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

• Published in: Rice (New York, N.Y.) Vol. 9; no. 1; p. 52
• Main Authors: De Leon, Teresa B., Linscombe, Steven, Subudhi, Prasanta K.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-10-2016; Springer Nature B.V
• Subjects: Agriculture; Biomedical and Life Sciences; Genetic linkage; Genotype & phenotype; Life Sciences; Original; Original Article; Plant Breeding/Biotechnology; Plant Ecology; Plant Genetics and Genomics; Plant Sciences; Plant tolerance; Rice; Salinity; Selective breeding; Salt tolerance; Candidate gene; Quantitative trait locus; Single nucleotide polymorphism; Genotyping by sequencing; Oryza sativa
• ISSN: 1939-8425; 1939-8433; 1934-8037
• DOI: 10.1186/s12284-016-0125-2

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.