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Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid, one locus Outline: triclosan in biosolids fitness haploid life cycle selection coefficients long term predictions

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Page 1: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Models of Selection

Goal: to build models that can predict a population’s response to natural selection

What are the key factors?

Today’s model: haploid, one locus

Outline: triclosan in biosolids fitness haploid life cycle selection coefficients long term predictions

Page 2: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

When does selection act?

Page 3: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Triclosan and

biosolids

Triclosan:

Biosolids:

Triclosan in biosolids??

Page 4: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Fitness: The sum total effect of selection within a generation

Absolute Fitness =

Relative Fitness =

Page 5: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Key questions for model

Page 6: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

One-locus haploid modelFor what organisms is this model appropriate?

Page 7: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Initial frequencies, fitnessf(A) = p(t)

f(a) = q(t)

WA = relative fitness of A

Wa = relative fitness of a

Page 8: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

One-locus haploid model

p[t]q[t]

WA

Wa

f'(A) = __WAp(t)___ WAp(t) + Waq(t) 

 f'(a) = __Waq(t)___ WAp(t) + Waq(t)

 Example:p(t) = 0.5; q(t) = 0.5WA = 1; Wa = 0.8

Page 9: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

One-locus haploid model

p(t)WA

p(t)WA + q(t)Wa

Page 10: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Relative, not absolute, fitness determines changes in allele

frequencies

a

Aa

A

A

A A

Aa

a

a

a

a

Aa

A

A

A A

Aa

a

a

a

a

A

A

A

A A

Aa

a

a

a

a

A

A A

a

6 A, 6 a 6 A, 6 a

Survival of A = 1, of a = 2/3

Survival of A = 1/2, of a = 1/3

f’(A) = 0.6 f’(A) = 0.6

Page 11: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Haploid selection: rest of life cycle

Page 12: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Adults mate at random

Undergo meiosis

One-locus haploid model

Page 13: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

One-locus haploid model

p(t+1) = p(t)WA

p(t)WA + q(t)Wa

p = p(t+1) – p(t) = (WA – Wa)p(t)q(t)

W(t)

W(t) = p(t)WA + q(t)Wa

Page 14: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

One-locus haploid model

p = p(t+1) – p(t) = (WA – Wa)p(t)q(t)

W(t)

What does this tell us about selection?

Page 15: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

A note about variance

Page 16: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

• We can use a simple trick to answer this question. If we divide p[t+1] by q[t+1]:

What will happen over periods of time longer than one generation?

The ratio of p[t] to q[t] changes by W

A/W

a every generation.

p(t+1) p(t)WA

q(t+1) q(t)Wa

=

Page 17: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Predicting allele frequencies

q(t) = 1- p(t), so

p(0)WAt

p(0)WAt + q(0)Wa

t

p(t) =

Now, for any generation t:

p(t) p(0)WAt

q(t) q(0)Wat=

hint: keep right side together, divide by fraction

Page 18: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Using the model I

What would the frequency of allele A be after 100 generations of selection if A is 10% more fit than allele a and if one in

every hundred alleles is initially A?

p(0)WAt

p(0)WAt + q(0)Wa

t

p(t) =

Page 19: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Using the model IIIf A changes in frequency from

0.001 to 0.01 in 10 generations, by how much must it be favored?

p(t) p(0)WAt

q(t) q(0)Wat=

Page 20: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Selection coefficients

Page 21: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Selection coefficient exampleHow long would it take for 95% of the

alleles to be A if A is initially present in 5% of the population and if the selection

coefficient favoring allele A is...s = 0.1?

Page 22: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

The time needed for an allele to go from low frequency to high is the inverse of the selection coefficient s = 0.1 -> tens of generations

Some general principles

Page 23: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Does the mean fitness of a population always increase over

time?Var(W(t)) = p(t)(WA - W(t))2 + q(t)(Wa-W(t))2

 = p(t)q(t)(WA - Wa)2

ΔW = W(t+1) - W(t) = Var(W(t)) 

W(t)

Page 24: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

"The rate of increase in fitness of any organism at any time is equal to its genetic variance in fitness at that

time."R. A. Fisher (1930) The Genetical Theory of

Natural Selection

The Fundamental Theorem of Natural Selection

Page 25: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

Two strains of E. coli (TD9 and TD1)• Had a genetic difference in the lactose pathway• Competed in two environments:

• Glucose-limited (Open symbols)• Lactose-limited (Closed symbols)

• What is the selection coefficient (s)?

Example: Dykhuizen and Dean (1990)

Page 26: Models of Selection Goal: to build models that can predict a population’s response to natural selection What are the key factors? Today’s model: haploid,

References and readings

ReferencesHeidler, J. et al. 2006. Partitioning, Persistence, and Accumulation in Digested Sludge of the Topical Antiseptic Triclocarban during Wastewater Treatment. Environ. Sci. Technol.; 40(11); 3634-3639

ReadingsChapter 6.1 – 6.3 (5.1 – 5.3), question 3.

More questionsWould a dominant or recessive allele change frequency faster in a haploid organism? why?

Calculate the relative fitnesses for these two genotypes:genotype: A a starting count (before selection) 100 100 ending count (after selection) 90 30What is the selection co-efficient?Assume that the mixture starts out with f(A) = 0.5. What will the frequency be after 20 generations?