Assessment of Microsatellite Markers for Varieties Identification: A Case of Six Varieties of Maize Hybrids Sold in Tanzania

Maize (Zea mays L.) is among the top three most cultivated cereal crops in Africa. The crop is utilized as human food, animal feed and a source of income (Kabululu et al., 2017). Maize is rich in nutrients, including protein, oil, fiber, vitamins A and B, starch and sugar. Sub-Saharan Africa (SSA) has around 40 million hectares of land where maize is farmed (Ayesiga et al., 2023). In SSA, maize production was based on the use of traditional open-pollinated varieties (OPVs), characterized by low yields due to the severe succumbing of both biotic and abiotic factors (Mwase et al., 2015; Tumwesigye et al., 2024). The advancement in crop improvement programs by the public and private sectors has resulted in the generation of hybrid varieties that can withstand stresses, resulting in increased yields and food security (Crossa et al., 2014). The suitability of these varieties attracted the attention of farmers over traditional OPVs, leading to their amplified demands (Wani et al., 2017). These demands attempt to persuade some seed dealers to sell counterfeit seed varieties (Kahwili, 2020; Machibya et al.,2021; Setimela et al., 2016). Thus, the sale of counterfeit seeds has necessitated for the National Designated Authority (NDA) the need for quality control tests to oversee the authenticity of the hybrid seed varieties sold to farmers.
       
Currently, the quality control test to evaluate the authenticity of varieties relies on a field observation collectively known as the grow-out test (GOT). This test involves the assessment of different morphological traits of a particular variety in field conditions against the descriptor of that variety (Kumari et al., 2022). Despite its significance, GOT faces some drawbacks, such as taking a long time, needing relatively large space, being affected by environmental factors, being subjective and sometimes taking a whole cropping season (Bora et al., 2016; Krishna et al., 2020). Alternatively, molecular markers have the potential to resolve the inherent challenges accompanied by GOT. This is because they are not affected by environmental factors; the method has a short turnaround time and is relatively less costly (Aydin et al., 2023).  
       
The application of molecular markers in various genetic studies, such as genetic diversity, QTL mapping and marker-assisted selection (MAS) breeding, paved the way for DNA fingerprinting of crop varieties (Ramesh et al., 2020). Different types of molecular markers based on PCR and non-PCR are used in such studies and these include restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), inter-simple sequence repeats (ISSR), microsatellite (SSR) and single nucleotide polymorphism (SNP). Among these molecular markers, microsatellite markers are preferred because they are co-dominantly inherited, multiallelic, highly polymorphic and very informative (Singh et al., 2022).
       
Therefore, this study aimed to determine the utility of microsatellite markers in varieties identification as a complement to GOT. The microsatellite markers fingerprinting information generated from the selected maize hybrid varieties will serve as baseline data for efficient and timely identification of those varieties, thus protecting them from counterfeiting.

Plant material
 
Six varieties of commercial maize hybrids released in Tanzania, coded H1, H2, H3, H5, H6 and H9, were acquired from public and private seed companies.
 
Study area
 
A field experiment was conducted in Arusha, Tanzania, at Madiira Farm, located at an altitude of 1250 m above sea level, at latitude 03o.22'S and longitude 36.48'E. The area has fertile and well drained loamy soil with a pH of 6.1. The region receives 20^oC and 28^oC of annual low and high temperatures, respectively. The region receives an average annual rainfall of 1180 mm. On the other hand, a laboratory experiment was conducted at the Nelson Mandela African Institution of Science and Technology (NM-AIST)-molecular biology laboratory.
 
Experimental design and layout
 
Six varieties of maize hybrids were laid out in a complete randomized block design with four replicates. Spacing was 0.75 m to 0.25 m of 2 plants per hole; after two weeks, thinning was done to leave one plant per hole. The experiment was conducted during the rainy season and planting was done on March 25, 2023. Agronomic practices were done uniformly in all plots.
 
Morphological data collection
 
11 quantitative and 21 qualitative traits (Table 1) were used to evaluate the level of variation among the varieties following the guidelines of the International Union for the Protection of New Varieties of Plants for Maize (UPOV, 2009).


 
DNA fingerprinting of maize hybrid varieties using microsatellite markers
 
DNA extraction
 
After two weeks from the planting date, the young leaf tissues of six to seven plants were sampled per variety grown in the field experiment. Total genomic DNA was extracted using the cetyltrimethylammonium bromide (CTAB) method as described by Jhansi et al. (2015).
 
Polymerase chain reaction (PCR)
 
This study used seven microsatellite markers that were obtained from the maize genomic database (https://www.maizegdb.org/) (Table 2). The target DNA amplification was done in a final volume of a PCR mixture of 25.0 µl, comprised of 12.5 µl of 2X one Taq PCR master mix, 0.5 µl of 100 µM each of forward and reverse primer, 9.5 µl nuclease-free water and 2.0 µl of 50 ng/µl template DNA. PCR products were resolved using gel electrophoresis, subsequently followed by scoring of bands.


 
Data analysis
 
Quantitative data were analyzed by a one-way analysis of variance (ANOVA) test in statistical package for social sciences (SPSS version 20).
       
The amplified PCR fragments from each polymorphic microsatellite marker were scored according to their band sizes, followed by analysis of Nei’s genetic distance by using the GenAIEX software, version 6.5. Furthermore, the phylogenic tree of the six varieties of maize hybrids was constructed based on Neighbor Joining clustering using DARwin software, version 6.

Morphological characterization of six varieties of maize hybrids
 
Morphological characterization is essential for variety identification. In the present study, 11 quantitative and 21 qualitative traits assessed during different plant growth stages. 11 qualitative traits showed significant variation among all six tested varieties (Table 3). Each variety tested in the present study was obtained from different seed companies; thus, the qualitative results confirm their different identity.  



The finding is in line with Mahmood et al. (2022), who morphologically assessed 20 maize inbred lines and found that all the varieties showed significant variation in their quantitative traits because those varieties were bred differently.
       
Six qualitative traits (first leaf: anthocyanin coloration of sheath, first leaf: shape of apex, stem: degree of stem zig-zag, ear: color of top of grain, ear: color of dorsal side of grain, ear: anthocyanin coloration of glumes of cob) exhibited monomorphism and couldn’t discriminate between the studied varieties. These monomorphic traits were not useful in variety identification because they were commonly possessed in all the tested varieties. So far, some traits showed dimorphic and trimorphic characteristics (Table 4); these traits were able to distinguish at least one variety from among the other tested varieties and were found to be informative for variety identification. A similar finding is in accordance with Asati et al. (2023). In the present study, qualitative traits showed minimal variations among the test varieties when compared to quantitative traits. The minimal variation in qualitative traits among the tested varieties could be due to the related parental lines obtained during the breeding program.


 
DNA fingerprinting of six varieties of maize hybrids using microsatellite markers
 
In the present study, out of seven microsatellite markers screened, two markers (phi080 and umc1071) were polymorphic and the other five markers (umc1064, umc1013, umc1746, umc1136 and phi076) produced monomorphic bands. A microsatellite marker (phi080) produced a unique banding pattern of two alleles per locus with a base pair of 120 and 150 to identify H2 from the rest of the five hybrids, which had similar banding patterns Fig 1 (A). Furthermore, the microsatellite marker umc1071 produced a unique profile with two alleles per locus with a base pair of 100 and 130 to identify H1 from the rest of the five hybrids, which produced similar bands. [Fig 1 (B)]. Markers phi080 and umc1071 are highly polymorphic, as they evidently distinguished two varieties from the other varieties. The two varieties (H1 and H2) are proven to have high genetic variations compared to the other varieties; this makes them advantageous for easy identification. Therefore, variety H1 can be identified by marker umc1071, while variety H2 can be identified by marker phi080. This finding is comparable to Sharma et al. (2014). The similar banding patterns in H3, H5, H6 and H9 varieties could be due to a narrow genetic base among Zea mays or a small number of polymorphic markers used in the present study as the high number of polymorphic markers used during DNA fingerprinting increases the chance of representing the whole maize genome (Jayasooriya et al., 2013).




 
Nei’s genetic distance
 
Nei’s genetic distance (Table 5) among six varieties of maize hybrids ranged from zero to four. The highest measure of genetic distance was four, followed by three, which was observed in H1 and H2, respectively. This verifies the genetic dissimilarity between each of H1 and H2 and the rest of the four varieties. The genetic dissimilarity is vital in the identification of different varieties (Jayasooriya et al., 2013). The least genetic distance measure was zero, which was observed in both H3, H5, H6 and H9 (Table 2). A genetic distance of zero in H3, H5, H6 and H9 indicates the common ancestors among these varieties. This result is consistent with the findings of Yu et al. (2012), who found the minimum genetic distance approaching zero among six genotypes of wax maize and revealed that those genotypes were the sibling lines from the same pedigree.

Neighbor Joining clustering
 
The unweighted Neighbor Joining tree (Fig 2) made clusters of three populations from six varieties of maize hybrids. Each of the two hybrids, namely H1 and H2, clustered away from the other four varieties (H3, H5, H6 and H9), which clustered together, forming the same population. The different clustering of each of the two varieties (H1 and H2) from the rest of the four varieties indicates the genetic variations between the two varieties and from the rest of the four varieties that clustered together; this supports the unambiguous fingerprinting of H1 and H2 from the rest of the other four hybrids. Four varieties (H3, H5, H6 and H9) clustered together, revealing their relativeness and possibly confirming that they bled from similar germplasm, resulting in the possession of the same alleles in all four varieties. Similar clustering was reported by Kumar et al. (2022).


       
The microsatellite marker results in the present study agree with those of GOT; therefore, the bridge of both methods was crucial, though GOT took a relatively long time, approximately six months and it was labor-intensive. The same was noted by Zhang et al. (2023), who complemented
 
 the SNP results with morphological analysis when working with tomato varieties.

The application of microsatellite markers complemented with morphological characters enabled successful fingerprinting of two commercial varieties of maize hybrids, herein coded as H1 and H2, out of the six varieties included in this study. Two markers, namely phi080 and umc1071, could be used for fast and timely varietal identification of H1 and H2. This study provides evidence and baseline data for consideration of the incorporation of these markers in varieties identification. Since a small sample size was used in terms of varieties, this study recommends that future research should focus on increasing the number of varieties.

The present study was supported by Tanzania Official Seed Certification Institute (TOSCI)
 
Disclaimers
 
The view and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content. 
 

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.