A numerical framework for genetic hitchhiking in populations of variable size

Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection

Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.

Brazilian Populations of Aedes aegypti Resistant to Pyriproxyfen Exhibit Lower Susceptibility to Infection with Zika Virus

Zika virus (ZIKV) infection has caused devastating consequences in Brazil as infections were associated with neurological complications in neonates. Aedes aegypti is the primary vector of ZIKV, and the evolution of insecticide resistance (IR) in this species can compromise control efforts. Although relative levels of phenotypic IR in mosquitoes can change considerably over time, its influence on vector competence for arboviruses is unclear. Pyriproxyfen (PPF)-resistant populations of Ae. aegypti were collected from five municipalities located in Northeast of Brazil, which demonstrated different resistance levels; low (Serrinha, Brumado), moderate (Juazeiro do Norte, Itabuna), and high (Quixadá). Experimental per os infection using ZIKV were performed with individuals from these populations and with an insecticide susceptible strain (Rockefeller) to determine their relative vector competence for ZIKV. Although all populations were competent to transmit ZIKV, mosquitoes derived from populations with moderate to high levels of IR exhibited similar or lower susceptibility to ZIKV infection than those from populations with low IR or the susceptible strain. These observations suggest an association between IR and arbovirus infection, which may be attributable to genetic hitchhiking. The use of PPF to control Brazilian Ae. aegypti may be associated with an indirect benefit of reduced susceptibility to infection, but no changes in disseminated infection and transmission of ZIKV among PPF-resistant phenotypes.

On the prospect of achieving accurate joint estimation of selection with population history

As both natural selection and population history can affect genome-wide patterns of variation, disentangling the contributions of each has remained as a major challenge in population genetics. We here discuss historical and recent progress towards this goal—highlighting theoretical and computational challenges that remain to be addressed, as well as inherent difficulties in dealing with model complexity and model violations—and offer thoughts on potentially fruitful next steps.

Octopaminergic/tyraminergic Tdc2 neurons regulate biased sperm usage in female Drosophila melanogaster

In polyandrous internally fertilizing species, a multiply-mated female can use stored sperm from different males in a biased manner to fertilize her eggs. The female's ability to assess sperm quality and compatibility is essential for her reproductive success, and represents an important aspect of postcopulatory sexual selection. In Drosophila melanogaster, previous studies demonstrated that the female nervous system plays an active role in influencing progeny paternity proportion, and suggested a role for octopaminergic/tyraminergic Tdc2 neurons in this process. Here, we report that inhibiting Tdc2 neuronal activity causes females to produce a higher-than-normal proportion of first-male progeny. This difference is not due to differences in sperm storage or release, but instead is attributable to the suppression of second-male sperm usage bias that normally occurs in control females. We further show that a subset of Tdc2 neurons innervating the female reproductive tract is largely responsible for the progeny proportion phenotype that is observed when Tdc2 neurons are inhibited globally. On the contrary, overactivation of Tdc2 neurons does not further affect sperm storage and release or progeny proportion. These results suggest that octopaminergic/tyraminergic signaling allows a multiply-mated female to bias sperm usage, and identify a new role for the female nervous system in postcopulatory sexual selection.

What is N e, anyway?

Few doubt that effective population size (Ne) is one of the most important parameters in evolutionary biology, but how many can say they really understand the concept? Ne is the evolutionary analogue of the number of individuals (or adults) in the population, N. Whereas ecological consequences of population size depend on N, evolutionary consequences (rates of loss of genetic diversity and increase in inbreeding; relative effectiveness of selection) depend on Ne. Formal definitions typically relate effective size to a key population genetic parameter, such as loss of heterozygosity or variance in allele frequency. However, for practical application to real populations, it is more useful to define Ne in terms of three demographic parameters: number of potential parents (adult N), and mean and variance in offspring number. Defined this way, Ne determines the rate of random genetic drift across the entire genome in the offspring generation. Other evolutionary forces (mutation, migration, selection)—together with factors such as variation in recombination rate—can also affect genetic variation, and this leads to heterogeneity across the genome in observed rates of genetic change. For some, it has been convenient to interpret this heterogeneity in terms of heterogeneity in Ne, but unfortunately this has muddled the concepts of genetic drift and effective population size. A commonly-repeated misconception is that Ne is the number of parents that actually contribute genes to the next generation (NP). In reality, NP can be smaller or larger than Ne, and the NP/Ne ratio depends on the sex ratio, the mean and variance in offspring number, and whether inbreeding or variance Ne is of interest.