Evaluation of genetic diversity and population structure of Iranian native henna ecotypes using ISSR molecular markers and phenotypic traits

Document Type : Research Paper

Authors

1 PhD Student, Department of Horticultural Sciences, Estahban Branch, Islamic Azad University, Estahban, Iran.

2 Assistant Professor, Department of Horticultural Sciences, Estahban Branch, Islamic Aza University, Estahban, Iran.

3 Crop and Horticultural Science Research Department, South Kerman Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Jiroft, Iran.

4 Professor, Research and Technology Institute of Plant Production, Afzalipour Research Institute, Shahid Bahonar University of Kerman, Iran.

5 Assistant Professor, Research & Technology Institute of Plant Production, Afzalipour Research Institute Shahid Bahonar University of Kerman, Iran

Abstract

Objective
Henna (Lawsonia inermis L.) is a valuable medicinal plant used in medicine and dyeing industries. This study aimed to investigate the genetic diversity of Iranian native henna ecotypes using ISSR molecular markers and phenotypic traits to preserve genetic resources and advance breeding programs.
Materials and Methods
In this study, 140 henna ecotypes were cultivated in a lattice design with two replications. Important phenotypic traits including plant height, leaf dry weight, stem dry weight, leaf area index, and the ratio of leaf dry weight to stem dry weight were measured in seven selected plants from each plot. DNA was extracted using the modified CTAB method, and nine ISSR markers with the maximum number of polymorphic bands among 20 markers were selected and used.
Results
Variance analysis revealed significant differences between ecotypes in all studied phenotypic traits. The high degree of polymorphism and ability to distinguish ecotypes demonstrated the high efficiency of ISSR markers in evaluating henna genetic diversity. Structure analysis separated the 140 henna ecotypes into three different subpopulations. Cluster analysis of phenotypic data using Ward's method divided the ecotypes into four groups. The ecotypes of Zehkalut (HA245), Rudbar (ET244), and two ecotypes of Qalehganj (EH100 and GB107) with high averages of all studied traits were placed in the second phenotypic cluster group. Additionally, phenotypic cluster analysis showed that ecotypes with the highest average plant height were also in the second group. Three ecotypes from the Qalehganj region (AGH140, LA137, and NE253) and one ecotype from the Shahdad region (SHH157) had the highest stem dry weight, all of which were located in the third phenotypic cluster group. Cluster analysis of molecular data based on the Jaccard method and principal component analysis of genotypic data placed ecotypes into more distinct groups. Molecular data revealed greater genetic differentiation between ecotypes than phenotypic information. The genetic distance analysis showed the least difference between AGH140 and NG142 ecotypes from the Qalehganj region, while the GA198 ecotype from the Dalgan region exhibited the greatest genetic difference from other ecotypes.
Conclusions
The population structure identified in this study can serve as a necessary prerequisite for association mapping in future studies. The obtained diversity and genetic distance results are valuable for preserving genetic resources and selecting parents to improve the breeding value of genotypes.

Keywords

References

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Agricultural Biotechnology Journal
Volume 17, Issue 1
March 2025
Pages 27-44

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