Case studies in molecular population genetics

Collections of DNA from nature for many individuals and loci give us the raw material for studying evolution at the molecular level. Chapter 9, “Case studies in molecular population genetics: genotype to phenotype to selection,” dives into several case studies of exciting real-world organisms that demonstrate the application from A to Z of the concepts developed throughout the book. It includes summaries of the natural context for each organism, ranging from armoring in fish (Eda, Pitx1) and color crypsis in mice (Mc1r) to butterfly flight ability (Pgi) and toxin metabolism in Drosophila fruit flies (Cyp6g1, Adh), then walks through the molecular data, their visualization, and their analysis. Complications and caveats to real-world analysis are discussed for how to identify demographic and selective effects in empirical datasets. The approaches include both candidate gene studies and genome scans, and show how different molecular population genetic analyses work in concert with one another. These population genetic analyses also can dovetail with functional molecular genetic experiments and with genetic mapping using crosses or genome-wide association study analysis. Chapter 9 ends by introducing a summary of several advanced topics in molecular population genetics, including concepts and tests for selection on standing variation, the genomic scale of data computation and evolutionary modelling, and connections to human evolution.

Quantifying genetic variation at the molecular level

Chapter 3, “Quantifying genetic variation at the molecular level,” introduces quantitative methods for measuring variation directly in DNA sequences to help decipher fundamental properties of populations and what they can tell us about evolution. It provides an overview of the evolutionary factors that contribute to genetic variation, like mutational input, effective population size, genetic drift, migration rate, and models of migration. This chapter surveys the principal ways to measure and summarize polymorphisms within a single population and across multiple populations of a species, including heterozygosity, nucleotide polymorphism estimators of θ‎, the site frequency spectrum, and F ST, and by providing illustrative natural examples. Populations are where evolution starts, after mutations arise as the spark of population genetic variation, and Chapter 3 describes how to quantify the variation to connect observations to predictions about how much polymorphism there ought to be under different circumstances.

Neutral theories of molecular evolution

Chapter 4, “Neutral theories of molecular evolution,” outlines the logic and predictions of the neutral theory of molecular evolution and its derivatives as a simple conceptual framework for understanding DNA sequence evolution. It introduces the standard neutral model as a null model of evolutionary change in DNA sequences to describe patterns of polymorphism within species and divergence between species. An overview is provided for the molecular clock concept and for predictions about the amount of polymorphism and allele frequency distributions within populations. This chapter covers how population size and selection intersect to define nearly neutral fitness effects and their implications, as well as misinterpretations and misapplications of Neutral Theory. This overview provides a foundation for how theoretical predictions offer null models for tests of molecular evolution developed in later chapters.

Natural selection and demography as causes of molecular non-randomness

Chapter 7, “Natural selection and demography as causes of molecular non-randomness,” outlines the predictable molecular evolutionary patterns that arise when the Neutral Theory has its assumptions violated. It summarizes predictions about genetic variation, the shape of genealogies, and the accumulation of divergence between lineages when natural selection and non-standard demographic scenarios occur in populations. This chapter provides an overview of the general, qualitative impacts on molecular population genetic data by positive selection, purifying selection, and balancing selection, as well as by demographic population growth, contraction, and subdivision. It covers the concepts of selective sweeps, genetic hitchhiking, and background selection, placed in a heuristic context of skews in polymorphism, genealogies, the site frequency spectrum, and distinct metrics of divergence. This chapter also summarizes the consequences of genetic linkage to sex chromosomes and plastid genomes. This overview builds up intuition about selection, demography, and genome organization as important molecular population genetic factors that motivate further analysis with quantitative tests of neutrality.

Genealogy in evolution

Chapter 5, “Genealogy in evolution,” introduces branching tree diagrams as an intuitive way to visualize the evolutionary relationships between alleles, haplotypes, individuals, and species. It describes the nomenclature of gene tree topologies, the stochasticity in tree shape across genes, and the notion of a most recent common ancestor. This chapter also covers reverse-time genealogical thinking with coalescent theory and how it integrates with predictions about nucleotide polymorphism and the site frequency spectrum. An overview of how phylogenies show between-species genealogical relationships is used to highlight the concepts of orthology and homoplasy, how to calculate and interpret different metrics of DNA sequence divergence, the role of ancestral polymorphism in creating distinct gene trees, the multiple mutational hits problem, and factors that influence calculations of the time to the most recent common ancestor for species trees versus gene trees. This chapter surveys how to think of evolution in terms of genealogies that relate gene copies within a species or among species, and how to connect ideas about gene trees to other ideas in molecular population genetics.

Recombination and linkage disequilibrium in evolutionary signatures

Chapter 6, “Recombination and linkage disequilibrium in evolutionary signatures,” explores the role of partial genetic linkage within and between genes in influencing patterns of nucleotide polymorphism and evolutionary change. It introduces the concept of linkage disequilibrium as the non-random association of alleles at different loci, the potential causes of linkage disequilibrium, and different methods to quantify and visualize it. The empirical effects of partial recombination on patterns of linkage disequilibrium in genomes are illustrated with theoretical predictions and natural examples. The phenomena of non-crossover recombination and gene conversion are presented, as is the application of linkage disequilibrium to inferring population demography and the genetic mapping of traits. This chapter lays the foundation for understanding how complete linkage, partial linkage, and no linkage integrate with the other forces in evolutionary theory and with the empirical analysis of molecular population genetic data.

The origins of molecular diversity

At its simplest, evolution is change in the relative abundance of alternative alleles, from one generation to the next. But where do these different alleles come from? As the ultimate origin of all genetic novelty, the input of new mutations into a population forms the critical first step for incorporating biological detail into how we conceive of genome evolution. Chapter 2, “The origins of molecular diversity,” summarizes the many mechanisms of mutation, the distribution of fitness effects, and how to characterize mutational processes themselves in conceptual models. It covers point mutations, indels, microsatellites, transposable elements, and other mutation types in the context of the genetic code and gene duplication, as well as the role of mutation accumulation experiments in understanding mutation rates and fitness effects. The infinite alleles, infinite sites, and stepwise mutation models are summarized, along with the concept of homoplasy and complexities to the mutation process in nature. These important extra pieces of biological realism connect more closely the mechanisms of evolution to show the path toward a deeper analysis of genomes.

Introduction

Chapter 1, “Introduction: What is molecular population genetics?,” presents the motivations, applications, and historical context for molecular population genetics as a subdiscipline within biology. It describes how changes to DNA are inextricably woven into thinking about evolution and how molecular population genetics can be used to transport our thinking backward and forward through time. Key classic theoretical ideas summarizing allele frequency change, probability of fixation, and the time to fixation are encapsulated in brief vignettes. Both fundamental and applied uses of molecular population genetic perspectives are summarized in this survey of the historical, conceptual, and empirical development of the branch of science that we call population genetics and its integration with DNA sequences.

Molecular deviants

Chapter 8, “Molecular deviants: sequence signatures of selection and demography,” dives into the logic and mechanics of some of the most common tests of neutrality to show how and why data can reveal differences from the predictions of the standard neutral model. It introduces approaches based on skewed patterns of polymorphism alone, including Tajima’s D test, and on differentiation or divergence alone, like the Lewontin-Krakauer, Population Branch Statistic (PBS), and K A / K S relative-rates tests. Chapter 8 also covers tests of neutrality that integrate information from both within and between species, including the HKA-test and McDonald-Kreitman (MK) test. The logic for other tests of neutrality also is introduced, including ABBA-BABA, Composite Likelihood Ratio (CLR), Extended Haplotype Homozygosity (EHH), and other approaches. Practical implications of ancestral polymorphism and slightly deleterious polymorphisms are discussed, for example, in calculating and interpreting the neutrality index and fraction of positively selected sites (α‎). The goal of this chapter is to explain the logic of methods applied to molecular population genetic data to read the story of evolutionary history from the genome.