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Methods
BCB 444/544 F07 ISU Terribilini #30- Phylogenetics - Distance-Based Methods 11/02/07 1
BCB 444/
Lecture 30
Phylogenetics – Distance-Based
Methods
#30_Nov
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Wed Oct 30 - Lecture 29 Phylogenetics Basics
- Chp 10 - pp 127 - 141 Thurs Oct 31 - Lab 9 Gene & Regulatory Element Prediction Fri Oct 30 - Lecture 30 Phylogenetic – Distance-Based Methods
- Chp 11 - pp 142 – 169 Mon Nov 5 - Lecture 31 Phylogenetics – Parsimony and ML
- Chp 11 - pp 142 - 169
Required Reading (before lecture)
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Assignments & Announcements
Mon Oct 29 - HW# HW#5 = Hands-on exercises with phylogenetics and tree-building software Due: Mon Nov 5 (not Fri Nov 1 as previously posted)
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BCB 544 "Team" Projects
Last week of classes will be devoted to Projects
- Written reports due:
- Mon Dec 3 (no class that day)
- Oral presentations (20-30') will be:
- Wed-Fri Dec 5,6,
- 1 or 2 teams will present during each class period
¾ SeeGuidelines for Projects posted online
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BCB 544 Only: New Homework Assignment
544 Extra# Due: √PART 1 - ASAP PART 2 - meeting prior to 5 PM Fri Nov 2
Part 1 - Brief outline of Project, email to Drena & Michael after response/approval, then: Part 2 - More detailed outline of project Read a few papers and summarize status of problem Schedule meeting with Drena & Michael to discuss ideas
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Seminars this Week
BCB List of URLs for Seminars related to Bioinformatics: http://www.bcb.iastate.edu/seminars/index.html
- Nov 2 Fri - BCB Faculty Seminar 2:10 in 102 ScI
- Bob Jernigan BBMB, ISU
- Control of Protein Motions by Structure
Methods
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Chp 10 - Phylogenetics
SECTION IV MOLECULAR PHYLOGENETICS
Xiong: Chp 10 Phylogenetics Basics
- Evolution and Phylogenetics
- Terminology
- Gene Phylogeny vs. Species Phylogeny
- Forms of Tree Representation
- Why Finding a True Tree is Dificult
- Procedure of Building a Phylogenetic Tree
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Tree Building Procedure
- Choose molecular markers
- Perform MSA
- Choose a model of evolution
- Determine tree building method
- Assess tree reliability
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Choice of Molecular Markers
- Very closely related organisms - nucleic acid sequence will show more differences
- For individuals within a species - faster mutation rate is in noncoding regions of mtDNA
- More distantly related species - slowly evolving nucleic acid sequences like ribosomal RNA or protein sequences
- Very distantly related species - use highly conserved protein sequences
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Multiple Sequence Alignment
- Most critical step in tree building - cannot build correct tree without correct alignment
- Should build alignments with multiple programs, then inspect and compare to identify the most reasonable one
- Most alignments need manual editing
- Make sure important functional residues align
- Align secondary structure elements
- Use full alignment or just parts
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Automatic Editing of Alignments
- Rascal and NorMD – correct alignment errors, remove potentially unrelated or highly divergent sequences
- Gblocks – detect and eliminate poorly aligned positions and divergent regions
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How do we measure divergence between sequences?
- Simple measure – just count the
number of substitutions observed
between the sequences in the MSA
- Problem – number of substitutions may
not represent the number of
evolutionary events that actually
occurred
Methods
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What about differences in mutation rates between positions within a sequence?
- One of our assumptions was that all positions in a sequence are evolving at the same rate
- Bad assumption
- Third position in a codon changes with higher frequency
- In proteins, some amino acids can change and others cannot
- This variation is called among-site rate heterogeneity
- Many tree building programs have parameters meant to deal with this problem – adds to complexity of getting the correct tree
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Chp 11 – Phylogenetic Tree Construction Methods and Programs
SECTION IV MOLECULAR PHYLOGENETICS
Xiong: Chp 11 Phylogenetic Tree Construction Methods and Programs
- Distance-Based Methods
- Character-Based Methods
- Phylogenetic Tree Evaluation
- Phylogenetic Programs
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Tree Construction
- Two main categories of tree building methods
- Distance-based
- Overall similarity between sequences
- Character-based
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Distance-Based Methods
- Given a MSA and an evolutionary
model, calculate the distance between
all pairs of sequences
- Construct distance matrix
- Construct phylogenetic tree based on
the distance matrix
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Distance Matrices
a 0 b 6 0 c 7 3 0 d 14 10 9 0 a b c d
a b
c
d
0 1 2 3 4 56 7 8
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Distance-Based Methods
- Two ways to construct a tree based on
a distance matrix
Methods
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Clustering-Based Methods
- E.g., UPGMA and Neighbor-Joining
- A cluster is a set of taxa
- Interspecies distances translate into intercluster distances
- Clusters are repeatedly merged
- “Closest” clusters merged first
- Distances are recomputed after merging
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UPGMA
- UPGMA – Unweighted Pair Group Method Using Arithmetic Average
- Uses molecular clock assumption – all taxa evolve at a constant rate and are equally distant from the root ( ultrametric tree )
- This assumption is usually wrong
- So why use UPGMA?
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UPGMA Example
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UPGMA Example
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UPGMA Example
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UPGMA Example
Methods
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Neighbor Joining Example
D 0.60 0.70 0.
C 0.35 0.
B 0.
A B C
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Neighbor Joining Example
- Initialize tree into a star shape with
all taxa connected to the center
- Step 1: Compute r-values and
transformed r-values for all taxa
675 2
35
4 2
'
- 4 0. 35 0. 6 1. 35
= = −
=
= + + = + + =
A A
A AB AC AD r r
r d d d
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Neighbor Joining Example
- Step 2: Compute converted distances
05
35 1. 55 2
1
- 4
2
1 '
= −
= − +
dAB = dAB − rA + rB
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Neighbor Joining Example
D -1 -1 -1.
C -1 -
B -1.
A B C
- Step 3: Fill out converted distance
matrix
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Neighbor Joining Example
- Step 4: Create a node by merging closest taxa
- In this example, the distance between A and B is the same as the distance between C and D
- We can pick either pair to start with
- Let’s pick A and B and create a node called U
U
B
A
C D
A B
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Neighbor Joining Example
- Step 5: Compute branch lengths
- Use the equation for computing the distance from a taxa to a node
[ ( )]
[ ( )]
- 15
2
- 4 0. 675 0. 775
2
' '
=
d r r d
U
B
A
Methods
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Neighbor Joining Example
- Step 6: Construct reduced distance matrix by computing converted distances from each taxa to the new node U
- In UPGMA, we simply calculated the average
[ ( ) ( )]
[( )^ (^ )]
CU =^ AC UA BC UB
d d d d
d
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Neighbor Joining Example
D 0.45 0.
C 0.
U C
Our reduced distance matrix:
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Neighbor Joining Example
- From here, we go back to step 1
- Continue until all taxa have been decomposed from the star tree
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Optimality-Based Methods
- Clustering methods produce a single tree with no ability to judge how good it is compared to alternative tree topologies
- Optimality-based methods compare all possible tree topologies and select a tree that best fits the distance matrix
- Two algorithms:
- Fitch-Margoliash
- Minimum evolution
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Fitch-Margoliash
- Selects best tree among all possible trees based on minimum deviation between distances calculated in the tree and distances in the distance matrix
- Basically, a least squares method
- Dij = distance between i and j in matrix
- dij = distance between i and j in tree
- Objective: Find tree that minimizes
∑ ≤<≤
1 ij n
2
(Dij dij)
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Minimum Evolution
- Similar to Fitch-Margoliash, but uses a different optimality criterion
- Searches for a tree with the minimum total branch length
- This is an indirect way of achieving the best fit of the branch lengths with the original data
