In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology

Hassani, Seyed Mohammad Reza; Talebi, Reza; Pourdad, S. S.; Naji, Amir Mohammad; Fayaz, Farzad

doi:10.1007/s11033-020-05312-x

Cited by 28 publications

(27 citation statements)

References 46 publications

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“…All four populations clustered accessions from Turkey. Our results are strongly supported by Hassani et al [29] as they observed that safflower accessions from the Asian continent like Pakistan, Iran, Turkey, and India were found genetically similar and grouped into the same cluster. Clustering of the safflower accessions originating from the Mediterranean region to other localities suggested the distribution of safflower accessions from the Mediterranean region to other geographies.…”

Section: Genetic Structure and Diversity In Safflower Panelsupporting

confidence: 89%

“…A total of 91% of the genetic diversity was present within country group (Table 4). This is supported by Hassani et al [29], where the majority of genetic variation among accessions within populations was obtained. The presence of a higher level of genetic variation within populations can be attributed to gene flow, which depends on the informal seed exchanges between farmers of different ecological zones [42].…”

Section: Discussionsupporting

confidence: 60%

“…DArTseq technology has been used to explore the genetic diversity and population structure of different crops with a large number of entries and complex genomes [38,39]. Hassani et al [29] used DArTseq technology to explore genetic variations in a world panel of 89 safflower genotypes of diverse origin. The safflower panel utilized in their investigation is different from our panel except one accession, i.e., Afghanistan-1.…”

Section: Discussionmentioning

confidence: 99%

“…During this study we also aimed to explore the phenotypic and genetic diversity, population structure and marker-trait association in an international safflower panel using silicoDArT markers. Hassani et al [29] used 1136 silicoDArT and 2295 SNP markers, while we used a higher number of markers (12232) for the molecular characterization. Moreover, Hassani et al [29] used germplasm from 12 countries, while we included germplasm from 26 countries to explore population structure more extensively.…”

Section: Discussionmentioning

confidence: 99%

“…The application of DNA hybridization-based technologies like some SNP technologies and Diversity Arrays Technology are more suitable for such purposes. Hassani et al [29] implemented DArTseq technology to assess genetic diversity in 89 safflower accessions originating from different countries of the world. They applied 1136 silicoDArT markers along with 2295 SNPs in their investigation.…”

Section: Introductionmentioning

confidence: 99%

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Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information

Ali

Nadeem

Barut

et al. 2020

Plants

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Safflower is an important oilseed crop mainly grown in the arid and semi-arid regions of the world. The aim of this study was to explore phenotypic and genetic diversity, population structure, and marker-trait association for 100-seed weight in 94 safflower accessions originating from 26 countries using silicoDArT markers. Analysis of variance revealed statistically significant genotypic effects (p < 0.01), while Turkey samples resulted in higher 100-seed weight compared to Pakistan samples. A Constellation plot divided the studied germplasm into two populations on the basis of their 100-seed weight. Various mean genetic diversity parameters including observed number of alleles (1.99), effective number of alleles (1.54), Shannon’s information index (0.48), expected heterozygosity (0.32), and unbiased expected heterozygosity (0.32) for the entire population exhibited sufficient genetic diversity using 12232 silicoDArT markers. Analysis of molecular variance (AMOVA) revealed that most of the variations (91%) in world safflower panel are due to differences within country groups. A model-based structure grouped the 94 safflower accessions into populations A, B, C and an admixture population upon membership coefficient. Neighbor joining analysis grouped the safflower accessions into two populations (A and B). Principal coordinate analysis (PCoA) also clustered the safflower accessions on the basis of geographical origin. Three accessions; Egypt-5, Egypt-2, and India-2 revealed the highest genetic distance and hence might be recommended as candidate parental lines for safflower breeding programs. The mixed linear model i.e., the Q + K model, demonstrated that two DArTseq markers (DArT-45483051 and DArT-15672391) had significant association (p < 0.01) for 100-seed weight. We envisage that identified DArTseq markers associated with 100-seed weight will be helpful to develop high-yielding cultivars of safflower through marker-assisted breeding in the near future.

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Section: Genetic Structure and Diversity In Safflower Panelsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information

Ali

Nadeem

Barut

et al. 2020

Plants

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Appropriate statistical methods for analysis of safflower genetic diversity using agglomerative hierarchical cluster analysis through combination of phenotypic traits and molecular markers

Houmanat

Douaik²,

Charafi

et al. 2021

Crop Science

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Combining phenotypic and genotypic germplasm characterization is a key to efficient and successful safflower (Carthamus tinctorius L.) breeding program by identifying valuable and confirmed parents. This study aimed to investigate and use appropriate statistical methods for such a characterization, and to identify potential genetic pools in safflower germplasm that may be useful for breeding program implementation. The genetic diversity of 45 accessions from different countries, provided by the USDA-ARS, was assessed during two cropping seasons, using agromorphological traits and inter simple sequence repeat (ISSR) molecular markers. Agglomerative hierarchical cluster analysis (AHCA) was used with appropriate similarity distances, and Ward and unweighted pair group method with arithmetic mean (UPGMA) linkages. Agreement between distance-linkage combinations was evaluated using cophenetic correlation, Mantel test, Fisher exact test, Cramer's V, overall accuracy, and Cohen's κ. Both agromorphological phenotyping and molecular genotyping revealed significant genetic diversity. Ward linkage was better than UPGMA, using simple matching distance for molecular markers and Gower distance for phenotypic traits as well as for combined phenotypic traits and molecular markers. It delineated the studied accessions into four main clusters. Some accessions showed desirable profiles that can be used in future breeding programs. This is the first report of a series of appropriate statistical methods that can be used for assessing genetic diversity in safflower, combining phenotypic traits and molecular markers, and thus identifying relevant genetic pools for breeding program.

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Genomics, Phenomics, and Next Breeding Tools for Genetic Improvement of Safflower (Carthamus tinctorius L.)

et al. 2021

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In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology

Cited by 28 publications

References 46 publications

Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information

Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information

Appropriate statistical methods for analysis of safflower genetic diversity using agglomerative hierarchical cluster analysis through combination of phenotypic traits and molecular markers

Genomics, Phenomics, and Next Breeding Tools for Genetic Improvement of Safflower (Carthamus tinctorius L.)

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