Evolutionary assembly of cooperating cell types in an animal chemical defense system

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What paths do advantageous alleles take during short‐term evolutionary change?

Combining experimental evolution with whole‐genome resequencing is a promising new strategy for investigating the dynamics of evolutionary change. Published studies that have resequenced laboratory‐selected populations of sexual organisms have typically focused on populations sampled at the end of an evolution experiment. These studies have attempted to associate particular alleles with phenotypic change and attempted to distinguish between different theoretical models of adaptation. However, neither the population used to initiate the experiment nor multiple time points sampled during the evolutionary trajectory are generally available for examination. In this issue of Molecular Ecology, Orozco‐terWengel et al. (2012) take a significant step forward by estimating genome‐wide allele frequencies at the start, 15 generations into and at the end of a 37‐generation Drosophila experimental evolution study. The authors identify regions of the genome that have responded to laboratory selection and describe the temporal dynamics of allele frequency change. They identify two common trajectories for putatively adaptive alleles: alleles either gradually increase in frequency throughout the entire 37 generations or alleles plateau at a new frequency by generation 15. The identification of complex trajectories of alleles under selection contributes to a growing body of literature suggesting that simple models of adaptation, whereby beneficial alleles arise and increase in frequency unimpeded until they become fixed, may not adequately describe short‐term response to selection.     

Genetic and evolutionary relationships among Asian Macaques

Published gene frequency data, checked for consistency of allele definitions across laboratories and for comparability of geographically identical samples, were pooled into a data set containing frequencies at nine loci for each of 20 populations that encompassed 10 macaque species. Genetic distances were calculated by the methods of Kidd and Cavalli-Sforza (1974). These distances were used to construct phylogenetic trees and to evaluate the relationships between divergence times and effective population sizes. Inter-and intraspecific genetic distances and the groupings defined by phenetic tree analyses support Fooden’s (1976) classification of the genus Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain qualitatively the inferred evolutionary relationships among macaque species. Many assumptions are required in order to estimate the variables necessary in the quantitative prediction of genetic differences for a comparison between any two populations. Examination of those assumptions demonstrates the need for more accurate genetic as well as paleozoogeographic information. An erratum to this article is available at .     

Recent activities of the Microbiology in Schools Advisory Committee

Ecology and evolution

Agricultural education

Evolution and education

Education division elections

ISII in Europe

Tree project

Science teaching scholarship

Biology of terrestrial arthropods

A microscopied museum     

The role of epiphytism in architecture and evolutionary constraint within mycorrhizal networks of tropical orchids

Characterizing the architecture of bipartite networks is increasingly used as a framework to study biotic interactions within their ecological context and to assess the extent to which evolutionary constraint shape them. Orchid mycorrhizal symbioses are particularly interesting as they are viewed as more beneficial for plants than for fungi, a situation expected to result in an asymmetry of biological constraint. This study addressed the architecture and phylogenetic constraint in these associations in tropical context. We identified a bipartite network including 73 orchid species and 95 taxonomic units of mycorrhizal fungi across the natural habitats of Reunion Island. Unlike some recent evidence for nestedness in mycorrhizal symbioses, we found a highly modular architecture that largely reflected an ecological barrier between epiphytic and terrestrial subnetworks. By testing for phylogenetic signal, the overall signal was stronger for both partners in the epiphytic subnetwork. Moreover, in the subnetwork of epiphytic angraecoid orchids, the signal in orchid phylogeny was stronger than the signal in fungal phylogeny. Epiphytic associations are therefore more conservative and may co‐evolve more than terrestrial ones. We suggest that such tighter phylogenetic specialization may have been driven by stressful life conditions in the epiphytic niches. In addition to paralleling recent insights into mycorrhizal networks, this study furthermore provides support for epiphytism as a major factor affecting ecological assemblage and evolutionary constraint in tropical mycorrhizal symbioses.     

Dynamics of the Coreceptor-LCK Interactions during T Cell Development Shape the Self-Reactivity of Peripheral CD4 and CD8 T Cells

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Distinguishing Drift and Selection Empirically: “The Great Snail Debate” of the 1950s

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case – Maxime Lamotte’s study of natural populations of the land snail, Cepaea nemoralis in the 1950s – shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations under study, Lamotte was able to make a good case for a significant role for␣drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not (always) impossible.