Michael C. Whitlock

The incomplete natural history of mitochondria

Mitochondrial DNA (mtDNA) has been used to study molecular ecology and phylogeography for 25 years. Much important information has been gained in this way, but it is time to reflect on the biology of the mitochondrion itself and consider opportunities for evolutionary studies of the organelle itself and its ecology, biochemistry and physiology. This review has four sections. First, we review aspects of the natural history of mitochondria and their DNA to show that it is a unique molecule with specific characteristics that differ from nuclear DNA. We do not attempt to cover the plethora of differences between mitochondrial and nuclear DNA; rather we spotlight differences that can cause significant bias when inferring demographic properties of populations and/or the evolutionary history of species. We focus on recombination, effective population size and mutation rate. Second, we explore some of the difficulties in interpreting phylogeographical data from mtDNA data alone and suggest a broader use of multiple nuclear markers. We argue that mtDNA is not a sufficient marker for phylogeographical studies if the focus of the investigation is the species and not the organelle. We focus on the potential bias caused by introgression. Third, we show that it is not safe to assume a priori that mtDNA evolves as a strictly neutral marker because both direct and indirect selection influence mitochondria. We outline some of the statistical tests of neutrality that can, and should, be applied to mtDNA sequence data prior to making any global statements concerning the history of the organism. We conclude with a critical examination of the neglected biology of mitochondria and point out several surprising gaps in the state of our knowledge about this important organelle. Here we limelight mitochondrial ecology, sexually antagonistic selection, life‐history evolution including ageing and disease, and the evolution of mitochondrial inheritance.

Indirect measures of gene flow and migration: FST≠1/(4Nm+1)

The difficulty of directly measuring gene flow has lead to the common use of indirect measures extrapolated from genetic frequency data. These measures are variants of FST, a standardized measure of the genetic variance among populations, and are used to solve for Nm, the number of migrants successfully entering a population per generation. Unfortunately, the mathematical model underlying this translation makes many biologically unrealistic assumptions; real populations are very likely to violate these assumptions, such that there is often limited quantitative information to be gained about dispersal from using gene frequency data. While studies of genetic structure per se are often worthwhile, and FST is an excellent measure of the extent of this population structure, it is rare that FST can be translated into an accurate estimate of Nm.

Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach.

The most commonly used method in evolutionary biology for combining information across multiple tests of the same null hypothesis is Fishers combined probability test. This note shows that an alternative method called the weighted Z‐test has more power and more precision than does Fishers test. Furthermore, in contrast to some statements in the literature, the weighted Z‐method is superior to the unweighted Z‐transform approach. The results in this note show that, when combining P‐values from multiple tests of the same hypothesis, the weighted Z‐method should be preferred.

PERSPECTIVE:EVOLUTION AND DETECTION OF GENETIC ROBUSTNESS

Abstract Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms underlying robustness are diverse, ranging from thermodynamic stability at the RNA and protein level to behavior at the organismal level. Phenotypes can be robust either against heritable perturbations (e.g., mutations) or nonheritable perturbations (e.g., the weather). Here we primarily focus on the first kind of robustness—genetic robustness—and survey three growing avenues of research: (1) measuring genetic robustness in nature and in the laboratory; (2) understanding the evolution of genetic robustness; and (3) exploring the implications of genetic robustness for future evolution.

Some population genetic consequences of colony formation and extinction: genetic correlations within founding groups.

Extinction and recolonization in an island model affects genetic differentiation among subpopulations through a combination of sampling and mixing. We investigate the balance of these forces in a general model of population founding that predicts first the genetic variance among new groups and then the effect of these new groups on the total genetic variance among all populations. We allow for a broad range of types of mixing at the time of colonization and demonstrate the significant effects on differentiation from the probability of common origin of gametes (φ). We further demonstrate that kin‐structured founding and inbreeding within populations can have a significant effect on the genetic variance among groups and use these results to make predictions about lineal fission and fusion of populations. These results show that population structure is critically affected by non‐equilibrium dynamics and that the properties of new populations, especially founding number, probability of common origin, and kin structure, are vital in our understanding of genetic variation.

Evolutionary inference from QST.

Q ST is a commonly used metric of the degree of genetic differentiation among populations displayed by quantitative traits. Typically, QST is compared to FST measured on putatively neutral loci; if QST=FST, this is taken as evidence of spatially heterogeneous and diversifying selection. This paper reviews the uses, assumptions and statistics of QST and FST comparisons. Unfortunately, QST/FST comparisons are statistically challenging. For a single trait, QST must be compared not to the mean FST but to the distribution of FST values. The sources of biases and sampling error for QST are reviewed, and a new method for comparing QST and FST is suggested. Simulation results suggest that the distribution of neutral FST and QST values are little affected by various deviations from the island model. Consequently, the distributions of QST and FST are well approximated by the Lewontin–Krakauer prediction, even with realistic deviations from the island‐model assumptions.

The Red Queen Beats the Jack-Of-All-Trades: The Limitations on the Evolution of Phenotypic Plasticity and Niche Breadth

The evolution of niche breadth or phenotypic plasticity is often assumed to be limited by negative genetic correlations among fitness in different environments, but these trade-offs are rarely observed. Many other constraints can reduce the mean niche breadth of species. This article discusses one of these limitations-that species with broader niche breadths can have a slower rate of evolutionary response. Species with narrower niche breadths have higher probabilities of fixing beneficial alleles, taking less time to do so; they have fewer deleterious alleles drifting to fixation (a lighter drift load) and a lower frequency of deleterious alleles at mutation-selection equilibrium (a lighter mutation load). These patterns are true even with no correlation at all between fitness in different environments; no trade-offs are assumed. Furthermore, niche breadth is likely to evolve to be more narrow, because of the association between location and alleles favored in local habitats for individuals with reduced migration, assortative mating, or habitat selection. The evolution of niche breadth and plasticity is not a simple function of the fitness in different environments; understanding niche breadth evolution requires consideration of the limitations of the evolutionary process per se.

FIXATION OF NEW ALLELES AND THE EXTINCTION OF SMALL POPULATIONS: DRIFT LOAD, BENEFICIAL ALLELES, AND SEXUAL SELECTION

With a small effective population size, random genetic drift is more important than selection in determining the fate of new alleles. Small populations therefore accumulate deleterious mutations. Left unchecked, the effect of these fixed alleles is to reduce the reproductive capacity of a species, eventually to the point of extinction. New beneficial mutations, if fixed by selection, can restore some of this lost fitness. This paper derives the overall change in fitness due to fixation of new deleterious and beneficial alleles, as a function of the distribution of effects of new mutations and the effective population size. There is a critical effective size below which a population will on average decline in fitness, but above which beneficial mutations allow the population to persist. With reasonable estimates of the relevant parameters, this critical effective size is likely to be a few hundred. Furthermore, sexual selection can act to reduce the fixation probability of deleterious new mutations and increase the probability of fixing new beneficial mutations. Sexual selection can therefore reduce the risk of extinction of small populations.

Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests

FST outlier tests are a potentially powerful way to detect genetic loci under spatially divergent selection. Unfortunately, the extent to which these tests are robust to nonequilibrium demographic histories has been understudied. We developed a landscape genetics simulator to test the effects of isolation by distance (IBD) and range expansion on FST outlier methods. We evaluated the two most commonly used methods for the identification of FST outliers (FDIST2 and BayeScan, which assume samples are evolutionarily independent) and two recent methods (FLK and Bayenv2, which estimate and account for evolutionary nonindependence). Parameterization with a set of neutral loci (‘neutral parameterization’) always improved the performance of FLK and Bayenv2, while neutral parameterization caused FDIST2 to actually perform worse in the cases of IBD or range expansion. BayeScan was improved when the prior odds on neutrality was increased, regardless of the true odds in the data. On their best performance, however, the widely used methods had high false‐positive rates for IBD and range expansion and were outperformed by methods that accounted for evolutionary nonindependence. In addition, default settings in FDIST2 and BayeScan resulted in many false positives suggesting balancing selection. However, all methods did very well if a large set of neutral loci is available to create empirical P‐values. We conclude that in species that exhibit IBD or have undergone range expansion, many of the published FST outliers based on FDIST2 and BayeScan are probably false positives, but FLK and Bayenv2 show great promise for accurately identifying loci under spatially divergent selection.

The genetic architecture of adaptation under migration-selection balance.

Many ecologically important traits have a complex genetic basis, with the potential for mutations at many different genes to shape the phenotype. Even so, studies of local adaptation in heterogeneous environments sometimes find that just a few quantitative trait loci (QTL) of large effect can explain a large percentage of observed differences between phenotypically divergent populations. As high levels of gene flow can swamp divergence at weakly selected alleles, migration–selection–drift balance may play an important role in shaping the genetic architecture of local adaptation. Here, we use analytical approximations and individual‐based simulations to explore how genetic architecture evolves when two populations connected by migration experience stabilizing selection toward different optima. In contrast to the exponential distribution of allele effect sizes expected under adaptation without migration (Orr 1998), we find that adaptation with migration tends to result in concentrated genetic architectures with fewer, larger, and more tightly linked divergent alleles. Even if many small alleles contribute to adaptation at the outset, they tend to be replaced by a few large alleles under prolonged bouts of stabilizing selection with migration. All else being equal, we also find that stronger selection can maintain linked clusters of locally adapted alleles over much greater map distances than weaker selection. The common empirical finding of QTL of large effect is shown to be expected with migration in a heterogeneous landscape, and these QTL may often be composed of several tightly linked alleles of smaller effect.