Genetic Diversity and Population Structure of Normal Maize Germplasm Collected in South Sudan Revealed by SSR Markers

Abstract

Maize is one of the leading global cereals, and in South Sudan maize cultivation occurs in nearly all of the country’s agro-ecological zones. Despite its widespread cultivation, farmers in South Sudan depend on undeveloped varieties, which results in very low yields in the field. In the current study, 27 simple sequence repeat (SSR) markers were used to investigate genetic diversity and population structures among 37 landrace maize accessions collected from farmers’ fields in South Sudan. In total, 200 alleles were revealed with an average of 7.4 alleles per locus and a range from 3.0 to 13.0 alleles per locus. The observed heterozygosity values ranged from 0.06 to 0.91 with an average of 0.35. High polymorphic information content (PIC) values were identified with a mean of 0.69, which indicates the informativeness of the chosen SSR loci. Genetic structure analysis revealed a moderate genetic differentiation among the maize populations with a fixation index of 0.16, while there was very high genetic differentiation within the groups of populations of three regions with a mean fixation index (F) of 0.37. An unweighted pair group method with an arithmetic mean (UPGMA) dendrogram clustered the 37 maize accessions into three groups with 43% genetic similarity. The clustering pattern of the maize accessions was moderately consistent with their collection area. The findings of this study will provide maize breeders with a better understanding of maize diversification as well as a reserve of genetic resources for use in the selection of advantageous and useful resources for the development of maize varieties in South Sudan.

Morphological Variation in Normal Maize Landrace Accessions Collected from South Sudan

“…These studies investigated the phenotypic traits of maize accessions from Italy, the north-eastern Himalayas, and Algeria respectively and found that the accessions were not clustered together based on their geographical region. Mixing of germplasm accessions among local farms could be the reason behind the weak relationship among the accessions from the same region, which is the same finding that was reported in our previous report for accession clustering based on microsatellite marker data (Mathiang et al 2022).…”

“…Utilization of this method will help in forming an accurate estimation of the level of phenotypic variation in maize accessions collected from South Sudan. In a previous study, we used simple sequence repeat (SSR) or microsatellite markers for genetic diversity studies of maize landrace accessions collected from South Sudan, and provided the first report about the genetic variation of maize landrace accessions of South Sudan (Mathiang et al 2022). Recently, many tools have become available for studying the genetic relationships between landrace germplasm using various molecular markers; however, morphological characterization is the first step in germplasm evaluation and classification (Smith et al 1990).…”

Genetic Relationships of 118 Castanea Specific Germplasms and Construction of Their Molecular ID Based on Morphological Characteristics and SSR Markers

“…The length of the burn-in period was set at 10,000, and the number of Markov chain Monte Carlo (MCMC) repeats after burn-in was set at 100,000 to estimate individual admixture proportions ( Q ). Evanno’s method [ 49 ] and the online software Structure Harvester [ 50 ] were used to determine the optimal grouping K values [ 51 , 52 , 53 ]. Principal coordinate analysis (PCoA) was performed using GenAlex 6.41 software [ 54 , 55 ].…”