Dataset Information

Genetic Diversity and Population Structure Analysis of the USDA Olive Germplasm Using Genotyping-By-Sequencing (GBS).

ABSTRACT: Olives are one of the most important fruit and woody oil trees cultivated in many parts of the world. Olive oil is a critical component of the Mediterranean diet due to its importance in heart health. Olives are believed to have been brought to the United States from the Mediterranean countries in the 18th century. Despite the increase in demand and production areas, only a few selected olive varieties are grown in most traditional or new growing regions in the US. By understanding the genetic background, new sources of genetic diversity can be incorporated into the olive breeding programs to develop regionally adapted varieties for the US market. This study aimed to explore the genetic diversity and population structure of 90 olive accessions from the USDA repository along with six popular varieties using genotyping-by-sequencing (GBS)-generated SNP markers. After quality filtering, 54,075 SNP markers were retained for the genetic diversity analysis. The average gene diversity (GD) and polymorphic information content (PIC) values of the SNPs were 0.244 and 0.206, respectively, indicating a moderate genetic diversity for the US olive germplasm evaluated in this study. The structure analysis showed that the USDA collection was distributed across seven subpopulations; 63% of the accessions were grouped into an identifiable subpopulation. The phylogenetic and principal coordinate analysis (PCoA) showed that the subpopulations did not align with the geographical origins or climatic zones. An analysis of the molecular variance revealed that the major genetic variation sources were within populations. These findings provide critical information for future olive breeding programs to select genetically distant parents and facilitate future gene identification using genome-wide association studies (GWAS) or a marker-assisted selection (MAS) to develop varieties suited to production in the US.

SUBMITTER: Islam ASMF

PROVIDER: S-EPMC8701156 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Sophora moorcroftiana is a perennial leguminous low shrub endemic to the Yarlung Zangbo River basin in Tibet with irreplaceable economic and ecological value. To determine the drivers of evolution in this species, 225 individuals belonging to 15 populations from different geographic locations were sampled, and population genetics was studied using high-throughput genotyping-by-sequencing (GBS). Based on genetic diversity analysis, phylogenetic analysis, principal component analysis, and structure analysis, 15 natural populations were clustered into the following five subgroups: subgroup I (Shigatse subgroup) was located in the upper reaches of the Yarlung Zangbo River with a relatively high level of population genetic variation (means for PIC, Shannon and PI were 0.173, 0.326 and 0.0000305, respectively), and gene flow within the subgroup was also high (mean value for Nm was 4.67). Subgroup II (including Pop 7 and Pop 8; means for PIC, Shannon and PI were 0.182, 0.345 and 0.0000321, respectively), located in the middle reaches of the Yarlung Zangbo River had relatively high levels of gene flow with the populations distributed in the upper and lower reaches. The Nm between subgroup II with subgroups I and III was 3.271 and 2.894, respectively. Considering all the genetic diversity indices Pop 8 had relatively high genetic diversity. Subgroup III (the remaining mixed subgroup of Lhasa and Shannan) was located in the middle reaches of the Yarlung Zangbo River and the means for PIC, Shannon and PI were 0.172, 0.324 and 0.0000303, respectively. Subgroup IV (Nyingchi subgroup), located in the lower reaches of the Yarlung Zangbo River basin, showed a further genetic distance from the other subgroups and the means for PIC, Shannon and PI were 0.147, 0.277 and 0.0000263, respectively. Subgroup V (Nyingchi Gongbu Jiangda subgroup), located in the upper reaches of the Niyang River, had the lowest level of genetic variation (means for PIC, Shannon and PI were 0.106, 0.198 and 0.0000187, respectively) and gene flow with other populations (mean value for Nm was 0.42). According to the comprehensive analysis, the S. moorcroftiana populations generally expanded from upstream to downstream and displayed a high level of genetic differentiation in the populations in the upper and lower reaches. There were high levels of gene exchange between the central populations with upstream and downstream populations, and wind-induced seed dispersal was an important factor in the formation of this gene exchange mode.

Project description:BACKGROUND:Yams (Dioscorea spp.) are economically important food for millions of people in the humid and sub-humid tropics. Dioscorea dumetorum (Kunth) is the most nutritious among the eight-yam species, commonly grown and consumed in West and Central Africa. Despite these qualities, the storage ability of D. dumetorum is restricted by severe postharvest hardening of the tubers that can be addressed through concerted breeding efforts. The first step of any breeding program is bound to the study of genetic diversity. In this study, we used the Genotyping-By-Sequencing of Single Nucleotide Polymorphism (GBS-SNP) to investigate the genetic diversity and population structure of 44 accessions of D. dumetorum in Cameroon. Ploidy was inferred using flow cytometry and gbs2ploidy. RESULTS:We obtained on average 6371 loci having at least information for 75% accessions. Based on 6457 unlinked SNPs, our results demonstrate that D. dumetorum is structured into four populations. We clearly identified, a western/north-western, a western, and south-western populations, suggesting that altitude and farmers-consumers preference are the decisive factors for differential adaptation and separation of these populations. Bayesian and neighbor-joining clustering detected the highest genetic variability in D. dumetorum accessions from the south-western region. This variation is likely due to larger breeding efforts in the region as shown by gene flow between D. dumetorum accessions from the south-western region inferred by maximum likelihood. Ploidy analysis revealed diploid and triploid levels in D. dumetorum accessions with mostly diploid accessions (77%). Male and female accessions were mostly triploid (75%) and diploid (69%), respectively. The 1C genome size values of D. dumetorum accessions were on average 0.333?±?0.009?pg and 0.519?±?0.004?pg for diploids and triploids, respectively. CONCLUSIONS:Germplasm characterization, population structure and ploidy are an essential basic information in a breeding program as well as for conservation of intraspecific diversity. Thus, results obtained in this study provide valuable information for the improvement and conservation of D. dumetorum. Moreover, GBS appears as an efficient powerful tool to detect intraspecific variation.

Project description:Sweetpotato (Ipomoea batatas) is the sixth most important food crop and plays a critical role in maintaining food security worldwide. Support for sweetpotato improvement research in breeding and genetics programs, and maintenance of sweetpotato germplasm collections is essential for preserving food security for future generations. Germplasm collections seek to preserve phenotypic and genotypic diversity through accession characterization. However, due to its genetic complexity, high heterogeneity, polyploid genome, phenotypic plasticity, and high flower production variability, sweetpotato genetic characterization is challenging. Here, we characterize the genetic diversity and population structure of 604 accessions from the sweetpotato germplasm collection maintained by the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Plant Genetic Resources Conservation Unit (PGRCU) in Griffin, Georgia, United States. Using the genotyping-by-sequencing platform (GBSpoly) and bioinformatic pipelines (ngsComposer and GBSapp), a total of 102,870 polymorphic SNPs with hexaploid dosage calls were identified from the 604 accessions. Discriminant analysis of principal components (DAPC) and Bayesian clustering identified six unique genetic groupings across seven broad geographic regions. Genetic diversity analyses using the hexaploid data set revealed ample genetic diversity among the analyzed collection in concordance with previous analyses. Following population structure and diversity analyses, breeder germplasm subsets of 24, 48, 96, and 384 accessions were established using K-means clustering with manual selection to maintain phenotypic and genotypic diversity. The genetic characterization of the PGRCU sweetpotato germplasm collection and breeder germplasm subsets developed in this study provide the foundation for future association studies and serve as precursors toward phenotyping studies aimed at linking genotype with phenotype.

Project description:Palmer amaranth (Amaranthus palmeri) is a major weed in United States cotton and soybean production systems. Originally native to the Southwest, the species has spread throughout the country. In 2004 a population of A. palmeri was identified with resistance to glyphosate, a herbicide heavily relied on in modern no-tillage and transgenic glyphosate-resistant (GR) crop systems. This project aims to determine the degree of genetic relatedness among eight different populations of GR and glyphosate-susceptible (GS) A. palmeri from various geographic regions in the United States by analyzing patterns of phylogeography and diversity to ascertain whether resistance evolved independently or spread from outside to an Arizona locality (AZ-R). Shikimic acid accumulation and EPSPS genomic copy assays confirmed resistance or susceptibility. With a set of 1,351 single nucleotide polymorphisms (SNPs), discovered by genotyping-by-sequencing (GBS), UPGMA phylogenetic analysis, principal component analysis, Bayesian model-based clustering, and pairwise comparisons of genetic distances were conducted. A GR population from Tennessee and two GS populations from Georgia and Arizona were identified as genetically distinct while the remaining GS populations from Kansas, Arizona, and Nebraska clustered together with two GR populations from Arizona and Georgia. Within the latter group, AZ-R was most closely related to the GS populations from Kansas and Arizona followed by the GR population from Georgia. GR populations from Georgia and Tennessee were genetically distinct from each other. No isolation by distance was detected and A. palmeri was revealed to be a species with high genetic diversity. The data suggest the following two possible scenarios: either glyphosate resistance was introduced to the Arizona locality from the east, or resistance evolved independently in Arizona. Glyphosate resistance in the Georgia and Tennessee localities most likely evolved separately. Thus, modern farmers need to continue to diversify weed management practices and prevent seed dispersal to mitigate herbicide resistance evolution in A. palmeri.

Project description:Phenotypic evaluation and efficient utilization of germplasm collections can be time-intensive, laborious, and expensive. However, with the plummeting costs of next-generation sequencing and the addition of genomic selection to the plant breeder's toolbox, we now can more efficiently tap the genetic diversity within large germplasm collections. In this study, we applied and evaluated genomic prediction's potential to a set of 482 pea (Pisum sativum L.) accessions-genotyped with 30,600 single nucleotide polymorphic (SNP) markers and phenotyped for seed yield and yield-related components-for enhancing selection of accessions from the USDA Pea Germplasm Collection. Genomic prediction models and several factors affecting predictive ability were evaluated in a series of cross-validation schemes across complex traits. Different genomic prediction models gave similar results, with predictive ability across traits ranging from 0.23 to 0.60, with no model working best across all traits. Increasing the training population size improved the predictive ability of most traits, including seed yield. Predictive abilities increased and reached a plateau with increasing number of markers presumably due to extensive linkage disequilibrium in the pea genome. Accounting for population structure effects did not significantly boost predictive ability, but we observed a slight improvement in seed yield. By applying the best genomic prediction model (e.g., RR-BLUP), we then examined the distribution of genotyped but nonphenotyped accessions and the reliability of genomic estimated breeding values (GEBV). The distribution of GEBV suggested that none of the nonphenotyped accessions were expected to perform outside the range of the phenotyped accessions. Desirable breeding values with higher reliability can be used to identify and screen favorable germplasm accessions. Expanding the training set and incorporating additional orthogonal information (e.g., transcriptomics, metabolomics, physiological traits, etc.) into the genomic prediction framework can enhance prediction accuracy.

Dataset Information

Genetic Diversity and Population Structure Analysis of the USDA Olive Germplasm Using Genotyping-By-Sequencing (GBS).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets