The integration of molecular markers has significantly advanced the accuracy and speed of genetic analysis in plants, thereby accelerating the adoption of molecular breeding in field crops and forestry species. Among these, single nucleotide polymorphisms (SNPs) have emerged as the most widely utilized markers due to their high abundance across genomes and compatibility with high-throughput genotyping platforms. These functional markers hold great promise for enhancing the efficiency of marker-assisted selection (MAS) in crop improvement programs. Next-generation sequencing (NGS) technologies continue to play a transformative role in SNP genotyping, particularly for large-scale discovery applications. A key factor in scaling up SNP genotyping lies in minimizing the number of biochemical reactions required per assay. Therefore, the development of robust, multiplexed genotyping methods capable of amplifying numerous genomic loci simultaneously has become essential. Despite these advancements, there remains a gap in the availability of ultra-high-throughput and cost-efficient genotyping platforms suitable for routine use in applied breeding. This review highlights and evaluates four contemporary SNP genotyping assays and platforms, illustrating their roles in achieving scalable and accurate genotyping. Additionally, the paper provides an overview of current progress in SNP marker discovery, validation, and application in quantitative trait locus (QTL) analysis and modern plant breeding strategies.

This study seeks to determine the genetic diversity among two cassava populations for total carotene content, dry matter, and hydrogen cyanide using single nucleotide polymorphic (SNP) markers. 376 cassava genotypes from two populations were assayed with nine trait-linked SNP markers. Data collected were subjected to marker (Minor Allele Frequency-MAF; Gene Diversity-GD; Heterozygosity-He; and Polymorphic Information Content-PIC) and principal components (PCA) analyses. A high call rate of 96 to 100% was observed across the populations. Discriminate analysis of PCA and hierarchical cluster dendrogram using the SNP markers categorized the genotypes into three clusters with 257, 88 and 15 genotypes in clusters 1, 2, and 3, respectively. The variation explained by the first two PCs was 39.1%. The level of genetic diversity observed in this study indicates sufficient variation in the two populations, hence promising for the pyramiding of genes for the three traits. The SNP markers used for this study were highly informative and polymorphic and revealed good estimates of genetic diversity. Clustering patterns of the genotypic backgrounds along the PC axis reflect an intense exchange of genetic backgrounds among the populations studied. Results from this study may contribute significantly to cassava breeding and germplasm conservation programs.

Biofortification is a promising, cost effective and sustainable strategy to mitigate micronutrient deficiencies and related health complications. The principal aims of the study encompassed the quantification of the carotenoid content of 147 maize inbred lines, the identification of variable regions within the ZEP1 gene, the correlation of these observed variances in the presence of this gene with carotenoid content, and to identify lines harboring the favorable alleles for the crtRB1 gene. The correlations observed among the carotenoids synthesized by specific branch of the biosynthetic pathway were both significant and positive. Utilizing gel-based genotyping, 24 lines with contrasting carotenoid profiles were selected, evaluated and sequenced. Analysis of the variation in the sequence classified these lines into distinct groups. The findings highlight that inbred lines both group 1 and group 8 exhibited significant associations with the carotenoid content of the lines. Specifically, ZEP1_7852, a discernible variation belonging to group 8, was significantly associated with zeaxanthin content and total carotenoid content. Twenty-five inbred lines with provitamin A content surpassing 15 μg/g that harbor the favorable alleles of the crtRB1 gene were identified using KASP SNP zm0016. These lines can be used as donor parents for further enhancement of provitamin A in maize.

Wheat production in Zimbabwe is strongly influenced by environmental variability, making it difficult for breeders to identify genotypes that are both high yielding and stable across locations. This study evaluated the yield performance and stability of pre-release bread wheat genotypes across contrasting environments in Zimbabwe. A total of 25 genotypes in 2020 and 24 genotypes in 2021 were tested using a randomized complete block design (RCBD) with three replications at three sites Gwebi Variety Testing Centre (GVTC), Harare Research Station (DR&SS), and Panmure, forming six test environments across two winter seasons. Grain yield and key agronomic traits were recorded and analyzed using combined analysis of variance, correlation analysis, and genotype plus genotype-by-environment (GGE) biplot methods. The combined analysis of variance revealed highly significant (p < 0.001) effects of location on all traits in both years, confirming strong environmental influence on wheat performance. Genotypic differences were also significant for most traits in each season. In 2020, genotype × location interaction for grain yield and grain weight was not significant, indicating relatively stable genotype ranking across environments. In contrast, significant genotype × location interaction in 2021 demonstrated strong crossover effects, with genotypes responding differently across sites. When the 15 genotypes common to both years were analyzed together, genotype × location interaction for grain yield was again not significant, indicating that this subset of genotypes expressed greater yield stability across environments. GGE biplot analysis revealed clear differences in genotype adaptation and stability. The mean versus stability view identified G10 and G4 as high yielding with moderate stability, while G5 and G8 were closest to the ideal genotype, combining high yield and wide adaptation. The which-won-where pattern separated the test environments into two main mega-environments, with G3 and G10 performing best in GVTC- and Harare-based environments, while G4, G5, and G8 were superior at Panmure-related environments. Environment E3 (Harare 2020) was identified as the most representative and closest to an ideal test environment, while E1, E2, E5, and E6 were more discriminating and useful for detecting genotype differences. The findings of this study demonstrated that both yield level and stability must be considered when selecting wheat genotypes for Zimbabwe. Genotypes G5 and G8 showed the best combination of high grain yield and stability and are therefore recommended for broad adaptation. Genotypes such as G3 showed high yield but strong environmental sensitivity and are better suited for specific environments. These findings provide valuable guidance for wheat breeding and variety recommendation in Zimbabwe’s diverse production environments.