Document Type : Original Article
Authors
1 M.Sc. student of Crop Biotechnology, Department of Agronomy & Plant Breeding, Faculty of Agricultural Sciences, Gonbad Kavous University, Gonbad Kavous, Iran.
2 Associated Professor of Genetic Biometrics, Department of Plant Production, Faculty of Agricultural Sciences, Gonbad Kavous University, Gonbad Kavous, Iran.
3 Assistant Professor of Soil Chemistry and Fertility, Department of Plant Production, Faculty of Agricultural Sciences, Gonbad Kavous University, Gonbad Kavous, Iran.
4 Academic member, Seed and Plant Improvement Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran.
Abstract
Background
Barley (Hordeum vulgare L.) is one of the most important cereals in the world. Drought is one of the most important abiotic stress and severely limits the production of barley around the world. Diversity is the basis of all screenings and genotypic selection also needs diversity. The use of haplotypes in the study of genetic relationships is important. This is more important when there is little indication of the power of the individual's markers, or when there are several genetic markers in the selected QTLs. Association analysis and study of the relationship between molecular markers and agronomic traits have several applications, including the possibility of studying the genetic potential of specific genotypes before phenotyping, identifying alleles related to traits in the germplasm, facilitating locating QTLs and validation of candidate genes responsible for quantitative traits. The aim of this experiment was to investigate the allelic variation, association analysis and haplotypes of continuous microsatellite markers to drought tolerance genes in the barley.
Materials and methods
The experiments were carried out as an augmented design with 96 barley genotypes along with four controls. 18 traits were evaluated on the plants. Then, to evaluate the allelic and haplotypic diversity, the genotypes were tested using five microsatellite markers related to drought tolerance. In the end, phenotypic information was compared with genotypic information, and the relationship between them was determined by linear forward regression.
Findings
The analysis of the data obtained from the markers revealed that there were 26 multivariate alleles and also an average of 3.429 alleles for each marker, with the highest number of GBMS180, GMBS183 and EBmac0755 markers with 6 alleles. The results of the PIC show the highest value of the GBMS180 marker and the lowest value of the Bmag0782 marker; the mean of PIC was also 0.6267. The genetic diversity was also between 0.7117 and 0.7602 with an average of 0.6807. The GBMS180 has the highest value and the Bmag0782 has the lowest value. Haplotype evaluation of microsatellite markers on 96 genotypes studied genotypes in fifty-eight haplotype groups, among which the third haplotype group had the most sub cluster with three genotypes. The nineteen group, which included genotype 134, with the highest yield and drought tolerant, with 5183.333 kg ha-1. The results of the coupling analysis indicated that the GMBS183-D allele was involved in controlling four traits of the number of spikes, spike weight, number of seeds per spike and yield, and had the greatest effect among other alleles on the increase or decrease in yield and its components.
Discussion
Linear regression and haplotype studies did not overlap, although the forward linear regression of alleles was studied individually and the allelic groups were able to interact with each other, but the obtained data did not have two match methods. But a comparison of the results of allelic variation was similar to linear regression and showed GMBS183, which had the highest PIC, among four attributes related to yield and its components in controlling the three traits of the number of spikes, number of seeds per spike and yield. This marker was also present in control of days to physiological reppining, which plays an important role in plant escape from the stresses, especially drought stress, and R2 is equivalent to 15.4%. This suggests that the results of linear regression match the results of the allele variation and overlap each other.
Keywords
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