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Biodiversity loss threatens ecosystems and human well-being, making accurate, large-scale monitoring crucial. Environmental DNA (eDNA) has enabled species detection from substrates such as water, without the need for direct observation. Lately, airborne eDNA has been showing promise for tracking organisms from insects to mammals in terrestrial ecosystems. Conventional biodiversity assessments are often labor-intensive and limited in scope, leaving gaps in our understanding of ecosystem response to environmental change. Here, we demonstrate that airborne eDNA can detect organisms across the tree of life, quantify changes in abundance congruent with traditional monitoring, and reveal land-use induced regional decline of diversity in a northern boreal ecosystem over more than three decades. By analyzing 34 years of archived aerosol filters, we reconstruct weekly temporal relative abundance data for more than 2700 genera using non-targeted methods. This study provides unified, ecosystem-scale biodiversity surveillance spanning multiple decades, with data collected at weekly intervals on both the individual species and community level. Previously, large scale analyses of ecosystem changes, targeting all types of organisms, has been prohibitively expensive and difficult to attempt. Here, we present a way of holistically doing this type of analysis in a single framework.

Bryophytes constitute a diverse plant group with important roles in ecosystem functioning, in particular in arctic and subarctic environments. As they are physiologically strongly dependent on climatic conditions bryophytes could serve as indicators of ongoing climatic change. Their spores are generally dispersed by wind, and because of contrasting phenologies among species, the composition of the spore cloud changes throughout the year. Unlike vascular plant pollen, airborne bryophyte spores have few specific morphological characteristics, and therefore spore dispersal phenology has, until now, relied on highly laborious in situ observations.

Here, we report on multi-decadal shifts in the phenology of spore dispersal in 16 bryophyte taxa using a unique 35-year time series of environmental DNA (eDNA) data collected in Kiruna, northern Sweden. We used shotgun sequencing data from air filters and matched reads to all major organism groups, of which a high proportion were bryophyte reads.

We found consistent shifts in bryophyte phenology, such that most bryophyte taxa advanced their (i) start of season with 4 weeks on average, and (ii) mid-season with 6 weeks, ranging between 4 and 7 weeks. Changes at the season end were less consistent across the 16 bryophyte taxa, although seven of them showed phenological delays over time. Rising temperatures during the third and fourth quarters of the year preceding spore release were correlated with phenological shifts, suggesting that bryophytes may enter hibernation at later stages of sporophyte development, with warmer conditions promoting more advanced sporophyte maturation by the onset of spring. As a consequence of the phenological shifts, seasons during which spores were observed became several weeks longer over the studied time period for most taxa.

Synthesis: We conclude that the phenological shifts in our study suggest strong perturbations in bryophyte phenology, consistent with ongoing climate change. Our results demonstrate that studying airborne particles using eDNA methodology is a valuable complement to other monitoring methods, not the least in bryophytes and other less well-surveyed taxa.

Crop pests and diseases increasingly challenge the global food system. To prepare for and detect outbreaks, surveillance plays an important role. Traditional monitoring methods are often organism-specific, making large-scale monitoring of crop pathogens and pests impractical. We here investigate the potential for using shotgun sequencing of airborne eDNA for large-scale surveillance of crop pathogens and pests. We show that it is possible to detect DNA from all types of organisms in air, and that DNA can be classified down to species level. However, the accuracy of the identification is highly dependent on the quality of reference genomes of both the pathogens or pests, and their close relatives present in the region. Finally, we find that observed degree of crop damages correlate with amount of DNA from crop pathogens and pests in air, showing the promise of this approach for surveillance of all types of crop pathogens and pests.

Mammalian DNA folds into 3D structures that facilitate and regulate genetic processes such as transcription, DNA repair, and epigenetics. Several insights derive from chromosome capture methods, such as Hi-C, which allow researchers to construct contact maps depicting 3D interactions among all DNA segment pairs. These maps show a complex cross-scale organization spanning megabase-pair compartments to short-ranged DNA loops. To better understand the organizing principles, several groups analyzed Hi-C data assuming a Russian-doll-like nested hierarchy where DNA regions of similar sizes merge into larger and larger structures. Apart from being a simple and appealing description, this model explains, e.g., the omnipresent chequerboard pattern seen in Hi-C maps, known as A/B compartments, and foreshadows the co-localization of some functionally similar DNA regions. However, while successful, this model is incompatible with the two competing mechanisms that seem to shape a significant part of the chromosomes' 3D organization: loop extrusion and phase separation. This paper aims to map out the chromosome's actual folding hierarchy from empirical data. To this end, we take advantage of Hi-C experiments and treat the measured DNA-DNA interactions as a weighted network. From such a network, we extract 3D communities using the generalized Louvain algorithm. This algorithm has a resolution parameter that allows us to scan seamlessly through the community size spectrum, from A/B compartments to topologically associated domains (TADs). By constructing a hierarchical tree connecting these communities, we find that chromosomes are more complex than a perfect hierarchy. Analyzing how communities nest relative to a simple folding model, we found that chromosomes exhibit a significant portion of nested and non-nested community pairs alongside considerable randomness. In addition, by examining nesting and chromatin types, we discovered that nested parts are often associated with active chromatin. These results highlight that cross-scale relationships will be essential components in models aiming to reach a deep understanding of the causal mechanisms of chromosome folding.

The genomes of immortalized cell lines (and cancer cells) are characterized by multiple types of aberrations, ranging from single nucleotide polymorphisms (SNPs) to structural rearrangements that have accumulated over time. Consequently, it is difficult to estimate the relative impact of different aberrations, the order of events, and which gene functions were under selective pressure at the early stage towards cellular immortalization. Here, we have established novel cell cultures derived from Drosophila melanogaster embryos that were sampled at multiple time points over a one-year period. Using short-read DNA sequencing, we show that copy-number gain in preferentially stress-related genes were acquired in a dominant fraction of cells in 300-days old cultures. Furthermore, transposable elements were active in cells of all cultures. Only a few (<1%) SNPs could be followed over time, and these showed no trend to increase or decrease. We conclude that the early cellular responses of a novel culture comprise sequence duplication and transposable element activity. During immortalization, positive selection first occurs on genes that are related to stress response before shifting to genes that are related to growth.

Background: Surface raw water used as a source for drinking water production is a critical resource, sensitive to contamination. We conducted a study on Swedish raw water sources, aiming to identify mutually co-occurring metacommunities of bacteria, and environmental factors driving such patterns.

Methods: The water sources were different regarding nutrient composition, water quality, and climate characteristics, and displayed various degrees of anthropogenic impact. Water inlet samples were collected at six drinking water treatment plants over 3 years, totaling 230 samples. The bacterial communities of DNA sequenced samples (n = 175), obtained by 16S metabarcoding, were analyzed using a joint model for taxa abundance.

Results: Two major groups of well-defined metacommunities of microorganisms were identified, in addition to a third, less distinct, and taxonomically more diverse group. These three metacommunities showed various associations to the measured environmental data. Predictions for the well-defined metacommunities revealed differing sets of favored metabolic pathways and life strategies. In one community, taxa with methanogenic metabolism were common, while a second community was dominated by taxa with carbohydrate and lipid-focused metabolism.

Conclusion: The identification of ubiquitous persistent co-occurring bacterial metacommunities in freshwater habitats could potentially facilitate microbial source tracking analysis of contamination issues in freshwater sources.

Mammalian DNA folds into 3D structures that facilitate and regulate genetic processes such as transcription, DNA repair, and epigenetics. Several insights derive from chromosome capture methods, such as Hi-C, which allow researchers to construct contact maps depicting 3D interactions among all DNA segment pairs. These maps show a complex cross-scale organization spanning megabase-pair compartments to short-ranged DNA loops. To better understand the organizing principles, several groups analyzed Hi-C data assuming a Russian-doll-like nested hierarchy where DNA regions of similar sizes merge into larger and larger structures. Apart from being a simple and appealing description, this model explains, e.g., the omnipresent chequerboard pattern seen in Hi-C maps, known as A/B compartments, and foreshadows the co-localization of some functionally similar DNA regions. However, while successful, this model is incompatible with the two competing mechanisms that seem to shape a significant part of the chromosomes’ 3D organization: loop extrusion and phase separation. This paper aims to map out the chromosome’s actual folding hierarchy from empirical data. To this end, we take advantage of Hi-C experiments and treat the measured DNA-DNA interactions as a weighted network. From such a network, we extract 3D communities using the generalized Louvain algorithm. This algorithm has a resolution parameter that allows us to scan seamlessly through the community size spectrum, from A/B compartments to topologically associated domains (TADs). By constructing a hierarchical tree connecting these communities, we find that chromosomes are more complex than a perfect hierarchy. Analyzing how communities nest relative to a simple folding model, we found that chromosomes exhibit a significant portion of nested and non-nested community pairs alongside considerable randomness. In addition, by examining nesting and chromatin types, we discovered that nested parts are often associated with active chromatin. These results highlight that crossscale relationships will be essential components in models aiming to reach a deep understanding of the causal mechanisms of chromosome folding.

Background: Immortalized cell lines are widely used model systems whose genomes are often highly rearranged and polyploid. However, their genome structure is seldom deciphered and is thus not accounted for during analyses. We therefore used linked short- and long-read sequencing to perform haplotype-level reconstruction of the genome of a Drosophila melanogaster cell line (S2-DRSC) with a complex genome structure.

Results: Using a custom implementation (that is designed to use ultra-long reads in complex genomes with nested rearrangements) to call structural variants (SVs), we found that the most common SV was repetitive sequence insertion or deletion (> 80% of SVs), with Gypsy retrotransposon insertions dominating. The second most common SV was local sequence duplication. SNPs and other SVs were rarer, but several large chromosomal translocations and mitochondrial genome insertions were observed. Haplotypes were highly similar at the nucleotide level but structurally very different. Insertion SVs existed at various haplotype frequencies and were unlinked on chromosomes, demonstrating that haplotypes have different structures and suggesting the existence of a mechanism that allows SVs to propagate across haplotypes. Finally, using public short-read data, we found that transposable element insertions and local duplications are common in other D. melanogaster cell lines.

Conclusions: The S2-DRSC cell line evolved through retrotransposon activity and vast local sequence duplications, that we hypothesize were the products of DNA re-replication events. Additionally, mutations can propagate across haplotypes (possibly explained by mitotic recombination), which enables fine-tuning of mutational impact and prevents accumulation of deleterious events, an inherent problem of clonal reproduction. We conclude that traditional linear homozygous genome representation conceals the complexity when dealing with rearranged and heterozygous clonal cells.

The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads.

Several processes in the cell, such as gene regulation, start when key proteins recognize and bind to short DNA sequences. However, as these sequences can be hundreds of million times shorter than the genome, they are hard to find by simple diffusion: diffusion-limited association rates may underestimate in vitro measurements up to several orders of magnitude. Moreover, the rates increase if the DNA is coiled rather than straight. Here we model how this works in vivo in mammalian cells. We use chromatin-chromatin contact data from Hi-C experiments to map the protein target-search onto a network problem. The nodes represent DNA segments and the weight of the links are proportional to measured contact probabilities. We then put forward a diffusion-reaction equation for the density of searching protein that allows us to calculate the association rates across the genome analytically. For segments where the rates are high, we find that they are enriched with active gene starts and have high RNA expression levels. This paper suggests that the DNA's 3D conformation is important for protein search times in vivo and offers a method to interpret protein-binding profiles in eukaryotes that cannot be explained by the DNA sequence itself.