Genome-Wide Association Studies of Agronomic and Yield Traits in Sweet Corn (Zea mays L. var. saccharata)

Dissection of genetic architecture for tiller and yield - related traits in sugarcane (Saccharum spontaneum L.) by genome - wide association study.

Sugarcane (Saccharum spp.) is an important crop for food and energy security. Identifying SNPs and genes associated with sugarcane yield and related traits is crucial for developing high - yielding sugarcane cultivars through molecular breeding. Here, we measured nine phenotypic traits across 160 sugarcane genotypes and employed multiple statistical models (namely MLM, CMLM, MLMM, FarmCPU and SUPER) in GWAS to identify stable and pleiotropic loci. A total of 200 SNPs corresponding to 137 QTLs were detected to be significantly associated with nine traits using multiple statistical models, among which 18 QTLs were consistently identified by two or more models. Notably, the SNP S9A_47793177 on chromosome 9A showed the strongest association with phenotypic variation in aboveground biomass, with a phenotypic explanation rate of 70.54%. Additionally, several QTLs significantly associated with tillering - related traits were identified, suggesting that these QTLs may play crucial roles in the regulation of tillering. The QTLs and SNPs identified in this study provide a significant foundation for molecular marker - assisted breeding in sugarcane. This advancement can significantly enhance the efficiency of genetic improvement for sugarcane yield and tillering - related traits.

Genetic diversity, GWAS, and candidate genes identification for plant architecture traits in maize (Zea mays L.)

Genetic diversity and yield trait associations in soybean germplasm using SSR markers

Soybean (Glycine max (L.) Merrill), a vital food and oilseed crop native to China, has the development of high-yield and high-quality new varieties as a core objective in soybean breeding. However, studies on genetic diversity and marker-trait associations for yield-related traits across multiple environments using simple sequence repeat (SSR) markers remain limited. This study utilized 20 pairs of SSR primers to investigate genetic diversity and marker-trait associations (MTAs) between SSR markers and yield-related traits in 150 soybean accessions of diverse origins, which were grown under two environmental conditions. Genetic diversity analysis of 12 key agronomic traits, including plant height, number of branches, number of pods per plant, and hundred-seed weight, showed substantial phenotypic variation with large ranges and high coefficients of variation among the accessions. Cluster analysis based on agronomic traits classified the germplasm into five clusters under environment E1 and four clusters under environment E2. SSR primer amplification of the accessions’ genomic DNA produced an average of 7.10 amplified loci and 6.80 polymorphic loci per primer pair, with an average polymorphic locus rate of 96%. The average values of effective allele number (Ne), gene diversity index (H), Shannon’s information index (I), polymorphism information content (PIC), and genetic similarity coefficient (GSC) were 1.5035, 0.3581, 0.5176, 0.3539, and 0.57, respectively. SSR-based cluster analysis divided the 150 accessions into three distinct clusters. Principal coordinate analysis (PCoA) validated that the selected SSR primers could effectively discriminate among the accessions. Population structure analysis indicated complex genetic relationships and substantial genetic diversity within the germplasm panel. Association analysis between agronomic traits and SSR markers identified 44 markers significantly associated with yield-related traits, of which 13 were simultaneously linked to two or more yield-related traits. Using generalized linear model (GLM) and mixed linear model (MLM) analyses, six SSR markers significantly associated with yield-related traits were consistently detected across the two environments. These results provide a theoretical basis for germplasm utilization and molecular breeding in soybean.

Genome-wide association study reveals marker-trait associations for key agronomic and grain quality traits in durum wheat under rainfed and irrigated conditions in Turkish environments

Multi-model genome-wide association analysis of agronomic traits in a Kabuli chickpea MAGIC-subset population (Cicer arietinum L.) across Mediterranean environments

Chickpea is one of the most consumed legumes due to its high nutritional value and accessibility to low-income populations. However, due to climate change, chickpea cultivation is exposed to various environmental stresses affecting its production and productivity. This study evaluates the agronomic performance of 168 MAGIC subset population across two Mediterranean environments, in Marchouch (Morocco) and Terbol (Lebanon). Genome-wide association studies (GWAS) were conducted to identify potential marker-trait associations (MTAs) using the general linear model (GLM), the mixed linear model (MLM), and the fixed- and random-effect circulant probability unification (FarmCPU), with kinship and principal components used as covariates. The results revealed high genetic variation among the genotypes tested, with significant genotype-by-environment interactions for most traits studied. Genotypes with good agronomic performance (M-1407, M-2038, M-2079, M-242, M-2551, and M-987) were identified under both environments. Early flowering and maturation resulted in a significant increase in grain yield of around 66%. Grain yield varied from 151.85 to 882.7 g m-2 and from 183.59 to 365.76 g m-2 under Marchouch and Terbol conditions, respectively, showing higher genetic variation under Marchouch than under Terbol. Correlation analysis revealed strong, significant correlations among the studied traits. GWAS revealed clear genetic variation across environments, with Marchouch showing stronger and more consistent association signals than Terbol. In total, 72 reliable MTAs were detected for phenological traits, 38 for plant height, 18 for grain yield, and 197 for hundred-seed weight across both sites. A major genomic hotspot on chromosome 4 (11.97–13.63 Mbp) harbored stable and pleiotropic MTAs. Functional annotation of regions surrounding significant SNPs revealed 59 putative candidate genes, highlighting potential biological processes related to growth, signaling, and stress responses that require further validation. These results provide a foundation for further research on marker-assisted selection to improve chickpea productivity and yield stability in stressed environments.

Identification of stable and high-yielding maize genotypes using BLUP-based stability and multi-trait selection indices across diverse environments

Maize (Zea mays L.) is one of the most important cereal crops worldwide and serves as a major source of food, feed, and industrial raw material; however, identification of high-yielding and stable maize genotypes across diverse environments is a key objective of maize improvement programs. A total of 60 maize genotypes were evaluated across four environments [summer 2023 (E1), winter 2023 (E2), summer 2024 (E3), and winter 2024 (E4)] in an alpha lattice design with two replications, comprising six incomplete blocks with 10 entries per block. Subsequently, 15 morphological and yield-related traits were assessed to identify superior and stable maize genotypes across environments. A pooled analysis of variance revealed highly significant effects of genotypes, environments, and genotype × environment interaction for all traits. Broad-sense heritability was high for grain yield (92.40%), biological yield (97.10%), cob yield (92.60%), and plant height (99.20%), whereas anthesis silking interval showed low heritability (12.70%), indicating strong environmental influence. Grain yield exhibited strong positive genotypic correlations with cob yield, biological yield, plant height, kernels per ear, ear length, seed index, and ear diameter. Factor analysis under MGIDI identified three factors explaining 76.06% of total variation, representing yield components, partitioning efficiency, and ear morphology traits. Based on 15% selection intensity, nine genotypes were selected with predicted genetic gains ranging from −0.523% for anthesis–silking interval (indicating a desirable reduction in ASI) to 50.6% for grain yield. The highest coincidence index was observed between MGIDI and FAI-BLUP (66.67%). Genotypes G26 and G27 were consistently selected across all indices, indicating superior performance and stability. These genotypes are promising candidates for multi-location evaluation and can serve as potential parents in hybridization programs aimed at improving grain yield and adaptability in maize.