgene_gamma = 1 7.13 * gamma prior for overall rates for genes sigma2_gamma = 1 1.15 * gamma prior for sigma^2 (for clock=2 or 3) rgene : prior on rate parameter; Sigma2 : prior on rate heterogeneity;
  • 24. TimeTrees 300 250 200 150 100 50 0 Time (millions of years)
  • 25. TimeTrees Ssc Bta Cfa Fca Eca Rno Mmu Ocu Hsa Ptr Ppy Mml Tvu1 Gga 0 50 100 150 200 Time (millions of years)
  • 26. TimeTrees Ssc Bta Cfa Fca Eca Rno Mmu Ocu Hsa Ptr Ppy Mml Tvu1 Gga 0 50 100 150 200 Time (millions of years)
  • 27. BEAST
  • 30. 95% Credibility intervals TT TT Success Failure Model Match Model Violation
  • 31.

Notes de l'éditeur

  1. Evolution expressed in time units Allows comparisons across trees with different evolutionary scales (e.g., different rates)
  2. Basic principle of molecular clocks Global clocks vs. local/relaxed clocks Rate variation models
  3. Basic principle of molecular clocks Global clocks vs. local/relaxed clocks Rate variation models
  4. Basic principle of molecular clocks Global clocks vs. local/relaxed clocks Rate variation models
  5. Basic principle of molecular clocks Global clocks vs. local/relaxed clocks Rate variation models
  6. Basic principle of molecular clocks Global clocks vs. local/relaxed clocks Rate variation models
  7. Screen shots of Beauti with the various options Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  8. Screen shots of Beauti with the various options Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  9. Screen shots of Beauti with the various options Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  10. Screen shots of Beauti with the various options Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  11. Screen shots of Beauti with the various options Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  12. Show how to fix phylogeny Discuss problem of priors and how to define them discuss calibration distributions Priors only
  13. Cauchy distribution for calibrations
  14. Cauchy distribution for calibrations
  15. Cauchy distribution for calibrations
  16. Screen shots of mcmctree ctl files AR vs. RR Cauchy distribution for calibrations