The program MrBayes reads the NEXUS format. Therefore, data can be entered with the DATA block described above. The command block for MrBayes is written just below the DATA block. Annotations for each command and option are taken from the program’s manual.
A.4.1 The MrBayes command block:
BEGIN MRBAYES; [starts the MrBayes block]
SET [Sets run conditions and defines active data partition]
AUTOCLOSE = YES [The program will not prompt you during the course of executing the file.]
NOWARNINGS = YES; [If nowarnings is set to yes, then the program will not prompt you when overwriting an output file that is already present.]
OUTGROUP 1; [This command assigns the first taxon of the DATA block to the outgroup. Only a single taxon can be assigned to be the outgroup.]
LSET [Sets the parameters of the likelihood model]
NST = 6 [Sets the number of substitution types. "6" allows all rates to be different, subject to the constraint of time-reversibility (e.g., a GTR model).]
RATES = GAMMA [Sets the model for among-site rate variation. Gamma specifies Gamma- distributed rates across sites. The rate at a site is drawn from a gamma distribution. The gamma distribution has a single parameter that describes how much rates vary.]
NGAMMACAT = 6; [Sets the number of rate categories for the gamma distribution. The gamma distribution is continuous. However, it is virtually impossible to calculate likelihoods under the continuous gamma distribution. Hence, an approximation to the continuous gamma is used; the gamma
distribution is broken into ncat categories of equal weight (1/ncat). The mean rate for each category represents the rate for the entire category. This option allows you to specify how many rate categories to use when approximating the gamma.]
MCMC [This command starts the Markov chain Monte Carlo (MCMC) analysis. The posterior probability of phylogenetic trees (and other parameters of the substitution model) cannot be determined analytically. Instead, MCMC is used to approximate the posterior probabilities of trees by drawing (dependent) samples from the posterior distribution. This program can implement a variant of MCMC called "Metropolis-coupled Markov chain Monte Carlo", or MCMCMC for short. Basically, "Nchains" are run, with Nchains - 1 of them heated. The chains are labeled 1, 2, ..., Nchains. The heat that is applied to the i-th chain is B = 1 / (1 + temp X i). B is the power to which the posterior probability is raised. When B = 0, all trees have equal probability and the chain freely visits trees. B = 1 is the "cold" chain (or the
distribution of interest). MCMCMC can mix better than ordinary MCMC; after all of the chains have gone through one cycle, two chains are chosen at random and an attempt is made to swap the states (with the probability of a swap being determined by the Metropolis et al.
equation). This allows the chain to potentially jump a valley in a single bound.]
NGEN = 1000000 [This option sets the number of cycles for the MCMC algorithm. This should be a big number as you want the chain to first reach stationarity, and then remain there for enough time to take
lots of samples.]
PRINTFREQ = 500 [This specifies how often information about the chain is printed to the screen.]
SAMPLEFREQ = 50 [This specifies how often the Markov chain is sampled. You can sample the chain every cycle, but this results in very large output files. Thinning the chain is a way of making these files smaller and making the samples more independent. ]
NCHAINS = 4 [Specifies how many chains are run for the MCMCMC variant.]
STARTINGTREE = RANDOM [The starting tree for the chain can either be randomly selected or user-defined. It might be a good idea to start from randomly chosen trees; convergence seems likely if independently run chains, each of which started from different random trees, converge to the same answer.]
SAVEBRLENS = YES; [This specifies whether branch length information is saved with the trees.]
Appendix
SUMT [This command summarizes the trees in a file named "<filename>". All of the trees are read from the file and the proportion of the time any single taxon bipartition is found is counted.
The proportion of the time that the bipartition is found is an approximation of the posterior probability of the bipartition. (Remember that a taxon bipartition is defined by removing a branch on the tree, dividing the tree into those taxa to the left and right of the removed branch. This set is called a taxon bipartition.) The branch length of the bipartition is also recorded. The result is a list of the taxon bipartitions found, the frequency with which they were found, the posterior probability of the bipartition and, if the branch lengths were recorded, the mean and variance of the length of the branch. ]
CONTYPE = HALFCOMPAT [creates a consensus tree equivalent to a 50 % Majority rule consensus tree]
BURNIN = 4000; [Specifies the number of initial, saved trees that are ignored when calculating the consensus tree. It may take a while for the chain to reach stationarity. Samples taken when the chain is not at stationarity (the early phase of the chain) should be discarded. The default is 0, but you may want to discard those trees that were sampled while the chain was not at stationarity.]
END; [Denotes end of a block in file]
QUIT; [Quits the program]
The MrBayes command block without annotations:
begin mrbayes;
set autoclose=yes nowarnings=yes;
[outgroup 1;]
lset nst=6 rates=gamma ngammacat=6;
mcmc ngen=1000000 printfreq=500 samplefreq=50 nchains=4 startingtree=random savebrlens=yes;
sumt contype=halfcompat burnin=4000;
quit;
end;
Acknowledgements
154
Acknowledgements
First of all, I´d like to express my gratitude to Prof. T. Friedl and Prof. G. Rambold, who initiated this project. Further, especial acknowledgement is due to Prof. T. Friedl who provided supreme lab facilities without which this work could not have succeeded as far as it did. Many thanks are also due for his invitation to access his collection of literature.
For an initial introduction to lichenes, I am much indepted to Patrick Dornes, who most patiently shared his competence and enthusiasm about lichens with me and certainly provided a valuable stimulus to me. Special thanks are due to PD H. Mayrhofer, who wisely selected Physciaceae species of particular interest. Also his recommendations for initial readings on Physciaceae are heartily appreciated.
I am grateful to Patrick Dornes, Anders Nordin and the herbarium curators Walter Obermayer, Harrie Sipman and Dagmar Triebel for providing valuable sample vouchers and helping in sample determination. Many thanks to Virginia Souza-Egypsi, Alfredo Espinosa and Patrick Dornes for excellent guidance on various excursions where fresh material had been collected.
Thanks are due to Andreas Beck, who gave an initial introduction to DNA extraction and PCR amplification. I would like to thank Elke Zufall-Roth for excellent assistance in the lab as well as Dominik Hepperle and Frank Kauff for valuable advice in phylogenetic analyses. Thanks are due to Jana Fredersdorf, Claudia Kamcke, Thomas Lehmann und Boris Rewald for their cooperation in the student lab 2001 in which numerous seqeunce data had been generated.
I´m especially indepted to Prof. T. Friedl for an extensive review of the complete manuscript of this thesis. Without his comments many of the results and much of the discussion wouldn´t have been presented as pointed and structured. I further would like to thank Helmut Mayrhofer, David Hewitt, Toby Spribille, Jochen Heinrichs, Maren Huck and Patrick Dornes for helpful comments on various parts of the manuscript.
Many thanks are due to Prof. D. Bhattacharya (Iowa, USA) for his invitation to his lab to work on secondary structure and self-splicing activity in group I introns in Oct. 1999 and Prof. F. Lutzoni for his invitation to continue the work on introns at his fabulous lab at Duke University (Durham NC, USA) Oct. – Dec. 2002. Thanks are due to the Universitätsbund Göttingen, who financially supported visits to various conferences.
Special thanks to the EPSAG crew (Elke Zufall-Roth, Ilse Kunkel, Marlis Heinemann, Dr. D. Mende and all the others) for the friendly atmosphere which made lab work so much more enjoyable. Special thanks are expressed to Dr. D. Mende for his patience and competence in maintainig computers and software.
Last not least I thank my parents for their extensive support throughout the years.
Erklärung
Erklärung
Hiermit erkläre ich, daß ich die Arbeit selbständig verfaßt und keine anderen als die von mir
angegebenen Quellen und Hilfsmittel benutzt habe. Ferner erkläre ich, daß ich nicht anderweitig mit oder ohne Erfolg versuche t habe, eine Dissertation einzureichen oder mich der Doktorprüfung zu unterziehen.
Göttingen,
Lebenslauf
156
Lebenslauf
Name: Gert Helms
Adresse: Lange Str. 29 Geburtstag: 27.05.1968
Geburtsort: Tübingen
Nationalität: deutsch
Bildung:
Gymnasium Mainz-Gons. 1978 - 1987Abitur 23.06.1987
Zivildienst:
Rettungshelfer in Würzburg 01.10.1987 - 31.05.1989Studium:
Biologie in Kaiserslautern Okt.1989 - Feb. 1996 Diplom 29.02.1996Beginn der Promotion an der Universität Göttingen: 1.4.1999 Voraussichtliches Ende der Promotion: 7.11.2003