Two decades of suspect evidence for adaptive molecular evolution - Negative selection confounding positive selection signals

There is a large literature in the last two decades affirming adaptive DNA sequences evolution between species. The main lines of evidence are from i) the McDonald-Kreitman (MK) test, which compares divergence and polymorphism data, and ii) the PAML test, which analyzes multi-species divergence data. Here, we apply these two tests concurrently on the genomic data of Drosophila and Arabidopsis. To our surprise, the >100 genes identified by the two tests do not overlap beyond random expectation. Because the non-concordance could be due to low powers leading to high false-negatives, we merge every 20 - 30 genes into a "supergene". At the supergene level, the power of detection is large but the calls still do not overlap. We rule out methodological reasons for the non-concordance. In particular, extensive simulations fail to find scenarios whereby positive selection can only be detected by either MK or PAML, but not both. Since molecular evolution is governed by positive and negative selection concurrently, a fundamental assumption for estimating one (say, positive selection) is that the other is constant. However, in a broad survey of primates, birds, Drosophila and Arabidopsis, we found that negative selection rarely stays constant for long in evolution. As a consequence, the variation in negative selection is often mis-construed as signals of positive selection. In conclusion, MK, PAML or any method that examines genomic sequence evolution has to explicitly address the variation in negative selection before estimating positive selection. In a companion study, we propose a possible path forward in two stages – first, by mapping out the changes in negative selection and then using this map to estimate positive selection. For now, the large literature on positive selection between species has to await the re-assessment.

Metabolic subgroups and cardiometabolic multimorbidity in the UK Biobank

Background: Ischemic heart disease (IHD), diabetes, cancer and dementia share features of age-associated metabolic dysfunction. We hypothesized that metabolic diversity explains the diversity of morbidity later in life. Methods: We analyzed data from the UK Biobank (N = 329,908). A self-organizing map (SOM, an artificial neural network) was trained with 51 metabolic traits adjusted for age and sex. The SOM analyses produced six subgroups that summarized the multi-variable metabolic diversity. The subgroup with the lowest adiposity and disease burden was chosen as the reference. Hazard ratios (HR) were modeled by Cox regression (P < 0.0001 unless otherwise indicated). Enrichment of multi-morbidity over random expectation was tested by permutation analysis. Results: The subgroup with the highest sex hormones was not associated with IHD (HR = 1.04, P = 0.14). The subgroup with high urinary excretion without kidney stress (HR = 1.24) and the subgroup with the highest apolipoprotein B and blood pressure (HR = 1.52) were associated with IHD. The subgroup with high adiposity, inflammation and kidney stress was associated with IHD (HR = 2.11), cancer (HR= 1.29), dementia (HR = 1.70) and mortality (HR = 2.12). The subgroup with high triglycerides and liver enzymes was at risk of diabetes (HR = 15.6). Paradoxical enrichment of multimorbidity in young individuals and in favorable subgroups was observed. Conclusions: These results support metabolic diversity as an explanation to diverging morbidity and demonstrate the potential value of population-based metabolic subgroups as public health targets for reducing aggregate burden of chronic diseases in ageing populations.

Insect biomass decline scaled to species diversity: General patterns derived from a hoverfly community

Reports of declines in biomass of flying insects have alarmed the world in recent years. However, how biomass declines reflect biodiversity loss is still an open question. Here, we analyze the abundance (19,604 individuals) of 162 hoverfly species (Diptera: Syrphidae), at six locations in German nature reserves in 1989 and 2014, and generalize the results with a model varying decline rates of common vs. rare species. We show isometric decline rates between total insect biomass and total hoverfly abundance and a scale-dependent decline in hoverfly species richness, ranging between −23% over the season to −82% at the daily level. We constructed a theoretical null model to explore how strong declines in total abundance translate to changing rank-abundance curves, species persistence, and diversity measures. Observed persistence rates were disproportionately lower than expected for species of intermediate abundance, while the rarest species showed decline and appearance rates consistent with random expectation. Our results suggest that large insect biomass declines are predictive of insect diversity declines. Under current threats, even the more common species are in peril, calling for a reevaluation of hazards and conservation strategies that traditionally target already rare and endangered species only.

F-Seq2: improving the feature density based peak caller with dynamic statistics

Genomic and epigenomic features are captured at a genome-wide level by using high-throughput sequencing (HTS) technologies. Peak calling delineates features identified in HTS experiments, such as open chromatin regions and transcription factor binding sites, by comparing the observed read distributions to a random expectation. Since its introduction, F-Seq has been widely used and shown to be the most sensitive and accurate peak caller for DNase I hypersensitive site (DNase-seq) data. However, the first release (F-Seq1) has two key limitations: lack of support for user-input control datasets, and poor test statistic reporting. These constrain its ability to capture systematic and experimental biases inherent to the background distributions in peak prediction, and to subsequently rank predicted peaks by confidence. To address these limitations, we present F-Seq2, which combines kernel density estimation and a dynamic ‘continuous’ Poisson test to account for local biases and accurately rank candidate peaks. The output of F-Seq2 is suitable for irreproducible discovery rate analysis as test statistics are calculated for individual candidate summits, allowing direct comparison of predictions across replicates. These improvements significantly boost the performance of F-Seq2 for ATAC-seq and ChIP-seq datasets, outperforming competing peak callers used by the ENCODE Consortium in terms of precision and recall.

The transcriptional aftermath in two independently formed hybrids of the opportunistic pathogen Candida orthopsilosis

Interspecific hybridization can drive evolutionary adaptation to novel environments. The Saccharomycotina clade of budding yeasts includes many hybrid lineages, and hybridization has been proposed as a source for new pathogenic species. Candida orthopsilosis is an emerging opportunistic pathogen for which most clinical isolates are hybrids, each derived from one of at least four independent crosses between the same two parental lineages. To gain insight on the transcriptomic aftermath of hybridization in these pathogens, we analyzed allele-specific gene expression in two independently formed hybrid strains, and in a homozygous strain representative of one parental lineage. Our results show that the effect of hybridization on overall gene expression is rather limited, affecting ~4% of the studied genes. However, we identified a larger effect in terms of imbalanced allelic expression, affecting ~9.5% of the heterozygous genes in the hybrids. Some of these altered genes have functions related to pathogenicity, including zinc transport and superoxide dismutase activities. Additionally, the number of shared genes with imbalanced expression in the two independently formed hybrids was higher than random expectation, suggesting selective retention. While it remains unclear whether the observed imbalanced genes play a role in virulence, our results suggest that differences in allele-specific expression may add an additional layer of phenotypic plasticity to traits related to virulence in C. orthopsilosis hybrids.ImportanceHow new pathogens emerge is an important question that remains largely unanswered. Some emerging yeast pathogens are hybrids originated through the crossing of two different species, but how hybridization contributes to a higher virulence is unclear. Here we show that hybrids selectively retain gene regulation plasticity inherited from the two parents, and that this plasticity affects genes involved in virulence.

Convergence within divergence: insights of wheat adaptation from Triticum population sequencing

Bread wheat expanded its habitats from a small core area of the Fertile Crescent to global environments within ∼10,000 years. Genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within genera Triticum and Aegilops, we identified composite introgression from these wild populations contributing 13%∼36% of the bread wheat genome, which tremendously increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaption to human selection showed 2- to 16-fold enrichment relative to random expectation in Triticum species despite their drastic differences in ploidy levels and growing zones, indicating the vital importance of adaptive constraints in the success of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on leveraging adaptation success across species for crop improvement.

Using community phylogenetics to assess phylogenetic structure in the Fitzcarrald region of Western Amazonia

ABSTRACT Here we explore the use of community phylogenetics as a tool to document patterns of biodiversity in the Fitzcarrald region, a remote area in Southwestern Amazonia. For these analyses, we subdivide the region into basin-wide assemblages encompassing the headwaters of four Amazonian tributaries (Urubamba, Yuruá, Purús and Las Piedras basins), and habitat types: river channels, terra firme (non-floodplain) streams, and floodplain lakes. We present a robust, well-documented collection of fishes from the region including 272 species collected from 132 field sites over 63 field days and four years, comprising the most extensive collection of fishes from this region to date. We conduct a preliminary community phylogenetic analysis based on this collection and recover results largely statistically indistinguishable from the random expectation, with only a few instances of phylogenetic structure. Based on these results, and of those published in other recent biogeographic studies, we conclude that the Fitzcarrald fish species pool accumulated over a period of several million years, plausibly as a result of dispersal from the larger species pool of Greater Amazonia.

Additive effects of connectivity provided by different habitat types drive plant assembly

How connectivity affects plant assemblages is a central issue in landscape ecology. So far, empirical studies have produced contradictory results, possibly because studies: (1) inaccurately assess connectivity by prioritizing the respective effect of the type of habitat on plant assemblages and (2) omit the range of possible plant responses to connectivity depending on dispersal vectors. We focused on three dominant habitat types in agricultural landscapes (woodland, grassland and cropland), and analysed the effect of connectivity on herbaceous plant assemblage similarity for three primary dispersal modes (animal-dispersed, wind-dispersed and unassisted). Using circuit theory, we measured connectivity provided by woodland, grassland and cropland habitats independently. The similarity of plant assemblages was evaluated relative to the random expectation based on the regional pool. Overall, plant assemblage similarity in woodlands and temporary grasslands was dependent on connectivity, but not in wheat croplands. Only animal-dispersed species responded to connectivity. The similarity of animal-dispersed assemblages in woodlands was increased by the connectivity provided by woodland habitats, but was reduced by cropland habitats, whereas in temporary grasslands, similarity was increased by the connectivity provided by cropland habitats. Our results suggest that animal-dispersed species supplement their dispersal pathways, thus improving our knowledge of plant assembly rules in fragmented landscapes.

Species turnover reveals hidden effects of decreasing nitrogen deposition in mountain hay meadows

Nitrogen (N) deposition is a major threat to biodiversity in many habitats. The recent introduction of cleaner technologies in Switzerland has led to a reduction in the emissions of nitrogen oxides, with a consequent decrease in N deposition. We examined different drivers of plant community change, that is, N deposition, climate warming, and land-use change, in Swiss mountain hay meadows, using data from the Swiss biodiversity monitoring program. We compared indicator values of species that disappeared from or colonized a site (species turnover) with the indicator values of randomly chosen species from the same site. While oligotrophic plant species were more likely to colonize, compared to random expectation, we found only weak shifts in plant community composition. In particular, the average nutrient value of plant communities remained stable over time (2003–2017). We found the largest deviations from random expectation in the nutrient values of colonizing species, suggesting that N deposition or other factors that change the nutrient content of soils were important drivers of the species composition change over the last 15 years in Swiss mountain hay meadows. In addition, we observed an overall replacement of species with lower indicator values for temperature with species with higher values. Apparently, the community effects of the replacement of eutrophic species with oligotrophic species was outweighed by climate warming. Our results add to the increasing evidence that plant communities in changing environments may be relatively stable regarding average species richness or average indicator values, but that this apparent stability is often accompanied by a marked turnover of species.

Species turnover reveals hidden effects of decreasing nitrogen deposition in mountain hay meadows

Nitrogen (N) deposition is a major threat to biodiversity in many habitats. The recent introduction of cleaner technologies in Switzerland has led to a reduction in the emissions of nitrogen oxides, with a consequent decrease in N deposition. We examined different drivers of plant community change, i.e. N deposition, climate warming, and land-use change, in Swiss mountain hay meadows, using data from the Swiss biodiversity monitoring program. We compared indicator values of species that disappeared from or colonized a site (species turnover) with the indicator values of randomly chosen species from the same site. While oligotrophic plant species were more likely to colonize, compared to random expectation, we found only weak shifts in plant community composition. In particular, the average nutrient value of plant communities remained stable over time (2003-2017). We found the largest deviations from random expectation in the nutrient values of colonizing species, suggesting that N deposition or other factors that change the nutrient content of soils were important drivers of the species composition change over the last 15 years in Swiss mountain hay meadows. In addition, we observed an overall replacement of species with lower indicator values for temperature with species with higher values. Apparently, the community effects of the replacement of eutrophic species with oligotrophic species was outweighed by climate warming. Our results add to the increasing evidence that plant communities in changing environments may be relatively stable regarding average species richness or average indicator values, but that this apparent stability is often accompanied by a marked turnover of species.