1. Phylogenetic Inference
Data
Optimality Criteria
Algorithms
Results
Practicalities
9/20/2018
Chuck Staben

2. Our Goals Infer Phylogeny Phylogenetic inference Optimality criteria
Algorithm
Phylogenetic inference
(interesting ones)
9/20/2018
Chuck Staben

3. Watch Out
“The danger of generating incorrect results is inherently greater in computational phylogenetics than in many other fields of science.”
“…the limiting factor in phylogenetic analysis is not so much in the facility of software applicaition as in the conceptual understanding of what the software is doing with the data.”
9/20/2018
Chuck Staben

4. Phylogenetic Models
No transfer of genetic information by hybridization
All sequences are homologous
Each position in alignment homologous
Observed variation is valid sample from included group
Positions evolve independently
9/20/2018
Chuck Staben

5. Steps in Analysis Data Model (Alignment) DNA base substitution model
alignment method
“trimming” to a phylogenetic set
DNA base substitution model
Build Trees
Algorithm based vs Criterion based
Distance based vs Character-based
9/20/2018
Chuck Staben

6. Choice of Input Data Informative Data Type Molecule of interest
Aligned sequences, RFLP, morphological data…
Molecule of interest
rRNA (general purpose)
interesting character
Number/type of taxa
ingroup and outgroup
Informative
9/20/2018
Chuck Staben

7. rRNA Genes Duplication? Conserved across kingdoms
Varies within species
Widely sequenced, easy
Long, lots of characters
Duplication?
9/20/2018
Chuck Staben

8. Multiple Alignment Method
Computer dependence
Phylogenetic Assumptions
Alignment parameters
(substitution matrix, gap cost)
Aligned features
primary sequence, structure
Optimization
statistical, non-statistical
9/20/2018
Chuck Staben

9. Typical Alignment Method
CLUSTAL, then manual editing
Manual editing for phylogeny
phylogenetic assumption in guide tree
parameters a priori and dynamic
primary structure (with some “influence”
optimization non-statistical
9/20/2018
Chuck Staben

10. Estimate from "quick" tree building,
Substitution Models
G to A, C to T versus N to N
amino acid substitution
forwards and backwards identical?
site-to-site variation
Simpler model better
Estimate from "quick" tree building,
Observed Variation
9/20/2018
Chuck Staben

11. Tree-Building Methods
Distance
UPGMA, NJ, FM, ME
Character
Maximum Parsimony (PAUP)
Maximum Likelihood (PHYLIP)
Acrimonious Debates
9/20/2018
Chuck Staben

12. Distance Methods Most Often Wrong! CLUSTAL
Measure distance (dissimilarity)
Accurate if distances are all summative (ultrametric)
NEVER true over large distance
Methods
UPGMA (Unweighted pair group method with Arithmetic Mean)
NJ (Neighbor joining)
FM (Fitch-Margoliash)
ME (Minimal Evolution)
Most Often Wrong!
CLUSTAL
9/20/2018
Chuck Staben

13. Which Distance Method? UPGMA NJ ME and FM seem best
Least accurate, most used NJ
EXTREMELY RAPID
GIVES ONLY 1 TREE
ME and FM seem best
Minimize tree path lengths
9/20/2018
Chuck Staben

14. Character Methods Maximum Parsimony Maximum Likelihood
minimal changes to produce data
can use different substitution models
Maximum Likelihood
turns problem “inside out”
coin flip analogy
increasingly popular
9/20/2018
Chuck Staben

15. Searching for Trees
9/20/2018
Chuck Staben

16. Tree Search Algorithms
Exhaustive
VERY INTENSIVE
Branch and Bound
Compromise
Heuristic
FAST (usually start with NJ)
9/20/2018
Chuck Staben

17. Evaluating Trees Consenus Tree Randomized Trees
Skewness tests
Randomized Character Data
Permutation tests
Bootstrap, Jackknife
resampling techniques
>70% probably correct; 50% overestimates accuracy
9/20/2018
Chuck Staben

18. Rooting Trees Molecular Clock Extrinsic Evidence Paralog rooting
Root=midpoint, longest span
Almost ALWAYS WRONG
Extrinsic Evidence
select fungus as root for plants, eg
long branch attraction can be problem
Paralog rooting
long branch problems
9/20/2018
Chuck Staben

19. Tree Congruence Tree-to-Tree Comparison
2 different characters/same groups
Important for evaluating biological hypotheses
lentiviruses diverged within their current hosts only
plant pathogenicity has arisen many times in fungi
9/20/2018
Chuck Staben

20. Common Software PAUP PHYLIP GCG PAUPSTAR (MACs best!) UNIX (Seqanal)
Pileup, Lineup, Paupsearch, Paupdisplay
PAUPSTAR (MACs best!)
PHYLIP
UNIX (Seqanal)
9/20/2018
Chuck Staben

21. Phylogenetic Stories HIV Coevolution, host and pathogen Big Tree
complete genome accessible
evolution rapid
selection, neutralism?
human interest (dentist and his patients, eg.)
Coevolution, host and pathogen
Big Tree
9/20/2018
Chuck Staben

22. Phylogenetic Resources
NCBI Taxonomy Browser
RDP database
“Tree of Life”
9/20/2018
Chuck Staben

23. Practicalities Quality of input data critical
Examine data from all possible angles
distance, parsimony, likelihood
Outgroup taxon critical
problem if outgroup shares a selective property with a subset of ingroup
Order of input can be problematic
Jumble them!
9/20/2018
Chuck Staben

24. plagiarized by Chuck Staben, 1998
Trees
plagiarized by Chuck Staben, 1998
Seargent Joyce Kilmer, 1914
9/20/2018
Chuck Staben