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, 9 (1), 52

Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza Sativa L.) Using a High-Density GBS-Based SNP Linkage Map

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Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza Sativa L.) Using a High-Density GBS-Based SNP Linkage Map

Teresa B De Leon et al. Rice (N Y).

Abstract

Background: Salinity is one of the many abiotic stresses limiting rice production worldwide. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated to salinity tolerance. However, due to large confidence interval for the position of QTLs, utility of reported QTLs and the associated markers has been limited in rice breeding programs. The main objective of this study is to construct a high-density rice genetic map for identification QTLs and candidate genes for salinity tolerance at seedling stage.

Results: We evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K+ concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance mechanisms.

Conclusion: The saturation of SNP markers in our linkage map increased the resolution of QTL mapping. Our study offers new insights on salinity tolerance and presents useful candidate genes that will help in marker-assisted gene pyramiding to develop salt tolerant rice varieties.

Keywords: Candidate gene; Genotyping by sequencing; Oryza sativa; Quantitative trait locus; Salt tolerance; Single nucleotide polymorphism.

Figures

Fig. 1
Fig. 1
Frequency distribution of Bengal/Pokkali F6 RIL population for traits related to seedling salinity tolerance. Na+ Conc., Na+ concentration; K+ conc., K+ concentration; NaK, Na+/K+ ratio; SIS, log transformed salt injury score; CHL, chlorophyll content measured by SPAD-502 unit; DWT, dry weight; SHL, shoot length; RTL, root length; SRR, Shoot length to root length ratio
Fig. 2
Fig. 2
Molecular genetic map showing the positions of QTLs for nine traits investigated under salt stress. Linkage and QTL mapping were implemented in ICIM QTL Mapping 4.0 using 9303 GBS-SNP markers in 187 Bengal/Pokkali F6 RILs. Chromosome regions that are dark indicate the saturation of markers while regions that are white indicate the absence of marker placed in those segments. Genetic distance in centimorgan was determined by Kosambi map function. Each arrow represents a single QTL for a particular trait
Fig. 3
Fig. 3
Functional classification of annotated candidate genes delimited by additive QTLs for salinity tolerance. a classification by biological class; b classification by molecular function; c classification by protein class

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