This journal frequently contains papers that report values of F-statistics estimated from genetic data collected from several populations. These parameters, FST, FIT, and FIS, were introduced by Wright (1951), and offer a convenient means of summarizing population structure. While there is some disagreement about the interpretation of the quantities, there is considerably more disagreement on the method of evaluating them. Different authors make different assumptions about sample sizes or numbers of populations and handle the difficulties of multiple alleles and unequal sample sizes in different ways. Wright himself, for example, did not consider the effects of finite sample size. The purpose of this discussion is to offer some unity to various estimation formulae and to point out that correlations of genes in structured populations, with which F-statistics are concerned, are expressed very conveniently with a set of parameters treated by Cockerham (1 969, 1973). We start with the parameters and construct appropriate estimators for them, rather than beginning the discussion with various data functions. The extension of Cockerham's work to multiple alleles and loci will be made explicit, and the use of jackknife procedures for estimating variances will be advocated. All of this may be regarded as an extension of a recent treatment of estimating the coancestry coefficient to serve as a mea-

https://www.jstor.org/stable/pdfplus/2408641.pdf

Estimating F-statistics for the analysis of population structure.

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Although much biological research depends upon species diagnoses, taxonomic expertise is collapsing. We are convinced that the sole prospect for a sustainable identification capability lies in the construction of systems that employ DNA sequences as taxon 'barcodes'. We establish that the mitochondrial gene cytochrome c oxidase I (COI) can serve as the core of a global bioidentification system for animals. First, we demonstrate that COI profiles, derived from the low-density sampling of higher taxonomic categories, ordinarily assign newly analysed taxa to the appropriate phylum or order. Second, we demonstrate that species-level assignments can be obtained by creating comprehensive COI profiles. A model COI profile, based upon the analysis of a single individual from each of 200 closely allied species of lepidopterans, was 100% successful in correctly identifying subsequent specimens. When fully developed, a COI identification system will provide a reliable, cost-effective and accessible solution to the current problem of species identification. Its assembly will also generate important new insights into the diversification of life and the rules of molecular evolution.

/pdf/biological-identifications-through-dna-barcodes-2m7h08avvi.pdf

Biological identifications through DNA barcodes

So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Two authoritative treatises have recently addressed the evolutionary origins of the eukaryotic genome’s many surprising architectural features, such as the fact that more than 50% of the DNA in various species is made up of active or retired transposable elements.Austin Burt and Robert Trivers describe diverse tactics by which seemingly selfish pieces of DNA actively spread and persist in populations of sexual reproducers and thereby generate extensive intragenomic (intergenic) strife. Michael Lynch, by contrast, emphasizes how even deleterious mutations can passively drift to fixation in small populations. The worldviews in these two books may seem fundamentally at odds, but they share a powerful notion that all eukaryotic genomes are like intracellular ecosystems, the natural histories of which are fundamental to how sexual genomes evolve.

The Natural History of the Sexual Genome: proactive drivers and passive drifters

In the Light of Evolution: Volume VII: The Human Mental Machinery

Author(s): Redelings, Benjamin D; Kumagai, Seiji; Wang, Liuyang; Tatarenkov, Andrey; Sakai, Ann K; Weller, Stephen G; Culley, Theresa M; Avise, John C; Uyenoyama, Marcy K | Abstract: We present a Bayesian method for characterizing the mating system of populations reproducing through a mixture of self-fertilization and random outcrossing. Our method uses patterns of genetic variation across the genome as a basis for inference about pure hermaphroditism, androdioecy, and gynodioecy. We extend the standard coalescence model to accommodate these mating systems, accounting explicitly for multilocus identity disequilibrium, inbreeding depression, and variation in fertility among mating types. We incorporate the Ewens Sampling Formula (ESF) under the infinite-alleles model of mutation to obtain a novel expression for the likelihood of mating system parameters. Our Markov chain Monte Carlo (MCMC) algorithm assigns locus-specific mutation rates, drawn from a common mutation rate distribution that is itself estimated from the data using a Dirichlet Process Prior (DPP) model. Among the parameters jointly inferred are the population-wide rate of self-fertilization, locus-specific mutation rates, and the number of generations since the most recent outcrossing event for each sampled individual.

/pdf/bayesian-co-estimation-of-selfing-rate-and-locus-specific-2tb2rb25t5.pdf

John C. Avise

Papers

The Natural History of the Sexual Genome: proactive drivers and passive drifters

In the Light of Evolution: Volume VII: The Human Mental Machinery

Bayesian co-estimation of selfing rate and locus-specific mutation rates for a partially selfing population

Genetic Variation, Population Structure, and Phylogeography

Demographic and life history characteristics influence the cytonuclear composition of mosquitofish populations