Journal of Evolutionary Biology最新文献

Statistical analysis and data visualization are integral parts of science communication. One of the major issues in current data analysis practice is an overdependency on-and misuse of-p-values. Researchers have been advocating for the estimation and reporting of effect sizes for quantitative research to enhance the clarity and effectiveness of data analysis. Reporting effect sizes in scientific publications has until now been mainly limited to numeric tables, even though effect size plotting is a more effective means of communicating results. We have developed the Durga R package for estimating and plotting effect sizes for paired and unpaired group comparisons. Durga allows users to estimate unstandardized and standardized effect sizes and bootstrapped confidence intervals of the effect sizes. The central functionality of Durga is to combine effect size visualizations with traditional plotting methods. Durga is a powerful statistical and data visualization package that is easy to use, providing the flexibility to estimate effect sizes of paired and unpaired data using different statistical methods. Durga provides a plethora of options for plotting effect size, which allows users to plot data in the most informative and aesthetic way. Here, we introduce the package and its various functions. We further describe a workflow for estimating and plotting effect sizes using example data sets.

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

In response to environmental and human-imposed selective pressures, agroecosystem pests frequently undergo rapid evolution, with some species having a remarkable capacity to rapidly develop pesticide resistance. Temporal sampling of genomic data can comprehensively capture such adaptive changes over time, for example, by elucidating allele frequency shifts in pesticide resistance loci in response to different pesticides. Here, we leveraged museum specimens spanning over a century of collections to generate temporal contrasts between pre- and post-insecticide populations of an agricultural pest moth, Helicoverpa armigera. We used targeted exon sequencing of 254 samples collected across Australia from the pre-1950s (prior to insecticide introduction) to the 1990s, encompassing decades of changing insecticide use. Our sequencing approach focused on genes that are known to be involved in insecticide resistance, environmental sensation, and stress tolerance. We found an overall lack of spatial and temporal population structure change across Australia. In some decades (e.g., 1960s and 1970s), we found a moderate reduction of genetic diversity, implying stochasticity in evolutionary trajectories due to genetic drift. Temporal genome scans showed extensive evidence of selection following insecticide use, although the majority of selected variants were low impact. Finally, alternating trajectories of allele frequency change were suggestive of potential antagonistic pleiotropy. Our results provide new insights into recent evolutionary responses in an agricultural pest and show how temporal contrasts using museum specimens can improve mechanistic understanding of rapid evolution.

Extrapolating microevolutionary models does not always provide satisfactory explanations for phenotypic diversification on million-year time scales. For example, short-term evolutionary change is often modeled assuming a fixed adaptive landscape, but macroevolutionary changes are likely to involve changes in the adaptive landscape itself. A better understanding of how the adaptive landscape changes across different time intervals and how these changes cause populations to evolve has the potential to narrow the gap between micro- and macroevolution. Here, we analyze two fossil diatom time series of exceptional quality and resolution covering time intervals of a few hundred thousand years using models that account for different behaviors of the adaptive landscape. We find that one of the lineages evolves on a randomly and continuously changing landscape, whereas the other lineage evolves on a landscape that shows a rapid shift in the position of the adaptive peak of a magnitude that is typically associated with species-level differentiation. This suggests phenotypic evolution beyond generational timescales may be a consequence of both gradual and sudden repositioning of adaptive peaks. Both lineages are showing rapid and erratic evolutionary change and are constantly readapting towards the optimal trait state, observations that align with evolutionary dynamics commonly observed in contemporary populations. The inferred trait evolution over a span of a few hundred thousand years in these two lineages is therefore chimeric in the sense that it combines components of trait evolution typically observed on both short and long timescales.

To quantify selection acting on a trait, methods have been developed using either within or between-species variation. However, methods using within-species variation do not integrate the changes at the macroevolutionary scale. Conversely, current methods using between-species variation usually discard within-species variation, thus not accounting for processes at the micro-evolutionary scale. The main goal of this study is to define a neutrality index for a quantitative trait, by combining withinand between-species variation. This neutrality index integrates nucleotide polymorphism and divergence for normalizing trait variation. As such, it does not require estimation of population size nor of time of speciation for normalization. Our index can be used to seek deviation from the null model of neutral evolution, and test for diversifying selection. Applied to brain mass and body mass at the mammalian scale, we show that brain mass is under diversifying selection. Finally, we show that our test is not sensitive to the assumption that population sizes, mutation rates and generation time are constant across the phylogeny, and automatically adjust for it.

Double-strand breaks (DSB), the most difficult to repair DNA damage, are mainly repaired by non-homologous end-joining (NHEJ) or homologous recombination (HR). Previous studies seem to indicate that primates, and particularly humans, have a better NHEJ system. A distinctive feature of the primate lineage (beside longevity) is encephalization, i.e., the expansion of the brain relative to body mass (BM). Using existing transcriptome data from 34 mammalian species, we investigated the possible correlations between the expression of genes involved in NHEJ and encephalization, BM, and longevity. The same was done also for genes involved in the HR pathway. We found that, while HR gene expression is better correlated with longevity, NHEJ gene expression is strongly (and better) correlated with encephalization. Since the brain is composed of postmitotic cells, DSB repair should be mainly performed by NHEJ in this organ. Therefore, we interpret the correlation we found as an indication that NHEJ efficiency coevolved with encephalization.

Arms race dynamics are a common outcome of host-parasite coevolution. While they can theoretically be maintained indefinitely, realistic arms races are expected to be finite. Once an arms race has ended, for example due to the evolution of a generalist-resistant host, the system may transition into coevolutionary dynamics that favour long-term diversity. In microbial experiments, host-parasite arms races often transition into a stable coexistence of generalist-resistant hosts, (semi-)susceptible hosts, and parasites. While long-term host diversity is implicit in these cases, parasite diversity is usually overlooked. In this study, we examined parasite diversity after the end of an experimental arms race between a unicellular alga (Chlorella variabilis) and its lytic virus (PBCV-1). First, we isolated virus genotypes from multiple time points from two replicate microcosms. A time-shift experiment confirmed that the virus isolates had escalating host ranges, i.e., that arms races had occurred. We then examined the phenotypic and genetic diversity of virus isolates from the post-arms race phase. Post-arms race virus isolates had diverse host ranges, survival probabilities, and growth rates; they also clustered into distinct genetic groups. Importantly, host range diversity was maintained throughout the post-arms race phase, and the frequency of host range phenotypes fluctuated over time. We hypothesize that this dynamic polymorphism was maintained by a combination of fluctuating selection and demographic stochasticity. Together with previous work in prokaryotic systems, our results link experimental observations of arms races to natural observations of long-term host and parasite diversity.

Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer video game as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual's survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.