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Phylogenomic data provide valuable opportunities for studying evolutionary rates and timescales. These analyses require theoretical and statistical tools based on molecular clocks. We present ClockstaRX, a flexible platform for exploring and testing evolutionary rate signals in phylogenomic data. Here, information about evolutionary rates in branches across gene trees is placed in Euclidean space, allowing data transformation, visualization, and hypothesis testing. ClockstaRX implements formal tests for identifying groups of loci and branches that make a large contribution to patterns of rate variation. This information can then be used to test for drivers of genomic evolutionary rates or to inform models for molecular dating. Drawing on the results of a simulation study, we recommend forms of data exploration and filtering that might be useful prior to molecular-clock analyses. [ABSTRACT FROM AUTHOR]

Birth–death models are stochastic processes describing speciation and extinction through time and across taxa and are widely used in biology for inference of evolutionary timescales. Previous research has highlighted how the expected trees under the constant-rate birth–death (crBD) model tend to differ from empirical trees, for example, with respect to the amount of phylogenetic imbalance. However, our understanding of how trees differ between the crBD model and the signal in empirical data remains incomplete. In this Point of View, we aim to expose the degree to which the crBD model differs from empirically inferred phylogenies and test the limits of the model in practice. Using a wide range of topology indices to compare crBD expectations against a comprehensive dataset of 1189 empirically estimated trees, we confirm that crBD model trees frequently differ topologically compared with empirical trees. To place this in the context of standard practice in the field, we conducted a meta-analysis for a subset of the empirical studies. When comparing studies that used Bayesian methods and crBD priors with those that used other non-crBD priors and non-Bayesian methods (i.e. maximum likelihood methods), we do not find any significant differences in tree topology inferences. To scrutinize this finding for the case of highly imbalanced trees, we selected the 100 trees with the greatest imbalance from our dataset, simulated sequence data for these tree topologies under various evolutionary rates, and re-inferred the trees under maximum likelihood and using the crBD model in a Bayesian setting. We find that when the substitution rate is low, the crBD prior results in overly balanced trees, but the tendency is negligible when substitution rates are sufficiently high. Overall, our findings demonstrate the general robustness of crBD priors across a broad range of phylogenetic inference scenarios but also highlight that empirically observed phylogenetic imbalance is highly improbable under the crBD model, leading to systematic bias in data sets with limited information content. [ABSTRACT FROM AUTHOR]

Phylogenetics is now fundamental in life sciences, providing insights into the earliest branches of life and the origins and spread of epidemics. However, finding suitable phylogenies from the vast space of possible trees remains challenging. To address this problem, for the first time, we perform both tree exploration and inference in a continuous space where the computation of gradients is possible. This continuous relaxation allows for major leaps across tree space in both rooted and unrooted trees, and is less susceptible to convergence to local minima. Our approach outperforms the current best methods for inference on unrooted trees and, in simulation, accurately infers the tree and root in ultrametric cases. The approach is effective in cases of empirical data with negligible amounts of data, which we demonstrate on the phylogeny of jawed vertebrates. Indeed, only a few genes with an ultrametric signal were generally sufficient for resolving the major lineages of vertebrates. Optimization is possible via automatic differentiation and our method presents an effective way forward for exploring the most difficult, data-deficient phylogenetic questions. [ABSTRACT FROM AUTHOR]

The impact of post‐divergence gene flow in speciation has been documented across a range of taxa in recent years, and may have been especially widespread in highly mobile, wide‐ranging marine species, such as cetaceans. Here, we studied individual genomes from nine species across the three families of the toothed whale superfamily Delphinoidea (Delphinidae, Phocoenidae and Monodontidae). To investigate the role of post‐divergence gene flow in the speciation process, we used a multifaceted approach, including (i) phylogenomics, (ii) the distribution of shared derived alleles and (iii) demographic inference. We found the divergence of lineages within Delphinoidea did not follow a process of pure bifurcation, but was much more complex. Sliding‐window phylogenomics reveal a high prevalence of discordant topologies within the superfamily, with further analyses indicating these discordances arose due to both incomplete lineage sorting and gene flow. D‐statistics and f‐branch analyses supported gene flow between members of Delphinoidea, with the vast majority of gene flow occurring as ancient interfamilial events. Demographic analyses provided evidence that introgressive gene flow has likely ceased between all species pairs tested, despite reports of contemporary interspecific hybrids. Our study provides the first steps towards resolving the large complexity of speciation within Delphinoidea; we reveal the prevalence of ancient interfamilial gene flow events prior to the diversification of each family, and suggest that contemporary hybridisation events may be disadvantageous, as hybrid individuals do not appear to contribute to the parental species' gene pools. [ABSTRACT FROM AUTHOR]

The blue antelope (Hippotragus leucophaeus) is the only large African mammal species to have become extinct in historical times, yet no nuclear genomic information is available for this species. A recent study showed that many alleged blue antelope museum specimens are either roan (Hippotragus equinus) or sable (Hippotragus niger) antelopes, further reducing the possibilities for obtaining genomic information for this extinct species. While the blue antelope has a rich fossil record from South Africa, climatic conditions in the region are generally unfavorable to the preservation of ancient DNA. Nevertheless, we recovered two blue antelope draft genomes, one at 3.4× mean coverage from a historical specimen (∼200 years old) and one at 2.1× mean coverage from a fossil specimen dating to 9,800–9,300 cal years BP, making it currently the oldest paleogenome from Africa. Phylogenomic analyses show that blue and sable antelope are sister species, confirming previous mitogenomic results, and demonstrate ancient gene flow from roan into blue antelope. We show that blue antelope genomic diversity was much lower than in roan and sable antelope, indicative of a low population size since at least the early Holocene. This supports observations from the fossil record documenting major decreases in the abundance of blue antelope after the Pleistocene–Holocene transition. Finally, the persistence of this species throughout the Holocene despite low population size suggests that colonial-era human impact was likely the decisive factor in the blue antelope's extinction. [ABSTRACT FROM AUTHOR]

Aim: Urbanization exposes species to novel ecological conditions. Some species thrive in urban areas, whereas many others are excluded from these human‐made environments. Previous analyses suggest that the ability to cope with rapid environmental change is associated with long‐term patterns of diversification, but whether the suite of traits associated with the ability to colonize urban environments is linked to this process remains poorly understood. Location: World. Time period: Current. Major taxa studied: Passerine birds. Methods: We applied macroevolutionary models to a large dataset of passerine birds to compare the evolutionary history of urban‐tolerant species with that of urban‐avoidant species. Specifically, we examined models of state‐dependent speciation and extinction to assess the macroevolution of urban tolerance as a binary trait, in addition to models of quantitative trait‐dependent diversification based on relative urban abundance. We also ran simulation‐based model assessments to explore potential sources of bias. Results: We provide evidence that historically, species with traits promoting urban colonization have undergone faster diversification than urban‐avoidant species, indicating that urbanization favours clades with a historical tendency towards rapid speciation or reduced extinction. In addition, we find that past transitions towards states that currently impede urban colonization by passerines have been more frequent than in the opposite direction. Furthermore, we find a portion of urban‐avoidant passerines to be recent and to undergo fast diversification. All highly supported models give this result consistently. Main conclusions Urbanization is mainly associated with the loss of lineages that are inherently more vulnerable to extinction over deep time, whereas cities tend to be colonized by less vulnerable lineages, for which urbanization might be neutral or positive in terms of longer‐term diversification. Urban avoidance is associated with high rates of recent diversification for some clades occurring in regions with relatively intact natural ecosystems and low current levels of urbanization. [ABSTRACT FROM AUTHOR]

Species of the mustelid subfamily Guloninae inhabit diverse habitats on multiple continents, and occupy a variety of ecological niches. They differ in feeding ecologies, reproductive strategies and morphological adaptations. To identify candidate loci associated with adaptations to their respective environments, we generated a de novo assembly of the tayra (Eira barbara), the earliest diverging species in the subfamily, and compared this with the genomes available for the wolverine (Gulo gulo) and the sable (Martes zibellina). Our comparative genomic analyses included searching for signs of positive selection, examining changes in gene family sizes and searching for species‐specific structural variants. Among candidate loci associated with phenotypic traits, we observed many related to diet, body condition and reproduction. For example, for the tayra, which has an atypical gulonine reproductive strategy of aseasonal breeding, we observed species‐specific changes in many pregnancy‐related genes. For the wolverine, a circumpolar hypercarnivore that must cope with seasonal food scarcity, we observed many changes in genes associated with diet and body condition. All types of genomic variation examined (single nucleotide polymorphisms, gene family expansions, structural variants) contributed substantially to the identification of candidate loci. This argues strongly for consideration of variation other than single nucleotide polymorphisms in comparative genomics studies aiming to identify loci of adaptive significance. [ABSTRACT FROM AUTHOR]

The historical signal in nucleotide sequences becomes eroded over time by substitutions occurring repeatedly at the same sites. This phenomenon, known as substitution saturation, is recognized as one of the primary obstacles to deep-time phylogenetic inference using genome-scale data sets. We present a new test of substitution saturation and demonstrate its performance in simulated and empirical data. For some of the 36 empirical phylogenomic data sets that we examined, we detect substitution saturation in around 50% of loci. We found that saturation tends to be flagged as problematic in loci with highly discordant phylogenetic signals across sites. Within each data set, the loci with smaller numbers of informative sites are more likely to be flagged as containing problematic levels of saturation. The entropy saturation test proposed here is sensitive to high evolutionary rates relative to the evolutionary timeframe, while also being sensitive to several factors known to mislead phylogenetic inference, including short internal branches relative to external branches, short nucleotide sequences, and tree imbalance. Our study demonstrates that excluding loci with substitution saturation can be an effective means of mitigating the negative impact of multiple substitutions on phylogenetic inferences. [Phylogenetic model performance; phylogenomics; substitution model; substitution saturation; test statistics.] [ABSTRACT FROM AUTHOR]

Phylogenetic analyses of genomic data provide a powerful means of reconstructing the evolutionary relationships among organisms, yet such analyses are often hindered by conflicting phylogenetic signals among loci. Identifying the signals that are most influential to species-tree estimation can help to inform the choice of data for phylogenomic analysis. We investigated this in an analysis of 30 phylogenomic data sets. For each data set, we examined the association between several branch-length characteristics of gene trees and the distance between these gene trees and the corresponding species trees. We found that the distance of each gene tree to the species tree inferred from the full data set was positively associated with variation in root-to-tip distances and negatively associated with mean branch support. However, no such associations were found for gene-tree length, a measure of the overall substitution rate at each locus. We further explored the usefulness of the best-performing branch-based characteristics for selecting loci for phylogenomic analyses. We found that loci that yield gene trees with high variation in root-to-tip distances have a disproportionately distant signal of tree topology compared with the complete data sets. These results suggest that rate variation across lineages should be taken into consideration when exploring and even selecting loci for phylogenomic analysis.[Branch support; data filtering; nucleotide substitution model; phylogenomics; substitution rate; summary coalescent methods.] [ABSTRACT FROM AUTHOR]

The reconstruction of evolutionary relationships among species is fundamental for our understanding of biodiversity. Today, evolutionary relationships are closely related with the depiction of the tree of life, and research on the topic is underpinned by methods in molecular phylogenetics that have grown in popularity since the 1960s. These methods depend on our understanding of how nucleotide or amino acid sequences evolve through time and in different lineages. Armed with this knowledge, researchers can make inferences about the relationships and amount of genomic divergence among species. David Duchêne introduces the reconstruction of phylogenetic trees from genomic data. [ABSTRACT FROM AUTHOR]

During the Miocene, Hyaenidae was a highly diverse family of Carnivora that has since been severely reduced to four species: the bone-cracking spotted, striped, and brown hyenas, and the specialized insectivorous aardwolf. Previous studies investigated the evolutionary histories of the spotted and brown hyenas, but little is known about the remaining two species. Moreover, the genomic underpinnings of scavenging and insectivory, defining traits of the extant species, remain elusive. Here, we generated an aardwolf genome and analyzed it together with the remaining three species to reveal their evolutionary relationships, genomic underpinnings of their scavenging and insectivorous lifestyles, and their respective genetic diversities and demographic histories. High levels of phylogenetic discordance suggest gene flow between the aardwolf lineage and the ancestral brown/striped hyena lineage. Genes related to immunity and digestion in the bone-cracking hyenas and craniofacial development in the aardwolf showed the strongest signals of selection, suggesting putative key adaptations to carrion and termite feeding, respectively. A family-wide expansion in olfactory receptor genes suggests that an acute sense of smell was a key early adaptation. Finally, we report very low levels of genetic diversity within the brown and striped hyenas despite no signs of inbreeding, putatively linked to their similarly slow decline in effective population size over the last ∼2 million years. High levels of genetic diversity and more stable population sizes through time are seen in the spotted hyena and aardwolf. Taken together, our findings highlight how ecological specialization can impact the evolutionary history, demographics, and adaptive genetic changes of an evolutionary lineage. [ABSTRACT FROM AUTHOR]

Evolution leaves heterogeneous patterns of nucleotide variation across the genome, with different loci subject to varying degrees of mutation, selection, and drift. In phylogenetics, the potential impacts of partitioning sequence data for the assignment of substitution models are well appreciated. In contrast, the treatment of branch lengths has received far less attention. In this study, we examined the effects of linking and unlinking branch-length parameters across loci or subsets of loci. By analyzing a range of empirical data sets, we find consistent support for a model in which branch lengths are proportionate between subsets of loci: gene trees share the same pattern of branch lengths, but form subsets that vary in their overall tree lengths. These models had substantially better statistical support than models that assume identical branch lengths across gene trees, or those in which genes form subsets with distinct branch-length patterns. We show using simulations and empirical data that the complexity of the branch-length model with the highest support depends on the length of the sequence alignment and on the numbers of taxa and loci in the data set. Our findings suggest that models in which branch lengths are proportionate between subsets have the highest statistical support under the conditions that are most commonly seen in practice. The results of our study have implications for model selection, computational efficiency, and experimental design in phylogenomics. [ABSTRACT FROM AUTHOR]

Statistical phylogenetic analyses of genomic data depend on models of nucleotide or amino acid substitution. The adequacy of these substitution models can be assessed using a number of test statistics, allowing the model to be rejected when it is found to provide a poor description of the evolutionary process. A potentially valuable use of model-adequacy test statistics is to identify when data sets are likely to produce unreliable phylogenetic estimates, but their differences in performance are rarely explored. We performed a comprehensive simulation study to identify test statistics that are sensitive to some of the most commonly cited sources of phylogenetic estimation error. Our results show that, for many test statistics, traditional thresholds for assessing model adequacy can fail to reject the model when the phylogenetic inferences are inaccurate and imprecise. This is particularly problematic when analysing loci that have few informative sites. We propose new thresholds for assessing substitution model adequacy and demonstrate their effectiveness in analyses of three phylogenomic data sets. These thresholds lead to frequent rejection of the model for loci that yield topological inferences that are imprecise and are likely to be inaccurate. We also propose the use of a summary statistic that provides a practical assessment of overall model adequacy. Our approach offers a promising means of enhancing model choice in genome-scale data sets, potentially leading to improvements in the reliability of phylogenomic inference. [ABSTRACT FROM AUTHOR]

ABSTRACT: Molecular dating analyses allow evolutionary timescales to be estimated from genetic data, offering an unprecedented capacity for investigating the evolutionary past of all species. These methods require us to make assumptions about the relationship between genetic change and evolutionary time, often referred to as a ‘molecular clock’. Although initially regarded with scepticism, molecular dating has now been adopted in many areas of biology. This broad uptake has been due partly to the development of Bayesian methods that allow complex aspects of molecular evolution, such as variation in rates of change across lineages, to be taken into account. But in order to do this, Bayesian dating methods rely on a range of assumptions about the evolutionary process, which vary in their degree of biological realism and empirical support. These assumptions can have substantial impacts on the estimates produced by molecular dating analyses. The aim of this review is to open the ‘black box’ of Bayesian molecular dating and have a look at the machinery inside. We explain the components of these dating methods, the important decisions that researchers must make in their analyses, and the factors that need to be considered when interpreting results. We illustrate the effects that the choices of different models and priors can have on the outcome of the analysis, and suggest ways to explore these impacts. We describe some major research directions that may improve the reliability of Bayesian dating. The goal of our review is to help researchers to make informed choices when using Bayesian phylogenetic methods to estimate evolutionary rates and timescales. [ABSTRACT FROM AUTHOR]

The brain plays a critical role in a wide variety of functions including behaviour, perception, motor control, and homeostatic maintenance. Each function can undergo different selective pressures over the course of evolution, and as selection acts on the outputs of brain function, it necessarily alters the structure of the brain. Two models have been proposed to explain the evolutionary patterns observed in brain morphology. The concerted brain evolution model posits that the brain evolves as a single unit and the evolution of different brain regions are coordinated. The mosaic brain evolution model posits that brain regions evolve independently of each other. It is now understood that both models are responsible for driving changes in brain morphology; however, which factors favour concerted or mosaic brain evolution is unclear. Here, we examined the volumes of the 6 major neural subdivisions across 14 species of the agamid lizard genus Ctenophorus (dragons). These species have diverged multiple times in behaviour, ecology, and body morphology, affording a unique opportunity to test neuroevolutionary models across species. We assigned each species to an ecomorph based on habitat use and refuge type, then used MRI to measure total and regional brain volume. We found evidence for both mosaic and concerted brain evolution in dragons: concerted brain evolution with respect to body size, and mosaic brain evolution with respect to ecomorph. Specifically, all brain subdivisions increase in volume relative to body size, yet the tectum and rhombencephalon also show opposite patterns of evolution with respect to ecomorph. Therefore, we find that both models of evolution are occurring simultaneously in the same structures in dragons, but are only detectable when examining particular drivers of selection. We show that the answer to the question of whether concerted or mosaic brain evolution is detected in a system can depend more on the type of selection measured than on the clade of animals studied. [ABSTRACT FROM AUTHOR]

In statistical phylogenetic analyses of DNA sequences, models of evolutionary change commonly assume that base composition is stationary through time and across lineages. This assumption is violated by many data sets, but it is unclear whether the magnitude of these violations is sufficient to mislead phylogenetic inference. We investigated the impacts of compositional heterogeneity on phylogenetic estimates using a method for assessing model adequacy. Based on a detailed simulation study, we found that common frequentist criteria are highly conservative, such that the model is often rejected when the phylogenetic estimates do not show clear signs of bias. We propose new criteria and provide guidelines for their usage. We apply these criteria to genome-scale data from 40 birds and find that loci with severely non-homogeneous base composition are uncommon. Our results show the importance of using well-informed diagnostic statistics when testing model adequacy for phylogenomic analyses. [ABSTRACT FROM AUTHOR]

Themolecularclockisavaluableandwidelyusedtoolforestimatingevolutionaryratesandtimescalesinbiologicalresearch.Therehas beenconsiderableprogressinthetheoryandpracticeofmolecularclocksoverthepastfivedecades.Althoughtheideaofamolecular clock was originally put forward in the context of protein evolution and advanced using various biochemical techniques, it is now primarily applied to analyses of DNA sequences. An interesting but very underappreciated aspect of molecular clocks is that they can be based on genetic data other than DNA or protein sequences. For example, evolutionary timescales can be estimated using microsatellites, protein folds, and even the extent of recombination. These genome features hold great potential for molecular dating, particularly in cases where nucleotide sequences might be uninformative or unreliable. Here we present an outline of the differentgeneticdatatypesthathavebeenusedformoleculardating,andwedescribethefeaturesthatgoodmolecularclocksshould possess. We hope that our article inspires further work on the genome as an evolutionary timepiece. [ABSTRACT FROM AUTHOR]

Background: Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. Results: We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Conclusions: Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult. [ABSTRACT FROM AUTHOR]

Molecular clock models are commonly used to estimate evolutionary rates and timescales from nucleotide sequences. The goal of these models is to account for rate variation among lineages, such that they are assumed to be adequate descriptions of the processes that generated the data. A common approach for selecting a clock model for a data set of interest is to examine a set of candidates and to select the model that provides the best statistical fit. However, this can lead to unreliable estimates if all the candidate models are actually inadequate. For this reason, a method of evaluating absolute model performance is critical. We describe a method that uses posterior predictive simulations to assess the adequacy of clock models. We test the power of this approach using simulated data and find that the method is sensitive to bias in the estimates of branch lengths, which tends to occur when using underparameterized clock models. We also compare the performance of the multinomial test statistic, originally developed to assess the adequacy of substitution models, but find that it has low power in identifying the adequacy of clock models. We illustrate the performance of our method using empirical data sets from coronaviruses, simian immunodeficiency virus, killer whales, and marine turtles. Our results indicate that methods of investigating model adequacy, including the one proposed here, should be routinely used in combination with traditional model selection in evolutionary studies. This will reveal whether a broader range of clock models to be considered in phylogenetic analysis. [ABSTRACT FROM AUTHOR]

Phylogenetic estimation of evolutionary timescales has become routine in biology, forming the basis of a wide range of evolutionary and ecological studies. However, there are various sources of bias that can affect these estimates. We investigated whether tree imbalance, a property that is commonly observed in phylogenetic trees, can lead to reduced accuracy or precision of phylogenetic timescale estimates. We analysed simulated data sets with calibrations at internal nodes and at the tips, taking into consideration different calibration schemes and levels of tree imbalance. We also investigated the effect of tree imbalance on two empirical data sets: mitogenomes from primates and serial samples of the African swine fever virus. In analyses calibrated using dated, heterochronous tips, we found that tree imbalance had a detrimental impact on precision and produced a bias in which the overall timescale was underestimated. A pronounced effect was observed in analyses with shallow calibrations. The greatest decreases in accuracy usually occurred in the age estimates for medium and deep nodes of the tree. In contrast, analyses calibrated at internal nodes did not display a reduction in estimation accuracy or precision due to tree imbalance. Our results suggest that molecular-clock analyses can be improved by increasing taxon sampling, with the specific aims of including deeper calibrations, breaking up long branches and reducing tree imbalance. [ABSTRACT FROM AUTHOR]

Evolutionary timescales can be estimated from genetic data using phylogenetic methods based on the molecular clock. To account for molecular rate variation among lineages, a number of relaxed-clock models have been developed. Some of these models assume that rates vary among lineages in an autocorrelated manner, so that closely related species share similar rates. In contrast, uncorrelated relaxed clocks allow all of the branch-specific rates to be drawn from a single distribution, without assuming any correlation between rates along neighbouring branches. There is uncertainty about which of these two classes of relaxed-clock models are more appropriate for biological data. We present an R package, NELSI, that allows the evolution of DNA sequences to be simulated according to a range of clock models. Using data generated by this package, we assessed the ability of two Bayesian phylogenetic methods to distinguish among different relaxed-clock models and to quantify rate variation among lineages. The results of our analyses show that rate autocorrelation is typically difficult to detect, even when there is complete taxon sampling. This provides a potential explanation for past failures to detect rate autocorrelation in a range of data sets. [ABSTRACT FROM AUTHOR]

Three principal methods are under discussion as possible pathways to "true" de-extinction; i.e., back-breeding, cloning, and genetic engineering. 1,2 Of these, while the latter approach is most likely to apply to the largest number of extinct species, its potential is constrained by the degree to which the extinct species genome can be reconstructed. We explore this question using the extinct Christmas Island rat (Rattus macleari) as a model, an endemic rat species that was driven extinct between 1898 and 1908. 3–5 We first re-sequenced its genome to an average of >60× coverage, then mapped it to the reference genomes of different Rattus species. We then explored how evolutionary divergence from the extant reference genome affected the fraction of the Christmas Island rat genome that could be recovered. Our analyses show that even when the extremely high-quality Norway brown rat (R. norvegicus) is used as a reference, nearly 5% of the genome sequence is unrecoverable, with 1,661 genes recovered at lower than 90% completeness, and 26 completely absent. Furthermore, we find the distribution of regions affected is not random, but for example, if 90% completeness is used as the cutoff, genes related to immune response and olfaction are excessively affected. Ultimately, our approach demonstrates the importance of applying similar analyses to candidates for de-extinction through genome editing in order to provide critical baseline information about how representative the edited form would be of the extinct species. • Evolutionary divergence limits the completeness of extinct species genomes • The extinct Christmas Island rat was re-sequenced to ca. 60× coverage • Nevertheless, 4.85% of the Norway brown rat genome remains absent after mapping • Absences are not random; immune response and olfaction are excessively affected Lin et al. explore how evolutionary divergence constrains the potential of de-extinction, using the Christmas Island rat as a model. Although 95% of its genome is recovered when re-sequenced at high depth, regions that remain unmapped to the reference likely have significant consequences for any attempt at de-extinction using genome editing. [ABSTRACT FROM AUTHOR]