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Inference of Population Structure Using Multilocus Genotype Data
Abstract
We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
... FST values between pairs of populations were used to construct a neighbor-joining tree [25] with the software MEGA X [26]. 6 A Bayesian analysis of genetic structure was also carried out using the software STRUCTURE version 2.3.3 [27]. The genotypic data of populations was analyzed under an admixture model of correlated allele frequencies among populations [28]. ...
... Results from STRUCTURE were processed with CLUMPP and DIStruct, and a graphical image of ancestral gene clusters were generated [12,13]. The number of clusters that best explained the data were determined by computing the posterior probability of K supported by the estimates of the posterior probabilities of the data P(X|K) following Pritchard et al. [27], and the maximum posterior probability differences (ΔK) of contiguous K obtained by the Delta method of Evanno et al. [29]. ...
The grooved carpet-shell clam is one of the most economically relevant shellfish species living in the Mediterranean and nearby Atlantic coasts. Previous studies using different types of genetic markers showed a remarkable genetic divergence of the Eastern Mediterranean, Western Mediterranean and Atlantic populations, but important details remained unclear. Here, data from six nuclear introns scored for restriction fragment size polymorphisms in eight populations that have not been studied before have been pooled for the analysis with data scattered through three previous studies, totaling 32 samples from 29 locations. The results show lower levels of heterozygosity, higher mean number of alleles, and alleles with restricted distribution in the Mediterranean populations, suggesting the existence of a large isolated population in the eastern Mediterranean at the middle Pleistocene. The data also confirm the similarity of populations from Tunisia to western Mediterranean populations. Finally, a genetic mosaic is apparent in the Atlantic coasts of the Iberian Peninsula, with a divergence of Rias Baixas populations from more northern populations and Central Portugal populations. The effects of oceanic fronts, seasonal upwellings, river plumes and/or fishery management operations could explain this and other features of the Atlantic populations.
... Seasonality can be an important driver of species abundance and distribution and has 29 been observed in terrestrial [e.g., 1,2] and aquatic ecosystems [e.g., 3,4]. Periodic 30 changes in the biotic and abiotic environment can often be linked to changes in species 31 biomasses and functional groups. ...
... CC-BY-NC-ND 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is To identify subpopulations within the A. formosa isolates we used the Bayesian 149 clustering analysis software STRUCTURE v2.3.4 [29,30]. We set the number of 150 . ...
Most ecosystems are characterized by seasonality, which, through biotic and abiotic changes, influences species biomass dynamics. Recent studies have shown that ecologically important traits can evolve rapidly in response to environmental changes, resulting in eco-evolutionary dynamics with consequences for population and community dynamics. Evidence for seasonal effects on intraspecific variation is still scarce and understanding eco-evolutionary dynamics in the presence of seasonal fluctuations remains a major challenge. Following the phytoplankton spring bloom in Lake Constance, we investigated how seasonal changes influence the intraspecific diversity of Asterionella formosa both at genotypic and phenotypic levels. We found a high degree of genetic and phenotypic differentiation characterizing Asterionella population, explained by a clustering of the isolates into early and late spring according to lake thermal stratification. Yet, most traits related to environmental parameters as well as fitness in different seasonal environments did not show a clear response to seasonality (i.e., temperature and nutrients), indicating that seasonal changes in biotic interactions (i.e., parasitic chytrids) were the major drivers of the observed seasonal shift in Asterionella genotypes. Our results highlight the importance of studying eco-evolutionary processes for understanding variations in population and community dynamics in response to seasonal environmental fluctuations.
... Through the use of 71 SNP markers and a Bayesian statistical model in STRUCTURE v2.3.4 [45], the population structure of the 68 lines was examined. A run-length of 10,000 burning periods and 10,000 MCMC replications were used to accomplish the analysis. ...
... Low-quality SNPs were eliminated before genome-wide association mapping using TASSEL v5.0, which involved excluding markers with a minor allele frequency of less than 5% and a call rate below 75%. TASSEL v5.0 software was employed for the genome-wide association mapping, and the mixed linear model (MLM) was applied with 50,000 permutations for multiple testing corrections [45]. Molecular marker data, phenotypic data, population estimated ancestry (Q matrix), and kinship (K) matrix were all included in the MLM analysis [57]. ...
Keywords: ABSTRACT GWAS, MTA, GBS, SNP, MAS, Elite Breeding lines of Rice Genome-wide association mapping studies (GWAS) in elite breeding line populations aim to identify marker-trait association (MTA) relevant to agronomic traits. Unlike previous GWAS studies that primarily utilized diverse collections of crop germplasm, we had specifically focused on a breeding population to ensure the applicability of our findings to breeding programs. To achieve this, we genotyped the breeding population using genotyping-by-sequencing (GBS) with 71 single nucleotide polymorphism (SNP) markers. Our objective was to expedite the selection process in the breeding program by performing GWAS. We successfully identified 37 MTA associated with agronomic traits. Chromosome 7 exhibited the highest number of significant associations, with eight MTAs. Notably, 27% of the identified MTAs coincided with or were in similar genomic regions as previously reported QTLs or genes from previous studies. The remaining 73% of the MTAs represented new associations that were not previously identified. These findings can be used to boost yield and comprehend the genetic mechanisms of rice by cloning the genes underlying the features and applying them to MAS. SNP markers linked to certain loci can be used to combine advantageous alleles to create new lines with enhanced yield traits. This work is licensed under a Creative Commons Attribution Non-Commercial 4.0 International License.
... In addition, we used the genetic marker FIR059, which exhibits differential and possibly adaptive variation among different refugial regions in southern Europe where Alcaide et al. (2019) and Castellana et al. (2021) found a adaptive correlation to drouht stress with allele distribution. For comparison, we used STRUCTURE (Pritchard et al. 2000) to compare genetic clusters between stands in Mecklenburg Western Pomerania and potential refugial regions using this loci. ...
... Population structure analysis was performed using the STRUCTURE 2.3.4 program (Pritchard et al., 2000) using all 11 SSRs. Due to polyploid patterns the markers EMCs38 and GOT021 were each split into two regions by a threshold allele size. ...
Castanea sativa Mill. is an important European tree species that has been used for timber and nut production since Greek and Roman times. In Germany, the species accounts for only a small proportion of forest stands but it is attracting increasing interest due to its possible potential for climate tolerance and resilience. However, the status of German sweet chestnut stands in terms of genetic diversity and adaptive potential is poorly investigated. We took a representative sample of 520 individuals from 13 stands in northern Germany (Mecklenburg Western Pomerania; MWP) and genotyped these at 11 genomic SSRs and EST-SSRs. In addition, we compared our data with the available literature, focusing on the possible origin of the MWP populations. The analysis of genetic structure identified three distinct genetic groups within MWP, suggesting different origins or seed mixtures of various provenances. The comparison with reference data at the EST-SSR FIR059 suggests that the MWP stands originate from the western gene pool. The genetic variation observed in most MWP stands is at approximately the same level as stands in the natural range. Therefore, these stands with high diversity seem to be particularly suitable for further production of seed and plant material in MWP. This study contributes to the understanding of the genetic diversity and origin of sweet chestnut stands outside their natural distribution in MWP. It provides valuable knowledge for the evaluation and conservation of genetic resources of this tree species, which is expected to receive more attention under warmer and drier conditions.
... Structure ver. 2.3.4 software was used as a model-based approach (Pritchard et al. 2000). This method detected the real number of subpopulations (K) using following criteria: the likelihood of admixture and the correlation between allele frequencies. ...
... For information on population structure in faba bean germplasm based on allelic frequency, we used approaches as described by Pritchard et al. (2000). The analysis of 100 germplasms revealed that the value of K ranged between 2 and 3. ...
In the present study, population structure and genetic diversity were studied among 100 faba bean germplasm lines along with three checks using 29 SSR (microsatellite) markers and morphological traits. ET218734, ET226572, and ET218734 genotypes exhibited maximum seed yield and high mean performance for various yield-attributing traits. The D 2 statistics analysis grouped genotypes into five clusters. SSR marker analysis revealed, on average, 2 alleles per locus ranging from 2 to 3 among the studied genotypes. Polymorphic information content (PIC) for these markers ranged from 0.063 to 0.492 with an average of 0.37. Population structure analysis classified the studied genotypes into three major clusters. The Molecular Diversity Distance was found to be greatest among Cluster III and Cluster I (0.289), while the lowest was among Cluster II and Cluster I (0.148). The allele frequency divergence (expected heterozygosity) was found highest on Cluster II (0.164), and the lowest was on Cluster III (0.096).
... We used the Bayesian clustering program STRUCTURE version 2.3.4 (Falush et al. 2007;Pritchard et al. 2000) to identify genetic groups of all sampled 716 C. subpubescens trees in the Hahajima Islands, then checked whether these genetic groups corresponded to phenotypic groups. This program assigns individuals to K subpopulations (clusters) based on an admixture model and a correlated allele frequencies model. ...
Callicarpa subpubescens, endemic to the Ogasawara Islands, is suggested to have multiple ecotypes in the Hahajima Islands, specifically in the central part of the Ogasawara Islands. In this study, associations between genetic groups and spatial distribution, habitat, leaf morphology, size structure, and flowering time of each genetic group were investigated on Hahajima and the satellite Imoutojima Islands. Genetic groups were identified using EST-SSR markers, revealing four ecotypes named based on morphological features: Dwarf (D), Glabrescent (G), Tall (T), and Middle (M), with M being a result of the hybridization of G and T. Ecotype D, adapted to dry environments, is characterized by small tree size, dense thick leaves with abundant hairs, and is distributed in dry scrub. Ecotype G, adapted to understory of mesic forests, lacks leaf hairs. Ecotype T, adapted to the canopy of mesic forests, has hairy leaves and is tall in tree height. Ecotype M, adapted to the canopy of mesic scrub or edges of mesic forests, has hairy leaves but with a shorter tree height than ecotype T. Flowering peaks differed among all ecotype pairs except G and M, but the flowering times more or less overlapped among all ecotypes, suggesting that pre-mating isolation among ecotypes is not perfect. Postmating isolation is considered absent, as there were no differences in the results, germination, and survival rates of one-year seedlings among inter- and intra-ecotype crossings. The existence of such ecotypes provides valuable insights into the ongoing speciation processes adapting to the oceanic island environments.
... Non-associated loci were then considered as putatively neutral genetic markers. Therefore, 27 SNPs under potential selection were removed (20 for elevation and 8 for health status, 1 of them as common; Table S2) and we created an input file for STRUCTURE version 2.3.3 (Pritchard et al. 2000) using the remaining 44 putatively neutral SNPs. To assess the neutral population genetic structure, we ran the implemented Bayesian clustering algorithm using the admixture model with correlated allele frequencies. ...
The analysis of genetic variation underlying local adaptation in natural populations, together with the response to different external stimuli, is currently a hot topic in forest sciences, with the aim of identifying genetic markers controlling key phenotypic traits of interest for their inclusion in restoration and breeding programs.
In Europe, one of the main tree species is Norway spruce ( Picea abies (L.) H.Karst.). Using the MassARRAY® platform, 568 trees from North Rhine‐Westphalia (Germany) were genotyped with 94 single nucleotide polymorphisms (SNPs) related to circadian and growth rhythms, and to stress response. The association analysis of the selected markers with health status and elevation was performed using three different methods, and those identified by at least two of these were considered as high confidence associated SNPs.
While just five markers showed a weak association with health condition, 32 SNPs were correlated with elevation, six of which were considered as high confidence associated SNPs, as indicated by at least two different association methods. Among these genes, thioredoxin and pseudo response regulator 1 (PRR1) are involved in redox homeostasis and ROS detoxification, APETALA2‐like 3 (AP2L3), a transcription factor, is involved in seasonal apical growth, and a RPS2‐like is a disease resistance gene.
The function of some of these genes in controlling light‐dependent reactions and metabolic processes suggests signatures of adaptation to local photoperiod and the synchronization of the circadian rhythm. This work provides new insights into the genetic basis of local adaptation over a shallow elevation gradient in Norway spruce.
... This information is often used as a basis to infer ancestries. The development of methods to infer population structure has been part of research for decades, with both model-based (Pritchard et al., 2000;Tang et al., 2005;Raj et al., 2014;Behr et al., 2016;Wang, 2022;Dominguez Mantes et al., 2023) and model-free approaches (Patterson et al., 2006;Jombart et al., 2010) being pursued. For a compact summary, we recommend Wang (2022). ...
Understanding the genetic ancestry of populations is central to numerous scientific and societal fields. It contributes to a better understanding of human evolutionary history, advances personalized medicine, aids in forensic identification, and allows individuals to connect to their genealogical roots. Existing methods, such as ADMIXTURE, have significantly improved our ability to infer ancestries. However, these methods typically work with a fixed number of independent ancestral populations. As a result, they provide insight into genetic admixture, but do not include a hierarchical interpretation. In particular, the intricate ancestral population structures remain difficult to unravel. Alternative methods with a consistent inheritance structure, such as hierarchical clustering, may offer benefits in terms of interpreting the inferred ancestries. Here, we present tangleGen, a soft clustering tool that transfers the hierarchical machine learning framework Tangles, originally developed in mathematical graph theory, to the field of population genetics. The hierarchical perspective of tangleGen on the composition and structure of populations improves the interpretability of the inferred ancestral relationships. Moreover, tangleGen adds a new layer of explainability, as it allows identifying the SNPs that are responsible for the clustering structure. We demonstrate the capabilities and benefits of tangleGen for the inference of ancestries, using both simulated data and data from the 1000 Genomes Project.
... We analyzed the existence of population structure with the software Structure v.2.3.4. (Pritchard et al. 2000) under the admixed and correlated allele frequency model. We conducted ten independent runs for each value of K (1-4) using 1,000,000 MCMC iterations following a burn-in period of 500,000 steps, without putative population information. ...
Effective conservation management depends on the maintenance of key areas that allow population connectivity across the landscape. However, the lack of knowledge of how habitat conversion affects species movement hinders the identification of these areas. Here, we analyzed the impact of habitat fragmentation on landscape connectivity for Leopardus guttulus, a small Neotropical felid threatened by the high habitat fragmentation across the Atlantic Forest, and mapped and ranked the most important core areas and corridors for conservation actions. We also estimated genetic diversity indices and predicted the viability of the current core areas in the future. Our analyses suggest that L. guttulus populations are fragmented, and connectivity links between populations are few and weak. We predict that due to their size, estimated density and low connectivity, some current core areas may not maintain viable populations in the long-term. Also, ongoing land-use changes may further isolate remaining populations, leading to progressive reductions in the populations they support. In this study, we spatially prioritize the most critical areas for L. guttulus conservation and highlighted the urge that exists in the adoption of management measures for its conservation.
... using Pandas (McKinney 2010) and Matplotlib(Hunter 2007) in Python 3 (Van Rossum & Drake, 2009). To help visualise the samples for genetic differentiation, it was categorised into the six sampling zones de ned inFig. 1.The number of genetic clusters (K) present in the population was modelled using the programme STRUCTURE v.2.3.1(Pritchard et al., 2000;Falush et al., 2003). The programme relies on a Bayesian clustering algorithm which we used to analyse the data with default settings and a burn-in period of 100 000, followed by 400 000 replicates with no prior population information. Values of K ranged from one to 10, with each K value replicated ve times to assess the most likely numb ...
We investigated the genetic diversity of the contemporary Scottish pine marten population using neutral microsatellite markers, sampling 206 individuals across an area of almost 32,000 km2. Our results revealed that the genetic diversity in the Scottish population is modest with the levels of observed and expected heterozygosity ranging from the Highlands (Ho 0.52, He 0.55) to the Cairngorms (Ho 0.44, He 0.42), and the number of alleles ranged from 3.3 in the Highlands and Central to 2.3 in Dumfries and Galloway, but there were high levels of genetic admixture across the country, some of which may be attributed to natural demographic recovery from previously isolated refuges, and unofficial translocations have also influenced the genetic mixing evident in the population today. Genetic sub structuring, resulting in the Wahlund effect, complicated evaluations of diversity, effective population size, and bottlenecks, and commonly used linkage disequilibrium methods for estimating effective population size yielded improbably low figures. A less commonly used method relying on sibship proved more resilient to the effects of genetic sub structuring, but still yielded estimates under 200, below the viability threshold for long-term population survival. Despite demographic expansion, genetic recovery lagged, suggesting the need for increased gene flow through wildlife corridors.
... These coessential clusters may lead to insights into the underlying structure of the protein homeostasis system. To identify these clusters, we fit a nonparametric Bayesian model based on a Gamma-Poisson model analogous to topic models like Latent Dirichlet Allocation (22,23). and essential components across various protein homeostasis components subjected to proteotoxic stresses of different levels. ...
Every protein progresses through a natural lifecycle from birth to maturation to death; this process is coordinated by the protein homeostasis system. Environmental or physiological conditions trigger pathways that maintain the homeostasis of the proteome. An open question is how these pathways are modulated to respond to the many stresses that an organism encounters during its lifetime. To address this question, we tested how the fitness landscape changes in response to environmental and genetic perturbations using directed and massively parallel transposon mutagenesis in Caulobacter crescentus. We developed a general computational pipeline for the analysis of gene-by-environment interactions in transposon mutagenesis experiments. This pipeline uses a combination of general linear models (GLMs), statistical knockoffs, and a nonparametric Bayesian statistical model to identify essential genetic network components that are shared across environmental perturbations. This analysis allows us to quantify the similarity of proteotoxic environmental perturbations from the perspective of the fitness landscape. We find that essential genes vary more by genetic background than by environmental conditions, with limited overlap among mutant strains targeting different facets of the protein homeostasis system. We also identified 146 unique fitness determinants across different strains, with 19 genes common to at least two strains, showing varying resilience to proteotoxic stresses. Experiments exposing cells to a combination of genetic perturbations and dual environmental stressors show that perturbations that are quantitatively dissimilar from the perspective of the fitness landscape are likely to have a synergistic effect on the growth defect.
... Departures from Hardy-Weinberg proportions within local subpopulations (ponds with N ≥ 14 individuals) were estimated as F IS using the R package HIERFSTAT (v. 0.04-22;Goudet, 2005). The number of distinct genetic clusters K with the highest support was estimated using the Bayesian clustering approaches implemented in STRUCTURE (v.2.3.4;Pritchard et al., 2000) and BAPS (v.6;Corander et al., 2008). For non-spatial clustering in STRUCTURE, an admixture model with correlated allele frequencies was assumed. ...
The intensification of agriculture and urbanisation has precipitated the decline of numerous species, including the northern crested newt (Triturus cristatus). To mitigate the impacts of habitat degradation and loss, restoration initiatives depend on evidence-based decision-making to identify priority sites for conservation efforts. Here, we employed a multidisciplinary approach, drawing on population genetics, species distribution modelling (SDMs) and landscape genetics to develop a spatial prioritisation framework for the creation and/or restoration of crested newt breeding ponds in Luxembourg.
For the genetic analyses, more than 1000 crested newts from 98 ponds across Luxembourg were genotyped at 15 microsatellite loci to assess genetic diversity and spatial clustering. The relationship between newt presence and environmental variables was evaluated using SDMs. Priority restoration areas were identified with PRIORITZR, integrating genetic diversity, habitat suitability and connectivity.
The population genetic structure was characterised by spatial clustering, which followed an isolation-by-distance pattern. Five sites were identified as significantly differentiated from the remaining populations, warranting targeted conservation efforts.
Standing water bodies and proximity to the nearest occupied pond were the most important predictors of crested newt presence. The highest gain in habitat suitability through the creation of new ponds was predicted to occur in southwest Luxembourg.
Based on the country-wide predicted occurrence of crested newts and gains in habitat suitability, areas of highest restoration potential were identified in close proximity to existing crested newt populations. The produced maps of priority restoration areas should inform future conservation efforts of the crested newt in Luxembourg.
While the importance of preserving genetic diversity is widely recognised, the theory-practice gap frequently precludes the incorporation of genetic aspects into in situ conservation measures or management policies. This case study demonstrates the integration of multidisciplinary analyses within an evidence-based framework to guide species conservation efforts.
... The most likely number of distinct genetic clusters (K) was estimated using the Bayesian clustering approach, as implemented in STRUCTURE (v.2.3.4;Pritchard et al., 2000), with the admixture model and correlated allele frequencies. The alternative ancestry prior with separate α for each population and a starting value of 1/K was employed as recommended by Wang (2017). The burn-in period was set to 200,000 Markov chain Monte Carlo (MCMC) iterations, followed by 1000,000 MCMC for each K value ranging from ...
Population genetics is a valuable tool for assessing the impact of human‐altered landscapes on genetic connectivity in various species. However, when applied to insects, challenges arise due to potentially large effective population sizes (), high dispersal capacities and the recency of anthropogenic impacts.
This study assessed the population genetic structure of two pollinators across a human‐altered landscape in Luxembourg. Samples from the ashy mining bee ( Andrena cineraria , N = 201) and the greater bee fly ( Bombylius major, N = 637) were genotyped at 25 microsatellite loci, including a genotyping‐by‐amplicon‐sequencing approach for A. cineraria .
Despite high statistical power of > 0.002 in B. major and > 0.0025 in A. cineraria , no deviations from genetic homogeneity were detected. For both species, there was no evidence for isolation‐by‐distance or genetic clustering. Genetic homogeneity was most likely the result of high levels of gene flow that compensate for the effects of genetic drift.
Estimates of ranged between several thousand to tens of thousands, although precision was low. Simulations highlighted that genetic lag times can substantially affect our ability to detect recent (<50 generations) population differentiation when is very large. Lag times were shorter with data from 25,000 simulated di‐allelic loci, but only when sample sizes remained high.
Insect genetic studies should consider lag times due to large and ensure sample size and markers offer adequate power to reject the null hypothesis of no landscape effect on genetic connectivity.
... În primă fază, gruparea plantajelor a fost investigată şi prin analiza coordonatelor principale (PcoA) implementată în GenAlEx versiunea 6.51b2. Structura genetică a fost determinată cu ajutorul programului STRUCTURE 2.3.4 (Pritchard et al. 2000), utilizând modelul admixture fără a include informaţia cu privire la plantajul analizat. Setările au constat în 50.000 de paşi burn-in, 100.000 iteraţii Markov Chain Monte Carlo, cu 5 rulări indepen-dente pentru fiecare valoare k (1-5). ...
Bradul (Abies alba Mill.) este cea mai productivă specie de conifere din România și reprezintă aproximativ 5% din pădurile sale. În ultimele secole, pădurile de brad din Carpații României au fost exploatate intens, ceea ce a dus la o reducere substanțială a suprafeței, de la 10-15% în secolul al XIX-lea la proporția prezentă. Deși regenerarea naturală a bradului este predominantă, regenerarea artificială este folosită în special pentru creșterea stabilității, în arborete de amestec (de ex. cu molid). Datorită fructificației bune a plantajelor de brad și a calității ridicate a semințelor, materialul forestier de reproducere utilizat în prezent în lucrările de reîmpădurire provine și din plantaje. În acest studiu, am analizat cinci plantaje de brad de diferite dimensiuni și compoziții clonale situate în cele mai importante regiuni de proveniență ale României. S-au folosit microsateliți nucleari (nSSR) și markeri EST-SSR pentru a caracteriza clonele individuale și pentru a evalua structura genetică și diversitatea genetică. 185 de clone au fost genotipate cu succes și a fost verificată prezența genotipurilor străine. Rezultatele au arătat o pierdere a alelelor odată cu scăderea numărului de clone în plantaje și o valoare crescută a diversității genetice atunci când numărul de clone este comparabil, chiar dacă originea este diferită. Analiza bayesiană a indicat că modelul de grupare este în conformitate cu originea clonelor. Informațiile genetice obținute pot contribui la înființarea noilor plantaje de brad de generație avansată și la o gestionare îmbunătățită a plantajelor.
... Tassel 5.1 (Bradbury et al., 2007) was used to carry out the principal component analysis (PCA). Bayesian clustering was performed using STRUCTURE 2.3.4 (Falush et al., 2003) and the best grouping of classes was determined. The parameters were set as follows: the burn-in period was 50 000, the number of MCMC repeats was set to 100 000, the optimal number of groups (k) was determined using the DK method (Dk: [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20], and the number of iterations was 5. ...
Radish (Raphanus sativus L.) is a vegetable crop with economic value and ecological significance in the genus Radish, family Brassicaceae. In recent years, developed countries have attached great importance to the collection and conservation of radish germplasm resources and their research and utilization, but the lack of population genetic information and molecular markers has hindered the development of the genetic breeding of radish. In this study, we integrated the radish genomic data published in databases for the development of single-nucleotide polymorphism (SNP) markers, and obtained a dataset of 308 high-quality SNPs under strict selection criteria. With the support of Kompetitive Allele-Specific PCR (KASP) technology, we screened a set of 32 candidate core SNP marker sets to analyse the genetic diversity of the collected 356 radish varieties. The results showed that the mean values of polymorphism information content (PIC), minor allele frequency (MAF), gene diversity and heterozygosity of the 32 candidate core SNP markers were 0.32, 0.30, 0.40 and 0.25, respectively. Population structural analysis, principal component analysis and genetic evolutionary tree analysis indicated that the 356 radish materials were best classified into two taxa, and that the two taxa of the material were closely genetically exchanged. Finally, on the basis of 32 candidate core SNP markers we calculated 15 core markers using a computer algorithm to construct a fingerprint map of 356 radish varieties. Furthermore, we constructed a core germplasm population consisting of 71 radish materials using 32 candidate core markers. In this study, we developed SNP markers for radish cultivar identification and genetic diversity analysis, and constructed DNA fingerprints, providing a basis for the identification of radish germplasm resources and molecular marker-assisted breeding as well as genetic research.
... Several marker-based parameters such as the number of polymorphic bands (NPB), marker index (MI), polymorphism information content (PIC), and resolving power (Rp) were calculated as proposed by Prevost and Wilkinson (1999) and Varshney et al. (2007). To determine the actual number of subpopulations (K), structure analysis was performed based on the Bayesian approach using STRU CTU RE software (Pritchard et al. 2000). In this analysis, 10 independent runs with 50,000 for burn-in period and Markov 1 3 ...
Knowledge about genetic diversity is one of the most important principals for breeding wheat programs. In the present study, the genetic diversity in a set of durum wheat genotypes (86 samples) was investigated using several agronomic traits and fourteen CAAT-box derived polymorphism (CBDP) markers. Based on the obtained results, considerable variability in plant height, thousand-kernel weight, and grain yield was found across two growing seasons. Using the factor analysis and ideotype-design best linear unbiased predictor (FAI-BLUP) index and the multi-trait stability index (MTSI), three genotypes G2, G4, and G64 were selected as desirable genotypes in terms of all measured traits. In the molecular analysis, the used markers indicated clear amplification across investigated durum wheat genotypes with a percent polymorphism of 100%, and all CBDP primers amplified 93 polymorphic fragments. Mean values of resolving power (Rp), polymorphic information content (PIC), and marker index (MI) were 4.07, 0.32, and 2.21, respectively. The results obtained from cluster and principal coordinate analyses indicated similar grouping patterns, and so that all investigated durum wheat genotypes were classified into three clear clusters, while the structure analysis grouped all genotypes into four groups. Based on the analysis of molecular variance (AMOVA), the genetic variance within explored sub-populations was greater than between them (62% vs. 38%). Furthermore, the highest values of the number of effective alleles (Ne), Shannon’s information index (I), percentage of polymorphism loci (PPL), and Nei’s gene diversity (He) were estimated for sub-populations Pop-1 and Pop-4. Our results provide a piece of evidence for an acceptable potential of CBDP markers for further integration into marker-assisted selection.
... This analysis aimed to investigate any possible admixtures that may have taken place among the populations under study. The Bayesian approach was employed to examine the population structures via cluster analysis techniques, utilizing the STRUCTURE software (Hubisz et al., 2009;Falush et al., 2003Falush et al., , 2007Pritchard et al., 2000). The STRUCTURE analysis employed an admixture model and independent allele frequencies, with a length value of 20 000 being set. ...
This study aimed to investigate the genetic characterization and diversity of Hair goats from 10 regions using 20 microsatellite markers. A total of 522 alleles were observed. The INRA0023 locus exhibited the greatest number of alleles (48), while the DRBP1 locus had the highest effective allele number (16.27), and the BM1818 and DRBP1 loci had the highest polymorphic information content value (0.94). The expected heterozygosity value ranged from 0.85 (ILSTS011) to 0.94 (BM1818, SRCRSP15, and DRBP1). The Hair goat populations in Konya and Hatay displayed the lowest and highest allele numbers, with values of 10.40 and 16.25, respectively. The fixation index (FIS) values are significant in defining population structures and determining the extent of heterozygosity losses. The FIS values exhibited a range of 0.031 in Muǧla to 0.226 in Burdur. A total of 107 unique alleles were identified in Hair goat populations. However, it is noteworthy that, out of all the alleles, only 25 had a frequency exceeding 5 %. The results indicate that the microsatellite markers utilized demonstrate sufficient levels of polymorphism, making them appropriate for efficiently investigating the genetic variability of Hair goat populations.
... Therefore, we adopted two different approaches: a discriminant analysis of principal components (DAPC) implemented in R package adegenet 2.1.8 (Jombart, 2008;Jombart & Ahmed, 2011), and the Bayesian approach implemented in the program Structure 2.3.4 (Falush et al., 2003;Pritchard et al., 2000). In Structure, we fitted a model with population admixture and correlated allele frequencies to estimate the most likely number of distinct genetic clusters (K), including spatial information about sampling sites (LOCPRIOR procedure). ...
Aim: High-elevation specialist species are threatened by climate change and habitat
loss, and their distributions are becoming increasingly reduced and fragmented. In such a context, dispersal ability is crucial to maintain gene flow among patches of suitable habitat. However, information about dispersal is often lacking for these species, especially for those taxa that are usually considered as good dispersers such as birds. We adopted a landscape genomics approach to investigate dispersal in a climate-sensitive high-elevation specialist bird. Our aims were to assess the levels of gene flow within a wide mountain area, and to assess the effects of geographic distance and landscape characteristics on dispersal, by testing the isolation by distance (IBD) hypothesis against the isolation by resistance (IBR) hypothesis.
Location: European Alps.
Taxon: Montifringilla nivalis.
Methods: We sampled individuals from several breeding areas and obtained single nucleotide polymorphism (SNP) data by ddRAD sequencing. We then calculated site-and individual level genetic distances and individual inbreeding coefficients. To test IBD versus IBR, we related genetic distances to both geographic distances and different measures of landscape resistance by using maximum likelihood population effects models.
Results: Gene flow among breeding areas was partly restricted, and we found support for IBD, indicating that geographic distance limits snowfinch dispersal. Spatial patterns of genetic distances suggested that philopatry strongly contributed to determine the observed IBD. High inbreeding coefficients in several individuals indicated frequent mating among relatives.
Main Conclusions: Restricted dispersal and frequent inbreeding within ‘sky island’
systems can also occur in highly mobile species, because their potential ability to
cover very large distances can be counteracted by high philopatry levels that are likely related to high dispersal costs. IBD and philopatry will increasingly hinder snowfinch dispersal among suitable areas within the future more restricted and fragmented breeding range, increasing the risks of local extinctions.
... As a complementary measure, we used a clustering-based approach to calculate individual admixture proportions using NGSadmix (Skotte et al., 2013). To estimate the best K, we ran NGSadmix for K 2-10 with 20 replicates per run and then examined the log-likelihood values using both the ΔK method (Evanno et al., 2005) and the mean posterior probability likelihood (ln(Pr(X|K)); Pritchard et al., 2000). ...
Urbanisation is rapidly altering ecosystems, leading to profound biodiversity loss. To mitigate these effects, we need a better understanding of how urbanisation impacts dispersal and reproduction. Two contrasting population demographic models have been proposed that predict that urbanisation either promotes (facilitation model) or constrains (fragmentation model) gene flow and genetic diversity. Which of these models prevails likely depends on the strength of selection on specific phenotypic traits that influence dispersal, survival, or reproduction. Here, we a priori examined the genomic impact of urbanisation on the Neotropical túngara frog ( Engystomops pustulosus ), a species known to adapt its reproductive traits to urban selective pressures. Using whole‐genome resequencing for multiple urban and forest populations we examined genomic diversity, population connectivity and demographic history. Contrary to both the fragmentation and facilitation models, urban populations did not exhibit substantial changes in genomic diversity or differentiation compared with forest populations, and genomic variation was best explained by geographic distance rather than environmental factors. Adopting an a posteriori approach, we additionally found both urban and forest populations to have undergone population declines. The timing of these declines appears to coincide with extensive human activity around the Panama Canal during the last few centuries rather than recent urbanisation. Our study highlights the long‐lasting legacy of past anthropogenic disturbances in the genome and the importance of considering the historical context in urban evolution studies as anthropogenic effects may be extensive and impact nonurban areas on both recent and older timescales.
... (Jombart, 2008;Jombart & Ahmed, 2011) using Radiator (Gosselin et al., 2020) for file conversion. As population structure is best examined using several lines of evidence, we also ran a Bayesian estimation of population structure in STRUCTURE 2.3.4 (Pritchard et al., 2000), which we parallelised using ParallelStructure v1.0 (Besnier & Glover, 2013). We used the admixture model, with the correlated allele frequencies model, lambda set to 1, and a burn in of 500,000, followed by 1,000,000 MCMC iterations. ...
Conservation translocations often inherently involve a risk of genetic diversity loss, and thus loss of adaptive potential, but this risk is rarely quantified or monitored through time. The reintroduction of beavers to Scotland, via the Scottish Beaver Trial in Knapdale, is an example of a translocation that took place in the absence of genetic data for the founder individuals and resulted in a small and suspected to be genetically depauperate population. In this study we use a high‐density SNP panel to assess the genetic impact of that initial translocation and the effect of subsequent reinforcement translocations using animals from a different genetic source to the original founders. We demonstrate that the initial translocation did, indeed, lead to low genetic diversity (Ho = 0.052) and high mean kinship (KING‐robust = 0.159) in the Knapdale population compared to other beaver populations. We also show that the reinforcement translocations have succeeded in increasing genetic diversity (Ho = 0.196) and reducing kinship (KING robust = 0.028) in Knapdale. As yet, there is no evidence of admixture between the two genetic lineages that are now present in Knapdale and such admixture is necessary to realise the full genetic benefits of the reinforcement and for genetic reinforcement and then rescue to occur; future genetic monitoring will be required to assess whether this has happened. We note that, should admixture occur, the Knapdale population will harbour combinations of genetic diversity not currently seen elsewhere in Eurasian beavers, posing important considerations for the future management of this population. We consider our results in the wider context of beaver conservation throughout Scotland and the rest of Britain, and advocate for more proactive genetic sampling of all founders to allow the full integration of genetic data into translocation planning in general.
... Parameters of genetic diversity, Hardy-Weinberg genotype equilibrium, F-statistics of interpopulation differentiation, gene flow (Nm), and the molecular variance (AMOVA) were calculated using the GenAlEx 6.503 add-in for MSExcel [19]. To identify the population structure, the Bayesian clustering algorithm in the [20] and Geneland 3.3.0 [21][22][23][24][25][26][27][28] softwares was used. ...
... STRUCTURE v.2.3.4 software (Pritchard et al., 2000) was used to detect genetic groups and to inference the population structure, as described in Băcilă et al. (2015). ...
Onobrychis montana DC. Subsp. transsilvanica (Simonk.) Jáv. (Fabaceae) is a plant taxon, endemic to the South-Eastern Carpathians, whose taxonomic status is treated inconsistently by the classic taxonomy based on morphological traits. In a previous study, by sequencing several chloroplast DNA regions and AFLP genotyping, we tried to elucidate the controversy concerning its taxonomic status in relation to the more widespread O. montana DC., and determined its phylogeographic structure within the Carpathians. The present study, based on DNA fingerprinting by seven SSR markers, brings more insights on this problematic taxon by conferring higher resolution and sub-clustering previously identified phylogeographic groups. However, the newly SSR genetic data are in agreement with molecular evidence revealed by AFLP and chloroplastic SNPs and do not support O. montana DC. Subsp. transsilvanica (Simonk.) Jáv. As a distinct species from O. montana DC.
... The population structure of cassava accessions was analyzed using the Bayesian approach. The clustering algorithm based on the ADMIXTURE model, implemented in STRUCTURE v. 2.3.4 [46] was used. The most likely number of clusters (k) was deduced using 15 independent iterations for each value of k (ranging from 1 to 20), with 50,000 run-in steps followed by 500,000 Markov Chain Monte Carlo (MCMC) simulations. ...
Genetic diversity is very important in crop improvement. This study was carried out to assess the genetic diversity and the number of unique multilocus genotypes (MLGs) in cassava collection in Burkina Faso. To achieve this objective 130 cassava accessions were genotyped using 32 simple sequence repeat (SSR) markers. The results revealed that among these markers, twelve (12) were highly informative, with the PIC values greater than 0.50, twelve (12) were moderately informative, with the PIC values ranged between 0.25 and 0.50, and eight (8) were not very informative, with the PIC values lower than 0.25. A moderate level of genetic diversity was found for the population, indicated by the average expected heterozygosity (0.45) and the observed heterozygosity (0.48). About 83.8% of unique multilocus genotypes were found in the cassava collection indicating that SSR markers seem to be most appropriate for MLGs identification. Population structure analysis based on hierarchical clustering identified two subpopulations and Bayesian approach suggested five clusters. Additionally, DAPC analysis separated the cassava accessions into 13 subpopulations. The comparison of these results and the previous study using SNP, suggest that each type of markers can be used to assessment the genetic structure of cassava grown in Burkina Faso.
... We used Bayesian clustering and principal coordinate analysis (PCoA) to estimate population structure. For Bayesian clustering, STRUCTURE v.2.3.4 (Pritchard et al., 2000) with the admixture model was used. To ensure that loci were unlinked as expected by STRUCTURE, we pruned the dataset (kept 9389 SNPs) using the indeppairwise function (1000 100 0.2) in PLINK1.9 ...
The rapid climate change poses considerable threat to biodiversity by constantly alter-ing species distribution, phenotypic variation and allele frequencies. Understanding the interplay between the climate and species phenotypic and genetic variation is thus cru-cial to inform conservation strategies. In this study, we investigated local adaptation of a widespread aquatic species in China, Zizania latifolia .
We performed restriction-site associated DNA sequencing (RAD-seq) for 66 wild samples composed of 10 populations, two populations in each of the five major eco-geographical regions of China and 6 cultivated samples derived from three culti-vars found in central China. We assessed genetic diversity and structure, genetic-envi-ronmental association, and genome-wide association studies for the 60 wild samples.
Low levels of genetic variability were found in the Z. latifolia populations rang-ing from H E = 0.08 to H E = 1.52. Population structure showed that samples belonged to two major groups, north and south clades, split along a temperature boundary. It was estimated that the two groups diverged during the 8.2kiloyear event and later experi-enced severe genetic bottlenecks with advancement of agriculture and increase in hu-man population some 2k years later.
Landscape analysis using SNP and trait data showed that environment was more important in shaping the genetic structure than geography, but the combined effect of environment and geography explained >90% of both genetic and morphological varia-tion. Several loci were found to be correlated with environmental variables as well as morphological traits, most of which were annotated as retrotransposons. Considering the abundance of transposable elements in the Z. latifolia genome, differentiation and local adaptation was inferred to be partly driven by temperature-induced transposable elements activity.
... Population structure analysis was determined by using the Structure 2.3.4 program to find the genetic structure of the given population (Pritchard et al., 2000). We ran the software with the model parameter based on admixture and correlated allele frequency with the burn-in period of 1,00,000, followed by 1,00,000 Markov chain Monte Carlo (MCMC) replications. ...
The productivity of rice is greatly affected by the infection of the plant pathogenic fungus Rhizoctonia solani, which causes a significant grain yield reduction globally. There exist a limited number of rice accessions that are available to develop sheath blight resistance (ShB). Our objective was to identify a good source of the ShB resistance , understand the heritability, and trait interactions, and identify the genomic regions for ShB resistance traits by genome-wide association studies (GWAS). In the present study, a set of 330 traditional landraces and improved rice varieties were evaluated for ShB resistance and created a core panel of 192 accessions used in the GWAS. This panel provides a more considerable amount of genetic variance and found a significant phenotypic variation among the panel of rice accessions for all the agro-morphological and disease-resistance traits over the seasons. The infection rate of ShB and disease reaction were calculated as percent disease index (PDI) and area under the disease progress curve (AUDPC). The correlation analysis showed a significant positive association between PDIs and AUPDC and a negative association between PDI and plant height, flag leaf length, and grain yield. The panel was geno-typed with 133 SSR microsatellite markers, resulting in a genome coverage of 314.83 Mb, and the average distance between markers is 2.53 Mb. By employing GLM and MLM (Q + K) models, 30 marker-trait associations (MTAs) were identified with targeted traits over the seasons. Among these QTLs, eight were found to be novel and located on 2, 4, 8, 10, and 12 chromosomes, which explained the pheno-typic variation ranging from 5% to 15%. With the GWAS approach, six candidate R Naveenkumar and Annamalai Anandan contributed equally.
... Genetic distances among populations were estimated with the pairwise fixation index (F ST ), and their significance was tested by running 10,000 permutations in ARLEQUIN 3.5.2.2 (Excoffier & Lischer, 2010). A Bayesian clustering analysis was performed using STRUCTURE 2.3.4 (Pritchard, Stephens & Donnelly, 2000) to estimate the number of populations. Ten independent runs with K values from 1 to 6, 1 million Markov chain Monte Carlo (MCMC) interactions, and 10% burn-in were completed. ...
Molecular analysis is a powerful tool for assessing and developing conservation strategies for endangered species. Elasmobranchs comprise one of the most threatened groups of vertebrates, with about one‐third of the species subject to some degree of threat. This is the case for Pseudobatos horkelii , the Brazilian guitarfish, which has suffered severe population reductions (>80%) in recent decades, mainly through coastal overfishing. Understanding the genetic diversity of this species is paramount to applying adequate management and conservation strategies.
In this context, the present study evaluated the genetic diversity of P. horkelii , employing single‐nucleotide polymorphism (SNP) nuclear markers obtained by double‐digest restriction site‐associated DNA sequencing (ddRADseq). Samples collected in three areas along the Brazilian Coast (Rio de Janeiro, São Paulo, and Rio Grande do Sul) provided an average of 1,565,339 reads and 2,846 SNPs.
The results indicate the presence of at least two genetically distinct populations along the Brazilian Coast, with molecular diversity differences noted among clusters. The heterozygosity excess observed in all populations is likely the result of a bottleneck, probably resulting from overfishing and habitat fragmentation. Moreover, the upwelling phenomenon in Cabo Frio, in the state of Rio de Janeiro, may have a significant influence over the observed genetic structure.
The gene flow between the clusters was estimated and was noted as asymmetric between the populations studied. The observed patterns may be the result of the combination of biological characteristics and overfishing pressure in the past decades. The evidence of structured populations presenting genetic diversity differences provides insightful information for the development of stock management and conservation strategies for the Brazilian guitarfish.
Biomarcadores de Cáncer Gástrico es un libro derivado de nuestras investigaciones, que recopila los principales hallazgos básicos y poblacionales tendientes a dilucidar las causas de cáncer gástrico y los determinantes para la prevención de la enfermedad. La determinación de biomarcadores de la enfermedad en población de Nariño-Colombia, sera de su interés, ya que esta enfermedad tiene una de las tasas de incidencia mas altas del mundo en la población andina y/o se convierte en uno de los referentes teóricos o metodológicos para investigadores de las Ciencias Biomédicas y Ciencias de la Salud. Las razones fundamentales para leerlo: Que parte del libro sirva a nuestros estudiantes de pregrado y posgrado como referencia básica para el entendimiento de los factores que exponen a un individuo al desarrollo de cáncer gástrico y el aprendizaje de las técnicas de biología molecular y genómicas que se aplican para identificar biomarcadores humanos y de Helicobacater pylori (H. pylori) para cáncer. Por otra parte se describen temas que se consideran necesarios para formular marcos teóricos y estados del arte acompañados de metodologías de punta, que posibilitan el uso de información en la estructuración de proyectos de investigación en su campo de actuación.
La amplia gama de biomarcadores de cáncer gástrico que se ilustran en el libro recopilan una historia académica de trabajo de investigación de más de 25 años y posibilitarán resolver la ausencia de buenos textos sobre la temática en castellano y que, a la vez, se constituya en material de consulta bibliográfica en los procesos de investigación científica en las áreas del conocimiento.
La documentación del aislamiento e identificación del oncopatógeno H. pylori de mucosa gástrica humana permitirá al lector tener un referente respecto a cómo superar las dificultades del cultivo in vitro del microorganismo que, en mi experiencia, es el más “fastidioso” en cuanto a su manejo-conservación y activación en el laboratorio. Es importante divulgar los avances que nos permitieron determinar biomacadores de virulencia y de patogenicidad de H. pylori; los de susceptibilidad humana a cáncer gástrico y que, igual, bajo el uso de las ciencias ómicas o genómicas, los biomarcadores ancestrales y evolutivos H. pylori-humanos, de aplicación clínica personalizada y de investigación traslacional en el perfilamiento de pacientes de Nariño con alto riesgo de cáncer gástrico y su adecuado tratamiento de prevención de la enfermedad. El texto incluye la idea referida a que el cáncer gástrico surge del colapso de la relación de equilibrio entre el ecosistema gástrico y la bacteria H. pylori, junto con los principales cambios fisiopatológicos en la cascada precancerosa de Correa. Comprender el origen del cáncer gástrico desde el punto de vista de sistema ecológico y conocer las características evolutivas huesped-H. pylori trae perspectivas sobre el desarrollo de nuevas estrategias para la prevenición del cáncer gástrico.
Throughout the globe morphological, biochemical and genetic variability exists in chilli and is harnessed to achieve specific breeding objectives. In this study, chilli germplasm was characterized based on horticultural traits, biochemical quantifica-tion and simple sequence repeat (SSR) polymorphism for diversity estimation. A total of 36 SSR primers were utilised to study the genetic divergence among 48 genotypes of chilli collected from nine states of India. Among the 36 primers, sixteen amplified null alleles. A total of 41 alleles were detected with average 2.05 alleles per locus. The largest number of alleles (5) were obtained with marker CAMS-234. The polymorphic information content ranged from 0.06 to 0.72 with an average of 0.50. On the basis of SSR analysis, the UPGMA cluster classified 48 genotypes into three groups. There was significant variability in germplasm for all morpho-biochemical traits. Kashi Anmol (100.50 q/ha) expressed the highest yield. Highest vitamin C content at green stage was recorded in IC-561635 (187 mg/100 g) and the greatest capsaicin content (9547.90 µg/g) equivalent to pungency of 171,862.2 Scoville heat units (SHU) was recorded in Bhut Jolokia. Principal component analysis indicates that the first five principal components explain 74.63% per cent of the total variation. Additionally, analysis of molecular variance (AMOVA) showed that 1% of the total genetic variation occurred among the population and 99% genetic variation within the populations, whereas the pairwise F st specified the moderate genetic variation ranging from 0.002 to 0.020. The present investigation has strengthened the knowledge of genetic worth of this germplasm for application in various genetic improvement programmes.
This study summarizes the taxonomic treatment of the camel spider genus Chanbria Muma, 1951. Taking an integrative taxonomic approach incorporating phylogenomic, morphological, and geographical information, the genus is herein revised. Of the four species currently placed in the genus, two are retained: Chanbria regalis Muma, 1951 and Chanbria serpentinus Muma, 1951. Eremochelis plicatus (Muma, 1962) is transferred to this genus because it is consistently recovered in a clade with Chanbria based on several phylogenetic analyses using hundreds of loci recovered from ultraconserved element data. In this study, we re-analyse previously acquired genomic data to assess former species hypotheses and identify new morphological synapomorphies that support the monophyly of Chanbria. The genetic data support the synonymization of Chanbria rectus Muma, 1962 syn. nov. with C. regalis. Furthermore, we synonymize Chanbria tehachapianus Muma, 1962 syn. nov. with C. regalis because C. tehachapianus was erected based on limited morphological information and lack of geographical separation between other populations of C. regalis. Two new species, Chanbria brookharti sp. nov. and Chanbria mapemes sp. nov., are described. This brings the total number of species of Chanbria described to five recognized species: C. regalis, C. serpentinus, C. plicatus com. nov., C. brookharti sp. nov., and C. mapemes sp. nov.
The cosmopolitan ectoparasite human head louse, Pediculus humanus capitis (De Geer)(Phthiraptera:Pediculidae), affects mostly school-aged children, with infestations reported every year mainly due to louse resistance to pyrethroids. One of the main resistance mechanisms of pyrethroids is the target site insensitivity (kdr), which is caused by single-nucleotide point mutations (SNPs) located in the voltage-sensitive sodium channel gene.In this study, we analyzed individual head lice toxicologically via the description of their susceptibility profile to permethrin and genetically through the genotypification of their kdr alleles as well as nuclear microsatellite loci. Lice were collected from 4 schools in the city of Buenos Aires, Argentina. The resistance ratios varied from 33.3% to 71.4%, with a frequency of the T917I kdr mutation of 87.31% and with 83.6% of the head lice being homozygous resistant to pyrethroids. Microsatellite data indicated that all the louse school populations had genotype proportions that deviated from Hardy–Weinberg expectations, with FIS > 0 reflecting a deficit of heterozygotes. Bottleneck analysis suggested that all louse school populations underwent a recent reduction
in population sizes, while 3 of the 4 schools had gene flow values around 1, indicating ongoing gene flow among those schools. Our study suggests that school louse populations in the city of Buenos Aires may form a metapopulation, where each school represents a small population that undergoes extinction and recoloniza-
tion processes under strong permethrin selection. This is the first multilevel analysis integrating toxicological, kdr-genotyping, and microsatellite data in human louse populations.
Crescent butterflies of the Phyciodes tharos group have a long-standing reputation for taxonomic difficulty. We assessed species boundaries in the P. tharos group using genome-wide single-nucleotide polymorphism (SNP) data, focusing on sampling in western Canada, where 4 species (P. tharos, P. cocyta, P. batesii, and P. pulchella) have classically been recognized. Phylogenetic and cluster-based analyses confirm that there are indeed 4 species based on the maintenance of genomic integrity in the presence of occasional hybridization and low levels of gene flow. Mitochondrial cytochrome c oxidase I (COI) does not consistently distinguish species, with haplotypes extensively shared between species. Limited sampling of P. batesii indicates complex boundaries and interactions with other Phyciodes, especially with P. pulchella and P. cocyta. This study demonstrates the power of a genome-wide perspective to elucidate the integrity of boundaries between recently diverged species that remain capable of occasional hybridization.
Declines in bumble bee species range and abundances are documented across multiple continents and have prompted the need for research to aid species recovery and conservation. The rusty patched bumble bee (Bombus affinis) is the first federally listed bumble bee species in North America. We conducted a range-wide population genetics study of B. affinis from across all extant conservation units to inform conservation efforts. To understand the species’ vulnerability and help establish recovery targets, we examined population structure, patterns of genetic diversity, and population differentiation. Additionally, we conducted a site-level analysis of colony abundance to inform prioritizing areas for conservation, translocation, and other recovery actions. We find substantial evidence of population structuring along an east-to-west gradient. Putative populations show evidence of isolation by distance, high inbreeding coefficients, and a range-wide male diploidy rate of ~15%. Our results suggest the Appalachians represent a genetically distinct cluster with high levels of private alleles and substantial differentiation from the rest of the extant range. Site-level analyses suggest low colony abundance estimates for B. affinis compared to similar datasets of stable, co-occurring species. These results lend genetic support to trends from observational studies, suggesting that B. affinis has undergone a recent decline and exhibit substantial spatial structure. The low colony abundances observed here suggest caution in overinterpreting the stability of populations even where B. affinis is reliably detected interannually. These results help delineate informed management units, provide context for the potential risks of translocation programs, and help set clear recovery targets for this and other threatened bumble bee species.
Edaphic conditions of serpentine soils, naturally rich in heavy metals, act as a strong selection pressure that shapes specific metal-tolerant ecotypes. Medicago lupulina L. (black medick) is not only a widespread plant species that prefers calcareous and dry soil types but also grows at the borders of serpentine formations. It can also be found in waste and disturbed habitats. This is a species with reported phytoremediation potential, however, there is no published data regarding the impact of the environment on the genetic distribution of this species. The aim of our research was to explore how selection pressure of serpentine soils affects genetic diversity of M. lupulina and to test heavy-metal accumulation capacity of this species. Specimens of 11 M. lupulina populations were collected from serpentine outcrops located in Central and Eastern Bosnia as well as from non-serpentine sites. Soil and plant samples were analyzed for the total contents of heavy metals using air-acetylene flame atomic absorption spectroscopy. Genetic diversity was analyzed using AFLP (Amplified Fragment Length Polymorphism) markers. Serpentine soils showed high nickel, cobalt, chromium and iron concentrations. Nickel and manganese concentrations in soil samples and plant material showed statistically significant correlation. Although plants in two populations show the ability to extract Ni, M. lupulina does not show hyperaccumulating properties. Despite severe selective pressure, genetic diversity in serpentine populations is not reduced. Analyses of intrapopulation and interpopulation genetic diversity showed significant genetic differentiation among populations which is not related to their geographic distance. Population from non-metalliferous soil showed clear separation from all other populations. Diversity data suggest that serpentine populations maintain genetic diversity by undetected mechanisms and that edaphic factors rather than geography influence genetic structure analyzed M. lupulina populations.
Polymorphism of 10 nuclear microsatellite loci in coho salmon populations in the Asian part of the range was studied for the first time. Three genetically distinct regional stock complexes were identified: Kamchatka, northern part of the Sea of Okhotsk and Sakhalin. It was shown that all populations, regardless of their geographic location, are characterized by a high level of genetic polymorphism.
Members of the genus Clivia show considerable variation in flower pigmentation and morphology. Such variation is effected by mutations that emerge in candidate flower development genes over time. Besides population history, mutations can further illuminate the effects of demographic events in populations in addition to population genetic parameters including selection, recombination, and linkage disequilibrium (LD). The current study aimed to find sequence variants in two anthocyanin biosynthetic genes (DFR and bHLH) of Clivia miniata and use the data to assess population genetic factors from a random collection of orange/red- and yellow-flowered specimens. Overall, average nucleotide diversity in the two anthocyanin genes was moderate (π = 0.00646), whereas haplotypes differed significantly (Hd ≥ 0.9). Gene evolution was seemingly driven by mutations (CmiDFR) or recombination (CmibHLH001). LD decayed swiftly within the analyzed gene regions and supported the feasibility of assessing trait-variant associations via the association/linkage mapping approach. In the end, most associations were found to be spurious, but one haplotype in CmibHLH001 showed a promising correlation to the orange/red flower phenotype in Clivia specimens. In all, the present study is the first to measure gene-level diversity in C. miniata – data that had never been reported so far. Further, the study also identified allelic and haplotypic variants that may be beneficial in future association genetic studies of Clivia. Such studies, however, consider large diverse populations to control for statistical bias intrinsic to the analysis of small datasets.
Tomato has been cultivated in Greece for more than 200 years, even though is not native to the country. Greece with a favourable environment all-round the year, has become a major competitor in tomato production around Europe. However, there is an increasing demand to improve tomato crop, to withstand harsh environmental conditions (extreme temperatures, salinity, etc.), and to develop high-quality final products. People have devoted a significant effort to crop improvement through phenotypic screening resulting in a large number of tomato landraces. An increasing demand to clarify the relationships among local tomato landraces and hybrids utilizing the most preferred molecular markers the simple sequence repeats (SSR-markers) is the main objective of this study. Twenty-seven tomato landraces and two tomato hybrids cultivated in Crete, Greece, were genotyped utilizing eleven simple sequence repeats (SSR) along with the Structure analysis of the germplasm. A neighbour-joining dendrogram of the 27 landraces and the two hybrids was produced. The Structure analysis indicated that nine ancestral populations are hidden inside the group of all the genotypes tested, using Evanno's method. The final objective was to make these data publicly available through the first Greek relational database (Greek Tomato Database-GTD). GTD was developed allowing the users to update and enrich the database, with new and supplemental information. This work is the first molecular fingerprint of the 27 landraces of Greece which is documented along with the phenotypic information in the GTD.
The escalating global movement of alien species, facilitated by increased trade and travel, poses a pressing need to comprehend their invasive potential and the consequent ecological and economic ramifications. Despite a growing body of evidence on rapid evolutionary shifts in invasive species, comprehensive insights into the genetic variability underlying these adaptations are constrained by limited genomic resources. Understanding the role of genetic variation in the success or failure of biological invaders is crucial,. This study focuses on the chrysanthemum lace bug, Corythucha marmorata , as a model 2system to investigate the interplay of genetic variation, local adaptation, and invasion dynamics. Our analysis reveals a low genetic structure among countries, with significant genetic differentiation observed within populations. The scarcity of private alleles suggests a limited number of independent sources for the invader populations. Furthermore, the prevalence of a single genetic cluster indicates potential novel-selection pressures, potentially influenced by the host plant. The lace bug's specialization on goldenrod is emphasized despite reports of exploiting various hosts.
Inferring the geographic mode of speciation is essential for explaining the generation and assembly of biodiversity, but has been rarely applied to the temperate flora of China. Fagus longipetiolata and F. lucida are a sister pair of beech species with largely overlapping ranges in subtropical China, however, little is known about the geographic mode of speciation and the formation of their sympatric distributions. In this study, we used IMa2 and fastsimcoal2 to simulate the speciation history of the two sisters. On the basis of 11 nuclear loci screened for 27 populations/species, their divergence time was estimated to 8.37 Mya by IMa2, and weak interspecific gene flow was detected. The simulation by fastsimcoal2 found that F. longipetiolata and F. lucida diverged ~8.53 Mya, then came into contact and hybridized at 0.8 Mya. The extended Bayesian skyline plots indicated that F. lucida began demographic expansion prior to the Pleistocene at 3 Mya, whereas F. longipetiolata increased its effective population size during the Quaternary, between 0.8 and 0.5 Mya. Ecological niche analysis and niche modelling showed that the two beeches had subtle niche differentiation and their projected distributions were largely overlapped across the late Quaternary. These results, coupled with well-studied fossil records in Fagus, demonstrate that these two beech species diverged allopatrically at the high latitudes of the Northern Hemisphere, and came into contact and hybridized with each other after successive migrations into subtropical (i.e. warm temperate) China recently. However, the two beeches may have developed strong intrinsic reproductive barriers due to long-term allopatry, allowing them to coexist in subtropical China. Our results illuminate the assembly history of the temperate woody flora in subtropical China, supporting that many relict temperate lineages in subtropical China may have established their populations recently.
Population genetic structure is influenced by a combination of contemporary and historical events; however, this structure can be complicated by ongoing gene flow. While it is well known that contemporary hybridization occurs frequently among many closely related species, it often remains uncertain as to which populations are involved in introgression events, and this can be even more difficult to infer when introgression is historical. Here we use restriction-site associated DNA sequencing (RADseq) to look at the level of introgression among four species of songbirds in North America: the black-capped, mountain, boreal, and chestnut-backed chickadee. Samples from both sympatric and allopatric sites across the species’ ranges supported limited ongoing mixing among the four species with Bayesian clustering and PCA. In contrast, f4-statistics and admixture graphs revealed extensive historical introgression among geographically structured populations. Almost all historical admixture events were among populations west of the Rocky Mountains, and almost all populations west of the Rocky Mountains, excluding island and coastal populations, showed evidence of historical admixture. The inclusion of all four chickadee species proved crucial in differentiating which species were involved in hybridization events to avoid erroneous conclusions. Taken together, the results suggest a complex pattern of divergence with gene flow.
Freshwater snails are pivotal in transmitting schistosomiasis, a tropical parasitic disease affecting over 150 million people. The adaptive potential of these snails is a critical factor in determining how climate change and other environmental factors influence disease transmission dynamics, yet it has remained unexplored. Bulinus truncatus is the schistosome intermediate host snail with the widest geographic distribution and therefore plays a pivotal role in determining the maximum range of urogenital schistosomiasis. In this study, we assessed the local adaptation capacity of B. truncatus to temperature through an integrative approach encompassing phenotypic, ecophysiological, and genomic data. Ten snail populations from diverse thermal environments were collected in three countries, with eight populations reared in a common garden. The F2 generation (total N= 2592) was exposed to eight chronic temperature treatments and various life-history traits were recorded for over 14 weeks. Subsequently, ecophysiological analyses were conducted on the ten last surviving snails per population. Genotyping the parental generation collected in the field using a genotyping-by-sequencing (GBS) approach, revealed 12,875 single nucleotide polymorphisms (SNPs), of which 4.91 % were potentially under selection. We observed a significant association between these outlier SNPs, temperature, and precipitation. Thermal adaptations in life-history traits were evident, with lower survival rates at high temperatures of warm- origin snails compensated for by higher reproduction rates. Cold-origin snails, on the other hand, exhibited higher growth rates adapted to a shorter growing season. Ecophysiological adaptations included elevated sugar and haemoglobin contents in cold-adapted snails. In contrast, warm-adapted snails displayed increased protein levels but also more oxidative damage. Furthermore, heightened phenoloxidase levels indicated a more robust immune response in snails from parasite-rich regions. The substantial local adaptation capacity of B. truncatus holds profound implications for its response to climate change, future schistosomiasis risk, and the effectiveness of schistosomiasis control measures.
Highlights
Local adaptation influences species’ responses to climate change
The snail Bulinus truncatus showed a high thermal local adaptation (LA) potential
LA is apparent through variations in life history and ecophysiological traits
We identified a significant genetic basis underlying this LA
LA of the hosts could sustain schistosomiasis transmission under global warming
Fusarium graminearum is the main causal agent of Fusarium head blight (FHB) disease in wheat in Europe. To reveal population structure and to pinpoint genetic targets of selection we studied genomes of 96 strains of F . graminearum using population genomics. Bayesian and phylogenomic analyses indicated that the F . graminearum emergence in Europe could be linked to two independently evolving populations termed here as East European (EE) and West European (WE) population. The EE strains are primarily prevalent in Eastern Europe, but to a lesser extent also in western and southern areas. In contrast, the WE population appears to be endemic to Western Europe. Both populations evolved in response to population-specific selection forces, resulting in distinct localized adaptations that allowed them to migrate into their environmental niche. The detection of positive selection in genes with protein/zinc ion binding domains, transcription factors and in genes encoding proteins involved in transmembrane transport highlights their important role in driving evolutionary novelty that allow F . graminearum to increase adaptation to the host and/or environment. F . graminearum also maintained distinct sets of accessory genes showing population-specific conservation. Among them, genes involved in host invasion and virulence such as those encoding proteins with high homology to tannase/feruloyl esterase and genes encoding proteins with functions related to oxidation-reduction were mostly found in the WE population. Our findings shed light on genetic features related to microevolutionary divergence of F . graminearum and reveal relevant genes for further functional research aiming at better control of this pathogen.
The biogeographic history of a species results from responses to past and current processes, and understanding those responses at both temporal scales is essential. We explored phylogeographic and current genetic variation structure in Ctenomys flamarioni—a subterranean rodent that inhabits a small region of the coastal plain of Brazil—and contrasted the roles of “present-day niche suitability” versus “historical climate stability” to understand current and past intraspecific genetic diversity. We used both mitochondrial DNA sequences (concatenated Cytb and D-loop, n = 78) and nuclear DNA (9 microsatellites loci, n = 154) molecular markers for individuals across the entire distribution of the species. We used phylogeographic trees, Bayesian clustering, and haplotype networks to explore genetic variation and diversity. We correlated genetic diversity with measures of current niche suitability and potential areas of Late Quaternary paleostability. Phylogeographic patterns confirmed low levels of genetic diversity structured at different hierarchical levels. We also found a weak but significant pattern of isolation by distance, indicating that geographical distance partially modulates genetic differences among populations. We also observed a positive correlation between genetic diversity and climate paleostability for microsatellites at local and regional scales. However, we found no significant association between genetic diversity and niche suitability for microsatellites at local or regional scales. We observed several signatures of bottleneck and population expansion at different geographic scales. Our results suggest that Quaternary climatic fluctuations—acting together with habitat suitability and other contemporary factors—played a fundamental role in elucidating the evolutionary history of the species—including patterns of historical dispersal, and current patterns of habitat occupation and genetic structure. In addition, based on our molecular and environmental data sets from the across the range of the species and considering the restricted endemism of C. flamarioni, we emphasize the urgency of conservation actions to protect this endangered species.
Identifying the drivers of microgeographic speciation (i.e., speciation over small, local geographic scales) is key to understand the origin of speciose groups. Here, we use genomic data to infer the demographic processes underlying diversification in Poecilimon luschani (Orthoptera: Tettigoniidae), a species complex belonging to the most diverse genus of bush crickets from the Mediterranean region (>170 taxa) that comprises three recognized subspecies with small allopatric distributions in the topographically complex Teke Peninsula, southwestern Anatolia. Phylogenomic reconstructions that include all other taxa within the species group confirmed that subspecies of P. luschani originated from a common ancestor during the Pleistocene, supporting recent (<1 Ma) diversification within a small geographical area (ca. 120 × 80 km). Genetic clustering analyses corroborated the distinctiveness of each subspecies and the cohesiveness of their respective populations, with abrupt genetic discontinuities coinciding with contemporary range boundaries. Indeed, our analyses uncovered the presence of two sympatric cryptic sister lineages that diverged <300 ka ago and do not admix despite being co-distributed. Collectively, these results support that all lineages within the complex represent independently evolving entities corresponding to full-fledged species. Statistical evaluation of alternative models of speciation strongly support a scenario of divergence in isolation followed by a period of limited gene flow during the last glacial period, when all lineages experienced marked expansions according to demographic reconstructions. Our study exemplifies how localized allopatric divergence and fast evolution of reproductive isolation can promote microgeographic speciation and explain the high rates of endemism characterising biodiversity hotspots.
Common lilac ( Syringa vulgaris L.) is a popular landscaping plant. Our aim was to obtain a large set of single nucleotide polymorphism (SNP) markers, to reveal the precise identities of the investigated S. vulgaris accessions, and to discover genetic relationships among them. The studied plant material included local Finnish, previously unidentified accessions, known reference cultivars, and so-called historical accessions i.e., old shrubs growing in historic cultural landscapes. We intended to verify cultivar names for some valuable local common lilac accessions and to provide insights into the history of common lilac cultivation in Finland. In the analyses, we used a set of 15,007 SNP markers. First, polymorphic information contents were calculated (mean 0.190, range 0.012–0.500 per marker). Then, to investigate genetic relationships among genotypes, a phylogenetic tree was constructed, and a principal coordinate analysis was conducted. A Bayesian analysis of population structure was performed to determine the number and distribution of genetic clusters among samples. Genetic marker data combined with existing historical and phenotypic knowledge revealed novel information on the unidentified cultivars and on the genetic relationships among studied accessions and solved the arrival and early history of common lilac in Finland. Overall, such comprehensive genomic characterization and deep understanding of genetic relationships of S. vulgaris can be used when utilizing present cultivars and developing new ones in future breeding programs.
The grasshopper Trimerotropis pallidipennis species complex is distributed across arid and semi-arid environments from North to South America, reaching high altitudes along the Andes Mountain range. Currently, there are four valid species of Trimerotropis in South America. However, some species were found to comprise several genetic lineages. Here, we describe the genetic structure, lineage diversification, and environmental requirements within the Trimerotropis species complex in South America based on sequences from the mitochondrial COI gene, 4048 single nucleotide polymorphisms, and ecological niche modelling. The analyses revealed the existence of at least five lineages: two with a restricted geographical distribution and three with a very wide one. The results provide evidence that glacial cycles promoted not only the presence of refuge areas but also the isolation of widely distributed lineages on the eastern and western sides of the southern Andes, potentially driving the emergence of the Trimerotropis sp. lineage, which can tolerate more temperate habitats. Our results provide evidence for the effects of Pleistocene climatic changes on the diversification history of a South American grasshopper species complex.
Zieria buxijugum, Z. formosa, and Z. parrisiae are three closely related, Critically Endangered species of questionable taxonomic validity that occur within six kilometres of each other on the south coast of New South Wales, Australia. We investigated genetic relationships and diversity of these species, along with two related but taxonomically distinct congeners, Z. granulata and Z. tuberculata, and a possible undescribed taxon, Z. aff. tuberculata. Double-digest restriction-site associated sequencing (ddRADseq) was used to generate anonymous genomic loci that were used for phylogenetic, network, and genetic structure analyses, and for estimating genetic diversity of the threatened species. Our results support the current taxonomic status of Z. buxijugum, Z. formosa, and Z. parrisiae, and suggest that Z. aff. tuberculata warrants recognition as a distinct species. We detected no evidence of inbreeding in the three Critically Endangered species, and found their genetic diversity to be similar to that of the more widespread species Z. granulata and Z. tuberculata. Comparison of plant material held in ex situ collections at the Australian National Botanic Gardens with wild plants highlighted several genotypes of the Critically Endangered species that are not represented in the ex situ collection, and we provide suggestions for the future inclusion of those unrepresented genotypes.
Genetic diversity within a species can be shaped by abiotic factors, such as climate and geography. We aimed to ascertain the relative importance of these two abiotic factors to Indrella ampulla, a monotypic snail species from the Western Ghats, India, that has three colour morphs with some overlapping distributions. We also wanted to investigate whether these colour morphs represent divergent lineages or incipient species. We sequenced one nuclear and two mitochondrial genes from 32 individuals of I. ampulla. We used phylogenetic, population genetic, and niche modelling tools to address these questions. The results suggested that the colour morphs were not reciprocally monophyletic and exhibited considerable niche overlap, suggesting that they cannot be considered as incipient species. Furthermore, the results showed that the impact of palaeoclimatic oscillations in shaping the genetic diversity of this species cannot be determined conclusively. The Palghat Gap seems to have shaped the genetic diversity in this group to a certain degree. The colour morph distributed south of the Palghat Gap did not show admixture and exhibited the least amount of niche overlap with the other morphs. The geography of the landscape seems to have played a prominent role in shaping genetic diversity in this species.
Freshwater darters belonging to the orangethroat darter species complex, or Ceasia, are widely distributed in the Central and Southern United States, with ranges that span both glaciated and unglaciated regions. Up to 15 species have been recognized in the complex, with one, Etheostoma spectabile, having a widespread northern distribution and another, Etheostoma pulchellum, having a sizeable southern distribution. The other species in the complex have much more restricted distributions in unglaciated regions of the Central Highlands. We sampled 384 darters from 52 sites covering much of the range of Ceasia and evaluated patterns of genetic diversity, genetic structure, and pre‐ and post‐glacial patterns of range contraction and expansion. We anticipated finding much stronger signals of genetic differentiation and diversification in unglaciated regions, given the higher species diversity and levels of endemism reported there. Surprisingly, microsatellite genotyping revealed two well‐differentiated genetic clusters of E. spectabile in samples from glaciated regions, one confined to the Illinois River basin and another found in the Wabash drainage and Great Lakes tributaries. This suggests that there was expansion from two isolated glacial refugia, with little subsequent post‐glacial gene flow. Fish collected from throughout the unglaciated region were less genetically differentiated. Fish assigned to Etheostoma burri and Etheostoma uniporum based on collection sites and morphological characters were not genetically differentiated from E. spectabile samples from the region. Hybridization and introgression occurring in the Central Highlands may confound genetic delineation of species in this region of high endemism and diversity.
Habitat fragmentation can facilitate local adaptation of species to heterogeneous environments and affect population demographic history. To understand the factors influencing evolutionary dynamics, such as climatic fluctuations and complex geomorphological features, we used 18 chloroplast microsatellites, 15 nuclear microsatellites, three chloroplast fragments, and two nuclear regions to explore the genetic structure and phylogeographical history of Pseudotaxus chienii. Furthermore, its current and past distributions were constructed based on ecological niche modelling. Moderate to high levels of genetic diversity were found at the species level. Precipitation was a decisive factor influencing the genetic structure of P. chienii. In addition, local adaptation to heterogeneous environments also contributed to maintain the fragmented distribution. Finally, incomplete lineage sorting led to the cyto-nuclear discordance. Overall, we show that pre-Quaternary and Quaternary climatic fluctuations and restricted gene flow exerted significant effects on the formation and maintenance of the fragmented distribution of P. chienii. The study provides new insights into the evolutionary history of plants in subtropical China.
As currently defined, DNA fingerprint profiles do not uniquely identify individuals. For criminal cases involving DNA evidence, forensic scientists evaluate the conditional prob-ability that an unknown, but distinct, individual matches the crime sample, given that the defendant matches. Estimates of the conditional probability of observing matching profiles are based on reference populations maintained by forensic testing laboratories. Each of these databases is heterogeneous, being composed of subpopulations of different heritages. This heterogeneity has an impact on the weight of the evidence. A hierarchical Bayes model is formulated that incorporates the key physical characteristics inherent in these data. With the help of Markov chain Monte Carlo sampling, levels of heterogeneity are estimated for three major ethnic groups in the database of Lifecodes Corporation.
A method for simultaneously estimating the admixture proportions of a hybrid population and Wright's fixation index, FST, for that hybrid is presented. It is shown that the variance of admixture estimates can be partitioned into two components: (1) due to sample size, and (2) due to evolutionary variance (i.e., genetic drift). A chi-square test used to detect heterogeneity of admixture estimates from different alleles, or loci, can now be corrected for both sources of random errors. Hence, its value for the detection of natural selection from heterogeneous admixture estimates is improved. The estimation and testing procedures described above are independent of the dynamics of the admixture process. However, when the admixture dynamics can be specified, FST can be predicted from genetic principles. Two admixture models are considered here, gene flow and intermixture. These models are of value because they lead to very different predictions regarding the accumulation of genes from the parental populations and the accumulation of variance due to genetic drift. When there is not evidence for natural selection, and it is appropriate to apply these models to data, the variance effective size (Ne) of the hybrid population can be estimated. Applications are made to three human populations: two of these are Afro-American populations and one is a Yanomamö Indian village. Natural selection could not be detected using the chi-square test in any of these populations. However, estimates of effective population sizes do lead to a richer description of the genetic structure of these populations.
Genetic variation at hypervariable loci is being used extensively for linkage analysis and individual identification, and may be useful for inter-population studies. Here we show that polymorphic microsatellites (primarily CA repeats) allow trees of human individuals to be constructed that reflect their geographic origin with remarkable accuracy. This is achieved by the analysis of a large number of loci for each individual, in spite of the small variations in allele frequencies existing between populations. Reliable evolutionary relationships could also be established in comparisons among human populations but not among great ape species, probably because of constraints on allele length variation. Among human populations, diversity of microsatellites is highest in Africa, which is in contrast to other nuclear markers and supports the hypothesis of an African origin for humans.
A method is proposed for allowing for the effects of population differentiation, and other factors, in forensic inference based on DNA profiles. Much current forensic practice ignores, for example, the effects of coancestry and inappropriate databases and is consequently systematically biased against defendants. Problems with the 'product rule' for forensic identification have been highlighted by several authors, but important aspects of the problems are not widely appreciated. This arises in part because the match probability has often been confused with the relative frequency of the profile. Further, the analogous problems in paternity cases have received little attention. The proposed method is derived under general assumptions about the underlying population genetic processes. Probabilities relevant to forensic inference are expressed in terms of a single parameter whose values can be chosen to reflect the specific circumstances. The method is currently used in some UK courts and has important advantages over the 'Ceiling Principle' method, which has been criticized on a number of grounds.
Attempts to study the genetic population structure of large mammals are often hampered by the low levels of genetic variation observed in these species. Polar bears have particularly low levels of genetic variation with the result that their genetic population structure has been intractable. We describe the use of eight hypervariable microsatellite loci to study the genetic relationships between four Canadian polar bear populations: the northern Beaufort Sea, southern Beaufort Sea, western Hudson Bay, and Davis Strait-Labrador Sea. These markers detected considerable genetic variation, with average heterozygosity near 60% within each population. Interpopulation differences in allele frequency distribution were significant between all pairs of populations, including two adjacent populations in the Beaufort Sea. Measures of genetic distance reflect the geographic distribution of populations, but also suggest patterns of gene flow which are not obvious from geography and may reflect movement patterns of these animals. Distribution of variation is sufficiently different between the Beaufort Sea populations and the two more eastern ones that the region of origin for a given sample can be predicted based on its expected genotype frequency using an assignment test. These data indicate that gene flow between local populations is restricted despite the long-distance seasonal movements undertaken by polar bears.
In DNA profile analysis, uncertainty arises due to a number of factors such as sampling error, single bands and correlations within and between loci. One of the most important of these factors is kinship: criminal and innocent suspect may share one or more bands through identity by descent from a common ancestor. Ignoring this uncertainty is consistently unfair to innocent suspects. The effect is usually small, but may be important in some cases. The report of the US National Research Committee proposed a complicated, ad-hoc and overly-conservative method of dealing with some of these problems. We propose an alternative approach which addresses directly the effect of kinship. Whilst remaining conservative, it is simple, logically coherent and makes efficient use of the data.
We employed F-statistics to analyze quantitative and isozyme variation among five populations of Pinus contorta ssp. latifolia, a wind-pollinated outcrossing conifer with wide and continuous distribution in west North America. Estimates of population differentiation (FST) for six quantitative traits were compared with the overall estimate of the differentiation (F*ST) from 19 isozymes that tested neutral to examine whether similar evolutionary processes were involved in morphological and isozyme differentiation. While the FST estimates for specific gravity, stem diameter, stem height and branch length were significantly greater than the F*ST estimate, as judged from the 95% confidence intervals by bootstrapping, the FST estimates for branch angle and branch diameter were indistinguishable from the F*ST estimate. Differentiation in stem height and stem diameter might reflect the inherent adaptation of the populations for rapid growth to escape suppression by neighboring plants during establishment and to regional differences in photoperiod, precipitation and temperature. In contrast, divergences in wood specific gravity and branch length might be correlated responses to population differentiation in stem growth. Possible bias in the estimation of FST due to Hardy-Weinberg disequilibrium (FIS not equal to 0), linkage disequilibrium, maternal effects and nonadditive genetic effects was discussed with special reference to P. contorta ssp. latifolia.
Immigration is an important force shaping the social structure, evolution, and genetics of populations. A statistical method is presented that uses multilocus genotypes to identify individuals who are immigrants, or have recent immigrant ancestry. The method is appropriate for use with allozymes, microsatellites, or restriction fragment length polymorphisms (RFLPs) and assumes linkage equilibrium among loci. Potential applications include studies of dispersal among natural populations of animals and plants, human evolutionary studies, and typing zoo animals of unknown origin (for use in captive breeding programs). The method is illustrated by analyzing RFLP genotypes in samples of humans from Australian, Japanese, New Guinean, and Senegalese populations. The test has power to detect immigrant ancestors, for these data, up to two generations in the past even though the overall differentiation of allele frequencies among populations is low.
We derive here two new estimators of admixture proportions based on a coalescent approach that explicitly takes into account molecular information as well as gene frequencies. These estimators can be applied to any type of molecular data (such as DNA sequences, restriction fragment length polymorphisms [RFLPs], or microsatellite data) for which the extent of molecular diversity is related to coalescent times. Monte Carlo simulation studies are used to analyze the behavior of our estimators. We show that one of them (mY) appears suitable for estimating admixture from molecular data because of its absence of bias and relatively low variance. We then compare it to two conventional estimators that are based on gene frequencies. mY proves to be less biased than conventional estimators over a wide range of situations and especially for microsatellite data. However, its variance is larger than that of conventional estimators when parental populations are not very differentiated. The variance of mY becomes smaller than that of conventional estimators only if parental populations have been kept separated for about N generations and if the mutation rate is high. Simulations also show that several loci should always be studied to achieve a drastic reduction of variance and that, for microsatellite data, the mean square error of mY rapidly becomes smaller than that of conventional estimators if enough loci are surveyed. We apply our new estimator to the case of admixed wolflike Canid populations tested for microsatellite data.
We analyzed the European genetic contribution to 10 populations of African descent in the United States (Maywood, Illinois; Detroit; New York; Philadelphia; Pittsburgh; Baltimore; Charleston, South Carolina; New Orleans; and Houston) and in Jamaica, using nine autosomal DNA markers. These markers either are population-specific or show frequency differences >45% between the parental populations and are thus especially informative for admixture. European genetic ancestry ranged from 6.8% (Jamaica) to 22.5% (New Orleans). The unique utility of these markers is reflected in the low variance associated with these admixture estimates (SEM 1.3%-2.7%). We also estimated the male and female European contribution to African Americans, on the basis of informative mtDNA (haplogroups H and L) and Y Alu polymorphic markers. Results indicate a sex-biased gene flow from Europeans, the male contribution being substantially greater than the female contribution. mtDNA haplogroups analysis shows no evidence of a significant maternal Amerindian contribution to any of the 10 populations. We detected significant nonrandom association between two markers located 22 cM apart (FY-null and AT3), most likely due to admixture linkage disequilibrium created in the interbreeding of the two parental populations. The strength of this association and the substantial genetic distance between FY and AT3 emphasize the importance of admixed populations as a useful resource for mapping traits with different prevalence in two parental populations.
Gene flow between genetically distinct populations creates linkage disequilibrium (admixture linkage disequilibrium [ALD]) among all loci (linked and unlinked) that have different allele frequencies in the founding populations. We have explored the distribution of ALD by using computer simulation of two extreme models of admixture: the hybrid-isolation (HI) model, in which admixture occurs in a single generation, and the continuous-gene-flow (CGF) model, in which admixture occurs at a steady rate in every generation. Linkage disequilibrium patterns in African American population samples from Jackson, MS, and from coastal South Carolina resemble patterns observed in the simulated CGF populations, in two respects. First, significant association between two loci (FY and AT3) separated by 22 cM was detected in both samples. The retention of ALD over relatively large (>10 cM) chromosomal segments is characteristic of a CGF pattern of admixture but not of an HI pattern. Second, significant associations were also detected between many pairs of unlinked loci, as observed in the CGF simulation results but not in the simulated HI populations. Such a high rate of association between unlinked markers in these populations could result in false-positive linkage signals in an admixture-mapping study. However, we demonstrate that by conditioning on parental admixture, we can distinguish between true linkage and association resulting from shared ancestry. Therefore, populations with a CGF history of admixture not only are appropriate for admixture mapping but also have greater power for detection of linkage disequilibrium over large chromosomal regions than do populations that have experienced a pattern of admixture more similar to the HI model, if methods are employed that detect and adjust for disequilibrium caused by continuous admixture.
The utilization of DNA evidence in cases of forensic identification has become widespread over the last few years. The strength of this evidence against an individual standing trial is typically presented in court in the form of a likelihood ratio (LR) or its reciprocal (the profile match probability). The value of this LR will vary according to the nature of the genetic relationship between the accused and other possible perpetrators of the crime in the population. This paper develops ideas and methods for analysing data and evaluating LRs when the evidence is based on short tandem repeat profiles, with special emphasis placed on a Bayesian approach. These are then applied in the context of a particular quadruplex profiling system used for routine case-work by the UK Forensic Science Service.
The Bayes factor is a ratio of two posterior normalizing constants, which may be difficult to compute. We compare several methods of estimating Bayes factors when it is possible to simulate observations from the posterior distributions, via Markov chain Monte Carlo or other techniques. The methods that we study are all easily applied without consideration of special features of the problem, provided that each posterior distribution is well behaved in the sense of having a single dominant mode. We consider a simulated version of Laplace's method, a simulated version of Bartlett correction, importance sampling, and a reciprocal importance sampling technique. We also introduce local volume corrections for each of these. In addition, we apply the bridge sampling method of Meng and Wong. We find that a simulated version of Laplace's method, with local volume correction, furnishes an accurate approximation that is especially useful when likelihood function evaluations are costly. A simple bridge sampling technique in conjunction with Laplace's method often achieves an order of magnitude improvement in accuracy.
In the context of Bayes estimation via Gibbs sampling, with or without data augmentation, a simple approach is developed for computing the marginal density of the sample data (marginal likelihood) given parameter draws from the posterior distribution. Consequently, Bayes factors for model comparisons can be routinely computed as a by-product of the simulation. Hitherto, this calculation has proved extremely challenging. Our approach exploits the fact that the marginal density can be expressed as the prior times the likelihood function over the posterior density. This simple identity holds for any parameter value. An estimate of the posterior density is shown to be available if all complete conditional densities used in the Gibbs sampler have closed-form expressions. To improve accuracy, the posterior density is estimated at a high density point, and the numerical standard error of resulting estimate is derived. The ideas are applied to probit regression and finite mixture models.
New methodology for fully Bayesian mixture analysis is developed, making use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter subspaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution. The methodology is applied here to the analysis of univariate normal mixtures, using a hierarchical prior model that offers an approach to dealing with weak prior information while avoiding the mathematical pitfalls of using improper priors in the mixture context.
Recently founded populations represent an enormous challenge for genetic analysis: new populations are often genetically impoverished, making it hard to find sufficiently variable markers, and what little variation is present tends to be ancestral, rendering phylogenetic methods inappropriate. Recently, novel genetic markers and new statistical analyses have made multilocus genotyping an invaluable tool in the fledgling field of nonequilibrium population genetics. Such advances are not of mere academic interest but address questions of great economic, medical and conservation significance.
We have analysed data of three European populations speaking non-Indoeuropean languages: Hungarians, Lapps, and Finns. Principal coordinate analysis shows that Lapps are almost exactly intermediate between people located geographically near the Ural mountains and speaking Uralic languages, and central and northern Europeans. Hungarians and Finns are definitely closer to Europeans. An analysis of genetic admixture between Uralic and European ancestors shows that Lapps are slightly more than 50% European, Hungarians are 87% European, and Finns are 90% European. There is basic agreement between these conclusions and historical data on Hungary. Less is known about Finns and very little about Lapps.
Most quantitative traits in most populations exhibit heritable genetic variation. Lande proposed that high levels of heritable variation may be maintained by mutation in the face of stabilizing selection. Several analyses have appeared of two distinct models with n additive polygenic loci subject to mutation and stabilizing selection. Each is reviewed and a new analysis and model are presented. Lande and Fleming analyzed extensions of a model originally treated by Kimura which assumes a continuum of possible allelic effects at each locus. Latter and Bulmer analyzed a model with diallelic loci. The published analyses of these models lead to qualitatively different predictions concerning the dependence of the equilibrium genetic variance on the underlying biological parameters. A new asymptotic analysis of the Kimura model shows that the different predictions are not consequences of the number of alleles assumed but rather are attributable to assumptions concerning the relative magnitudes of per locus mutation rates, the phenotypic effects of mutation, and the intensity of selection. This conclusion is reinforced by analysis of a model with triallelic loci. None of the approximate analyses presented are mathematically rigorous. To quantify their accuracy and display the domains of validity for alternative approximations, numerically determined equilibria are presented. In addition, empirical estimates of mutation rates and selection intensity are reviewed, revealing weaknesses in both the data and its connection to the models. Although the mathematical results and underlying biological requirements of my analyses are quite different from those of Lande , the results do not refute his hypothesis that considerable additive genetic variance may be maintained by mutation-selection balance. However, I argue that the validity of this hypothesis can only be determined with additional data and mathematics.
To test hypotheses about the origin of modern humans, we analyzed mtDNA sequences, 30 nuclear restriction-site polymorphisms (RSPs), and 30 tetranucleotide short tandem repeat (STR) polymorphisms in 243 Africans, Asians, and Europeans. An evolutionary tree based on mtDNA displays deep African branches, indicating greater genetic diversity for African populations. This finding, which is consistent with previous mtDNA analyses, has been interpreted as evidence for an African origin of modern humans. Both sets of nuclear polymorphisms, as well as a third set of trinucleotide polymorphisms, are highly consistent with one another but fail to show deep branches for African populations. These results, which represent the first direct comparison of mtDNA and nuclear genetic data in major continental populations, undermine the genetic evidence for an African origin of modern humans.
Disease association with a genetic marker is often taken as a preliminary indication of linkage with disease susceptibility. However, population subdivision and admixture may lead to disease association even in the absence of linkage. In a previous paper, we described a test for linkage (and linkage disequilibrium) between a genetic marker and disease susceptibility; linkage is detected by this test only if association is also present. This transmission/disequilibrium test (TDT) is carried out with data on transmission of marker alleles from parents heterozygous for the marker to affected offspring. The TDT is a valid test for linkage and association, even when the association is caused by population subdivision and admixture. In the previous paper, we did not explicitly consider the effect of recent history on population structure. Here we extend the previous results by examining in detail the effects of subdivision and admixture, viewed as processes in population history. We describe two models for these processes. For both models, we analyze the properties of (a) the TDT as a test for linkage (and association) between marker and disease and (b) the conventional contingency statistic used with family data to test for population association. We show that the contingency test statistic does not have a chi 2 distribution if subdivision or admixture is present. In contrast, the TDT remains a valid chi 2 statistic for the linkage hypothesis, regardless of population history.
Certain human hereditary conditions, notably those with low penetrance and those which require an environmental event such as infectious disease exposure, are difficult to localize in pedigree analysis, because of uncertainty in the phenotype of an affected patient's relatives. An approach to locating these genes in human cohort studies would be to use association analysis, which depends on linkage disequilibrium of flanking polymorphic DNA markers. In theory, a high degree of linkage disequilibrium between genes separated by 10-20 cM will be generated and persist in populations that have a history of recent (3-20 generations ago) admixture between genetically differentiated racial groups, such as has occurred in African Americans and Hispanic populations. We have conducted analytic and computer simulations to quantify the effect of genetic, genomic, and population parameters that affect the amount and ascertainment of linkage disequilibrium in populations with a history of genetic admixture. Our goal is to thoroughly explore the ranges of all relevant parameters or factors (e.g., sample size and degree of genetic differentiation between populations) that may be involved in gene localization studies, in hopes of prescribing guidelines for an efficient mapping strategy. The results provide reasonable limits on sample size (200-300 patients), marker number (200-300 in 20-cM intervals), and allele differentiation (loci with allele frequency difference of > or = .3 between admixed parent populations) to produce an efficient approach (> 95% ascertainment) for locating genes not easily tracked in human pedigrees.
Our goal is to infer, from human genetic data, general patterns as well as details of human evolutionary history. Here we present the results of an analysis of genetic data at the level of the individual. A tree relating 144 individuals from 12 human groups of Africa, Asia, Europe, and Oceania, inferred from an average of 75 DNA polymorphisms/individual, is remarkable in that most individuals cluster with other members of their regional group. In order to interpret this tree, we consider the factors that influence the tree pattern, including the number of genetic loci examined, the length of population isolation, the sampling process, and the extent of gene flow among groups. Understanding the impact of these factors enables us to infer details of human evolutionary history that might otherwise remain undetected. Our analyses indicate that some recent ancestor(s) of each of a few of the individuals tested may have immigrated. In general, the populations within regional groups appear to have been isolated from one another for <25,000 years. Regional groups may have been isolated for somewhat longer.
Genes that underlie ethnic differences in disease risk can be mapped in affected individuals of mixed descent if the ancestry of the alleles at each marker locus can be assigned to one of the two founding populations. Linkage can be detected by testing for association of the disease with the ancestry of alleles at the marker locus, by conditioning on the admixture (defined as the proportion of genes that have ancestry from the high-risk population) of both parents. With regard to exploiting the effects of admixture, this test is more flexible and powerful than the transmission-disequilibrium test. Under the assumption of a multiplicative model, the statistical power for a given sample size depends only on parental admixture and the risk ratio r between populations that is generated by the locus. The most informative families are those in which mean parental admixture is .2-.7 and in which admixture is similar in both parents. The number of markers required for a genome search depends on the number of generations since admixture and on the information content for ancestry (f) of the markers, defined as a function of allele frequencies in the two founding populations. Simulations using a hidden Markov model suggest that, when admixture has occurred 2-10 generations earlier, a multipoint analysis using 2,000 biallelic markers, with f values of 30%, can extract 70%-90% of the ancestry information for each locus. Sets of such markers could be selected from libraries of single-nucleotide polymorphisms, when these become available.
We examine the issue of population stratification in association-mapping studies. In case-control studies of association, population subdivision or recent admixture of populations can lead to spurious associations between a phenotype and unlinked candidate loci. Using a model of sampling from a structured population, we show that if population stratification exists, it can be detected by use of unlinked marker loci. We show that the case-control-study design, using unrelated control individuals, is a valid approach for association mapping, provided that marker loci unlinked to the candidate locus are included in the study, to test for stratification. We suggest guidelines as to the number of unlinked marker loci to use.
We propose a novel latent-class approach to detect and account for population stratification in a case-control study of association between a candidate gene and a disease. In our approach, population substructure is detected and accounted for using data on additional loci that are in linkage equilibrium within subpopulations but have alleles that vary in frequency between subpopulations. We have tested our approach using simulated data based on allele frequencies in 12 short tandem repeat (STR) loci in four populations in Argentina.
The utilization of DNA evidence in cases of forensic identification has become widespread over the last few years. The strength of this evidence against an individual standing trial is typically presented in court in the form of a likelihood ratio (LR) or its reciprocal (the profile match probability). The value of this LR will vary according to the nature of the genetic relationship between the accused and other possible perpetrators of the crime in the population. This paper develops ideas and methods for analysing data and evaluating LRs when the evidence is based on short tandem repeat profiles, with special emphasis placed on a Bayesian approach. These are then applied in the context of a particular quadruplex profiling system used for routine case-work by the UK Forensic Science Service.
Markov chain Monte Carlo methods for Bayesian computation have until recently been restricted to problems where the joint
distribution of all variables has a density with respect to some fixed standard underlying measure. They have therefore not
been available for application to Bayesian model determination, where the dimensionality of the parameter vector is typically
not fixed. This paper proposes a new framework for the construction of reversible Markov chain samplers that jump between
parameter subspaces of differing dimensionality, which is flexible and entirely constructive. It should therefore have wide
applicability in model determination problems. The methodology is illustrated with applications to multiple change-point analysis
in one and two dimensions, and to a Bayesian comparison of binomial experiments.
In a Bayesian analysis of finite mixture models, parameter estimation and clustering are sometimes less straightforward that might be expected. In particular, the common practice of estimating parameters by their posterior mean, and summarising joint posterior distributions by marginal distributions, often leads to nonsensical answers. This is due to the so-called "labelswitching " problem, which is caused by symmetry in the likelihood of the model parameters. A frequent response to this problem is to remove the symmetry using artificial identifiability constraints. We demonstrate that this fails in general to solve the problem, and describe an alternative class of approaches, relabelling algorithms, which arise from attempting to minimise the posterior expected loss under a class of loss functions. We describe in detail one particularly simple and general relabelling algorithm, and illustrate its success in dealing with the labelswitching problem on two examples. KEYWORDS: ...
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