Characterization of the genetic relationship between the domains of sleep and circadian-related behaviors with substance use phenotypes

Sleep problems and substance use frequently cooccur. While substance use can often manifest as specific sleep deficits, genetic pleiotropy could also explain part of the relationship between sleep and substance use. Here we assess the genetic overlap between substance use behaviors and both sleep and circadian-related activity measures by deriving genetic clusters between these domains and testing processes of causality vs. horizontal pleiotropy using the largest publicly available genome-wide summary statistics of substance use behaviors (N= 79,729 - 632,802) and sleep/activity phenotypes/endophenotypes to date (N=85,502 - 449,734). We found 31 genetic correlations between substance use and sleep/activity measures after Bonferroni correction. Two specific genetic clusters explained our patterns of overlap. Genes associated with tobacco use severity (age of first regular tobacco use and smoking cessation) share overlap with elements of sleep health (sleep duration, sleep efficiency, and chronotype). Substance consumption (drinks per day and cigarettes per day) and problematic substance use behaviors (cannabis use disorder, opioid use disorder, and problematic alcohol use) clustered strongly with problematic measures of sleep (insomnia, self-reported short sleep duration, increased number of sleep episodes, increased sleep duration variability, diurnal inactivity) as well as measures of circadian-related activity (L5, M10, and sleep midpoint). Latent causal variable analyses determined that horizontal pleiotropy (rather than causality) underlies a majority of the associations between substance use and sleep/circadian related measures, except one plausible genetically causal relationship for opioid use disorder on self-reported long sleep duration. Results indeed show significant genetic overlap between substance use and sleep/circadian-related activity measures.

Archetypal Analysis for Population Genetics

The estimation of genetic clusters using genomic data has application from genome-wide association studies (GWAS) to demographic history to polygenic risk scores (PRS) and is expected to play an important role in the analyses of increasingly diverse, large-scale cohorts. However, existing methods are computationally-intensive, prohibitively so in the case of nationwide biobanks. Here we explore Archetypal Analysis as an efficient, unsupervised approach for identifying genetic clusters and for associating individuals with them. Such unsupervised approaches help avoid conflating socially constructed ethnic labels with genetic clusters by eliminating the need for exogenous training labels. We show that Archetypal Analysis yields similar cluster structure to existing unsupervised methods such as ADMIXTURE and provides interpretative advantages. More importantly, we show that since Archetypal Analysis can be used with lower-dimensional representations of genetic data, significant reductions in computational time and memory requirements are possible. When Archetypal Analysis is run in this fashion, it takes several orders of magnitude less compute time than the current standard, ADMIXTURE. Finally, we demonstrate uses ranging across datasets from humans to canids.

Diversity, Dispersal and Mode of Reproduction of Amanita exitialis in Southern China

Amanita exitialis is a poisonous mushroom and has caused many deaths in southern China. In this study, we collected 118 fruiting bodies of A. exitialis from seven different sites in Guangdong Province in southern China and investigated their genetic relationships using 14 polymorphic molecular markers. These 14 markers grouped the 118 fruiting bodies into 20 multilocus genotypes. Among these 20 genotypes, eight were each found only once while the remaining 12 were each represented by two to 54 fruiting bodies. Interestingly, among the 12 shared genotypes, four were shared between/among local populations that were separated by as far as over 80 km, a result consistent with secondary homothallic reproduction and long-distance spore dispersal. Despite the observed gene flow, significant genetic differentiations were found among the local populations, primarily due to the over-representation of certain genotypes within individual local populations. STRUCTURE analyses revealed that the 118 fruiting bodies belonged to three genetic clusters, consistent with divergence within this species in this geographic region. Interestingly, we found an excess of heterozygous individuals at both the local and the total sample level, suggesting potential inbreeding depression and heterozygous advantage in these populations of A. exitialis. We discuss the implications of our results for understanding the life cycle, dispersal, and evolution of this poisonous mushroom.

The History and Diversity of Rice Domestication as Resolved From 1464 Complete Plastid Genomes

The plastid is an essential organelle in autotrophic plant cells, descending from free-living cyanobacteria and acquired by early eukaryotic cells through endosymbiosis roughly one billion years ago. It contained a streamlined genome (plastome) that is uniparentally inherited and non-recombinant, which makes it an ideal tool for resolving the origin and diversity of plant species and populations. In the present study, a large dataset was amassed by de novo assembling plastomes from 295 common wild rice (Oryza rufipogon Griff.) and 1135 Asian cultivated rice (Oryza sativa L.) accessions, supplemented with 34 plastomes from other Oryza species. From this dataset, the phylogenetic relationships and biogeographic history of O. rufipogon and O. sativa were reconstructed. Our results revealed two major maternal lineages across the two species, which further diverged into nine well supported genetic clusters. Among them, the Or-wj-I/II/III and Or-wi-I/II genetic clusters were shared with cultivated (percentage for each cluster ranging 54.9%∼99.3%) and wild rice accessions. Molecular dating, phylogeographic analyses and reconstruction of population historical dynamics indicated an earlier origin of the Or-wj-I/II genetic clusters from East Asian with at least two population expansions, and later origins of other genetic clusters from multiple regions with one or more population expansions. These results supported a single origin of japonica rice (mainly in Or-wj-I/II) and multiple origins of indica rice (in all five clusters) for the history of rice domestication. The massive plastomic data set presented here provides an important resource for understanding the history and evolution of rice domestication as well as a genomic resources for use in future breeding and conservation efforts.

The Effects of Climate Change on Landscape Connectivity and Genetic Clusters in a Small Subtropical and Warm-Temperate Tree

Climate change is a great threat to global biodiversity and has resulted in serious ecological consequences. Although the potential effects of climate change on genetic diversity have recently received much research attention, little research has focused on the impacts of climate change on genetic connectivity and the relationship between climate stability and genetic divergence. Here, we combined population connectivity with genetic data to predict the impacts of future climate change on genetic connectivity. Coupled with climatic variables and genetic data, we used POPS software to create spatially explicit simulations and predict the dynamics in genetic clusters in response to climate changes. A generalized additive model was employed to test the correlation between climatic stability and genetic diversification. Our findings indicated that a reduction in species distribution due to severe climate change would lead to a substantial loss of genetic connectivity. More severe future climatic scenarios would likely cause greater loss of variability or more distinct homogenization in genetic variation of species. Relatively low interpolated genetic distances are generally associated with areas of greater losses in climatic suitability from the present to the future. The displacement of climatic genetic clusters will challenge species adaptation to future climate change because of the loss of fundamental evolutionary potential. The persistence capacity of plant species may be weakened in the face of future climate change.

Unexpected diversity in Central European Vespoidea (Hymenoptera, Mutillidae, Myrmosidae, Sapygidae, Scoliidae, Tiphiidae, Thynnidae, Vespidae), with description of two species of Smicromyrme Thomson, 1870

The present study presents DNA barcoding results for 134 species of Central European Vespoidea, families Mutillidae, Myrmosidae, Sapygidae, Scoliidae, Tiphiidae, Thynnidae, and Vespidae, including DNA barcodes for 100 of the 114 German species. DNA barcoding resulted in unexpected diversity in several families, each with two or more genetic clusters identified by Barcode Index Numbers (BINs). Smicromyrme burgeri Schmid-Egger, sp. nov. and S. langobardensis Schmid-Egger, sp. nov. are described as new from Germany and Italy, respectively. A neotype is designated for Smicromyrme rufipes (Fabricius, 1878). The results of DNA barcoding are discussed in respect to detecting cryptic species and refining species limits.

Broad-scale puma connectivity could restore genomic diversity to fine-scale coastal populations

Urbanization is decreasing wildlife habitat and connectivity worldwide, including for apex predators, such as the puma (Puma concolor). Puma populations along California's central and southern coastal habitats have experienced rapid fragmentation from development, leading to calls for demographic and genetic management. To address urgent conservation genomic concerns, we used double-digest restriction-site associated DNA (ddRAD) sequencing to analyze 16,285 genome-wide single-nucleotide polymorphisms (SNPs) from 401 broadly sampled pumas. Our analyses indicated support for 4–10 geographically nested, broad- to fine-scale genetic clusters. At the broadest scale, the 4 genetic clusters had high genetic diversity and exhibited low linkage disequilibrium, indicating pumas have retained statewide genomic diversity. However, multiple lines of evidence indicated substructure, including 10 fine-scale genetic clusters, some of which exhibited allelic fixation and linkage disequilibrium. Fragmented populations along the Southern Coast and Central Coast had particularly low genetic diversity and strong linkage disequilibrium, indicating genetic drift and close inbreeding. Our results demonstrate that genetically at-risk populations are typically nested within a broader-scale group of interconnected populations that collectively retains high genetic diversity and heterogeneous fixations. Thus, extant variation at the broader scale has potential to restore diversity to local populations if management actions can enhance vital gene flow and recombine locally sequestered genetic diversity. These state- and genome-wide results are critically important for science-based conservation and management practices. Our broad- and fine-scale population genomic analysis highlights the information that can be gained from population genomic studies aiming to provide guidance for fragmented population conservation management.

Polymorphism in populations of Corydalis subjenisseensis s. l. (Papaveraceae) in the south of the Yenisei Siberia

Corydalis subjenisseensis (Antipova) is a tuberous ephemeroid characterized by a high morphological diversity. During the research work genetic polymorphism of 7 populations Corydalis subjenisseensis s. l., growing in the southof the Yenisei Siberia were analyzed using ISSR markers. The amplification of genomic DNA with 8 ISSR primers yielded100 DNA amplicons of which 78 were polymorphic. The number of amplified DNA fragments, depending on the primer,varied from 9 (ISSR-17) to 21 (HB14). The maximum level of genetic variation was observed for Western Sayan populations growing in aspen and fir forests. The genetic differentiation among populations (Gst) was 0.2415, indicating a highlevel of differentiation. The similarity dendrogram performed in the TFPGA program shows a division into 2 groups: thefirst group includes the Krasnoyarsk and Khakass populations of C. subjenisseensis, the second group includes the Tanzybei populations, which are characterized by a high level of polymorphism. A similar structure is observed when buildingclusters using the Bayesian approach. 69 genotypes are divided into a maximum of 7 genetic clusters. Among the populations of the Tanzybei, individuals of presumably hybridogenic origin are found, grouped around two centers of “attraction”.

Genetic differentiation between inshore and offshore populations of northern shrimp (Pandalus borealis)

Many marine organisms have a permanent presence both inshore and offshore and spawn in multiple areas, yet their status as separate populations or stocks remain unclear. This is the situation for the northern shrimp (Pandalus borealis) around the Arctic Ocean, which in northern Norway represents an important income for a small-scale coastal fishery and a large-vessel offshore fleet. In Norwegian waters, we uncovered two distinct genetic clusters, viz. a Norwegian coastal and a Barents Sea cluster. Shrimps with a mixed heritage from the Norwegian coastal and the Barents Sea clusters, and genetically different from both, inhabit the fjords at the northernmost coast (Finnmark). Genetic structure between fjords did not display any general trend, and only the Varangerfjord in eastern Finnmark displayed significant genetic structure within the fjord. Shrimps in the Finnmark fjords differed in some degree from shrimps both in the adjacent Barents Sea and along the rest of the coast and should probably be considered a separate management unit.

Phylodynamic Pattern of Genetic Clusters, Paradigm Shift on Spatio-temporal Distribution of Clades, and Impact of Spike Glycoprotein Mutations of SARS-CoV-2 Isolates from India

Background: The COVID-19 pandemic is associated with high morbidity and mortality, with the emergence of numerous variants. The dynamics of SARS-CoV-2 with respect to clade distribution is uneven, unpredictable and fast changing. Aims: Retrieving the complete genomes of SARS-CoV-2 from India and subjecting them to analysis on phylogenetic clade diversity, Spike (S) protein mutations and their functional consequences such as immune escape features and impact on infectivity. Methods: Whole genome of SARS-CoV-2 isolates (n=4,326) deposited from India during the period from January 2020 to December 2020 is retrieved from GISAID and various analyses performed using in silico tools. Results: Notable clade dynamicity is observed indicating the emergence of diverse SARS-CoV-2 variants across the country. GR clade is predominant over the other clades and the distribution pattern of clades is uneven. D614G is the commonest and predominant mutation found among the S-protein followed by L54F. Mutation score prediction analyses reveal that there are several mutations in S-protein including the RBD and NTD regions that can influence the virulence of virus. Besides, mutations having immune escape features as well as impacting the immunogenicity and virulence through changes in the glycosylation patterns are identified. Conclusions: The study has revealed emergence of variants with shifting of clade dynamics within a year in India. It is shown uneven distribution of clades across the nation requiring timely deposition of SARS-CoV-2 sequences. Functional evaluation of mutations in S-protein reveals their significance in virulence, immune escape features and disease severity besides impacting therapeutics and prophylaxis.