Sex differences in deleterious genetic variants in a haplodiploid social insect

Deleterious variants are selected against but can linger in populations at low frequencies for long periods of time, decreasing fitness and contributing to disease burden in humans and other species. Deleterious variants occur at low frequency but distinguishing deleterious variants from low frequency neutral variation is challenging based on population genetics data. As a result, we have little sense of the number and identity of deleterious variants in wild populations. For haplodiploid species, it has been hypothesized that deleterious alleles will be directly exposed to selection in haploid males, but selection can be masked in diploid females due to partial or complete dominance, resulting in more efficient purging of deleterious mutations in males. Therefore, comparisons of the differences between haploid and diploid genomes from the same population may be a useful method for inferring rare deleterious variants. This study provides the first formal test of this hypothesis. Using wild populations of Northern paper wasps (Polistes fuscatus), we find that males have fewer overall variants, and specifically fewer missense and nonsense variants, than females from the same population. Allele frequency differences are especially pronounced for rare missense and nonsense mutations and these differences lead to a lower genetic load in males than females. Based on these data we estimate that a large number of highly deleterious mutations are segregating in the paper wasp population. Stronger selection against deleterious alleles in haploid males may have implications for adaptation in other haplodiploid insects and provides evidence that wild populations harbor abundant deleterious variants.

How Genetics Might Explain the Unusual Link Between Malaria and COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated coronavirus disease 2019 (COVID-19) pandemic has been the subject of a large number of studies in recent times. Here, starting from the evidence that in Italy, the areas with the lowest number of COVID-19 cases were those with the highest incidence of malaria in the early 1900's, we explore possible inverse relationships between malaria and COVID-19. Indeed, some genetic variants, which have been demonstrated to give an advantage against malaria, can also play a role in the incidence and severity of SARS-CoV-2 infections (e.g., the ACE2 receptor). To verify this scientific hypothesis, we here use public data from whole-genome sequencing (WGS) experiments to extrapolate the genetic information of 46 world populations with matched COVID-19 data. In particular, we focus on 47 genes, including ACE2 and genes which have previously been reported to play a role in malaria. Only common variants (>5%) in at least 30% of the selected populations were considered, and, for this subset, we correlate the intra-population allele frequency with the COVID-19 data (cases/million inhabitants), eventually pinpointing meaningful variants in 6 genes. This study allows us to distinguish between positive and negative correlations, i.e., variants whose frequency significantly increases with increasing or decreasing COVID-19 cases. Finally, we discuss the possible molecular mechanisms associated with these variants and advance potential therapeutic options, which may help fight and/or prevent COVID-19.

freqpcr: estimation of population allele frequency using qPCR ΔΔCq measures from bulk samples

PCR techniques, both quantitative (qPCR) and non-quantitative, have been used to estimate allele frequency in a population. However, the labor required to sample numerous individuals, and subsequently handle each sample, makes quantification of rare mutations, including pesticide resistance genes at the early stages of resistance development, challenging. Meanwhile, pooling DNA from multiple individuals as a “bulk sample” may reduce handling costs. The qPCR output for a bulk sample, however, contains uncertainty owing to variations in DNA yields from each individual, in addition to measurement errors. In this study, we developed a statistical model for the interval estimation of allele frequency using ΔΔCq-based qPCR analyses of multiple bulk samples collected from a population. We assumed a gamma distribution as the individual DNA yield and developed an R package for parameter estimation, which was verified with real DNA samples from acaricide-resistant spider mites, as well as a numerical simulation. Our model resulted in unbiased point estimates of the allele frequency compared with simple averaging of the ΔΔCq values, while their confidence intervals suggest that collecting and pooling additional samples from individuals may produce higher precision than individual PCR tests with moderate sample sizes.

. Identification of CYP2C9, VKORC1 genotypes and recommendation of warfarin dose for Vietnamese cardiovascular patients

Warfarin is a well-known anticoagulant that capable of reducing the activity of vitamin K-dependent clotting factors. It has been widely used for cardiovascular patients. However, patient’s genotype of CYP2C9 and VKORC1 remarkably affects the metabolism of warfarin. This study aims to identify the CYP2C9 and VKORC1 genotypes of 96 Vietnamese patients suffering cardiodynia or myocardial infarction and establish their daily warfarin dose. The PCR-RFLP method was used to identified the CYP2C9*2, CYP2C9*3 and VKORC1 alleles. The result indicated that allelic frequencies for CYP2C9*3 were observed at 3% of investigated patients while CYP2C9*2 alleles and genotypes were not detected in this study population. Allele frequency of VKORC1 (c. -1639G>A) was observed at 84%. Base on the CYP2C9 and VKORC1 genotypes, we recommended the daily warfarin dose for of these patients.

De novo missense variants in LMBRD2 are associated with developmental and motor delays, brain structure abnormalities and dysmorphic features

ObjectiveTo determine the potential disease association between variants in LMBRD2 and complex multisystem neurological and developmental delay phenotypes.MethodsHere we describe a series of de novo missense variants in LMBRD2 in 10 unrelated individuals with overlapping features. Exome sequencing or genome sequencing was performed on all individuals, and the cohort was assembled through GeneMatcher.ResultsLMBRD2 encodes an evolutionary ancient and widely expressed transmembrane protein with no known disease association, although two paralogues are involved in developmental and metabolic disorders. Exome or genome sequencing revealed rare de novo LMBRD2 missense variants in 10 individuals with developmental delay, intellectual disability, thin corpus callosum, microcephaly and seizures. We identified five unique variants and two recurrent variants, c.1448G>A (p.Arg483His) in three cases and c.367T>C (p.Trp123Arg) in two cases. All variants are absent from population allele frequency databases, and most are predicted to be deleterious by multiple in silico damage-prediction algorithms.ConclusionThese findings indicate that rare de novo variants in LMBRD2 can lead to a previously unrecognised early-onset neurodevelopmental disorder. Further investigation of individuals harbouring LMBRD2 variants may lead to a better understanding of the function of this ubiquitously expressed gene.

Effective variant filtering and expected candidate variant yield in studies of rare human disease

ABSTRACTIn studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we derive effective guidelines for variant filtering and report the expected number of candidates for de novo dominant and recessive modes of inheritance. The filters are applied to common attributes, including genotype quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield approximately 10 candidate SNP and INDEL variants per exome, and 19 per genome. For whole genomes, this includes an average of three de novo, ten compound-heterozygotes, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

Mutation Rate Model Used in the DNA VIEW Program

The first problem considered in this paper is the problem of correctness of a mutation model used in the DNA VIEW program. To this end, we theoretically predict population allele frequency changes in time according to this and similar models (we determine the limit frequencies of alleles—they are uniformly distributed). Furthermore, we evaluate the speed of the above changes using computer simulation applied to our DNA database. Comparing uniformly distributed allele frequencies with these existing in the population (for example, using entropy), we conclude that this mutation model is not correct. The evolution does not follow this direction (direction of uniformly distributed frequencies). The second problem relates to the determination of the extent to which an incorrect mutation model can disturb DNA VIEW program results. We show that in typical computations (simple paternity testing without maternal mutation) this influence is negligible, but in the case of maternal mutation, this should be taken into account. Furthermore, we show that this model is inconsistent from a theoretical viewpoint. Equivalent methods result in different error levels.

MicroHapDB: a portable and extensible database of all published microhaplotype marker and frequency data

ABSTRACTMicrohaplotypes are the subject of significant interest in the forensics community as a promising multi-purpose forensic DNA marker for human identification. Microhaplotype markers are composed of multiple SNPs in close proximity, such that a single NGS read can simultaneously genotype the individual SNPs and phase them in aggregate to determine the associated donor haplotype. Abundant throughout the human genome, numerous recent studies have sought to discover and rank microhaplotype markers according to allelic diversity within and among populations. Microhaplotypes provide an appealing alternative to STR markers for human identification and mixture deconvolution, but can also be optimized for ancestry inference or combined with phenotype SNPs for prediction of externally visible characteristics in a multiplex NGS assay. Designing and evaluating panels of microhaplotypes is complicated by the lack of a convenient database of all published data, as well as the lack of population allele frequency data spanning disparate marker collections. We present MicroHapDB, a comprehensive database of published microhaplotype marker and frequency data, as a tool to advance the development of microhaplotype-based human forensics capabilities. We also present population allele frequencies derived from 26 global population samples for all microhaplotype markers published to date, facilitating the design and interpretation of custom multi-source panels. We submit MicroHapDB as a resource for community members engaged in marker discovery, population studies, assay development, and panel and kit design.

Linking a mutation to survival in wild mice

Adaptive evolution in new or changing environments can be difficult to predict because the functional connections between genotype, phenotype, and fitness are complex. Here, we make these explicit connections by combining field and laboratory experiments in wild mice. We first directly estimate natural selection on pigmentation traits and an underlying pigment locus, Agouti, by using experimental enclosures of mice on different soil colors. Next, we show how a mutation in Agouti associated with survival causes lighter coat color through changes in its protein binding properties. Together, our findings demonstrate how a sequence variant alters phenotype and then reveal the ensuing ecological consequences that drive changes in population allele frequency, thereby illuminating the process of evolution by natural selection.