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Gene drives have great potential for suppression of pest populations and removal of exotic invasive species. CRISPR homing suppression drive is a powerful but unconfined drive, posing risks of uncontrolled spread. Thus, developing methods for confining a gene drive is of great significance. Tethered drive combines a confined system such as Toxin-Antidote Recessive Embryo drive with a strong drive such as a homing suppression drive. It can prevent the homing drive from spreading beyond the confined drive and can be constructed readily, giving it good prospects for future development. However, we have found that care must be taken when deploying tethered drive systems in some scenarios. Simulations of tethered drive in a panmictic population model reveal that successful deployment requires a proper release ratio between the two components, tailored to prevent the suppression drive from eliminating the confined system before it has the chance to spread. Spatial models where the population moves over a one-dimensional landscape display a more serious phenomenon of drive wave interference between the two tethered drive components. If the faster suppression drive wave catches up to the confined drive wave, success is still possible, but it is dependent on drive performance and ecological parameters. Two-dimensional simulations further restrict the parameter range for drive success. Thus, careful consideration must be given to drive performance and ecological conditions, as well as specific release proposals for potential application of tethered drive systems.

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Aspen (Populus tremula L.) is a keystone species and a model system for forest tree genomics. We present an updated resource comprising a chromosome-scale assembly, population genetics and genomics data. Using the resource, we explore the genetic basis of natural variation in leaf size and shape, traits with complex genetic architecture. We generated the genome assembly using long-read sequencing, optical and high-density genetic maps. We conducted whole-genome resequencing of the Umeå Aspen (UmAsp) collection. Using the assembly and re-sequencing data from the UmAsp, Swedish Aspen (SwAsp) and Scottish Aspen (ScotAsp) collections we performed genome-wide association analyses (GWAS) using Single Nucleotide Polymorphisms (SNPs) for 26 leaf physiognomy phenotypes. We conducted Assay of Transposase Accessible Chromatin sequencing (ATAC-Seq), identified genomic regions of accessible chromatin, and subset SNPs to these regions, improving the GWAS detection rate. We identified candidate long non-coding RNAs in leaf samples, quantified their expression in an updated co-expression network, and used this to explore the functions of candidate genes identified from the GWAS. A GWAS found SNP associations for seven traits. The associated SNPs were in or near genes annotated with developmental functions, which represent candidates for further study. Of particular interest was a ~177-kbp region harbouring associations with several leaf phenotypes in ScotAsp. We have incorporated the assembly, population genetics, genomics, and GWAS data into the PlantGenIE.org web resource, including updating existing genomics data to the new genome version, to enable easy exploration and visualisation. We provide all raw and processed data to facilitate reuse in future studies.

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One of the aims of population genetics is to identify genetic differences/similarities among individuals of multiple ancestries. Many approaches including principal component analysis, clustering, and maximum likelihood techniques can be used to assign individuals to a given ancestry based on their genetic makeup. Although there are several tools that implement such algorithms, there is a lack of interactive visual platforms to run a variety of algorithms in one place. Therefore, we developed PopMLvis, a platform that offers an interactive environment to visualize genetic similarity data using several algorithms, and generate figures that can be easily integrated into scientific articles.

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Thyrinteina arnobia (Lepidoptera: Geometridae) is a native American species. Despite its historical importance as an insect pest in Eucalyptus plantations, more information is needed regarding the population diversity, demography, and climatic variables associated with its distribution in different regions of Brazil. We used a phylogeographic approach to infer the genetic diversity, genetic structure, and demographic parameters of T. arnobia. We also conducted an ecological niche modeling (ENM) to predict suitable areas for T. arnobia occurrence in Brazil and other countries worldwide. Although T. arnobia populations have low genetic diversity in Brazil, we identified mitochondrial haplogroups predominating in different Brazilian regions and high ФST and ФCT values in AMOVA, suggesting a low frequency of insect movement among these regions. These results indicate that outbreaks of T. arnobia in Eucalyptus areas in different regions of Brazil are associated with local or regional populations, with no significant contribution from long-distance dispersal from different regions or biomes, suggesting that pest management strategies would be implemented on a regional scale. In Brazil, the demographic and spatial expansion signals of T. arnobia seem to be associated with the history of geographical expansion of Eucalyptus plantations, a new sustainable host for this species. ENM indicated that isothermality and annual rainfall are critical climatic factors for the occurrence of T. arnobia in tropical and subtropical areas in the Americas. ENM also suggested that T. arnobia is a potential pest in Eucalyptus areas in all Brazilian territory and in regions from Africa, Asia, and Oceania.

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Coprinellus disseminatus and other morphologically similar species are widely dispersed worldwide and are commonly referred to as "fairy inkcap". Based on the molecular phylogenetic study and morphological observation, a thorough investigation was carried out utilising 74 collections of related species that were gathered from seventeen provinces and five Chinese fungaria between 1998 and 2023 and revealed 11 lineages of "fairy inkcap", nine of which were found in China, and which belonged to the two genera Coprinellus and Tulosesus. In sect. Disseminati, genetic diversities (π), and fixation index (Fst) amongst lineages were computed, and a haplotype-based network was established to ascertain the relationships amongst each clade. A new section of Coprinellus, sect. Aureodisseminati, were discovered. In addition, four new species (C. aureodisseminatus, C. austrodisseminatus, C. parcus, and C. velutipes), a new subspecies of C. disseminatus, a new combination (Tulosesus pseudodisseminatus), the first discovery of epigamous type of C. magnoliae and a new record to China (T. subdisseminatus) were also identified and thoroughly described with accompanying illustrations. Their differences in macro- and micro-features, as well as their character sequence, were discussed.

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BACKGROUND: Centromere function is highly conserved across eukaryotes, but the underlying centromeric DNA sequences vary dramatically between species. Centromeres often contain a high proportion of repetitive DNA, such as tandem repeats and/or transposable elements (TEs). Einkorn wheat centromeres lack tandem repeat arrays and are instead composed mostly of the two long terminal repeat (LTR) retrotransposon families RLG_Cereba and RLG_Quinta which specifically insert in centromeres. However, it is poorly understood how these two TE families relate to each other and if and how they contribute to centromere function and evolution. RESULTS: Based on conservation of diagnostic motifs (LTRs, integrase and primer binding site and polypurine-tract), we propose that RLG_Cereba and RLG_Quinta are a pair of autonomous and non-autonomous partners, in which the autonomous RLG_Cereba contributes all the proteins required for transposition, while the non-autonomous RLG_Quinta contributes GAG protein. Phylogenetic analysis of predicted GAG proteins showed that the RLG_Cereba lineage was present for at least 100 million years in monocotyledon plants. In contrast, RLG_Quinta evolved from RLG_Cereba between 28 and 35 million years ago in the common ancestor of oat and wheat. Interestingly, the integrase of RLG_Cereba is fused to a so-called CR-domain, which is hypothesized to guide the integrase to the functional centromere. Indeed, ChIP-seq data and TE population analysis show only the youngest subfamilies of RLG_Cereba and RLG_Quinta are found in the active centromeres. Importantly, the LTRs of RLG_Quinta and RLG_Cereba are strongly associated with the presence of the centromere-specific CENH3 histone variant. We hypothesize that the LTRs of RLG_Cereba and RLG_Quinta contribute to wheat centromere integrity by phasing and/or placing CENH3 nucleosomes, thus favoring their persistence in the competitive centromere-niche. CONCLUSION: Our data show that RLG_Cereba cross-mobilizes the non-autonomous RLG_Quinta retrotransposons. New copies of both families are specifically integrated into functional centromeres presumably through direct binding of the integrase CR domain to CENH3 histone variants. The LTRs of newly inserted RLG_Cereba and RLG_Quinta elements, in turn, recruit and/or phase new CENH3 deposition. This mutualistic interplay between the two TE families and the plant host dynamically maintains wheat centromeres.

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Botrytis blossom blight and fruit rot, caused by Botrytis cinerea, is a significant threat to blueberries, potentially resulting in substantial economic losses if not effectively managed. Despite the recommendation of various cultural and chemical practices to control this pathogen, there are widespread reports of fungicide resistance, leading to decreased efficacy. This study aimed to characterize the resistance profile of B. cinerea isolated from blighted blossoms and fruit in 2019, 2020 and 2022 (n = 131, 40, and 37 for the respective years). Eight fungicides (fludioxonil, thiabendazole, pyraclostrobin, boscalid, fluopyram, fenhexamid, iprodione, and cyprodinil) were tested using conidial germination at specific discriminatory doses. Additionally, 86 isolates were phylogenetically characterized using the internal transcribed spacer regions (ITS) and the protein coding genes: glyceraldehyde-3-phosphate dehydrogenase (G3PDH), heat-shock protein 60 (HSP60), and RNA polymerase II second largest subunit (RPB2). This revealed higher fungicide resistance frequencies in 2020 and 2022 compared to 2019. Over all 3 years, over 80% of the isolates were sensitive to fludioxonil, fluopyram, and fenhexamid. Pyraclostrobin and boscalid showed the lowest sensitivity frequencies (<50%). While multi-fungicide resistance was observed in all the years, none of the isolates demonstrated simultaneous resistance to all tested fungicides. Botrytis cinerea was the most prevalent species among the isolates (74) with intraspecific diversity detected by the genes. Two isolates were found to be closely related to B. fabiopsis, B. galanthina, and B. caroliniana and 10 isolates appeared to be an undescribed species. This study reports the discovery of a potentially new species sympatric with B. cinerea on blueberries in Michigan.

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Winter flounder Pseudopleuronectes americanus (Walbaum 1792) are a coastal flatfish species of economic and cultural importance that have dwindled to <15, % of their historic abundance in the southern New England/Mid-Atlantic region of the United States, with evidence indicating near-extirpation of certain local populations. This species exhibits intricate behaviors in spawning and migration that contribute to population complexity and resilience. These behaviors encompass full or partial philopatry to natal estuaries, the generation of multiple pulses of larval delivery, and partial migration. The patterns of genetic diversity within and among estuaries and cohorts presented here carry important implications in understanding the susceptibility to demographic shocks, even if the full extent of genetic diversity within and among winter flounder stocks on the US East Coast remains unresolved. Our findings reveal connectivity between estuaries in Long Island, New York, suggesting the potential for genetic rescue of depleted subpopulations. Family reconstruction and relatedness analysis indicate that split cohorts and migration contingents are not the result of genetically distinct lineages. We found no evidence for genetic structure separating these groups, and in some instances, we were able to detect closely related individuals that belonged to different migratory contingents or cohorts. Characterizing the spatial and behavioral organization of this species at the population level is crucial for comprehending its potential for recovery, not only in terms of biomass but also in reinstating the complex population structure that supports resilience. The search for generality in winter flounder spawning and migration behavior remains elusive, but perhaps the lack of generalities within this species is what has allowed it to persist in the face of decades of environmental and anthropogenic stressors.

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A comprehensive knowledge of human leukocyte antigen (HLA) molecular variation worldwide is essential in human population genetics research and disease association studies and is also indispensable for clinical applications such as allogeneic hematopoietic cell transplantation, where ensuring HLA compatibility between donors and recipients is paramount. Enormous progress has been made in this field thanks to several decades of HLA population studies allowing the development of helpful databases and bioinformatics tools. However, it is still difficult to appraise the global HLA population diversity in a synthetic way. We thus introduce here a novel approach, based on approximately 2000 data sets, to assess this complexity by providing a fundamental synopsis of the most frequent HLA alleles observed in different regions of the world. This new knowledge will be useful not only as a fundamental reference for basic research, but also as an efficient guide for clinicians working in the field of transplantation.

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BACKGROUND: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare and lethal arrhythmia. Ryanodine receptor 2 (RYR2) mutation accounts for ∼60% of CPVT patients which is inherited in an autosomal dominant pattern. OBJECTIVE: This study aimed to identify CPVT-related mutations and clinical characteristics among Taiwanese CPVT patients and compare to other cohorts worldwide. METHODS: Clinical and genetic data were obtained from the Sudden Arrhythmia Death Syndrome Registry in Taiwan (SADS-TW). Forty clinically diagnosed Taiwanese CPVT patients were included. RESULTS: This is the first nationwide CPVT cohort in Taiwan. Among the 29 Taiwanese patients with CPVT-related gene mutations, 55% had RYR2 mutations, a rate similar to other ethnicities. Three out of 12 RYR2 variants were unreported. Exercise-induced symptoms including syncope and cardiac arrest were more frequent in East Asian cohorts (Taiwanese 79%, Japanese 91%), compared to Caucasian cohorts (59%) (p = 0.002). CONCLUSION: The discovery of diverse RYR2 mutations in the Taiwanese CVPT population demonstrates the importance of genetic testing in different ethnicities.

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BACKGROUND: Captive breeding, along with artificial selection can significantly impact population structure by influencing allele frequencies and driving populations towards specific adaptation. Selective sweeps are powerful forces in shaping genetic variation within populations and can drive rapid spread of beneficial alleles while simultaneously reducing genetic diversity in localized regions of the genome. The present work was undertaken to assess the genetic structure and consequences of artificial selection in 10th generation of genetically improved rohu by comparing with wild populations. METHODS AND RESULTS: The present study used 11,022 high-quality genome wide SNPs to compare the population genetic structure and signatures of selection between Jayanti rohu population and its wild counterpart. Outlier analysis revealed presence of 14 adaptive SNPs, out of which 5 were classified to be under decisive selection pressure. Notably, Jayanti rohu (JR) displayed 297 private alleles exclusive to its population. Chromosomes 7 and 16 emerged as potential hotspots containing a majority of the identified SNPs. Structure and principal component analysis revealed two distinct clusters, effectively distinguishing the JR and wild rohu populations. Phylogenetic analysis indicated a separate cluster of JR population distant from wild groups. CONCLUSION: The results of present study shall help in elucidating patterns of genetic variation and characterizing selection signatures associated with captive bred and natural populations of rohu. The genomic resources generated through this work shall be helpful in improving the traceability of selectively bred germplasm for developing future strategies of genetic management.

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Advancements in genome assembly and sequencing technology have made whole genome sequence (WGS) data and reference genomes accessible to study polyploid species. Compared to popular reduced-representation sequencing approaches, the genome-wide coverage and greater marker density provided by WGS data can greatly improve our understanding of polyploid species and polyploid biology. However, biological features that make polyploid species interesting also pose challenges in read mapping, variant identification, and genotype estimation. Accounting for characteristics in variant calling like allelic dosage uncertainty, homology between subgenomes, and variance in chromosome inheritance mode can reduce errors. Here, I discuss the challenges of variant calling in polyploid WGS data and discuss where potential solutions can be integrated into a standard variant calling pipeline.

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BACKGROUND AND AIMS: Species delimitation can be challenging when analysing recently diverged species, especially those taxonomically synonymised due to morphological similarities. We aimed to untangle the relationships between two grassland species, Petunia guarapuavensis and Petunia scheideana, exploring the dynamics of fast divergence and addressing their species delimitation. METHODS: We used a low-coverage genome sequencing and population genomic approach to distinguish species and populations between P. guarapuavensis and P. scheideana. Our analysis focused on detecting structuration, hybridisation/introgression, and phylogenetic patterns. We employed demographic models to support species delimitation while exploring potential phylogeographic barriers influencing gene flow. KEY RESULTS: Our findings indicated differentiation between the two species and revealed another lineage, which was phylogenetically distinct from the others and had no evidence of gene flow with them. The presence of a river acted as a phylogeographic barrier, limiting gene flow and allowing for structuration between closely related lineages. The optimal species delimitation scenario involved secondary contact between well-established lineages. CONCLUSIONS: The rapid divergence observed in these Petunia species explains the lack of significant morphological differences, as floral diagnostic traits in species sharing the pollinators tend to evolve more slowly. This study highlights the complexity of species delimitation in recently diverged groups and emphasises the importance of genomic approaches in understanding evolutionary relationships and speciation dynamics.

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When biological populations expand into new territory, the evolutionary outcomes can be strongly influenced by genetic drift, the random fluctuations in allele frequencies. Meanwhile, spatial variability in the environment can also significantly influence the competition between subpopulations vying for space. Little is known about the interplay of these intrinsic and extrinsic sources of noise in population dynamics: When does environmental heterogeneity dominate over genetic drift or vice versa, and what distinguishes their population genetics signatures? Here, in the context of neutral evolution, we examine the interplay between a population's intrinsic, demographic noise and an extrinsic, quenched random noise provided by a heterogeneous environment. Using a multispecies Eden model, we simulate a population expanding over a landscape with random variations in local growth rates and measure how this variability affects genealogical tree structure, and thus genetic diversity. We find that, for strong heterogeneity, the genetic makeup of the expansion front is to a great extent predetermined by the set of fastest paths through the environment. The landscape-dependent statistics of these optimal paths then supersede those of the population's intrinsic noise as the main determinant of evolutionary dynamics. Remarkably, the statistics for coalescence of genealogical lineages, derived from those deterministic paths, strongly resemble the statistics emerging from demographic noise alone in uniform landscapes. This cautions interpretations of coalescence statistics and raises new challenges for inferring past population dynamics.

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A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.

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Reproductive interference is defined as an interspecific interaction that reduces fitness via mating processes. Although its ecological and evolutionary consequences have attracted much attention, how reproductive interference affects the population genetic structures of interacting species is still unclear. In flowering plants, recent studies found that self-pollination can mitigate the negative effects of reproductive interference. Selfing-biased seed production is expected to increase population-level inbreeding and the selfing rate, and limits gene flow via pollinator outcrossing among populations. We examined the population genetics of the mixed-mating annual herb Commelina communis f. ciliata, focusing on reproductive interference by the sympatric competing congener C. communis using microsatellite markers. First, we found that almost all C. c. f. ciliata populations had relatively high inbreeding coefficients. Then, comparing sympatric and allopatric populations, we found evidence that reproductive interference from a competing congener increased the inbreeding coefficient and selfing rate. Allopatric populations exhibit varied selfing rates while almost all sympatric populations exhibit extremely high selfing rates, suggesting that population selfing rates were also influenced by unexamined factors, such as pollinator limitation. Besides, our findings revealed that reproductive interference from a competing congener did not limit gene flow among populations. We present the first report on how reproductive interference affects the genetic aspects of populations. Our results suggested that the high selfing rate of C. c. f. ciliata promotes its sympatric distribution with C. communis, even in the presence of reproductive interference, although it is not clear whether reproductive interference directly causes the high selfing rate.

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Haemophilus influenzae is part of the human nasopharyngeal microbiota and a pathogen causing invasive disease. The extensive genetic diversity observed in H. influenzae necessitates discriminatory analytical approaches to evaluate its population structure. This study developed a core genome multilocus sequence typing (cgMLST) scheme for H. influenzae using pangenome analysis tools and validated the cgMLST scheme using datasets consisting of complete reference genomes (N = 14) and high-quality draft H. influenzae genomes (N = 2297). The draft genome dataset was divided into a development dataset (N = 921) and a validation dataset (N = 1376). The development dataset was used to identify potential core genes, and the validation dataset was used to refine the final core gene list to ensure the reliability of the proposed cgMLST scheme. Functional classifications were made for all the resulting core genes. Phylogenetic analyses were performed using both allelic profiles and nucleotide sequence alignments of the core genome to test congruence, as assessed by Spearman's correlation and ordinary least square linear regression tests. Preliminary analyses using the development dataset identified 1067 core genes, which were refined to 1037 with the validation dataset. More than 70% of core genes were predicted to encode proteins essential for metabolism or genetic information processing. Phylogenetic and statistical analyses indicated that the core genome allelic profile accurately represented phylogenetic relatedness among the isolates (R 2 = 0.945). We used this cgMLST scheme to define a high-resolution population structure for H. influenzae, which enhances the genomic analysis of this clinically relevant human pathogen.

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Genetic variability persists across diverse populations, and it may impact the characterization of heritable diseases in different ancestral groups. Cystinosis is a metabolic disease caused by pathogenic variants in the CTNS gene causing the cellular accumulation of cystine. We attempted to assess the currently poorly characterized prevalence of cystinosis by employing a population genetics methodology. However, we encountered a significant challenge due to genetic variations across different populations, and the consideration of potential disparities in access to healthcare made our results inconclusive. Pathogenic CTNS variants were identified in a representative global population cohort using The Human Gene Mutation Database (HGMD) and the 1000 Genomes (1 KG) database. The c.124G>A (p.Val42Ile) variant was reported to be pathogenic based on an observation in the white population presenting with atypical phenotypes, but it would be reclassified as benign in the African ancestral group if applying the ACMG allele frequency guideline due to its high allele frequency specifically in this population. Inclusion or exclusion of this c.124G>A (p.Val42Ile) variant results in a significant change in estimated disease prevalence, which can impact the diagnosis and treatment of affected patients with a broad range of phenotypic presentations. This observation led us to postulate that pathogenic manifestations of the disease may be underdiagnosed due to variable expressivity and systemic inequities in access to care, specifically in the African subpopulation. We call for a more cautious and inclusive approach to achieve more equitable care across diverse populations.

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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.

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With the advent of "next-generation" sequencing and the continuous reduction in sequencing costs, an increasing amount of genomic data has emerged, such as whole-genome, whole-exome, and targeted sequencing data. These applications are popular not only in mega sequencing projects, such as the 1000 Genomes Project and UK BioBank, but also among individual researchers. Evolutionary genetic analyses, such as the dN/dS ratio and Tajima's D, are demanded more and more for whole-genome-level population data. These analyses are often carried out under a uniform custom bin size across the genome. However, these analyses require subdivision of a genomic region into functional units, such as protein-coding regions, introns, and untranslated regions, and computing these genetic measures for large-scale data remains challenging. In a recent investigation, we successfully devised a method to address this issue. This method requires a multi-sample VCF file containing population data, a reference genome, target regions in the BED file, and a list of samples to be included in the analysis. Given that the targeted regions are extracted in a new VCF file, targeted population genetic analysis can be performed. We conducted Tajima's D analysis using this approach on intact and pseudogenes, as well as non-coding regions.