PowerPoint to accompany Genetics: From Genes to Genomes Fourth Edition Leland H. Hartwell, Leroy Hood, Michael L. Goldberg, Ann E. Reynolds, and Lee M.

PowerPoint to accompany

Genetics: From Genes to GenomesFourth Edition

Leland H. Hartwell, Leroy Hood, Michael L. Goldberg, Ann E. Reynolds, and Lee M. Silver

Prepared by Mary A. BedellUniversity of Georgia

1Copyright © The McGraw-Hill Companies, Inc. Permission required to reproduce or display

Hartwell et al., 4th edition

Beyond the Individual Gene and GenomeBeyond the Individual Gene and Genome

2

PART PART VIVI

Copyright © The McGraw-Hill Companies, Inc. Permission required to reproduce or display Hartwell et al., 4th edition, Chapter 19

Variation and Selection in Populations

19.1 The Hardy-Weinberg Law: Predicting Genetic Variation in Populations19.2 Causes of Allele Frequency Changes19.3 Analyzing Quantitative Variation

CHAPTER OUTLINECHAPTER OUTLINE

CHAPTERCHAPTERCHAPTERCHAPTER

Three subfields of genetics based on the unit Three subfields of genetics based on the unit object that is the focus of studyobject that is the focus of study

Molecular genetics – the unit entity is the gene

Formal genetics – the unit entity is the individual organism, defined by genotype

Population genetics – the unit entity is a population of interbreeding individuals


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Terms used to describe populationsTerms used to describe populations

Population – group of interbreeding individuals of the same species that inhabit the same space at the same time

Gene pool – sum total of alleles carried by all members of a population

• Changes can occur because of mutation, immigration of new individuals into or out of the population, or decreased fitness

Microevolution – changes in allele frequencies within a population


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Terms used to describe populations (cont)Terms used to describe populations (cont)

Phenotype frequency – proportion of individuals in a population that have a particular phenotype

Genotype frequency – proportion of individuals in a population that carry a particular genotype

Example: A gene with two alleles (A and B) in a population of 20 individuals

12 are AA 4 are AB 4 are BB

Genotype frequencies: AA = 12/20 = 0.6

AB = 4/20 = 0.2

BB = 4/20 = 0.2


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Calculating allele frequenciesCalculating allele frequencies

Allele frequency – proportion of gene copies in a population that are of a given allele type

Example with genotype frequencies: AA = 12/20 = 0.6

AB = 4/20 = 0.2

BB = 4/20 = 0.2

Allele frequencies: in 20 people, there is a total of 40 alleles

12 AA individuals 24 A alleles

4 AB individuals 4 A alleles and 4 B alleles

4 BB individuals 8 B alleles

Frequency of A alleles = (24 + 4)/40 = 0.7

Frequency of B alleles = (8 + 4)/40 = 0.3


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From genotype frequencies to From genotype frequencies to allele frequenciesallele frequencies


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Fig 19.2

The Hardy-Weinberg law correlates allele and The Hardy-Weinberg law correlates allele and genotype frequenciesgenotype frequencies

Developed independently in 1908 by G.H. Hardy and W. Weinberg

Five simplifying assumptions:

• The population has an infinite number of individuals

• Individuals mate at random

• No new mutations appear

• No migration into or out of the population

• Genotypes have no effect on ability to survive and transmit alleles to the next generation


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Predicting genotype frequencies in Predicting genotype frequencies in the next generationthe next generation

Sexually reproducing, diploid organisms

Two steps needed to relate genotype frequencies in one generation to the next generation

• Allele frequencies should be the same in adults as in gametes

• Allele frequencies in gametes can be used to calculate expected genotype frequencies in zygotes of the next generation


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The Hardy-Weinberg law is a binomial equationThe Hardy-Weinberg law is a binomial equation

In a large population of randomly breeding individuals with no new mutations, no migration, and no differences in fitness based on genotype:

p2 + 2pq + q2 = 1


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Fig 19.3

(Equation 19.1)

Predicting the frequency of albinism: Predicting the frequency of albinism: A case studyA case study

In a population of 100,000 people:

100 aa albinos, 1800 Aa carriers, 98,100 AA individuals

Total A alleles = (2 x 98,100) + 1800 = 198,000

Total a alleles = (2 x 100) + 1800 = 2,000

Frequency of A allele = p = 198,000/200,000 = 0.99

Frequency of a allele = q = 2,000/200,000 = 0.01

p2 = (0.99)2 = 0.9801 2pq = 2(0.99)(0.01) = 0.0198

q2 = (0.01)2 = 0.0001

Predicted genotypes in the next generation of 100,000 individuals:

100,000 x 0.9801 = 98,010 AA individuals

100,000 x 0.0198 = 1980 Aa individuals

100,000 x 0.0001 = 10 aa individualsCopyright © The McGraw-Hill Companies, Inc. Permission required to reproduce or display

Hartwell et al., 4th edition, Chapter 1911

The population genetics of blue-eye colorThe population genetics of blue-eye color

Blue-eye color in humans is recessive to brown eyes and arose 6,000 – 10,000 years ago

Trait is very common in Europe but rare outside of Europe


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Fig 19.4a

Geographic differences in proportions of European populations expressing the blue eyes phenotype

A SNP located in an enhancer of the A SNP located in an enhancer of the OCA2OCA2 gene is associated with blue eye colorgene is associated with blue eye color

The SNP rs12913832 is located in an intron of the HERC2 gene


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Fig 19.4c

Fig 19.4b

Haplotype structure of SNP alleles at the OCA2-HERC2 region

Frequencies of the A and G alleles of the SNP Frequencies of the A and G alleles of the SNP rs12913832 in different populationsrs12913832 in different populations

p = rs12913832A

q = rs12913832G


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Fig 19.4d

Use of the Hardy-Weinberg equation with Use of the Hardy-Weinberg equation with mixed populationsmixed populations

Example: Blue-eye phenotype in a population derived from 100 people from northern Finland and 100 people from Yakuts of eastern Siberia

p = frequency of rs12913832A q = frequency of rs12913832G

In Finnish population of 100 people, q = 0.84

q2 = (0.84)2 = 0.71 2pq = 2 (0.16)(0.84) = 0.27

71 estimated to be GG (blue eyes)

27 estimated to be GA (brown-eyed carriers)

In Yakut population of 100 people, q = 0.10

q2 = (0.1)2 = 0.01 2pq = 2 (0.9)(0.1) = 0.18

1 estimated to be GG (blue eyes)

18 estimated to be GA (brown-eyed carriers)Copyright © The McGraw-Hill Companies, Inc. Permission required to reproduce or display


Blue eyes vs. brown eyes in a mixed Blue eyes vs. brown eyes in a mixed population (cont)population (cont)

Total population = 100 Finns + 100 Yakuts = 200

Total GG (blue eyes) = 71 Finns + 1 Yakut = 72

Total GA (carriers) = 27 Finns + 18 Yakuts = 45

Total number of G alleles = (2 x 72) + 45 = 189

Frequency of G alleles = q = 189/400 = 0.47

Expected frequency of offspring with blue eyes (GG) from these 100 Finns and 100 Yakuts:

q2 = (0.47)2 = 0.22

If 200 offspring, then 0.22 x 200 = 44 with blue eyes


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Properties of populations described by Properties of populations described by Hardy-Weinberg equilibriumHardy-Weinberg equilibrium

Conservation of allele proportions

• Even though the genotype frequencies can change in the second generation, there will be no change in allele frequencies

A stratified population formed from two (or more) distinct populations will become balanced in a single generation

• At Hardy-Weinberg equilibrium, genotype frequencies will be p2, 2pq, and q2


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Hardy-Weinberg provides a starting point for Hardy-Weinberg provides a starting point for modeling population deviationsmodeling population deviations

Natural populations rarely meet the simplified assumptions of Hardy-Weinberg

• New mutations at each locus arise occasionally

• No population is infinitely large

• Migrations of small groups of individuals does occur

• Mating is not random

• There are genotype-specific differences in fitness

Hardy-Weinberg equation is useful for estimating population changes through a few generations

• Not as useful for predicting long-term changes, but does provide a foundation for modeling


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Using Monte Carlo simulations to model Using Monte Carlo simulations to model long-term changes in allele frequencieslong-term changes in allele frequencies

Monte Carlo simulations use a computer program to model possible outcomes of randomly chosen matings over a designated number of generations

• Starting population has a defined number of individuals that are homozygous and heterozygous

• Mating pairs are chosen through a random-number generating program

• Genotypes of offspring at each generation are based on probabilities


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Using Monte Carlo simulations to model Using Monte Carlo simulations to model long-term changes in allele frequencies (cont)long-term changes in allele frequencies (cont)

At each generation in the simulation:

• Total offspring number and parental population size are equal

• Parental generation is discarded and offspring serve as parents of next generation

Multiple, independent simulations are performed

Each simulation represents a possible pathway of genetic drift

• Change in allele frequencies as a consequence of random inheritance from one generation to the next


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Modeling genetic drift in populations Modeling genetic drift in populations of different sizesof different sizes

Six Monte Carlo simulations run with two initial populations of heterozygous individuals

• In these simulations, there was no selection


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Fig 19.5

(a) Initial population has 10 individuals (b) Initial population has 500 individuals

Population size and time to fixationPopulation size and time to fixation

Fixation – when only one allele in a population has survived and all individuals are homozygous for that allele

• No further changes can occur (in the absence of migration or mutation)

At each generation, changes in allele frequencies are relatively small

Over many generations, there can be large changes in allele frequency

In populations with 2 alleles present at equal frequencies, median number of generations to fixation is roughly equal to the total number of gene copies in breeding individuals

• e.g. Population of 10, median fixation time is 20 generations


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Founder effects and population bottlenecksFounder effects and population bottlenecks

Founder effects – occur when a few individuals separate from a larger populations and establish a new population

• Founder allele frequencies can be different from original population

Population bottlenecks – large proportion of individuals die (e.g. from environmental disturbances)

• Survivors are equivalent to a founder population


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Natural selection acts on differences in fitness Natural selection acts on differences in fitness to alter allele frequenciesto alter allele frequencies

Fitness – individual's relative ability to survive and transmit its genes to the next generation (a statistical measurement)

• Cannot be measured in individuals in a population

• But, can be measured in all individuals of the same genotype in a population

• Two basic components: viability and reproductive success

Natural selection – the process that progressively eliminates individuals whose fitness is lower

• Individuals whose fitness is higher become the parents of the next generation

• Occurs in all natural populations


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Natural selection often acts through Natural selection often acts through environmental conditionsenvironmental conditions

Natural selection in giraffes on the savannah

• During long droughts, longer necks are needed to reach tree leaves


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Fig 19.6

Giraffes with longer necks had higher fitness than giraffes with short necks

Modifications to Hardy-WeinbergModifications to Hardy-Weinberg

In populations undergoing selection, each genotype has a relative fitness

e.g. Population with two allele (R and r)

Relative fitness (ω) of each genotype (RR, Rr, and rr):

ωRR ωRr ωrr

Relative frequencies of each genotype at adulthood:

p2ωRR 2pqωRr q2ωrr

Individual fitness for each genotype is arbitrary

Average fitness of the population:

= p2ωRR + 2pqωRr + q2ωrr


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ω (Equation 19.4a)


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Fig 19.7

Changes in allele Changes in allele frequencies caused frequencies caused

by selectionby selection

Calculating the changes in allele frequencies Calculating the changes in allele frequencies due to selectiondue to selection

p' and q' represent allele frequencies after one generation of selection


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q 2rr (2pqRr ) / 2

q (qrr pRr )

q'

Δq = q' – q =

s = selection coefficient

Varies from 0 (no selection) to 1 (complete selection)

If s = 0, Δq is always negative

Rate of decrease depends on the allele frequencies

As q approaches 0, rate of decrease gets slower (Fig 19.8)

spq 2

(Equation 19.5)

(Equation 19.7)

Predicted and observed decrease in the Predicted and observed decrease in the frequency of a lethal recessive allele over timefrequency of a lethal recessive allele over time


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Fig 19.8

An example of Monte Carlo modeling An example of Monte Carlo modeling of natural selectionof natural selection

Population with 500 individuals (1 Rr, 499 rr)

ωRR = 1.00 ωRr = 0.98 ωrr = 0.98


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Fig 19.9

Six simulations:

In three simulations, R allele goes extinct in <100 generations

In three simulations, R allele moves to fixation

The fitness of alternative genotypes The fitness of alternative genotypes in different environmentsin different environments

H. sapiens migrated out of Africa 70,000 years ago

Exposure to ultraviolet rays from sun decreases with increasing distance from equator

• Affects vitamin D production and skin cancer incidence

• Close to equator, dark skin protects against skin cancer

• Farther from equator, lighter skin allows more UV for sufficient vitamin D production

Skin pigmentation is a complex quantitative trait and is determined by alleles at many genes

Alleles of several genes show strong associations with different populations around the world (Fig 19.10)


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Geographic distribution of allele frequencies at Geographic distribution of allele frequencies at two skin pigmentation locitwo skin pigmentation loci

Distribution of KITLG alleles


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Fig 19.10a

Distribution of SLC24A5 alleles

Fig 19.10b

Genetic response to cultural innovationsGenetic response to cultural innovations

Lactase gene (LCT) required to digest milk

• In pre-agricultural societies, lactase isn't required after weaning

• LCT expression is turned off after weaning

After cattle domestication (Turkey, ~8,000 years ago), ability to digest milk conferred a survival advantage

~ 5,000 years ago, a DNA alteration in an LCT regulatory sequence occurred

• Allows LCT expression at high level throughout life

• Different modern populations around the world vary in LCT allele frequencies (Fig 19.10d)


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Frequency of the Frequency of the sickle-cell allele sickle-cell allele

across Africa where across Africa where malaria is prevalentmalaria is prevalent

Sickle-cell anemia is a recessive trait caused by mutations in the β-globin locus

Heterozygous advantage – individuals that are carriers of sickle-cell are resistant to malaria

Fig 19.11

Balancing selection maintains deleterious Balancing selection maintains deleterious alleles in a populationalleles in a population

For the β-globin locus, B1 is the normal allele and B2 is a recessive disease allele

Relative fitness for B1B2 = 1

Selection coefficient for B1B1 = 1 – s1

Selection coefficient for B2B2 = 1 – s2

Changes in allele frequency resulting from selection


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Equilibrium frequency of B2 (qe) is reached when:

pq (s1p s2q )

Δq =

(Equation 19.8)

s1

s1 s2qe = (Equation 19.9)

A comprehensive example: Human behavior A comprehensive example: Human behavior can affect evolution of pathogens and pestscan affect evolution of pathogens and pests

Evolution of drug resistance in bacterial pathogens

• e.g. Tuberculosis and evolution of multi-drug resistant strains of TB

Factors contributing to rapid evolution of resistance

• Short generation time and rapid reproduction

• Large population densities

• Strong selection imposed by antibiotics

• Gene transfer between bacteria


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The evolution of The evolution of resistance in TB bacteriaresistance in TB bacteria

Repeated cycles of antibiotic treatment coupled with premature cessation of treatment

• At beginning of treatment, occasional mutations in bacteria can occur that confer resistance

• If antibiotic treatment is prematurely terminated, the drug-resistant bacteria can proliferate


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Fig 19.12

Evolution of pesticide resistanceEvolution of pesticide resistance

Large-scale use of DDT and other synthetic insecticides began in 1940s

• DDT is a nerve toxin in insects

• Dominant mutations in a single gene confer resistance through detoxification of DDT

• With insecticide application, strong selection favors heterozygotes

By 1984, there were >450 species of mites and insects that had become resistant


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Changes in genotype frequencies in Changes in genotype frequencies in mosquitoes in response to DDTmosquitoes in response to DDT

Use of DDT in Bangkok to control A. aegytpi mosquitoes - began in 1964 and discontinued in 1967

R is dominant, resistance allele; S is susceptibility allele


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Fig 19.14b

RR genotype confers a fitness cost:

In the absence of the insecticide, resistance is subject to negative selection

Analyzing quantitative trait variationAnalyzing quantitative trait variation

Factors causing continuous variation of quantitative traits

• Number of genes that determine the trait

• Genetic and environmental factors that affect penetrance and expressivity of the genes

One of the goals of quantitative analysis is to separate the genetics effects from the environmental effects


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Studies of dandelions can help sort out the Studies of dandelions can help sort out the effects of genes versus the environmenteffects of genes versus the environment

Most dandelion seeds arise from mitotic divisions – all seeds from a single plant are genetically identical

Goal is to compare influence of genes and environment on the length of the stem at flowering


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Fig 19.15a

Finding the mean and variance of Finding the mean and variance of stem length in dandelionsstem length in dandelions

Genetically identical plants grown on hillside:

• Variation in stem length should be a consequence of environmental interactions (VE)


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Fig 19.15b

Genetically identical dandelions grown Genetically identical dandelions grown in two environmentsin two environments

VE for growth in greenhouse < VE for growth on hillside

This difference in VE is a measure of the impact of the more diverse environmental conditions on the hillside


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Fig 19.15c

Growth of genetically identical and genetically Growth of genetically identical and genetically diverse dandelions in a greenhousediverse dandelions in a greenhouse

Difference in variance between genetically diverse and identical plants is VG, the genetic variance


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Fig 19.15d


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Fig 19.15e

Growth of genetically identical and genetically Growth of genetically identical and genetically diverse dandelions on a hillsidediverse dandelions on a hillside

Total phenotype variance (VP) = VE + VG

Heritability is the proportion of phenotypic Heritability is the proportion of phenotypic variance due to genetic variancevariance due to genetic variance


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h 2 VG

VG VE

VG

VP (Equation 19.11)

Heritability of a trait is always defined for a specific population in a specific set of environmental conditions

Amounts of genetic, environmental, and phenotypic variation may differ among traits

Heritability is measured in studies of groups with defined genetic differences

Measuring the heritability of bill depth in Measuring the heritability of bill depth in populations of Darwin’s finchespopulations of Darwin’s finches

Geospiza fortis on Daphne Major in the Galápagos Islands


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Correlation between beak size of offspring and the average of the parents' beak sizes (slope of line is 0.82)

Fig 19.16a, b

Results if finch populations had no Results if finch populations had no environmental or no genetic effectsenvironmental or no genetic effects

Approximately 82% of variation in bill depth in Darwin's finches is due to genetic variation among individuals (Fig 19.16b, slope of line is 0.82)

• If the environment had no effect, then heritability would be 1.0

• If there was not genetic contribution, then heritability would be 0


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Fig 19.16c, d

Heritability of polygenic traits in humans Heritability of polygenic traits in humans can be studied using twinscan be studied using twins


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Fig 19.17a

Concordance of a trait in two children Concordance of a trait in two children raised in the same familyraised in the same family

If the heritability is 0.0, no differences would be observed between monozygotic (MZ), dizygotic (DZ), or unrelated by adoption (UR)


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Fig 19.17b

Concordance of a trait in two children Concordance of a trait in two children raised in the same family (cont)raised in the same family (cont)

If the heritability is 1.0, differences would be observed in comparing monozygotic (MZ), dizygotic (DZ), or unrelated by adoption (UR)

The extent of difference varies with the trait frequency


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Fig 19.17b

A trait's heritability determines its A trait's heritability determines its potential for evolutionpotential for evolution

Heritability quantifies the potential for selection

• A trait with high heritability has a large potential for evolution

• Selection differential = S

Difference between value for this trait in the parents and value for this trait in the entire population (breeding and non-breeding)

• Response to selection = R

The amount of change in the mean value of a trait that results from selection

R = h2SCopyright © The McGraw-Hill Companies, Inc. Permission required to reproduce or display


(Equation 19.12)

Bristle number in parents and offspring in a lab Bristle number in parents and offspring in a lab population of population of D. melanogasterD. melanogaster


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Fig 19.18

This trait has a high heritability:

• Parents with high bristle numbers have offspring with high bristle numbers

• Parents with low bristle numbers have offspring with low bristle numbers

Evolution of abdominal bristle number in Evolution of abdominal bristle number in response to artificial selection in response to artificial selection in DrosophilaDrosophila

Artificial selection can be imposed on this trait –

• Flies with high bristle number bred together

• Flies with low bristle number bred together


54

Fig 19.19

PowerPoint to accompany Genetics: From Genes to Genomes Fourth Edition Leland H. Hartwell, Leroy Hood, Michael L. Goldberg, Ann E. Reynolds, and Lee M.

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