Population structure and genetic diversity of Brachiaria grass (Urochloa spp.) accessions from the Democratic Republic of Congo using DArTseq single nucleotide polymorphism markers

Tetracentron sinense Oliv. (T. sinense), as a tertiary living fossil, has experienced a significant decline in population numbers. Currently, genetic resources depletion and human activities have led to habitat fragmentation of relict and endangered plants, despite the abundant evidence of its medicinal, economic, and ecological value. Conservation strategies were clarified and evaluated based on the genetic structure characteristics and diversity patterns among 25 wild populations using Restriction site-associated DNA sequencing (RAD-seq) technology. Through SNP calling, filtering, genetic diversity analysis, discriminant analysis of principal components (DAPC), maximum-likelihood phylogenetic tree, and ADMIXTURE clustering, significant population structure and differentiation were identified. The results revealed a total of 2,169 single nucleotide polymorphisms (SNPs), indicating lower genetic variation but higher genetic differentiation (He: 0.10, I: 0.16, Fst: 0.33). Analysis of molecular variance (AMOVA) showed that genetic variation within populations accounted for 77% of the total variance. DAPC, maximum-likelihood phylogenetic tree, and ADMIXTURE clustering analysis grouped the 25 populations into five distinct clades influenced by isolation, restricted gene flow, and complex topography. To preserve the genetic integrity of T. sinense, it is recommended to establish conservation units corresponding to different geographic clades, with a focus on populations with low/high genetic diversity by implementing artificial reproduction and germplasm resource nurseries. Given the species' vulnerable conservation status, urgent implementation of the aforementioned conservation strategies is necessary to safeguard the remaining genetic resources.

Tetracentron sinense Oliv. (T. sinense), as a tertiary living fossil, has experienced a significant decline in population numbers. Currently, genetic resources depletion and human activities have led to habitat fragmentation of relict and endangered plants, despite the abundant evidence of its medicinal, economic, and ecological value. Conservation strategies were clarified and evaluated based on the genetic structure characteristics and diversity patterns among 25 wild populations using Restriction site-associated DNA sequencing (RAD-seq) technology. Through SNP calling, filtering, genetic diversity analysis, discriminant analysis of principal components (DAPC), maximum-likelihood phylogenetic tree, and ADMIXTURE clustering, significant population structure and differentiation were identified. The results revealed a total of 2,169 single nucleotide polymorphisms (SNPs), indicating lower genetic variation but higher genetic differentiation (He: 0.10, I: 0.16, Fst: 0.33). Analysis of molecular variance (AMOVA) showed that genetic variation within populations accounted for 77% of the total variance. DAPC, maximum-likelihood phylogenetic tree, and ADMIXTURE clustering analysis grouped the 25 populations into five distinct clades influenced by isolation, restricted gene flow, and complex topography. To preserve the genetic integrity of T. sinense, it is recommended to establish conservation units corresponding to different geographic clades, with a focus on populations with low/high genetic diversity by implementing artificial reproduction and germplasm resource nurseries. Given the species' vulnerable conservation status, urgent implementation of the aforementioned conservation strategies is necessary to safeguard the remaining genetic resources.

Understanding the genetic diversity and population structure of rice is crucial for breeding programs, conservation efforts, and the development of sustainable agricultural practices. This study aimed to assess the genetic diversity and population structure of 94 rice (Oryza sativa L.) genotypes from the Democratic Republic of Congo using a set of 8389 high-quality DArTseq-based single nucleotide polymorphism (SNP) markers. The average polymorphic information content (PIC) of the markers was 0.25. About 42.4% of the SNPs had a PIC value between 0.25 and 0.5, which were moderately informative. The ADMIXTURE program was used for structure analysis, which revealed five sub-populations (K = 5), with admixtures. In principal component analysis (PCA), the first three principal components accounted for 36.3% of the total variation. Analysis of molecular variance revealed significant variation between sub-populations (36.09%) and within genotypes (34.04%). The low overall number of migrants (Nm = 0.23) and high fixation index (Fst = 0.52) indicated limited gene flow and significant differentiation between the sub-populations. Observed heterozygosity (Ho = 0.08) was lower than expected heterozygosity (He = 0.14) because of the high inbreeding (Fis = 0.52) nature of rice. A high average Euclidean genetic distance (0.87) revealed the existence of genetic diversity among the 94 genotypes. The significant genetic diversity among the evaluated rice genotypes can be further explored to obtain potentially desirable genes for rice improvement.

Landraces are considered a valuable source of potential genetic diversity that could be used in the selection process in any plant breeding program. Here, we assembled a population of 600 bread wheat landraces collected from eight different countries, conserved at the ICARDA's genebank, and evaluated the genetic diversity and the population structure of the landraces using single nucleotide polymorphism (SNP) markers. A total of 11,830 high-quality SNPs distributed across the genomes A (40.5%), B (45.9%), and D (13.6%) were used for the final analysis. The population structure analysis was evaluated using the model-based method (STRUCTURE) and distance-based methods [discriminant analysis of principal components (DAPC) and principal component analysis (PCA)]. The STRUCTURE method grouped the landraces into two major clusters, with the landraces from Syria and Turkey forming two clusters with high proportions of admixture, whereas the DAPC and PCA analysis grouped the population into three subpopulations mostly according to the geographical information of the landraces, i.e., Syria, Iran, and Turkey with admixture. The analysis of molecular variance revealed that the majority of the variation was due to genetic differences within the populations as compared with between subpopulations, and it was the same for both the cluster-based and distance-based methods. Genetic distance analysis was also studied to estimate the differences between the landraces from different countries, and it was observed that the maximum genetic distance (0.389) was between the landraces from Spain and Palestine, whereas the minimum genetic distance (0.013) was observed between the landraces from Syria and Turkey. It was concluded from the study that the model-based methods (DAPC and PCA) could dissect the population structure more precisely when compared with the STRUCTURE method. The population structure and genetic diversity analysis of the bread wheat landraces presented here highlight the complex genetic architecture of the landraces native to the Fertile Crescent region. The results of this study provide useful information for the genetic improvement of hexaploid wheat and facilitate the use of landraces in wheat breeding programs.

Decision letter: Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates

The success of plant biofuels relies on finding inexpensive feedstocks that do not compete with food crops and can be cultivated economically in diverse geographical regions and agricultural production systems. Brassica juncea L. is a native crop of the western and central Asia, is considered a good biodiesel candidate due to its high oil content with high unsaturated fatty acids that can be refined into biofuels that equal petroleum-based fuels characteristics. To build genomic resources for B.juncea, a diversity panel consisting of 340 of accessions, were collected from 22 countries and stored at the USDA repository, and were genotyped to explore genetic diversity, relatedness, and population structure. A total of 99030 high-quality single nucleotide polymorphisms (SNP) markers were identified using genotyping-by-sequencing (GBS) technology. Those SNP were distributed over the 18 chromosomes with an average of 5000 SNP per chromosome, an average polymorphism information content (PIC) value of 0.23 and an expected heterozygosity (He) value of 0.281 indicating the genetic diversity within the USDA collection of B. juncea. Population structure and principal components analyses (PCA) based on identified SNPs revealed five distinct subpopulations, with the largest subpopulation containing accessions traced back to Pakistan and India. Analysis of molecular variance (AMOVA) revealed that 40% of the variation in USDA collection was among the five subpopulations, while 49% of the variation was due to the variation among accessions used in the analysis. High fixation index (FST) among distinguished subpopulations indicates a wide genetic diversity and high genetic differentiation among subpopulations. The results explored the genetic diversity in the USDA collection of B. juncea that could be used to genetically improve the crop. This information and accessions provide tools to enhance genetic gain in B. juncea breeding programs through genome-wide association analysis studies (GWAS) and marker-assisted selection (MAS) approaches.

Assessing the genetic diversity of yam germplasm from different geographical origins for cultivation and breeding purposes is an essential step for crop genetic resource conservation and genetic improvement, especially where the crop faces minimal attention. This study aimed to classify the population structure, and assess the extent of genetic diversity in 207 Dioscorea rotundata genotypes sourced from three different geographical origins. A total of 4,957 (16.2%) single nucleotide polymorphism markers were used to assess genetic diversity. The SNP markers were informative, with polymorphic information content ranging from 0.238 to 0.288 and a mean of 0.260 across all the genotypes. The observed and expected heterozygosity was 0.12 and 0.23, respectively while the minor allele frequency ranged from 0.093 to 0.124 with a mean of 0.109. The principal coordinate analysis, model-based structure and discriminant analysis of principal components, and the Euclidean distance matrix method grouped 207 yam genotypes into three main clusters. Genotypes from West Africa (Ghana and Nigeria) had significant similarities with those from Uganda. Analysis of molecular variance revealed that within-population variation across three different geographical origins accounted for 93% of the observed variation. This study, therefore, showed that yam improvement in Uganda is possible, and the outcome will constitute a foundation for the genetic improvement of yams in Uganda.

Assessing the genetic diversity of yam germplasm from different geographical origins for cultivation and breeding purposes is an essential step for crop genetic resource conservation and genetic improvement, especially where the crop faces minimal attention. This study aimed to classify the population structure, and assess the extent of genetic diversity in 207 Dioscorea rotundata genotypes sourced from three different geographical origins. A total of 4,957 (16.2%) single nucleotide polymorphism markers were used to assess genetic diversity. The SNP markers were informative, with polymorphic information content ranging from 0.238 to 0.288 and a mean of 0.260 across all the genotypes. The observed and expected heterozygosity was 0.12 and 0.23, respectively while the minor allele frequency ranged from 0.093 to 0.124 with a mean of 0.109. The principal coordinate analysis, model-based structure and discriminant analysis of principal components, and the Euclidean distance matrix method grouped 207 yam genotypes into three main clusters. Genotypes from West Africa (Ghana and Nigeria) had significant similarities with those from Uganda. Analysis of molecular variance revealed that within-population variation across three different geographical origins accounted for 93% of the observed variation. This study, therefore, showed that yam improvement in Uganda is possible, and the outcome will constitute a foundation for the genetic improvement of yams in Uganda.

Watermelon is an economically important vegetable fruit worldwide. The objective of this study was to conduct a genetic diversity of 68 watermelon accessions using single nucleotide polymorphisms (SNPs). Genotyping by sequencing (GBS) was used to discover SNPs and assess genetic diversity and population structure using STRUCTURE and discriminant analysis of principal components (DAPC) in watermelon accessions. Two groups of watermelons were used: 1) highly utilized 41 watermelon accessions at the National Agrobiodiversity Center (NAC) at the Rural Development Administration in South Korea; and 2) 27 Korean commercial watermelons. Results revealed the presence of four clusters within the populations differentiated principally based on seed companies. In addition, there was higher genetic differentiation among commercial watermelons of each company. It is hypothesized that the results obtained from this study would contribute towards the expansion of this crop as well as providing data about genetic diversity, which would be useful for the preservation of genetic resources or for future breeding programs.

Sesame, Sesamum indicum L., is one of the oldest domesticated crops used for its oil and protein in many parts of the world. To build genomic resources for sesame that could be used to improve sesame productivity and responses to stresses, a USDA sesame germplasm collection of 501 accessions originating from 36 countries was used in this study. The panel was genotyped using genotyping-by-sequencing (GBS) technology to explore its genetic diversity and population structure and the relatedness among its accessions. A total of 24,735 high-quality single-nucleotide polymorphism (SNP) markers were identified over the 13 chromosomes. The marker density was 1900 SNP per chromosome, with an average polymorphism information content (PIC) value of 0.267. The marker polymorphisms and heterozygosity estimators indicated the usefulness of the identified SNPs to be used in future genetic studies and breeding activities. The population structure, principal components analysis (PCA), and unrooted neighbor-joining phylogenetic tree analyses classified two distinct subpopulations, indicating a wide genetic diversity within the USDA sesame collection. Analysis of molecular variance (AMOVA) revealed that 29.5% of the variation in this population was due to subpopulations, while 57.5% of the variation was due to variation among the accessions within the subpopulations. These results showed the degree of differentiation between the two subpopulations as well as within each subpopulation. The high fixation index (FST) between the distinguished subpopulations indicates a wide genetic diversity and high genetic differentiation among and within the identified subpopulations. The linkage disequilibrium (LD) pattern averaged 161 Kbp for the whole sesame genome, while the LD decay ranged from 168 Kbp at chromosome LG09 to 123 Kbp in chromosome LG05. These findings could explain the complications of linkage drag among the traits during selections. The selected accessions and genotyped SNPs provide tools to enhance genetic gain in sesame breeding programs through molecular approaches.

BackgroundThe consumption of oats has rapidly increased due to their exceptional nutritional value. However, concerns over genetic erosion have emerged as oat breeding programs rely on a highly limited genetic pool. This study aimed to expand the genetic diversity pool of oats by collecting wild oat (Avena fatua L.) populations in South Korea and assessing their genetic diversity and seed storage protein patterns.ResultsA total of 237 A. fatua individuals were collected in 2022 from eight regions in the southwestern coastal areas of South Korea. Genetic diversity and seed storage protein patterns were analyzed using genotyping-by-sequencing (GBS) and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The GBS analysis identified 20,836 single-nucleotide polymorphisms (SNPs). An analysis of molecular variance (AMOVA) based on regional populations revealed that 40.9% of the genetic variation was attributed to differences among populations, while 59.1% was within populations, indicating high genetic differentiation within regional populations. Subsequent population structure analysis and discriminant analysis of principal components (DAPC) both stated the formation of two distinct genetic groups, with an AMOVA value of 70.9% between the groups, suggesting a high level of genetic variation. Pairwise FST analysis was conducted to compare the genetic differentiation between two populations, revealing that Jindo and Jangheung exhibited the highest level of genetic differentiation (FST = 0.795) among the geographic groups. Seed storage proteins were analyzed using SDS-PAGE, and the patterns were grouped using k-means clustering. A comparison between the groups based on protein patterns and those based on genetic variation revealed no significant correlation.ConclusionThis study provides data on the genetic diversity of A. fatua, a wild relative of cultivated oats, aimed at expanding the genetic pool of oats for future breeding programs. These findings are expected to be a foundational resource for oat breeding and genetic improvement efforts.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12870-025-07315-x.

Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.

Tamarix chinensis Lour. is a 3-6-meter-tall small tree with high salt- and alkali- tolerance and aggressive invasiveness, mainly distributed in the eastern part of China in warm-temperate and subtropical climate zones, yet there is little information available regarding genetic diversity and population structure. A total of 204 individuals of nine T. chinensis populations were investigated for genetic diversity and population structure using a set of 12 highly polymorphic microsatellite markers. The total number of alleles detected was 162, the average number of effective allele was 4.607, the average polymorphism information content (PIC) value of the 12 loci was 0.685, and the mean observed heterozygosity (Ho) and the mean expected heterozygosity (He) was 0.653 and 0.711, respectively. Analysis of molecular variance (AMOVA) showed a 5.32% genetic variation among T. chinensis populations. Despite a low population differentiation, Bayesian clustering analysis, discriminant analysis of principal components (DAPC) and the unweighted pair group method with arithmetic mean (UPGMA) clearly identified three genetic clusters correlated to the populations' geographic origin: the northern populations including those from Yellow River Delta, the Fangshan (FS) population from Beijing, the Changyi (CY) population from Bohai Bay, the Huanjiabu (HHJ) population from Hangzhou Bay, and the remaining two populations from Hangzhou Bay. There was a significant relationship between the genetic distance and geographical distance of the paired populations. Gene flow (Nm) was 4.254 estimated from FST. T. chinensis possessed high genetic diversity comparable to tree species, and although the population differentiation is shallow, our results classified the sampled populations according to sampling localities, suggesting the different origins of the study populations.

Brazil is among the largest producers and consumers of common bean (Phaseolus vulgaris L.) and can be considered a secondary center of diversity for the species. The aim of this study was to estimate the genetic diversity, population structure, and relationships among 288 common bean accessions in an American Diversity Panel (ADP) genotyped with 4,042 high-quality single nucleotide polymorphisms (SNPs). The results showed inter-gene pool hybridization (hybrids) between the two main gene pools (i.e., Mesoamerican and Andean), based on principal component analysis (PCA), discriminant analysis of principal components (DAPC), and STRUCTURE analysis. The genetic diversity parameters showed that the Mesoamerican group has higher values of diversity and allelic richness in comparison with the Andean group. Considering the optimal clusters (K), clustering was performed according to the type of grain (i.e., market group), the institution of origin, the period of release, and agronomic traits. A new subset was selected and named the Mesoamerican Diversity Panel (MDP), with 205 Mesoamerican accessions. Analysis of molecular variance (AMOVA) showed low genetic variance between the two panels (i.e., ADP and MDP) with the highest percentage of the limited variance among accessions in each group. The ADP showed occurrence of high genetic differentiation between populations (i.e., Mesoamerican and Andean) and introgression between gene pools in hybrids based on a set of diagnostic SNPs. The MDP showed better linkage disequilibrium (LD) decay. The availability of genetic variation from inter-gene pool hybridizations presents a potential opportunity for breeders towards the development of superior common bean cultivars.

Knowledge about genetic diversity and population structure among goat populations is essential for understanding environmental adaptation and fostering efficient utilization, development, and conservation of goat breeds. Uganda's indigenous goats exist in three phenotypic groups: Mubende, Kigezi, and Small East African. However, a limited understanding of their genetic attributes and population structure hinders the development and sustainable utilization of the goats. Using the Goat Illumina 60k chip International Goat Genome Consortium V2, the whole-genome data for 1,021 indigenous goats sourced from 10 agroecological zones in Uganda were analyzed for genetic diversity and population structure. A total of 49,337 (82.6%) single-nucleotide polymorphism markers were aligned to the ARS-1 goat genome and used to assess the genetic diversity, population structure, and kinship relationships of Uganda's indigenous goats. Moderate genetic diversity was observed. The observed and expected heterozygosities were 0.378 and 0.383, the average genetic distance was 0.390, and the average minor allele frequency was 0.30. The average inbreeding coefficient (Fis) was 0.014, and the average fixation index (Fst) was 0.016. Principal component analysis, admixture analysis, and discriminant analysis of principal components grouped the 1,021 goat genotypes into three genetically distinct populations that did not conform to the known phenotypic populations but varied across environmental conditions. Population 1, comprising Mubende (90%) and Kigezi (8.1%) goats, is located in southwest and central Uganda, a warm and humid environment. Population 2, which is 59% Mubende and 49% Small East African goats, is located along the Nile Delta in northwestern Uganda and around the Albertine region, a hot and humid savannah grassland. Population 3, comprising 78.4% Small East African and 21.1% Mubende goats, is found in northeastern to eastern Uganda, a hot and dry Commiphora woodlands. Genetic diversity and population structure information from this study will be a basis for future development, conservation, and sustainable utilization of Uganda's goat genetic resources.