2024 : 6 : 20
Mehry Askari Mehrabadi

Mehry Askari Mehrabadi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-5586-6317
Education: PhD.
ScopusId: 57193743462
Faculty: Science
Address: Arak University
Phone:

Research

Title
Genotypes Identification in Iranian Morus alba L. Populations Using Inter-simple Sequence Repeat Markers
Type
JournalPaper
Keywords
Infraspecific variation , ISSR , Genetic diversity ,Morus alba ,Population structure
Year
2020
Journal Iranian Journal of Science and Technology
DOI
Researchers Mehry Askari Mehrabadi ، Seyed Mehdi Talebi ، Alex اmatsyura

Abstract

Morus alba L. (Mulberry) is an economic and medicinal tree, originated from the Himalaya region and gradually spread all over the world. Most of the recently developed mulberry varieties have similar narrow genetic base and limited capacity against environmental stress and pathogens. To enhance the species resistance, we need to increase genetic diversity of its varieties using higher genotypes differentiation in breeding programs. We investigated genetic diversity and structure of some mulberry Iranian populations to register different genotypes, which could be implemented in further genetic breeding programs. For this purpose, the nuclear genome of ten populations (4–7 individuals per each population) were extracted using the CTAB modified method and amplified using 30 ISSR primers. Genetic diversity parameters, polymorphism indexes and population structure were detected using GenAlex v. 6.4, GenoDive v. 2.0, PopGene v. 1.32 and Structure. We detected that the number of different alleles and polymorphic bands together with genetic diversity parameters varied among the populations. The results of AMOVA demonstrated the significant genetic interpopulation variations. Our research outputs were consistent with the high GST and HT amounts and low rate of Nm and Hs, which indicating high genetic differentiation of the populations. These results suggested that genetic drift created high genetic differentiation among some populations. We determined the optimal value of K (6) by structure analysis and K-means clustering. This was supported by six detected genotypes among mulberry populations based on the UPGMA tree of Nei’s genetic distance, MDS plot, structure analysis and neighbor-net diagram. These genotypes have high genetic diversity, and they should be considered in prospective breeding programs to develop the mulberry varieties with improved yield and quality, and enhanced tolerance toward adverse environmental stress and diseases.