» Articles » PMID: 34199003

Transferability of ISSR, SCoT and SSR Markers for × Ramat and Genetic Relationships Among Commercial Russian Cultivars

Abstract

Characterization of genetic diversity in germplasm collections requires an efficient set of molecular markers. We assessed the efficiency of 36 new SCoT markers, 10 new ISSR markers, and 5 microsatellites for the characterization of genetic diversity in chrysanthemum core collection of 95 accessions (Russian and foreign cultivars). Seven new SCoT (SCoT12, 20, 21, 23, 29, 31, 34) and six new ISSR markers ((GA)8T, (CT)8G, (CTTCA)3, (GGAGA)3, (TC)8C, (CT)8TG) were efficient for the genetic diversity analysis in × collection. After STRUCTURE analysis, most Russian cultivars showed 20-50% of genetic admixtures of the foreign cultivars. Neighbor joining analysis based on the combination of SSR, ISSR, and SCoT data showed the best accordance with phenotype and origin compared to the separate analysis by each marker type. The position of the accessions within the phylogenetic tree corresponded with the origin and with some important traits, namely, plant height, stem and peduncle thickness, inflorescence type, composite flower and floret types, flower color, and disc color. In addition, several SCoT markers were suitable to separate the groups distinctly by the phenotypical traits such as plant height (SCoT29, SCoT34), thickness of the stem and peduncle (SCoT31, SCoT34), and leaf size and the floret type (SCoT31). These results provide new findings for the selection of markers associated with important traits in Chrysanthemum for trait-oriented breeding and germplasm characterization.

Citing Articles

SSR markers development and their application in genetic diversity of burdock (Arctium lappa L.) germplasm.

Su Y, Fu J, Xie H, Huang Z, Li Y, Luo Y BMC Plant Biol. 2025; 25(1):196.

PMID: 39953403 PMC: 11827309. DOI: 10.1186/s12870-025-06203-8.


Evaluation of Genetic Diversity and Identification of Cultivars in Spray-Type Chrysanthemum Based on SSR Markers.

Mekapogu M, Lim S, Choi Y, Lee S, Jung J Genes (Basel). 2025; 16(1.

PMID: 39858628 PMC: 11764994. DOI: 10.3390/genes16010081.


Genetic diversity and population structure of cowpea mutant collection using SSR and ISSR molecular markers.

Diallo S, Badiane F, Kabkia B, Diedhiou I, Diouf M, Diouf D Sci Rep. 2024; 14(1):31833.

PMID: 39738245 PMC: 11686381. DOI: 10.1038/s41598-024-83087-y.


Morphological, Biochemical, and Molecular Diversity Assessment of Egyptian Bottle Gourd Cultivars.

Ibrahim E, Alhaithloul H, Shamseldin S, Awaly S, Hesham A, Abdelkader M Genet Res (Camb). 2024; 2024:4182158.

PMID: 38205231 PMC: 10781529. DOI: 10.1155/2024/4182158.


InDel and SCoT Markers for Genetic Diversity Analysis in a Citrus Collection from the Western Caucasus.

Kulyan R, Samarina L, Shkhalakhova R, Kuleshov A, Ukhatova Y, Antonova O Int J Mol Sci. 2023; 24(9).

PMID: 37175981 PMC: 10179493. DOI: 10.3390/ijms24098276.


References
1.
Evanno G, Regnaut S, Goudet J . Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005; 14(8):2611-20. DOI: 10.1111/j.1365-294X.2005.02553.x. View

2.
Serrote C, Reiniger L, Silva K, Rabaiolli S, Stefanel C . Determining the Polymorphism Information Content of a molecular marker. Gene. 2019; 726:144175. DOI: 10.1016/j.gene.2019.144175. View

3.
Tsumura Y, Ohba K, Strauss S . Diversity and inheritance of inter-simple sequence repeat polymorphisms in Douglas-fir (Pseudotsuga menziesii) and sugi (Cryptomeria japonica). Theor Appl Genet. 2013; 92(1):40-5. DOI: 10.1007/BF00222949. View

4.
Amiryousefi A, Hyvonen J, Poczai P . iMEC: Online Marker Efficiency Calculator. Appl Plant Sci. 2018; 6(6):e01159. PMC: 6025818. DOI: 10.1002/aps3.1159. View

5.
Li P, Zhang F, Chen S, Jiang J, Wang H, Su J . Genetic diversity, population structure and association analysis in cut chrysanthemum (Chrysanthemum morifolium Ramat.). Mol Genet Genomics. 2016; 291(3):1117-25. DOI: 10.1007/s00438-016-1166-3. View