J. Maynard Smith's research while affiliated with University of Sussex and other places

Extensive data from multilocus electrophoresis are available for many bacterial populations. In some cases, for example Neisseria gonorrhoeae, these data are consistent with the population being in linkage equilibrium. This raises the following question. What frequency of transformation, or other means of genetic recombination, is needed, relative to mutation, to produce apparent panmixis? Simulation of a finite-population model suggests that, if transformation is at least twenty times as frequent as mutation, the population structure will be indistinguishable from a panmictic one, using the best available data sets. That is, relatively infrequent transformation is sufficient to produce approximate linkage equilibrium.

The patterns of nucleotide polymorphism in human mitochondrial sequences rock the belief that mitochondria do not recombine.

There are two types of recombination that we may wish to detect: rare recombinants between members of different populations or species and repeated recombination within a population. Methods appropriate in the former context are inappropriate in the latter because they depend on recognizing the existence of runs of nucleotides with similar ancestry. If recombination is sufficiently frequent, no such runs will be present. Several methods, including the homoplasy test and the incompatibility test, are described that are appropriate for detecting repeated recombination and for measuring its importance, relative to mutation, in causing genetic change. The sensitivity of these tests is investigated by simulating populations with varying frequencies of mutation and recombination and calculating the various statistics on samples.

In this article, a method is proposed for detecting recombination in the sequences of a gene from a set of closely related organisms. The method, the Homoplasy Test, is appropriate when the sequences are rather similar, differing by 1%-5% of nucleotides. It is effective in detecting relatively frequent recombination between a set of rather similar strains, in contrast to previous methods which detect rare or unique transfers between more distant strains. It is based on the fact that, if there is no recombination and if no repeated mutations have occurred (homoplasy), then the number of polymorphic sites, v, is equal to the number of steps, t, in a most-parsimonious tree. If the number of "apparent homoplasies" in the most-parsimonious tree, h = t-v, is greater than zero, then either homoplasies have occurred by mutation or there has been recombination. An estimate of the distribution of h expected on the null hypothesis of no recombination depends on Se, the "effective site number," defined as follows: if ps is the probability that two independent substitutions in the gene occur at the same site, then Se = 1/ps. Se can be estimated if a suitable outgroup is available. The Homoplasy Test is applied to three bacterial genes and to simulated gene trees with varying amounts of recombination. Methods of estimating the rate, as opposed to the occurrence, of recombination are discussed.

The nucleotide divergence at synonymous third sites between two lineages will increase with time since the latest common ancestor, up to some saturation level. The "null-hypothesis divergence" is defined as the percentage of difference predicted at synonymous third sites, allowing for amino acid composition and codon bias, but assuming that codon bias is the same at all sites occupied by a given amino acid, when equilibrium has been reached between forward and backward substitutions. For two highly expressed genes, gapA and ompA, in the enterobacteria, the estimated values of the null-hypothesis divergence are 39.3 and 38.15%, respectively, compared to estimated values of saturation divergence of 19.0 and 25.4%. A possible explanation for this discrepancy is that different codons for a given amino acid are favored at different sites in the same gene.

Sequences of the gapA and ompA genes from 10 genera of enterobacteria have been analyzed. There is strong bias in codon usage, but different synonymous codons are preferred at different sites in the same gene. Site-specific preference for unfavored codons is not confined to the first 100 codons and is usually manifest between two codons utilizing the same tRNA. Statistical analyses, based on conclusions reached in an accompanying paper, show that the use of an unfavored codon at a given site in different genera is not due to common descent and must therefore be caused either by sequence-specific mutation or sequence-specific selection. Reasons are given for thinking that sequence-specific mutation cannot be responsible. We are unable to explain the preference between synonymous codons ending in C or T, but synonymous choice between A and G at third sites is largely explained by avoidance of AG-G (where the hyphen indicates the boundary between codons). We also observed that the preferred codon for proline in Enterobacter cloacea has changed from CCG to CCA.

Technical advances in molecular genetics over the past decade have made it possible to reconstruct phylogenetic trees of a wider range of organisms with much greater accuracy than was previously possible. The meeting on which the papers in this volume are based brought together research workers who are developing and applying new approaches to use these molecular phylogenies as tools for answering questions in diverse areas of biological investigation. The underlying theme of this volume is scientific inference. How can we use phylogenetic trees to infer evolutionary process? The answer to that question inevitably lies in revealing a pattern which is recognized as agreeing with or deviating from an expectation. That expectation may be about tree structure itself, revealed from a formal null model which describes the evolutionary process that results in tree generation. Alternatively, the expectation may be about character evolution, in which case tree structure is central to revealing the different occasions on which similar character states actually evolved.

Protein 1 (PI) is a major porin of Neisseria gonorrhoeae and Neisseria meningitidis and is encoded by a single locus, porB. Alleles of the porB locus of N. gonorrhoeae are assigned to two homology groups, PI(A) and PI(B), on the basis of immunological and structural similarity. In a like manner, alleles of the porB locus of the closely related bacterium, N. meningitidis, are allocated into class 2 and class 3 homology groups. An individual strain of N. gonorrhoeae or N. meningitidis expresses either one or other of these porin homology groups but never both, and the antigenic reactions of these highly diverse outer membrane proteins form part of the N. gonorrhoeae and N. meningitidis serotyping schemes. A comparison of the number of synonymous and nonsynonymous substitutions per site between the two most divergent alleles of each of these four groups of porB alleles shows that PI(A) alleles have accumulated significantly more nonsynonymous substitutions per site than synonymous substitutions. In contrast the distribution of synonymous and nonsynonymous substitutions between alleles of class 2 and class 3 porins are not significantly different from random. We localize the regions of the PI(A) alleles with an excess of amino acid changes to the surface-exposed loops of these outer membrane proteins and suggest that positive Darwinian selection for diversity, driven by the human immune system, can most easily explain the allelic polymorphism and the pattern of synonymous and nonsynonymous substitutions.