Association Analysis for Proline and Fructan Content in Barley (Hordeum vulgare L.) under Late Spring Cold Stress Using Microsatellite Markers

Introduction

Biotic and abiotic environmental stresses are factors that reduce the quantity and quality of agricultural products. One type of stress is late spring freeze, which can cause significant damage to farmers and producers depending on the growth stage of the crop. Marker-trait association analysis allows for the rapid and initial identification of quantitative trait loci based on linkage disequilibrium. This method is a powerful tool for elucidating the genetics of complex agricultural traits and identifying alleles that control the trait of interest. The aim of this study was to evaluate the population structure and conduct marker association analysis of SSR markers with the physiological traits of barley genotypes under late spring freeze stress conditions. Overall, the identified markers in this study, upon validation through complementary tests, could serve as specific markers in breeding programs through Marker Assisted Selection (MAS).

Materials and methods

In this study, to investigate the genetic diversity and determine the pattern of linkage disequilibrium as well as analyze the relationship of some physiological traits in cultivated barley, 60 genotypes were prepared from the Seed and Plant Improvement Research Institute of Karaj. The genotypes were grown in factorial experimental conditions using a completely randomized design with three replications. After growth, the genotypes underwent temperature tests (8°C and -2°C), and the relevant physiological data were measured and collected. The analysis of variance for physiological traits and the comparison of means were performed. DNA extraction from the genotypes under investigation was carried out using the CTAB method, and the quality of the DNA was assessed using agarose gel, while its quantity was determined spectrophotometrically. Twenty SSR markers were utilized in the PCR. The bands on the gels were scored as co-dominant, and the resulting matrix data was used for statistical analysis. Effective population structure analysis was conducted using the Bayesian method in the Structure software pakage. Association analysis was conducted by MLM considering the structure data matrix (Q) and the kinship matrix (K) as covariates in TASSELV.2.1 software.

Research findings

Based on the analysis of variance of physiological data, there was a significant difference in all studied traits among barley varieties under both +8°C and -2°C temperature conditions. Based on the mean comparison results for proline trait, at the temperature levels of +8°C and -2°C, the highest values were observed in the TN-02-6734 and Bahman genotypes, respectively, and the lowest values were observed in the Nosrat and TN-02-4952 genotypes, respectively. The highest and lowest fructan contents were observed in the 'Dasht' and 'TN-02-6297' genotypes at 8°C, respectively. At -2°C, the highest and lowest fructan contents were found in the 'Reyhan' and 'TN-02-6297' genotypes, respectively. The polymorphic information content varied from 0.59 at marker Bmag0077 to 0.82 at marker Bmag0032. Gene diversity ranged from 63.0 to 0.84 with an average of 0.74. The major allele frequency ranged from 0.21 to 0.52. The population structure analysis indicated the presence of two subpopulations. Mixed linear model (MLM)-based association analysis, considering Q (Population structure deta) and K (Kinship matrix) matrices as covariates, revealed a significant association between 5 SSR makrers and studied traits (P-value<0.05). A total of 3 loci were significantly associated with proline trait under -2°C conditions (Bmag0518, Bmag0211, Ebmac0674), one locus was significantly associated with proline trait under +8°C conditions (Bmag0223), and one locus was significantly associated with fructose trait under + 8°C conditions (Bmag0173). No significant marker was identified for the fructan trait under -2°C conditions. Based on the obtained results the markers including Bmag0518, Bmag0211, Ebmac0674, Bmag0223, and Bmag0173 can be used as the best markers for genetic analysis and marker assisted selection in barley cold tolerance breeding programs.