An Introduction to Population Genetics Theory and Applications

About this book

An Introduction to Population Genetics is intended as a text for a one-semester biology course in population genetics at the undergraduate or graduate levels. The goal of the book is to present both classical population genetics theory developed in terms of allele and haplotype frequencies and modern population genetics theory developed in terms of coalescent theory. An Introduction to Population Genetics assumes little prior knowledge of mathematics. Appendices provide the mathematical background necessary to understand the basic theory presented.

Contents

Preface

Introduction

    Types of Genetic Data
    Detecting Differences in Genotype

1. Allele Frequencies, Genotype Frequencies, and Hardy–Weinberg Equilibrium

    Allele Frequencies
    Genotype Frequencies
        K-Allelic Loci
        Example: The MC1R Gene
    Hardy–Weinberg Equilibrium
        The MC1R Gene Revisited
        Box 1.1. Probability and Independence
        Box 1.2. Derivation of HWE Genotype Frequencies
        Tay–Sachs Disease
    Extensions and Generalizations of HWE
        Deviations from HWE1: Assortative Mating
        Deviations from HWE 2: Inbreeding
        Deviations from HWE3: Population Structure
        Deviations from HWE 4: Selection
        The Inbreeding Coefficient
        Testing for Deviations from HWE
        Box 1.3. The Chi-Square Test

2. Genetic Drift and Mutation

    The Wright–Fisher Model
        Genetic Drift and Expected Allele Frequencies
        Box 2.1. Expectation
        Patterns of Genetic Drift in the Wright–Fisher Model
        Effect of Population Size in the Wright–Fisher Model
    Mutation
        Effects of Mutation on Allele Frequency
        Probability of Fixation
        Species Divergence and the Rate of Substitution
        The Molecular Clock
        Dating the Human–Chimpanzee Divergence Time

3. Coalescence Theory: Relating Theory to Data

    Coalescence in a Sample of Two Chromosomes (n=2)
        Coalescence in Large Populations
        Mutation, Genetic Variability, and Population Size
    Infinite Sites Model
        The Tajima’s Estimator
        The Concept of Effective Population Size
        Interpreting Estimates of ?
    The Infinite Alleles Model and Expected Heterozygosity
    The Coalescence Process in a Sample of n Individuals
        The Coalescence Tree and the tMRCA
        Total Tree Length and the Number of Segregating Sites
    The Site Frequency Spectrum (SFS)
    Tree Shape as a Function of Population Size

4. Population Subdivision

    The Wahlund Effect
        FST: Quantifying Population Subdivision
        The Wright–Fisher Model with Migration
        The Coalescence Process with Migration
        Expected Coalescence Times for n = 2
        FST and Migration Rates
    Divergence Models
        Expected Coalescence Times, Pairwise Difference and FST in Divergence Models
        Isolation by Distance

5. Inferring Population History and Demography

    Inferring Demography Using Summary Statistics
        Coalescence Simulations and Confidence Intervals
        Box 5.1. Simulating Coalescence Trees
        Estimating Evolutionary Trees
        Box 5.2. The UPGMA Method for Estimating Trees
        Gene Trees vs. Species Trees
        Interpreting Estimated Trees from Population Genetic Data
    Likelihood and the Felsenstein Equation
        MCMC and Bayesian Methods
        The Effect of Recombination
        Population Assignment, Clustering, and Admixture

6. Linkage Disequilibrium and Gene Mapping

    Linkage Disequilibrium
        Box 6.1. Coefficients of Linkage Disequilibrium
        Box 6.2. LD Coefficients for Two Diallelic Loci
        Box 6.3. r2 as a Correlation Coefficient
        Evolution of D
        Box 6.4. r2 and ?2
        Box 6.5. Change in D Due to Random Mating
        Box 6.6. Recurrent Mutation Reduces D?
        Two-Locus Wahlund Effect
        Box 6.7. Two-Locus Wahlund Effect
    Genealogical Interpretation of LD
        Recombination
    Association Mapping
        Box 6.8. Example of a Case-Control Test

7. Selection I

    Selection in Haploids
    Selection in Diploids
        Box 7.1. Haploid Selection
        Box 7.2. One Generation of Viability Selection
        Box 7.3. Algebraic Calculation of Allele Frequency Changes
        Box 7.4. Special Cases of Selection
        Box 7.5. Genic Selection
        Box 7.6. Heterozygote Advantage
        Box 7.7. Estimates of Selection Coefficients for the S Allele in a West African Population
        Mutation–Selection Balance
            Allelic Heterogeneity
            Fertility Selection

8. Selection in a Finite Population

    Fixation Probabilities of New Mutations
        Box 8.1. Simulating Trajectories
    Rates of Substitution of Selected Alleles
        Box 8.2. Accounting for Multiple Substitutions
        Box 8.3. Computing Synonymous and Nonsynonymous Rates
    Genetic Hitchhiking
        Selective Sweeps
        Box 8.4. Hitchhiking in a Haploid Population
        Partial Sweeps
        Associative Overdominance
        Box 8.5. Estimating the Age of a Mutation

9. The Neutral Theory and Tests of Neutrality

    The HKA Test
    The MacDonald–Kreitman (MK) Test
    The Site Frequency Spectrum (SFS)
    Tajima's D Test
    Tests Based on Genetic Differentiation among Populations
    Tests Using LD and Haplotype Structure

10. Selection II: Interaction and Conflict

    Selection on Sex Ratio
    Resolving Conflicts
        Box 10.1. The Prisoner's Dilemma
    Kin Selection
    Selfish Genes
        Meiotic Drive
        Transposons
    Species Formation

11. Quantitative Genetics

    Biometrical Analysis
        Box 11.1. Normal Distribution
        Box 11.2. Variance of the Mid-parental Value
    Breeding Value
    Quantitative Trait Loci
    Multiple Quantitative Trait Loci
        Genotype–Environment Interactions
    Mapping Quantitative Trait Loci
        Box 11.3. Mapping Alleles When Starting with Homozygous Populations

Appendix A. Basic Probability Theory
Appendix B. The Exponential Distribution and Coalescence Times
Appendix C. Maximum Likelihood and Bayesian Estimation
Appendix D. Critical Values of the Chi-square Distribution with d Degrees of Freedom
Solutions to Odd-Numbered Exercises
Glossary
Credits
Index

Customer Reviews

Biography

Rasmus Nielsen is a Professor in the Departments of Integrative Biology and Statistics at the University of California at Berkeley. He first came to Berkeley to pursue a Ph.D. in Population Genetics (with advisor, now coauthor, Montgomery Slatkin), having already earned a Masters in Biology from the University of Copenhagen. Dr. Nielsen was awarded both a Fullbright Fellowship and a Sloan Research Fellowship, and received the Ole Rømer Award and the ElitForsk Award. He edited the book Statistical Methods in Molecular Evolution. Dr. Nielsen and lab members work on statistical and computational methods and their applications in population genetics, medical genetics, molecular ecology, and molecular evolution.

Montgomery Slatkin is a Professor in the Department of Integrative Biology at the University of California at Berkeley. He earned a B.S. in Mathematics from MIT, and a Ph.D. in Applied Biomathematics from Harvard University (with George F. Carrier and William H. Bossert). In addition to two prior books published by Sinauer Associates (the edited volumes Coevolution, with Douglas J. Futuyma, and Exploring Evolutionary Biology: Readings from American Scientist), Dr. Slatkin is editor of Evolution: Essays in Honour of John Maynard Smith (with P. J. Greenwood and P. H. Harvey, Cambridge University Press) and Modern Developments in Theoretical Population Genetics (with M. Veuille, Oxford University Press). He was elected a member of the American Academy of Arts and Science (1997), awarded a Guggenheim Fellowship (1999–2000), and received the Sewall Wright Award of the American Society of Naturalists (2000). His research focus is population genetics and genomics, particularly of humans and archaic human relatives.