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Analysis of population structure and genetic diversity of Iranian Wild Salicornia (Salicornia iranica Akhani) population.

Authors :
Aghaei, Mohammad
Hassani, Abbas
Nazemiyeh, Hosein
Mandoulkani, Babak Abdollahi
Saadatian, Mohammad
Source :
Journal of Genetic Engineering & Biotechnology; Dec2022, Vol. 20 Issue 1, p1-15, 15p
Publication Year :
2022

Abstract

Background: Salicornia is a halophyte plant capable of being irrigated with seawater, which can be used as an alternative food. Given this, it is necessary to study the potentials of this plant’s morphological diversity in the natural environment. In this study, 33 wild populations of Salicornia were collected from different geographical areas around Urmia Lake during the flowering stage, and 55 morphological traits and 25 ISSR loci of the plant were analyzed. Based on morphological and molecular traits and the cluster analysis, Salicornia populations were divided into four and two groups, respectively. Results: Overall, the high percentage of polymorphic loci (65.69%), the average number of effective alleles per locus (1.63), and the Shannon data index (0.540) indicate that ISSR markers was used to identify genetic diversity. Molecular data cluster analysis divided the studied populations into two main groups, which included 12.12% and 87.88% of the populations, respectively. Based on the effective analysis of the population’s genetic structure and the precise classification of individuals into suitable sub-populations, the value of K=2 was calculated. Conclusions: The research findings indicated that the populations of Salicornia have a considerable diversity in morphological traits. Furthermore, markers UBC823, B, A7, and K, as well as markers with the Shannon index, effective allele, and large heterozygosis values, are the most effective markers in comparison with other markers used in this study. The findings of this study will aid in parental selection studies for breeding programs of Salicornia in future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1687157X
Volume :
20
Issue :
1
Database :
Supplemental Index
Journal :
Journal of Genetic Engineering & Biotechnology
Publication Type :
Academic Journal
Accession number :
156491511
Full Text :
https://doi.org/10.1186/s43141-022-00337-0