Intensive Course on Population Genetics. Ville Mustonen

Size: px
Start display at page:

Download "Intensive Course on Population Genetics. Ville Mustonen"

Transcription

1 Intensive Course on Population Genetics Ville Mustonen

2 Population genetics: The study of the distribution of inherited variation among a group of organisms of the same species [Oxford Dictionary of Biology]

3 Cross- and intra-species comparisons at the molecular level m ingroup samples outgroup AACTGTCCACGTTCTTCCGATGCAGCCTGA AACTGTCCACGTTCTTCCGATGCAGCCTGA AACTGTCCACGTTCTTCCGATGCAGCCTGA AACTGTCCACGTTCTTCCGATGCAGCCTGA AACTGTCCACGTTCTTCCGATGCAGCCTGA AACTGTCCAGGTTCTTCCGATGCAGCCTGA AACTGTCCAGGTTCTTCCGATGCAGCCTGA AACTGTCCAGGTTCTTCCGATGCAGCCTGA AACTGTCCAGGTTCTTCCGACGCAGCCTGA frequency counts polymorphic locus substitution event

4 Let s study fundamental evolutionary forces: 1. genetic drift (noise in reproduction) 2. selection (differential reproductive success of individuals) 3. mutation (process providing variation) 4....

5 Genetic drift: noise in reproduction time in generations individuals

6

7 Wright - Fisher process p b = N b /N = x p a = N a /N =1 x P (m, N, t + 1) = ( ) N x m m t (1 x t ) N m m = Nx t m 2 m 2 = Nx t (1 x t ) x t+1 = x t x 2 t+1 x t+1 2 = x t(1 x t ) N

8 Wright - Fisher process x t τ d N N= N=100 t 0.8 x t t

9 Selection: differential reproductive success of individuals N a = F a N a N b = F b N b t ẋ = d dt N b (t) N a (t)+n b (t) N b N b = N a + N b N a + N b = (F b F a )x(1 x) N b + N a N a + N b

10 Selection ẋ = F ba x(1 x) x(t) = x 0 exp(f ba t) 1+x 0 (exp(f ba t) 1) x t τ s 1/F ba t

11 Mutation: source of variation time in generations individuals

12 Mutation: source of variation N a = µn b µn a N b = µn a µn b µ µ ẋ = d dt N b (t) N a (t)+n b (t) N b = N a + N b = µ(1 2x) N b N a + N b N b + N a N a + N b

13 Mutation ẋ = µ(1 2x) x(t) = 1 2 (1 + exp( 2µt)(2x 0 1)) 1.0 τ 0.8 m 1/µ x 0.6 t t

14 Drift, Selection and Mutation 1.0 τ d N N= x t t

15 Drift, Selection and Mutation x t τs 1/Fba t

16 Drift, Selection and Mutation x t 0.6 τ m 1/µ t

17 Drift, Selection and Mutation Langevin equation: ẋ(t) =F ba x(t)[1 x(t)] + µ[1 2x(t)] + χ x (t) χ x (t) =0 χ x (t)χ x (t ) =(x(1 x)/n ) δ(t t )

18 One locus two alleles model Wright-Fisher process with mutation and selection Ratio of time scales: N 1/µ = µn 1 lighter shading indicates the fitter state population fraction of allele b µt

19 Diffusion equation p(x, t) probability density of populations g(x, ɛ, dt) probability of change x x + ɛ, dt p(x, t + dt) = p(x ɛ, t)g(x ɛ, ɛ, dt)dɛ = = p(x, t) p(x, t)g(x, ɛ, dt) ɛ x pg + ɛ2 2 g(x, ɛ, dt)dɛ x p 2 pg +... dɛ x2 ɛgdɛ x 2 p ɛ 2 gdɛ [SH Rice, Evolutionary Theory (2004)]

20 = p(x, t) g(x, ɛ, dt)dɛ x p ɛgdɛ x 2 p ɛ 2 gdɛ = p(x, t) p(x, t)m(x) x dt p(x, t)v (x) x 2 dt g(x, ɛ, dt)dɛ = 1 ɛg(x, ɛ, dt)dɛ = ɛ rate of directional change of allele frequency at point x = M(x)dt ɛ 2 g(x, ɛ, dt)dɛ = ɛ 2 + var(ɛ) = V (x)dt variance of allele frequency change due to nondirectional effects

21 p(x, t + dt) p(x, t) dt = p(x, t)m(x) x p(x, t)v (x) x 2 p(x, t) t = p(x, t)m(x) x p(x, t)v (x) x 2 Now we just need to plug in our earlier results to get Kimura s diffusion equation for one locus two alleles case: p(x, t) t = x(1 x) x 2 p(x, t) N x [F bax(1 x)+µ(1 2x)]p(x, t)

22 One locus two alleles model: looking at the averages 1 Equilibrium distributions G t (x x0) x

23 One locus two alleles model: looking at the averages 1 after infinite time 0.1 Q(x) x

24 Substitution rate from Kimura s diffusion equation u/µ 4 u(2nf ba )= µ2nf ba 1 exp( 2NF ba ) NF ba

25 Substitution dynamics N 1/µ = µn 1 p a = u ba p b u ab p a p b = u ab p a u ba p b

26 Substitution dynamics p a = p b = u ba u ba + u ab u ab u ba + u ab p a = p b exp( 2NF ba ) N deleterious = N beneficial exp(2nf ba )

27 Conclusions Fundamental evolutionary forces: 1. genetic drift, diffusive force (!), effect strongest in small populations, changes allele frequencies at time-scale 2N 2. selection, directed force, increases the fitter phenotypes, timescale 1/F 3. mutation, directed force, restarts the process from monomorphic states, time-scale 1/µ More complex scenarios, recombination, linkage, diploid genomes, demographics, frequency/time-dependent selection... Further reading, Gillespie: Population Genetics, Hartl and Clark: Principles of Population Genetics

Fitness landscapes and seascapes

Fitness landscapes and seascapes Fitness landscapes and seascapes Michael Lässig Institute for Theoretical Physics University of Cologne Thanks Ville Mustonen: Cross-species analysis of bacterial promoters, Nonequilibrium evolution of

More information

Gene Genealogies Coalescence Theory. Annabelle Haudry Glasgow, July 2009

Gene Genealogies Coalescence Theory. Annabelle Haudry Glasgow, July 2009 Gene Genealogies Coalescence Theory Annabelle Haudry Glasgow, July 2009 What could tell a gene genealogy? How much diversity in the population? Has the demographic size of the population changed? How?

More information

Population Genetics and Evolution III

Population Genetics and Evolution III Population Genetics and Evolution III The Mechanisms of Evolution: Drift São Paulo / January 2019 SMRI (Italy) luca@peliti.org 1 Drift 2 The Population Genetics Triad Sewall Wright Ronald A. Fisher Motoo

More information

The Evolution of Gene Dominance through the. Baldwin Effect

The Evolution of Gene Dominance through the. Baldwin Effect The Evolution of Gene Dominance through the Baldwin Effect Larry Bull Computer Science Research Centre Department of Computer Science & Creative Technologies University of the West of England, Bristol

More information

Population Genetics: a tutorial

Population Genetics: a tutorial : a tutorial Institute for Science and Technology Austria ThRaSh 2014 provides the basic mathematical foundation of evolutionary theory allows a better understanding of experiments allows the development

More information

Linking levels of selection with genetic modifiers

Linking levels of selection with genetic modifiers Linking levels of selection with genetic modifiers Sally Otto Department of Zoology & Biodiversity Research Centre University of British Columbia @sarperotto @sse_evolution @sse.evolution Sally Otto Department

More information

From Biophysics to Evolutionary Genetics: Statistical Aspects of Gene Regulation

From Biophysics to Evolutionary Genetics: Statistical Aspects of Gene Regulation To appear in BMC Bioinformatics (2007) From Biophysics to Evolutionary Genetics: Statistical Aspects of Gene Regulation Michael Lässig Institut für Theoretische Physik, Universität zu Köln, Zülpicher Str.

More information

Gene regulation: From biophysics to evolutionary genetics

Gene regulation: From biophysics to evolutionary genetics Gene regulation: From biophysics to evolutionary genetics Michael Lässig Institute for Theoretical Physics University of Cologne Thanks Ville Mustonen Johannes Berg Stana Willmann Curt Callan (Princeton)

More information

An Application of Perturbation Methods in Evolutionary Ecology

An Application of Perturbation Methods in Evolutionary Ecology Dynamics at the Horsetooth Volume 2A, 2010. Focused Issue: Asymptotics and Perturbations An Application of Perturbation Methods in Evolutionary Ecology Department of Mathematics Colorado State University

More information

Neutral Theory of Molecular Evolution

Neutral Theory of Molecular Evolution Neutral Theory of Molecular Evolution Kimura Nature (968) 7:64-66 King and Jukes Science (969) 64:788-798 (Non-Darwinian Evolution) Neutral Theory of Molecular Evolution Describes the source of variation

More information

Darwinian Selection. Chapter 6 Natural Selection Basics 3/25/13. v evolution vs. natural selection? v evolution. v natural selection

Darwinian Selection. Chapter 6 Natural Selection Basics 3/25/13. v evolution vs. natural selection? v evolution. v natural selection Chapter 6 Natural Selection Basics Natural Selection Haploid Diploid, Sexual Results for a Diallelic Locus Fisher s Fundamental Theorem Darwinian Selection v evolution vs. natural selection? v evolution

More information

Classical Selection, Balancing Selection, and Neutral Mutations

Classical Selection, Balancing Selection, and Neutral Mutations Classical Selection, Balancing Selection, and Neutral Mutations Classical Selection Perspective of the Fate of Mutations All mutations are EITHER beneficial or deleterious o Beneficial mutations are selected

More information

Recovery of a recessive allele in a Mendelian diploid model

Recovery of a recessive allele in a Mendelian diploid model Recovery of a recessive allele in a Mendelian diploid model Loren Coquille joint work with A. Bovier and R. Neukirch (University of Bonn) Young Women in Probability and Analysis 2016, Bonn Outline 1 Introduction

More information

The Wright-Fisher Model and Genetic Drift

The Wright-Fisher Model and Genetic Drift The Wright-Fisher Model and Genetic Drift January 22, 2015 1 1 Hardy-Weinberg Equilibrium Our goal is to understand the dynamics of allele and genotype frequencies in an infinite, randomlymating population

More information

Introduction to Natural Selection. Ryan Hernandez Tim O Connor

Introduction to Natural Selection. Ryan Hernandez Tim O Connor Introduction to Natural Selection Ryan Hernandez Tim O Connor 1 Goals Learn about the population genetics of natural selection How to write a simple simulation with natural selection 2 Basic Biology genome

More information

6 Introduction to Population Genetics

6 Introduction to Population Genetics Grundlagen der Bioinformatik, SoSe 14, D. Huson, May 18, 2014 67 6 Introduction to Population Genetics This chapter is based on: J. Hein, M.H. Schierup and C. Wuif, Gene genealogies, variation and evolution,

More information

Derivation of Itô SDE and Relationship to ODE and CTMC Models

Derivation of Itô SDE and Relationship to ODE and CTMC Models Derivation of Itô SDE and Relationship to ODE and CTMC Models Biomathematics II April 23, 2015 Linda J. S. Allen Texas Tech University TTU 1 Euler-Maruyama Method for Numerical Solution of an Itô SDE dx(t)

More information

Evolution in a spatial continuum

Evolution in a spatial continuum Evolution in a spatial continuum Drift, draft and structure Alison Etheridge University of Oxford Joint work with Nick Barton (Edinburgh) and Tom Kurtz (Wisconsin) New York, Sept. 2007 p.1 Kingman s Coalescent

More information

Genetics and Natural Selection

Genetics and Natural Selection Genetics and Natural Selection Darwin did not have an understanding of the mechanisms of inheritance and thus did not understand how natural selection would alter the patterns of inheritance in a population.

More information

Genetic Variation in Finite Populations

Genetic Variation in Finite Populations Genetic Variation in Finite Populations The amount of genetic variation found in a population is influenced by two opposing forces: mutation and genetic drift. 1 Mutation tends to increase variation. 2

More information

Population Genetics I. Bio

Population Genetics I. Bio Population Genetics I. Bio5488-2018 Don Conrad dconrad@genetics.wustl.edu Why study population genetics? Functional Inference Demographic inference: History of mankind is written in our DNA. We can learn

More information

Major questions of evolutionary genetics. Experimental tools of evolutionary genetics. Theoretical population genetics.

Major questions of evolutionary genetics. Experimental tools of evolutionary genetics. Theoretical population genetics. Evolutionary Genetics (for Encyclopedia of Biodiversity) Sergey Gavrilets Departments of Ecology and Evolutionary Biology and Mathematics, University of Tennessee, Knoxville, TN 37996-6 USA Evolutionary

More information

How robust are the predictions of the W-F Model?

How robust are the predictions of the W-F Model? How robust are the predictions of the W-F Model? As simplistic as the Wright-Fisher model may be, it accurately describes the behavior of many other models incorporating additional complexity. Many population

More information

Computational Approaches to Statistical Genetics

Computational Approaches to Statistical Genetics Computational Approaches to Statistical Genetics GWAS I: Concepts and Probability Theory Christoph Lippert Dr. Oliver Stegle Prof. Dr. Karsten Borgwardt Max-Planck-Institutes Tübingen, Germany Tübingen

More information

6 Introduction to Population Genetics

6 Introduction to Population Genetics 70 Grundlagen der Bioinformatik, SoSe 11, D. Huson, May 19, 2011 6 Introduction to Population Genetics This chapter is based on: J. Hein, M.H. Schierup and C. Wuif, Gene genealogies, variation and evolution,

More information

UNIT 8 BIOLOGY: Meiosis and Heredity Page 148

UNIT 8 BIOLOGY: Meiosis and Heredity Page 148 UNIT 8 BIOLOGY: Meiosis and Heredity Page 148 CP: CHAPTER 6, Sections 1-6; CHAPTER 7, Sections 1-4; HN: CHAPTER 11, Section 1-5 Standard B-4: The student will demonstrate an understanding of the molecular

More information

Tutorial on Theoretical Population Genetics

Tutorial on Theoretical Population Genetics Tutorial on Theoretical Population Genetics Joe Felsenstein Department of Genome Sciences and Department of Biology University of Washington, Seattle Tutorial on Theoretical Population Genetics p.1/40

More information

Introduction to population genetics & evolution

Introduction to population genetics & evolution Introduction to population genetics & evolution Course Organization Exam dates: Feb 19 March 1st Has everybody registered? Did you get the email with the exam schedule Summer seminar: Hot topics in Bioinformatics

More information

Problems on Evolutionary dynamics

Problems on Evolutionary dynamics Problems on Evolutionary dynamics Doctoral Programme in Physics José A. Cuesta Lausanne, June 10 13, 2014 Replication 1. Consider the Galton-Watson process defined by the offspring distribution p 0 =

More information

Diffusion Models in Population Genetics

Diffusion Models in Population Genetics Diffusion Models in Population Genetics Laura Kubatko kubatko.2@osu.edu MBI Workshop on Spatially-varying stochastic differential equations, with application to the biological sciences July 10, 2015 Laura

More information

Question: If mating occurs at random in the population, what will the frequencies of A 1 and A 2 be in the next generation?

Question: If mating occurs at random in the population, what will the frequencies of A 1 and A 2 be in the next generation? October 12, 2009 Bioe 109 Fall 2009 Lecture 8 Microevolution 1 - selection The Hardy-Weinberg-Castle Equilibrium - consider a single locus with two alleles A 1 and A 2. - three genotypes are thus possible:

More information

EVOLUTIONARY DYNAMICS AND THE EVOLUTION OF MULTIPLAYER COOPERATION IN A SUBDIVIDED POPULATION

EVOLUTIONARY DYNAMICS AND THE EVOLUTION OF MULTIPLAYER COOPERATION IN A SUBDIVIDED POPULATION Friday, July 27th, 11:00 EVOLUTIONARY DYNAMICS AND THE EVOLUTION OF MULTIPLAYER COOPERATION IN A SUBDIVIDED POPULATION Karan Pattni karanp@liverpool.ac.uk University of Liverpool Joint work with Prof.

More information

Genetical theory of natural selection

Genetical theory of natural selection Reminders Genetical theory of natural selection Chapter 12 Natural selection evolution Natural selection evolution by natural selection Natural selection can have no effect unless phenotypes differ in

More information

Introductory seminar on mathematical population genetics

Introductory seminar on mathematical population genetics Exercises Sheets Introductory seminar on mathematical population genetics WS 20/202 Kristan Schneider, Ada Akerman Ex Assume a single locus with alleles A and A 2 Denote the frequencies of the three (unordered

More information

Some mathematical models from population genetics

Some mathematical models from population genetics Some mathematical models from population genetics 5: Muller s ratchet and the rate of adaptation Alison Etheridge University of Oxford joint work with Peter Pfaffelhuber (Vienna), Anton Wakolbinger (Frankfurt)

More information

Evolutionary Theory. Sinauer Associates, Inc. Publishers Sunderland, Massachusetts U.S.A.

Evolutionary Theory. Sinauer Associates, Inc. Publishers Sunderland, Massachusetts U.S.A. Evolutionary Theory Mathematical and Conceptual Foundations Sean H. Rice Sinauer Associates, Inc. Publishers Sunderland, Massachusetts U.S.A. Contents Preface ix Introduction 1 CHAPTER 1 Selection on One

More information

Stationary Distribution of the Linkage Disequilibrium Coefficient r 2

Stationary Distribution of the Linkage Disequilibrium Coefficient r 2 Stationary Distribution of the Linkage Disequilibrium Coefficient r 2 Wei Zhang, Jing Liu, Rachel Fewster and Jesse Goodman Department of Statistics, The University of Auckland December 1, 2015 Overview

More information

Background Selection in Partially Selfing Populations

Background Selection in Partially Selfing Populations Background Selection in Partially Selfing Populations Denis Roze To cite this version: Denis Roze. Background Selection in Partially Selfing Populations. Genetics, Genetics Society of America, 2016, 202,

More information

Microevolution 2 mutation & migration

Microevolution 2 mutation & migration Microevolution 2 mutation & migration Assumptions of Hardy-Weinberg equilibrium 1. Mating is random 2. Population size is infinite (i.e., no genetic drift) 3. No migration 4. No mutation 5. No selection

More information

Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate.

Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate. OEB 242 Exam Practice Problems Answer Key Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate. First, recall

More information

Formative/Summative Assessments (Tests, Quizzes, reflective writing, Journals, Presentations)

Formative/Summative Assessments (Tests, Quizzes, reflective writing, Journals, Presentations) Biology Curriculum Map 2017-18 2 Weeks- Introduction to Biology: Scientific method, lab safety, organizing and analyzing data, and psuedoscience. This unit establishes the fundamental nature of scientific

More information

1 Errors in mitosis and meiosis can result in chromosomal abnormalities.

1 Errors in mitosis and meiosis can result in chromosomal abnormalities. Slide 1 / 21 1 Errors in mitosis and meiosis can result in chromosomal abnormalities. a. Identify and describe a common chromosomal mutation. Slide 2 / 21 Errors in mitosis and meiosis can result in chromosomal

More information

Evolution of molecular phenotypes under stabilizing selection

Evolution of molecular phenotypes under stabilizing selection Evolution of molecular phenotypes under stabilizing selection Armita Nourmohammad 1,2,, Stephan Schiffels 1,3,, Michael Lässig 1 arxiv:1301.3981v1 [q-bio.pe] 17 Jan 2013 1 Institute für Theoretische Physik,

More information

Case-Control Association Testing. Case-Control Association Testing

Case-Control Association Testing. Case-Control Association Testing Introduction Association mapping is now routinely being used to identify loci that are involved with complex traits. Technological advances have made it feasible to perform case-control association studies

More information

Selection and Population Genetics

Selection and Population Genetics Selection and Population Genetics Evolution by natural selection can occur when three conditions are satisfied: Variation within populations - individuals have different traits (phenotypes). height and

More information

Inbreeding depression due to stabilizing selection on a quantitative character. Emmanuelle Porcher & Russell Lande

Inbreeding depression due to stabilizing selection on a quantitative character. Emmanuelle Porcher & Russell Lande Inbreeding depression due to stabilizing selection on a quantitative character Emmanuelle Porcher & Russell Lande Inbreeding depression Reduction in fitness of inbred vs. outbred individuals Outcrossed

More information

URN MODELS: the Ewens Sampling Lemma

URN MODELS: the Ewens Sampling Lemma Department of Computer Science Brown University, Providence sorin@cs.brown.edu October 3, 2014 1 2 3 4 Mutation Mutation: typical values for parameters Equilibrium Probability of fixation 5 6 Ewens Sampling

More information

QUANTITATIVE MODELS PLAY A CRUCIAL role in evolutionary biology, especially

QUANTITATIVE MODELS PLAY A CRUCIAL role in evolutionary biology, especially C H A P T E R 2 8 Models of Evolution QUANTITATIVE MODELS PLAY A CRUCIAL role in evolutionary biology, especially in population genetics. Mathematical analysis has shown how different evolutionary processes

More information

Mutation-Selection Systems

Mutation-Selection Systems Chapter 12 Mutation-Selection Systems The basic mechanisms of population biology are mutation, selection, recombination and genetic drift. In the previous chapter we concentrated on mutation and genetic

More information

8. Genetic Diversity

8. Genetic Diversity 8. Genetic Diversity Many ways to measure the diversity of a population: For any measure of diversity, we expect an estimate to be: when only one kind of object is present; low when >1 kind of objects

More information

Runaway. demogenetic model for sexual selection. Louise Chevalier. Jacques Labonne

Runaway. demogenetic model for sexual selection. Louise Chevalier. Jacques Labonne Runaway demogenetic model for sexual selection Louise Chevalier Master 2 thesis UPMC, Specialization Oceanography and Marine Environments Jacques Labonne UMR Ecobiop INRA - National Institute for Agronomic

More information

Processes of Evolution

Processes of Evolution 15 Processes of Evolution Forces of Evolution Concept 15.4 Selection Can Be Stabilizing, Directional, or Disruptive Natural selection can act on quantitative traits in three ways: Stabilizing selection

More information

Microevolution Changing Allele Frequencies

Microevolution Changing Allele Frequencies Microevolution Changing Allele Frequencies Evolution Evolution is defined as a change in the inherited characteristics of biological populations over successive generations. Microevolution involves the

More information

Endowed with an Extra Sense : Mathematics and Evolution

Endowed with an Extra Sense : Mathematics and Evolution Endowed with an Extra Sense : Mathematics and Evolution Todd Parsons Laboratoire de Probabilités et Modèles Aléatoires - Université Pierre et Marie Curie Center for Interdisciplinary Research in Biology

More information

2. Map genetic distance between markers

2. Map genetic distance between markers Chapter 5. Linkage Analysis Linkage is an important tool for the mapping of genetic loci and a method for mapping disease loci. With the availability of numerous DNA markers throughout the human genome,

More information

BIOL Evolution. Lecture 9

BIOL Evolution. Lecture 9 BIOL 432 - Evolution Lecture 9 J Krause et al. Nature 000, 1-4 (2010) doi:10.1038/nature08976 Selection http://www.youtube.com/watch?v=a38k mj0amhc&feature=playlist&p=61e033 F110013706&index=0&playnext=1

More information

Dynamics of Coexistence of Asexual and Sexual Reproduction in Adaptive Landscape

Dynamics of Coexistence of Asexual and Sexual Reproduction in Adaptive Landscape Dynamics of Coexistence of Asexual and Sexual Reproduction in Adaptive Landscape Shuyun Jiao,Yanbo Wang, Ping Ao Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine of Ministry

More information

6 Price equation and Selection in quantitative characters

6 Price equation and Selection in quantitative characters 6 Price equation and Selection in quantitative characters There are several levels of population description. At the most fundamental level, e describe all genotypes represented in the population. With

More information

Lecture 14 Chapter 11 Biology 5865 Conservation Biology. Problems of Small Populations Population Viability Analysis

Lecture 14 Chapter 11 Biology 5865 Conservation Biology. Problems of Small Populations Population Viability Analysis Lecture 14 Chapter 11 Biology 5865 Conservation Biology Problems of Small Populations Population Viability Analysis Minimum Viable Population (MVP) Schaffer (1981) MVP- A minimum viable population for

More information

Introduction to Wright-Fisher Simulations. Ryan Hernandez

Introduction to Wright-Fisher Simulations. Ryan Hernandez Introduction to Wright-Fisher Simulations Ryan Hernandez 1 Goals Simulate the standard neutral model, demographic effects, and natural selection Start with single sites, and build in multiple sites 2 Hardy-Weinberg

More information

Modelling populations under fluctuating selection

Modelling populations under fluctuating selection Modelling populations under fluctuating selection Alison Etheridge With Aleksander Klimek (Oxford) and Niloy Biswas (Harvard) The simplest imaginable model of inheritance A population of fixed size, N,

More information

Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin

Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin CHAPTER 1 1.2 The expected homozygosity, given allele

More information

A. Correct! Genetically a female is XX, and has 22 pairs of autosomes.

A. Correct! Genetically a female is XX, and has 22 pairs of autosomes. MCAT Biology - Problem Drill 08: Meiosis and Genetic Variability Question No. 1 of 10 1. A human female has pairs of autosomes and her sex chromosomes are. Question #01 (A) 22, XX. (B) 23, X. (C) 23, XX.

More information

Effective population size and patterns of molecular evolution and variation

Effective population size and patterns of molecular evolution and variation FunDamental concepts in genetics Effective population size and patterns of molecular evolution and variation Brian Charlesworth Abstract The effective size of a population,, determines the rate of change

More information

EXERCISES FOR CHAPTER 3. Exercise 3.2. Why is the random mating theorem so important?

EXERCISES FOR CHAPTER 3. Exercise 3.2. Why is the random mating theorem so important? Statistical Genetics Agronomy 65 W. E. Nyquist March 004 EXERCISES FOR CHAPTER 3 Exercise 3.. a. Define random mating. b. Discuss what random mating as defined in (a) above means in a single infinite population

More information

Wright-Fisher Models, Approximations, and Minimum Increments of Evolution

Wright-Fisher Models, Approximations, and Minimum Increments of Evolution Wright-Fisher Models, Approximations, and Minimum Increments of Evolution William H. Press The University of Texas at Austin January 10, 2011 1 Introduction Wright-Fisher models [1] are idealized models

More information

4. Populationsgenetik

4. Populationsgenetik 4. Populationsgenetik Populations are never uniform, but individuals differ genetically and phenotypically. Population genetics is concerned with the study of the genetic composition of populations and

More information

Quantitative trait evolution with mutations of large effect

Quantitative trait evolution with mutations of large effect Quantitative trait evolution with mutations of large effect May 1, 2014 Quantitative traits Traits that vary continuously in populations - Mass - Height - Bristle number (approx) Adaption - Low oxygen

More information

1.5.1 ESTIMATION OF HAPLOTYPE FREQUENCIES:

1.5.1 ESTIMATION OF HAPLOTYPE FREQUENCIES: .5. ESTIMATION OF HAPLOTYPE FREQUENCIES: Chapter - 8 For SNPs, alleles A j,b j at locus j there are 4 haplotypes: A A, A B, B A and B B frequencies q,q,q 3,q 4. Assume HWE at haplotype level. Only the

More information

STABILIZING SELECTION ON HUMAN BIRTH WEIGHT

STABILIZING SELECTION ON HUMAN BIRTH WEIGHT STABILIZING SELECTION ON HUMAN BIRTH WEIGHT See Box 8.2 Mapping the Fitness Landscape in Z&E FROM: Cavalli-Sforza & Bodmer 1971 STABILIZING SELECTION ON THE GALL FLY, Eurosta solidaginis GALL DIAMETER

More information

Lecture 22: Signatures of Selection and Introduction to Linkage Disequilibrium. November 12, 2012

Lecture 22: Signatures of Selection and Introduction to Linkage Disequilibrium. November 12, 2012 Lecture 22: Signatures of Selection and Introduction to Linkage Disequilibrium November 12, 2012 Last Time Sequence data and quantification of variation Infinite sites model Nucleotide diversity (π) Sequence-based

More information

NEUTRAL EVOLUTION IN ONE- AND TWO-LOCUS SYSTEMS

NEUTRAL EVOLUTION IN ONE- AND TWO-LOCUS SYSTEMS æ 2 NEUTRAL EVOLUTION IN ONE- AND TWO-LOCUS SYSTEMS 19 May 2014 Variations neither useful nor injurious would not be affected by natural selection, and would be left either a fluctuating element, as perhaps

More information

The effect of linkage on establishment and. survival of locally beneficial mutations

The effect of linkage on establishment and. survival of locally beneficial mutations Genetics: Early Online, published on March 13, 2014 as 10.1534/genetics.114.163477 The effect of linkage on establishment and survival of locally beneficial mutations Simon Aeschbacher,,1, Reinhard Bürger

More information

Febuary 1 st, 2010 Bioe 109 Winter 2010 Lecture 11 Molecular evolution. Classical vs. balanced views of genome structure

Febuary 1 st, 2010 Bioe 109 Winter 2010 Lecture 11 Molecular evolution. Classical vs. balanced views of genome structure Febuary 1 st, 2010 Bioe 109 Winter 2010 Lecture 11 Molecular evolution Classical vs. balanced views of genome structure - the proposal of the neutral theory by Kimura in 1968 led to the so-called neutralist-selectionist

More information

Lecture 24: Multivariate Response: Changes in G. Bruce Walsh lecture notes Synbreed course version 10 July 2013

Lecture 24: Multivariate Response: Changes in G. Bruce Walsh lecture notes Synbreed course version 10 July 2013 Lecture 24: Multivariate Response: Changes in G Bruce Walsh lecture notes Synbreed course version 10 July 2013 1 Overview Changes in G from disequilibrium (generalized Bulmer Equation) Fragility of covariances

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research education use, including for instruction at the authors institution

More information

Functional divergence 1: FFTNS and Shifting balance theory

Functional divergence 1: FFTNS and Shifting balance theory Functional divergence 1: FFTNS and Shifting balance theory There is no conflict between neutralists and selectionists on the role of natural selection: Natural selection is the only explanation for adaptation

More information

Quantitative-Genetic Models and Changing Environments

Quantitative-Genetic Models and Changing Environments Bürger R & Krall C (2004). Quantitative-Genetic Models and Changing Environments. In: Evolutionary Conservation Biology, eds. Ferrière R, Dieckmann U & Couvet D, pp. 171 187. Cambridge University Press.

More information

122 9 NEUTRALITY TESTS

122 9 NEUTRALITY TESTS 122 9 NEUTRALITY TESTS 9 Neutrality Tests Up to now, we calculated different things from various models and compared our findings with data. But to be able to state, with some quantifiable certainty, that

More information

Mutation, Selection, Gene Flow, Genetic Drift, and Nonrandom Mating Results in Evolution

Mutation, Selection, Gene Flow, Genetic Drift, and Nonrandom Mating Results in Evolution Mutation, Selection, Gene Flow, Genetic Drift, and Nonrandom Mating Results in Evolution 15.2 Intro In biology, evolution refers specifically to changes in the genetic makeup of populations over time.

More information

Critical Mutation Rate Has an Exponential Dependence on Population Size

Critical Mutation Rate Has an Exponential Dependence on Population Size Critical Mutation Rate Has an Exponential Dependence on Population Size Alastair Channon 1, Elizabeth Aston 1, Charles Day 1, Roman V. Belavkin 2 and Christopher G. Knight 3 1 Research Institute for the

More information

Theoretical Population Biology

Theoretical Population Biology Theoretical Population Biology 87 (013) 6 74 Contents lists available at SciVerse ScienceDirect Theoretical Population Biology journal homepage: www.elsevier.com/locate/tpb Genotype imputation in a coalescent

More information

Are there species smaller than 1mm?

Are there species smaller than 1mm? Are there species smaller than 1mm? Alan McKane Theoretical Physics Division, University of Manchester Warwick, September 9, 2013 Alan McKane (Manchester) Are there species smaller than 1mm? Warwick, September

More information

p(d g A,g B )p(g B ), g B

p(d g A,g B )p(g B ), g B Supplementary Note Marginal effects for two-locus models Here we derive the marginal effect size of the three models given in Figure 1 of the main text. For each model we assume the two loci (A and B)

More information

A Simple Haploid-Diploid Evolutionary Algorithm

A Simple Haploid-Diploid Evolutionary Algorithm A Simple Haploid-Diploid Evolutionary Algorithm Larry Bull Computer Science Research Centre University of the West of England, Bristol, UK larry.bull@uwe.ac.uk Abstract It has recently been suggested that

More information

Stochastic Demography, Coalescents, and Effective Population Size

Stochastic Demography, Coalescents, and Effective Population Size Demography Stochastic Demography, Coalescents, and Effective Population Size Steve Krone University of Idaho Department of Mathematics & IBEST Demographic effects bottlenecks, expansion, fluctuating population

More information

Darwinian Selection. Chapter 7 Selection I 12/5/14. v evolution vs. natural selection? v evolution. v natural selection

Darwinian Selection. Chapter 7 Selection I 12/5/14. v evolution vs. natural selection? v evolution. v natural selection Chapter 7 Selection I Selection in Haploids Selection in Diploids Mutation-Selection Balance Darwinian Selection v evolution vs. natural selection? v evolution ² descent with modification ² change in allele

More information

Lecture 18 : Ewens sampling formula

Lecture 18 : Ewens sampling formula Lecture 8 : Ewens sampling formula MATH85K - Spring 00 Lecturer: Sebastien Roch References: [Dur08, Chapter.3]. Previous class In the previous lecture, we introduced Kingman s coalescent as a limit of

More information

Competing selective sweeps

Competing selective sweeps Competing selective sweeps Sebastian Bossert Dissertation zur Erlangung des Doktorgrades der Fakultät für Mathematik und Physik der Albert-Ludwigs-Universität Freiburg im Breisgau Pr r t r rö r r t Pr

More information

1.3 Forward Kolmogorov equation

1.3 Forward Kolmogorov equation 1.3 Forward Kolmogorov equation Let us again start with the Master equation, for a system where the states can be ordered along a line, such as the previous examples with population size n = 0, 1, 2,.

More information

The inevitability of unconditionally deleterious substitutions during adaptation arxiv: v2 [q-bio.pe] 17 Nov 2013

The inevitability of unconditionally deleterious substitutions during adaptation arxiv: v2 [q-bio.pe] 17 Nov 2013 The inevitability of unconditionally deleterious substitutions during adaptation arxiv:1309.1152v2 [q-bio.pe] 17 Nov 2013 David M. McCandlish 1, Charles L. Epstein 2, and Joshua B. Plotkin 1 1 Department

More information

Soft selective sweeps in complex demographic scenarios

Soft selective sweeps in complex demographic scenarios Genetics: Early Online, published on July 24, 2014 as 10.1534/genetics.114.165571 Soft selective sweeps in complex demographic scenarios Benjamin A. Wilson, Dmitri A. Petrov, Philipp W. Messer Department

More information

arxiv: v1 [q-bio.pe] 20 Sep 2018

arxiv: v1 [q-bio.pe] 20 Sep 2018 SAIONARY FREQUENCIES AND MIXING IMES FOR NEURAL DRIF PROCESSES WIH SPAIAL SRUCURE ALEX MCAVOY 1, BEN ADLAM 1,2, BENJAMIN ALLEN 1,3, MARIN A. NOWAK 1,4,5 arxiv:1809.07788v1 q-bio.pe 20 Sep 2018 1 Program

More information

The Genetics of Natural Selection

The Genetics of Natural Selection The Genetics of Natural Selection Introduction So far in this course, we ve focused on describing the pattern of variation within and among populations. We ve talked about inbreeding, which causes genotype

More information

Understanding relationship between homologous sequences

Understanding relationship between homologous sequences Molecular Evolution Molecular Evolution How and when were genes and proteins created? How old is a gene? How can we calculate the age of a gene? How did the gene evolve to the present form? What selective

More information

Outline of lectures 3-6

Outline of lectures 3-6 GENOME 453 J. Felsenstein Evolutionary Genetics Autumn, 007 Population genetics Outline of lectures 3-6 1. We want to know what theory says about the reproduction of genotypes in a population. This results

More information

Michael Whitlock. #?:Joh. ~esearch Interests. Page 1 of; ubc. ca

Michael Whitlock. #?:Joh. ~esearch Interests. Page 1 of; ubc. ca v1ichael Whitlock Michael Whitlock Page 1 of; #?:Joh thitlock@zoology. ubc. ca \.ssociate Professor )ep-~lrtment of Zoology Jniversity of British Columbia 3.S., Baylor; Ph.D., Vanderbilt ~uce Scholar,

More information

Mathematical modelling of Population Genetics: Daniel Bichener

Mathematical modelling of Population Genetics: Daniel Bichener Mathematical modelling of Population Genetics: Daniel Bichener Contents 1 Introduction 3 2 Haploid Genetics 4 2.1 Allele Frequencies......................... 4 2.2 Natural Selection in Discrete Time...............

More information

Lecture 1 Hardy-Weinberg equilibrium and key forces affecting gene frequency

Lecture 1 Hardy-Weinberg equilibrium and key forces affecting gene frequency Lecture 1 Hardy-Weinberg equilibrium and key forces affecting gene frequency Bruce Walsh lecture notes Introduction to Quantitative Genetics SISG, Seattle 16 18 July 2018 1 Outline Genetics of complex

More information

The mathematical challenge. Evolution in a spatial continuum. The mathematical challenge. Other recruits... The mathematical challenge

The mathematical challenge. Evolution in a spatial continuum. The mathematical challenge. Other recruits... The mathematical challenge The mathematical challenge What is the relative importance of mutation, selection, random drift and population subdivision for standing genetic variation? Evolution in a spatial continuum Al lison Etheridge

More information