Inferring Process from Pattern in Fungal Population Genetics

Ignazio Carbone1; Linda Kohn2 kohn@utm.utoronto.ca    1 Center for Integrated Fungal Research, Department of Plant Pathology, North Carolina State University, Box 7244 – Partners II Building, Raleigh, NC 27695-7244, USA
2 Department of Botany, University of Toronto, 3359 Mississauga Rd. N., Mississauga, ON L5L 1C6, Canada.
Corresponding author: L.M. Kohn

Our focus in this review is on powerful new methods for determining population patterning over time and space and how from this, the dynamic processes leading to population divergence and speciation can be inferred. We focus on fungal populations, but draw from the wider literature on population genetics, evolutionary statistics, and, of course, phylogeography (see Avise, 2000). We discuss the problems of gene duplication, paralogy, orthology, and deep coalescence as challenges to finding the interface between population divergence and speciation. Our main objective, however, is to guide the reader through the key phylogenetic, nested phylogenetic, coalescent and Bayesian operations with the aid of a set of figures based on a simple, hypothetical dataset of DNA haplotypes. Phylogenetic and compatibility approaches are presented with the goal of not only detecting recombination, but of detecting recombination when it is not widespread throughout a phylogeny. This is a major challenge in fungal systems with substantial asexual reproduction or with significant selfed sexual reproduction in a haploid genome. The key feature here is that recombination can be “localized” in some but not all clades in a phylogeny and that these clades can be identified. From this, contemporary versus historical patterns of recombination can be inferred from a phylogeny. Phylogenetic approaches based on conversion of the phylogeny to a nested hierarchical statistical design are presented for fuller exploration of associations between each nested level of the phylogeny and any variable, such as geographical location, host, or symptom type. The basic operations for both testing for population subdivision based on geographical associations, and for cladistic inference of population processes are presented. Our hypothetical dataset is also used to demonstrate how genealogical relationships and population parameters can be inferred using coalescent and Bayesian methods. The basic principles of these approaches are graphically presented, along with useful references and comments on key assumptions implicit in methods currently available.

1 INTRODUCTION

Population genetics is the study of the structure of populations and of the evolutionary processes that shape these structural patterns. The patterns of distinct, divergent populations are inferred from the genetic diversity of contemporary samples made from “the field”, including clinical patient populations. The evolutionary processes include mutation, gene flow, recombination, selection, and drift. Population divergence resulting from such evolutionary processes, as well as from hybridization or vicariance (fragmentation of the environment that can lead to fragmentation of populations), eventually results in speciation. Through phylogenetic and coalescent statistical models, including Bayesian approaches, we can retrospectively determine the most probable chronology of events causing population divergence and identify the most probable events responsible for this divergence. Population genomics takes the genetics of natural or experimental populations steps further to study changes in genotype and gene expression during adaptation, one of the many applications of microarray technology (Cowen et al. 2002; Zeyl 2000).

The fundamental source of biological variation is mutation. This variation is shuffled among individuals by genetic exchange, through sex or horizontal transfer, recombination and segregation. Natural selection, i.e. differential reproduction, acts on the individual, but of course the results of selection are only visible in populations. Populations of a species are dynamic; in practice, the boundary between evolving, diverging populations and speciation may be difficult to define. Populations may diverge in response to changes in population size, genetic drift (random changes in allele frequencies to which small populations are especially prone), and changes in gene flow (the movement of genes, gametes, or individuals). Genetic diversity can be described and quantified in three ways (McDonald and Linde 2002a). Nucleotide diversity within genes or genomic regions (loci) is measured as the average number of nucleotide differences per site, π, between any two randomly chosen DNA sequences from a population (Nei 1987). In contrast, the two types of genetic diversity that are major components of population structure are gene diversity, the number and frequency of alleles at a single locus in a population, and genotype diversity, the number and frequency of multilocus genotypes (distinct individuals) in a population. Increasing gene diversity results not only in additional alleles but also in an equalization of allele frequencies (McDonald and Linde 2002a). For the purposes of this review, a population is defined as a group of individuals that occupy a particular geographical space in time, share a common ancestry, undergo genetic drift together, and may eventually become reproductively, ecologically and genetically well-differentiated as species (de Queiroz 1998).

Fungal population genetics has been amply reviewed (Anderson and Kohn 1998; Burdon 1993; Leung et al. 1993; McDonald 1997; McDonald and Linde 2002a; Milgroom 1996). A perusal of these reviews offers a history of a field that has exploded with the development of different types of molecular markers, from isozymes to RFLPs, AFLPs, microsatellites, oligonucleotides, and single nucleotide polymophisms (SNPs), as well as with the improved implementation of several types of statistical analyses and the development of important, new statistical approaches.

Once gene and genotypic diversity are determined by means of markers as allele frequencies among single or multilocus haplotypes, a range of analyses can partition this diversity as patterns of distinct populations or subpopulations. From these patterns, inferences of gene flow or genetic drift can be made. Leung et al. (1993), McDermott and McDonald (1993), and Milgroom (1995) reviewed the concepts, analyses (including virulence) and standard statistical approaches to determining population structure. These include measures of genetic variation and determination of partitions (patterns) of this variation by means of F statistics, notably FSt (Wright 1951) and GST (Nei 1973). Leung et al. (1993) introduced tree-building methods for inferring similarity among individuals.

In sexual reproduction, regular genetic exchange through mating and recombination can accelerate the evolution of new genotypes by bringing together mutations arising in different individuals. In fungi, recombination in sexual reproduction and processes of recombination outside of sex, such as parasexuality or transposition, are evident, although not to the extent that such events confound phylogenetic inference in most of the fungi investigated to date. Fungi do not show the substantial trafficking in mobile genetic elements seen in Bacteria. Horizontal gene transfer among widely divergent taxa, another means of recombination, has not yet been strongly demonstrated in fungi (Rosewich and Kistler 2000). Under strict clonality, mutations are only transmitted vertically from parent to offspring and such populations might be expected to evolve more slowly than non-clonal populations under conditions where adaptive mutations are limiting. Of course, large population size may make a wide variety of mutations available. Because fungi often reproduce predominantly asexually, their populations may occupy the “grey zone” between panmixia (random mating) and clonality. Milgroom (1996) reviewed the evolutionary significance of recombination and critically examined how frequencies of multilocus genotypes can be used to find evidence of recombination, to test a hypothesis of random mating, and to determine recombination frequency. Clonality in fungi has been reviewed by Anderson and Kohn (1995). More recently, in the context of considering how fungi fit the classical models of population genetics, Anderson and Kohn (1998) provided an overview of the phylogenetic criterion for recombination, also reviewing the evidence for mitochondrial recombination in fungi.

In a review on assessing fitness in fungal populations, Pringle and Taylor (2002) recommended choosing appropriate fitness measures matched to components of often complex life cycles, as well as considering life history and ecological characteristics, such as iterative versus single sporulation. The goals would be to predict or measure the fitness of pathogen genotypes and to determine the effects of specific pathogen genotypes on the fitness of host genotypes (see also: Antonovics and Kareiva 1988; Brunet and Mundt 2000).

McDonald (1997) reviewed genetic markers and sampling designs most suitable for examining population genetic structure. Although isozymes and other electrophoretically based markers continue to be useful, DNA nucleotide sequence is the gold standard because of...