Genetic structure of Eurasian beaver in Romania: insights after two decades from the reintroduction

Once exploited for fur, meat, and extracting the yellowish exudate called castoreum, the Eurasian beaver disappeared from Romania during the eighteenth century. After, the reintroductions carried out two decades ago are currently thriving in the Danube River basin. Using nine nSSR markers, we analysed samples from 98 individuals, and we found no genetic substructure, suggesting high dispersal and gene flow capabilities. The stepwise mutation model (SMM) indicated the existence of a recent genetic bottleneck, though the Eurasian beaver retains high levels of genetic diversity and population growth facilitated variation in nSSR loci. A fine-scale spatial correlation in females was detected, contrasting with males’ dispersal on longer distances. While the movement and establishment of individuals’ new territories were made under natural predation pressure, the mix following natural expansion improved the fitness and could contribute to a higher genetic diversity than the source population. With any reintroduction, a focus on capturing individuals from various geographic origins, as well as securing many and suitable founding individuals (adults, subadults, and juveniles) with mixed origins, could secure the post-genetic bottleneck recovery and higher genetic diversity. Beyond this conservation success, future management strategies should consider building a National Action Plan (NAP) for the species, including a permanent genetic monitoring programme for Eurasian beaver.

A Deeper Insight into Evolutionary Patterns and Phylogenetic History of ASFV Epidemics in Sardinia (Italy) through Extensive Genomic Sequencing

African swine fever virus (ASFV) is the etiological agent of the devastating disease African swine fever (ASF), for which there is currently no licensed vaccine or treatment available. ASF is defined as one of the most serious animal diseases identified to date, due to its global spread in regions of Africa, Europe and Asia, causing massive economic losses. On the Italian island of Sardinia, the disease has been endemic since 1978, although the last control measures put in place achieved a significant reduction in ASF, and the virus has been absent from circulation since April 2019. Like many large DNA viruses, ASFV mutates at a relatively slow rate. However, the limited availability of whole-genome sequences from spatial-localized outbreaks makes it difficult to explore the small-scale genetic structure of these ASFV outbreaks. It is also unclear if the genetic variability within outbreaks can be captured in a handful of sequences, or if larger sequencing efforts can improve phylogenetic reconstruction and evolutionary or epidemiological inference. The aim of this study was to investigate the phylogenetic patterns of ASFV outbreaks between 1978 and 2018 in Sardinia, in order to characterize the epidemiological dynamics of the viral strains circulating in this Mediterranean island. To reach this goal, 58 new whole genomes of ASFV isolates were obtained, which represents the largest ASFV whole-genome sequencing effort to date. We provided a complete description of the genomic diversity of ASFV in terms of nucleotide mutations and small and large indels among the isolates collected during the outbreaks. The new sequences capture more than twice the genomic and phylogenetic diversity of all the previously published Sardinian sequences. The extra genomic diversity increases the resolution of the phylogenetic reconstruction, enabling us to dissect, for the first time, the genetic substructure of the outbreak. We found multiple ASFV subclusters within the phylogeny of the Sardinian epidemic, some of which coexisted in space and time.

Neural ADMIXTURE: rapid population clustering with autoencoders

Characterizing the genetic substructure of large cohorts has become increasingly important as genetic association and prediction studies are extended to massive, increasingly diverse, biobanks. ADMIXTURE and STRUCTURE are widely used unsupervised clustering algorithms for characterizing such ancestral genetic structure. These methods decompose individual genomes into fractional cluster assignments with each cluster representing a vector of DNA marker frequencies. The assignments, and clusters, provide an interpretable representation for geneticists to describe population substructure at the sample level. However, with the rapidly increasing size of population biobanks and the growing numbers of variants genotyped (or sequenced) per sample, such traditional methods become computationally intractable. Furthermore, multiple runs with different hyperparameters are required to properly depict the population clustering using these traditional methods, increasing the computational burden. This can lead to days of compute. In this work we present Neural ADMIXTURE, a neural network autoencoder that follows the same modeling assumptions as ADMIXTURE, providing similar (or better) clustering, while reducing the compute time by orders of magnitude. In addition, this network can include multiple outputs, providing the equivalent results as running the original ADMIXTURE algorithm many times with different numbers of clusters. These models can also be stored, allowing later cluster assignment to be performed with a linear computational time.

Genetic substructure and complex demographic history of South African Bantu speakers

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.

Genome sequencing and morphometric analysis of alpine bumblebees experiencing climate change reveal ongoing phenotypic shifts and a lack of population structure

ABSTRACTPopulations of the bumblebees Bombus sylvicola and Bombus balteatus in Colorado have experienced decreases in tongue length, a trait important for plant-pollinator mutualisms, in the last six decades. It is hypothesized that this reflects selection exerted by changes in floral composition under climate change. Here we combine extensive morphometric and population genomic data to investigate population structure, whether morphological change is ongoing, and the genetic basis of morphological change. We generate highly-contiguous genome assemblies of both species using long-read sequencing. We then perform whole-genome sequencing and morphometric measurements of 580 samples of these species from seven high-altitude localities. Out of 281 samples originally identified as B. sylvicola, 67 formed a separate genetic cluster comprising the newly-discovered cryptic species B. incognitus. However, there is very little additional genetic substructure, suggesting that gene flow occurs readily between mountains. We find a significant decrease in tongue length between bees collected between 2008-2014 and in 2017, indicating that morphological shifts are ongoing. We did not discover any genetic associations with tongue length, but a SNP related to production of a proteolytic digestive enzyme is implicated in body size variation. We identify evidence of covariance between kinship and both tongue length and body size, which is suggestive of a genetic component of these traits, although it is not possible to rule out shared environmental effects between colonies. Our results provide evidence for ongoing evolution of a morphological trait important for pollination and indicate that this trait likely has a complex genetic and environmental basis.

Integrating Linguistics, Social Structure, and Geography to Model Genetic Diversity within India

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification. While geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a dataset of 891 individuals from 90 well-defined groups. Bringing together geography, genetics and demographic factors, we developed COGG (Correlation Optimization of Genetics and Geodemographics) to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure using a ridge leverage score statistic. Integrating data from India with a dataset of additional 1,323 individuals from 50 Eurasian populations we find that Indo-European and Dravidian speakers of India show shared genetic drift with Europeans, whereas the Tibeto-Burman speaking tribal groups have maximum shared genetic drift with East Asians.

Genetic-substructure and complex demographic history of South African Bantu speakers

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ∼400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.

Genetic Characterization of the “Chusca Lojana”, a Creole Goat Reared in Ecuador, and Its Relationship with Other Goat Breeds

The largest population of goats (62%) in Ecuador is in the dry forest region in the south of the country. A Creole goat, named “Chusca Lojana”, has adapted to the dry forest region where environmental conditions are warm-dry, with sparse vegetation. Knowledge of the genetic information of the Creole goat is important to determine intra-racial diversity, the degree of genetic distance among other breeds of goats, and the possible substructure of the population, which is valuable for the conservation of such a species’ genetic resources. A total of 145 samples of the Creole goat was taken from the four biotypes previously identified. Genetic analyses were performed using 38 microsatellites recommended for studies of goat genetic diversity (FAO-ISAG). The results of within-breed genetic diversity showed a mean number of alleles per locus (MNA) of 8, an effective number of alleles (Ae) of 4.3, an expected heterozygosity (He) of 0.71, an observed heterozygosity (Ho) of 0.63, polymorphic information content (PIC) of 0.67, and an FIS value of 0.11. Between-breed genetic diversity among 43 goat populations (native of Spain, American Creole, Europeans, and Africans) showed the following values: FIS = 0.087, FIT = 0.176, and FST = 0.098. Regarding the analysis of the population structure, the results showed that the Creole Chusca Lojana goat population is homogeneous and no genetic separation was observed between the different biotypes (FST = 0.0073). In conclusion, the Chusca Lojana goat has a high genetic diversity, without exhibiting a genetic substructure. Therefore, it should be considered as a distinct population because crossbreeding with other breeds was not detected.

Ancient genome-wide DNA from France highlights the complexity of interactions between Mesolithic hunter-gatherers and Neolithic farmers

Starting from 12,000 years ago in the Middle East, the Neolithic lifestyle spread across Europe via separate continental and Mediterranean routes. Genomes from early European farmers have shown a clear Near Eastern/Anatolian genetic affinity with limited contribution from hunter-gatherers. However, no genomic data are available from modern-day France, where both routes converged, as evidenced by a mosaic cultural pattern. Here, we present genome-wide data from 101 individuals from 12 sites covering today’s France and Germany from the Mesolithic (N = 3) to the Neolithic (N = 98) (7000–3000 BCE). Using the genetic substructure observed in European hunter-gatherers, we characterize diverse patterns of admixture in different regions, consistent with both routes of expansion. Early western European farmers show a higher proportion of distinctly western hunter-gatherer ancestry compared to central/southeastern farmers. Our data highlight the complexity of the biological interactions during the Neolithic expansion by revealing major regional variations.