Genetic diversity and population structure of sorghum [Sorghum bicolor (L.) Moench] genotypes in Ethiopia as revealed by microsatellite markers

In the tropical and semi-arid regions of Africa, sorghum [Sorghum bicolor (L.) Moench] is mainly grown as a major food security crop. Understanding the extent and pattern of genetic variability is a prerequisite criterion for sorghum improvement and conservation. The genetic diversity and population structure of 100 genotypes of sorghum were profiled using 15 microsatellite loci. A total of 108 alleles, with an overall mean of 7.2 alleles per locus, were produced by all of the microsatellite loci used due to their high polymorphism. Polymorphic information content values ranging from 0.68 to 0.89 indicated that all of the loci are effective genetic tools for analysing the genetic structure of sorghum. Different diversity metrics were used to evaluate genetic diversity among populations, and Nei's gene diversity index ranged from 0.74 to 0.81 with an overall mean of 0.78. Poor genetic differentiation (FST: 0.02; p < 0.0001) was found, where 98% of entire variability was accounted by the within populations genetic variability, leaving only 2.32% among populations. The highest genetic differentiation and Nis's genetic distance were observed between the sorghum populations of the Southern Nation and Nationalities Peoples and Dire Dawa regions. Due to increased gene flow (Nm = 10.53), the clustering, principal coordinate analysis and STRUCTURE analysis failed to categorize the populations into genetically different groups corresponding to their geographic sampling areas. In general, it was found that the mi-crosatellite loci were highly informative and therefore valuable genetic tools to unfold the genetic diversity and population structure of Ethiopian sorghum genotypes. Among the five populations studied, sorghum populations from Amhara and Oromia had the highest genetic variation, indicating that the regions could be perhaps hotspots for useful alleles for the development of better-performing genotypes, and also for designing appropriate germplasm management strategies.