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Population Genetics, Genetic Structure, and Inbreeding of Commiphora gileadensis (L.) C. Chr Inferred from SSR Markers in Some Mountainous Sites of Makkah Province.

Hassan MansourKhalid H AlamerZaki M Al-Hasawi
Published in: Plants (Basel, Switzerland) (2023)
Commiphora gileadensis (L.) C. Chr is a perennial plant existing mainly in the southern and western mountains of the Arabian Peninsula. In the Makkah province, the remaining populations are threatened by many factors such as overcutting, overgrazing, and urban developments. These dangers are expected to be aggravated by the progression of aridification factors arising from climate change. To overcome the decline in remaining populations of this valuable species, a timely evaluation of the population's genetic variables and genetic structure is vital for the conservation of existing C. gileadensis populations. In this study, we used 61 SSR primers to achieve this objective. Only 50 loci showed polymorphisms, which led to further analysis of the population genetics for 600 genotypes that were collected from 50 populations of C. gileadensis found in 10 different sites in the Makkah region: Gebel Al Muliesaa, Wadi Albathna, Wadi Houra, Wadi Albaidaa, Wadi Elebiedia, Gebel Kniethl, Wadi Sayaa, Wadi Elbarasa, Wadi Alfawara, and Wadi Alkharar. The results showed an obvious decrease in genetic diversity variables in all studied populations. The range of PPL was between 8 and 40; additionally, the low H T value of 0.804 and the high value of inbreeding, F is = 0.238, reflected a severe lack of heterozygotes. High levels of F ST and G ST and low gene flow indicate considerable segregation among the C. gileadensis populations, which creates a barrier to gene migration. Our data suggest the need for conservation planning for C. gileadensis in order to avoid the species' forthcoming extinction. Efforts should be largely oriented around managing water consumption, prohibiting overcutting and overgrazing, and establishing appropriate seed banks.
Keyphrases
  • genetic diversity
  • genome wide
  • climate change
  • copy number
  • south africa
  • dna methylation
  • early onset
  • transcription factor
  • machine learning