Population Genetic Research Articles

Genetic Diversity and Population Structure Analysis of Soybean [Glycine max (L.) Merrill] Genotypes Using Agro-Morphological Traits and SNP Markers

Background/Objectives: Understanding the genetic diversity of soybean genotypes can provide valuable information that guides parental selection and the design of an effective hybridization strategy in a soybean breeding program. In order to identify genetically diverse, complementary, and prospective parental lines for breeding, this study set out to ascertain the genetic diversity, relationships, and population structure among 35 soybean genotypes based on agro-morphological traits and Single Nucleotide Polymorphic (SNP) marker data. Methods/Results: Cluster analysis, based on agro-morphological traits, grouped the studied genotypes into four clusters. The first two principal components accounted for 62.8% of the total phenotypic variation, where days to 50% flowering, days to 95% maturity, grain yield, shattering score, and lodging score had high and positive contributions to the total variation. Using the SNP marker information, mean values of 0.16, 0.19, 0.067, and 0.227 were obtained for minor allele frequency (MAF), polymorphic information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He), respectively. Using different clustering approaches (admixture population structure, principal component scatter plot, and hierarchical clustering), the studied genotypes were grouped into four major clusters. Conclusions:The agro-morphological and molecular analysis results indicated the existence of moderate genetic diversity among the studied genotypes. The traits identified to be significantly related to yield provide valuable information for the genetic improvement of soybeans for yield.

Unveiling genetic diversity and population structure for nutraceutical and grain ionome profile in traditional rice cultivars

Unveiling genetic diversity and population structure for nutraceutical and grain ionome profile in traditional rice cultivars

Whole genome sequencing of Castanea mollissima and molecular mechanisms of sugar and starch synthesis.

The chestnut tree exhibits self-incompatibility, where the selection of the male parent (pollen xenia) significantly affects seed starch metabolism, as well as fruit yield and quality. Despite its importance, the molecular mechanisms underlying pollen xenia remains largely unknown. In this study, we utilized the 'Lan You' variety of C. mollissima to construct a high-quality reference genome. As a result, a first Telomere-to-telomere (T2T) gap-free genome for this species was successfully assembled. A total of 560 transcription factors and 22 structural genes were identified as consistent across the TO-GCNs, indicating a consistent regulation pattern in the co-expression of genes involved in starch accumulation. These networks were further divided into three sub-networks: T1, T2, and T3. Among these, the T1 and T2 sub-networks exhibited a higher number of structural genes with consistent regulation patterns and were closely associated with sugar biosynthesis. The gene SBE (Camol08G0254600) was identified as the hub gene with the highest degree of connectivity, encoding a key rate-limiting enzyme in the amylopectin biosynthesis pathway. This study provides a foundation for further research on C. mollissima population genetics, genetic improvement, and strategies aimed at enhancing yield and quality.

Population genomics of a specialized insect, Tetraopes texanus (Coleoptera: Cerambycidae), across a fragmented grassland system

AbstractSpecialist insects are especially susceptible to loss of genetic diversity in the face of habitat destruction and fragmentation. Implementing effective conservation practices for specialist insects will benefit from knowledge of population structure and genetic diversity. Because insects are hyper-diverse, characterizing the population structure of all species within the insect community is untenable, even if focused within a particular habitat type. Thus, concentrating on a single species specialized to a particular habitat type is needed to infer general trends. Here, we investigate the range-wide population genetics of Tetraopes texanus Horn 1878 (Coleoptera: Cerambycidae), which provides a useful model of grassland insects due to its’ habitat specificity and unique biology. Tetraopes texanus occurs primarily in Texas and Oklahoma, into Northern Mexico, and possibly into eastern New Mexico but also occurs in Black Belt prairies of Mississippi and Alabama. Mitochondrial and nuclear DNA (RAD-seq) analysis identified two distinct population clusters of T. texanus corresponding to the Texas and Oklahoma population and the Mississippi and Alabama population. Demographic models indicate ongoing, though incomplete, isolation of the two populations, with estimated dates of divergence in the mid-Pleistocene, coinciding with the end of a glacial period and a shift in glacial interval. These results can inform conservation of grassland adapted insects and offers insight to the biogeography of the Gulf Coastal Plain.

Temporal and inter-specific population genetics analyses of Sebastiscus marmoratus and S. tertius provide novel implications for fishery management

ABSTRACT Understanding population genetic diversity and evolutionary dynamics of marine fish species can provide theoretical bases for fishery management and germplasm conservation, especially facing a changing environment. The rockfish species in genus Sebastiscus are economically important species for farming and sport fisheries in China, Japan and Korea. In this study, inter-annual and inter-specific comparisons on genetic diversity, population differentiation and historical demography of S. marmoratus and S. tertius collected from coastal waters of Zhangzhou, China were conducted using mitochondrial control region sequences. High levels of genetic diversity were observed in both species, indicating high adaptive potential to environmental changes. Demographic analyses detected recent population expansion in population S. tertius (Ste-2020) and population S. marmoratus collected in 2020 (Sma-2020), yet failed in population collected in 2016 (Sma-2016). Moreover, in population Sma-2020, novel haplotypes were detected and grouped into a separate sub-branch, revealed by neighbour-joining topology. Detected recent population expansion and novel haplotypes might be considered as a response to environmental changes. Besides, results of genetic differentiation analysis suggested high intra-specific genetic variation in both species. These genetic data and information will provide novel implications for strengthening the management of S. marmoratus and S. tertius fisheries in climate change scenarios.

Genetic variability and discriminatory power of RM Y-STRs in gilgit men: a population study

AbstractShort Tandem Repeats (STRs) found on the Y chromosome have multiple applications, such as in forensic investigations, male identification for legal reasons, as well as population genetics. However, commercially accessible Y-STR tests are limited in their capability to distinguish closely linked male individuals in forensic genetics. Recent studies have revealed that Rapidly Mutating Y-STRs (RM Y-STRs) offer significantly greater haplotype diversity around the worldwide populations associated to conventional Y-STRs, though some RM Y-STR loci are not contained, current commercial kits. The objective of this research is to create a database of RM Y-STR haplotype frequencies for the Gilgit population in Pakistan and evaluate the effectiveness of these genetic markers in distinguishing individuals with genetic variations. The research involved examining several RM Y-STRs in 56 unrelated Gilgit men. The statistical analysis determined that the majority of the loci-maintained haplotype values, as specific varied in certain cases. The results presented that the RM Y-STRs were very effective in distinguishing genetic changes among the Gilgit population, through a GD value of 0 for DYD403S1 and GD values greater than 0.7 for all other loci, with maximum value of 0.9920 for the RM Y-STR DYS612.

Genetic Diversity and Population Structure of Cacao (Theobroma cacao L.) Germplasm from Sierra Leone and Togo Based on KASP–SNP Genotyping

Cacao (Theobroma cacao L.) is a tropical tree species belonging to the Malvaceae, which originated in the lowland rainforests of the Amazon. It is a major agricultural commodity, which contributes towards the Gross Domestic Product of West African countries, where it accounts for about 70% of the world’s production. Understanding the genetic diversity of genetic resources in a country, especially for an introduced crop such as cacao, is crucial to their management and effective utilization. However, very little is known about the genetic structure of the cacao germplasm from Sierra Leone and Togo based on molecular information. We assembled cacao germplasm accessions (235 from Sierra Leone and 141 from Togo) from different seed gardens and farmers’ fields across the cacao-producing states/regions of these countries for genetic diversity and population structure studies based on single nucleotide polymorphism (SNP) markers using 20 highly informative and reproducible KASP–SNPs markers. Genetic diversity among these accessions was assessed with three complementary clustering methods, including model-based population structure, discriminant analysis of principal components (DAPC), and phylogenetic trees. STRUCTURE and DAPC exhibited some consistency in the allocation of accessions into subpopulations or groups, although some discrepancies in their groupings were noted. Hierarchical clustering analysis grouped all the individuals into two major groups, as well as several sub-clusters. We also conducted a network analysis to elucidate genetic relationships among cacao accessions from Sierra Leone and Togo. Analysis of molecular variance (AMOVA) revealed high genetic diversity (86%) within accessions. A high rate of mislabeling/duplicate genotype names was revealed in both countries, which may be attributed to errors from the sources of introduction, labeling errors, and lost labels. This preliminary study demonstrates the use of KASP–SNPs for fingerprinting that can help identify duplicate/mislabeled accessions and provide strong evidence for improving accuracy and efficiency in cacao germplasm management as well as the distribution of correct materials to farmers.

The genetic diversity and population structure of wild and cultivated Avena species in Ethiopia using a SSR markers

Oats are grains that can be consumed by both animals and humans. They have thrived in Ethiopia, where certain oat species are considered native to the region. This work represents the first investigation of the population structure and genetic diversity of Ethiopian and other country oats. This led the scientists to explore the genetic diversity and population structure of wild and cultivated Ethiopian oats (Avena) species as well as oat cultivated in USA, the Netherlands and Austria. This study's main objective looks to be to investigate the variation in genetic makeup of cultivated and wild oat species. Studying the population structure of the oat species in the germplasm of Ethiopia, USA, the Netherlands and Austria. We used nineteen fluorescent SSR (simple sequence repeat) markers since previous research had indicated that these markers had high PIC (polymorphism information content) values. Five species of Avena were studied among the 176 oat accessions: A. sativa (cultivated oats) and four wild oats, such as A. abyssinica, A. vaviloviana, A. fatua, and A. sterilis. The AMOVA investigation revealed significant genetic distinctions among populations, individuals, and within individuals, explaining 18 % of the variance within populations, 4 % among populations, and 78 % within individuals. The AMOVA analysis of Avena species demonstrated extensive variance, with 33 % variation among species and 67 % within each species, underscoring robust species differentiation. The study also discovered gene interchange between wild oat and cultivated populations, defining two Avena species: domesticated oats and wild oats. Using the STRUCTURE software at K = 2, PCoA, and UPGMA, a distinct genetic structure was displayed in the dataset. Despite variations in ploidy levels and genomes, A. sterilis and A. vaviloviana were determined to be more closely linked, whereas A. abyssinica and A. fatua demonstrated a close association. This research delivers valuable insights for scientists and can be employed in oat breeding programs to improve future oat yield and productivity.

Assessment of Genetic Diversity and Population Structure of Exotic Sugar Beet (Beta vulgaris L.) Varieties Using Three Molecular Markers.

Sugar beet (Beta vulgaris L.) is a biennial herb belonging to the Amaranthaceae family. It contributes to approximately 30% of the world's total sucrose production and is an economically important crop. In this study, we analyzed the genetic diversity and population structure of 132 exotic sugar beet varieties using three molecular makers: four pairs of simple sequence repeat (SSR) primers, three pairs of insertion-deletion sequence (InDel) primers, and 20 cis-element amplification polymorphism (CEAP) primers. The results indicated that the number of alleles (Na) was 298, among which the number of effective alleles (Ne) was 182.426 (accounting for approximately 61.2%). The mean value of the genetic diversity index was 0.836. The polymorphic information content (PIC) was 0.639-0.907 (mean = 0.819), indicating a high level of polymorphism. These sugar beet varieties were classified into six clusters using the UPGMA method of cluster analysis. Population structure analysis revealed that the most ideal K value was 6. This indicated that the test materials could be divided into six categories, consistent with the clustering results. The clustering results indicated that most sugar beet varieties from the same breeding company clustered together, and the genetic distance between them was small, indicating that they may share the same male and/or female parent. Some varieties from different companies clustered together, indicating a narrow genetic base and potential exchange of germplasm resources between breeding companies. This study revealed the genetic differences among exotic sugar beet varieties and characteristics of the population structure. It provided a scientific basis for the identification of sugar beet varieties and markers-assisted breeding in China in the future.

The carrot cyst nematode Heterodera carotae: a major plant-parasitic nematode requiring more investigation

Summary The present study reviews the knowledge to date on the carrot cyst nematode Heterodera carotae, which has become the primary threat to the carrot sector following the withdrawal of the last chemical soil fumigants in Europe. A keyword co-occurrence network was used to structure this review into five research areas: i) biology and epidemiology of H. carotae; ii) molecular identification and phylogeny; iii) population genetics and genomics; iv) control methods and strategies; and v) root exudates and hatching stimulation. Our findings indicate that H. carotae is an under-studied plant-parasitic nematode species, with several identified alternative control methods that require further investigation.

A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys

Abstract Understanding how ecological assemblages vary in space and time is essential for advancing our knowledge of biodiversity dynamics and ecosystem functioning. Metabarcoding of environmental DNA (eDNA) is an efficient method for documenting biodiversity changes in both marine and terrestrial ecosystems. However, current methods fail to detect and display the biodiversity structure within and between eDNA samples limiting ecological and biogeographical interpretations. We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. The method aims to reduce the multi‐taxa composition structure into a low number of dimensions defined by these sources. This method is inspired by admixture analysis in population genetics. Using a marine fish eDNA survey on 263 sampling stations detecting 2888 molecular operational taxonomic units (MOTUs), we apply this method to analyse the biogeography and mixing patterns of fish assemblages at regional and large scales. At large scale, our analysis reveals six primary pools of fish samples characterized by distinct biogeographic patterns, with some mixtures between these pools. We identify pools composed of unique sources, corresponding to distinct and more isolated regions such as the Mediterranean and Scotia Seas. We also identify pools composed of a greater mix of sources, corresponding to geographically connected areas, such as tropical regions. Additionally, we identify the taxa underpinning the formation of each pool. In the regional analysis of Mediterranean eDNA samples, our method successfully identifies different pools, allowing the detection of not only geographic gradients but also human‐induced gradients corresponding to protection levels. Spatial matrix factorization adds a new method in community ecology, where each sample is considered as a mixture of K unobserved sources, to assess the dissimilarity of ecological assemblages revealing environmental and human‐induced gradients. Beyond the study of fish eDNA samples, this method has the potential to shed new light on any biodiversity survey and provide new bioindicators of global change.

Agent-Based Geosimulation of Yayoi Period Population Dynamics in Kyushu, Japan

Current scholarship in Japanese archaeology recognizes the people and culture of the Yayoi period as being descended from both continental migrants (Toraijin) and the native inhabitants (Jomon people). However, the number of migrants that came to Japan and the degree to which they were directly responsible for the development of Yayoi culture is a topic of debate. Using northern Kyushu as a case study, the author employs an agent-based simulation based on geospatial data to model the spread of population, rice agriculture, and continental genetics during the Early Yayoi period. Multiple simulations are performed with varying parameters related to migrant population size, marriage customs, and the ratio of men to women amongst migrants to test their effect on the demographics of the Yayoi period. Simulation results were compared to population estimates and the distribution of mitochondrial DNA in order to determine their validity. Experiment 1 showed that the average number of continental migrants was likely in the order of magnitude of 10s of people per year (approx. 40 to 50) during the first 500 years of the Yayoi period. Experiment 2 demonstrated that polygyny can lead to increased population growth and aids in the spread of continental genetics, but without more rigorous evaluation criteria it is difficult to conclude whether it was practiced during the period. The methods used in this study demonstrate how agent-based simulations can model realistically sized populations moving through geographic space by basing simulation inputs on geospatial data and population estimates.

Genomic epidemiology and evolutionary dynamics of the Omicron variant of SARS-CoV-2 during the fifth wave of COVID-19 in Pakistan.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed extraordinary challenges to global health systems and economies. The virus's rapid evolution has resulted in several variants of concern (VOCs), including the highly transmissible Omicron variant, characterized by extensive mutations. In this study, we investigated the genetic diversity, population differentiation, and evolutionary dynamics of the Omicron VOC during the fifth wave of COVID-19 in Pakistan. A total of 954 Omicron genomes sequenced during the fifth wave of COVID-19 in Pakistan were analyzed. A Bayesian framework was employed for phylogenetic reconstructions, molecular dating, and population dynamics analysis. Using a population genomics approach, we analyzed Pakistani Omicron samples, revealing low within-population genetic diversity and significant structural variation in the spike (S) protein. Phylogenetic analysis showed that the Omicron variant in Pakistan originated from two distinct lineages, BA.1 and BA.2, which were introduced from South Africa, Thailand, Spain, and Belgium. Omicron-specific mutations, including those in the receptor-binding domain, were identified. The estimated molecular evolutionary rate was 2.562E-3 mutations per site per year (95% HPD interval: 8.8067E-4 to 4.1462E-3). Bayesian skyline plot analysis indicated a significant population expansion at the end of 2021, coinciding with the global Omicron outbreak. Comparative analysis with other VOCs showed Omicron as a highly divergent, monophyletic group, suggesting a unique evolutionary pathway. This study provides a comprehensive overview of Omicron's genetic diversity, genomic epidemiology, and evolutionary dynamics in Pakistan, emphasizing the need for global collaboration in monitoring variants and enhancing pandemic preparedness.

Principal component analysis revisited: fast multitrait genetic evaluations with smooth convergence.

A cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits are considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy. However, the number of parameters in the multitrait model grows exponentially with the number of traits which reduces its scalability. Here, we suggest using principal component analysis to reduce the dimensions of the response variables, and then using the computed principal components as separate responses in the genetic evaluation analysis. As principal components are orthogonal to each other so that phenotypic covariance is abscent between principal components, a full multivariate analysis can be approximated by separate univariate analyses instead which should speed up computations considerably. We compared the approach to both traditional multivariate analysis and factor analytic approach in terms of computational requirement and rank lists according to predicted genetic merit on two forest tree datasets with 22 and 27 measured traits, respectively. Obtained rank lists of the top 50 individuals were in good agreement. Interestingly, the required computational time of the approach only took a few seconds without convergence issues, unlike the traditional approach which required considerably more time to run (7 and 10 h, respectively). The factor analytic approach took approximately 5-10 min. Our approach can easily handle missing data and can be used with all available linear mixed effect model softwares as it does not require any specific implementation. The approach can help to mitigate difficulties with multitrait genetic analysis in both breeding and wild populations.

Monitoring spatiotemporal patterns in the genetic diversity of a European butterfly species

Abstract The importance of genetic diversity has been recognised by the Convention on Biological Diversity but attempts at monitoring or improving the genetic diversity of populations have been minimal. Here, we investigate changes over time in the genetic diversity of a wild insect species, Maniola jurtina (Lepidoptera: Nymphalidae) and present a large‐scale investigation into contemporary spatial genetic diversity. Using microsatellite markers, we calculate multiple measures of genetic diversity and divergence for M. jurtina populations over 8 years in the UK and compare these findings with long‐term abundance trends. We also conduct a large‐scale spatial analysis into the genetic diversity and population structuring of M. jurtina across Europe. All UK populations sampled have high levels of gene flow and genetic diversity, with genetic diversity stable over time. Across Europe, we find some population structuring between populations in the UK and the European mainland, suggesting restricted geneflow between the two regions. The monitoring of a wild species' genetic diversity is an achievable aim, and one that could be carried out for many species, particularly Lepidoptera. Future approaches may aim to develop higher resolution genetic markers and cover a wider range of species. The use of abundance data offers additional insight, and we find that concurrent, dedicated genetic monitoring can provide effective tracking of biodiversity trends.

Parity-specific differences in spatial genetics and dispersal in the common lizard.

Dispersal is a key demographic parameter that plays an important role in determining spatial population dynamic and genetic structure. Linking differences in dispersal patterns to key life-history traits is often confounded by inconsistent environmental pressures experienced by different populations. To explore the link between dispersal and life history, we focus on a site where oviparous and viviparous lineages of the common lizard (Zootoca vivipara) are found adjacent to each other. We take advantage of this shared environment to investigate parity-specific dispersal patterns using high resolution, individual-level spatial genetic autocorrelation and population genomic approaches (11,726 SNPs; 293 oviparous and 310 viviparous individuals). We found isolation-by-distance patterns to be present in both the oviparous and viviparous populations. Density was 2.5 times higher in the viviparous population than the oviparous one, though heterozygosity and genetic diversity measures were similar in the two populations. We found marked differences in the extent of genetic neighbourhoods between the lineages, with the viviparous population showing both dispersal (σ) and spatial genetic autocorrelation (Moran's I) at two-fold greater geographic distances than the oviparous population. We found clear evidence of male-biased dispersal from genetic estimates in the viviparous population. In the oviparous population, evidence of male-biased dispersal is weak or absent. These differences are likely to be closely linked to specific requirements of the alternative reproductive strategies and may be the demographic consequences of mother-offspring interactions. Fine-scale geographic and individual-level measures are key to understanding parity mode differences at microevolutionary scales and to better identifying their ecological and evolutionary impacts.

Inferring ancestry with the hierarchical soft clustering approach tangleGen.

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, which leverages graph theoretical concepts, 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 ancestral relationships, using both simulated data and data from the 1000 Genomes Project.

Population genetics of the freshwater red alga Batrachospermum gelatinosum (Rhodophyta) II: Phylogeographic analyses reveal spatial genetic structure among and within five major drainage basins in eastern North America.

The freshwater red alga Batrachospermum gelatinosum has a well-documented distribution spanning historically glaciated and unglaciated eastern North America. This alga has no known desiccation-resistant propagule; thus, long-distance dispersal events are likely rare. We predicted strong genetic structure among drainage basins and admixture among sites within basins. We predicted greater genetic diversity at lower latitude sites because they likely serve as refugia and the origin of northward, post-Pleistocene range expansion. We used 10 microsatellite loci to investigate genetic diversity from 311 gametophytes from 18 sites in five major drainage basins: South Atlantic Gulf, Mid-Atlantic, Ohio River, Great Lakes, and Northeast. Our data showed strong genetic partitioning among drainage basins and among sites within basins, yet no isolation by distance was detected. Genetic diversity varied widely among sites and was not strictly related to latitude as predicted. The results from B. gelatinosum provide strong support that each stream site contributes to the unique genetic variation within the species, potentially due to limited dispersal and the prevailing reproductive mode of intragametophytic selfing. Simulations of migration suggested post-Pleistocene dispersal from the Mid-Atlantic. Batrachospermum gelatinosum potentially persisted in refugia that were just south of the ice margins rather than in the southernmost part of its range. Research of other taxa with similar ranges could determine whether these results are generally applicable for freshwater red algae. Nevertheless, these results from B. gelatinosum add to the growing literature focused on the patterns and genetic consequences of post-Pleistocene range expansion by eastern North American biota.

Monitoring the genetic diversity in holothurian populations from the Italian coasts with mitochondrial DNA sequences

Sea cucumbers are deposit feeding members of marine benthic communities. The over-exploitation of sea cucumber natural stocks, especially in the Mediterranean basin, is having negative impacts on the marine ecosystem. This concerns had led the Italian government to take legal actions to preserve these important marine resources. The aim of this study was to evaluate the level of genetic diversity and population structures within two sympatric Holothuria sea cucumber species, H. polii and H. tubulosa, across ten Mediterranean areas along Italy. A 323 bp portion of the COI mitochondrial gene was sequenced in a total of 441 holothurians (251 H. polii, 177 H. tubulosa and 13 from other species). Genetic diversity analyses and analysis of molecular variance (AMOVA) suggest that H. polii and H. tubulosa species are distinct, but within and among populations are homogeneous, indicating active gene flows across the Mediterranean areas investigated. H. polii showed a lower genetic diversity than H. tubulosa, probably related to differences in life history traits. Phylogenetic analyses showed a clear differentiation between the two species, even if six specimens morphologically assigned to a species clustered within the other species, indicating a possible occurrence of hybridization events. These data will be useful in implementing conservation actions for these holothurian genetic resources.

Single nucleotide polymorphism (SNP) analysis reveals ancestry and genetic diversity of cultivated and wild grapevines in Croatia

BackgroundCroatia is a geographically small country with a remarkable diversity of cultivated and spontaneous grapevines. Local germplasm has been characterised by microsatellite markers, but a detailed analysis based on single nucleotide polymorphisms (SNPs) is still lacking. Here we characterize the genetic diversity of 149 accessions from three germplasm repositories and four natural sites using 516,101 SNPs to identify complete parent-offspring trios and their relations with spontaneous populations, offering a proof-of-concept for the use of reduced-representation genome sequencing in population genetics and genome-wide association studies (GWAS).ResultsPrincipal component analysis revealed a clear discontinuity between cultivated (V. vinifera subsp. sativa) and spontaneous grapevines, supporting the notion that the latter represent local populations of the wild progenitor (V. vinifera subsp. sylvestris). ADMIXTURE identified three ancestry components. Two sativa components are alternatively predominant in cultivars grown either in northern Adriatic Croatia and Continental Croatia or in Dalmatia (i.e. central and southern Adriatic Croatia). A sylvestris component, which is predominant in accessions from spontaneous populations, is a minor ancestry component in cultivated accessions. TREEMIX provided evidence of unidirectional migration from the vineyards to natural sites, suggesting that gene flow has gone preferentially from the introduced domesticated germplasm into local wild populations rather than vice versa. Identity-by-descent analysis indicated an extensive kinship network, including 14 complete parent-offspring trios, involving only cultivated accessions, six full-sibling relationships and invalidated a presumed pedigree of one of the most important varieties in Croatia, ‘Plavac Mali’. Despite this strong population structure, significant association was found between 143 SNPs and berry skin colour and between 2 SNPs and leaf hairiness, across two previously known genomic regions.ConclusionsThe clear genetic separation between Croatian cultivars and sylvestris ruled out the hypothesis that those cultivars originated from local domestication events. On the other hand, the evidence of a crop-to-wild gene flow signals the need for an urgent adoption of conservation strategies that preserve the residual genetic integrity of wild relatives. The use of this reduced-representation genome sequencing protocol in grapevine enables an accurate pedigree reconstruction and can be recommended for GWAS experiments.