Patterns of de novo tandem repeat mutations and their role in autism.

Autism spectrum disorder (ASD) is an early-onset developmental disorder characterized by deficits in communication and social interaction and restrictive or repetitive behaviours1,2. Family studies demonstrate that ASD has a substantial genetic basis with contributions both from inherited and de novo variants3,4. It has been estimated that de novo mutations may contribute to 30% of all simplex cases, in which only a single child is affected per family5. Tandem repeats (TRs), defined here as sequences of 1 to 20 base pairs in size repeated consecutively, comprise one of the major sources of de novo mutations in humans6. TR expansions are implicated in dozens of neurological and psychiatric disorders7. Yet, de novo TR mutations have not been characterized on a genome-wide scale, and their contribution to ASD remains unexplored. Here we develop new bioinformatics methods for identifying and prioritizing de novo TR mutations from sequencing data and perform a genome-wide characterization of de novo TR mutations in ASD-affected probands and unaffected siblings. We infer specific mutation events and their precise changes in repeat number, and primarily focus on more prevalent stepwise copy number changes rather than large expansions. Our results demonstrate a significant genome-wide excess of TR mutations in ASD probands. Mutations in probands tend to be larger, enriched in fetal brain regulatory regions, and are predicted to be more evolutionarily deleterious. Overall, our results highlight the importance of considering repeat variants in future studies of de novo mutations.

Inferring the mode and strength of ongoing selection.

Genome sequence data are no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics toward sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences but are not optimized for extracting the information contained in the larger and richer data sets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called trio-based inference of dominance and selection (TIDES) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state of the art by making no assumptions regarding demography, linkage, or dominance. We discuss how our method paves the way for studying natural selection from new angles.

Skeleton of a Cretaceous mammal from Madagascar reflects long-term insularity.

The fossil record of mammaliaforms (mammals and their closest relatives) of the Mesozoic era from the southern supercontinent Gondwana is far less extensive than that from its northern counterpart, Laurasia1,2. Among Mesozoic mammaliaforms, Gondwanatheria is one of the most poorly known clades, previously represented by only a single cranium and isolated jaws and teeth1-5. As a result, the anatomy, palaeobiology and phylogenetic relationships of gondwanatherians remain unclear. Here we report the discovery of an articulated and very well-preserved skeleton of a gondwanatherian of the latest age (72.1-66 million years ago) of the Cretaceous period from Madagascar that we assign to a new genus and species, Adalatherium hui. To our knowledge, the specimen is the most complete skeleton of a Gondwanan Mesozoic mammaliaform that has been found, and includes the only postcranial material and ascending ramus of the dentary known for any gondwanatherian. A phylogenetic analysis including the new taxon recovers Gondwanatheria as the sister group to Multituberculata. The skeleton, which represents one of the largest of the Gondwanan Mesozoic mammaliaforms, is particularly notable for exhibiting many unique features in combination with features that are convergent on those of therian mammals. This uniqueness is consistent with a lineage history for A. hui of isolation on Madagascar for more than 20 million years.

MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations.

Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.

Long-term Small Population Size, Deleterious Variation, and Altitude Adaptation in the Ethiopian Wolf, a Severely Endangered Canid.

Ethiopian wolves, a canid species endemic to the Ethiopian Highlands, have been steadily declining in numbers for decades. Currently, out of 35 extant species, it is now one of the world's most endangered canids. Most conservation efforts have focused on preventing disease, monitoring movements and behavior, and assessing the geographic ranges of sub-populations. Here, we add an essential layer by determining the Ethiopian wolf's demographic and evolutionary history using high-coverage (∼40×) whole-genome sequencing from 10 Ethiopian wolves from the Bale Mountains. We observe exceptionally low diversity and enrichment of weakly deleterious variants in the Ethiopian wolves in comparison with two North American gray wolf populations and four dog breeds. These patterns are consequences of long-term small population size, rather than recent inbreeding. We infer the demographic history of the Ethiopian wolf and find it to be concordant with historic records and previous genetic analyses, suggesting Ethiopian wolves experienced a series of both ancient and recent bottlenecks, resulting in a census population size of fewer than 500 individuals and an estimated effective population size of approximately 100 individuals. Additionally, long-term small population size may have limited the accumulation of strongly deleterious recessive mutations. Finally, as the Ethiopian wolves have inhabited high-altitude areas for thousands of years, we searched for evidence of high-altitude adaptation, finding evidence of positive selection at a transcription factor in a hypoxia-response pathway [CREB-binding protein (CREBBP)]. Our findings are pertinent to continuing conservation efforts and understanding how demography influences the persistence of deleterious variation in small populations.

Genomic Underpinnings of Population Persistence in Isle Royale Moose.

Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.

In vivo evaluation of Clostridioides difficile enoyl-ACP reductase II (FabK) inhibition by phenylimidazole unveils a promising narrow-spectrum antimicrobial strategy.

Clostridioides difficile infection (CDI) is a leading cause of hospital-acquired diarrhea, which often stems from disruption of the gut microbiota by broad-spectrum antibiotics. The increasing prevalence of antibiotic-resistant C. difficile strains, combined with disappointing clinical trial results for recent antibiotic candidates, underscores the urgent need for novel CDI antibiotics. To this end, we investigated C. difficile enoyl ACP reductase (CdFabK), a crucial enzyme in de novo fatty acid synthesis, as a drug target for microbiome-sparing antibiotics. To test this concept, we evaluated the efficacy and in vivo spectrum of activity of the phenylimidazole analog 296, which is validated to inhibit intracellular CdFabK. Against major CDI-associated ribotypes 296 had an Minimum inhibitory concentration (MIC90) of 2 µg/mL, which was comparable to vancomycin (1 µg/mL), a standard of care antibiotic. In addition, 296 achieved high colonic concentrations and displayed dosed-dependent efficacy in mice with colitis CDI. Mice that were given 296 retained colonization resistance to C. difficile and had microbiomes that resembled the untreated mice. Conversely, both vancomycin and fidaxomicin induced significant changes to mice microbiomes, in a manner consistent with prior reports. CdFabK, therefore, represents a potential target for microbiome-sparing CDI antibiotics, with phenylimidazoles providing a good chemical starting point for designing such agents.

Negative selection on complex traits limits phenotype prediction accuracy between populations.

Phenotype prediction is a key goal for medical genetics. Unfortunately, most genome-wide association studies are done in European populations, which reduces the accuracy of predictions via polygenic scores in non-European populations. Here, we use population genetic models to show that human demographic history and negative selection on complex traits can result in population-specific genetic architectures. For traits where alleles with the largest effect on the trait are under the strongest negative selection, approximately half of the heritability can be accounted for by variants in Europe that are absent from Africa, leading to poor performance in phenotype prediction across these populations. Further, under such a model, individuals in the tails of the genetic risk distribution may not be identified via polygenic scores generated in another population. We empirically test these predictions by building a model to stratify heritability between European-specific and shared variants and applied it to 37 traits and diseases in the UK Biobank. Across these phenotypes, ∼30% of the heritability comes from European-specific variants. We conclude that genetic association studies need to include more diverse populations to enable the utility of phenotype prediction in all populations.

Biophysical library screening using a Thermo-FMN assay to identify and characterize Clostridioides difficile FabK inhibitors.

Clostridioides difficile, a gram-positive anaerobic bacterium, is one of the most frequent causes of nosocomial infections. C. difficile infection (CDI) results in almost a half a million infections and approximately 30,000 deaths in the U.S. each year. Broad-spectrum antibacterial use is a strong risk factor for development of recurring CDI. There is a critical need for narrow-spectrum antibacterials with activity limited to C. difficile. The C. difficile enoyl-acyl carrier protein (ACP) reductase II enzyme (CdFabK), an essential and rate-limiting enzyme in the organism's fatty acid biosynthesis pathway (FAS-2), is an attractive target for narrow-spectrum CDI therapeutics as it is not present in many of the non-pathogenic gut organisms. We have previously characterized inhibitors of the CdFabK enzyme with narrow-spectrum anti-difficile activity and favorable in vivo efficacy, ADME, and low dysbiosis. To expand our knowledge of the structural requirements for CdFabK inhibition, we seek to identify new inhibitors with novel chemical scaffolds. Herein we present the optimization of a thermo-FMN biophysical assay based on the principles of differential scanning fluorimetry, or thermal shift, which leverages the fluorescence signal of the FabK enzyme's FMN prosthetic group. The optimized assay was validated by pilot testing a 10K diversity-based chemical library and novel scaffold hit compounds were identified and biochemically characterized. Additionally, we show that the thermo-FMN assay can be used to determine the thermodynamic dissociation constant, Kd, of CdFabK inhibitors.

Greater strength of selection and higher proportion of beneficial amino acid changing mutations in humans compared with mice and Drosophila melanogaster.

Quantifying and comparing the amount of adaptive evolution among different species is key to understanding how evolution works. Previous studies have shown differences in adaptive evolution across species; however, their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and ancestral population and estimate that at least 20% of nonsynonymous substitutions between humans and an outgroup species were fixed by positive selection. This estimate is much higher than previous estimates, which did not correct for the sizes of the outgroup species and ancestral population. Next, we jointly estimate the proportion and selection coefficient (p + and s +, respectively) of newly arising beneficial nonsynonymous mutations in humans, mice, and Drosophila melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same p + and s + of beneficial mutations across species and estimate that humans have a higher p+s + compared with that of D. melanogaster and mice. We show that this result cannot be caused by biased gene conversion or hypermutable CpG sites. We discuss possible biological explanations that could generate the observed differences in the amount of adaptive evolution across species.

The influence of gene flow on population viability in an isolated urban caracal population.

Wildlife populations are becoming increasingly fragmented by anthropogenic development. Small and isolated populations often face an elevated risk of extinction, in part due to inbreeding depression. Here, we examine the genomic consequences of urbanization in a caracal (Caracal caracal) population that has become isolated in the Cape Peninsula region of the City of Cape Town, South Africa, and is thought to number ~50 individuals. We document low levels of migration into the population over the past ~75 years, with an estimated rate of 1.3 effective migrants per generation. As a consequence of this isolation and small population size, levels of inbreeding are elevated in the contemporary Cape Peninsula population (mean FROH = 0.20). Inbreeding primarily manifests as long runs of homozygosity >10 Mb, consistent with the effects of isolation due to the rapid recent growth of Cape Town. To explore how reduced migration and elevated inbreeding may impact future population dynamics, we parameterized an eco-evolutionary simulation model. We find that if migration rates do not change in the future, the population is expected to decline, though with a low projected risk of extinction. However, if migration rates decline or anthropogenic mortality rates increase, the potential risk of extinction is greatly elevated. To avert a population decline, we suggest that translocating migrants into the Cape Peninsula to initiate a genetic rescue may be warranted in the near future. Our analysis highlights the utility of genomic datasets coupled with computational simulation models for investigating the influence of gene flow on population viability.

Updating M6 pregnancy of unknown location risk-prediction model including evaluation of clinical factors.

OBJECTIVES: Ectopic pregnancy (EP) is a major high-risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow-up. The M6 model is currently the best risk-prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors. METHODS: This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for ß-human chorionic gonadotropin (ß-hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow-up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P ) and without (M6NP ) progesterone were refitted and extended with clinical factors. Model validation was performed using internal-external cross-validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation. RESULTS: Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial ß-hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver-operating-characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84-0.88 for EV, with respective sensitivities of 94% and 92-93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82-0.86 for EV, with respective sensitivities of 92% and 93-94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between -0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between -0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by -0.02 to -0.01, specificity by 0.03 to 0.04 and Net Benefit by -0.005 to 0.006. Extending M6NP altered sensitivity by -0.03 to -0.01, specificity by 0.05 to 0.07 and Net Benefit by -0.005 to 0.006. CONCLUSIONS: The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Negative linkage disequilibrium between amino acid changing variants reveals interference among deleterious mutations in the human genome.

Evolutionary forces like Hill-Robertson interference and negative epistasis can lead to deleterious mutations being found on distinct haplotypes. However, the extent to which these forces depend on the selection and dominance coefficients of deleterious mutations and shape genome-wide patterns of linkage disequilibrium (LD) in natural populations with complex demographic histories has not been tested. In this study, we first used forward-in-time simulations to predict how negative selection impacts LD. Under models where deleterious mutations have additive effects on fitness, deleterious variants less than 10 kb apart tend to be carried on different haplotypes relative to pairs of synonymous SNPs. In contrast, for recessive mutations, there is no consistent ordering of how selection coefficients affect LD decay, due to the complex interplay of different evolutionary effects. We then examined empirical data of modern humans from the 1000 Genomes Project. LD between derived alleles at nonsynonymous SNPs is lower compared to pairs of derived synonymous variants, suggesting that nonsynonymous derived alleles tend to occur on different haplotypes more than synonymous variants. This result holds when controlling for potential confounding factors by matching SNPs for frequency in the sample (allele count), physical distance, magnitude of background selection, and genetic distance between pairs of variants. Lastly, we introduce a new statistic HR(j) which allows us to detect interference using unphased genotypes. Application of this approach to high-coverage human genome sequences confirms our finding that nonsynonymous derived alleles tend to be located on different haplotypes more often than are synonymous derived alleles. Our findings suggest that interference may play a pervasive role in shaping patterns of LD between deleterious variants in the human genome, and consequently influences genome-wide patterns of LD.

The impact of identity by descent on fitness and disease in dogs.

Domestic dogs have experienced population bottlenecks, recent inbreeding, and strong artificial selection. These processes have simplified the genetic architecture of complex traits, allowed deleterious variation to persist, and increased both identity-by-descent (IBD) segments and runs of homozygosity (ROH). As such, dogs provide an excellent model for examining how these evolutionary processes influence disease. We assembled a dataset containing 4,414 breed dogs, 327 village dogs, and 380 wolves genotyped at 117,288 markers and data for clinical and morphological phenotypes. Breed dogs have an enrichment of IBD and ROH, relative to both village dogs and wolves, and we use these patterns to show that breed dogs have experienced differing severities of bottlenecks in their recent past. We then found that ROH burden is associated with phenotypes in breed dogs, such as lymphoma. We next test the prediction that breeds with greater ROH have more disease alleles reported in the Online Mendelian Inheritance in Animals (OMIA). Surprisingly, the number of causal variants identified correlates with the popularity of that breed rather than the ROH or IBD burden, suggesting an ascertainment bias in OMIA. Lastly, we use the distribution of ROH across the genome to identify genes with depletions of ROH as potential hotspots for inbreeding depression and find multiple exons where ROH are never observed. Our results suggest that inbreeding has played a large role in shaping genetic and phenotypic variation in dogs and that future work on understudied breeds may reveal new disease-causing variation.

A signature of Neanderthal introgression on molecular mechanisms of environmental responses.

Ancient human migrations led to the settlement of population groups in varied environmental contexts worldwide. The extent to which adaptation to local environments has shaped human genetic diversity is a longstanding question in human evolution. Recent studies have suggested that introgression of archaic alleles in the genome of modern humans may have contributed to adaptation to environmental pressures such as pathogen exposure. Functional genomic studies have demonstrated that variation in gene expression across individuals and in response to environmental perturbations is a main mechanism underlying complex trait variation. We considered gene expression response to in vitro treatments as a molecular phenotype to identify genes and regulatory variants that may have played an important role in adaptations to local environments. We investigated if Neanderthal introgression in the human genome may contribute to the transcriptional response to environmental perturbations. To this end we used eQTLs for genes differentially expressed in a panel of 52 cellular environments, resulting from 5 cell types and 26 treatments, including hormones, vitamins, drugs, and environmental contaminants. We found that SNPs with introgressed Neanderthal alleles (N-SNPs) disrupt binding of transcription factors important for environmental responses, including ionizing radiation and hypoxia, and for glucose metabolism. We identified an enrichment for N-SNPs among eQTLs for genes differentially expressed in response to 8 treatments, including glucocorticoids, caffeine, and vitamin D. Using Massively Parallel Reporter Assays (MPRA) data, we validated the regulatory function of 21 introgressed Neanderthal variants in the human genome, corresponding to 8 eQTLs regulating 15 genes that respond to environmental perturbations. These findings expand the set of environments where archaic introgression may have contributed to adaptations to local environments in modern humans and provide experimental validation for the regulatory function of introgressed variants.

Association of Gabapentinoids With Opioid-Related Overdose in the Inpatient Setting: A Single Center Retrospective Case-Control Study.

Objectives: Recent data suggest concomitant gabapentinoid use increases opioid-related overdose (ORO) risk; however, this association has not been well studied in the hospital setting. The primary objective of this study was to compare ORO risk, indicated by naloxone administration, in patients receiving opioids plus gabapentinoids versus opioids alone. Methods: In this retrospective case-control study of adults admitted to a large community hospital from 1/1/20 to 12/31/21, all cases (defined as patients who received naloxone more than 24 hours after admission) identified were matched 1:1 to randomly selected controls (defined as patients on opioids who did not receive naloxone). The primary outcome was the percentage of cases and controls with concomitant inpatient gabapentinoid use. Logistic regression was performed to determine the independent association between gabapentinoids and ORO (as evidenced by inpatient naloxone administration). Results: Baseline characteristics were similar between the 144 cases and 144 controls. Gabapentinoid exposure was greater for cases than controls (34.0%vs 20.8%, P = .0118). Median hospital length of stay (11vs 4 days, P < .0001) and mortality (19%vs 5%; P = .0018) were also higher for cases. In logistic regression analysis, ORO (adjusted OR 4.91; 95% CI 1.86-12.96) and serotonergic medication exposure (adjusted OR 4.31; 95% CI 1.50-12.38) were significantly associated with gabapentinoid use. Conclusions: Concomitant gabapentinoid use with opioids was associated with increased ORO risk in the inpatient setting. When considering prescribing gabapentinoids in conjunction with opioids in the hospital setting, potential benefits should be weighed against increased overdose risk.

Fatal Human Rabies Infection With Suspected Host-Mediated Failure of Post-Exposure Prophylaxis Following a Recognized Zoonotic Exposure-Minnesota, 2021.

BACKGROUND: No human rabies post-exposure prophylaxis (PEP) failure has been documented in the United States using modern cell culture-based vaccines. In January 2021, an 84-year-old male died from rabies 6 months after being bitten by a rabid bat despite receiving timely rabies PEP. We investigated the cause of breakthrough infection. METHODS: We reviewed medical records, laboratory results, and autopsy findings and performed whole-genome sequencing (WGS) to compare patient and bat virus sequences. Storage, administration, and integrity of PEP biologics administered to the patient were assessed; samples from leftover rabies immunoglobulin were evaluated for potency. We conducted risk assessments for persons potentially exposed to the bat and for close patient contacts. RESULTS: Rabies virus antibodies present in serum and cerebrospinal fluid were nonneutralizing. Antemortem blood testing revealed that the patient had unrecognized monoclonal gammopathy of unknown significance. Autopsy findings showed rabies meningoencephalitis and metastatic prostatic adenocarcinoma. Rabies virus sequences from the patient and the offending bat were identical by WGS. No deviations were identified in potency, quality control, administration, or storage of administered PEP. Of 332 persons assessed for potential rabies exposure to the case patient, 3 (0.9%) warranted PEP. CONCLUSIONS: This is the first reported failure of rabies PEP in the Western Hemisphere using a cell culture-based vaccine. Host-mediated primary vaccine failure attributed to previously unrecognized impaired immunity is the most likely explanation for this breakthrough infection. Clinicians should consider measuring rabies neutralizing antibody titers after completion of PEP if there is any suspicion for immunocompromise.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations.

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Genomic analyses reveal range-wide devastation of sea otter populations.

The genetic consequences of species-wide declines are rarely quantified because the timing and extent of the decline varies across the species' range. The sea otter (Enhydra lutris) is a unique model in this regard. Their dramatic decline from thousands to fewer than 100 individuals per population occurred range-wide and nearly simultaneously due to the 18th-19th century fur trade. Consequently, each sea otter population represents an independent natural experiment of recovery after extreme population decline. We designed sequence capture probes for 50 Mb of sea otter exonic and neutral genomic regions. We sequenced 107 sea otters from five populations that span the species range to high coverage (18-76×) and three historical Californian samples from ~1500 and ~200 years ago to low coverage (1.5-3.5×). We observe distinct population structure and find that sea otters in California are the last survivors of a divergent lineage isolated for thousands of years and therefore warrant special conservation concern. We detect signals of extreme population decline in every surviving sea otter population and use this demographic history to design forward-in-time simulations of coding sequence. Our simulations indicate that this decline could lower the fitness of recovering populations for generations. However, the simulations also demonstrate how historically low effective population sizes prior to the fur trade may have mitigated the effects of population decline on genetic health. Our comprehensive approach shows how demographic inference from genomic data, coupled with simulations, allows assessment of extinction risk and different models of recovery.

Euarchontans from Fantasia, an upland middle Eocene locality at the western margin of the Bighorn Basin.

The fossil record of North American Eocene mammals is best known from relatively low-elevation 'basin center' fossil localities in intermontane depositional basins of the Western Interior. This sampling bias, largely drawn from preservational bias, has limited our understanding of fauna from higher elevation Eocene fossil localities. Here we describe new specimens of crown primates and microsyopid plesiadapiforms from a middle Eocene (Bridgerian) locality ('Fantasia') from the western margin of the Bighorn Basin in Wyoming. Fantasia has been considered a 'basin-margin' site and geological evidence suggests that it was already at a high elevation relative to the basin center at the time of deposition. New specimens were described and identified using comparisons across museum collections and published faunal descriptions. Linear measurements were used to characterize the patterns of variation in dental size. Contrary to expectations derived from other Eocene basin-margin sites in the Rocky Mountains, Fantasia has low anaptomorphine omomyid diversity and lacks evidence for the co-occurrence of ancestor-descendant pairs. Fantasia also differs from other Bridgerian sites in having low abundance of Omomys and unusual body sizes of several euarchontan taxa. Some specimens of Anaptomorphus and cf. Omomys are larger than those found in coeval sites, while specimens of Notharctus and Microsyops are intermediate in size between middle and late Bridgerian samples of these genera from basin-center sites. These findings suggest that high elevation fossil localities like Fantasia may record atypical faunal samples that should be more thoroughly explored to understand faunal dynamics during the periods of significant regional uplift like that represented by the middle Eocene record of the Rocky Mountains. Furthermore, modern faunal data indicate that species body mass may be influenced by elevation, which may further complicate the use of body mass to determine species identity in the fossil record in the regions of high topographic relief.