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Candidate genes for drought tolerance and improved productivity in rice (Oryza sativa L.)
Authors:M S Vinod  Naveen Sharma  K Manjunatha  Adnan Kanbar  N B Prakash  H E Shashidhar
Institution:(1) Marker-Assisted Selection Lab, Department of Genetics and Plant Breeding, University of Agricultural Sciences, 560 065 Bangalore, India;(2) Biometrics and Bioinformatics Unit, International Rice Research Institute, Los Banos, Philippines;(3) Department of Agronomy, Faculty of Agriculture, University of Damascus, Damascus, Syria;(4) Department of Soil Science and Agricultural Chemistry, University of Agricultural Sciences, 560 065 Bangalore, India
Abstract:Candidate genes are sequenced genes of known biological action involved in the development or physiology of a trait. Twenty-one putative candidate genes were designed after an exhaustive search in the public databases along with an elaborate literature survey for candidate gene products and/or regulatory sequences associated with enhanced drought resistance. The downloaded sequences were then used to design primers considering the flanking sequences as well. Polymerase chain reaction (PCR) performed on 10 diverse cultivars that involvedJaponica, Indica and local accessions, revealed 12 polymorphic candidate genes. Seven polymorphic candidate genes were then utilized to genotype 148 individuals of CT9993 × IR62266 doubled haploid (DH) mapping population. The segregation data were tested for deviation from the expected Mendelian ratio (1:1) using a Chi-square test (<1%). Based on this, four candidate genes were assessed to be significant and the remaining three, as non-significant. All the significant candidate genes were biased towards CT9993, the female parent in the DH mapping population. Single-marker analysis strongly associated (<1%) them to different traits under both well-watered and low-moisture stress conditions. Two candidate genes,EXP15 andEXP13, were found to be associated with root number and silicon content in the stem respectively, under both well-watered and low-moisture stress conditions
Keywords:Candidate gene  mapping population  polymerase chain reaction  single marker analysis
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