Sociality and the rate of molecular evolution

The molecular clock does not tick at a uniform rate in all taxa but maybe influenced by species characteristics. Eusocial species (those with reproductive division of labor) have been predicted to have faster rates of molecular evolution than their nonsocial relatives because of greatly reduced effective population size; if most individuals in a population are nonreproductive and only one or few queens produce all the offspring, then eusocial animals could have much lower effective population sizes than their solitary relatives, which should increase the rate of substitution of nearly neutral mutations. An earlier study reported faster rates in eusocial honeybees and vespid wasps but failed to correct for phylogenetic nonindependence or to distinguish between potential causes of rate variation. Because sociality has evolved independently in many different lineages, it is possible to conduct a more wide-ranging study to test the generality of the relationship. We have conducted a comparative analysis of 25 phylogenetically independent pairs of social lineages and their nonsocial relatives, including bees, wasps, ants, termites, shrimps, and mole rats, using a range of available DNA sequences (mitochondrial and nuclear DNA coding for proteins and RNAs, and nontranslated sequences). By including a wide range of social taxa, we were able to test whether there is a general influence of sociality on rates of molecular evolution and to test specific predictions of the hypothesis: (1) that social species have faster rates because they have reduced effective population sizes; (2) that mitochondrial genes would show a greater effect of sociality than nuclear genes; and (3) that rates of molecular evolution should be correlated with the degree of sociality. We find no consistent pattern in rates of molecular evolution between social and nonsocial lineages and no evidence that mitochondrial genes show faster rates in social taxa. However, we show that the most highly eusocial Hymenoptera do have faster rates than their nonsocial relatives. We also find that social parasites (that utilize the workers from related species to produce their own offspring) have faster rates than their social relatives, which is consistent with an effect of lower effective population size on rate of molecular evolution. Our results illustrate the importance of allowing for phylogenetic nonindependence when conducting investigations of determinants of variation in rate of molecular evolution.

Evolution of duplicate control regions in the mitochondrial genomes of metazoa: A case study with Australasian Ixodes ticks

To investigate the evolution pattern and phylogenetic utility of duplicate control regions (CRs) in mitochondrial (mt) genomes, we sequenced the entire mt genomes of three Ixodes species and part of the mt genomes of another I I species. All the species from the Australasian lineage have duplicate CRs, whereas the other species have one CR. Sequence analyses indicate that the two CRs of the Australasian Ixodes ticks have evolved in concert in each species. In addition to the Australasian Ixodes ticks, species from seven other lineages of metazoa also have mt genomes with duplicate CRs. Accumulated mtDNA sequence data from these metazoans and two recent experiments on replication of mt genomes in human cell lines with duplicate CRs allowed us to re-examine four intriguing questions about the presence of duplicate CRs in the mt genomes of metazoa: (1) Why do some mt genomes, but not others, have duplicate CRs? (2) How did mt genomes with duplicate CRs evolve? (3) How could the nucleotide sequences of duplicate CRs remain identical or very similar over evolutionary time? (4) Are duplicate CRs phylogenetic markers? It appears that mt genomes with duplicate CRs have a selective advantage in replication over mt genomes with one CR. Tandem duplication followed by deletion of genes is the most plausible mechanism for the generation of mt genomes with duplicate CRs. Once duplicate CRs occur in an mt genome, they tend to evolve in concert, probably by gene conversion. However, there are lineages where gene conversion may not always occur, and, thus, the two CRs may evolve independently in these lineages. Duplicate CRs have much potential as phylogenetic markers at low taxonomic levels, such as within genera, within families, or among families, but not at high taxonomic levels, such as among orders.

The crystal structure of a bacterial Class II ketol-acid reductolsomerase: Domain conservation and evolution

Ketol-acid reductoisomerase (KARI; EC 1.1.1.86) catalyzes two steps in the biosynthesis of branched-chain amino acids. Amino acid sequence comparisons across species reveal that there are two types of this enzyme: a short form (Class 1) found in fungi and most bacteria, and a long form (Class 11) typical of plants. Crystal structures of each have been reported previously. However, some bacteria such as Escherichia coli possess a long form, where the amino acid sequence differs appreciably from that found in plants. Here, we report the crystal structure of the E. coli enzyme at 2.6 A resolution, the first three-dimensional structure of any bacterial Class 11 KARI. The enzyme consists of two domains, one with mixed alpha/beta structure, which is similar to that found in other pyridine nucleotide-dependent dehydrogenases. The second domain is mainly alpha-helical and shows strong evidence of internal duplication. Comparison of the active sites between KARI of E. coli, Pseudomonas aeruginosa, and spinach shows that most residues occupy conserved positions in the active site. E. coli KARI was crystallized as a tetramer, the likely biologically active unit. This contrasts with P. aeruginosa KARI, which forms a dodecamer, and spinach KARI, a dimer. In the E. coli KARI tetramer, a novel subunit-to-subunit interacting surface is formed by a symmetrical pair of bulbous protrusions.

Divergent selection and the evolution of signal traits and mating preferences

Mating preferences are common in natural populations, and their divergence among populations is considered an important source of reproductive isolation during speciation. Although mechanisms for the divergence of mating preferences have received substantial theoretical treatment, complementary experimental tests are lacking. We conducted a laboratory evolution experiment, using the fruit fly Drosophila serrata, to explore the role of divergent selection between environments in the evolution of female mating preferences. Replicate populations of D. serrata were derived from a common ancestor and propagated in one of three resource environments: two novel environments and the ancestral laboratory environment. Adaptation to both novel environments involved changes in cuticular hydrocarbons, traits that predict mating success in these populations. Furthermore, female mating preferences for these cuticular hydrocarbons also diverged among populations. A component of this divergence occurred among treatment environments, accounting for at least 17.4% of the among- population divergence in linear mating preferences and 17.2% of the among-population divergence in nonlinear mating preferences. The divergence of mating preferences in correlation with environment is consistent with the classic by- product model of speciation in which premating isolation evolves as a side effect of divergent selection adapting populations to their different environments.

Coadaptation: A unifying principle in evolutionary thermal biology

Over the last 50 yr, thermal biology has shifted from a largely physiological science to a more integrated science of behavior, physiology, ecology, and evolution. Today, the mechanisms that underlie responses to environmental temperature are being scrutinized at levels ranging from genes to organisms. From these investigations, a theory of thermal adaptation has emerged that describes the evolution of thermoregulation, thermal sensitivity, and thermal acclimation. We review and integrate current models to form a conceptual model of coadaptation. We argue that major advances will require a quantitative theory of coadaptation that predicts which strategies should evolve in specific thermal environments. Simply combining current models, however, is insufficient to understand the responses of organisms to thermal heterogeneity; a theory of coadaptation must also consider the biotic interactions that influence the net benefits of behavioral and physiological strategies. Such a theory will be challenging to develop because each organism's perception of and response to thermal heterogeneity depends on its size, mobility, and life span. Despite the challenges facing thermal biologists, we have never been more pressed to explain the diversity of strategies that organisms use to cope with thermal heterogeneity and to predict the consequences of thermal change for the diversity of communities.

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.