Controlling Population Evolution in the Laboratory to Evaluate Methods of Historical Inference

Natural populations of known detailed past demographic history are extremely valuable to evaluate methods of historical inference, yet are extremely rare. As an alternative approach, we have generated multiple replicate microsatellite data sets from laboratory-cultured populations of a gonochoric free-living nematode, Caenorhabditis remanei, that were constrained to pre-defined demographic histories featuring different levels of migration among populations or bottleneck events of different magnitudes. These data sets were then used to evaluate the performances of two recently developed population genetics methods, BayesAss+, that estimates recent migration rates among populations, and Bottleneck, that detects the occurrence of recent bottlenecks. Migration rates inferred by BayesAss+ were generally over-estimates, although these were often included within the confidence interval. Analyses of data sets simulated in-silico, using a model mimicking the laboratory experiments, produced less biased estimates of the migration rates, and showed increased efficiency of the program when the number of loci and sampled genotypes per population was higher. In the replicates for which the pre-bottleneck laboratory-cultured populations did not significantly depart from a mutation/drift equilibrium, an important assumption of the program Bottleneck, only a portion of the bottleneck events were detected. This result was confirmed by in-silico simulations mirroring the laboratory bottleneck experiments. More generally, our study demonstrates the feasibility, and highlights some of the limits, of the approach that consists in generating molecular genetic data sets by controlling the evolution of laboratory-reared nematode populations, for the purpose of validating methods inferring population history

Inferring selection in the Anopheles gambiae species complex: an example from immune-related serine protease inhibitors

<p>Abstract</p> <p>Background</p> <p>Mosquitoes of the <it>Anopheles gambiae </it>species complex are the primary vectors of human malaria in sub-Saharan Africa. Many host genes have been shown to affect <it>Plasmodium </it>development in the mosquito, and so are expected to engage in an evolutionary arms race with the pathogen. However, there is little conclusive evidence that any of these mosquito genes evolve rapidly, or show other signatures of adaptive evolution.</p> <p>Methods</p> <p>Three serine protease inhibitors have previously been identified as candidate immune system genes mediating mosquito-Plasmodium interaction, and serine protease inhibitors have been identified as hot-spots of adaptive evolution in other taxa. Population-genetic tests for selection, including a recent multi-gene extension of the McDonald-Kreitman test, were applied to 16 serine protease inhibitors and 16 other genes sampled from the <it>An. gambiae </it>species complex in both East and West Africa.</p> <p>Results</p> <p>Serine protease inhibitors were found to show a marginally significant trend towards higher levels of amino acid diversity than other genes, and display extensive genetic structuring associated with the 2La chromosomal inversion. However, although serpins are candidate targets for strong parasite-mediated selection, no evidence was found for rapid adaptive evolution in these genes.</p> <p>Conclusion</p> <p>It is well known that phylogenetic and population history in the <it>An. gambiae </it>complex can present special problems for the application of standard population-genetic tests for selection, and this may explain the failure of this study to detect selection acting on serine protease inhibitors. The pitfalls of uncritically applying these tests in this species complex are highlighted, and the future prospects for detecting selection acting on the <it>An. gambiae </it>genome are discussed.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta