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As a new crop in Malaysia, forty-four Bambara groundnut ( Vigna subterranea L. verdc.) genotypes were sampled from eleven distinct populations of different origins to explore the genetic structure, genetic inconsistency, and fixation index. The Bambara groundnut, an African underutilized legume, has the capacity to boost food and nutrition security while simultaneously addressing environmental sustainability, food availability, and economic inequalities. A set of 32 ISSRs were screened out of 96 primers based on very sharp, clear, and reproducible bands which detected a total of 510 loci with an average of 97.64% polymorphism. The average calculated value of PIC  = 0.243, RP  = 5.30, H  = 0.285, and MI  = 0.675 representing the efficiency of primer set for genetic differentiation among the genotypes. The ISSR primers revealed the number of alleles ( Na  = 1.97), the effective number of alleles ( Ne  = 1.38), Nei's genetic diversity ( h  = 0.248), and a moderate level of gene flow ( Nm  = 2.26) across the genotypes studied. The estimated Shannon’s information index ( I  = 0.395) indicates a high level of genetic variation exists among the accessions. Based on Nei’s genetic dissimilarity a UPMGA phylogenetic tree was constructed and grouped the entire genotypes into 3 major clusters and 6 subclusters. PCA analysis revealed that first principal component extracted maximum variation (PC1 = 13.92%) than second principal component (PC2 = 12.59%). Bayesian model-based STRUCTURE analysis assembled the genotypes into 3 (best ΔK = 3) genetic groups. The fixation-index (F st ) analysis narrated a very great genetic diversity (F st  = 0.19 to 0.40) exists within the accessions of these 3 clusters. This investigation specifies the effectiveness of the ISSR primers system for the molecular portrayal of V. subterranea genotypes that could be used for genetic diversity valuation, detection, and tagging of potential genotypes with quick, precise, and authentic measures for this crop improvement through effective breeding schemes.

Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.

Inferring subject ancestry using genetic data is an important step in genetic association studies, required for dealing with population stratification. It has become more challenging to infer subject ancestry quickly and accurately since large amounts of genotype data, collected from millions of subjects by thousands of studies using different methods, are accessible to researchers from repositories such as the database of Genotypes and Phenotypes (dbGaP) at the National Center for Biotechnology Information (NCBI). Study-reported populations submitted to dbGaP are often not harmonized across studies or may be missing. Widely-used methods for ancestry prediction assume that most markers are genotyped in all subjects, but this assumption is unrealistic if one wants to combine studies that used different genotyping platforms. To provide ancestry inference and visualization across studies, we developed a new method, GRAF-pop, of ancestry prediction that is robust to missing genotypes and allows researchers to visualize predicted population structure in color and in three dimensions. When genotypes are dense, GRAF-pop is comparable in quality and running time to existing ancestry inference methods EIGENSTRAT, FastPCA, and FlashPCA2, all of which rely on principal components analysis (PCA). When genotypes are not dense, GRAF-pop gives much better ancestry predictions than the PCA-based methods. GRAF-pop employs basic geometric and probabilistic methods; the visualized ancestry predictions have a natural geometric interpretation, which is lacking in PCA-based methods. Since February 2018, GRAF-pop has been successfully incorporated into the dbGaP quality control process to identify inconsistencies between study-reported and computationally predicted populations and to provide harmonized population values in all new dbGaP submissions amenable to population prediction, based on marker genotypes. Plots, produced by GRAF-pop, of summary population predictions are available on dbGaP study pages, and the software, is available at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/Software.cgi.

Introgression can be an important source of adaptive phenotypes, although conversely it can have deleterious effects. Evidence for adaptive introgression is accumulating but information on the genetic architecture of introgressed traits lags behind. Here we determine trait architecture in Populus trichocarpa under introgression from P. balsamifera using admixture mapping and phenotypic analyses. Our results reveal that admixture is a key driver of clinal adaptation and suggest that the northern range extension of P. trichocarpa depends, at least in part, on introgression from P. balsamifera. However, admixture with P. balsamifera can lead to potentially maladaptive early phenology, and a reduction in growth and disease resistance in P. trichocarpa. Strikingly, an introgressed chromosome 9 haplotype block from P. balsamifera restores the late phenology and high growth parental phenotype in admixed P. trichocarpa. This epistatic restorer block may be strongly advantageous in maximizing carbon assimilation and disease resistance in the southernmost populations where admixture has been detected. We also confirm a previously demonstrated case of adaptive introgression in chromosome 15 and show that introgression generates a transgressive chlorophyll-content phenotype. We provide strong support that introgression provides a reservoir of genetic variation associated with adaptive characters that allows improved survival in new environments.

Inferring the genetic structure at the subpopulation level is crucial for understanding the demographic histories that shape genetic diversity. Among the most widely used approaches are methods based on admixture and structure modeling—named after the respective software tools—which have become standard due to their intuitive, interpretable outputs. In this study, we address a key methodological question: how does the traditional admixture-based decomposition of genetic components in multilocus population data relate to clustering approaches that leverage machine learning, specifically Self-Organizing Maps (SOMs)? We implemented this approach through our custom SOM-based tool, SOMmelier, which enables the portrayal of genetic structure by identifying modules of co-mutated SNPs and arranging them in a topology-aware genetic landscape. Topology-awareness refers to the organization of genetic modules in a two-dimensional map, where their spatial proximity reflects mutual similarity. We applied Admixture and SOMmelier to investigate the population genetics of European grapevine. Based on prior literature, we considered up to six genetic components, which formed a genetic landscape that closely mirrors the geographic expanse of the classical Mediterranean world—from Western Asia through the Caucasus to Western Europe. The resulting topology reflects the dynamic spatial and temporal nature of grapevine domestication and diffusion. We demonstrate that SOMmelier can recover the genetic components identified by Admixture solely through statistical clustering. By integrating the topological structure of SNP co-variation, it offers perspectives on population structure, evolutionary history, and trait associations in grapevine—and has applicability to other species and systems in population genetics.

Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.

Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. PA has at least a 50% higher incidence in populations of European ancestry compared to other ancestral groups, which may be due in part to genetic differences. We first compared the global proportions of European, African, and Amerindian ancestries in 301 PA cases and 1185 controls of self-identified Latino ethnicity from the California Biobank. We then conducted admixture mapping analysis to assess PA risk with local ancestry. We found PA cases had a significantly higher proportion of global European ancestry than controls (case median = 0.55, control median = 0.51, P value = 3.5x10-3). Admixture mapping identified 13 SNPs in the 6q14.3 region (SNX14) contributing to risk, as well as three other peaks approaching significance on chromosomes 7, 10 and 13. Downstream fine mapping in these regions revealed several SNPs potentially contributing to childhood PA risk. There is a significant difference in genomic ancestry associated with Latino PA risk and several genomic loci potentially mediating this risk.

The genomic architecture of functionally important traits is key to understanding the maintenance of reproductive barriers and trait differences when divergent populations or species hybridize. We conducted a genome-wide association study (GWAS) to study trait architecture in natural hybrids of two ecologically divergent Populus species. We genotyped 472 seedlings from a natural hybrid zone of Populus alba and Populus tremula for genome-wide markers from reduced representation sequencing, phenotyped the plants in common gardens for 46 phytochemical (phenylpropanoid), morphological and growth traits, and used a Bayesian polygenic model for mapping. We detected three classes of genomic architectures: traits with finite, detectable associations of genetic loci with phenotypic variation in addition to highly polygenic heritability; traits with indications for polygenic heritability only; and traits with no detectable heritability. For the first class, we identified genome regions with plausible candidate genes for phenyl-propanoid biosynthesis or its regulation, including MYB transcription factors and glycosyl transferases. GWAS in natural, recombinant hybrids represent a promising step towards resolving the genomic architecture of phenotypic traits in long-lived species. This facilitates the fine-mapping and subsequent functional characterization of genes and networks causing differences in hybrid performance and fitness.

Admixture, the exchange of genetic information between distinct source populations, is thought to be a major source of adaptive genetic variation. Unlike mutation events, which periodically generate single alleles, admixture can introduce many selected alleles simultaneously. As such, the effects of linkage between selected alleles may be especially pronounced in admixed populations. However, existing tools for identifying selected mutations within admixed populations only account for selection at a single site, overlooking phenomena such as linkage among proximal selected alleles. Here, we develop and extensively validate a method for identifying and quantifying the individual effects of multiple linked selected sites on a chromosome in admixed populations. Our approach numerically calculates the expected local ancestry landscape in an admixed population for a given multi-locus selection model, and then maximizes the likelihood of the model. After applying this method to admixed populations of Drosophila melanogaster and Passer italiae , we found that the impacts between linked sites may be an important contributor to natural selection in admixed populations. Furthermore, for the situations we considered, the selection coefficients and number of selected sites are overestimated in analyses that do not consider the effects of linkage among selected sites. Our results imply that linkage among selected sites may be an important evolutionary force in admixed populations. This tool provides a powerful generalized method to investigate these crucial phenomena in diverse populations.

The European whitefish (Coregonus lavaretus) species complex is a classic example of recent adaptive radiation. Here, we examine a whitefish population introduced to northern Finnish Lake Tsahkal in the late 1960s, where three divergent morphs (viz. littoral, pelagic, and profundal feeders) were found 10 generations after. Using demographic modeling based on genomic data, we show that whitefish morphs evolved during a phase of strict isolation, refuting a rapid sympatric divergence scenario. The lake is now an artificial hybrid zone between morphs originated in allopatry. Despite their current syntopy, clear genetic differentiation remains between two of the three morphs. Using admixture mapping, we identify five SNPs associated with gonad weight variation, a proxy for sexual maturity and spawning time. We suggest that ecological adaptations in spawning time evolved in allopatry are currently maintaining partial reproductive isolation in the absence of other barriers to gene flow.