Identification of single nucleotide polymorphisms for salinity tolerance at seedling stage in rice (Oryza sativa L.)
2012
Thein, S.Z.M. | Diaz, M.G.Q. | Hernandez, J.E., Philippines Univ. Los Banos, College, Laguna (Philippines) | Gregorio, G.B. | Thomson, M.J. | Singh, R.K., International Rice Research Inst., DAPO Box 7777, Metro Manila (Philippines). Plant Breeding, Genetics and Biotechnology Div.
Rice is sensitive to salinity, however, wide spectrum of rice genotypes respond to salinity differently and genes involved in salinity tolerance serve as candidate genes. There are novel genes hidden in the primary rice gene pool to enhance rice performance in saline prone areas. The most common form of genetic variation within natural populations in single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels). Thus, the authors made an effort to investigate such variation in key responsive genes from diverse germplasm. Three hundred rice genotypes from different geographic regions were screened for salinity tolerance at seedling stage and physiological parameters such as salt evaluation score (SES), Na, K concentration in shoot and chlorophyll content of fourth leaves were determined. Genome wide genotyping was performed during Illumina Goldengate Genotyping Assay. In this case, the genotypes were assayed using 384 indica x indica SNP set which was developed from 44K SNP chip by S. McCouch et al Cornell University. Candidate gene annotation were conducted to find the candidate genes underlying QTL flanked by the genetic markers of mapped QTL of mapping population in several studies. EcoTILLING method was performed to detect SNPs existing in rice germplasm at genes of interest. SNPs related to salinity tolerance among diverse genotypes were identified from EcoTILLING, sequencing and OryzaSNP database. It was observed that Na toxicity, K/Na in shoot and chlorophyll content of fourth leaves were significantly correlated with SES or salinity tolerance score.Using 384 indica x indica SNP set, the authors were able to classify the genotypes according to its subspecies. The authors could identify the candidate genes underlying within target QTLs. SNPs linked with salinity tolerance were investigated by employing EcoTILLING, sequencing and OryzaSNP database. Those SNPs will be used as markers to map candidate genes related to salinity.
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