Drivers of interlineage variability in mitogenomic evolutionary rates in Platyhelminthes
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Mitonuclear discordance between species is readily documented in marine fishes. Such discordance may either be the result of past natural phenomena or the result of recent introgression from previously seperated species after shifts in their spatial distributions. Using ancient DNA spanning five millennia, we here investigate the long-term presence of Pacific bluefin tuna (Thunnus orientalis) and albacore (Thunnus alalunga) -like mitochondrial (MT) genomes in Atlantic bluefin tuna (Thunnus thynnus), a species with extensive exploitation history and observed shifts in abundance and age structure. Comparing ancient (n = 130) and modern (n = 78) Atlantic bluefin MT genomes from most of its range, we detect no significant spatial or temporal population structure, which implies ongoing gene flow between populations and large effective population sizes over millennia. Moreover, we identify discordant MT haplotypes in ancient specimens up to 5000 years old and find that the frequency of these haplotypes has remained similar through time. We therefore conclude that MT discordance in the Atlantic bluefin tuna is not driven by recent introgression. Our observations provide oldest example of directly observed MT discordance in the marine environment, highlighting the utility of ancient DNA to obtain insights in the long-term persistence of such phenomena.
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Large language models (LLMs) have become increasingly capable, but their development often requires substantial computational resources. Although model merging has emerged as a cost-effective promising approach for creating new models by combining existing ones, it currently relies on human intuition and domain knowledge, limiting its potential. Here we propose an evolutionary approach that overcomes this limitation by automatically discovering effective combinations of diverse open-source models, harnessing their collective intelligence without requiring extensive additional training data or compute. Our approach operates in both parameter space and data flow space, allowing optimization beyond just the weights of the individual models. This approach even facilitates cross-domain merging, generating models such as a Japanese LLM with math reasoning capabilities. Surprisingly, our Japanese math LLM achieved state-of-the-art performance on a variety of established Japanese LLM benchmarks, even surpassing models with substantially more parameters, despite not being explicitly trained for such tasks. Furthermore, a culturally aware Japanese vision–language model generated through our approach demonstrates its effectiveness in describing Japanese culture-specific content, outperforming previous Japanese vision–language models. This work not only contributes new state-of-the-art models back to the open-source community but also introduces a new paradigm for automated model composition, paving the way for exploring alternative, efficient approaches to foundation model development.
Macroevolution along developmental lines of least resistance in fly wings
Evolutionary change requires genetic variation, and a reigning paradigm in biology is that rates of microevolution can be predicted from estimates of available genetic variation within populations. However, the accuracy of such predictions should decay on longer evolutionary timescales, as the influence of genetic constraints diminishes. Here we show that intrinsic developmental variability and standing genetic variation in wing shape in two distantly related flies, Drosophila melanogaster and Sepsis punctum, are aligned and predict deep divergence in the dipteran phylogeny, spanning >900 taxa and 185 million years. This alignment cannot be easily explained by constraint hypotheses unless most of the quantified standing genetic variation is associated with deleterious side effects and is effectively unusable for evolution. However, phenotyping of 71 genetic lines of S. punctum revealed no covariation between wing shape and fitness, lending no support to this hypothesis. We also find little evidence for genetic constraints on the pace of wing shape evolution along the dipteran phylogeny. Instead, correlational selection related to allometric scaling, simultaneously shaping developmental variability and deep divergence in fly wings, emerges as a potential explanation for the observed alignment. This suggests that pervasive natural selection has the potential to shape developmental architectures of some morphological characters such that their intrinsic variability predicts their long-term evolution.
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