Evolutionary Genetics
Human Genetics
http://slideshare.net/dangaston
daniel.gaston@dal.ca
March 7th, 2016Dr. Dan Gaston
"Nothing in Biology Makes Sense Except in the
Light of Evolution"
-- Theodosius Dobzhansky
Evolutionary Genetics
Genetics Evolution
Evolutionary Genetics
Population
Genetics
Evolution
Evolutionary Genetics: Darwinian Origins
Voyage of The Beagle: 1831-1836
Origin of Species: November 24th, 1859
Evolutionary Genetics: Mendel and Genetics
• Gregor Mendel's experiments:
1856-1865
• Mendel's rediscovery and early
modern genetics (de Vries,
Bateson, Morgan, Punnet): Early
1900’s
The Forces of Evolution
•Mutation
•Genetic Drift
•Selection
Mutation
Genetic Drift
Selection
• W = 1 – s
• W: Fitness
• s: Selection Coefficient
• s = 1 (Lethal)
• s = 0 (No difference in fitness)
Evolutionary Debates of the early-mid 20th
century
• Primarily differences in view and opinion on relative importance of
different forces:
• "The Mendelians": Geneticists who generally asserted the primacy
of mutation to greater or lesser degrees
• "The Naturalists": Field Biologists who generally asserted the
importance of natural selection
Evolutionary Genetics: Modern Synthesis
• The foundation of Evolutionary Genetics is the foundation of Population Genetics (1918-1939):
• RA Fisher
• JBS Haldane
• Sewall Wright
• The naturalists (1940s):
• Theodosius Dobzhansky
• EB Ford
• Ernst Mayr
• George Simpson
• Julian Huxley
"Natural selection is a mechanism for generating an exceedingly high degree of
improbability." - RA Fisher
Neutral and Nearly Neutral Theory of
Evolution
• Kimura (1968) and King and Jukes (1969) (Neutral Theory)
• Most genetic differences between organisms selectively neutral
• Synonymous mutations
• Molecular level dominated by neutral mutations and genetic drift
• Phenotypic level differences dominated by selection
• Expanded on By Tomoko Ohta and Kimura in 1973 (Nearly Neutral
Theory)
• In addition to neutral, beneficial, and deleterious mutations there are
also nearly neural mutations. Slightly deleterious and slightly
advantageous
Evidence for Near Neutrality
• Prediction: Fixation of Neutral sites will occur at the rate of mutation
(or nearly so for near neutrality)
Evidence for Near Neutrality
• Prediction: Fixation of Neutral sites will occur at the rate of mutation
(or nearly so for near neutrality)
• Evidence:
• Synonymous sites
• Introns
• Intergenic DNA
• Pseudogenes
Nearly Neutral Theory of Evolution
Neutral Evolution becomes the Null Hypothesis in Evolutionary
Biology. It is the default assumption in the absence of
evidence of selection
Mutation
Phylogenetic Trees and Models of Evolution
Phylogenetic Trees
Phylogenetic Trees
Phylogenetic Trees and Evolutionary Genetics:
Molecular Evolution
• Theoretical Framework in the 1960’s: Zuckerkandl, Pauling, Margoliash,
Fitch
• Originally based on comparing proteins based on electrophoresis and later
DNA via DNA-DNA hybridization experiments
• Sanger sequencing (1977) ushers in DNA sequencing
• A variety of techniques and statistical algorithms have been developed
over the decades:
• Maximum Parsimony
• Maximum Likelihood
• Bayesian Inference
• Distance Methods
• Neighbour-Joining
Phylogenetic Trees and Evolutionary Genetics:
Molecular Evolution
• Theoretical Framework in the 1960’s: Zuckerkandl, Pauling, Margoliash,
Fitch
• Originally based on comparing proteins based on electrophoresis and later
DNA via DNA-DNA hybridization experiments
• Sanger sequencing (1977) ushers in DNA sequencing
• A variety of techniques and statistical algorithms have been developed
over the decades:
• Maximum Parsimony
• Maximum Likelihood
• Bayesian Inference
• Distance Methods
• Neighbour-Joining
Maximum Parsimony
Maximum Parsimony
Minimize the amount of change
necessary to describe the
relationship between
organisms/sequences
Maximum Parsimony
A
B
C
D
A
C
B
D
A
D
C
B
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
g
a a
a g g
a a
a
a a
a
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
t
g a
c t t
c a
g
a g
c
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
a
a g
c a a
c g
a
g a
c
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
a
a g
c a a
c g
a
g a
c
Maximum Parsimony: Informative and Non-
Informative Sites
A
D
C
B
A
C
B
D
A
B
C
D
A aat tcg ctt cta gga atc tgc cta atc ctg
B ... ..a ..g ..a .t. ... ... t.. ... ..a
C ... ..a ..c ..c ... ..t ... ... ... t.a
D ... ..a ..a ..g ..g ..t ... t.t ..t t..
1 2 3 4 5 6 7
c
c t
t c c
t t
c
t c
t
Maximum Parsimony: Challenges
• Enumerating the minimum number of changes on a tree gets
inefficient as the number of leaf nodes increases (Easy)
• Fitch Algorithm Solution
• Evaluating all possible trees becomes impossible as the number of
leaf nodes increases (Hard)
• Number of unrooted trees for N leaf nodes:
• π(i=3 ...n) (2i – 5) (10 Nodes = > 2 million trees)
• Number of rooted trees for N leaf nodes:
• π(i=3 ...n) (2i – 3) (10 Nodes = >34 million trees)
Phylogenetic Trees and Evolutionary Genetics
• Performed on Amino Acid or Nucleotide sequences
• Performed on basis of single-genes, multiple genes, or whole
genomes
• Typically rely on:
• Multiple sequence alignment
• Model of evolution
• Amino acid or nucleic acid exchange probabilities
• Rates of substitution
• Site classes
Interesting Deviations
Horizontal Gene Transfer
Horizontal Gene Transfer
Horizontal Gene Transfer
Horizontal Gene Transfer
Horizontal Gene Transfer in Animals
Horizontal Gene Transfer in Animals
Horizontal Gene Transfer and Mammalian
Reproduction
Horizontal Gene Transfer and Mammalian
Reproduction
• Multiple Independent
acquisitions of Syncytin genes
• Syncytin gene acquisition
primarily in lineages with
moderate to highly invasive
placental type
• Cell fusion and
immunosuppresion
Human Evolution
Human Population Movement
Human Population Movement
Human Evolution: Neanderthal and
Denisovan Interbreeding
Human Evolution: Neanderthal and
Denisovan Interbreeding
Human Evolution: Neanderthal and
Denisovan Interbreeding
Recent Human Evolution and Population
Movements
Recent Human Evolution: Agriculture and
Immunology
• Evolution hasn’t stopped in humans, although modern medicine and
society has shifted selection pressures
• SLC22A4: Ergothioneine absorption. Variant with enhanced activity arises
and spreads in Neolithic Europe with the rise of agriculture and shift to
wheat consumption
• Lactase persistence arises in multiple populations around the world
• Lighter skin of Europeans relatively recent. First with arrival of migrants
from Turkey <9,000 years ago, then with a second mutations sometime
more recently
• Height (Particularly linked to Yamnaya introgression in Northern
Europeans)
"Nothing in Biology Makes Sense Except in the
Light of Evolution"
-- Theodosius Dobzhansky

Human genetics evolutionary genetics

  • 1.
  • 2.
    "Nothing in BiologyMakes Sense Except in the Light of Evolution" -- Theodosius Dobzhansky
  • 3.
  • 4.
  • 5.
    Evolutionary Genetics: DarwinianOrigins Voyage of The Beagle: 1831-1836 Origin of Species: November 24th, 1859
  • 6.
    Evolutionary Genetics: Mendeland Genetics • Gregor Mendel's experiments: 1856-1865 • Mendel's rediscovery and early modern genetics (de Vries, Bateson, Morgan, Punnet): Early 1900’s
  • 7.
    The Forces ofEvolution •Mutation •Genetic Drift •Selection
  • 8.
  • 9.
  • 10.
    Selection • W =1 – s • W: Fitness • s: Selection Coefficient • s = 1 (Lethal) • s = 0 (No difference in fitness)
  • 11.
    Evolutionary Debates ofthe early-mid 20th century • Primarily differences in view and opinion on relative importance of different forces: • "The Mendelians": Geneticists who generally asserted the primacy of mutation to greater or lesser degrees • "The Naturalists": Field Biologists who generally asserted the importance of natural selection
  • 12.
    Evolutionary Genetics: ModernSynthesis • The foundation of Evolutionary Genetics is the foundation of Population Genetics (1918-1939): • RA Fisher • JBS Haldane • Sewall Wright • The naturalists (1940s): • Theodosius Dobzhansky • EB Ford • Ernst Mayr • George Simpson • Julian Huxley "Natural selection is a mechanism for generating an exceedingly high degree of improbability." - RA Fisher
  • 13.
    Neutral and NearlyNeutral Theory of Evolution • Kimura (1968) and King and Jukes (1969) (Neutral Theory) • Most genetic differences between organisms selectively neutral • Synonymous mutations • Molecular level dominated by neutral mutations and genetic drift • Phenotypic level differences dominated by selection • Expanded on By Tomoko Ohta and Kimura in 1973 (Nearly Neutral Theory) • In addition to neutral, beneficial, and deleterious mutations there are also nearly neural mutations. Slightly deleterious and slightly advantageous
  • 14.
    Evidence for NearNeutrality • Prediction: Fixation of Neutral sites will occur at the rate of mutation (or nearly so for near neutrality)
  • 15.
    Evidence for NearNeutrality • Prediction: Fixation of Neutral sites will occur at the rate of mutation (or nearly so for near neutrality) • Evidence: • Synonymous sites • Introns • Intergenic DNA • Pseudogenes
  • 16.
  • 17.
    Neutral Evolution becomesthe Null Hypothesis in Evolutionary Biology. It is the default assumption in the absence of evidence of selection
  • 18.
  • 19.
    Phylogenetic Trees andModels of Evolution
  • 20.
  • 21.
  • 22.
    Phylogenetic Trees andEvolutionary Genetics: Molecular Evolution • Theoretical Framework in the 1960’s: Zuckerkandl, Pauling, Margoliash, Fitch • Originally based on comparing proteins based on electrophoresis and later DNA via DNA-DNA hybridization experiments • Sanger sequencing (1977) ushers in DNA sequencing • A variety of techniques and statistical algorithms have been developed over the decades: • Maximum Parsimony • Maximum Likelihood • Bayesian Inference • Distance Methods • Neighbour-Joining
  • 23.
    Phylogenetic Trees andEvolutionary Genetics: Molecular Evolution • Theoretical Framework in the 1960’s: Zuckerkandl, Pauling, Margoliash, Fitch • Originally based on comparing proteins based on electrophoresis and later DNA via DNA-DNA hybridization experiments • Sanger sequencing (1977) ushers in DNA sequencing • A variety of techniques and statistical algorithms have been developed over the decades: • Maximum Parsimony • Maximum Likelihood • Bayesian Inference • Distance Methods • Neighbour-Joining
  • 24.
  • 25.
    Maximum Parsimony Minimize theamount of change necessary to describe the relationship between organisms/sequences
  • 26.
  • 27.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7
  • 28.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7
  • 29.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7 g a a a g g a a a a a a
  • 30.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7 t g a c t t c a g a g c
  • 31.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7 a a g c a a c g a g a c
  • 32.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7 a a g c a a c g a g a c
  • 33.
    Maximum Parsimony: Informativeand Non- Informative Sites A D C B A C B D A B C D A aat tcg ctt cta gga atc tgc cta atc ctg B ... ..a ..g ..a .t. ... ... t.. ... ..a C ... ..a ..c ..c ... ..t ... ... ... t.a D ... ..a ..a ..g ..g ..t ... t.t ..t t.. 1 2 3 4 5 6 7 c c t t c c t t c t c t
  • 34.
    Maximum Parsimony: Challenges •Enumerating the minimum number of changes on a tree gets inefficient as the number of leaf nodes increases (Easy) • Fitch Algorithm Solution • Evaluating all possible trees becomes impossible as the number of leaf nodes increases (Hard) • Number of unrooted trees for N leaf nodes: • π(i=3 ...n) (2i – 5) (10 Nodes = > 2 million trees) • Number of rooted trees for N leaf nodes: • π(i=3 ...n) (2i – 3) (10 Nodes = >34 million trees)
  • 35.
    Phylogenetic Trees andEvolutionary Genetics • Performed on Amino Acid or Nucleotide sequences • Performed on basis of single-genes, multiple genes, or whole genomes • Typically rely on: • Multiple sequence alignment • Model of evolution • Amino acid or nucleic acid exchange probabilities • Rates of substitution • Site classes
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
    Horizontal Gene Transferand Mammalian Reproduction
  • 44.
    Horizontal Gene Transferand Mammalian Reproduction • Multiple Independent acquisitions of Syncytin genes • Syncytin gene acquisition primarily in lineages with moderate to highly invasive placental type • Cell fusion and immunosuppresion
  • 45.
  • 46.
  • 47.
  • 48.
    Human Evolution: Neanderthaland Denisovan Interbreeding
  • 49.
    Human Evolution: Neanderthaland Denisovan Interbreeding
  • 50.
    Human Evolution: Neanderthaland Denisovan Interbreeding
  • 51.
    Recent Human Evolutionand Population Movements
  • 52.
    Recent Human Evolution:Agriculture and Immunology • Evolution hasn’t stopped in humans, although modern medicine and society has shifted selection pressures • SLC22A4: Ergothioneine absorption. Variant with enhanced activity arises and spreads in Neolithic Europe with the rise of agriculture and shift to wheat consumption • Lactase persistence arises in multiple populations around the world • Lighter skin of Europeans relatively recent. First with arrival of migrants from Turkey <9,000 years ago, then with a second mutations sometime more recently • Height (Particularly linked to Yamnaya introgression in Northern Europeans)
  • 53.
    "Nothing in BiologyMakes Sense Except in the Light of Evolution" -- Theodosius Dobzhansky