quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation

Summary: quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo Contact: [email protected]

Brood size, sibling competition, and the cost of begging in great tits (Parus major)

Evolutionary theory of parent-offspring conflict explains begging displays of nestling birds as selfish attempts to influence parental food allocation. Models predict that this conflict may be resolved by honest signaling of offspring need to parents, or by competition among nestmates, leading to escalated begging scrambles. Although the former type of models has been qualitatively supported by experimental studies, the potential for a begging component driven by scramble competition cannot be excluded by the evidence. In a brood-size manipulation experiment with great tits, Parus major, we explored the scramble component in the begging activity of great tit nestlings by investigating the mechanisms of sibling competition in relation to brood size. While under full parental compensation, the feeding rate per nestling will remain constant over all brood sizes for both types of models; the scramble begging models alone predict an increase in begging intensity with brood size, if begging costs do not arise exclusively through predation. Great tit parents adjusted feeding rates to brood size and fed nestlings at similar rates and with similar prey sizes in all three brood-size categories. Despite full parental compensation, the begging and food solicitation activities increased with experimental brood size, whereas nestling body condition deteriorated. These findings support a scramble component in begging and suggest that the competition-induced costs of food solicitation behavior play an important role in the evolution of parent-offspring communicatio

Nachhaltige Wirkungen der Integrationsprogramme

Welche Auswirkungen haben die Integrationsprogramme der Sozialhilfe auf die Teilnehmenden im Hinblick auf ihre soziale oder berufliche Integration? Um die Wirkung messen zu können, wurden zwischen November 2015 und Februar 2017 drei Befragungen von Teilnehmenden von Integrationsprogrammen durchgeführt: bei Programmbeginn, bei Programmende nach sechs Monaten sowie neun Monate nach Programmende

Thoracic Gas Volume in Athletes and Non-Athletes

The purpose of this study was to analyze the predicted thoracic gas volume versus measured thoracic gas volume in college students, comparing NCAA collegiate athletes versus non-athletes using the Bod Pod. Forty-four college students, both males and females, athletes and non-athletes, completed a body composition test to obtain the predicted thoracic gas volume. The participants were then instructed by the Bod Pod software through the measured thoracic gas volume test. Due to low statistical power, athletes and non-athletes were unable to be compared, however, results of a two sample t-test showed that there was a statistically significant difference between measured thoracic gas volume and predicted thoracic gas volume within the population as a whole. The average predicted thoracic gas volume was 3.66 liters ± 0.103 while the measured thoracic gas volume was 4.02 liters ± 0.165. The significance level for the test was p ≤ 0.05 and the p-value obtained from the statistical analysis was p ≤ 0.001. It was concluded that within this study, there was a significant difference between the predicted and measured thoracic gas volumes of the population

Museomics identifies genetic erosion in two butterfly species across the 20th century in Finland

Erosion of biodiversity generated by anthropogenic activities has been studied for decades in many areas at species level, using taxa monitoring. In contrast, genetic erosion within species has rarely been tracked, and is often studied by inferring past population dynamics from contemporaneous estimators. An alternative to such inferences is the direct examination of past genes, by analysing museum collection specimens. While providing direct access to genetic variation over time, historical DNA is usually not optimally preserved, and it is necessary to apply genotyping methods based on hybridization-capture to unravel past genetic variation. In this study, we apply such a method (i.e., HyRAD), to large time series of two butterfly species in Finland, and present a new bioinformatic pipeline, namely PopHyRAD, that standardizes and optimizes the analysis of HyRAD data at the within-species level. In the localities for which the data retrieved have sufficient power to accurately examine genetic dynamics through time, we show that genetic erosion has increased across the last 100 years, as revealed by signatures of allele extinctions and heterozygosity decreases, despite local variations. In one of the two butterflies (Erebia embla), isolation by distance also increased through time, revealing the effect of greater habitat fragmentation over time.Peer reviewe

Complex genetic patterns in human arise from a simple range-expansion model over continental landmasses

© 2018 Kanitz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Although it is generally accepted that geography is a major factor shaping human genetic differentiation, it is still disputed how much of this differentiation is a result of a simple process of isolation-by-distance, and if there are factors generating distinct clusters of genetic similarity. We address this question using a geographically explicit simulation framework coupled with an Approximate Bayesian Computation approach. Based on six simple summary statistics only, we estimated the most probable demographic parameters that shaped modern human evolution under an isolation by distance scenario, and found these were the following: an initial population in East Africa spread and grew from 4000 individuals to 5.7 million in about 132 000 years. Subsequent simulations with these estimates followed by cluster analyses produced results nearly identical to those obtained in real data. Thus, a simple diffusion model from East Africa explains a large portion of the genetic diversity patterns observed in modern humans. We argue that a model of isolation by distance along the continental landmasses might be the relevant null model to use when investigating selective effects in humans and probably many other species

ABCtoolbox: a versatile toolkit for approximate Bayesian computations

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results

External quality assessment of SARS-CoV-2-sequencing: An ESGMD-SSM pilot trial across 15 European laboratories

Objective: This first pilot on external quality assessment (EQA) of SARS-CoV-2 whole genome sequencing, initiated by the ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD) and Swiss Society for Microbiology (SSM), aims to build a framework between laboratories in order to improve pathogen surveillance sequencing.Methods: Ten samples with varying viral loads were sent out to 15 clinical laboratories who had free choice of sequencing methods and bioinformatic analyses. The key aspects on which the individual centres were compared on were identification of 1) SNPs and indels, 2) Pango lineages, and 3) clusters between samples.Results: The participating laboratories used a wide array of methods and analysis pipelines. Most were able to generate whole genomes for all samples. Genomes were sequenced to varying depth (up to 100-fold difference across centres). There was a very good consensus regarding the majority of reporting criteria, but there were a few discrepancies in lineage and cluster assignment. Additionally, there were inconsistencies in variant calling. The main reasons for discrepancies were missing data, bioinformatic choices, and interpretation of data.Conclusions: The pilot EQA was an overall success. It was able to show the high quality of participating labs and provide valuable feedback in cases where problems occurred, thereby improving the sequencing setup of laboratories. A larger follow-up EQA should, however, improve on defining the variables and format of the report. Additionally, contamination and/or minority variants should be a further aspect of assessment.</p