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Spain has been one of the main global pandemic epicenters for coronavirus disease 2019 (COVID-19). Here, we analyzed >41 000 genomes (including >26 000 high-quality (HQ) genomes) downloaded from the GISAID repository, including 1 245 (922 HQ) sampled in Spain. The aim of this study was to investigate genome variation of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and reconstruct phylogeographic and transmission patterns in Spain. Phylogeographic analysis suggested at least 34 independent introductions of SARS-CoV-2 to Spain at the beginning of the outbreak. Six lineages spread very successfully in the country, probably favored by super-spreaders, namely, A2a4 (7.8%), A2a5 (38.4%), A2a10 (2.8%), B3a (30.1%), and B9 (8.7%), which accounted for 87.9% of all genomes in the Spanish database. One distinct feature of the Spanish SARS-CoV-2 genomes was the higher frequency of B lineages (39.3%, mainly B3a+B9) than found in any other European country. While B3a, B9, (and an important sub-lineage of A2a5, namely, A2a5c) most likely originated in Spain, the other three haplogroups were imported from other European locations. The B3a strain may have originated in the Basque Country from a B3 ancestor of uncertain geographic origin, whereas B9 likely emerged in Madrid. The time of the most recent common ancestor (TMRCA) of SARS-CoV-2 suggested that the first coronavirus entered the country around 11 February 2020, as estimated from the TMRCA of B3a, the first lineage detected in the country. Moreover, earlier claims that the D614G mutation is associated to higher transmissibility is not consistent with the very high prevalence of COVID-19 in Spain when compared to other countries with lower disease incidence but much higher frequency of this mutation (56.4% in Spain vs. 82.4% in rest of Europe). Instead, the data support a major role of genetic drift in modeling the micro-geographic stratification of virus strains across the country as well as the role of SARS-CoV-2 super-spreaders.
The interpretation of patterns of biodiversity requires the disentanglement of geographical and environmental variables. Disjunct alpine communities are geographically isolated from one another but experience similar environmental impacts. Isolated homogenous habitats may promote speciation but constrain functional trait variation. In this study, we examined the hypothesis that dispersal limitation promotes taxonomic divergence, whereas habitat similarity in alpine mountains leads to functional convergence. We performed standardized field investigation to sample non-volant small mammals from 18 prominent alpine sites in the Three Parallel Rivers area. We estimated indices quantifying taxonomic and functional alpha- and beta-diversity, as well as beta-diversity components. We then assessed the respective importance of geographical and environmental predictors in explaining taxonomic and functional compositions. No evidence was found to show that species were more functionally similar than expected in local assemblages. However, the taxonomic turnover components were higher than functional ones (0.471±0.230 vs. 0.243±0.215), with nestedness components showing the opposite pattern (0.063±0.054 vs. 0.269±0.225). This indicated that differences in taxonomic compositions between sites occurred from replacement of functionally similar species. Geographical barriers were the key factor influencing both taxonomic total dissimilarity and turnover components, whereas functional beta-diversity was primarily explained by climatic factors such as minimum temperature of the coldest month. Our findings provide empirical evidence that taxonomic and functional diversity patterns can be independently driven by different ecological processes. Our results point to the importance of clarifying different components of beta-diversity to understand the underlying mechanisms of community assembly. These results also shed light on the assembly rules and ecological processes of terrestrial mammal communities in extreme environments.
Accumulating studies have been conducted to identify risk genes and relevant biological mechanisms underlying major depressive disorder (MDD), among which transcriptomic analyses in brain regions engaged in cognitive and emotional processes, e.g., dorsolateral prefrontal cortex (DLPFC), have provided essential insights. Based on three independent DLPFC RNA-seq datasets including 79 MDD patients and 75 healthy controls, we performed differential expression analyses using two alternative approaches for cross-validation. We also conducted transcriptomic analyses in mice underwent chronic variable stress (CVS) and chronic social defeat stress (CSDS) respectively. We identified twelve differentially-expressed genes (DEGs) through both analytical methods in MDD patients, majority of which were also dysregulated in stressed mice. Notably, our analyses identified the immediate early gene FOS (Fos proto-oncogene) whose mRNA level was significantly decreased in both MDD patients as well as mice exposed to CVS, and the mice susceptible to CSDS exhibited a greater reduction of Fos expression compared with resilient mice, suggesting potentially key roles of this gene in the pathogenesis of MDD related to stress exposure. Altered transcriptomes in the DLPFC of MDD patients might (partially) be a result of stress exposure, supporting that stress is a primary risk factor for MDD.