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By using 16 simple sequence repeat (SSR) markers, the genetic relatedness of 21 exceptional walnut genotypes was assessed. A significant degree of genetic diversity was observed within a given population, as indicated by the number of alleles per locus ranging from 2 to 4. WGA-1, WGA-4, and WGA-79 contained the greatest number of alleles (4), followed by WGA-118, WGA-202, and WGA-42. Conversely, WGA-27, WGA-69, and WGA-32 contained the fewest alleles. The range of the PIC value was 0.11 to 0.38. Using model-based cluster analysis, all genotypes were categorized into two primary clusters according to the UPGMA dendrogram, with varying degrees of sub-clustering. All the genotypes were categorized into six genetically distant subpopulations. The genotypes were genetically distinct but had variable degrees of admixture. The anticipated heterozygosity at a specific locus ranged from 0.563 to 0.741. Additionally, population differentiation (Fst) ranged between 0.176 and 0.261. These findings highlight the importance of considering germplasm diversity in walnut breeding programs and conservation efforts aimed at enhancing walnut cultivation in the region. Overall, this study contributes to our understanding of walnut genetic diversity in the Northwestern Himalayan region of Jammu and Kashmir and informs future breeding and conservation strategies.

Lentil (Lens culinaris Medik. subsp. culinaris) constitutes one of the most important legumes globally, considering a major food source of protein, carbohydrates, and essential micronutrients. Nowadays, its cultivation is under increasing threat due to adverse climatic conditions. Knowledge of the genetic diversity and structure of the lentil germplasm will lead to a better optimization of its genetic resources in breeding programs in order to adapt to climate change. This study aimed to assess the genetic diversity and population structure of 31 lentil accessions consisting of 22 landraces and 9 commercial cultivars of small- and large-seeded types from Greece using ISSR markers. The ISSR-based characterization of the evaluated lentil populations revealed moderate genetic diversity, with polymorphism ranging from 14.29% to 45.45% and corresponding variation in Nei’s gene diversity (GD = 0.063-0.202) and Shannon’s information index (I = 0.091-0.289). Results from AMOVA indicated that 75% of the total variation fell within populations and so revealed strong intra-population heterogeneity, despite the species being highly self-pollinating. UPGMA and PCoA analyses revealed a central cluster of closely related populations and a set of genetically distinct lineages (DIG, KOR, PEL), while geographic structuring was not detected, suggesting the shaping impact of farmer-mediated seed exchange. Thus, these genetically diverse populations are considered important resources for widening the lentil gene pool for breeding, whereas those presenting low diversity may maintain locally adapted or rare alleles. In conclusion, the obtained results provide an important molecular basis for the conservation and further exploitation of Greek lentil landraces in future breeding programs.

There is a need to explore renewable alternatives (e.g., biofuels) that can produce energy sources to help reduce the reliance on fossil oils. In addition, the consumption of fossil oils adversely affects the environment and human health via the generation of waste water, greenhouse gases, and waste solids. , originated from southeastern Europe and southwestern Asia, is being re-embraced as an industrial oilseed crop due to its high seed oil content (36-47%) and high unsaturated fatty acid composition (>90%), which are suitable for jet fuel, biodiesel, high-value lubricants and animal feed. 's agronomic advantages include short time to maturation, low water and nutrient requirements, adaptability to adverse environmental conditions and resistance to common pests and pathogens. These characteristics make it an ideal crop for sustainable agricultural systems and regions of marginal land. However, the lack of genetic and genomic resources has slowed the enhancement of this emerging oilseed crop and exploration of its full agronomic and breeding potential. Here, a core of 213 spring accessions was collected and genotyped. The genotypic data was used to characterize genetic diversity and population structure to infer how natural selection and plant breeding may have affected the formation and differentiation within the natural populations, and how the genetic diversity of this species can be used in future breeding efforts. A total of 6,192 high-quality single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing (GBS) technology. The average polymorphism information content (PIC) value of 0.29 indicate moderate genetic diversity for the spring panel evaluated in this report. Population structure and principal coordinates analyses (PCoA) based on SNPs revealed two distinct subpopulations. Sub-population 1 (POP1) contains accessions that mainly originated from Germany while the majority of POP2 accessions (>75%) were collected from Eastern Europe. Analysis of molecular variance (AMOVA) identified 4% variance among and 96% variance within subpopulations, indicating a high gene exchange (or low genetic differentiation) between the two subpopulations. These findings provide important information for future allele/gene identification using genome-wide association studies (GWAS) and marker-assisted selection (MAS) to enhance genetic gain in breeding programs.

Metabarcoding is by now a well‐established method for biodiversity assessment in terrestrial, freshwater, and marine environments. Metabarcoding data sets are usually used for α‐ and β‐diversity estimates, that is, interspecies (or inter‐MOTU [molecular operational taxonomic unit]) patterns. However, the use of hypervariable metabarcoding markers may provide an enormous amount of intraspecies (intra‐MOTU) information mostly untapped so far. The use of cytochrome oxidase (COI) amplicons is gaining momentum in metabarcoding studies targeting eukaryote richness. COI has been for a long time the marker of choice in population genetics and phylogeographic studies. Therefore, COI metabarcoding data sets may be used to study intraspecies patterns and phylogeographic features for hundreds of species simultaneously, opening a new field that we suggest to name metaphylogeography. The main challenge for the implementation of this approach is the separation of erroneous sequences from true intra‐MOTU variation. Here, we develop a cleaning protocol based on changes in entropy of the different codon positions of the COI sequence, together with co‐occurrence patterns of sequences. Using a data set of community DNA from several benthic littoral communities in the Mediterranean and Atlantic seas, we first tested by simulation on a subset of sequences a two‐step cleaning approach consisting of a denoising step followed by a minimal abundance filtering. The procedure was then applied to the whole data set. We obtained a total of 563 MOTUs that were usable for phylogeographic inference. We used semiquantitative rank data instead of read abundances to perform AMOVAs and haplotype networks. Genetic variability was mainly concentrated within samples, but with an important between seas component as well. There were intergroup differences in the amount of variability between and within communities in each sea. For two species, the results could be compared with traditional Sanger sequence data available for the same zones, giving similar patterns. Our study shows that metabarcoding data can be used to infer intra‐ and interpopulation genetic variability of many species at a time, providing a new method with great potential for basic biogeography, connectivity and dispersal studies, and for the more applied fields of conservation genetics, invasion genetics, and design of protected areas.

This study was aimed to identification of certain crosses to produce hybrids with higher performance per se can be aided by the determination of simple sequence repeats (SSR), which can improve our understanding of the genetic divergence of maize lines and their classification into different heterotic groups. Variability for each locus was measured using the polymorphism information content (PIC), with an average of 0.55, suggesting that the markers were highly informative. Analysis of the molecular variance (AMOVA) indicated higher divergence among the maize lines, suggesting the existence of different groups. The unweighted pair group method with arithmetic mean analysis (UPGMA) and the three-dimensional principal coordinate analysis (PCoA) revealed seven heterotic groups. Therefore, knowledge on the genetic diversity distribution in these maize inbred lines is essential to determine strategies to exploit heterosis in breeding programs in future studies.

Date palm ( Phoenix dactylifera L.) is a dioecious, clonally propagated crop in which accurate genetic characterization is essential for germplasm management and breeding. This study used 12 SSR loci to quantify genetic diversity and resolve population structure within a sex-stratified Omani collection (Oman female and Oman male accessions), interpreted against a limited international reference panel (IRD) used strictly for contextual comparison. Across groups, SSR loci were highly polymorphic and captured moderate to high diversity, with mean allelic richness ranging from Na = 9.75–12.58 and expected heterozygosity from He = 0.736–0.797. Observed heterozygosity was consistently lower (Ho = 0.596–0.646), yielding positive inbreeding coefficients (Fis = 0.164–0.193). Pairwise differentiation indicated very weak sex-based subdivision within Oman (Fst = 0.021; Nei’s D = 0.143), whereas comparisons between Oman groups and IRD showed higher but still modest differentiation (Fst ≈ 0.057–0.059; D ≈ 0.508–0.534). AMOVA supported this pattern, with 92% of variation within populations and 8% among populations. Multivariate and model-based structure analyses identified clear genetic clustering overall (optimal K = 4), driven primarily by separation involving the IRD panel rather than by sex within Oman. Collectively, these findings demonstrate substantial within-Oman diversity with minimal sex-based structuring, while highlighting measurable divergence between the Omani collection and the contextual IRD reference panel.

Sunflower ( Helianthus annuus L.), known for its adaptability and high yield potential, is vital in global edible oil production. Estimating genetic diversity is a key pre-breeding activity in crop breeding. The current study comprised of 48 genotypes which were assessed for their biometrical traits at department of Oilseeds, Tamil Nadu Agricultural University, during the rainy season of 2022. The lines were subsequently characterised using 103 simple sequence repeat (SSR) markers for molecular diversity analysis. The results indicated that the net nucleotide distances indicated varying genetic divergence, with subpopulations II and V showing the highest (0.056) and I and IV the lowest (0.014). Subpopulation IV exhibited the highest heterozygosity (0.352), while subpopulation III had the lowest heterozygosity and a low Fst (0.173). Principal components analysis (PCA) and hierarchical cluster analysis were employed for assessing the morphological diversity, facilitating genotype grouping and parent selection for breeding programs. The first four components cumulatively accounted for 86.72% of the total variation. Cluster Analysis grouped 48 sunflower genotypes into three clusters based on genetic diversity. COSF 13B stands out for its high head diameter, oil content, seed yield, and oil yield based on mean performance of morphological data. Principal coordinate analysis (PCoA) mirrored the groupings from the Neighbor Joining method, with the first three components explaining 27.24% of the total variation. Molecular data analysis identified five distinct clusters among the germplasm. By integrating morphological and molecular marker data with genetic distance analysis, substantial diversity was revealed with the genotypes RHA 273 and GMU 325 consistently demonstrated high oil yield per plant. The genotypes GMU 477, GMU 450, COSF 13B, RHA 102, CMS 1103B, and RHA GPR 58 have been identified as suitable parents for enhancing oil content in sunflower breeding programs. These findings also aid in selecting SSR markers for genotype characterization and in choosing diverse parents for breeding programs.

Thymus daenensis is an important aromatic and medicinal plant endemic to Iran, with high biological and pharmacological properties. This study aimed to determine the genetic diversity and genetic differentiation pattern of 12 polycross-derived populations comprising 103 half-sib progenies of T. daenensis using inter-simple sequence repeats (ISSR) and start codon targeted (SCoT) markers. Although both marker systems showed a high level of polymorphism, SCoT was more efficient in the detection of polymorphism for this species. The analysis of molecular variance (AMOVA) results of the two marker systems assigned higher genetic variation to progenies within in each population (88%) than among populations (12%). Based on diversity indices, the Arak and Isfahan2 populations exhibited the highest genetic variation. Furthermore, the Mantel test indicated that there were different patterns of polymorphism distribution between the ISSR and SCoT techniques, suggesting their complementary role in DNA fingerprinting of T. daenensis . Results highlight the reliability and informativeness of SCoT markers in assessing the genetic diversity and differentiation of this endangered plant species. In conclusion, the findings of this study provide a foundation for the establishment of more effective breeding and conservative programs for T. daenensis . The use of ISSR and SCoT markers could utilize the available genetic diversity for developing improved Thyme cultivars, and this meets the growing demands for this economically and ecologically important medicinal plant.

China is the world's top producer of chestnuts. Population research through genetic techniques enhances our understanding of genetic diversity and population structure. Simple sequence repeats (SSRs) are the most extensively used markers in population genetics. In the present study, we evaluated the genetic diversity and genetic structure of natural Castanea mollissima populations with specific objectives including evaluating the geographic pattern of genetic diversity of wild Chinese chestnut; identifying spatial population structure and genetic differentiation between geographic locations; and proposing certain Chinese chestnut wild populations as reservoirs of genetic diversity for conservation. SSRs markers provide relevant and precise information on the dissemination of genetic diversity among populations having different categories of evolutionary drivers. Herein, the paper examines the genetic diversity and population structure of Chinese chestnut ( C. mollissima ) using nuclear SSRs. We analyzed 252 samples of C. mollissima from 14 populations and 11 different locations via eight multiplex SSR markers. Maps of genetic diversity parameters (e.g., number of alleles or N A , expected heterozygosity or H E , and private alleles richness or PAr) are generated through geo-statistical Inverse Distance Weighted (IDW) to construct a synthetic map that, in turn, reveals the population from Qinling-Daba Mountains possessed the highest genetic diversity (N A  = 8.3, H E  = 0.73). The analysis of molecular variance (AMOVA) analysis revealed that 89% of the genetic deviation found in C. mollissima exists within individuals and populations as opposed to 11% among different populations. Analysis of the SSRs using STRUCTURE identified five clusters with mixed population genetic structure by geographical location. Our results provide significant insight into the population structure of C. mollissima in China and present geographical locations of different gene pools to support conservation by identifying reservoirs of genetic diversity. These findings provide useful information related to markers, genetic diversity, and population structure of Chinese chestnuts.

Background The shea tree is a well-known carbon sink in Africa that requires a sustainable conservation of its gene pool. However, the genetic structure of its population is not well studied, especially in Côte d’Ivoire. In this study, 333 superior shea tree genotypes conserved in situ in Côte d’Ivoire were collected and genotyped with the aim of investigating its genetic diversity and population structure to facilitate suitable conservation and support future breeding efforts to adapt to climate change effects. Results A total of 7,559 filtered high-quality single nucleotide polymorphisms (SNPs) were identified using the genotyping by sequencing technology. The gene diversity (HE) ranged between 0.1 to 0.5 with an average of 0.26, while the polymorphism information content (PIC) value ranged between 0.1 to 0.5 with an average of 0.24, indicating a moderate genetic diversity among the studied genotypes. The population structure model classified the 333 genotypes into three genetic groups (GP1, GP2, and GP3). GP1 contained shea trees that mainly originated from the Poro, Tchologo, and Hambol districts, while GP2 and GP3 contained shea trees collected from the Bagoué district. Analysis of molecular variance (AMOVA) identified 55% variance within populations and 45% variance within individuals, indicating a very low genetic differentiation (or very high gene exchange) between these three groups ( F ST  = 0.004, gene flow Nm = 59.02). Morphologically, GP1 displayed spreading tree growth habit, oval nut shape, higher mean nut weight (10.62 g), wide leaf (limb width = 4.63 cm), and small trunk size (trunk circumference = 133.4 cm). Meanwhile, GP2 and GP3 showed similar morphological characteristics: erect and spreading tree growth habit, ovoid nut shape, lower mean nut weight (GP2: 8.89 g; GP3: 8.36 g), thin leaf (limb width = 4.45 cm), and large trunk size ( GP2: 160.5 cm, GP3: 149.1 cm). A core set of 100 superior shea trees, representing 30% of the original population size and including individuals from all four study districts, was proposed using the “maximum length sub-tree function” in DARwin v. 6.0.21. Conclusion These findings provide new knowledge of the genetic diversity and population structure of Ivorian shea tree genetic resources for the design of effective collection and conservation strategies for the efficient use of inbreeding.