The \"cost of domestication\" hypothesis suggests that the domestication of wild species increases the number, frequency, and/or proportion of deleterious genetic variants, potentially reducing their fitness in the wild. While extensively studied in domesticated species, this phenomenon remains understudied in fungi. Here, we used Saccharomyces cerevisiae, the world\'s oldest domesticated fungus, as a model to investigate the genomic characteristics of deleterious variants arising from fungal domestication. Employing a graph-based pan-genome approach, we identified 1,297,761 single nucleotide polymorphisms (SNPs), 278,147 insertion/deletion events (indels; <30 bp), and 19,967 non-redundant structural variants (SVs; ≥30 bp) across 687 S. cerevisiae isolates. Comparing these variants with synonymous SNPs (sSNPs) as neutral controls, we found that the majority of the derived nonsynonymous SNPs (nSNPs), indels, and SVs were deleterious. Heterozygosity was positively correlated with the impact of deleterious SNPs, suggesting a role of genetic diversity in mitigating their effects. The domesticated isolates exhibited a higher additive burden of deleterious SNPs (dSNPs) than the wild isolates, but a lower burden of indels and SVs. Moreover, the domesticated S. cerevisiae showed reduced rates of adaptive evolution relative to the wild S. cerevisiae. In summary, deleterious variants tend to be heterozygous, which may mitigate their harmful effects, but they also constrain breeding potential. Addressing deleterious alleles and minimizing the genetic load are crucial considerations for future S. cerevisiae breeding efforts.

Modern humans have experienced explosive population growth in the past thousand years. We hypothesized that recent human populations have inhabited environments with relaxation of selective constraints, possibly due to the more abundant food supply after the Last Glacial Maximum. The ratio of nonsynonymous to synonymous mutations (N/S ratio) is a useful and common statistic for measuring selective constraints. In this study, we reconstructed a high-resolution phylogenetic tree using a total of 26,419 East Eurasian mitochondrial DNA genomes, which were further classified into expansion and nonexpansion groups on the basis of the frequencies of their founder lineages. We observed a much higher N/S ratio in the expansion group, especially for nonsynonymous mutations with moderately deleterious effects, indicating a weaker effect of purifying selection in the expanded clades. However, this observation on N/S ratio was unlikely in computer simulations where all individuals were under the same selective constraints. Thus, we argue that the expanded populations were subjected to weaker selective constraints than the nonexpanded populations were. The mildly deleterious mutations were retained during population expansion, which could have a profound impact on present-day disease patterns.

Dominance refers to the effect of a heterozygous genotype relative to that of the two homozygous genotypes. The degree of dominance of mutations for fitness can have a profound impact on how deleterious and beneficial mutations change in frequency over time as well as on the patterns of linked neutral genetic variation surrounding such selected alleles. Since dominance is such a fundamental concept, it has received immense attention throughout the history of population genetics. Early work from Fisher, Wright, and Haldane focused on understanding the conceptual basis for why dominance exists. More recent work has attempted to test these theories and conceptual models by estimating dominance effects of mutations. However, estimating dominance coefficients has been notoriously challenging and has only been done in a few species in a limited number of studies. In this review, we first describe some of the early theoretical and conceptual models for understanding the mechanisms for the existence of dominance. Second, we discuss several approaches used to estimate dominance coefficients and summarize estimates of dominance coefficients. We note trends that have been observed across species, types of mutations, and functional categories of genes. By comparing estimates of dominance coefficients for different types of genes, we test several hypotheses for the existence of dominance. Lastly, we discuss how dominance influences the dynamics of beneficial and deleterious mutations in populations and how the degree of dominance of deleterious mutations influences the impact of inbreeding on fitness.

Huntington\'s disease (HD) is a chronic, inherited neurodegenerative condition marked by chorea, dementia, and changes in personality. The primary cause of HD is a mutation characterized by the expansion of a triplet repeat (CAG) within the huntingtin gene located on chromosome 4. Despite substantial progress in elucidating the molecular and cellular mechanisms of HD, an effective treatment for this disorder is not available so far. In recent years, researchers have been interested in studying cerebrospinal fluid (CSF) as a source of biomarkers that could aid in the diagnosis and therapeutic development of this disorder. Immunoglobulin heavy constant gamma 1 (IGHG1) is one of the CSF proteins found to increase significantly in HD. Considering this, it is reasonable to study the potential involvement of deleterious mutations in IGHG1 in the pathogenesis of this disorder. In this study, we explored the potential impact of deleterious mutations on IGHG1 and their subsequent association with HD. We evaluated 126 single-point amino acid substitutions for their impact on the structure and functionality of the IGHG1 protein while exploiting multiple computational resources such as SIFT, PolyPhen-2, FATHMM, SNPs&Go mCSM, DynaMut2, MAESTROweb, PremPS, MutPred2, and PhD-SNP. The sequence- and structure-based tools highlighted 10 amino acid substitutions that were deleterious and destabilizing. Subsequently, out of these 10 mutations, eight variants (Y32C, Y32D, P34S, V39E, C83R, C83Y, V85M, and H87Q) were identified as pathogenic by disease phenotype predictors. Finally, two pathogenic variants (Y32C and P34S) were found to reduce the solubility of the protein, suggesting their propensity to form protein aggregates. These variants also exhibited higher residual frustration within the protein structure. Considering these findings, the study hypothesized that the identified variants of IGHG1 may compromise its function and potentially contribute to HD pathogenesis.

Endangered species generally have small populations with low genetic diversity and a high genetic load. Thuja sutchuenensis is an endangered conifer endemic to southwestern China. It was once considered extinct in the wild, but in 1999 was rediscovered. However, little is known about its genetic load. We collected 67 individuals from five wild, isolated T. sutchuenensis populations, and used 636,151 SNPs to analyze the level of genetic diversity and genetic load in T. sutchuenensis to delineate the conservation units of T. sutchuenensis, based on whole transcriptome sequencing data, as well as target capture sequencing data. We found that populations of T. sutchuenensis could be divided into three groups. These groups had low levels genetic diversity and were moderately genetically differentiated. Our findings also indicate that T. sutchuenensis suffered two severe bottlenecks around the Last Glaciation Period and Last Glacial Maximum. Among Thuja species, T. sutchuenensis presented the lowest genetic load and hence might have purged deleterious mutations efficiently through purifying selection. However, distribution of fitness effects analysis indicated a high extinction risk for T. sutchuenensis. Multiple lines of evidence identified three management units for T. sutchuenensis. Although T. sutchuenensis possesses a low genetic load, low genetic diversity, suboptimal fitness, and anthropogenic pressures all present an extinction risk for this rare conifer. This might also hold true for many endangered plant species in the mountains all over the world.

Based on the observation that humans have variable responses of gene expression with the same dose of an adeno-associated vector, we hypothesized that there are deleterious variants in genes coding for processes required for adeno-associated virus (AAV)-mediated gene transfer/expression that may hamper or enhance the effectiveness of AAV-mediated gene therapy. To assess this hypothesis, we evaluated 69,442 whole genome sequences from three populations (European, African/African American, and Qatari) for predicted deleterious variants in 62 genes known to play a role in AAV-mediated gene transfer/expression. The analysis identified 5,564 potentially deleterious mutations of which 27 were classified as common based on an allele frequency ≥1% in at least one population studied. Many of these deleterious variants are predicated to prevent while others enhance effective AAV gene transfer/expression, and several are linked to known hereditary disorders. The data support the hypothesis that, like other drugs, human genetic variability contributes to the person-to-person effectiveness of AAV gene therapy and the screening for genetic variability should be considered as part of future clinical trials.

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).

Fisher\'s reproductive compensation (fRC) occurs when a species\' demography means the death of an individual results in increased survival probability of his/her relatives, usually assumed to be full sibs. This likely occurs in many species, including humans. Several important recessive human genetic diseases cause early foetal/infant death allowing fRC to act on these mutations. The impact of fRC on these genetic conditions has been previously calculated and shown to be substantial as quantified by ω, the fold increase in equilibrium frequencies of the mutation under fRC compared with its absence, i.e. ω = 1.22 and ω = 1.33 for autosomal and sex-linked loci, respectively. However, the impact of fRC on the frequency of the much larger class of semidominant, nonlethal mutations is unknown. This is calculated here as ω = 2 - h*s for autosomal loci and ω up to 2 for sex-linked loci where h is dominance (varied between 0.05 and 0.95) and s is selection coefficient (varied between 0.05 and 0.9). These results show that the actions of fRC can almost double the equilibrium frequency of deleterious mutations with low values of h and/or s (noting that \"low\" is s∼0.05 to 0.1). It is noted that fRC may act differentially across the genome with genes expressed early in life being fully exposed to fRC while those expressed later in life may be unaffected; this could lead to systematic differences in deleterious allele frequency across the genome.

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is, therefore, of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, that is whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterized the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence, and genetic background. We find statistical support for the presence of variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and those evolutionarily recent events, such as demographic changes and local adaptation, have little impact.

BACKGROUND: Biological mechanisms affecting gametogenesis, embryo development and postnatal viability have the potential to alter Mendelian inheritance expectations resulting in observable transmission ratio distortion (TRD). Although the discovery of TRD cases have been around for a long time, the current widespread and growing use of DNA technologies in the livestock industry provides a valuable resource of large genomic data with parent-offspring genotyped trios, enabling the implementation of TRD approach. In this research, the objective is to investigate TRD using SNP-by-SNP and sliding windows approaches on 441,802 genotyped Holstein cattle and 132,991 (or 47,910 phased) autosomal SNPs.
RESULTS: The TRD was characterized using allelic and genotypic parameterizations. Across the whole genome a total of 604 chromosomal regions showed strong significant TRD. Most (85%) of the regions presented an allelic TRD pattern with an under-representation (reduced viability) of carrier (heterozygous) offspring or with the complete or quasi-complete absence (lethality) for homozygous individuals. On the other hand, the remaining regions with genotypic TRD patterns exhibited the classical recessive inheritance or either an excess or deficiency of heterozygote offspring. Among them, the number of most relevant novel regions with strong allelic and recessive TRD patterns were 10 and 5, respectively. In addition, functional analyses revealed candidate genes regulating key biological processes associated with embryonic development and survival, DNA repair and meiotic processes, among others, providing additional biological evidence of TRD findings.
CONCLUSIONS: Our results revealed the importance of implementing different TRD parameterizations to capture all types of distortions and to determine the corresponding inheritance pattern. Novel candidate genomic regions containing lethal alleles and genes with functional and biological consequences on fertility and pre- and post-natal viability were also identified, providing opportunities for improving breeding success in cattle.