Elements of Bioinformatics

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ELEMENTS OF BIOINFORMATICS

10 PHYLOGENETIC ANALYSIS PHYLOGENETIC ANALYSIS

1. Introduction - phylogenetics

2. The structure of a phylogenetic tree

3. Methodology of tree construction

4. Software examples

METHOD OF CONSTRUCTION OF PHYLOGENETIC TREES

CLUSTERING CLADISTIC

• Do not account for • Account for evolutional evolutional relationship relationship

• UPGMA - Unweighted pair Group Method with • Maximum parsimony Arithmetic Mean

• Neighbour joining • Maximum likelihood

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THE CLUSTERING METHOD METHODS OF TREE CONSTRUCTION - UPGMA

STEPS IN UPGMA

1. Calculate a distance matrix between individuals

2. Choose the most similar individuals = nod

3. Calculate a new distance matrix

4. ... Go back to 2

5. 

ATCC ATGC TTCG TCGG

0 1 2 4 ATCC

0 3 3 ATGC

0 2 TTCG

ATCC ATGC TTCG TCGG

0 1 2 4 ATCC

0 3 3 ATGC

0 2 TTCG

2. Choose the most similar individuals = nod

ATCC ATGC TTCG TCGG 0 1 2 4 ATCC

0 3 3 ATGC

0 2 TTCG

0 TCGG 0.5 0.5

ATCC + ATGC TTCG TCGG

ATCC + 0 (2+3)/2=2.5 (4+3)/2=3.5 ATGC

0 2 TTCG

0 TCGG

ATCC + ATGC TTCG TCGG

ATCC + 0 (2+3)/2=2.5 (4+3)/2=3.5 ATGC

0 2 TTCG

0 TCGG

ATCC + ATGC TTCG TCGG ATCC + 0 (2+3)/2=2.5 (4+3)/2=3.5 ATGC

0 2 TTCG

0 TCGG

0.5 0.5 1 1

ATCC TTCG + + ATGC TCGG

ATCC + 0 (2+4+3+3)/4=3 ATGC

ATCC + 0 ATGC

ATCC TTCG + + ATGC TCGG

ATCC + 0 (2+4+3+3)/4=3 ATGC

ATCC + 0 ATGC 1.5 1.5

0.5 0.5 1 1

1. The most basic method

2. Very fast

3. A „molecular clock” assumption  assumes the same evolutionary speed on all lineages

1. Accounts for different speed of evolution across lineages

2. Relatively fast

3. Estimates of edge length

4. Results depend on the assumed model of evolution

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THE CLADISTIC METHOD METHODS OF TREE CONSTRUCTION – Maximum parsimony

STEPS IN MAXIMUM PARSIMONY

1. Sequence alignment

2. Construction of ALL possible trees

3. Selection of a tree with minimal number of mutations required

1. Sequence alignment

1 A A C C G A T 2 A A C C G C A 3 A G T C G T T 4 A G T C G G A

• The same values → sequence non-informative • All different values → sequence non-informative • Repeated values → sequence informative

2. Construction of all possible trees

The total number of possible trees:

• rooted (2n - 3) !! • unrooted (2n - 5) !! n – the number of sequences n !! = 1*3*5*7*...*n

n rooted unrooted

3 3 1 4 15 3 5 105 15 10 34 459 425 2 027 025

2. Construction of all possible trees

ACT GTA

GTA ACA GTA GTT

ACA GTT

3. Selection of a tree with minimal number of mutations required ACT GTA

GTA 3 1 GTA ACA 3 GTT GTA GTT

GTA 2 ACA GTT 1 GTT 1 2 2 GTT 1 ACT

1. Parsimony  Selects a tree with minimal number of mutations

2. Ockham razor  preferring the simplest of many possible solutions

1. Accounts for different probability of mutations  uses substitution models

2. Uses all sequence positions (not only informative)

3. Very slow

4. Accurate esults

5. Provides the probability of tree corectness

UPGMA MAXIMUM PARSIMONY

• Slow  a large number of • Simple, fast possible trees

• Analysis of large data sets - • Analysis of large data sets - possible problematic

• Does not account for • Accounts for evolution evolution through modelling mutations

Probability of tree corectness  bootstrap

GENERATE AN ARTIFICIAL DATA SET

Shuffle the nucleotide sequence

1000

GENERATE A TREE

DETERMINE THE REPEATABILITY OF A GIVEN BRANCH

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PRACTICAL EXAMPLE TREE CONSTRUCTION – example Clustal

1. Select sequences

2. Sequence alignment

3. Tree construction

Branch length

PHYLIP - www.phylip.com/

http://mobyle.pasteur.fr/cgi -bin/portal.py#welcome

TREEFINDER - www.treefinder.de