2024 : 11 : 21
Naghi Shabanian

Naghi Shabanian

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 56079428000
HIndex:
Faculty: Faculty of Natural Resources
Address: Dept. of Forestry, Faculty of Natural Resources, University of Kurdistan, Sanandaj, IRAN, P.O. Box 416, Postal Code 66177-15175
Phone: 08733620551

Research

Title
Genetic differentiation in Quercus infectoria from northwest of Iran revealed by different nuclear markers
Type
JournalPaper
Keywords
Analysis of molecular variance (AMOVA) . Conservation genetics . Inter-retrotransposon amplified polymorphism(IRAP) . Inter-simple sequence repeat (ISSR) . Start codon targeted (SCoT)
Year
2014
Journal Tree Genetics & Genomes
DOI
Researchers Mohammad Shafih Rahmani ، Liela Alikhani ، Naghi Shabanian ، Abdollah Khadivi-Khub

Abstract

The aim of the present study was to examine the genetic variability of natural populations of Quercus infectoria, based on inter-retrotransposon amplified polymorphism (IRAP), inter-simple sequence repeat (ISSR), and start codon targeted (SCoT) markers, in view of long-term conservation plans. A total of 150 accessions from ten populations of this species were sampled from northwest of Iran. Eighteen ISSR, ten IRAP, and ten SCoT primers generated a total of 466 unambiguous and repeatable bands, from which 448 (96.14 %) were polymorphic for all markers. The polymorphism information content (PIC) values for IRAP, ISSR, and SCoT markers were 0.26, 0.35, and 0.37, respectively. Genetic similarity and distance analyses indicated the existence of high variability among the studied accessions, so that a pairwise Jaccard’s genetic similarity based on combined data ranged from 0.27 to 0.79. Cluster analysis for three different molecular types revealed that the accessions taken for the analysis can be divided into two distinct clusters. Molecular variance analysis revealed that more than 70 % of the variation resided within populations and less than 30 % could be attributed to variation among populations, possibly due to gene flow between populations and life history traits. These data provide valuable information for natural resource conservation.