• Title of article

    Genetic diversity analysis of recombinant inbred lines of rice (Oryza sativa L.) using microsatellite markers

  • Author/Authors

    Danesh Gilevaei ، Maryam - University of Guilan , Danesh Gilevaei ، Maryam - University of Guilan , Samizadeh Lahigi ، Habibollah - University of Guilan , Samizadeh Lahigi ، Habibollah - University of Guilan , Rabiei ، Babak - University of Guilan , Rabiei ، Babak - University of Guilan

  • Pages
    12
  • From page
    42
  • To page
    53
  • Abstract
    Estimation of genetic diversity is an important factor in germplasm conservation and characterization. In rice breeding programs, genetic diversity information on specific regions of genome can be very useful for the application of marker assisted selection (MAS) and for gene mapping. A total of 152 rice lines were considered for breeding programs using microsatellites (SSR) technique. The total number of polymorphic alleles was 206 with an average of 2 alleles per SSR locus. The PIC value for the SSR loci ranged from 0.479 to 0.5 with an average of 0.498. The highest PIC value was observed for primers RM60, RM6832, RM3838 and RM592. RM1, RM237, RM154 and RM84 had the lowest PIC values in a decreasing order. Nei’s gene diversity ranged from 0.479 to 0.5 with an average of 0.498. Using Shannon’s diversity index, a mean genetic diversity of 0.691 was obtained. The lowest diversity was found for RM1, RM237, RM246, RM154 and RM279 in an ascending order and 27 SSR markers had the highest value (0.693). Cluster analysis using the UPGMA method based on Jaccard’s similarity coefficient classified all lines into three clusters. Association analysis by general linear model (GLM) method revealed that 62 SSR markers showed a significant association with 10 studied morphological traits. Twenty eight markers were associated with more than one trait. These may be further investigated in rice breeding programs to be introduced as informative and useful markers. Results showed the potential of SSR markers to identify rice lines at the DNA level. The information will help the selection of lines to serve for efficient rice breeding programs.
  • Keywords
    Association analysis , Cluster analysis , Genetic variation , Rice , SSR
  • Journal title
    Iranian Journal of Genetics and Plant Breeding
  • Serial Year
    2018
  • Journal title
    Iranian Journal of Genetics and Plant Breeding
  • Record number

    2464546