Soil salinity is becoming a growing issue nowadays, severely affecting the world’s most productive agricultural landscapes. With intersecting and competitive challenges of shrinking agricultural lands and increasing demand for food, there is an emerging need to build resilience for adaptation to anticipated climate change and land degradation. This necessitates the deep decoding of a gene pool of crop plant wild relatives which can be accomplished through salt-tolerant species, such as halophytes, in order to reveal the underlying regulatory mechanisms. Halophytes are generally defined as plants able to survive and complete their life cycle in highly saline environments of at least 200-500 mM of salt solution. The primary criterion for identifying salt-tolerant grasses (STGs) includes the presence of salt glands on the leaf surface and the Na⁺ exclusion mechanism since the interaction and replacement of Na⁺ and K⁺ greatly determines the survivability of STGs in saline environments. During the last decades or so, various salt-tolerant grasses/halophytes have been explored for the mining of salt-tolerant genes and testing their efficacy to improve the limit of salt tolerance in crop plants. Still, the utility of halophytes is limited due to the non-availability of any model halophytic plant system as well as the lack of complete genomic information. To date, although Arabidopsis (Arabidopsis thaliana) and salt cress (Thellungiella halophila) are being used as model plants in most salt tolerance studies, these plants are short-lived and can tolerate salinity for a shorter duration only. Thus, identifying the unique genes for salt tolerance pathways in halophytes and their introgression in a related cereal genome for better tolerance to salinity is the need of the hour. Modern technologies including RNA sequencing and genome-wide mapping along with advanced bioinformatics programs have advanced the decoding of the whole genetic information of plants and the development of probable algorithms to correlate stress tolerance limit and yield potential. Hence, this article has been compiled to explore the naturally occurring halophytes as potential model plant species for abiotic stress tolerance and to further breed crop plants to enhance salt tolerance through genomic and molecular tools.

The escalation of harmful pollutants, including heavy metals, due to industrialization and urbanization has become a global concern. To mitigate the negative impacts of heavy metal stress on germination and early plant development, growth regulators have been employed. This study aimed to evaluate the response of mung bean (Vigna radiata L.) to zinc stress in the presence of brassinosteroids, focusing on seedling growth and antioxidant potential. Mung bean seedlings were treated with three concentrations of 24-epibrassinolide (EBL) (0.1, 0.2, and 0.4 PPM) with or without zinc. Results demonstrated that the application of brassinosteroids, combined with zinc stress, significantly enhanced germination percentage (about 47.06, 63.64, and 120%), speed of germination (about 39.13, 50, and 100%), seedling growth (about 38% in case of treatment combined 0.4 PPM 24-EBL and 1.5 mM ZnSO₄) and seedling vigor index (204% in case of treatment combined 0.4 PPM 24-EBL and 1.5 mM ZnSO₄) compared to zinc-treated seedlings alone after 24 h. The activities of antioxidative enzymes (catalase, ascorbate peroxidase, polyphenol oxidase, and peroxidase) and total soluble protein content decreased, while lipid peroxidation and proline content exhibited a significant increase (p ≤ 0.05) when compared to the control. However, the negative effects induced by heavy metal stress on these parameters were significantly mitigated by EBL application. Notably, the most effective concentration of EBL in overcoming zinc stress was found to be 0.4 PPM. These findings underscore the potential of exogenously applied brassinosteroids as a valuable tool in phytoremediation projects by ameliorating heavy metal stress.

In India, systematic wheat yellow rust survey and pathotype (race) analysis work began in 1930. However, information on population structure and genetic diversity of yellow rust pathogen has not been available. To address this, we conducted studies on population structure and genetic diversity of Puccinia striiformis f. sp. tritici (Pst) pathotypes using 38 simple sequence repeat primer-pairs. Bayesian assignment and discriminant analysis of principal components indicated the presence of two distinct Pst subpopulations (Pop1 and Pop2) along with 37.9% admixed pathotypes. The unweighted pair-group method with arithmetic mean also categorized these pathotypes into two major clusters. Principal coordinates analysis explained 20.06 and 12.50% variance in horizontal and vertical coordinates, respectively. Index of association (I _A ) and the standardized index of association ([ ]) values showed that Pst subpopulations reproduced asexually (clonally). In total, 102 alleles were detected, with the expected heterozygosity (H _exp ) per locus ranging from 0.13 to 0.73, with a mean of 0.47. The average polymorphic information content value of 0.40 indicated high genetic diversity among pathotypes. Analysis of molecular variance revealed 12% of the total variance between subpopulations, 11% among the pathotypes of each subpopulation, and 77% within pathotypes. A significant moderate level of genetic differentiation (F _ST = 0.122, P < 0.001) and gene flow (N _m = 1.80) were observed between subpopulations. The Pst virulence phenotypes showed a weak positive correlation (R ² = 0.027, P < 0.02) with molecular genotypes.