Genetic Diversity Assessment of Four Rice Varieties using SNP Markers

Oumarou Souleymane, Batieno Teyioué Benoit Joseph, Baboucarr Manneh, Kwadwo Ofori and Eric Danquah
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Oumarou Souleymane: National Institute for Agricultural Research of Niger (INRAN)
Batieno Teyioué Benoit Joseph: National Institute for Agricultural Research of Niger (INRAN)
Baboucarr Manneh: National Institute for Agricultural Research of Niger (INRAN)
Kwadwo Ofori: National Institute for Agricultural Research of Niger (INRAN)
Eric Danquah: National Institute for Agricultural Research of Niger (INRAN)

European Journal of Engineering and Technology Research, 2017, vol. 2, issue 12, 17-22

Abstract: Markers assisted selection is a tool for improving the speed and efficiency of crop improvement. The identification of SNPs within the target genomic region of a QTL is necessary for efficient breeding of quantitative traits such as salt tolerance. The study was conducted to characterize parental lines using SNP markers and to identify the polymorphic SNPs for salt tolerance in QTL study of offspring. Four rice lines were evaluated under five levels of salt conditions including the control. The experimental design was a split-plot with two replications. Leaf samples were collected from four rice lines at heading stage and sent to LGC Genomics laboratory for genotyping using rice SNP platform. DNA extraction and SNP genotyping were performed using an internal protocol. The phenotypic data recorded were the visual scoring, tiller number, green leaf number, panicle number, panicle weight and dry weight. Phenotypic data were analyzed using SAS 9.2 software. The genotypic data were analyzed using MEGA6 and GGT2 software. Significant diversity was revealed among lines concerning all the phenotypic traits. Significant diversity, divergence and substitution pattern were observed among lines. 200 markers out of 1896 were polymorphic and selected for the next step.

Keywords: Rice; Lines; SNP Markers; Characterization. (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:2:y:2017:i:12:id:60504

DOI: 10.24018/ejeng.2017.2.12.504

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