Comparative evolution of influenza A virus H1 and H3 head and stalk domains across host species

IMPORTANCE

For decades, researchers have studied the rapid evolution of influenza A viruses for vaccine design and as a useful model system for the study of host/parasite evolution. By performing an exhaustive analysis of hemagglutinin protein (HA) sequences from 49 lineages independently evolving in birds, swine, canines, equines, and humans over the last century, our work uncovers surprising features of HA evolution. In particular, the canine H3 stalk, unlike human H3 and H1 stalk domains, is not evolving slowly, suggesting that evolution in the stalk domain is not universally constrained across all host species. Therefore, a broader multi-host perspective on HA evolution may be useful during the evaluation and design of stalk-targeted vaccine candidates.

Accelerating Bayesian inference of dependency between mixed-type biological traits

Inferring dependencies between mixed-type biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The state-of-the-art approach uses a phylogenetic multivariate probit model to accommodate binary and continuous traits via a latent variable framework, and utilizes an efficient bouncy particle sampler (BPS) to tackle the computational bottleneck-integrating many latent variables from a high-dimensional truncated normal distribution. This approach breaks down as the number of specimens grows and fails to reliably characterize conditional dependencies between traits. Here, we propose an inference pipeline for phylogenetic probit models that greatly outperforms BPS. The novelty lies in 1) a combination of the recent Zigzag Hamiltonian Monte Carlo (Zigzag-HMC) with linear-time gradient evaluations and 2) a joint sampling scheme for highly correlated latent variables and correlation matrix elements. In an application exploring HIV-1 evolution from 535 viruses, the inference requires joint sampling from an 11,235-dimensional truncated normal and a 24-dimensional covariance matrix. Our method yields a 5-fold speedup compared to BPS and makes it possible to learn partial correlations between candidate viral mutations and virulence. Computational speedup now enables us to tackle even larger problems: we study the evolution of influenza H1N1 glycosylations on around 900 viruses. For broader applicability, we extend the phylogenetic probit model to incorporate categorical traits, and demonstrate its use to study Aquilegia flower and pollinator co-evolution.

T Residues Preceded by Runs of G are Hotspots of T→G Mutation in Bacteria

The rate of mutation varies among positions in a genome. Local sequence context can affect the rate, and has different effects on different types of mutation. Here I report an effect of local context that operates to some extent in all bacteria examined: the rate of T→G mutation is greatly increased by preceding runs of three or more G residues. The strength of the effect increases with the length of the run. In Salmonella, in which the effect is strongest, a G run of length three increases the rate by a factor of ∼26, a run of length four increases it by almost a factor of 100, and runs of length five or more increase it by a factor of more than 400 on average. The effect is much stronger when the T is on the leading rather than the lagging strand of DNA replication. Several observations eliminate the possibility that this effect is an artifact of sequencing error.

Restriction Endonuclease-Based Modification-Dependent Enrichment (REMoDE) of DNA for Metagenomic Sequencing

Metagenomic sequencing is a swift and powerful tool to ascertain the presence of an organism of interest in a sample. However, sequencing coverage of the organism of interest can be insufficient due to an inundation of reads from irrelevant organisms in the sample. Here, we report a nuclease-based approach to rapidly enrich for DNA from certain organisms, including enterobacteria, based on their differential endogenous modification patterns. We exploit the ability of taxon-specific methylated motifs to resist the action of cognate methylation-sensitive restriction endonucleases that thereby digest unwanted, unmethylated DNA. Subsequently, we use a distributive exonuclease or electrophoretic separation to deplete or exclude the digested fragments, thus enriching for undigested DNA from the organism of interest. As a proof of concept, we apply this method to enrich for the enterobacteria Escherichia coli and Salmonella enterica by 11- to 142-fold from mock metagenomic samples and validate this approach as a versatile means to enrich for genomes of interest in metagenomic samples. IMPORTANCE Pathogens that contaminate the food supply or spread through other means can cause outbreaks that bring devastating repercussions to the health of a populace. Investigations to trace the source of these outbreaks are initiated rapidly but can be drawn out due to the labored methods of pathogen isolation. Metagenomic sequencing can alleviate this hurdle but is often insufficiently sensitive. The approach and implementations detailed here provide a rapid means to enrich for many pathogens involved in foodborne outbreaks, thereby improving the utility of metagenomic sequencing as a tool in outbreak investigations. Additionally, this approach provides a means to broadly enrich for otherwise minute levels of modified DNA, which may escape unnoticed in metagenomic samples.

Origins and Evolution of Seasonal Human Coronaviruses

Four seasonal human coronaviruses (sHCoVs) are endemic globally (229E, NL63, OC43, and HKU1), accounting for 5-30% of human respiratory infections. However, the epidemiology and evolution of these CoVs remain understudied due to their association with mild symptomatology. Using a multigene and complete genome analysis approach, we find the evolutionary histories of sHCoVs to be highly complex, owing to frequent recombination of CoVs including within and between sHCoVs, and uncertain, due to the under sampling of non-human viruses. The recombination rate was highest for 229E and OC43 whereas substitutions per recombination event were highest in NL63 and HKU1. Depending on the gene studied, OC43 may have ungulate, canine, or rabbit CoV ancestors. 229E may have origins in a bat, camel, or an unsampled intermediate host. HKU1 had the earliest common ancestor (1809-1899) but fell into two distinct clades (genotypes A and B), possibly representing two independent transmission events from murine-origin CoVs that appear to be a single introduction due to large gaps in the sampling of CoVs in animals. In fact, genotype B was genetically more diverse than all the other sHCoVs. Finally, we found shared amino acid substitutions in multiple proteins along the non-human to sHCoV host-jump branches. The complex evolution of CoVs and their frequent host switches could benefit from continued surveillance of CoVs across non-human hosts.

Recent Genetic Changes Affecting Enterohemorrhagic Escherichia coli Causing Recurrent Outbreaks

Enterohemorrhagic E. coli (EHEC) is responsible for significant human illness, death, and economic loss. The main reservoir for EHEC is cattle, but plant-based foods are common vectors for human infection. Several outbreaks have been attributed to lettuce and leafy green vegetables grown in the Salinas and Santa Maria regions of California. Bacteria causing different outbreaks are mostly not close relatives, but one group of closely-related O157:H7 has caused several of them. This unusual pattern of recurrence may have some genetic basis. Here I use whole-genome sequences to reconstruct the genetic changes that occurred in the recent ancestry of this EHEC. In a short period of time corresponding to little genetic change, there were several changes to adhesion-related sequences, mainly adhesins. These changes may have greatly altered the adhesive properties of the bacteria. Possible consequences include increased persistence of cattle infections, more bacteria shed in cattle feces, and greater virulence in humans. Similar constellations of genetic change, which are detectable by current sequencing-based surveillance, may identify other bacteria that are particular threats to human health. In addition, the Santa Maria subclade carries a nonsense mutation affecting ArsR, a repressor of genes that confer resistance to arsenic and antimony. This suggests that the persistent source of Santa Maria contamination is located in an area with arsenic-contaminated groundwater, a problem in many parts of California. This inference may aid identification of the reservoir of EHEC, which would greatly aid mitigation efforts. IMPORTANCE Food-borne bacterial infections cause substantial illness and death. Understanding how bacteria contaminate food and cause disease is important for combating the problem. Closely-related E. coli, likely originating in cattle, have repeatedly caused outbreaks spread by vegetables grown in California. Such recurrence is atypical, and might have a genetic basis. The genetic changes that occurred in the recent ancestry of these E. coli can be reconstructed from their DNA sequences. Several mutations affect genes involved in bacterial adhesion. These might affect persistence of infection in cattle, quantity of bacteria in their feces, and human disease. They also suggest a way of detecting dangerous bacteria from their genome sequences. Furthermore, a subgroup carries a mutation affecting the regulation of genes conferring arsenic resistance. This suggests that the reservoir for contamination utilizes groundwater contaminated with arsenic, a problem in parts of California. This observation may be an aid to locating the persistent reservoir of contamination.

Selection-Driven Gene Inactivation in Salmonella

Bacterial genes are sometimes found to be inactivated by mutation. This inactivation may be observable simply because selection for function is intermittent or too weak to eliminate inactive alleles quickly. Here, I investigate cases in Salmonella enterica where inactivation is instead positively selected. These are identified by a rate of introduction of premature stop codons to a gene that is higher than expected under selective neutrality, as assessed by comparison to the rate of synonymous changes. I identify 84 genes that meet this criterion at a 10% false discovery rate. Many of these genes are involved in virulence, motility and chemotaxis, biofilm formation, and resistance to antibiotics or other toxic substances. It is hypothesized that most of these genes are subject to an ongoing process in which inactivation is favored under rare conditions, but the inactivated allele is deleterious under most other conditions and is subsequently driven to extinction by purifying selection.

Methylation-Induced Hypermutation in Natural Populations of Bacteria

Methylation of DNA at the C-5 position of cytosine occurs in diverse organisms. This modification can increase the rate of C→T transitions at the methylated position. In Escherichia coli and related enteric bacteria, the inner C residues of the sequence CCWGG (W is A or T) are methylated by the Dcm enzyme. These sites are hot spots of mutation during rapid growth in the laboratory but not in nondividing cells, in which repair by the Vsr protein is effective. It has been suggested that hypermutation at these sites is a laboratory artifact and does not occur in nature. Many other methyltransferases, with a variety of specificities, can be found in bacteria, usually associated with restriction enzymes and confined to a subset of the population. Their methylation targets are also possible sites of hypermutation. Here, I show using whole-genome sequence data for thousands of isolates that there is indeed considerable hypermutation at Dcm sites in natural populations: their transition rate is approximately eight times the average. I also demonstrate hypermutability of targets of restriction-associated methyltransferases in several distantly related bacteria: methylation increases the transition rate by a factor ranging from 12 to 58. In addition, I demonstrate how patterns of hypermutability inferred from massive sequence data can be used to determine previously unknown methylation patterns and methyltransferase specificities.IMPORTANCE A common type of DNA modification, addition of a methyl group to cytosine (C) at carbon atom C-5, can greatly increase the rate of mutation of the C to a T. In mammals, methylation of CG sequences increases the rate of CG→TG mutations. It is unknown whether cytosine C-5 methylation increases the mutation rate in bacteria under natural conditions. I show that sites methylated by the Dcm enzyme exhibit an 8-fold increase in mutation rate in natural bacterial populations. I also show that modifications at other sites in various bacteria also increase the mutation rate, in some cases by a factor of forty or more. Finally, I demonstrate how this phenomenon can be used to infer sequence specificities of methylation enzymes.

A practical exact maximum compatibility algorithm for reconstruction of recent evolutionary history

Background

Maximum compatibility is a method of phylogenetic reconstruction that is seldom applied to molecular sequences. It may be ideal for certain applications, such as reconstructing phylogenies of closely-related bacteria on the basis of whole-genome sequencing.

Results

Here I present an algorithm that rapidly computes phylogenies according to a compatibility criterion. Although based on solutions to the maximum clique problem, this algorithm deals properly with ambiguities in the data. The algorithm is applied to bacterial data sets containing up to nearly 2000 genomes with several thousand variable nucleotide sites. Run times are several seconds or less. Computational experiments show that maximum compatibility is less sensitive than maximum parsimony to the inclusion of nucleotide data that, though derived from actual sequence reads, has been identified as likely to be misleading.

Conclusions

Maximum compatibility is a useful tool for certain phylogenetic problems, such as inferring the relationships among closely-related bacteria from whole-genome sequence data. The algorithm presented here rapidly solves fairly large problems of this type, and provides robustness against misleading characters than can pollute large-scale sequencing data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1520-4) contains supplementary material, which is available to authorized users.

Why does a protein's evolutionary rate vary over time?

The sequences of different proteins evolve at different rates. The relative evolutionary rate (ER) of a single protein also changes over evolutionary time. The cause of this ER fluctuation remains uncertain, and study of this phenomenon may shed light on protein evolution more broadly. We have characterized ER fluctuation in mammals and Drosophila. We found little correlation between the amount of rate variation observed for a protein and such factors as its expression level or phylogenetic distribution. Perhaps more surprisingly, we found little correlation between our measure of rate variation and ER itself. We also investigated the extent to which the ERs of different domains of a protein vary independently. We found that rates of different domains do tend to vary together. In fact, rates at positions in different domains are coupled just as strongly as rates at equally distant positions in the same domain. These findings provide clues to the protein evolutionary process.

Complex patterns of human antisera reactivity to novel 2009 H1N1 and historical H1N1 influenza strains

BACKGROUND

During the 2009 influenza pandemic, individuals over the age of 60 had the lowest incidence of infection with approximately 25% of these people having pre-existing, cross-reactive antibodies to novel 2009 H1N1 influenza isolates. It was proposed that older people had pre-existing antibodies induced by previous 1918-like virus infection(s) that cross-reacted to novel H1N1 strains.

METHODOLOGY/PRINCIPAL FINDINGS

Using antisera collected from a cohort of individuals collected before the second wave of novel H1N1 infections, only a minority of individuals with 1918 influenza specific antibodies also demonstrated hemagglutination-inhibition activity against the novel H1N1 influenza. In this study, we examined human antisera collected from individuals that ranged between the ages of 1 month and 90 years to determine the profile of seropositive influenza immunity to viruses representing H1N1 antigenic eras over the past 100 years. Even though HAI titers to novel 2009 H1N1 and the 1918 H1N1 influenza viruses were positively associated, the association was far from perfect, particularly for the older and younger age groups.

CONCLUSIONS/SIGNIFICANCE

Therefore, there may be a complex set of immune responses that are retained in people infected with seasonal H1N1 that can contribute to the reduced rates of H1N1 influenza infection in older populations.

Projection of seasonal influenza severity from sequence and serological data

Severity of seasonal influenza A epidemics is related to the antigenic novelty of the predominant viral strains circulating each year. Support for a strong correlation between epidemic severity and antigenic drift comes from infectious challenge experiments on vaccinated animals and human volunteers, field studies of vaccine efficacy, prospective studies of subjects with laboratory-confirmed prior infections, and analysis of the connection between drift and severity from surveillance data. We show that, given data on the antigenic and sequence novelty of the hemagglutinin protein of clinical isolates of H3N2 virus from a season along with the corresponding data from prior seasons, we can accurately predict the influenza severity for that season. This model therefore provides a framework for making projections of the severity of the upcoming season using assumptions based on viral isolates collected in the current season. Our results based on two independent data sets from the US and Hong Kong suggest that seasonal severity is largely determined by the novelty of the hemagglutinin protein although other factors, including mutations in other influenza genes, co-circulating pathogens and weather conditions, might also play a role. These results should be helpful for the control of seasonal influenza and have implications for improvement of influenza surveillance.

Expression level, evolutionary rate, and the cost of expression

There is great variation in the rates of sequence evolution among proteins encoded by the same genome. The strongest correlate of evolutionary rate is expression level: highly expressed proteins tend to evolve slowly. This observation has led to the proposal that a major determinant of protein evolutionary rate involves the toxic effects of protein that misfolds due to transcriptional and translational errors (the mistranslation-induced misfolding [MIM] hypothesis). Here, I present a model that explains the correlation of evolutionary rate and expression level by selection for function. The basis of this model is that selection keeps expression levels near optima that reflect a trade-off between beneficial effects of the protein's function and some nonspecific cost of expression (e.g., the biochemical cost of synthesizing protein). Simulations confirm the predictions of the model. Like the MIM hypothesis, this model predicts several other relationships that are observed empirically. Although the model is based on selection for protein function, it is consistent with findings that a protein's rate of evolution is at most weakly correlated with its importance for fitness as measured by gene knockout experiments.

Highly expressed and slowly evolving proteins share compositional properties with thermophilic proteins

The sequences of proteins encoded by a genome evolve at different rates. A correlate of a protein's evolutionary rate is its expression level: highly expressed proteins tend to evolve slowly. Some explanations of rate variation and the correlation between rate and expression predict that more slowly evolving and more highly expressed proteins have more favorable equilibrium constants for folding. Proteins from thermophiles generally have more stable folds than proteins from mesophiles, and it is known that there are systematic differences in amino acid content between thermophilic and mesophilic proteins. I examined whether there are analogous correlations of amino acid frequencies with evolutionary rate and expression level within genomes. In most of the organisms analyzed, there is a striking tendency for more slowly evolving proteins to be more thermophile-like in their amino acid compositions when adjustments are made for variation in GC content. More highly expressed proteins also tend to be more thermophile-like by the same criteria. These results suggest that part of the evolutionary rate variation among proteins is due to variation in the strength of selection for stability of the folded state. They also suggest that increasing strength of this selective force with expression level plays a role in the correlation between evolutionary rate and expression level.

Evolutionary dynamics of N-glycosylation sites of influenza virus hemagglutinin

The hemagglutinin protein of influenza virus bears several sites of N-linked asparagine glycosylation. The number and location of these sites varies with strain and substrain. The human H3 hemagglutinin has gained several glycosylation sites on the antigenically important globular head since its introduction to humans, presumably due to selection. Although there is abundant evidence that glycosylation can affect antigenic and functional properties of the protein, direct evidence for selection is lacking. We have analyzed gain and loss of glycosylation sites on the side branches of a large phylogenetic tree of H3 HA1 sequences (branches off of the main, long-term line of descent). Side branches contrast with the main line of descent: losses of glycosylation sites are not uncommon, and they outnumber gains. Although other explanations are possible, this observation is consistent with weak selection for glycosylation sites or a more complicated pattern of selection. Furthermore, terminal and internal branches differ with respect to rates of gain and loss of glycosylation sites. This pattern would not be expected under selective neutrality, but is easily explained by weak selection or selection that changes with the immune state of the host population. Thus, it provides evidence that selection acts on the glycosylation state of hemagglutinin.

The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes

Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.

Selection, subdivision and extinction and recolonization

In a subdivided population, the interaction between natural selection and stochastic change in allele frequency is affected by the occurrence of local extinction and subsequent recolonization. The relative importance of selection can be diminished by this additional source of stochastic change in allele frequency. Results are presented for subdivided populations with extinction and recolonization where there is more than one founding allele after extinction, where these may tend to come from the same source deme, where the number of founding alleles is variable or the founders make unequal contributions, and where there is dominance for fitness or local frequency dependence. The behavior of a selected allele in a subdivided population is in all these situations approximately the same as that of an allele with different selection parameters in an unstructured population with a different size. The magnitude of the quantity N(e)s(e), which determines fixation probability in the case of genic selection, is always decreased by extinction and recolonization, so that deleterious alleles are more likely to fix and advantageous alleles less likely to do so. The importance of dominance or frequency dependence is also altered by extinction and recolonization. Computer simulations confirm that the theoretical predictions of both fixation probabilities and mean times to fixation are good approximations.

Selection, Subdivision and Extinction and Recolonization

In a subdivided population, the interaction between natural selection and stochastic change in allele frequency is affected by the occurrence of local extinction and subsequent recolonization. The relative importance of selection can be diminished by this additional source of stochastic change in allele frequency. Results are presented for subdivided populations with extinction and recolonization where there is more than one founding allele after extinction, where these may tend to come from the same source deme, where the number of founding alleles is variable or the founders make unequal contributions, and where there is dominance for fitness or local frequency dependence. The behavior of a selected allele in a subdivided population is in all these situations approximately the same as that of an allele with different selection parameters in an unstructured population with a different size. The magnitude of the quantity Nese, which determines fixation probability in the case of genic selection, is always decreased by extinction and recolonization, so that deleterious alleles are more likely to fix and advantageous alleles less likely to do so. The importance of dominance or frequency dependence is also altered by extinction and recolonization. Computer simulations confirm that the theoretical predictions of both fixation probabilities and mean times to fixation are good approximations.

Selection in a subdivided population with local extinction and recolonization

In a subdivided population, local extinction and subsequent recolonization affect the fate of alleles. Of particular interest is the interaction of this force with natural selection. The effect of selection can be weakened by this additional source of stochastic change in allele frequency. The behavior of a selected allele in such a population is shown to be equivalent to that of an allele with a different selection coefficient in an unstructured population with a different size. This equivalence allows use of established results for panmictic populations to predict such quantities as fixation probabilities and mean times to fixation. The magnitude of the quantity N(e)s(e), which determines fixation probability, is decreased by extinction and recolonization. Thus deleterious alleles are more likely to fix, and advantageous alleles less likely to do so, in the presence of extinction and recolonization. Computer simulations confirm that the theoretical predictions of both fixation probabilities and mean times to fixation are good approximations.

Genome size and operon content

Prokaryotic genes are often organized into operons, clusters of genes that are transcribed together. Because all genes in an operon must be transcribed in the same direction, this organization will be reflected in a tendency for nearby genes to have the same orientation. This tendency can be used to estimate the degree to which the genes in a genome are clustered into operons. Application of the technique to Escherichia coli yields results that are similar to estimates based on detailed examination of the genome and empirical knowledge about particular operons. Results for Saccharomyces cerevisiae are consistent with the near absence of polycistronic transcripts in eukaryotes. The method is easily applied to other genomes that have been sequenced and annotated. Analysis of 26 bacterial and archaeal genomes indicates that the degree of clustering varies widely among prokaryotes. Comparison of these genomes shows that those containing more genes tend to have less clustering of genes into operons. This observation may have implications concerning the evolution of operons.

Selection in a subdivided population with dominance or local frequency dependence

The interplay between population structure and natural selection is an area of great interest. It is known that certain types of population subdivision do not alter fixation probabilities of selected alleles under genic, frequency-independent selection. In the presence of dominance for fitness or frequency-dependent selection these same types of subdivision can have large effects on fixation probabilities. For example, the barrier to fixation of a fitter allele due to underdominance is reduced by subdivision. Analytic results presented here relate a subdivided population that conforms to a finite island model to an approximately equivalent panmictic population. The size of this equivalent population is different from (larger than) the actual size of the subdivided population. Selection parameters are also different in the hypothetical equivalent population. As expected, the degree of dominance is lower in the equivalent population. The results are not limited to dominance but cover any form of polynomial frequency dependence.

A diffusion approximation for selection and drift in a subdivided population

The population-genetic consequences of population structure are of great interest and have been studied extensively. An area of particular interest is the interaction among population structure, natural selection, and genetic drift. At first glance, different results in this area give very different impressions of the effect of population subdivision on effective population size (N(e)), suggesting that no single value of N(e) can completely characterize a structured population. Results presented here show that a population conforming to Wright's island model of subdivision with genic selection can be related to an idealized panmictic population (a Wright-Fisher population). This equivalent panmictic population has a larger size than the actual population; i.e., N(e) is larger than the actual population size, as expected from many results for this type of population structure. The selection coefficient in the equivalent panmictic population, referred to here as the effective selection coefficient (s(e)), is smaller than the actual selection coefficient (s). This explains how the fixation probability of a selected allele can be unaffected by population subdivision despite the fact that subdivision increases N(e), for the product N(e)s(e) is not altered by subdivision.

Deleterious mutation and the evolution of eusociality

Certain arguments concerning the evolution of eusociality form a classic example of the application of the principles of kin selection. These arguments center on the different degrees of relatedness of potential beneficiaries of an individual's efforts, for example a female's higher relatedness to her sisters than to her daughters in a haplodiploid system. This type of reasoning is insufficicnt to account for the evolution and maintainence of sexual reproduction, because parthenogenic females produce offspring that are more closely related to them than are offspring produced sexually. Among the forces invoked to explain sexual reproduction is deleterious mutation. This factor can be shown to favor eusociality as well, because siblings produced by helping carry fewer deleterious alleles on average than would offspring. The strength of this effect depends on the genomewide deleterious mutation rate, U, and on the selection coefficient, s, associated with deleterious alleles. For small s, the effect depends approximately on the product Us. This phenomenon illustrates that an assumption implicit in some analyses-that the relatedness of an individual to an actor is all that matters to its value to that actor-can fail for the evolution of eusociality as it does for the evolution of sex.

Genetic and phylogenetic consequences of island biogeography

Island biogeography theory predicts that the number of species on an island should increase with island size and decrease with island distance to the mainland. These predictions are generally well supported in comparative and experimental studies. These ecological, equilibrium predictions arise as a result of colonization and extinction processes. Because colonization and extinction are also important processes in evolution, we develop methods to test evolutionary predictions of island biogeography. We derive a population genetic model of island biogeography that incorporates island colonization, migration of individuals from the mainland, and extinction of island populations. The model provides a means of estimating the rates of migration and extinction from population genetic data. This model predicts that within an island population the distribution of genetic divergences with respect to the mainland source population should be bimodal, with much of the divergence dating to the colonization event. Across islands, this model predicts that populations on large islands should be on average more genetically divergent from mainland source populations than those on small islands. Likewise, populations on distant islands should be more divergent than those on close islands. Published observations of a larger proportion of endemic species on large and distant islands support these predictions.

How to make a biological switch

Some biological regulatory systems must "remember" a state for long periods of time. A simple type of system that can accomplish this task is one in which two regulatory elements negatively regulate one another. For example, two repressor proteins might control one another's synthesis. Qualitative reasoning suggests that such a system will have two stable states, one in which the first element is "on" and the second "off", and another in which these states are reversed. Quantitative analysis shows that the existence of two stable steady states depends on the details of the system. Among other things, the shapes of functions describing the effect of one regulatory element on the other must meet certain criteria in order for two steady states to exist. Many biologically reasonable functions do not meet these criteria. In particular, repression that is well described by a Michaelis-Menten-type equation cannot lead to a working switch. However, functions describing positive cooperativity of binding, non-additive effects of multiple operator sites, or depletion of free repressor can lead to working switches.

The use of modified primers to eliminate cycle sequencing artifacts

Cycle sequencing is the workhorse of DNA sequencing projects, allowing the production of large amounts of product from relatively little template. This cycling regime, which is aimed at linear growth of the desired products, can also produce artifacts by exponential amplification of minor side-products. These artifacts can interfere with sequence determination. In an attempt to allow linear but prevent exponential growth of products, and thus eliminate artifacts, we have investigated the use of primers containing modified residues that cannot be replicated by DNA polymerase. Specifically, we have used primers containing 2'- O -methyl RNA residues or abasic residues. Oligomers consisting of six DNA residues and 20 2'- O -methyl RNA residues, with the DNA residues located at the 3'-end, primed as efficiently as DNA primers but would not support exponential amplification. Oligonucleotides containing fewer DNA residues were not used as efficiently as primers. DNA primers containing a single abasic site located six residues from the 3'-end also showed efficient priming ability without yielding exponential amplification products. Together these results demonstrate that certain types of modified primers can be used to eliminate artifacts in DNA sequencing. The technique should be particularly useful in protocols involving large numbers of cycles, such as direct sequencing of BAC and genomic DNA.

Divergence of the hyperthermophilic archaea Pyrococcus furiosus and P. horikoshii inferred from complete genomic sequences

Divergence of the hyperthermophilic Archaea, Pyrococcus furiosus and Pyrococcus horikoshii, was assessed by analysis of complete genomic sequences of both species. The average nucleotide identity between the genomic sequences is 70-75% within ORFs. The P. furiosus genome (1.908 mbp) is 170 kbp larger than the P. horikoshii genome (1.738 mbp) and the latter displays significant deletions in coding regions, including the trp, his, aro, leu-ile-val, arg, pro, cys, thr, and mal operons. P. horikoshii is auxotrophic for tryptophan and histidine and is unable to utilize maltose, unlike P. furiosus. In addition, the genomes differ considerably in gene order, displaying displacements and inversions. Six allelic intein sites are common to both Pyrococcus genomes, and two intein insertions occur in each species and not the other. The bacteria-like methylated chemotaxis proteins form a functional group in P. horikoshii, but are absent in P. furiosus. Two paralogous families of ferredoxin oxidoreductases provide evidence of gene duplication preceding the divergence of the Pyrococcus species.

Should we expect substitution rate to depend on population size?

The rate of nucleotide substitution is generally believed to be a decreasing function of effective population size, at least for nonsynonymous substitutions. This view was originally based on consideration of slightly deleterious mutations with a fixed distribution of selection coefficients. A realistic model must include the occurrence and fixation of some advantageous mutations that compensate for the loss of fitness due to deleterious substitutions. Some such models, such as so-called "fixed" models, also predict a population size effect on substitution rate. An alternative model, presented here, predicts the near absence of a population size effect on substitution rate. This model is based on concave log-fitness functions and a fixed distribution of mutational effects on the selectively important trait. Simulations of an instance of the model confirm the approximate insensitivity of the substitution rate to population size. Although much experimental evidence has been claimed to support the existence of a population size effect, the body of evidence as a whole is equivocal, and much of the evidence that is supposed to demonstrate such an effect would also suggest that it is very small. Perhaps the proposed model applies well to some genes and not so well to others, and genes therefore vary with regard to the population size effect.

Enzyme-linked fluorescent detection for automated multiplex DNA sequencing

Initiatives to sequence DNA on a large scale have created a need for increased throughput and decreased costs. One scheme for increasing throughput, multiplex sequencing, involves the processing of a mixture of sequencing templates followed by sequential hybridization to reveal the individual sequence ladders on a membrane. Because multiplex sequencing has not been fully automated, and has not seemed automatable, few sequencing efforts have attempted to exploit it. We describe here a scheme for the automation of multiplex sequencing. Probe hybridized to target DNA is detected via spatially localized enzyme-linked fluorescence. Light output is high enough that imaging is possible with simple instrumentation. Direct imaging within an automated hybridization apparatus is made feasible so that the entire process will be automatic once a multiplex membrane is produced. The technique has the potential to increase severalfold the throughput of automated sequencing instruments required for sequencing the human genome.

Rapid cycle allele-specific amplification: studies with the cystic fibrosis delta F508 locus

Rapid cycle DNA amplification is a polymerase chain reaction technique with improved product specificity and cycle times of 20-60 s, allowing complete 30-cycle reactions in 10-30 min. The presence or absence of the delta F508 deletion and wild-type allele was determined in 104 cystic fibrosis patients by rapid cycle DNA amplification. In separate allele-specific assays, sequences on both sides of the delta F508 locus were amplified with the 3' end of a discriminating primer at the delta F508 locus, with either a 3-bp or a 1-bp mismatch. With rapid cycling (35-s cycles), single-base discrimination was achieved over a broad range of annealing temperatures (50 degrees C or lower); with conventional cycling and "hot starts" (160-s cycles), only annealing temperatures of 61-62 degrees C sufficiently discriminated between alleles. With rapid cycling, genotype could still be assessed with annealing temperatures as low as 25 degrees C. We conclude that faster temperature cycling can improve the results of allele-specific amplification.

Rapid cycle allele-specific amplification: studies with the cystic fibrosis delta F508 locus

Rapid cycle DNA amplification is a polymerase chain reaction technique with improved product specificity and cycle times of 20-60 s, allowing complete 30-cycle reactions in 10-30 min. The presence or absence of the delta F508 deletion and wild-type allele was determined in 104 cystic fibrosis patients by rapid cycle DNA amplification. In separate allele-specific assays, sequences on both sides of the delta F508 locus were amplified with the 3' end of a discriminating primer at the delta F508 locus, with either a 3-bp or a 1-bp mismatch. With rapid cycling (35-s cycles), single-base discrimination was achieved over a broad range of annealing temperatures (50 degrees C or lower); with conventional cycling and "hot starts" (160-s cycles), only annealing temperatures of 61-62 degrees C sufficiently discriminated between alleles. With rapid cycling, genotype could still be assessed with annealing temperatures as low as 25 degrees C. We conclude that faster temperature cycling can improve the results of allele-specific amplification.