Exploring COVID-related relationship extraction: Contrasting data sources and analyzing misinformation.

The COVID-19 pandemic presented an unparalleled challenge to global healthcare systems. A central issue revolves around the urgent need to swiftly amass critical biological and medical knowledge concerning the disease, its treatment, and containment. Remarkably, text data remains an underutilized resource in this context. In this paper, we delve into the extraction of COVID-related relations using transformer-based language models, including Bidirectional Encoder Representations from Transformers (BERT) and DistilBERT. Our analysis scrutinizes the performance of five language models, comparing information from both PubMed and Reddit, and assessing their ability to make novel predictions, including the detection of "misinformation." Key findings reveal that, despite inherent differences, both PubMed and Reddit data contain remarkably similar information, suggesting that Reddit can serve as a valuable resource for rapidly acquiring information during times of crisis. Furthermore, our results demonstrate that language models can unveil previously unseen entities and relations, a crucial aspect in identifying instances of misinformation.

Named Entity Recognition and Relation Detection for Biomedical Information Extraction.

The number of scientific publications in the literature is steadily growing, containing our knowledge in the biomedical, health, and clinical sciences. Since there is currently no automatic archiving of the obtained results, much of this information remains buried in textual details not readily available for further usage or analysis. For this reason, natural language processing (NLP) and text mining methods are used for information extraction from such publications. In this paper, we review practices for Named Entity Recognition (NER) and Relation Detection (RD), allowing, e.g., to identify interactions between proteins and drugs or genes and diseases. This information can be integrated into networks to summarize large-scale details on a particular biomedical or clinical problem, which is then amenable for easy data management and further analysis. Furthermore, we survey novel deep learning methods that have recently been introduced for such tasks.

Correction to: Ancient polymorphisms contribute to genome-wide variation by long-term balancing selection and divergent sorting in Boechera stricta.

Following publication of the original article [1], the authors reported that the Availability of data and materials section required updating. The updated text reads as follows.

Ancient polymorphisms contribute to genome-wide variation by long-term balancing selection and divergent sorting in Boechera stricta.

BACKGROUND: Genomic variation is widespread, and both neutral and selective processes can generate similar patterns in the genome. These processes are not mutually exclusive, so it is difficult to infer the evolutionary mechanisms that govern population and species divergence. Boechera stricta is a perennial relative of Arabidopsis thaliana native to largely undisturbed habitats with two geographic and ecologically divergent subspecies. Here, we delineate the evolutionary processes driving the genetic diversity and population differentiation in this species. RESULTS: Using whole-genome re-sequencing data from 517 B. stricta accessions, we identify four genetic groups that diverged around 30-180 thousand years ago, with long-term small effective population sizes and recent population expansion after the Last Glacial Maximum. We find three genomic regions with elevated nucleotide diversity, totaling about 10% of the genome. These three regions of elevated nucleotide diversity show excess of intermediate-frequency alleles, higher absolute divergence (dXY), and lower relative divergence (FST) than genomic background, and significant enrichment in immune-related genes, reflecting long-term balancing selection. Scattered across the genome, we also find regions with both high FST and dXY among the groups, termed FST-islands. Population genetic signatures indicate that FST-islands with elevated divergence, which have experienced directional selection, are derived from divergent sorting of ancient polymorphisms. CONCLUSIONS: Our results suggest that long-term balancing selection on disease resistance genes may have maintained ancestral haplotypes across different geographical lineages, and unequal sorting of balanced polymorphisms may have generated genomic regions with elevated divergence. This study highlights the importance of ancestral balanced polymorphisms as crucial components of genome-wide variation.

Publisher correction: Young inversion with multiple linked QTLs under selection in a hybrid zone.

In Fig. 5 of the version of this Article originally published, the final number on the x axes of each panel was incorrectly written as 1.5; it should have read 7.5. This has now been corrected in all versions of the Article.

Young inversion with multiple linked QTLs under selection in a hybrid zone.

Fixed chromosomal inversions can reduce gene flow and promote speciation in two ways: by suppressing recombination and by carrying locally favoured alleles at multiple loci. However, it is unknown whether favoured mutations slowly accumulate on older inversions or if young inversions spread because they capture pre-existing adaptive quantitative trait loci (QTLs). By genetic mapping, chromosome painting and genome sequencing, we have identified a major inversion controlling ecologically important traits in Boechera stricta. The inversion arose since the last glaciation and subsequently reached local high frequency in a hybrid speciation zone. Furthermore, the inversion shows signs of positive directional selection. To test whether the inversion could have captured existing, linked QTLs, we crossed standard, collinear haplotypes from the hybrid zone and found multiple linked phenology QTLs within the inversion region. These findings provide the first direct evidence that linked, locally adapted QTLs may be captured by young inversions during incipient speciation.

Microgeographic Patterns of Genetic Divergence and Adaptation across Environmental Gradients in Boechera stricta (Brassicaceae).

Abiotic and biotic conditions often vary continuously across the landscape, imposing divergent selection on local populations. We used a provenance trial approach to examine microgeographic variation in local adaptation in Boechera stricta (Brassicaceae), a perennial forb native to the Rocky Mountains. In montane ecosystems, environmental conditions change considerably over short spatial scales, such that neighboring populations can be subject to different selective pressures. Using accessions from southern (Colorado) and northern (Idaho) populations, we characterized spatial variation in genetic similarity via microsatellite markers. We then transplanted genotypes from multiple local populations into common gardens in both regions. Continuous variation in local adaptation emerged for several components of fitness. In Idaho, genotypes from warmer environments (low-elevation or south-facing sites) were poorly adapted to the north-facing garden. In high- and low-elevation Colorado gardens, susceptibility to insect herbivory increased with source elevation. In the high-elevation Colorado garden, germination success peaked for genotypes that evolved at elevations similar to that of the garden and decreased for genotypes from higher and lower elevations. We also found evidence for local maladaptation in survival and fecundity components of fitness in the low-elevation Colorado garden. This approach is a first step in predicting how global change could affect evolutionary dynamics.