Revisiting the false positive rate in detecting recent positive selection

There is increasing interest in studying the molecular mechanisms of recent adaptations caused by positive selection in the genomics era. Such endeavors to detect recent positive selection, however, have been severely handicapped by false positives due to the confounding impact of demography and the population structure. To reduce false positives, it is critical to conduct a functional analysis to identify the true candidate genes/mutations from those that are filtered through neutrality tests. However, the extremely high cost of such functional analysis may restrict studies within a small number of model species. In particular, when the false positive rate of neutrality tests is high, the efficiency of the functional analysis will also be very low. Therefore, although the recent improvements have been made in the (joint) inference of demography and selection, our ultimate goal, which is to understand the mechanism of adaptation generally in a wide variety of natural populations, may not be achieved using the currently available approaches. More attention should thus be spent on the development of more reliable tests that could not only free themselves from the confounding impact of demography and the population structure but also have reasonable power to detect selection.     

Getting positive about selection

A report on the 68th Symposium on Quantitative Biology, The Genome of Homo Sapiens', Cold Spring Harbor, USA, 28 May-2 June 2003.     

Der positive Phototropismus dicotyler Keimpflanzen

Ohne ZusammenfassungMit 1 Textabbildung     

Genomic insights into positive selection

The traditional way of identifying targets of adaptive evolution has been to study a few loci that one hypothesizes a priori to have been under selection. This approach is complicated because of the confounding effects that population demographic history and selection have on patterns of DNA sequence variation. In principle, multilocus analyses can facilitate robust inferences of selection at individual loci. The deluge of large-scale catalogs of genetic variation has stimulated many genome-wide scans for positive selection in several species. Here, we review some of the salient observations of these studies, identify important challenges ahead, consider the limitations of genome-wide scans for selection and discuss the potential significance of a comprehensive understanding of genomic patterns of selection for disease-related research.     

Coexistence under positive frequency dependence

Negative frequency dependence resulting from interspecific interactions is considered a driving force in allowing the coexistence of competitors. While interactions between species and genotypes can also result in positive frequency dependence, positive frequency dependence has usually been credited with hastening the extinction of rare types and is not thought to contribute to coexistence. In the present paper, we develop a stochastic cellular automata model that allows us to vary the scale of frequency dependence and the scale of dispersal. The results of this model indicate that positive frequency dependence will allow the coexistence of two species at a greater rate than would be expected from chance. This coexistence arises from the generation of banding patterns that will be stable over long time-periods. As a result, we found that positive frequency-dependent interactions over local spatial scales promote coexistence over neutral interactions. This result was robust to variation in boundary conditions within the simulation and to variation in levels of disturbance. Under all conditions, coexistence is enhanced as the strength of positive frequency-dependent interactions is increased.     

Collective irrationality and positive feedback

Recent experiments on ants and slime moulds have assessed the degree to which they make rational decisions when presented with a number of alternative food sources or shelter. Ants and slime moulds are just two examples of a wide range of species and biological processes that use positive feedback mechanisms to reach decisions. Here we use a generic, experimentally validated model of positive feedback between group members to show that the probability of taking the best of options depends crucially on the strength of feedback. We show how the probability of choosing the best option can be maximized by applying an optimal feedback strength. Importantly, this optimal value depends on the number of options, so that when we change the number of options the preference of the group changes, producing apparent "irrationalities". We thus reinterpret the idea that collectives show "rational" or "irrational" preferences as being a necessary consequence of the use of positive feedback. We argue that positive feedback is a heuristic which often produces fast and accurate group decision-making, but is always susceptible to apparent irrationality when studied under particular experimental conditions.     

Hitchhiking under positive Darwinian selection

Positive selection can be inferred from its effect on linked neutral variation. In the restrictive case when there is no recombination, all linked variation is removed. If recombination is present but rare, both deterministic and stochastic models of positive selection show that linked variation hitchhikes to either low or high frequencies. While the frequency distribution of variation can be influenced by a number of evolutionary processes, an excess of derived variants at high frequency is a unique pattern produced by hitchhiking (derived refers to the nonancestral state as determined from an outgroup). We adopt a statistic, H, to measure an excess of high compared to intermediate frequency variants. Only a few high-frequency variants are needed to detect hitchhiking since not many are expected under neutrality. This is of particular utility in regions of low recombination where there is not much variation and in regions of normal or high recombination, where the hitchhiking effect can be limited to a small (<1 kb) region. Application of the H test to published surveys of Drosophila variation reveals an excess of high frequency variants that are likely to have been influenced by positive selection.