1. A short introduction to the theory and practice of phylogenetic inference
Bill Bruno
Brian Foley
Thomas Leitner
Theoretical Biology & Biophysics
Los Alamos National Laboratory

2. Overview Introduction & Alignments - Brian Foley
Distance-based Methods, Models & Tree search - Bill Bruno
Character-based Methods, Bootstrap & Molecular Clock - Thomas Leitner
Hands-On Work Time
Group Discussion

3. From Data: To Phylogenetic Tree: www.t10.lanl.gov
myosin/trees/trees.html

4. Multiple Sequence Alignments
Choose the data set
Select an appropriate outgroup
Next closest relative to group(s) under study
Still close enough to align well
Create the alignment
Get Sequences in right format (FASTA for example)
Use a program (CLUSTALW, HMMER, DIALIGN)
Hand-edit the alignment (BioEdit, SeAl, MASE, JALview)
Remove uncertain columns (gaps, for example)

5. Pairwise Alignments
Typical settings include gap open and gap extension penalties
Dynamic Programming Algorithm is fast and efficient
BLAST (Basic Local Alignment Search Tool) does a poor job with pairs that contain many in/dels BLAST scores depend on length as well as % identity

6. Multiple Sequence Alignments
NEVER blindly trust a machine-made alignment always view the entire alignment with an alignment editor (BioEdit, SeAl, MASE, jalview) and adjust or trim questionable regions
Consider gaps, IUPAC ambiguity codes (R = purine etc) and how the phylogenetic software will treat them, stripping columns with these characters is one option
Gene reorganization presents a problem for genome sized regions
Phylogenetic comparison can only be done on region of overlap of all sequences in the alignment
Multiple Sequence Alignment Software
ProbCons
TreeAlign Methods in Enzymology 183:
ClustalW Methods in Enzymology 266:
MALIGN Journal of Heredity 85:
HMMER
GeneDoc
GCG Wisconsin Package
TAAR
Ctree
DAMBE
POY
ALIGN
DNASIS
Etc…

7. Distance based methods
Alignment + Model 
Pairwise Distance Matrix 
Tree
When more than 3 taxa, tree distances are over determined. So, find best tree.
What is "best"?
Ideally, distance through tree = pairwise distances
Optimality conditions:
minimum evolution, least squares, Weighbor...

8. Substitution models Evolutionary Distance = rate  evolutionary time
: ModelTest via web
Evolutionary Distance = rate  evolutionary time
Distance of 1.0 means on average one change per site
Depends on model of evolution, except for short distances
(when there is never more than 1 change per site, no homoplasy)

9. Correcting for multiple events
T Sequence d D
AATAG GAATA 0 0
ACTAG GAATA 1 1
ACTAG GGATA 2 2
AATAG GGATA 1 3
AAAAG GAATA 1 5
AAAAA GAACA 3 7

10. Distance Tree Methods Extremely fast Can be unbiased, robust
Weighbor is most rigorous, but FastME can give excellent, but biased results
Suitable for other problems: UPGMA
More reliable
Weighbor
Fitch-
Margoliash
BioNJ
FastME NJ
Less robust
Faster
Slower

11. Searching for the best tree
There are (2n - 3)! / 2n-1(n-1)!
trees for n taxa
Thus, for larger datasets not all
trees can be tested
Exhaustive search
Heuristic search
Stepwise addition
Star decomposition
Branch swapping
Algorithmic trees
Other aspects of tree space
Random trees
Consensus trees
Unresolved trees
# TAXA
# TREES 2 1 4 3 5 15 10
2 E6 22
3 E23 50
3 E74
100
2 E182
10 E6
5 E

12. Character based methods
Uses the aligned sequences directly to calculate a tree according to an optimalization criterion:
Maximum parsimony (DNAPARS, PAUP*, MEGA, etc)
Discriminates using parsimonious informative sites
Selects the tree which requires the least number of steps to explain the alignment
Maximum likelihood (DNAML, PAUP*, PAML, etc)
Requires an explicit model of character evolution
Calculates likelihood for each state at all sites
Selects the tree with the highest overall likelihood (least negative log likelihood value)

13. Maximum Parsimony A B C O 1 3 2 O 3 2 1 1 12345 67890 GATCC TAGGC
Taxon Alignment 1
GATCC TAGGC
GGTCA CATGT
GGTCA TATCT
O GATAC CAGCA O 1 3 2
Character 2 A B C A G
(A)
(G) O 3 2 1
Maximum Parsimony tree
Tree Steps Sum A B C

14. Bootstrapping Non-parametric bootstrap
Bootstrap 50% majority-rule consensus tree
/ p1.136(1) |
p1.719(2)
| / p2.135(3)
| |
| / p3.105(4)
| | |
| | \ p3.529(5)
| |
| p5.317(6)
| p6.6767(7)
\ p7.6760(8)
| / p8.159(9)
| /
| | \ p8.822(10)
| /
| | | / p11.113(12)
| | \
\ \ p (13)
\ p9.256(11)
Bipartitions found in one or more trees and frequency of occurrence (bootstrap support
values):
1 1
Freq %
** %
***** %
** %
..*********** %
**.** %
..*** %
..***..* %
...** %
..***.** %
..** %
.....** %
..***.* %
.....*..***** %
.....**.***** %
*** %
..****** %
.....*.* %
..*.* %
*..** %
.**** %
...**..* %
..***.******* %
.....******** %
.....*.****** %
.****..* %
..**...* %
...*...* %
.****.** %
..***..****** %
100 groups at (relative) frequency less than 5% not shown
Non-parametric bootstrap
Calculate a tree under a model using a tree building method
Create pseudo replicates of the alignment
Recalculate a tree for each pseudo replicate
Compute a consensus tree of all pseudo trees
Tests the reliability/robustness of the model-method
Biased (usually conservative)
Parametric bootstrap
Tests the evolutionary model and process

15. The molecular clock Assumes ultra-metric data/tree
Genetic distance -time relationships

16. The molecular clock Evolutionary model important Rate variation
Genetic distance
Time

17. Hands-on Open file in BioEdit Calculate distance-matrix tree
Manually check & correct alignment
Calculate distance-matrix tree
Calculate matrix with DNADIST
Calculate tree with NEIGHBOR
Calculate character-based tree
DNAPARS or DNAML
Calculate bootstrap support
Use SEQBOOT, DNADIST, NEIGHBOR, CONSENSE
View tree in TreeView

18. Group discussion Pro’s & Con’s Where to spend your time & effort
What else is available