The frailty of adaptive hypotheses for the origins of organismal complexity

Photostasis and photosynthetic adaptation to polar life

Photostasis is the light-dependent maintenance of energy balance associated with cellular homeostasis in photoautotrophs. We review evidence that illustrates how photosynthetic adaptation in polar photoautrophs such as aquatic green algae, cyanobacteria, boreal conifers as well as terrestrial angiosperms exhibit an astonishing plasticity in structure and function of the photosynthetic apparatus. This plasticity contributes to the maintenance of photostasis, which is essential for the long-term survival in the seemingly inhospitable Antarctic and Arctic habitats. However, evidence indicates that polar photoautrophic species exhibit different functional solutions for the maintenance of photostasis. We suggest that this reflects, in part, the genetic diversity symbolized by inherent genetic redundancy characteristic of polar photoautotrophs which enhances their survival in a thermodynamically challenging environment.

GTDrift: a resource for exploring the interplay between genetic drift, genomic and transcriptomic characteristics in eukaryotes

We present GTDrift, a comprehensive data resource that enables explorations of genomic and transcriptomic characteristics alongside proxies of the intensity of genetic drift in individual species. This resource encompasses data for 1506 eukaryotic species, including 1413 animals and 93 green plants, and is organized in three components. The first two components contain approximations of the effective population size, which serve as indicators of the extent of random genetic drift within each species. In the first component, we meticulously investigated public databases to assemble data on life history traits such as longevity, adult body length and body mass for a set of 979 species. The second component includes estimations of the ratio between the rate of non-synonymous substitutions and the rate of synonymous substitutions (dN/dS) in protein-coding sequences for 1324 species. This ratio provides an estimate of the efficiency of natural selection in purging deleterious substitutions. Additionally, we present polymorphism-derived N e estimates for 66 species. The third component encompasses various genomic and transcriptomic characteristics. With this component, we aim to facilitate comparative transcriptomics analyses across species, by providing easy-to-use processed data for more than 16 000 RNA-seq samples across 491 species. These data include intron-centered alternative splicing frequencies, gene expression levels and sequencing depth statistics for each species, obtained with a homogeneous analysis protocol. To enable cross-species comparisons, we provide orthology predictions for conserved single-copy genes based on BUSCO gene sets. To illustrate the possible uses of this database, we identify the most frequently used introns for each gene and we assess how the sequencing depth available for each species affects our power to identify major and minor splice variants.

Beyond fitness: The information imparted in population states by selection throughout lifecycles

We approach the questions, what part of evolutionary change results from selection, and what is the adaptive information flow into a population undergoing selection, as a problem of quantifying the divergence of typical trajectories realized under selection from the expected dynamics of their counterparts under a null stochastic-process model representing the absence of selection. This approach starts with a formulation of adaptation in terms of information and from that identifies selection from the genetic parameters that generate information flow; it is the reverse of a historical approach that defines selection in terms of fitness, and then identifies adaptive characters as those amplified in relative frequency by fitness. Adaptive information is a relative entropy on distributions of histories computed directly from the generators of stochastic evolutionary population processes, which in large population limits can be approximated by its leading exponential dependence as a large-deviation function. We study a particular class of generators that represent the genetic dependence of explicit transitions around reproductive cycles in terms of stoichiometry, familiar from chemical reaction networks. Following Smith (2023), which showed that partitioning evolutionary events among genetically distinct realizations of lifecycles yields a more consistent causal analysis through the Price equation than the construction from units of selection and fitness, here we show that it likewise yields more complete evolutionary information measures.

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

Group-selection via aggregative propagule-formation enables cooperative multicellularity in an individual based, spatial model

The emergence of multicellularity is one of the major transitions in evolution that happened multiple times independently. During aggregative multicellularity, genetically potentially unrelated lineages cooperate to form transient multicellular groups. Unlike clonal multicellularity, aggregative multicellular organisms do not rely on kin selection instead other mechanisms maintain cooperation against cheater phenotypes that benefit from cooperators but do not contribute to groups. Spatiality with limited diffusion can facilitate group selection, as interactions among individuals are restricted to local neighbourhoods only. Selection for larger size (e.g. avoiding predation) may facilitate the emergence of aggregation, though it is unknown, whether and how much role such selection played during the evolution of aggregative multicellularity. We have investigated the effect of spatiality and the necessity of predation on the stability of aggregative multicellularity via individual-based modelling on the ecological timescale. We have examined whether aggregation facilitates the survival of cooperators in a temporally heterogeneous environment against cheaters, where only a subset of the population is allowed to periodically colonize a new, resource-rich habitat. Cooperators constitutively produce adhesive molecules to promote aggregation and propagule-formation while cheaters spare this expense to grow faster but cannot aggregate on their own, hence depending on cooperators for long-term survival. We have compared different population-level reproduction modes with and without individual selection (predation) to evaluate the different hypotheses. In a temporally homogeneous environment without propagule-based colonization, cheaters always win. Predation can benefit cooperators, but it is not enough to maintain the necessary cooperator amount in successive dispersals, either randomly or by fragmentation. Aggregation-based propagation however can ensure the adequate ratio of cooperators-to-cheaters in the propagule and is sufficient to do so even without predation. Spatiality combined with temporal heterogeneity helps cooperators via group selection, thus facilitating aggregative multicellularity. External stress selecting for larger size (e.g. predation) may facilitate aggregation, however, according to our results, it is neither necessary nor sufficient for aggregative multicellularity to be maintained when there is effective group-selection.

Calling Structural Variants with Confidence from Short-Read Data in Wild Bird Populations

Comprehensive characterization of structural variation in natural populations has only become feasible in the last decade. To investigate the population genomic nature of structural variation, reproducible and high-confidence structural variation callsets are first required. We created a population-scale reference of the genome-wide landscape of structural variation across 33 Nordic house sparrows (Passer domesticus). To produce a consensus callset across all samples using short-read data, we compare heuristic-based quality filtering and visual curation (Samplot/PlotCritic and Samplot-ML) approaches. We demonstrate that curation of structural variants is important for reducing putative false positives and that the time invested in this step outweighs the potential costs of analyzing short-read-discovered structural variation data sets that include many potential false positives. We find that even a lenient manual curation strategy (e.g. applied by a single curator) can reduce the proportion of putative false positives by up to 80%, thus enriching the proportion of high-confidence variants. Crucially, in applying a lenient manual curation strategy with a single curator, nearly all (>99%) variants rejected as putative false positives were also classified as such by a more stringent curation strategy using three additional curators. Furthermore, variants rejected by manual curation failed to reflect the expected population structure from SNPs, whereas variants passing curation did. Combining heuristic-based quality filtering with rapid manual curation of structural variants in short-read data can therefore become a time- and cost-effective first step for functional and population genomic studies requiring high-confidence structural variation callsets.

The global distribution of angiosperm genome size is shaped by climate

Angiosperms, which inhabit diverse environments across all continents, exhibit significant variation in genome sizes, making them an excellent model system for examining hypotheses about the global distribution of genome size. These include the previously proposed large genome constraint, mutational hazard, polyploidy-mediated, and climate-mediated hypotheses. We compiled the largest genome size dataset to date, encompassing 16 017 (> 5% of known) angiosperm species, and analyzed genome size distribution using a comprehensive geographic distribution dataset for all angiosperms. We observed that angiosperms with large range sizes generally had small genomes, supporting the large genome constraint hypothesis. Climate was shown to exert a strong influence on genome size distribution along the global latitudinal gradient, while the frequency of polyploidy and the type of growth form had negligible effects. In contrast to the unimodal patterns along the global latitudinal gradient shown by plant size traits and polyploid proportions, the increase in angiosperm genome size from the equator to 40-50°N/S is probably mediated by different (mostly climatic) mechanisms than the decrease in genome sizes observed from 40 to 50°N northward. Our analysis suggests that the global distribution of genome sizes in angiosperms is mainly shaped by climatically mediated purifying selection, genetic drift, relaxed selection, and environmental filtering.

Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans

Most eukaryotic genes undergo alternative splicing (AS), but the overall functional significance of this process remains a controversial issue. It has been noticed that the complexity of organisms (assayed by the number of distinct cell types) correlates positively with their genome-wide AS rate. This has been interpreted as evidence that AS plays an important role in adaptive evolution by increasing the functional repertoires of genomes. However, this observation also fits with a totally opposite interpretation: given that 'complex' organisms tend to have small effective population sizes (Ne), they are expected to be more affected by genetic drift, and hence more prone to accumulate deleterious mutations that decrease splicing accuracy. Thus, according to this 'drift barrier' theory, the elevated AS rate in complex organisms might simply result from a higher splicing error rate. To test this hypothesis, we analyzed 3496 transcriptome sequencing samples to quantify AS in 53 metazoan species spanning a wide range of Ne values. Our results show a negative correlation between Ne proxies and the genome-wide AS rates among species, consistent with the drift barrier hypothesis. This pattern is dominated by low abundance isoforms, which represent the vast majority of the splice variant repertoire. We show that these low abundance isoforms are depleted in functional AS events, and most likely correspond to errors. Conversely, the AS rate of abundant isoforms, which are relatively enriched in functional AS events, tends to be lower in more complex species. All these observations are consistent with the hypothesis that variation in AS rates across metazoans reflects the limits set by drift on the capacity of selection to prevent gene expression errors.

A nonadaptive explanation for macroevolutionary patterns in the evolution of complex multicellularity

"Complex multicellularity," conventionally defined as large organisms with many specialized cell types, has evolved five times independently in eukaryotes, but never within prokaryotes. A number of hypotheses have been proposed to explain this phenomenon, most of which posit that eukaryotes evolved key traits (e.g., dynamic cytoskeletons, alternative mechanisms of gene regulation, or subcellular compartments) which were a necessary prerequisite for the evolution of complex multicellularity. Here, we propose an alternative, nonadaptive hypothesis for this broad macroevolutionary pattern. By binning cells into groups with finite genetic bottlenecks between generations, the evolution of multicellularity greatly reduces the effective population size (Ne) of cellular populations, increasing the role of genetic drift in evolutionary change. While both prokaryotes and eukaryotes experience this phenomenon, they have opposite responses to drift: eukaryotes tend to undergo genomic expansion, providing additional raw genetic material for subsequent multicellular innovation, while prokaryotes generally face genomic erosion. Taken together, we hypothesize that these idiosyncratic lineage-specific evolutionary dynamics play a fundamental role in the long-term divergent evolution of complex multicellularity across the tree of life.

Thomas S. Kuhn: key to a better understanding of the extended evolutionary synthesis

In recent years, some scholars have explicitly questioned the desirability or utility of applying the classical and "old-fashioned" theories of scientific change by the likes of Karl Popper and Thomas S. Kuhn to the question of the precise nature and significance of the extended evolutionary synthesis (EES). Supposedly, these twentieth-century philosophers are completely irrelevant for a better understanding of this new theoretical framework for the study of evolution. Here, it will be argued that the EES can be fruitfully interpreted in terms of, as yet, insufficiently considered or even overlooked elements from Kuhn's theory. First, in his original, historical philosophy of science, Kuhn not only distinguished between small and big scientific revolutions, he also pointed out that paradigms can be extended and reformulated. In contrast with what its name suggests, the mainstream EES can be interpreted as a Kuhnian reformulation of modern evolutionary theory. Second, it has, as yet, also been overlooked that the EES can be interpreted in terms of Kuhn's later, tentative evolutionary philosophy of science. With the EES, an old dichotomy in evolutionary biology is maybe being formalized and institutionalized.

Tracing the evolution of tissue inhibitor of metalloproteinases in Metazoa with the Pteria penguin genome

Tissue inhibitors of metalloproteinase (TIMPs) play a pivotal role in regulating extracellular matrix (ECM) dynamics and have been extensively studied in vertebrates. However, understanding their evolution across invertebrate phyla is limited. Utilizing the high-quality Pteria penguin genome, we conducted phylogenomic orthology analyses across metazoans, revealing the emergence and distribution of the TIMP gene family. Our findings show that TIMP repertoires originated during eumetazoan radiation, experiencing independent duplication events in different clades, resulting in varied family sizes. Particularly, Pteriomorphia bivalves within Mollusca exhibited the most significant expansion and displayed the most diverse TIMP repertoires among metazoans. These expansions were attributed to multiple gene duplication events, potentially driven by the demands for functional diversification related to multiple adaptive traits, contributing to the adaptation of Pteriomorphia bivalves as stationary filter feeders. In this context, Pteriomorphia bivalves offer a promising model for studying invertebrate TIMP evolution.

Evolution of biological cooperation: an algorithmic approach

This manuscript presents an algorithmic approach to cooperation in biological systems, drawing on fundamental ideas from statistical mechanics and probability theory. Fisher's geometric model of adaptation suggests that the evolution of organisms well adapted to multiple constraints comes at a significant complexity cost. By utilizing combinatorial models of fitness, we demonstrate that the probability of adapting to all constraints decreases exponentially with the number of constraints, thereby generalizing Fisher's result. Our main focus is understanding how cooperation can overcome this adaptivity barrier. Through these combinatorial models, we demonstrate that when an organism needs to adapt to a multitude of environmental variables, division of labor emerges as the only viable evolutionary strategy.

The Constructive Black Queen hypothesis: new functions can evolve under conditions favouring gene loss

Duplication is a major route for the emergence of new gene functions. However, the emergence of new gene functions via this route may be reduced in prokaryotes, as redundant genes are often rapidly purged. In lineages with compact, streamlined genomes, it thus appears challenging for novel function to emerge via duplication and divergence. A further pressure contributing to gene loss occurs under Black Queen dynamics, as cheaters that lose the capacity to produce a public good can instead acquire it from neighbouring producers. We propose that Black Queen dynamics can favour the emergence of new function because, under an emerging Black Queen dynamic, there is high gene redundancy spread across a community of interacting cells. Using computational modelling, we demonstrate that new gene functions can emerge under Black Queen dynamics. This result holds even if there is deletion bias due to low duplication rates and selection against redundant gene copies resulting from the high cost associated with carrying a locus. However, when the public good production costs are high, Black Queen dynamics impede the fixation of new functions. Our results expand the mechanisms by which new gene functions can emerge in prokaryotic systems.

Endless forms of endless formation - The morphogenesis of organisms and scientific objects

The present article proceeds from the premises that living forms and abstract formalization come into being by similar mechanisms (e.g., random variation, selection, conventions) and have similar properties (e.g., semiosis, stasis and complexity). These convergences justify the comparative analysis of form's development, evolution and action in both fields. Here we shall focus on the notion of "endless forms" advanced by Darwin's seminal work in evolutionary biology "On The Origin of Species" to discuss the various ways in which it relates to biological formation. I shall explore the idea of "infinitude of evolved forms" through the lens of the five connotations of the word "endless" provided by the Merriam-Webster Thesaurus dictionary, which are: perpetual; incomputable; manifold; unfinished; steady. From each synonym chosen, a new iteration of dictionary search was made to produce a list of terms that are used in the reviewed literature to describe biological morphogenetic features, which are respectively: reproducible, unpredictable, additive, undetermined, the end of their own formation. In conclusion, I propose a tentative mapping between each of these five connotations and the biological processes at work in their making, which are, respectively: 1) copying organic information; coding organic signs; manufacturing organic meaning 2) natural variation, natural selection, natural conventions; 3) multilevel organization, differentiation/development, complexity; 4) ambiguity, degeneracy, semiotic thresholds; 5) homeostasis, autopoiesis, codepoiesis. The processes discussed here gained salience as developments, additions, or nuances to Darwin's original theory. It must be noted that, even though the discussion is mainly framed by Code Biology as a source of conceptualization, inputs from a wide range of theoretical perspectives will be given emphasis when suitable.

Origins and evolution of biological novelty

Understanding the origins and impacts of novel traits has been a perennial interest in many realms of ecology and evolutionary biology. Here, we build on previous evolutionary and philosophical treatments of this subject to encompass novelties across biological scales and eco-evolutionary perspectives. By defining novelties as new features at one biological scale that have emergent effects at other biological scales, we incorporate many forms of novelty that have previously been treated in isolation (such as novelty from genetic mutations, new developmental pathways, new morphological features, and new species). Our perspective is based on the fundamental idea that the emergence of a novelty, at any biological scale, depends on its environmental and genetic context. Through this lens, we outline a broad array of generative mechanisms underlying novelty and highlight how genomic tools are transforming our understanding of the origins of novelty. Lastly, we present several case studies to illustrate how novelties across biological scales and systems can be understood based on common mechanisms of change and their environmental and genetic contexts. Specifically, we highlight how gene duplication contributes to the evolution of new complex structures in visual systems; how genetic exchange in symbiosis alters functions of both host and symbiont, resulting in a novel organism; and how hybridisation between species can generate new species with new niches.

Beyond fitness: the nature of selection acting through the constructive steps of lifecycles

We address the problem of defining selection and extracting the adaptive part of evolutionary change, originally formalized by Fisher and Price. Conventionally, selection and adaptation are defined through fitness attributed to genes or genotypes chosen as units of selection. The construction through fitness is known to suffer ambiguities and omissions as a theory of change due to selection. We construct an alternative framing in which units of selection and fitness are replaced as the main abstractions by formal lifecycle models and reproduction rates through genetically distinct lifecycle realizations. Graphical representations of lifecycles express relations among reproductive stages that cannot be assigned to any one unit of selection. The lifecycle partition refines the statistics of overall reproductive success and resolves modes of selection that fitness either excludes or distorts through additive projections. We derive the Price equation in the basis of lifecycle realizations and compare it to the conventional Price equation for additive fitness of organisms. We show how the lifecycle approach recovers fitnesses acting concurrently at multiple levels, or contrasts forms of competition within and between levels that are invisible to additive fitness. Defining selection through lifecycles recasts population genetics from an object-focused to a construction- and process-focused representation.

Dead rats, dopamine, performance metrics, and peacock tails: Proxy failure is an inherent risk in goal-oriented systems

When a measure becomes a target, it ceases to be a good measure. For example, when standardized test scores in education become targets, teachers may start "teaching to the test," leading to breakdown of the relationship between the measure - test performance - and the underlying goal - quality education. Similar phenomena have been named and described across a broad range of contexts, such as economics, academia, machine learning, and ecology. Yet it remains unclear whether these phenomena bear only superficial similarities, or if they derive from some fundamental unifying mechanism. Here, we propose such a unifying mechanism, which we label proxy failure. We first review illustrative examples and their labels, such as the "cobra effect," "Goodhart's law," and "Campbell's law." Second, we identify central prerequisites and constraints of proxy failure, noting that it is often only a partial failure or divergence. We argue that whenever incentivization or selection is based on an imperfect proxy measure of the underlying goal, a pressure arises that tends to make the proxy a worse approximation of the goal. Third, we develop this perspective for three concrete contexts, namely neuroscience, economics, and ecology, highlighting similarities and differences. Fourth, we outline consequences of proxy failure, suggesting it is key to understanding the structure and evolution of goal-oriented systems. Our account draws on a broad range of disciplines, but we can only scratch the surface within each. We thus hope the present account elicits a collaborative enterprise, entailing both critical discussion as well as extensions in contexts we have missed.

Subfunctionalized expression drives evolutionary retention of ribosomal protein paralogs Rps27 and Rps27l in vertebrates

The formation of paralogs through gene duplication is a core evolutionary process. For paralogs that encode components of protein complexes such as the ribosome, a central question is whether they encode functionally distinct proteins or whether they exist to maintain appropriate total expression of equivalent proteins. Here, we systematically tested evolutionary models of paralog function using the ribosomal protein paralogs Rps27 (eS27) and Rps27l (eS27L) as a case study. Evolutionary analysis suggests that Rps27 and Rps27l likely arose during whole-genome duplication(s) in a common vertebrate ancestor. We show that Rps27 and Rps27l have inversely correlated mRNA abundance across mouse cell types, with the highest Rps27 in lymphocytes and the highest Rps27l in mammary alveolar cells and hepatocytes. By endogenously tagging the Rps27 and Rps27l proteins, we demonstrate that Rps27- and Rps27l-ribosomes associate preferentially with different transcripts. Furthermore, murine Rps27 and Rps27l loss-of-function alleles are homozygous lethal at different developmental stages. However, strikingly, expressing Rps27 protein from the endogenous Rps27l locus or vice versa completely rescues loss-of-function lethality and yields mice with no detectable deficits. Together, these findings suggest that Rps27 and Rps27l are evolutionarily retained because their subfunctionalized expression patterns render both genes necessary to achieve the requisite total expression of two equivalent proteins across cell types. Our work represents the most in-depth characterization of a mammalian ribosomal protein paralog to date and highlights the importance of considering both protein function and expression when investigating paralogs.

Minor variations in multicellular life cycles have major effects on adaptation

Multicellularity has evolved several independent times over the past hundreds of millions of years and given rise to a wide diversity of complex life. Recent studies have found that large differences in the fundamental structure of early multicellular life cycles can affect fitness and influence multicellular adaptation. Yet, there is an underlying assumption that at some scale or categorization multicellular life cycles are similar in terms of their adaptive potential. Here, we consider this possibility by exploring adaptation in a class of simple multicellular life cycles of filamentous organisms that only differ in one respect, how many daughter filaments are produced. We use mathematical models and evolutionary simulations to show that despite the similarities, qualitatively different mutations fix. In particular, we find that mutations with a tradeoff between cell growth and group survival, i.e. "selfish" or "altruistic" traits, spread differently. Specifically, altruistic mutations more readily spread in life cycles that produce few daughters while in life cycles producing many daughters either type of mutation can spread depending on the environment. Our results show that subtle changes in multicellular life cycles can fundamentally alter adaptation.

Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.

Frank Beach Award Winner: The centrality of the hypothalamic-pituitary-adrenal axis in dealing with environmental change across temporal scales

Understanding if and how individuals and populations cope with environmental change is an enduring question in evolutionary ecology that has renewed importance given the pace of change in the Anthropocene. Two evolutionary strategies of coping with environmental change may be particularly important in rapidly changing environments: adaptive phenotypic plasticity and/or bet hedging. Adaptive plasticity could enable individuals to match their phenotypes to the expected environment if there is an accurate cue predicting the selective environment. Diversifying bet hedging involves the production of seemingly random phenotypes in an unpredictable environment, some of which may be adaptive. Here, I review the central role of the hypothalamic-pituitary-adrenal (HPA) axis and glucocorticoids (GCs) in enabling vertebrates to cope with environmental change through adaptive plasticity and bet hedging. I first describe how the HPA axis mediates three types of adaptive plasticity to cope with environmental change (evasion, tolerance, recovery) over short timescales (e.g., 1-3 generations) before discussing how the implications of GCs on phenotype integration may depend upon the timescale under consideration. GCs can promote adaptive phenotypic integration, but their effects on phenotypic co-variation could also limit the dimensions of phenotypic space explored by animals over longer timescales. Finally, I discuss how organismal responses to environmental stressors can act as a bet hedging mechanism and therefore enhance evolvability by increasing genetic or phenotypic variability or reducing patterns of genetic and phenotypic co-variance. Together, this emphasizes the crucial role of the HPA axis in understanding fundamental questions in evolutionary ecology.

Under the magnifying glass: The ups and downs of rDNA copy number

The ribosomal DNA (rDNA) in Drosophila is found as two additive clusters of individual 35 S cistrons. The multiplicity of rDNA is essential to assure proper translational demands, but the nature of the tandem arrays expose them to copy number variation within and between populations. Here, we discuss means by which a cell responds to insufficient rDNA copy number, including a historical view of rDNA magnification whose mechanism was inferred some 35 years ago. Recent work has revealed that multiple conditions may also result in rDNA loss, in response to which rDNA magnification may have evolved. We discuss potential models for the mechanism of magnification, and evaluate possible consequences of rDNA copy number variation.

Supply-driven evolution: Mutation bias and trait-fitness distributions can drive macro-evolutionary dynamics

Many well-documented macro-evolutionary phenomena still challenge current evolutionary theory. Examples include long-term evolutionary trends, major transitions in evolution, conservation of certain biological features such as hox genes, and the episodic creation of new taxa. Here, we present a framework that may explain these phenomena. We do so by introducing a probabilistic relationship between trait value and reproductive fitness. This integration allows mutation bias to become a robust driver of long-term evolutionary trends against environmental bias, in a way that is consistent with all current evolutionary theories. In cases where mutation bias is strong, such as when detrimental mutations are more common than beneficial mutations, a regime called “supply-driven” evolution can arise. This regime can explain the irreversible persistence of higher structural hierarchies, which happens in the major transitions in evolution. We further generalize this result in the long-term dynamics of phenotype spaces. We show how mutations that open new phenotype spaces can become frozen in time. At the same time, new possibilities may be observed as a burst in the creation of new taxa.

Chromosome size matters: genome evolution in the cyperid clade

BACKGROUND AND AIMS

While variation in genome size and chromosome numbers and their consequences are often investigated in plants, the biological relevance of variation in chromosome size remains poorly known. Here, we examine genome and mean chromosome size in the cyperid clade (families Cyperaceae, Juncaceae and Thurniaceae), which is the largest vascular plant lineage with predominantly holocentric chromosomes.

METHODS

We measured genome size in 436 species of cyperids using flow cytometry, and augment these data with previously published datasets. We then separately compared genome and mean chromosome sizes (2C/2n) amongst the major lineages of cyperids and analysed how these two genomic traits are associated with various environmental factors using phylogenetically informed methods.

KEY RESULTS

We show that cyperids have the smallest mean chromosome sizes recorded in seed plants, with a large divergence between the smallest and largest values. We found that cyperid species with smaller chromosomes have larger geographical distributions and that there is a strong inverse association between mean chromosome size and number across this lineage.

CONCLUSIONS

The distinct patterns in genome size and mean chromosome size across the cyperids might be explained by holokinetic drive. The numerous small chromosomes might function to increase genetic diversity in this lineage where crossovers are limited during meiosis.

The genome loading model for the origin and maintenance of sex in eukaryotes

Understanding why sexual reproduction-which involves syngamy (union of gametes) and meiosis-emerged and how it has subsisted for millions of years remains a fundamental problem in biology. Considered as the essence of sex, meiotic recombination is initiated by a DNA double-strand break (DSB) that forms on one of the pairing homologous chromosomes. This DNA lesion is subsequently repaired by gene conversion, the non-reciprocal transfer of genetic information from the intact homolog. A major issue is which of the pairing homologs undergoes DSB formation. Accumulating evidence shows that chromosomal sites where the pairing homologs locally differ in size, i.e., are heterozygous for an insertion or deletion, often display disparity in gene conversion. Biased conversion tends to duplicate insertions and lose deletions. This suggests that DSB is preferentially formed on the "shorter" homologous region, which thereby acts as the recipient for DNA transfer. Thus, sex primarily functions as a genome (re)loading mechanism. It ensures the restoration of formerly lost DNA sequences (deletions) and allows the efficient copying and, mainly in eukaryotes, subsequent spreading of newly emerged sequences (insertions) arising initially in an individual genome, even if they confer no advantage to the host. In this way, sex simultaneously repairs deletions and increases genetic variability underlying adaptation. The model explains a remarkable increase in DNA content during the evolution of eukaryotic genomes.

Early effects of gene duplication on the robustness and phenotypic variability of gene regulatory networks

Background

Research on gene duplication is abundant and comes from a wide range of approaches, from high-throughput analyses and experimental evolution to bioinformatics and theoretical models. Notwithstanding, a consensus is still lacking regarding evolutionary mechanisms involved in evolution through gene duplication as well as the conditions that affect them. We argue that a better understanding of evolution through gene duplication requires considering explicitly that genes do not act in isolation. It demands studying how the perturbation that gene duplication implies percolates through the web of gene interactions. Due to evolution’s contingent nature, the paths that lead to the final fate of duplicates must depend strongly on the early stages of gene duplication, before gene copies have accumulated distinctive changes.

Methods

Here we use a widely-known model of gene regulatory networks to study how gene duplication affects network behavior in early stages. Such networks comprise sets of genes that cross-regulate. They organize gene activity creating the gene expression patterns that give cells their phenotypic properties. We focus on how duplication affects two evolutionarily relevant properties of gene regulatory networks: mitigation of the effect of new mutations and access to new phenotypic variants through mutation.

Results

Among other observations, we find that those networks that are better at maintaining the original phenotype after duplication are usually also better at buffering the effect of single interaction mutations and that duplication tends to enhance further this ability. Moreover, the effect of mutations after duplication depends on both the kind of mutation and genes involved in it. We also found that those phenotypes that had easier access through mutation before duplication had higher chances of remaining accessible through new mutations after duplication.

Conclusion

Our results support that gene duplication often mitigates the impact of new mutations and that this effect is not merely due to changes in the number of genes. The work that we put forward helps to identify conditions under which gene duplication may enhance evolvability and robustness to mutations.

An investigation of codon usage pattern analysis in pancreatitis associated genes

BACKGROUND

Pancreatitis is an inflammatory disorder resulting from the autoactivation of trypsinogen in the pancreas. The genetic basis of the disease is an old phenomenon, and evidence is accumulating for the involvement of synonymous/non-synonymous codon variants in disease initiation and progression.

RESULTS

The present study envisaged a panel of 26 genes involved in pancreatitis for their codon choices, compositional analysis, relative dinucleotide frequency, nucleotide disproportion, protein physical properties, gene expression, codon bias, and interrelated of all these factors. In this set of genes, gene length was positively correlated with nucleotide skews and codon usage bias. Codon usage of any gene is dependent upon its AT and GC component; however, AGG, CGT, and CGA encoding for Arg, TCG for Ser, GTC for Val, and CCA for Pro were independent of nucleotide compositions. In addition, Codon GTC showed a correlation with protein properties, isoelectric point, instability index, and frequency of basic amino acids. We also investigated the effect of various evolutionary forces in shaping the codon usage choices of genes.

CONCLUSIONS

This study will enable us to gain insight into the molecular signatures associated with the disease that might help identify more potential genes contributing to enhanced risk for pancreatitis. All the genes associated with pancreatitis are generally associated with physiological function, and mutations causing loss of function, over or under expression leads to an ailment. Therefore, the present study attempts to envisage the molecular signature in a group of genes that lead to pancreatitis in case of malfunction.

Epigenetic targeting of transposon relics: beating the dead horses of the genome?

Transposable elements (TEs) have been seen as selfish genetic elements that can propagate in a host genome. Their propagation success is however hindered by a combination of mechanisms such as mutations, selection, and their epigenetic silencing by the host genome. As a result, most copies of TEs in a given genome are dead relics: their sequence is too degenerated to allow any transposition. Nevertheless, these TE relics often, but not always, remain epigenetically silenced, and if not to prevent transposition anymore, one can wonder the reason for this phenomenon. The mere self-perpetuating loop inherent to epigenetic silencing could alone explain that even when inactive, TE copies remain silenced. Beyond this process, nevertheless, antagonistic selective forces are likely to act on TE relic silencing. Especially, without the benefit of preventing transposition, TE relic silencing may prove deleterious to the host fitness, suggesting that the maintenance of TE relic silencing is the result of a fine, and perhaps case-by-case, evolutionary trade-off between beneficial and deleterious effects. Ultimately, the release of TE relics silencing may provide a 'safe' ground for adaptive epimutations to arise. In this review, we provide an overview of these questions in both plants and animals.

Transposable element expansion and low-level piRNA silencing in grasshoppers may cause genome gigantism

Background

Transposable elements (TEs) have been likened to parasites in the genome that reproduce and move ceaselessly in the host, continuously enlarging the host genome. However, the Piwi-interacting RNA (piRNA) pathway defends animal genomes against the harmful consequences of TE invasion by imposing small-RNA-mediated silencing. Here we compare the TE activity of two grasshopper species with different genome sizes in Acrididae (Locusta migratoria manilensis♀1C = 6.60 pg, Angaracris rhodopa♀1C = 16.36 pg) to ascertain the influence of piRNAs.

Results

We discovered that repetitive sequences accounted for 74.56% of the genome in A. rhodopa, more than 56.83% in L. migratoria, and the large-genome grasshopper contained a higher TEs proportions. The comparative analysis revealed that 41 TEs (copy number > 500) were shared in both species. The two species exhibited distinct “landscapes” of TE divergence. The TEs outbreaks in the small-genome grasshopper occurred at more ancient times, while the large-genome grasshopper maintains active transposition events in the recent past. Evolutionary history studies on TEs suggest that TEs may be subject to different dynamics and resistances in these two species. We found that TE transcript abundance was higher in the large-genome grasshopper and the TE-derived piRNAs abundance was lower than in the small-genome grasshopper. In addition, we found that the piRNA methylase HENMT, which is underexpressed in the large-genome grasshopper, impedes the piRNA silencing to a lower level.

Conclusions

Our study revealed that the abundance of piRNAs is lower in the gigantic genome grasshopper than in the small genome grasshopper. In addition, the key gene HENMT in the piRNA biogenesis pathway (Ping-Pong cycle) in the gigantic genome grasshopper is underexpressed. We hypothesize that low-level piRNA silencing unbalances the original positive correlation between TEs and piRNAs, and triggers TEs to proliferate out of control, which may be one of the reasons for the gigantism of grasshopper genomes.

An overview of online resources for intra-species detection of gene duplications

Gene duplication plays an important role in evolutionary mechanism, which can act as a new source of genetic material in genome evolution. However, detecting duplicate genes from genomic data can be challenging. Various bioinformatics resources have been developed to identify duplicate genes from single and/or multiple species. Here, we summarize the metrics used to measure sequence identity among gene duplicates within species, compare several computational approaches that have been used to predict gene duplicates, and review recent advancements of a Basic Local Alignment Search Tool (BLAST)-based web tool and database, allowing future researchers to easily identify intra-species gene duplications. This article is a quick reference guide for research tools used for detecting gene duplicates.

Relative specificity as an important consideration in the big data era

Technological breakthroughs such as high-throughput methods, genomics, single-cell studies, and machine learning have fundamentally transformed research and ushered in the big data era of biology. Nevertheless, current data collections, analyses, and modeling frequently overlook relative specificity, a crucial property of molecular interactions in biochemical systems. Relative specificity describes how, for example, an enzyme reacts with its many substrates at different rates, and how this discriminatory action alone is sufficient to modulate the substrates and downstream events. As a corollary, it is not only important to comprehensively identify an enzyme’s substrates, but also critical to quantitatively determine how the enzyme interacts with the substrates and to evaluate how it shapes subsequent biological outcomes. Genomics and high-throughput techniques have greatly facilitated the studies of relative specificity in the 21st century, and its functional significance has been demonstrated in complex biochemical systems including transcription, translation, protein kinases, RNA-binding proteins, and animal microRNAs (miRNAs), although it remains ignored in most work. Here we analyze recent findings in big data and relative specificity studies and explain how the incorporation of relative specificity concept might enhance our mechanistic understanding of gene functions, biological phenomena, and human diseases.

No evidence for widespread positive selection on double substitutions within codons in primates and yeasts

Nucleotide substitutions in protein-coding genes can be divided into synonymous (S) and non-synonymous (N) ones that alter amino acids (including nonsense mutations causing stop codons). The S substitutions are expected to have little effect on function. The N substitutions almost always are affected by strong purifying selection that eliminates them from evolving populations. However, additional mutations of nearby bases can modulate the deleterious effect of single N substitutions and, thus, could be subjected to the positive selection. This effect has been demonstrated for mutations in the serine codons, stop codons and double N substitutions in prokaryotes. In all abovementioned cases, a novel technique was applied that allows elucidating the effects of selection on double substitutions considering mutational biases. Here, we applied the same technique to study double N substitutions in eukaryotic lineages of primates and yeast. We identified markedly fewer cases of purifying selection relative to prokaryotes and no evidence of codon double substitutions under positive selection. This is consistent with previous studies of serine codons in primates and yeast. In general, the obtained results strongly suggest that there are major differences between studied pro- and eukaryotes; double substitutions in primates and yeasts largely reflect mutational biases and are not hallmarks of selection. This is especially important in the context of detection of positive selection in codons because it has been suggested that multiple mutations in codons cause false inferences of lineage-specific site positive selection. It is likely that this concern is applicable to previously studied prokaryotes but not to primates and yeasts where markedly fewer double substitutions are affected by positive selection.

Multivariate selection and the making and breaking of mutational pleiotropy

The role of mutations have been subject to many controversies since the formation of the Modern Synthesis of evolution in the early 1940ties. Geneticists in the early half of the twentieth century tended to view mutations as a limiting factor in evolutionary change. In contrast, natural selection was largely viewed as a “sieve” whose main role was to sort out the unfit but which could not create anything novel alone. This view gradually changed with the development of mathematical population genetics theory, increased appreciation of standing genetic variation and the discovery of more complex forms of selection, including balancing selection. Short-term evolutionary responses to selection are mainly influenced by standing genetic variation, and are predictable to some degree using information about the genetic variance–covariance matrix (G) and the strength and form of selection (e. g. the vector of selection gradients, β). However, predicting long-term evolution is more challenging, and requires information about the nature and supply of novel mutations, summarized by the mutational variance–covariance matrix (M). Recently, there has been increased attention to the role of mutations in general and M in particular. Some evolutionary biologists argue that evolution is largely mutation-driven and claim that mutation bias frequently results in mutation-biased adaptation. Strong similarities between G and M have also raised questions about the non-randomness of mutations. Moreover, novel mutations are typically not isotropic in their phenotypic effects and mutational pleiotropy is common. Here I discuss the evolutionary origin and consequences of mutational pleiotropy and how multivariate selection directly shapes G and indirectly M through changed epistatic relationships. I illustrate these ideas by reviewing recent literature and models about correlational selection, evolution of G and M, sexual selection and the fitness consequences of sexual antagonism.

Cell types as species: Exploring a metaphor

The concept of "cell type," though fundamental to cell biology, is controversial. Cells have historically been classified into types based on morphology, physiology, or location. More recently, single cell transcriptomic studies have revealed fine-scale differences among cells with similar gross phenotypes. Transcriptomic snapshots of cells at various stages of differentiation, and of cells under different physiological conditions, have shown that in many cases variation is more continuous than discrete, raising questions about the relationship between cell type and cell state. Some researchers have rejected the notion of fixed types altogether. Throughout the history of discussions on cell type, cell biologists have compared the problem of defining cell type with the interminable and often contentious debate over the definition of arguably the most important concept in systematics and evolutionary biology, "species." In the last decades, systematics, like cell biology, has been transformed by the increasing availability of molecular data, and the fine-grained resolution of genetic relationships have generated new ideas about how that variation should be classified. There are numerous parallels between the two fields that make exploration of the "cell types as species" metaphor timely. These parallels begin with philosophy, with discussion of both cell types and species as being either individuals, groups, or something in between (e.g., homeostatic property clusters). In each field there are various different types of lineages that form trees or networks that can (and in some cases do) provide criteria for grouping. Developing and refining models for evolutionary divergence of species and for cell type differentiation are parallel goals of the two fields. The goal of this essay is to highlight such parallels with the hope of inspiring biologists in both fields to look for new solutions to similar problems outside of their own field.

Whole genome duplication and dispersed duplication characterize the evolution of the plant PINOID gene family across plant species

PINOID is a kinase belonging to the AGCVIII family, which regulates the polar distribution of PIN proteins and plays an important role in plant geotropism. However, the origin and evolutionary history of this gene family is not fully known. In this study, we identified 79 similar sequences across 17 plant species genomes (PINOID, D6PK, PINOID2, "hypothetical kinase"). Our results show that the AGCVIII kinase family may have originated from related "Hypothetical Kinases" that come out sister to the rest of the gene family members. These kinases differentiated their functions are found in different plant classes: D6PK in moss and PINOID and PINOID2 evolving in angiosperms including the pioneer plant Amborella trichopoda. Our study investigates the evolution of PINOID kinases from a phylogenetic perspective giving us insight into how this important plant signal transduction network switch evolved to play a fundamental and important function in plant growth and development. We highlight the importance of whole genome duplications and dispersed duplications as opposed to tandem duplications in the evolution of this gene family.

The origin of RNA interference: Adaptive or neutral evolution?

The origin of RNA interference (RNAi) is usually explained by a defense-based hypothesis, in which RNAi evolved as a defense against transposable elements (TEs) and RNA viruses and was already present in the last eukaryotic common ancestor (LECA). However, since RNA antisense regulation and double-stranded RNAs (dsRNAs) are ancient and widespread phenomena, the origin of defensive RNAi should have occurred in parallel with its regulative functions to avoid imbalances in gene regulation. Thus, we propose a neutral evolutionary hypothesis for the origin of RNAi in which qualitative system drift from a prokaryotic antisense RNA gene regulation mechanism leads to the formation of RNAi through constructive neutral evolution (CNE). We argue that RNAi was already present in the ancestor of LECA before the need for a new defense system arose and that its presence helped to shape eukaryotic genomic architecture and stability.

Where does RNA interference come from? This Essay describes a new step-by-step evolutionary model of how RNA interference might have originated in early eukaryotes through neutral events from the molecular machinery present in prokaryotes.

Extensive polyploid clonality was a successful strategy for seagrass to expand into a newly submerged environment

Polyploidy has the potential to allow organisms to outcompete their diploid progenitor(s) and occupy new environments. Shark Bay, Western Australia, is a World Heritage Area dominated by temperate seagrass meadows including Poseidon's ribbon weed, Posidonia australis. This seagrass is at the northern extent of its natural geographic range and experiences extremes in temperature and salinity. Our genomic and cytogenetic assessments of 10 meadows identified geographically restricted, diploid clones (2n = 20) in a single location, and a single widespread, high-heterozygosity, polyploid clone (2n = 40) in all other locations. The polyploid clone spanned at least 180 km, making it the largest known example of a clone in any environment on earth. Whole-genome duplication through polyploidy, combined with clonality, may have provided the mechanism for P. australis to expand into new habitats and adapt to new environments that became increasingly stressful for its diploid progenitor(s). The new polyploid clone probably formed in shallow waters after the inundation of Shark Bay less than 8500 years ago and subsequently expanded via vegetative growth into newly submerged habitats.

A synthetic synthesis to explore animal evolution and development

Identifying the general principles by which genotypes are converted into phenotypes remains a challenge in the post-genomic era. We still lack a predictive understanding of how genes shape interactions among cells and tissues in response to signalling and environmental cues, and hence how regulatory networks generate the phenotypic variation required for adaptive evolution. Here, we discuss how techniques borrowed from synthetic biology may facilitate a systematic exploration of evolvability across biological scales. Synthetic approaches permit controlled manipulation of both endogenous and fully engineered systems, providing a flexible platform for investigating causal mechanisms in vivo. Combining synthetic approaches with multi-level phenotyping (phenomics) will supply a detailed, quantitative characterization of how internal and external stimuli shape the morphology and behaviour of living organisms. We advocate integrating high-throughput experimental data with mathematical and computational techniques from a variety of disciplines in order to pursue a comprehensive theory of evolution.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

Structural Dynamics and Molecular Evolution of the SARS-CoV-2 Spike Protein

The ongoing coronavirus disease 2019 (COVID-19) pandemic demonstrates the threat posed by novel coronaviruses to human health. Coronaviruses share a highly conserved cell entry mechanism mediated by the spike protein, the sole product of the S gene. The structural dynamics by which the spike protein orchestrates infection illuminate how antibodies neutralize virions and how S mutations contribute to viral fitness. Here, we review the process by which spike engages its proteinaceous receptor, angiotensin converting enzyme 2 (ACE2), and how host proteases prime and subsequently enable efficient membrane fusion between virions and target cells. We highlight mutations common among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern and discuss implications for cell entry. Ultimately, we provide a model by which sarbecoviruses are activated for fusion competency and offer a framework for understanding the interplay between humoral immunity and the molecular evolution of the SARS-CoV-2 Spike. In particular, we emphasize the relevance of the Canyon Hypothesis (M. G. Rossmann, J Biol Chem 264:14587-14590, 1989) for understanding evolutionary trajectories of viral entry proteins during sustained intraspecies transmission of a novel viral pathogen.

The neural basis of interspecies interactions in insects

As insects move through the world, they continuously engage in behavioral interactions with other species. These interactions take on a spectrum of forms, from inconsequential encounters to predation, defense, and specialized symbiotic partnerships. All such interactions rely on sensorimotor pathways that carry out efficient categorization of different organisms and enact behaviors that cross species boundaries. Despite the universality of interspecies interactions, how insect brains perceive and process salient features of other species remains unexplored. Here, we present an overview of major questions concerning the neurobiology and evolution of behavioral interactions between species, providing a framework for future research on this critical role of the insect nervous system.

Evolutionary divergence of anaphase spindle mechanics in nematode embryos constrained by antagonistic pulling and viscous forces

Cellular functions like cell division are remarkably conserved across phyla. However the evolutionary principles of cellular organization that drive it are less well explored. Thus, an essential question remains: to what extent cellular parameters evolve without altering the basic function they sustain? Here we have observed 6 different nematode species for which the mitotic spindle is positioned asymmetrically during the first embryonic division. Whereas the C. elegans spindle undergoes oscillations during its displacement, the spindle elongates without oscillations in other species. We asked which evolutionary changes in biophysical parameters could explain differences in spindle motion while maintaining a constant output. Using laser microsurgery of the spindle we revealed that all species are subjected to cortical pulling forces, of varying magnitudes. Using a viscoelastic model to fit the recoil trajectories and with an independent measurement of cytoplasmic viscosity, we extracted the values of cytoplasmic drag, cortical pulling forces and spindle elasticity for all species. We found large variations in cytoplasmic viscosity whereas cortical pulling forces and elasticity were often more constrained. In agreement with previous simulations, we found that increased viscosity correlates with decreased oscillation speeds across species. However, the absence of oscillations despite low viscosity in some species, can only be explained by smaller pulling forces. Consequently, we find that spindle mobility across the species analyzed here is characterized by a tradeoff between cytoplasmic viscosity and pulling forces normalized by the size of the embryo. Our work provides a framework for understanding mechanical constraints on evolutionary diversification of spindle mobility.

Toward a theory of evolution as multilevel learning

We apply the theory of learning to physically renormalizable systems in an attempt to outline a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution that appear to be necessary and sufficient to render a universe observable and show that they entail the major features of biological evolution, including replication and natural selection. It is shown that these cornerstone phenomena of biology emerge from the fundamental features of learning dynamics such as the existence of a loss function, which is minimized during learning. We then sketch the theory of evolution using the mathematical framework of neural networks, which provides for detailed analysis of evolutionary phenomena. To demonstrate the potential of the proposed theoretical framework, we derive a generalized version of the Central Dogma of molecular biology by analyzing the flow of information during learning (back propagation) and predicting (forward propagation) the environment by evolving organisms. The more complex evolutionary phenomena, such as major transitions in evolution (in particular, the origin of life), have to be analyzed in the thermodynamic limit, which is described in detail in the paper by Vanchurin et al. [V. Vanchurin, Y. I. Wolf, E. V. Koonin, M. I. Katsnelson, Proc. Natl. Acad. Sci. U.S.A. 119, 10.1073/pnas.2120042119 (2022)].

Promiscuous Domains in Eukaryotes and HAT Proteins in FUNGI Have Followed Different Evolutionary Paths

Diverse studies have shown that the content of genes present in sequenced genomes does not seem to correlate with the complexity of the organisms. However, various studies have shown that organism complexity and the size of the proteome has, indeed, a significant correlation. This characteristic allows us to postulate that some molecular mechanisms have permitted a greater functional diversity to some proteins to increase their participation in developing organisms with higher complexity. Among those mechanisms, the domain promiscuity, defined as the ability of the domains to organize in combination with other distinct domains, is of great importance for the evolution of organisms. Previous works have analyzed the degree of domain promiscuity of the proteomes showing how it seems to have paralleled the evolution of eukaryotic organisms. The latter has motivated the present study, where we analyzed the domain promiscuity in a collection of 84 eukaryotic proteomes representative of all the taxonomy groups of the tree of life. Using a grammar definition approach, we determined the architecture of 1,223,227 proteins, conformed by 2,296,371 domains, which established 839,184 bigram types. The phylogenetic reconstructions based on differences in the content of information from measures of proteome promiscuity confirm that the evolution of the promiscuity of domains in eukaryotic organisms resembles the evolutionary history of the species. However, a close analysis of the PHD and RING domains, the most promiscuous domains found in fungi and functional components of chromatin remodeling enzymes and important expression regulators, suggests an evolution according to their function.

Evolution of a novel cell type in Dictyostelia required gene duplication of a cudA-like transcription factor

The evolution of novel cell types has been proposed to result from duplication of gene regulatory networks, but proven examples are rare. In addition to stalk cells and spores that make up the fruiting bodies of three major groups of Dictyostelia, those in group 4 additionally evolved basal disc and cup cells that respectively anchor the stalk to the substratum and the spore mass to the stalk. We noted a putative group-4-specific duplication of a cudA-like transcription factor (TF) in a comparative analysis of group-representative genomes. Using increased taxon sampling, we here confirmed that this TF, cdl1, duplicated into cdl1a and cdl1b in the common ancestor to group 4. cdl1a, but not cdl1b, showed signatures of positive selection, indicative of functional innovation. Deletion of cdl1a in Dictyostelium discoideum resulted in fruiting bodies with sagging spore heads that lacked the supporting cup cells and expression of cup-specific genes. Deletion of cdl1b resulted in thinner fruiting body stalks, while a cdl1b-cdl1a- double knockout showed more severe stalk defects, suggesting an ancestral role of cdl1 in stalk formation. This was confirmed in a closely related non-group 4 species, Polysphondylium violaceum, where cdl1 knockout caused defective stalk formation. These data indicate that the group-specific duplication of cdl1 and subsequent diversification of cdl1a played a pivotal role in the evolution of a novel somatic cell type in group 4 Dictyostelia.

Phenotype Bias Determines How Natural RNA Structures Occupy the Morphospace of All Possible Shapes

Morphospaces-representations of phenotypic characteristics-are often populated unevenly, leaving large parts unoccupied. Such patterns are typically ascribed to contingency, or else to natural selection disfavoring certain parts of the morphospace. The extent to which developmental bias, the tendency of certain phenotypes to preferentially appear as potential variation, also explains these patterns is hotly debated. Here we demonstrate quantitatively that developmental bias is the primary explanation for the occupation of the morphospace of RNA secondary structure (SS) shapes. Upon random mutations, some RNA SS shapes (the frequent ones) are much more likely to appear than others. By using the RNAshapes method to define coarse-grained SS classes, we can directly compare the frequencies that noncoding RNA SS shapes appear in the RNAcentral database to frequencies obtained upon a random sampling of sequences. We show that: 1) only the most frequent structures appear in nature; the vast majority of possible structures in the morphospace have not yet been explored; 2) remarkably small numbers of random sequences are needed to produce all the RNA SS shapes found in nature so far; and 3) perhaps most surprisingly, the natural frequencies are accurately predicted, over several orders of magnitude in variation, by the likelihood that structures appear upon a uniform random sampling of sequences. The ultimate cause of these patterns is not natural selection, but rather a strong phenotype bias in the RNA genotype-phenotype map, a type of developmental bias or "findability constraint," which limits evolutionary dynamics to a hugely reduced subset of structures that are easy to "find."

OUP accepted manuscript

“Junk DNA” is a popular yet controversial concept that states that organisms carry in their genomes DNA that has no positive impact on their fitness. Nonetheless, biochemical functions have been identified for an increasing fraction of DNA elements traditionally seen as “Junk DNA”. These findings have been interpreted as fundamentally undermining the “Junk DNA” concept. Here, we reinforce previous arguments that this interpretation relies on an inadequate concept of biological function that does not consider the selected effect of a given genomic structure, which is central to the “Junk DNA” concept. Next, we suggest that another (though ignored) confounding factor is that the discussion about biological functions includes two different dimensions: a horizontal, ecological dimension that reflects how a given genomic element affects fitness in a specific time, and a vertical, temporal dimension that reflects how a given genomic element persisted along time. We suggest that “Junk DNA” should be used exclusively relative to the horizontal dimension, while for the vertical dimension, we propose a new term, “Spam DNA”, that reflects the fact that a given genomic element may persist in the genome even if not selected for on their origin. Importantly, these concepts are complementary. An element can be both “Spam DNA” and “Junk DNA”, and “Spam DNA” can also be recruited to perform evolved biological functions, as illustrated in processes of exaptation or constructive neutral evolution.

HSDFinder: A BLAST-Based Strategy for Identifying Highly Similar Duplicated Genes in Eukaryotic Genomes

Gene duplication is an important evolutionary mechanism capable of providing new genetic material for adaptive and nonadaptive evolution. However, bioinformatics tools for identifying duplicate genes are often limited to the detection of paralogs in multiple species or to specific types of gene duplicates, such as retrocopies. Here, we present a user-friendly, BLAST-based web tool, called HSDFinder, which can identify, annotate, categorize, and visualize highly similar duplicate genes (HSDs) in eukaryotic nuclear genomes. HSDFinder includes an online heatmap plotting option, allowing users to compare HSDs among different species and visualize the results in different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional categories. The external software requirements are BLAST, InterProScan, and KEGG. The utility of HSDFinder was tested on various model eukaryotic species, including Chlamydomonas reinhardtii, Arabidopsis thaliana, Oryza sativa, and Zea mays as well as the psychrophilic green alga Chlamydomonas sp. UWO241, and was proven to be a practical and accurate tool for gene duplication analyses. The web tool is free to use at http://hsdfinder.com. Documentation and tutorials can be found via the GitHub: https://github.com/zx0223winner/HSDFinder.