Abstract

The genusAvicennia with eight species grow in intertidal zones of tropical and temperate regions, ranging in distribution from West Asia, to Australia, and Latin America. These mangroves have several medicinal applications for mankind. Many genetic and phylogenetic studies have been carried out on mangroves, but none is concerned with geographical adaptation of SNPs. We therefore, used ITS sequences of about 120 Avicennia taxa growing in different parts of the world and undertook computational analyses to identify discriminating SNPs among these species and to study their association with geographical variables. A combination of multivariate and Bayesian approaches such as CCA, RDA, and LFMM were conducted to identify the SNPs with potential adaptation to geographical and ecological variables. Manhattan plot revealed that many of these SNPs are significantly associated with these variables. The genetic changes accompanied by local and geographical adaptation were illustrated by skyline plot. These genetic changes occurred not under a molecular clock model of evolution and probably under a positive selection pressure imposed in different geographical regions in which these plants grow.

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