Mapping of genes controlling secondry metabolits in barley (Hordeum vulgare L.) under salinity stress

Introduction Barley (Hordeum vulgare L.) is one of the four important cereals in the world. Soil salinity is one of the major barriers to the production of important agricultural products. Crops are one of the most important factors affecting the level of secondary metabolites present in plants under protective conditions. Secondary metabolites help plants to survive and survive external disturbances (such as pests and pathogens) and stress environmental conditions (such as drought or unfavorable soil conditions). Many agriculturally important traits are controlled by many genes and are known as quantitative. The regions within genomes that related to genes associated with a particular quantitative trait are known as quantitative trait loci (QTLs). The identification of QTLs based only on classic phenotypic evaluation is not possible. A major breakthrough in the characterization of quantitative traits that created opportunities to select for QTLs was initiated by the development of DNA markers. One of the main uses of DNA markers in research has been in the providing of linkage maps. Linkage maps have been used for identifying chromosomal regions that contain genes controlling simple traits and quantitative traits using QTL analysis.   Materials and methods In order to locate secondrey metabolits of salinity tolerant genes in barley in vegetative and reproductive stages, 106 F8 lines caused Badia and Kavir crosses was used and cultivated as augumented design.This research was conducted in the research greenhouse of Gonbad Kavous University in 2019 and 2020. The seeds of 106 lines as well as were parents planted in the pot. For salinity stress, the lines were kept normal until the end of the vegetative phase and then irrigated with 16 dS.m-1 in the reproductive stage. At the end of grain filling period, leaf samples were taken from flag leaf and secondary metabolites of sugar, phenol, catalase and peroxidase were measured. The linkage map was provided with markers with clear and consistent Mendelian segregation markers (152 SSR markers, 72 ISSR alleles, 7 IRAP alleles, 29 CAAT alleles, 27 Scot alleles and 15 iPBS alleles). Four methods of mapping CIM, ICIM, STMIM and STPLM were used to identify the control QTLs and estimate the effect genetic of one of them.   Results Gene loci were detected for the sugar content using CIM, ICIM and STPLME in the region of chromosome 1 at 26 cM and near the Bmaq0211. Also, for the peroxidase effective loci on chromosome 3 were identified in 44 cM flanked Bmac0067 and HVM33. The SMIM method was identified at position 118 cM between ISSR13-1 and ISSR16-4 for the sugar content, phenol, peroxidase of a gene locus on chromosome 4.   Conclusions qSUG-4 QTLs (sugar content on chromosome 4) with a coefficient of 20.2 as well as qPHE-1 and qPHE-2 QTLs (phenol content on chromosomes 1 and 2) with coefficients of determination of 21.3, 29.21 and qPER-1, qPER-4b, qPER-5, qPER-7 (peroxidase on chromosomes 1, 4, 5 and 7) are a siutable candidate for marker-assisted selection programs in the barley recombinant line population