Introduction: Salinity is one of the main obstacles to increasing crop yield. The most severe problems in soil salinity occur in arid and semiarid regions. Barley (Hordeum vulgare L.) is widely planting in the arid and semiarid regions. It is the fourth most important cereal crop worldwide, and it has a long history as a model for genetic studies. It is the most salt tolerant cereal. Salt tolerance in crop plants is a genetic and physiological complex trait and is controlled by several quantitative trait loci. Both genetic diversity and the adaptation to a broad spectrum of micro-ecological conditions including water availability, temperature, soil type and altitude have strongly influenced the development of salt tolerance in barley.
Materials and Methods: In order to identify genomic regions controlling the agro-morphological characteristics and markers linked to them under normal and salinity stress conditions, an experiment with 136 double haploid lines of barley and their parents (Nure and Tremois) was conducted based on alpha lattice design with two replications at the Agricultural Research Center of Zabol, during 2020-2021 crop year. Agronomic traits were including tiller number per plant, spike number per plant, grain number per spike, awn length, internode length, node number, plant height, 1000-grain weight and grain yield. The combined analysis of variance, correlation coefficients between the traits and descriptive statistics calculated for normal and salt stress conditions. The data were analyses by the SAS (ver. 9.2) statistical software. QTL analysis was conducted by composite interval mapping (CIM) method using QTL Cartographer v2.5 for each of the normal and stress conditions and their averages separately (with threshold value (LOD) 2.5, minimum distance 2 cM between QTL).
Result and Discussion: The combined analysis of variance indicated significant differences among the genotypes for all studied traits. This indicates high levels of genetic diversity in this population. Since the population is double haploid lines, therefore, the diversity observed in this population is often caused by additive effects. Maximum correlations were observed between grain yield with tiller number, as well as spike number per plant. The high correlation between the traits may be due to the similar loci controlling QTLs or due to their linkage. According to the table of descriptive statistics, the studied double haploids are representative of all the possible double haploids resulting from the crossing of Tremois and Nure, and the studied traits are controlled by the additive effects of genes. In total, 24 QTL loci were identified for the studied traits: 9 QTLs were obtained under normal conditions, 8 QTLs were identified under stress conditions, and 7 QTLs were identified in the average of the two conditions. These QTLs explained 8 to 16% of the phenotypic variance (R2). The LOD value ranged of 2.5 - 5.04. The highest and lowest LOD values were related to QTLs of number of seeds per spike on chromosome 2H and number of nodes under stress conditions. Regarding marker-assisted selection, the stability of QTLs across different environments and genetic backgrounds is of utmost importance. Out of the 24 identified QTLs, only the QTL associated with the thousand seed weight trait (Qtgw1H) demonstrated stability, making it suitable for marker selection. The markers identified for this trait not only exhibit close linkage with the gene responsible for the thousand seed weight trait but also possess high heritability and are easily detectable. The markers associated with stable QTLs can be utilized in future studies.
Conclusion: Based on the findings of this research, significant statistical differences were observed among all genotypes. Transgressive segregation, both high and low, was evident across all traits. Two traits, namely the number of tillers per plant and the number of spikes per plant, exhibited QTLs at the same location, indicating a linkage and correlation between these traits. Among the 7 major QTLs identified in this study, the most prominent one was associated with the number of spikes per plant (Qng2Hma) on chromosome 2H, linked with marker E42M38_235-2H, which accounted for 16% of the phenotypic variance. Only one QTL (Qtgw1H) for 1000-grain weight, linked with marker WMC1E8, was identified as a stable QTL. These genomic regions, once validated across various genetic backgrounds and environments for salinity tolerance in barley, can be utilized in marker-assisted breeding.