Molecular basis of evolution.

1
Molecular basis of evolution.

• Goal to reconstruct the evolutionary history of
  all organisms in the form of phylogenetic trees.
• Classical approach phylogenetic trees were
  constructed based on the comparative morphology
  and physiology.
• Molecular phylogenetics phylogenetic trees are
  constructed by comparing DNA/protein sequences
  between organisms.

2
Evolution of mankind.

• Analysis of mitochondrial DNA proposes that Homo
  sapiens evolved from one group of Homo erectus in
  Africa (African Eve) 100,000 200,000 years ago.

American indians I, 25-35,000
Europeans 40-50,000
American indians II, 7-9,000
Asians 55-75,000
Africans 100,000
Adam appeared 250,000 years ago, much earlier!
3
Mechanisms of evolution.

• Evolution is caused by mutations of genes.
• Mutations spread through the population via
  genetic drift and/or natural selection.
• If mutant gene produces an advantage (new
  morphological character), this feature will be
  inherited by all descendant species.

4
Mutational changes of DNA sequences.

• 1. Substitution. 3.
  Insertion.
• Thr Tyr Leu Leu Thr
  Tyr Leu Leu
• ACC TAT TTG CTG ACC TAT TTG
  CTG
• ACC TCT TTG CTG ACC TAC TTT
  GCT G
• Thr Tyr Leu Leu Thr
  Tyr Phe Ala
• 2. Deletion. 4.
  Inversion.
• Thr Tyr Leu Leu Thr
  Tyr Leu Leu
• ACC TAT TTG CTG ACC TAT TTG
  CTG
• ACC TAT TGC TG- ACC TTT ATG
  CTG
• Thr Tyr Cys Thr
  Phe Met Leu

5
Gene duplication and recombination.

• New genes/proteins occur through the gene
  duplication and recombination.

Gene 1
Ancestral globin

duplication
Gene 2
globin
globin
hemoglobin
myoglobin
New gene
Duplication
Recombination
6
Codon usage.

• Phe UUU Ser UCU Tyr UAU
• UUC UCC UAC
• Leu UUA UCA Cys UGU
• UUG UCG UGC
• Frequencies of different codons for the same
  amino acid are different. Codon usage bias is
  caused
• Translationary machinery tends to use abundant
  tRNA (and codons corresponding to these tRNA).
  Codon usage bias is the same for all highly
  expressed genes in the same organism.
• Mutation pressure. Difference between mutation
  rates between GC ? AT and AT ? GC. GC-content is
  different in different organisms.

7
Synonymous and nonsynonymous nucleotide
substitutions.

• Synonymous substitutions in codons do not change
  the encoding amino acid, occur in the first and
  third codon positions.
• Nonsynonymous occur in the second position.
• ds/dn lt 1 indicates positive natural selection.
• ds, dn - of (non)synonymous substitutions per
  (non)synonymous site

8
Measures of evolutionary distance between amino
acid sequences.

• Evolutionary distance is usually measures by the
  number of amino acid substitutions.
• P-distance.

nd number of amino acid differences between two
sequences n number of aligned amino acids.
9
Poisson correction for evolutionary distance.

• Takes into account multiple substitutions and
  therefore is proportional to divergence time.
• PC-distance total of substitutions per site
  for two sequences

10
Gamma-distance.

• Substitution rate varies from site to site
  according to gamma-distribution.
• a gamma-parameter, describing the shape of the
  distribution, 0.2-3.5.
• When Plt0.2, there is no need to use
  gamma-distance.

11
Estimation of evolutionary rates in hemoglobin
alpha-chains.
P-distance PC-distance Gamma-distance
Human/cow 0.121 0.129 0.134
Human/kangaroo 0.186 0.205 0.216
Human/carp 0.486 0.665 0.789
To estimate the evolutionary rate of divergence
between human and cow (time of divergence between
these groups is 90 millions years), r 0.129 /
(290106) 0.71710-9 per site per year.
12
Another method to estimate evolutionary
distances amino acid substitution matrices.

• Substitutions occur more often between amino
  acids of similar properties.
• Dayhoff (1978) derived first matrices from
  multiple alignments of close homologs.
• The number of aa substitutions is measured in
  terms of accepted point mutations (PAM) one aa
  substitution per 100 sites.
• Dayhoff-distance can be approximated by
  gamma-distance with a2.25.

13
Fixation of mutations.

• Not all mutations are spread through population.
  Fixation when a mutation is incorporated into a
  genome of species.
• Majority of mutations are neutral (Kimura), do
  not effect the fitness of organism.
• Fixation rate will depend on the size of
  population (N), fitness (s) and mutation rate (µ)

14
Phylogenetic analysis.

• Phylogenetic trees are derived from multiple
  sequence alignments. Each column describes the
  evolution of one site.
• Each position/site in proteins/nucleic acids
  changes in evolution independently from each
  other.
• Insertions/deletions are ususally ignored and
  trees are constructed only from the aligned
  regions.

15
Evolutionary tree constructed from rRNA analysis.
16
The concept of evolutionary trees.

• - Trees show relationships between organisms.
• Trees consist of nodes and branches, topology -
  branching pattern.
• The length of each branch represents the number
  of substitutions occurred between two nodes. If
  rate of evolution is constant, branches will have
  the same length (molecular clock hypothesis).
• Trees can be binary or bifurcating.
• Trees can be rooted and unrooted. The root is
  placed by including a taxon which is known to
  branch off earlier than others.

17
Accuracies of phylogenetic trees.

• Two types of errors
• Topological error
• Branch length error
• Bootstrap test
• Resampling of alignment columns with replacement
  recalculating the tree counting how many times
  this topology occurred bootstrap confidence
  value. If it is gt0.95 reliable
  topology/interior branch.

18
Methods for phylogenetic trees construction.
Set of related sequences
Multiple sequence alignments
Strong sequence similarity?
Maximum parsimony methods
Yes
No
Recognizable sequence similarity?
Yes
Distance methods
No
Analyze reliability of prediction
Maximum likelihood methods
19
Calculating branch lengths from distances.
A B C
A ----- 20 30
B ----- ----- 44
C ----- ----- -----
a
c
b
20
1. Distance methods Neighbor-joining method.

• NJ is based on minimum evolution principle (sum
  of branch length should be minimized).
• Given the distance matrix between all sequences,
  NJ joins sequences in a tree so that to give the
  estimate of branch lengths.
• Starts with the star tree, calculates the sum of
  branch lengths.

C
B
b
c
D
a
d
e
A
E
21
Neighbor-joining method.

• 2. Combine two sequences in a pair, modify the
  tree. Recalculate the sum of branch lengths, S
  for each possible pair, choose the lowest S.

C
B
c
b
d
D
a
e
A
E
3. Treat cluster CDE as one sequence X,
calculate average distances between A and X,
B and X, calculate a and b. 4. Treat AB
as a single sequence, recalculate the distance
matrix. 5. Repeat the cycle and calculate the
next pair of branch lengths.
22
Classwork I

• Given a multiple sequence, construct distance
  matrix (p-distance) and calculate the branch
  lengths.
• APTHASTRLKHHDDHH
• ALTKKSTRIRHIPD-H
• DLTPSSTIIR-YPDLH

23
Classwork II NJ tree using MEGA.

• Go to CDD webpage and retrieve alignment of
  cd00157 in FASTA format.
• Import this alignment into MEGA and convert it to
  MEGA format http//www.megasoftware.net/mega3/mega
  .html .
• http//bioweb.pasteur.fr/seqanal/interfaces/p
  rotdist-simple.html
• 3. Construct NJ tree using different distance
  measures with bootstrap.
• 4. Analyze obtained trees.