Mitra Shahidi-zandi, Ghasem Mohammadi-Nejad *1, Somayeh Sardouei-Nasab, Maryam Dorrani-Nejad, Shokoofeh Khandani, Malihe Rahimi-Sadegh
Abstract: (8 Views)
Introduction and Objective: The ever-increasing growth of the world's population and the location of many parts of wheat cultivation areas in adverse and tense climates have increased the need toimprove production and cultivate high-yielding, resistant cultivars. Bread wheat (Triticum aestivum L.) is one of the most important crops in the world and Iran. It serves as the primary source of carbohydrates for approximately half of the global population and is cultivated in many countries. Around 20% of irrigated lands in dry and semi-dry regions of the world face salinity problems, which are worsening due to climate change and reduced precipitation. In Iran, approximately 24 million hectares of land are affected by varying degrees of salinity. Salt stress reduces vegetative and reproductive growth, leading to decreased wheat yield. Developing and improving salt-tolerant wheat varieties for different climatic regions of the country is the main solution to overcome the issue of salinity and prevent yield losses and significant damage to farmers in affected areas. Identifying chromosomal regions related to agronomic traits under salt stress is crucial for improving salt tolerance in wheat. In this context, research utilizing molecular markers to precisely identify the mechanisms involved in salt tolerance in crops is of great importance. The aim of this study was to assess the population structure and identify genomic regions controlling agronomic and morpho-physiological traits under salt stress, using 17,093 SNP markers and 274 wheat genotypes.
Materials and Methods: A total of 268 international bread wheat genotypes, obtained from the Institute of Plant Genetics and Crop Plant Research (IPK) in Germany, along with 6 control varieties (both salt-tolerant and salt-sensitive) including Tritipyrum, Superhead, Kavir, Sabalan, Karchia, and Gaspard, were evaluated during the 2020-2021 growing season in an augmented design with 3 blocks at the research farm of the Plant Production Technology Research Institute, Shahid Bahonar University of Kerman. To apply salt stress, irrigation with saline water began at the tillering stage with a salinity level of 8 dS/m. It was progressively increased by 1 dS/m with each irrigation cycle until it reached 12 dS/m, continuing until the physiological maturity of the plants. Physiological traits measured included carbon dioxide, stomatal conductance, photosynthesis rate (measured using a photosynthesis meter: ADC Bio Scientific Limited, UK), as well as morphological and agronomic traits including days to heading, days to maturity, flag leaf width, plant height, number of the fertile spike, grain weight per plant, number of grains per plant, number of grains per unit area, thousand-grain weight, biological yield, and grain yield during the entire growth period. Genotyping was performed using a 9K single nucleotide polymorphism (SNP) array at TraitGenetics GmbH, Germany. SNP markers were filtered based on an allele frequency threshold of 0.01 and a missing genotype rate higher than 0.05 to reduce the likelihood of false positives. Population structure analysis and precise categorization of the genotypes into appropriate subpopulations were carried out using the LEA package in R. The optimal number of subpopulations (K) was determined to be 5, after testing a range of 1 to 10. Marker-trait association (MTAs) analysis between the phenotypic data and SNP markers was performed using the TASSEL software and the General Linear Model (GLM) method. The significance threshold was determined by utilizing Ji and Li's method, where the error rate was calculated based on the formula for effective independent tests (n). The LOD score of 3.6 was used as the significance threshold. A total of 17,093 SNP markers were used for population structure analysis and comprehensive genome-wide association study (GWAS).Results: The number of subpopulations (K) was tested from 1 to 10, with an optimal K value of 5 determined for this dataset. According to the GWAS results, a total of 104 marker-trait associations (MTAs) were identified for various traits. The number of MTAs identified in the D genome was much lower than in the A and B genomes. Specifically, the A genome contained 39 MTAs, the B genome contained 49 MTAs, and the D genome contained only 16 MTAs. This discrepancy is likely due to the relatively low genetic diversity and limited gene flow in the D genome. Among the traits studied, the number of days to spike emergence showed the highest number of MTAs, with 21 MTAs identified. In contrast, traits such as photosynthesis rate, carbon dioxide, and flag leaf width were each found to have only one MTA, the lowest number of marker-trait associations among all the traits studied. The markers Jagger_c4412_265, BobWhite_c5694_120, and BS00088733_51 were associated with more than one phenotypic trait, suggesting the potential presence of pleiotropic effects or linkage between loci controlling multiple traits. These markers can be used to simultaneously improve several traits and thus enhance wheat performance under salt stress conditions.
Conclusions: The present study provides valuable results for the identification of candidate genes and a better understanding of the mechanisms of tolerance to salt stress in wheat breeding programs.
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