In silico mining and characterization of novel SSRs and candidate genes within QTLs controlling grain protein contents using MPSS signatures and micro array analysis in rice (Oryza sativa L.)

Protein content in rice grain (Oryza sativa L.) is an important trait from human nutrition perspective, particularly for those having rice as a main food in daily life. Several QTLs identified for the grain protein content (GPC) needs refinement and further genetic dissection to truly understand the trait. In this study we have searched for the putative candidate genes underlying five known QTLs, (AQT033, AQT034, AQT037, AQT039 and AQT040) governing high grain protein content in rice. Important putative candidate genes encoding glutelin precursor, peptide transporter, aminotransferases etc were found underlying selected QTLs. The in silico expression analysis of candidate genes by massively parallel signature sequence (MPSS) revealed very strong expression for gutelin precursor gene and higher expressions for phosphoesterase, peptide transporter, aminotransferases and calmudulin dependent protein kinase genes. The tissue library information revealed their higher expression in pollen, stigma, immature panicles, germinating and developing seed tissues at reproductive stage. Further characterization of the candidate genes by digital microarrays in the reproductive development stage resulted in identification of genes showing higher seed specific expression. Further, we assessed the abundance of simple sequence repeats (SSRs) in the candidate genes as well as genomic, ESTs and cDNA sequences underlying QTLs. A total of 483 SSRs including 113 SSRs in the genomic, 133 in the cDNA and 237 SSRs in the EST sequences were identified. According to sequence length, the potentially variable Class II SSRs were the most commonly found microsatellites, followed by hyper variable Class I markers. Seventeen QTL specific microsatellite markers have been developed from the genomic, cDNA and EST regions. The identification of novel microsatellite markers and putative candidate genes based on MPSS signatures and digital micro arrays in this study will help in the development of gene specific markers for marker-assisted mapping as well as discovery of novel GPC related genes in rice.