Identification of genes and molecular markers related to rice yield and agronomic traits under drought stress condition

Document Type : Research Paper

Authors

1 M.Sc. Student of Genetics and Plant Breeding, Department of Agronomy and Plant Breeding, Facuulty of Agricultural Sciences, University of Guilan, Rasht, Iran.

2 Associate Professor, Department of Agronomy and Plant Breeding, Facuulty of Agricultural Sciences, University of Guilan, Rasht, Iran.

3 PhD of Biotechnology, Department of Biotecnology, Facuulty of Agricultural Sciences, University of Guilan, Rasht, Iran.

Abstract

Drought is one of the most important limiting factors for economic produce crops especially rice in the world. In order to identify related markers to yield and agronomic traits under drought stress condition, 40 recombinant inbred lines F9 (RILs) derived from IR28 and Shah-Pasand varieties evaluated at Rice Research Institute of Iran (Rasht) in the spring and summer 2018, as randomized block design with three replications. In this regard, 110 SSR and EST-SSR markers were assessed on parents of population and identified 41 markers had proper polymorphism between two parents. According to the regression analysis results, 24 and 22 significant markers identified under normal and drought stress conditions respectively. The maximum adjusted (R2) under normal and drought stress conditions were assigned to RM3496 linked to days to flowering (24.8%) and RMES6-1 linked to panicle exsertion (28.1%), respectively. Two markers RM211 and RM6697 had the most number of significant relationship with different traits including panicle length, flag leaf length, number of filled grains per panicle, the total number of grain per panicle, and weight of filled grain per panicle under non-stress and drought stress conditions respectively. According to the bioinformatics searches, the maximum gene expression pattern under drought stress condition was related to gene with accession code LOC_Os01g43370. The identified informative markers and the detected genes by bioinformatics approaches after validation can be utilized in marker assisted-selection (MAS) or gene transfer approaches for improving rice yield and tolerance to drought stress.

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References

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