High genetic load without purging in caribou, a diverse species at risk.

High intra-specific genetic diversity is associated with adaptive potential, which is key for resilience to global change. However, high variation may also support deleterious alleles through genetic load, thereby increasing the risk of inbreeding depression if population sizes decrease. Purging of deleterious variation has been demonstrated in some threatened species. However, less is known about the costs of declines and inbreeding in species with large population sizes and high genetic diversity even though this encompasses many species globally that are expected to undergo population declines. Caribou is a species of ecological and cultural significance in North America with a wide distribution supporting extensive phenotypic variation but with some populations undergoing significant declines resulting in their at-risk status in Canada. We assessed intra-specific genetic variation, adaptive divergence, inbreeding, and genetic load across populations with different demographic histories using an annotated chromosome-scale reference genome and 66 whole-genome sequences. We found high genetic diversity and nine phylogenomic lineages across the continent with adaptive diversification of genes, but also high genetic load among lineages. We found highly divergent levels of inbreeding across individuals, including the loss of alleles by drift but not increased purging in inbred individuals, which had more homozygous deleterious alleles. We also found comparable frequencies of homozygous deleterious alleles between lineages regardless of nucleotide diversity. Thus, further inbreeding may need to be mitigated through conservation efforts. Our results highlight the "double-edged sword" of genetic diversity that may be representative of other species atrisk affected by anthropogenic activities.

Phased genome assemblies reveal haplotype-specific genetic load in the critically endangered Chinese Bahaba (Teleostei, Sciaenidae).

While haplotype-specific genetic load shapes the evolutionary trajectory of natural and captive populations, mixed-haplotype assembly and genotyping hindered its characterization in diploids. Herein, we produced two phased genome assemblies of the critically endangered fish Chinese Bahaba (Bahaba taipingensis, Sciaenidae, Teleostei) and resequenced 20 whole genomes to quantify population genetic load at a haplotype level. We identified frame-shifting variants as the most deleterious type, followed by mutations in the 5'-UTR, 3'-UTR and missense mutations at conserved amino acids. Phased haplotypes revealed gene deletions and high-impact deleterious variants. We estimated ~1.12% of genes missing or interrupted per haplotype, with a significant overlap of disrupted genes (30.35%) between haplotype sets. Relative proportions of deleterious variant categories differed significantly between haplotypes. Simulations suggested that purifying selection struggled to purge slightly deleterious genetic load in captive breeding compared to genotyping interventions, and that higher inter-haplotypic variance of genetic load predicted more efficient purging by artificial selection. Combining the knowledge of haplotype-resolved genetic load with predictive modelling will be immensely useful for understanding the evolution of deleterious variants and guiding conservation planning.

Muller's genetic load/species extinction hypothesis.

The genetic load hypothesis of Hermann Muller raised the profound question of possible species extinction, even for humans, following a prolonged accumulation of recessive genes due to ionizing radiation exposure within the population. Two major mouse radiation research teams in the United States provided the most extensive tests of Muller's hypothesis. One group continued its study for more than two decades, over 82 consecutive generations, approximating 2500 human years. Even though Muller had stressed for decades his fear of species-threatening effects, no significant effects were observed for related factors such as reproductive fitness and longevity. Yet, the paper presenting the data of the 82-generation negative study has only been cited five times in 45 years. Altogether numerous laboratories worldwide collected vast amounts of data on mice, rats, and swine in an unsuccessful attempt to see if there was convincing evidence to support the genetic load theory and claims that species might deteriorate or be rendered extinct. This paper re-examines Muller's genetic load hypothesis with a new evaluation of how that hypothesis was tested and the significance of the findings, with most of those studies being completed before the BEIR I Committee Report in 1972. That committee briefly discussed the available evidence, mostly ignoring those results as they proceeded to make hereditary risk estimates both for (1) the first generation after a radiation exposure and (2) for the time, in the distant future, when a hypothetical genetic equilibrium would be reached. Their estimates assumed accumulation of harmful mutations and a linear no-threshold dose response extending all of the way down to a single ionization. More recent data on induction by ionizing radiation of dominant mutations that affect the skeletons of mice provide further robust supporting evidence that the generationally cumulative and LNT-based assumptions underpinning Muller's genetic load hypothesis are not correct.

Genetic Load and Adaptive Potential of a Recovered Avian Species that Narrowly Avoided Extinction.

High genetic diversity is a good predictor of long-term population viability, yet some species persevere despite having low genetic diversity. Here we study the genomic erosion of the Seychelles paradise flycatcher (Terpsiphone corvina), a species that narrowly avoided extinction after having declined to 28 individuals in the 1960s. The species recovered unassisted to over 250 individuals in the 1990s and was downlisted from Critically Endangered to Vulnerable in the International Union for the Conservation of Nature Red List in 2020. By comparing historical, prebottleneck (130+ years old) and modern genomes, we uncovered a 10-fold loss of genetic diversity. Highly deleterious mutations were partly purged during the bottleneck, but mildly deleterious mutations accumulated. The genome shows signs of historical inbreeding during the bottleneck in the 1960s, but low levels of recent inbreeding after demographic recovery. Computer simulations suggest that the species long-term small Ne reduced the masked genetic load and made the species more resilient to inbreeding and extinction. However, the reduction in genetic diversity due to the chronically small Ne and the severe bottleneck is likely to have reduced the species adaptive potential to face environmental change, which together with a higher load, compromises its long-term population viability. Thus, small ancestral Ne offers short-term bottleneck resilience but hampers long-term adaptability to environmental shifts. In light of rapid global rates of population decline, our work shows that species can continue to suffer the effect of their decline even after recovery, highlighting the importance of considering genomic erosion and computer modeling in conservation assessments.

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).

Impacts of Population Size and Domestication Process on Genetic Diversity and Genetic Load in Genus Ovis.

In theoretical biology, a prevailing hypothesis posits a profound interconnection between effective population size (Ne), genetic diversity, inbreeding, and genetic load. The domestication and improvement processes are believed to be pivotal in diminishing genetic diversity while elevating levels of inbreeding and increasing genetic load. In this study, we performed a whole genome analysis to quantity genetic diversity, inbreeding, and genetic load across seven wild Ovis species and five domesticated sheep breeds. Our research demonstrates that the genetic load and diversity of species in the genus Ovis have no discernible impact on recent Ne, and three species within the subgenus Pachyceros tend to carry a higher genetic load and lower genetic diversity patterns. The results coincide with these species' dramatic decline in population sizes within the subgenus Pachyceros ~80-250 thousand years ago. European mouflon presented with the lowest Ne, lower genetic diversity, and higher individual inbreeding coefficient but a lower genetic load (missense and LoF). This suggests that the small Ne of European mouflon could reduce harmful mutations compared to other species within the genus Ovis. We showed lower genetic diversity in domesticated sheep than in Asiatic mouflon, but counterintuitive patterns of genetic load, i.e., lower weak genetic load (missense mutation) and no significant difference in strong genetic load (LoF mutation) between domestic sheep and Asiatic mouflon. These findings reveal that the "cost of domestication" during domestication and improvement processes reduced genetic diversity and purified weak genetic load more efficiently than wild species.

Environmental variance in male mating success modulates the positive versus negative impacts of sexual selection on genetic load.

Sexual selection on males is predicted to increase population fitness, and delay population extinction, when mating success negatively covaries with genetic load across individuals. However, such benefits of sexual selection could be counteracted by simultaneous increases in genome-wide drift resulting from reduced effective population size caused by increased variance in fitness. Resulting fixation of deleterious mutations could be greatest in small populations, and when environmental variation in mating traits partially decouples sexual selection from underlying genetic variation. The net consequences of sexual selection for genetic load and population persistence are therefore likely to be context dependent, but such variation has not been examined. We use a genetically explicit individual-based model to show that weak sexual selection can increase population persistence time compared to random mating. However, for stronger sexual selection such positive effects can be overturned by the detrimental effects of increased genome-wide drift. Furthermore, the relative strengths of mutation-purging and drift critically depend on the environmental variance in the male mating trait. Specifically, increasing environmental variance caused stronger sexual selection to elevate deleterious mutation fixation rate and mean selection coefficient, driving rapid accumulation of drift load and decreasing population persistence times. These results highlight an intricate balance between conflicting positive and negative consequences of sexual selection on genetic load, even in the absence of sexually antagonistic selection. They imply that environmental variances in key mating traits, and intrinsic genetic drift, should be properly factored into future theoretical and empirical studies of the evolution of population fitness under sexual selection.

Purging and accumulation of genetic load in conservation.

Our ability to assess the threat posed by the genetic load to small and declining populations has been greatly improved by advances in genome sequencing and computational approaches. Yet, considerable confusion remains around the definitions of the genetic load and its dynamics, and how they impact individual fitness and population viability. We illustrate how both selective purging and drift affect the distribution of deleterious mutations during population size decline and recovery. We show how this impacts the composition of the genetic load, and how this affects the extinction risk and recovery potential of populations. We propose a framework to examine load dynamics and advocate for the introduction of load estimates in the management of endangered populations.

Long-Term Balancing Selection and the Genetic Load Linked to the Self-Incompatibility Locus in Arabidopsis halleri and A. lyrata.

Balancing selection is a form of natural selection maintaining diversity at the sites it targets and at linked nucleotide sites. Due to selection favoring heterozygosity, it has the potential to facilitate the accumulation of a "sheltered" load of tightly linked recessive deleterious mutations. However, precisely evaluating the extent of these effects has remained challenging. Taking advantage of plant self-incompatibility as one of the best-understood examples of long-term balancing selection, we provide a highly resolved picture of the genomic extent of balancing selection on the sheltered genetic load. We used targeted genome resequencing to reveal polymorphism of the genomic region flanking the self-incompatibility locus in three sample sets in each of the two closely related plant species Arabidopsis halleri and Arabidopsis lyrata, and used 100 control regions from throughout the genome to factor out differences in demographic histories and/or sample structure. Nucleotide polymorphism increased strongly around the S-locus in all sample sets, but only over a limited genomic region, as it became indistinguishable from the genomic background beyond the first 25-30 kb. Genes in this chromosomal interval exhibited no excess of mutations at 0-fold degenerated sites relative to putatively neutral sites, hence revealing no detectable weakening of the efficacy of purifying selection even for these most tightly linked genes. Overall, our results are consistent with the predictions of a narrow genomic influence of linkage to the S-locus and clarify how natural selection in one genomic region affects the evolution of the adjacent genomic regions.

Genetic load in incomplete lupus erythematosus.

OBJECTIVE: Patients with incomplete lupus erythematosus (ILE) have lupus features but insufficient criteria for SLE classification. Some patients with ILE transition to SLE, but most avoid major organ involvement. This study tested whether the milder disease course in ILE is influenced by reduced SLE risk allele genetic load. METHODS: We calculated the genetic load based on 99 SLE-associated risk alleles in European American patients with SLE (≥4 American College of Rheumatology (ACR) 1997 criteria, n=170), patients with ILE (3 ACR 1997 criteria, n=169), a subset of patients with ILE not meeting Systemic Lupus International Collaborating Clinics (SLICC) classification (ILESLICC, n=119) and healthy controls (n=133). Unweighted genetic loads were calculated as the total sum of risk alleles for each individual, while weighted genetic loads were defined as the sum of risk alleles multiplied by the natural logarithm of the previously published OR of each risk allele for SLE susceptibility. RESULTS: The median unweighted and weighted SLE risk allele genetic load was significantly greater in patients with ILE (unweighted: 81, p value=0.01; weighted: 16.3, p value=0.001) and patients with SLE (80, p value=0.02; 16.29, p value=0.0006) compared with healthy controls (78, 15.76). Patients with ILESLICC trended towards an increased genetic load, although not statistically significant (unweighted: 80, p value=0.14; weighted: 16.05, p value=0.07). However, the median genetic load did not significantly differ between ILE and SLE, and genetic load did not differentiate patients with ILE and SLE (area under the curve=0.51, p=0.78) by receiver operator characteristic analysis. CONCLUSIONS: Patients with ILE and SLE have comparable genetic loads of SLE risk loci, suggesting similar genetic predispositions between these conditions. Phenotypical differences between SLE and ILE may instead be influenced by ILE-specific variants and gene-environment interactions.

An evolutionary perspective on genetic load in small, isolated populations as informed by whole genome resequencing and forward-time simulations.

Small populations are vulnerable to increased genetic load and drift that can lead to reductions in fitness and adaptive potential. By analyzing 66 individual whole genomes of Montezuma Quail (Cyrtonyx montezumae) from multiple populations, we illustrate how genetic load is dynamic over evolutionary time. We show that Montezuma Quail are evolving like a ring species, where the terminal extant populations from Arizona and Texas have been separated for ~16,500 years. The Texas populations have remained small but stable since the separation, whereas the Arizona population is much larger today but has been contracting for thousands of years. Most deleterious mutations across the genome are young and segregating privately in each population and a greater number of deleterious alleles are present in the larger population. Our data indicate that ancestral load is purged during strong bottlenecks, but the reduced efficiency of selection in small populations means that segregating deleterious mutations are more likely to rise in frequency over time. Forward-time simulations indicate that severe population declines in historically large populations is more detrimental to individual fitness, whereas long-term small populations are more at risk for reduced adaptive potential and population-level fitness. Our study highlights the intimate connections among evolutionary history, historical demography, genetic load, and evolutionary potential in wild populations.

From high masked to high realized genetic load in inbred Scandinavian wolves.

When new mutations arise at functional sites they are more likely to impair than improve fitness. If not removed by purifying selection, such deleterious mutations will generate a genetic load that can have negative fitness effects in small populations and increase the risk of extinction. This is relevant for the highly inbred Scandinavian wolf (Canis lupus) population, founded by only three wolves in the 1980s and suffering from inbreeding depression. We used functional annotation and evolutionary conservation scores to study deleterious variation in a total of 209 genomes from both the Scandinavian and neighbouring wolf populations in northern Europe. The masked load (deleterious mutations in heterozygote state) was highest in Russia and Finland with deleterious alleles segregating at lower frequency than neutral variation. Genetic drift in the Scandinavian population led to the loss of ancestral alleles, fixation of deleterious variants and a significant increase in the per-individual realized load (deleterious mutations in homozygote state; an increase by 45% in protein-coding genes) over five generations of inbreeding. Arrival of immigrants gave a temporary genetic rescue effect with ancestral alleles re-entering the population and thereby shifting deleterious alleles from homozygous into heterozygote genotypes. However, in the absence of permanent connectivity to Finnish and Russian populations, inbreeding has then again led to the exposure of deleterious mutations. These observations provide genome-wide insight into the magnitude of genetic load and genetic rescue at the molecular level, and in relation to population history. They emphasize the importance of securing gene flow in the management of endangered populations.

Eco-evolutionary extinction and recolonization dynamics reduce genetic load and increase time to extinction in highly inbred populations.

Understanding how genetic and ecological effects can interact to shape genetic loads within and across local populations is key to understanding ongoing persistence of systems that should otherwise be susceptible to extinction through mutational meltdown. Classic theory predicts short persistence times for metapopulations comprising small local populations with low connectivity, due to accumulation of deleterious mutations. Yet, some such systems have persisted over evolutionary time, implying the existence of mechanisms that allow metapopulations to avoid mutational meltdown. We first hypothesize a mechanism by which the combination of stochasticity in the numbers and types of mutations arising locally (genetic stochasticity), resulting local extinction, and recolonization through evolving dispersal facilitates metapopulation persistence. We then test this mechanism using a spatially and genetically explicit individual-based model. We show that genetic stochasticity in highly structured metapopulations can result in local extinctions, which can favor increased dispersal, thus allowing recolonization of empty habitat patches. This causes fluctuations in metapopulation size and transient gene flow, which reduces genetic load and increases metapopulation persistence over evolutionary time. Our suggested mechanism and simulation results provide an explanation for the conundrum presented by the continued persistence of highly structured populations with inbreeding mating systems that occur in diverse taxa.

Genomic insights into inter- and intraspecific mating system shifts in Primulina.

The mating system shift from outcrossing to selfing is one of the most frequent evolutionary trends in flowering plants. However, the genomic consequences of this shift remain poorly understood. Specifically, the relative importance of the demographic and genetic processes causing changes in genetic variation and selection efficacy associated with the evolution of selfing is unclear. Here we sequenced the genomes of two Primulina species with contrasting mating systems: P. eburnea (outcrossing) versus P. tabacum (outcrossing, mixed-mating and selfing populations). Whole-genome resequencing data were used to investigate the genomic consequences of mating system shifts within and between species. We found that highly selfing populations of P. tabacum display loss of genetic diversity, increased deleterious mutations, higher genomic burden and fewer adaptive substitutions. However, compared with outcrossing populations, mixed-mating populations did not display loss of genetic diversity and accumulation of genetic load. We find no evidence of population bottlenecks associated with the shift to selfing, which suggests that the genetic effects of selfing on Ne and possibly linked selection, rather than demographic history, are the primary drivers of diversity reduction in highly selfing populations. Our results highlight the importance of distinguishing the relative contribution of mating system and demography on the genomic consequences associated with mating system evolution in plants.

Genetic Load of SARS-CoV-2 in Aerosols Collected in Operating Theaters.

After the outbreak of COVID-19, additional protocols have been established to prevent the transmission of the SARS-CoV-2 from the patient to the health personnel and vice versa in health care settings. However, in the case of emergency surgeries, it is not always possible to ensure that the patient is not infected with SARS-CoV-2, assuming a potential source of transmission of the virus to health personnel. This work aimed to evaluate the presence of the SARS-CoV-2 and quantify the viral load in indoor air samples collected inside operating rooms, where emergency and scheduled operations take place. Samples were collected for 3 weeks inside two operating rooms for 24 h at 38 L/min in quartz filters. RNA was extracted from the filters and analyzed using RT-qPCR targeting SARS-CoV-2 genes E, N1 and N2 regions. SARS-CoV-2 RNA was detected in 11.3% of aerosol samples collected in operating rooms, despite with low concentrations (not detected at 13.5 cg/m3 and 10.5 cg/m3 in the scheduled and emergency operating rooms, respectively). Potential sources of airborne SARS-CoV-2 could be aerosolization of the virus during aerosol-generating procedures and in open surgery from patients that might have been recently infected with the virus, despite presenting a negative COVID-19 test. Another source could be related to health care workers unknowingly infected with the virus and exhaling SARS-CoV-2 virions into the air. These results highlight the importance of reinforcing preventive measures against COVID-19 in operating rooms, such as the correct use of protective equipment, screening programs for health care workers, and information campaigns. IMPORTANCE Operating rooms are critical environments in which asepsis must be ensured. The COVID-19 pandemic entailed the implementation of additional preventative measures in health care settings, including operating theaters. Although one of the measures is to operate only COVID-19 free patients, this measure cannot be always implemented, especially in emergency interventions. Therefore, a surveillance campaign was conducted during 3 weeks in two operating rooms to assess the level of SARS-CoV-2 genetic material detected in operating theaters with the aim to assess the risk of COVID-19 transmission during operating procedures. SARS-CoV-2 genetic material was detected in 11% of aerosol samples collected in operating rooms, despite with low concentrations. Plausible SARS-CoV-2 sources have been discussed, including patients and health care personnel infected with the virus. These results highlight the importance of reinforcing preventive measures against COVID-19 in operating rooms, such as the correct use of protective equipment, screening programs for health care workers and information campaigns.

Genomic evidence that a sexually selected trait captures genome-wide variation and facilitates the purging of genetic load.

The evolution of costly traits such as deer antlers and peacock trains, which drove the formation of Darwinian sexual selection theory, has been suggested to both reflect and affect patterns of genetic variance across the genome, but direct tests are missing. Here, we used an evolve and resequence approach to reveal patterns of genome-wide diversity associated with the expression of a sexually selected weapon that is dimorphic among males of the bulb mite, Rhizoglyphus robini. Populations selected for the weapon showed reduced genome-wide diversity compared to populations selected against the weapon, particularly in terms of the number of segregating non-synonymous positions, indicating enhanced purifying selection. This increased purifying selection reduced inbreeding depression, but outbred female fitness did not improve, possibly because any benefits were offset by increased sexual antagonism. Most single nucleotide polymorphisms (SNPs) that consistently diverged in response to selection were initially rare and overrepresented in exons, and enriched in regions under balancing or relaxed selection, suggesting they are probably moderately deleterious variants. These diverged SNPs were scattered across the genome, further demonstrating that selection for or against the weapon and the associated changes to the mating system can both capture and influence genome-wide variation.

Accounting for the genetic load in assisted reproductive technology.

The genetic load in the human genome has important ramifications for assisted reproductive technology (ART), human reproduction and fertility more generally. Here, we discuss these topics in the light of evolutionary genetic theory, the technological revolution in ART and the advances in the fields of genomics and bioinformatics.

Epistatic selection on a selfish Segregation Distorter supergene - drive, recombination, and genetic load.

Meiotic drive supergenes are complexes of alleles at linked loci that together subvert Mendelian segregation resulting in preferential transmission. In males, the most common mechanism of drive involves the disruption of sperm bearing one of a pair of alternative alleles. While at least two loci are important for male drive-the driver and the target-linked modifiers can enhance drive, creating selection pressure to suppress recombination. In this work, we investigate the evolution and genomic consequences of an autosomal, multilocus, male meiotic drive system, Segregation Distorter (SD) in the fruit fly, Drosophila melanogaster. In African populations, the predominant SD chromosome variant, SD-Mal, is characterized by two overlapping, paracentric inversions on chromosome arm 2R and nearly perfect (~100%) transmission. We study the SD-Mal system in detail, exploring its components, chromosomal structure, and evolutionary history. Our findings reveal a recent chromosome-scale selective sweep mediated by strong epistatic selection for haplotypes carrying Sd, the main driving allele, and one or more factors within the double inversion. While most SD-Mal chromosomes are homozygous lethal, SD-Mal haplotypes can recombine with other, complementing haplotypes via crossing over, and with wildtype chromosomes via gene conversion. SD-Mal chromosomes have nevertheless accumulated lethal mutations, excess non-synonymous mutations, and excess transposable element insertions. Therefore, SD-Mal haplotypes evolve as a small, semi-isolated subpopulation with a history of strong selection. These results may explain the evolutionary turnover of SD haplotypes in different populations around the world and have implications for supergene evolution broadly.

Genetic load: genomic estimates and applications in non-model animals.

Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components - the realized load (or expressed load) and the masked load (or inbreeding load) - can improve our understanding of the population genetics of deleterious mutations.