Genetic diversity of the Central European wild boar (Sus scrofa scrofa) population and domestic pig (Sus scrofa domesticus) breeds based on a microsatellite DNA locus

The results of studies of the genetic structure of the Central European wild boar (Sus scrofa scrofa) population and four breeds of domestic pigs (Duroc, Yorkshire, Large White and Landrace) bred in the Central Black Earth region of Russia are presented in this work. Based on 12 microsatellite loci, a significant ( p <0.05) decrease in the level of genetic variability in bred breeds was shown. The expected heterozygosity and Shannon index were as follows: in the wild boar, Ho = 0.763 ± 0.026, I = 1.717 ± 0.091; in the Duroc breed, Ho = 0.569 ± 0.068, I = 1.191 ± 0.157; in the Landrace, Ho = 0.618 ± 0.062, I = 1.201 ± 0.147; in the Large White, Ho = 0.680 ± 0.029, I = 1.362 ± 0.074; and in the Yorkshire, Ho = 0.642 ± 0.065, I = 1.287 ± 0.156. The results of checking genotypic Hardy–Weinberg equilibrium based on the G-test of maximum likelihood demonstrated that the overwhelming majority of loci in the wild boar population were in the state of said equilibrium. By contrast, in pig breed populations, some loci demonstrated a significant deviation from the indicated equilibrium. In addition, the Yorkshire, Large White, and Landrace populations had loci, for which the hypothesis of neutrality was reliably rejected based on the results of the Ewens–Watterson test. The revealed private alleles, characteristic of the wild boar and breeds, can later be used to identify them. The ordination of the centroids of different herds in the space of the first two principal coordinates based on the matrix of pairwise estimates of Nei’s genetic distances showed that the most distant populations are the Duroc and Boar breeds, and the most genetically close are the Yorkshire and Landrace breeds. The closest to the wild boar population was the Large White breed. The assessment of the effective size, carried out using the method based on the linkage disequilibrium and the molecular coancestry method, showed that in all studied groups, including the wild boar population, the effective size was less than 100 individuals. The low effective size of the wild boar population (Ne = 21.8, Neb = 4.0) is probably caused by the death and shooting of animals due to Pestis africana suum.

Legacy parasite collections reveal species-specific population genetic patterns among three species of zoonotic schistosomes (Trematoda: Schistosomatidae)

Multi-host helminth systems are difficult to study at a population level due to inherent spatial and temporal sampling challenges. Consequently, our understanding of the factors affecting gene flow, genetic drift and effective population size is limited. Population genetic parameters (Ne, Θ, π) are necessary in understanding fundamental processes in host-parasite evolution such as co-evolutionary dynamics, spread of resistance alleles and local adaptation. This study used museum specimens collected over 20-years of three congeneric trematode (Schistosomatidae) species: Trichobilharzia querquedulae, T. physellae, and Trichobilharzia species A . All contribute to the worldwide zoonotic disease cercarial dermatitis (i.e. swimmers Itch). Populations of each species were sampled for two mitochondrial (cox1 and nad4) and one nuclear loci (ITS1) to estimate population genetic structure, genetic diversity, effective size and population history. Significant differences in these measures were revealed among the three congeners. Trichobilharzia querquedulae maintained a well-connected globally diverse metapopulation, with an effective size approximately three times that of the other two species, which were characterized by lower overall genetic diversity and greater population structure, mediated by the definitive duck host. We hypothesize that the species-specific patterns are due to distinctive ecological preferences and migratory behaviors of their respective definitive hosts. This study demonstrates the value of natural history collections to facilitate population genetic studies that would otherwise be infeasible. Applying population genetic data within this comparative congeneric framework allows us to tease apart particular aspects of host-parasite natural history and its influence on microevolutionary patterns within complex helminth systems, including contributions to zoonotic disease.

Evolution of inbreeding: a gaze into five Italian beef cattle breeds history

In the last decades, intensive selection programs have led to sustained increases of inbreeding in dairy cattle, a feature that might have adverse consequences on the viability and phenotypic performance of their offspring. This study aimed to determine the evolution of inbreeding of five Italian beef cattle breeds (Marchigiana, Chianina, Romagnola, Maremmana, and Podolica) during a period of almost 20 years (2002–2019). The estimates of Ho, He, Fhat2, and Fped averaged across years (2002–2019) in the studied breeds fluctuated between 0.340–0.401, 0.348–0.392, –0.121–0.072, and 0.000–0.068, respectively. Moreover, annual rates of increase of the estimated inbreeding coefficients have been very low (Fhat2 = 0.01–0.02%; Fped = 0.003–0.004%). The use of a high number of bulls combined with strategies implemented by the Association of Italian Beef Cattle Breeders ANABIC to minimize inbreeding might explain these results. Despite the fact that diversity and inbreeding have remained quite stable during the last two decades, we have detected a sustained decrease of the population effective size of these five breeds. Such results should be interpreted with caution due to the inherent difficulty of estimating Ne from SNPs data in a reliable manner.

Effective population size for culturally evolving traits

ABSTRACTPopulation size has long been considered an important driver of cultural diversity and complexity. Results from population genetics, however, demonstrate that in populations with complex demographic structure or mode of inheritance, it is not the census population size, N, but the effective size of a population, Ne, that determines important evolutionary parameters. Here, we examine the concept of effective population size for traits that evolve culturally, through processes of innovation and social learning. We use mathematical and computational modeling approaches to investigate how cultural Ne and levels of diversity depend on (1) the way traits are learned, (2) population connectedness, and (3) social network structure. We show that one-to-many and frequency-dependent transmission can temporally or permanently lower effective population size compared to census numbers. We caution that migration and cultural exchange can have counter-intuitive effects on Ne. Network density in random networks leaves Ne unchanged, scale-free networks tend to decrease and small-world networks tend to increase Ne compared to census numbers. For one-to-many transmission and different network structures, effective size and cultural diversity are closely associated. For connectedness, however, even small amounts of migration and cultural exchange result in high diversity independently of Ne. Our results highlight the importance of carefully defining effective population size for cultural systems and show that inferring Ne requires detailed knowledge about underlying cultural and demographic processes.AUTHOR SUMMARYHuman populations show immense cultural diversity and researchers have regarded population size as an important driver of cultural variation and complexity. Our approach is based on cultural evolutionary theory which applies ideas about evolution to understand how cultural traits change over time. We employ insights from population genetics about the “effective” size of a population (i.e. the size that matters for important evolutionary outcomes) to understand how and when larger populations can be expected to be more culturally diverse. Specifically, we provide a formal derivation for cultural effective population size and use mathematical and computational models to study how effective size and cultural diversity depend on (1) the way culture is transmitted, (2) levels of migration and cultural exchange, as well as (3) social network structure. Our results highlight the importance of effective sizes for cultural evolution and provide heuristics for empirical researchers to decide when census numbers could be used as proxies for the theoretically relevant effective numbers and when they should not.

Short-wavelength Reverberant Wave Systems for Enhanced Reservoir Computing

Machine learning (ML) has found widespread application over a broad range of important tasks. To enhance ML performance, researchers have investigated computational architectures whose physical implementations promise compactness, high-speed execution, physical robustness, and low energy cost. Here, we experimentally demonstrate an approach that uses the high sensitivity of reverberant short wavelength waves for physical realization and enhancement of computational power of a type of ML known as reservoir computing (RC). The potential computation power of RC systems increases with their effective size. We here exploit the intrinsic property of short wavelength reverberant wave sensitivity to perturbations to expand the effective size of the RC system by means of spatial and spectral perturbations. Working in the microwave regime, this scheme is tested on different ML tasks. Our results indicate the general applicability of reverberant wave-based implementations of RC and of our effective reservoir size expansion techniques.

Associations of social network structure with cognition and amygdala volume in multiple sclerosis: An exploratory investigation

Background: Humans are inherently social, biologically programmed to connect with others. Social connections are known to impact mental and physical health. Objective: The aim of this study was to test whether social network structure is linked to cognition, mood, fatigue, and regional brain volumes in persons with multiple sclerosis (MS). Methods: A questionnaire quantifying individual-level social network structure (size, density, effective size, and constraint), a comprehensive battery of neuropsychological tests, and magnetic resonance imaging (MRI) was administered to 51 persons with relapsing–remitting MS. Linear regressions assessed associations of network variables to cognition, depression, fatigue, and structural brain volumes. Results: Higher network density and constraint, indicating stronger connections among network members, were associated with worse language functions. Conversely, larger network effective size, a measure of non-redundant network members, was associated with better language functions. No relationships of network structure to depression or fatigue were found. Larger network size was related to larger amygdala volume. Conclusion: Findings suggest that social network structure is linked to language function and amygdala volume in persons with MS. Patients with close-knit networks showed worse language function than those with open networks. Longitudinal studies with larger samples are warranted to evaluate potential causal links between social network structure and MS-related cognitive impairment.