Assessing genetic diversity and defining signatures of positive selection on the genome of dromedary camels from the southeast of the Arabian Peninsula

Front Vet Sci. 2023 Nov 30:10:1296610. doi: 10.3389/fvets.2023.1296610. eCollection 2023.


Dromedary camels (Camelus dromedarius) are members of the Camelini tribe within the Camelidae family. They are distributed throughout North Africa, the Arabian Peninsula and Southeast Asia. This domestic species is characterized by its superior adaptability to the harsh desert environment. In this study, whole autosomal data of 29 dromedary samples from the Southeast Arabian Peninsula in Oman; 10 from Muscat, 14 from Al-Batinah, and 5 from Al-Sharqiya, were investigated to assess their genetic relationship and to define candidate signatures of positive selection. A minimal genetic distinction that separates Muscat dromedaries from the other two populations was observed, with a degree of genetic admixture between them. Using the de-correlated composite of multiple signals (DCMS) approach, a total of 47 candidate regions within the autosomes of these dromedary populations were defined with signatures of positive selection. These candidate regions harbor a total of 154 genes that are mainly associated with functional categories related to immune response, lipid metabolism and energy expenditure, optical and auditory functions, and long-term memory. Different functional genomic variants were called on the candidate regions and respective genes that warrant further investigation to find possible association with the different favorable phenotypes in dromedaries. The output of this study paves the way for further research efforts aimed at defining markers for use in genomic breeding programs, with the goal of conserving the genetic diversity of the species and enhancing its productivity.

Keywords: de-correlated composite of multiple signals; dromedary camels; environmental adaptation; genetic diversity; signatures of selection.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by the Ministry of Higher Education, Research and Innovation. Grant code: RC/RG-AGR/ANVS/19/01.