Evolutionary Biology Concepts

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Evolutionary Biology Concepts

• Molecular Evolution
• Phylogenetic Inference

BIO520 Bioinformatics Jim Lund
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Evolution
Evolution is a process that results in heritable
changes in a population spread over many
generations. "In fact, evolution can be
precisely defined as any change in the frequency
of alleles within a gene pool from one generation
to the next." - Helena Curtis and N. Sue Barnes,
Biology, 5th ed. 1989 Worth Publishers, p.974
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Levels of Evolution

• Changes in allele frequencies within a species.
• Speciation.
• Molecular changes
• Single bp changes.
• Genomic changes (alterations in large DNA
  segments).

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Branching Descent
Evolutionary Tree
Family Tree
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Phylogeny

• Branching diagram showing the ancestral relations
  among species.
• Tree of Life
• History of evolutionary change
• FRAMEWORK for INFERENCE

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The framework for phylogenetics

• How do we describe phylogenies?
• How do we infer phylogenies?

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Inheritance
DNA
?RNA ?Protein ?Function
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Common Phylogenetic Tree Terminology
Terminal Nodes
Branches or Lineages
A
Represent the TAXA (genes, populations, species,
etc.) used to infer the phylogeny
B
C
D
Ancestral Node or ROOT of the Tree
E
Internal Nodes or Divergence Points (represent
hypothetical ancestors of the taxa)
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Phylogenetic trees diagram the evolutionary
relationships between the taxa
((A,(B,C)),(D,E)) The above phylogeny as
nested parentheses
These say that B and C are more closely related
to each other than either is to A, and that A, B,
and C form a clade that is a sister group to the
clade composed of D and E. If the tree has a
time scale, then D and E are the most closely
related.
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Two types of trees
Cladogram Phylogram
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Taxon B
Taxon B
1
Taxon C
Taxon C
1
Taxon A
Taxon A
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Taxon D
Taxon D
genetic change
no meaning
All show the same evolutionary relationships, or
branching orders, between the taxa.
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Rooted vs Unrooted Trees
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More Trees
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Trees-3
Polyphyletic Group
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Extinction
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Population Genetic Forces
Hardy-Weinberg Paradigm pq1 p2 2pq q2 1

• Natural Selection (fitness)
• Drift (homozygosity by chance)
• much greater in small populations
• Mutation/Recombination (variation)
• Migration
• homogenizes gene pools

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Modes of speciation

• Geographic isolation.
• Reproductive isolation.
• Sexual selection.
• Behavioral isolation.

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DNA, protein sequence change
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Multiple Changes/No Change
..CCU AUA GGG.. ..CCC AUA GGG.. ..CCC AUG
GGG.. ..CCC AUG GGC.. ..CCU AUG GGC.. ..CCU AUA
GGC..
5 mutations 1 DNA change 0 amino acid changes
(net)
Enumerating bp/aa changes underestimates
evolutionary change
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Mechanisms of DNA Sequence Change

• Neutral Drift vs Natural Selection

Traditional selection model
Neutral (Kimura/Jukes)
Pan-neutralism
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Mutation rate varies Gene-to-Gene
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Rate varies Site-to-Site
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Rate varies Site-to-Site
From Evolution. Mark Rdley, 3rd Ed.
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Constraints on Silent Changes

• Codon Biases-translation rates
• Transcription elongation rates
• polymerase pause sites
• Silent regulatory elements
• select for or against presence/absence
• Overall genome structure

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Neutralism in Eukaryotes vs Prokaryotes-Slightly
deleterious mutations Models
Most non-coding sites are neutral? Coding/noncodin
g can be flexible?
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DNA, Protein Similarity

• Similarity by common descent
• phylogenetic
• Similarity by convergence (rare)
• functional importance
• Similarity by chance
• random variation not limitless
• particular problem in wide divergence

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Homology-similar by common descent
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Inferring Trees and Ancestors
CCCAGG CCCAAG-gt CCCAAG CCCAAA-gt
CCTAAA CCTAAA-gt CCTAAC
Not always straightforward. The data doesnt
always give a single, correct answer.
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Homology, Orthology, Paralogy
Orthologs
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Paralogy Trap
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Improper Inference
Garbage in, garbage out!
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Our Goals

• Infer Phylogeny
• Optimality criteria
• Algorithm
• Phylogenetic inference
• (interesting ones)

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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
  application as in the conceptual understanding of
  what the software is doing with the data.