Demographic history and mutational load are of paramount importance for the adaptation of the endangered species. However, the effects of population evolutionary history and genetic load on the adaptive potential in endangered conifers remain unclear. Here, using population transcriptome sequencing, whole chloroplast genomes and mitochondrial DNA markers, combined with niche analysis, we determined the demographic history and mutational load for three threatened whitebark pines having different endangered statuses, Pinus bungeana, P. gerardiana and P. squamata. Demographic inference indicated that severe bottlenecks occurred in all three pines at different times, coinciding with periods of major climate and geological changes; in contrast, while P. bungeana experienced a recent population expansion, P. gerardiana and P. squamata maintained small population sizes after bottlenecking. Abundant homozygous-derived variants accumulated in the three pines, particularly in P. squamata, while the species with most heterozygous variants was P. gerardiana. Abundant moderately and few highly deleterious variants accumulated in the pine species that have experienced the most severe demographic bottlenecks (P. gerardiana and P. squamata), most likely because of purging effects. Finally, niche modeling showed that the distribution of P. bungeana might experience a significant expansion in the future, and the species\' identified genetic clusters are also supported by differences in the ecological niche. The integration of genomic, demographic and niche data has allowed us to prove that the three threatened pines have contrasting patterns of demographic history and mutational load, which may have important implications in their adaptive potential and thus are also key for informing conservation planning.

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.

The arylsulfatase A (ARSA) gene is observed to be deficient in patients with metachromatic leukodystrophy (MLD), a type of lysosomal storage disease. MLD is a severe neurodegenerative disorder characterized by an autosomal recessive inheritance pattern. This study aimed to map the most deleterious mutations at the metal binding sites of ARSA and the amino acids in proximity to the mutated positions. We utilized an array of computational tools, including PredictSNP, MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT, SNAP, and ConSurf, to identify the most detrimental mutations potentially implicated in MLD collected from UniProt, ClinVar, and HGMD. Two mutations, D29N and D30H, as being extremely deleterious based on assessments of pathogenicity, conservation, biophysical characteristics, and stability analysis. The D29 and D30 are located at the metal-interacting regions of ARSA and found to undergo post-translational modification, specifically phosphorylation. Henceforth, the in-depth effect of metal binding upon mutation was examined using molecular dynamics simulations (MDS) before and after phosphorylation. The MDS results exhibited high deviation for the D29N and D30H mutations in comparison to the native, and the same was confirmed by significant residue fluctuation and reduced compactness. These structural alterations suggest that such mutations may influence protein functionality, offering potential avenues for personalized therapeutic and providing a basis for potential mutation-specific treatments for severe MLD patients.

AbstractLocal adaptation frequently evolves in patches or environments that are connected via migration. In these cases, genomic regions that are linked to a locally adapted locus experience reduced effective migration rates. Via individual-based simulations of a two-patch system, we show that this reduced effective migration results in the accumulation of conditionally deleterious mutations, but not universally deleterious mutations, adjacent to adaptive loci. When there is redundancy in the genetic basis of local adaptation (i.e., genotypic redundancy), turnover of locally adapted polymorphisms allows conditionally deleterious mutation load to be purged. The amount of mutational load that accumulates adjacent to locally adapted loci is dependent on redundancy, recombination rate, migration rate, population size, strength of selection, and the phenotypic effect size of adaptive alleles. Our results highlight the need to be cautious when interpreting patterns of local adaptation at the level of phenotype or fitness, as the genetic basis of local adaptation can be transient, and evolution may confer a degree of maladaptation to nonlocal environments.

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.

MDC1 (Mediator of DNA damage Checkpoint protein 1) functions to facilitate the localization of numerous DNA damage response (DDR) components to DNA double-strand break sites. MDC1 is an integral component in preserving genomic stability and appropriate DDR regulation. There haven\'t been systematic investigations of MDC1 mutations that induce cancer and genomic instability. Variations in nsSNPs have the potential to modify the protein chemistry and their function. Describing functional SNPs in disease-associated genes presents a significant conundrum for investigators, it is possible to assess potential functional SNPs before conducting larger population examinations. Multiple sequences and structure-based bioinformatics strategies were implemented in the current in-silico investigation to discern potential nsSNPs of the MDC1 genes. The nsSNPs were identified with SIFT, SNAP2, Align GVGD, PolyPhen-2, and PANTHER, and their stability was determined with MUpro. The conservation, solvent accessibility, and structural effects of the mutations were identified with ConSurf, NetSurfP-2.0, and SAAFEC-SEQ respectively. Cancer-related analysis of the nsSNPs was conducted using cBioPortal and TCGA web servers. The present study appraised five nsSNPs (P1426T, P69S, P194R, P203L, and H131Y) as probably mutilating due to their existence in highly conserved regions and propensity to deplete protein stability. The nsSNPs P194R, P203L, and H131Y were concluded as deleterious and possibly damaging from the 5 prediction tools. The functional nsSNP P194R mutation is associated with skin cutaneous melanoma while no significant records were found for other nsSNPs. The present study concludes that the highly deleterious P194R mutations can potentially induce genomic instability and contribute to various cancers\' pathogenesis. Developing drugs targeting these mutations can undoubtedly be advantageous in large population-based studies, particularly in the development of precision medicine.

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.

Plants exhibit diverse breeding systems, with populations capable of outcrossing, selfing, and/or asexual reproduction. However, interactions between the three reproductive pathways remain not fully clear. Sexual reproduction introduces segregation and recombination, but incurs several costs. Selfing can affect the relative costs and benefits of sexual vs. asexual reproduction. Building population genetic models, I explore how selfing affects the evolution of a sexual reproduction rate modifier via (a) indirect selection due to segregation, (b) indirect selection from changes in recombination rates, and (c) selection from the cost of meiosis and mate limitation. The dominant selective force mediating the evolution of sex is found to vary with the rate of sexual reproduction and selfing, but selective force (a) and (c) are generally stronger than selective force (b). A modifier enhancing sexual reproduction tends to be favored by indirect selection generated by partially recessive, small-effect deleterious mutations, while hindered by highly recessive lethal mutations. Overall, evolution toward higher sexual reproduction is hindered at low sexual reproduction rates and intermediate selfing rates, but favored under high selfing rates. The results suggest that asexual reproduction may precede the evolution of selfing and offer insights into the evolution of mechanisms reducing geitonogamy in partially clonal populations.

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.

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.