Open AccessSpecies identification and population structure analysis in Hesperis L. (Brassicaceae)
Author(s) -
Zhiwei Zhang,
Hangcheng Yu,
Shuowen Feng,
Abbas Minaeifar
Publication year - 2021
Publication title -
genetika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.24
H-Index - 15
eISSN - 1820-6069
pISSN - 0534-0012
DOI - 10.2298/gensr2103357z
Subject(s) - brassicaceae , biology , genetic diversity , genetic structure , genetic divergence , taxon , genetic distance , evolutionary biology , ecology , gene flow , population , identification (biology) , zoology , genetic variation , gene , genetics , demography , sociology
In biology, biogeography, ecology, and conservation, species identification is critical. Hesperis L. is a Brassicaceae (Cruciferae) genus of 46 species found across the temperate northern hemisphere, from South and Central Europe to Southwest Asia, Caucasia, and the mountainous portions of West China and Mongolia. According to the latest therapies, Hesperis is expressed in Iran by six species. Despite the fact that several Hesperis species are widely distributed throughout Iran, nothing is known about their genetic diversity, divergence techniques, or dispersion patterns. As a result, we examined 122 accessions from six Hesperis species gathered from various locations in Iran using genetic (ISSR markers) and morphological techniques. A total of ten ISSR markers were employed in this study. The Nei's genetic distance was used to measure genetic distances, and descriptive statistics of folks were used to produce genetic parameters. There were a total of 118 polymorphic bands found. The study's aims are as follows: 1) Is it possible to identify Hesperis species using ISSR markers? 2) In Iran, what is the genetic make-up of these taxa? 3) How do interspecies relationships work? According to the conclusions of this research, morphological and ISSR data may be utilized to identify species. The Hesperis species are genetically distinct yet share significant genes, according to the AMOVA and STRUCTURE analyses.