Unveiling the underlying drivers of Phanerozoic marine diversification.

In investigating global patterns of biodiversity through deep time, many large-scale drivers of diversification have been proposed, both biotic and abiotic. However, few robust conclusions about these hypothesized effectors or their roles have been drawn. Here, we use a linear stochastic differential equation (SDE) framework to test for the presence of underlying drivers of diversification patterns before examining specific hypothesized drivers. Using a global dataset of observations of skeletonized marine fossils, we infer origination, extinction and sampling rates (collectively called fossil time series) throughout the Phanerozoic using a capture-mark-recapture approach. Using linear SDEs, we then compare models including and excluding hidden (i.e. unmeasured) drivers of these fossil time series. We find evidence of large-scale underlying drivers of marine Phanerozoic diversification rates and present quantitative characterizations of these. We then test whether changing global temperature, sea-level, marine sediment area or continental fragmentation could act as drivers of the fossil time series. We show that it is unlikely any of these four abiotic factors are the hidden drivers we identified, though there is evidence for correlative links between sediment area and origination/extinction rates. Our characterization of the hidden drivers of Phanerozoic diversification and sampling will aid in the search for their ultimate identities.

Age-dependent extinction and the neutral theory of biodiversity.

Red Queen (RQ) theory states that adaptation does not protect species from extinction because their competitors are continually adapting alongside them. RQ was founded on the apparent independence of extinction risk and fossil taxon age, but analytical developments have since demonstrated that age-dependent extinction is widespread, usually most intense among young species. Here, we develop ecological neutral theory as a general framework for modeling fossil species survivorship under incomplete sampling. We show that it provides an excellent fit to a high-resolution dataset of species durations for Paleozoic zooplankton and more broadly can account for age-dependent extinction seen throughout the fossil record. Unlike widely used alternative models, the neutral model has parameters with biological meaning, thereby generating testable hypotheses on changes in ancient ecosystems. The success of this approach suggests reinterpretations of mass extinctions and of scaling in eco-evolutionary systems. Intense extinction among young species does not necessarily refute RQ or require a special explanation but can instead be parsimoniously explained by neutral dynamics operating across species regardless of age.

Adaptive protein evolution through length variation of short tandem repeats in Arabidopsis.

Intrinsically disordered protein regions are of high importance for biotic and abiotic stress responses in plants. Tracts of identical amino acids accumulate in these regions and can vary in length over generations because of expansions and retractions of short tandem repeats at the genomic level. However, little attention has been paid to what extent length variation is shaped by natural selection. By environmental association analysis on 2514 length variable tracts in 770 whole-genome sequenced Arabidopsis thaliana, we show that length variation in glutamine and asparagine amino acid homopolymers, as well as in interaction hotspots, correlate with local bioclimatic habitat. We determined experimentally that the promoter activity of a light-stress gene depended on polyglutamine length variants in a disordered transcription factor. Our results show that length variations affect protein function and are likely adaptive. Length variants modulating protein function at a global genomic scale has implications for understanding protein evolution and eco-evolutionary biology.

Length variation in short tandem repeats affects gene expression in natural populations of Arabidopsis thaliana.

The genetic basis for the fine-tuned regulation of gene expression is complex and ultimately influences the phenotype and thus the local adaptation of natural populations. Short tandem repeats (STRs) consisting of repetitive DNA motifs have been shown to regulate gene expression. STRs are variable in length within a population and serve as a heritable, but semi-reversible, reservoir of standing genetic variation. For sessile organisms, such as plants, STRs could be of major importance in fine-tuning gene expression as a response to a shifting local environment. Here, we used a transcriptome dataset from natural accessions of Arabidopsis thaliana to investigate population-wide gene expression patterns in light of genome-wide STR variation. We empirically modeled gene expression as a response to the STR length within and around the gene and demonstrated that an association between gene expression and STR length variation is unequivocally present in the sampled population. To support our model, we explored the promoter activity in a transcriptional regulator involved in root hair formation and provided experimentally determined causality between coding sequence length variation and promoter activity. Our results support a general link between gene expression variation and STR length variation in A. thaliana.

Hydrology influences breeding time in the white-throated dipper.

BACKGROUND: Earlier breeding is one of the strongest responses to global change in birds and is a key factor determining reproductive success. In most studies of climate effects, the focus has been on large-scale environmental indices or temperature averaged over large geographical areas, neglecting that animals are affected by the local conditions in their home ranges. In riverine ecosystems, climate change is altering the flow regime, in addition to changes resulting from the increasing demand for renewable and clean hydropower. Together with increasing temperatures, this can lead to shifts in the time window available for successful breeding of birds associated with the riverine habitat. Here, we investigated specifically how the environmental conditions at the territory level influence timing of breeding in a passerine bird with an aquatic lifestyle, the white-throated dipper Cinclus cinclus. We relate daily river discharge and other important hydrological parameters, to a long-term dataset of breeding phenology (1978-2015) in a natural river system. RESULTS: Dippers bred earlier when winter river discharge and groundwater levels in the weeks prior to breeding were high, and when there was little snow in the catchment area. Breeding was also earlier at lower altitudes, although the effect dramatically declined over the period. This suggests that territories at higher altitudes had more open water in winter later in the study period, which permitted early breeding also here. Unexpectedly, the largest effect inducing earlier breeding time was territory river discharge during the winter months and not immediately prior to breeding. The territory river discharge also increased during the study period. CONCLUSIONS: The observed earlier breeding can thus be interpreted as a response to climate change. Measuring environmental variation at the scale of the territory thus provides detailed information about the interactions between organisms and the abiotic environment.

Alteration of (Frequency-Dependent) Fitness in Time-Shift Experiments Reveals Cryptic Coevolution and Uncoordinated Stasis in a Virtual Jurassic Park.

Among the major unresolved questions in ecosystem evolution are whether coevolving multispecies communities are dominated more by biotic or by abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile; these issues remain difficult to address experimentally. Digital evolution, a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve, is an excellent platform for investigating such topics in a rigorous experimental manner. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (Strong and Weak), along with unperturbed Control experiments. We performed several kinds of competition experiments using simplified versions of these communities to see whether long-term stability that was implied previously by ecological and phylogenetic metrics was also reflected in performance, namely, whether fitness was static over long periods of time. Results from Control and Weak treatment communities revealed almost completely transitive evolution, while Strong treatment communities showed higher incidences of temporal intransitivity, with pre-treatment ecotypes often able to displace some of their post-recovery successors. However, pre-treatment carryovers more often had lower fitness in mixed communities than in their own fully native conditions. Replacement and invasion experiments pitting single ecotypes against pre-treatment reference communities showed that many of the invading ecotypes could measurably alter the fitnesses of one or more residents, usually with depressive effects, and that the strength of these effects increased over time even in the most stable communities. However, invaders taken from Strong treatment communities often had little or no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and never affected an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.

Whole transcriptome analysis of the Atlantic cod vaccine response reveals subtle changes in adaptive immunity.

Atlantic cod has lost the Major Histocompatibility complex class II pathway - central to pathogen presentation, humoral response and immunity. Here, we investigate the immunological response of Atlantic cod subsequent to dip vaccination with Vibrioanguillarum bacterin using transcriptome sequencing. The experiment was conducted on siblings from an Atlantic cod family found to be highly susceptible towards vibriosis where vaccination has demonstrated improved pathogen resistance. Gene expression analyses at 2, 4, 21 and 42 days post vaccination revealed GO-term enrichment for muscle, neuron and metabolism-related pathways. In-depth characterization of immune-related GO terms demonstrated down-regulation of MHCI antigen presentation, C-type lectin receptor signaling and granulocyte activation over time. Phagocytosis, interferon-gamma signaling and negative regulation of innate immunity were increasingly up-regulated over time. Individual differentially expressed immune genes implies weak initiation of acute phase proteins with little or no inflammation. Furthermore, gene expression indicates presence of T-cells, NK-like cells, B-cells and monocytes/macrophages. Three MHCI transcripts were up-regulated with B2M and SEC61. Overall, we find no clear immune-related transcriptomic response which could be attributed to Atlantic cod's alternative immune system. However, we cannot rule out that this response is related to vaccination protocol/sampling strategy. Earlier functional studies demonstrate significant memory in Atlantic cod post dip vaccination and combined with our results indicate the presence of other adaptive immunity mechanisms. In particular, we suggest that further investigations should look into CD8+ memory T-cells, γδ T-cells, T-cell independent memory or memory induced through NK-like/other lymphoid cells locally in the mucosal lining for this particular vaccination strategy.

Disentangling the immune response and host-pathogen interactions in Francisella noatunensis infected Atlantic cod.

The genetic repertoire underlying teleost immunity has been shown to be highly variable. A rare example is Atlantic cod and its relatives Gadiformes that lacks a hallmark of vertebrate immunity: Major Histocompatibility Complex class II. No immunological studies so far have fully unraveled the functionality of this particular immune system. Through global transcriptomic profiling, we investigate the immune response and host-pathogen interaction of Atlantic cod infected with the facultative intracellular bacterium Francisella noatunensis. We find that Atlantic cod displays an overall classic innate immune response with inflammation, acute-phase proteins and cell recruitment through up-regulation of e.g. IL1B, fibrinogen, cathelicidin, hepcidin and several chemotactic cytokines such as the neutrophil attractants CXCL1 and CXCL8. In terms of adaptive immunity, we observe up-regulation of interferon gamma followed by up-regulation of several MHCI transcripts and genes related to antigen transport and loading. Finally, we find up-regulation of immunoglobulins and down-regulation of T-cell and NK-like cell markers. Our analyses also uncover some contradictory transcriptional findings such as up-regulation of anti-inflammatory IL10 as well as down-regulation of the NADPH oxidase complex and myeloperoxidase. This we interpret as the result of host-pathogen interactions where F. noatunensis modulates the immune response. In summary, our results suggest that Atlantic cod mounts a classic innate immune response as well as a neutrophil-driven response. In terms of adaptive immunity, both endogenous and exogenous antigens are being presented on MHCI and antibody production is likely enabled through direct B-cell stimulation with possible neutrophil help. Collectively, we have obtained novel insight in the orchestration of the Atlantic cod immune system and determined likely targets of F. noatunensis host-pathogen interactions.

Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms.

Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.

Common species link global ecosystems to climate change: dynamical evidence in the planktonic fossil record.

Common species shape the world around us, and changes in their commonness signify large-scale shifts in ecosystem structure and function. However, our understanding of long-term ecosystem response to environmental forcing in the deep past is centred on species richness, neglecting the disproportional impact of common species. Here, we use common and widespread species of planktonic foraminifera in deep-sea sediments to track changes in observed global occupancy (proportion of sampled sites at which a species is present and observed) through the turbulent climatic history of the last 65 Myr. Our approach is sensitive to relative changes in global abundance of the species set and robust to factors that bias richness estimators. Using three independent methods for detecting causality, we show that the observed global occupancy of planktonic foraminifera has been dynamically coupled to past oceanographic changes captured in deep-ocean temperature reconstructions. The causal inference does not imply a direct mechanism, but is consistent with an indirect, time-delayed causal linkage. Given the strong quantitative evidence that a dynamical coupling exists, we hypothesize that mixotrophy (symbiont hosting) may be an ecological factor linking the global abundance of planktonic foraminifera to long-term climate changes via the relative extent of oligotrophic oceans.

Do Not Divide Count Data with Count Data; A Story from Pollination Ecology with Implications Beyond.

Studies in ecology are often describing observed variations in a certain ecological phenomenon by use of environmental explanatory variables. A common problem is that the numerical nature of the ecological phenomenon does not always fit the assumptions underlying traditional statistical tests. A text book example comes from pollination ecology where flower visits are normally reported as frequencies; number of visits per flower per unit time. Using visitation frequencies in statistical analyses comes with two major caveats: the lack of knowledge on its error distribution and that it does not include all information found in the data; 10 flower visits in 20 flowers is treated the same as recording 100 visits in 200 flowers. We simulated datasets with various "flower visitation distributions" over various numbers of flowers observed (exposure) and with different types of effects inducing variation in the data. The different datasets were then analyzed first with the traditional approach using number of visits per flower and then by using count data models. The analysis of count data gave a much better chance of detecting effects than the traditionally used frequency approach. We conclude that if the data structure, statistical analyses and interpretations of results are mixed up, valuable information can be lost.

Ecological interactions on macroevolutionary time scales: clams and brachiopods are more than ships that pass in the night.

Competition among organisms has ecological and evolutionary consequences. However, whether the consequences of competition are manifested and measureable on macroevolutionary time scales is equivocal. Marine bivalves and brachiopods have overlapping niches such that competition for food and space may occur. Moreover, there is a long-standing debate over whether bivalves outcompeted brachiopods evolutionarily, because brachiopod diversity declined through time while bivalve diversity increased. To answer this question, we estimate the origination and extinction dynamics of fossil marine bivalve and brachiopod genera from the Ordovician through to the Recent while simultaneously accounting for incomplete sampling. Then, using stochastic differential equations, we assess statistical relationships among diversification and sampling dynamics of brachiopods and bivalves and five paleoenvironmental proxies. None of these potential environmental drivers had any detectable influence on brachiopod or bivalve diversification. In contrast, elevated bivalve extinction rates causally increased brachiopod origination rates, suggesting that bivalves have suppressed brachiopod evolution.

Identifying pathogenic processes by integrating microarray data with prior knowledge.

BACKGROUND: It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogenic pathways are still not completely understood. Often the set of genes or proteins identified as altered in genome-wide screens show a poor overlap with canonical disease pathways. These findings are difficult to interpret, yet crucial in order to improve the understanding of the molecular processes underlying the disease progression. We present a novel method for identifying groups of connected molecules from a set of differentially expressed genes. These groups represent functional modules sharing common cellular function and involve signaling and regulatory events. Specifically, our method makes use of Bayesian statistics to identify groups of co-regulated genes based on the microarray data, where external information about molecular interactions and connections are used as priors in the group assignments. Markov chain Monte Carlo sampling is used to search for the most reliable grouping. RESULTS: Simulation results showed that the method improved the ability of identifying correct groups compared to traditional clustering, especially for small sample sizes. Applied to a microarray heart failure dataset the method found one large cluster with several genes important for the structure of the extracellular matrix and a smaller group with many genes involved in carbohydrate metabolism. The method was also applied to a microarray dataset on melanoma cancer patients with or without metastasis, where the main cluster was dominated by genes related to keratinocyte differentiation. CONCLUSION: Our method found clusters overlapping with known pathogenic processes, but also pointed to new connections extending beyond the classical pathways.