Phylogenetic Analysis

Gabor T. Marth

Department of Biology, Boston Collegemarth@bc.edu

BI420 – Introduction to Bioinformatics

Figures from Higgs & Attwood

The goals of phylogenetics

To understand the evolutionary relationships among species, e.g.- the order in which they diverged- the time since divergence

The assumptions in phylogenetics

1. Any group of organisms are related to each

other by descent from a common ancestor

2. The relationships between organisms are

described by a bifurcating tree

3. Change in characteristics between organisms

occurs over time

Phylogenetic “objects”

taxonclade

node

branch

Phylogenetic tree

Constructing an evolutionary tree

Step 2. Construction of multiple sequence alignment

Step 1. Selection of appropriate sequences

Step 3. Calculation of pair-wise evolutionary distances

Step 4. Tree construction

Step 5. Tree evaluation

1. Sequence selection

• find sequences with an appropriate amount of divergence: there can be too little or too much divergence (e.g. genes identical across taxa, or non-conserved genomic sequence)• try to select orthologous sequences to make sure that the genes used for tree construction are likely to have preserved functions

2. Multiple alignment

(mitochondrial small subunit RNA gene)

• informative sites• alignment editing• mechanics of multiple alignment construction covered in earlier classes in the course

3. Pair-wise distance

• measures how diverged two sequences are:

ACGCGTTATTACAGTTGACTACACGTTATGACAGTTGACT

2 differences in 20bp D = 2/20 = 0.1 (10% divergence)

Jukes-Cantor (JC) d = -3/4 ln(1-D*4/3) = 0.10732 (evolutionary distance)

• how evolutionarily distant two sequences are:

Pair-wise distances

Pair-wise JC distance matrix

More complex substitution models

• substitutions between less similar residues indicate more divergence than between more similar residues (hydrophobic vs. hydrophilic)

A C G TA - 2 1 2C 2 - 2 1G 1 2 - 2T 2 1 2 -

ACGCGTTATTACAGTTGACTACACGTTATGACAGTTGACT A/G (1) + T/G (2) diff = 3

• amino acid substitution matrices (e.g. PAM, BLOSUM)

4. Tree construction

• goal is to group (cluster) sequences in a hierarchical fashion• each step creates a “node” that represents the common ancestor of all the species/sequences within the group

CA of group containing (A,B)

CA of group containing (A,B,C,D)

CA of group containing (A,B)

UPGMA method for phylogeny construction

UPGMA (unweighted pair-group method with arithmetic mean) is conceptually very simple

Step #1. Cluster two nodes with the shortest distance: e.g. if d(C,D) is lower than d(A,B), d(A,C), etc. then group C and D together. CD is now a new “node”

Step #2. re-calculate distance between new node CD and all other current node, e.g.:d(CD, A) = ½ * (d(C,A) + d(D,A))

Go to Step #1. until every node is clustered into a single group

CD

Example

UPGMA phylogeny from a given distance matrix

First cluster: Chimp + Pygmy chimp

Example (cont’d)

After performing the complete clustering with UPGMA, we get the following rooted tree:

There are many other tree-building methods (see Higgs & Attwood)

Branch lengths

ultra-metricity

additivity

Rooted vs. un-rooted trees

Tree rooted with an outgroup (rodents)

5. Tree evaluation

• Goal: to evaluate the strength of the phylogenetic signal in the data and the robustness of the tree

• Bootstrapping: re-sample the original columns of the alignment with replacement, and produce a random, artificial alignment

Bootstrap support

• Report: for each node, the %-age of times resampled alignments produced the same tree topology (from that node down to the leaves)

strong bootstrap support

weak bootstrap support