Dataset Information

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections.

ABSTRACT: Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A mixed genotyping strategy was implemented, by combining proprietary genotyping-by-sequencing data with public whole-genome-sequencing data, to generate an integrative 11,834-common single nucleotide polymorphism matrix including the three breeding collections. In general, the GD estimates obtained were moderate. An analysis of molecular variance provided evidence of population structure between breeding collections. However, the optimal number of subpopulations, studied via discriminant analysis of principal components (K = 12), the bayesian STRUCTURE algorithm (K = 6) and distance-based methods (K = 9) remains unclear, since no single unifying characteristic is apparent for any of the inferred groups. Different overall patterns of linkage disequilibrium (LD) were observed across chromosomes, with Chr10, Chr17, Chr5, and Chr2 showing the highest LD. This work represents the largest and most comprehensive inter-breeding collection analysis of genomic diversity for cultivated sunflower conducted to date.

SUBMITTER: Filippi CV

PROVIDER: S-EPMC7140877 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections.

Filippi Carla V CV Merino Gabriela A GA Montecchia Juan F JF Aguirre Natalia C NC Rivarola Máximo M Naamati Guy G Fass Mónica I MI Álvarez Daniel D Di Rienzo Julio J Heinz Ruth A RA Contreras Moreira Bruno B Lia Verónica V VV Paniego Norma B NB

Genes 20200306 3

Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A ...[more]

PMID: 32155892

Similar Datasets

Project description:BackgroundPeach (Prunus persica (L.) Batsch) is one of the most important model fruits in the Rosaceae family. Native to the west of China, where peach has been domesticated for more than 4,000 years, its cultivation spread from China to Persia, Mediterranean countries and to America. Chinese peach has had a major impact on international peach breeding programs due to its high genetic diversity. In this research, we used 48 highly polymorphic SSRs, distributed over the peach genome, to investigate the difference in genetic diversity, and linkage disequilibrium (LD) among Chinese cultivars, and North American and European cultivars, and the evolution of current peach cultivars.ResultsIn total, 588 alleles were obtained with 48 SSRs on 653 peach accessions, giving an average of 12.25 alleles per locus. In general, the average value of observed heterozygosity (0.47) was lower than the expected heterozygosity (0.60). The separate analysis of groups of accessions according to their origin or reproductive strategies showed greater variability in Oriental cultivars, mainly due to the high level of heterozygosity in Chinese landraces. Genetic distance analysis clustered the cultivars into two main groups: one included four wild related Prunus, and the other included most of the Oriental and Occidental landraces and breeding cultivars. STRUCTURE analysis assigned 469 accessions to three subpopulations: Oriental (234), Occidental (174), and Landraces (61). Nested STRUCTURE analysis divided the Oriental subpopulation into two different subpopulations: 'Yu Lu' and 'Hakuho'. The Occidental breeding subpopulation was also subdivided into nectarine and peach subpopulations. Linkage disequilibrium (LD) analysis in each of these subpopulations showed that the percentage of linked (r2 > 0.1) intra-chromosome comparisons ranged between 14% and 47%. LD decayed faster in Oriental (1,196 Kbp) than in Occidental (2,687 Kbp) samples. In the 'Yu Lu' subpopulation there was considerable LD extension while no variation of LD with physical distance was observed in the landraces. From the first STRUCTURE result, LG1 had the greatest proportion of alleles in LD within all three subpopulations.ConclusionsOur study demonstrates a high level of genetic diversity and relatively fast decay of LD in the Oriental peach breeding program. Inclusion of Chinese landraces will have a greater effect on increasing genetic diversity in Occidental breeding programs. Fingerprinting with genotype data for all 658 cultivars will be used for accession management in different germplasms. A higher density of markers are needed for association mapping in Oriental germplasm due to the low extension of LD. Population structure and evaluation of LD provides valuable information for GWAS experiment design in peach.

Project description:Profiling the genetic composition and relationships among groundnut germplasm collections is essential for the breeding of new cultivars. The objectives of this study were to assess the genetic diversity and population structure among 100 improved groundnut genotypes using agronomic traits and high-density single nucleotide polymorphism (SNP) markers. The genotypes were evaluated for agronomic traits and drought tolerance at the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT)/India across two seasons. Ninety-nine of the test genotypes were profiled with 16363 SNP markers. Pod yield per plant (PY), seed yield per plant (SY), and harvest index (HI) were significantly (p < 0.05) affected by genotype × environment interaction effects. Genotypes ICGV 07222, ICGV 06040, ICGV 01260, ICGV 15083, ICGV 10143, ICGV 03042, ICGV 06039, ICGV 14001, ICGV 11380, and ICGV 13200 ranked top in terms of pod yield under both drought-stressed and optimum conditions. PY exhibited a significant (p ≤ 0.05) correlation with SY, HI, and total biomass (TBM) under both test conditions. Based on the principal component (PC) analysis, PY, SY, HSW, shelling percentage (SHP), and HI were allocated in PC 1 and contributed to the maximum variability for yield under the two water regimes. Hence, selecting these traits could be successful for screening groundnut genotypes under drought-stressed and optimum conditions. The model-based population structure analysis grouped the studied genotypes into three sub-populations. Dendrogram for phenotypic and genotypic also grouped the studied 99 genotypes into three heterogeneous clusters. Analysis of molecular variance revealed that 98% of the total genetic variation was attributed to individuals, while only 2% of the total variance was due to variation among the subspecies. The genetic distance between the Spanish bunch and Virginia bunch types ranged from 0.11 to 0.52. The genotypes ICGV 13189, ICGV 95111, ICGV 14421, and ICGV 171007 were selected for further breeding based on their wide genetic divergence. Data presented in this study will guide groundnut cultivar development emphasizing economic traits and adaptation to water-limited agro-ecologies, including in Ethiopia.

Project description:BackgroundWheat (Triticum aestivium L.) is an important crop globally which has a complex genome. To identify the parents with useful agronomic characteristics that could be used in the various breeding programs, it is very important to understand the genetic diversity among global wheat genotypes. Also, understanding the genetic diversity is useful in breeding studies such as marker-assisted selection (MAS), genome-wide association studies (GWAS), and genomic selection.ResultsTo understand the genetic diversity in wheat, a set of 103 spring wheat genotypes which represented five different continents were used. These genotypes were genotyped using 36,720 genotyping-by-sequencing derived SNPs (GBS-SNPs) which were well distributed across wheat chromosomes. The tested 103-wheat genotypes contained three different subpopulations based on population structure, principle coordinate, and kinship analyses. A significant variation was found within and among the subpopulations based on the AMOVA. Subpopulation 1 was found to be the more diverse subpopulation based on the different allelic patterns (Na, Ne, I, h, and uh). No high linkage disequilibrium was found between the 36,720 SNPs. However, based on the genomic level, D genome was found to have the highest LD compared with the two other genomes A and B. The ratio between the number of significant LD/number of non-significant LD suggested that chromosomes 2D, 5A, and 7B are the highest LD chromosomes in their genomes with a value of 0.08, 0.07, and 0.05, respectively. Based on the LD decay, the D genome was found to be the lowest genome with the highest number of haplotype blocks on chromosome 2D.ConclusionThe recent study concluded that the 103-spring wheat genotypes and their GBS-SNP markers are very appropriate for GWAS studies and QTL-mapping. The core collection comprises three different subpopulations. Genotypes in subpopulation 1 are the most diverse genotypes and could be used in future breeding programs if they have desired traits. The distribution of LD hotspots across the genome was investigated which provides useful information on the genomic regions that includes interesting genes.

Project description:BackgroundDue to the recent domestication of peanut from a single tetraploidization event, relatively little genetic diversity underlies the extensive morphological and agronomic diversity in peanut cultivars today. To broaden the genetic variation in future breeding programs, it is necessary to characterize germplasm accessions for new sources of variation and to leverage the power of genome-wide association studies (GWAS) to discover markers associated with traits of interest. We report an analysis of linkage disequilibrium (LD), population structure, and genetic diversity, and examine the ability of GWA to infer marker-trait associations in the U.S. peanut mini core collection genotyped with a 58 K SNP array.ResultsLD persists over long distances in the collection, decaying to r2 = half decay distance at 3.78 Mb. Structure within the collection is best explained when separated into four or five groups (K = 4 and K = 5). At K = 4 and 5, accessions loosely clustered according to market type and subspecies, though with numerous exceptions. Out of 107 accessions, 43 clustered in correspondence to the main market type subgroup whereas 34 did not. The remaining 30 accessions had either missing taxonomic classification or were classified as mixed. Phylogenetic network analysis also clustered accessions into approximately five groups based on their genotypes, with loose correspondence to subspecies and market type. Genome wide association analysis was performed on these lines for 12 seed composition and quality traits. Significant marker associations were identified for arachidic and behenic fatty acid compositions, which despite having low bioavailability in peanut, have been reported to raise cholesterol levels in humans. Other traits such as blanchability showed consistent associations in multiple tests, with plausible candidate genes.ConclusionsBased on GWA, population structure as well as additional simulation results, we find that the primary limitations of this collection for GWAS are a small collection size, significant remaining structure/genetic similarity and long LD blocks that limit the resolution of association mapping. These results can be used to improve GWAS in peanut in future studies - for example, by increasing the size and reducing structure in the collections used for GWAS.

Dataset Information

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections.

Publications

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets