Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice

Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families.Author Summary: Rice, a model monocot, is the first crop plant to have its entire genome sequenced. Although genome-wide transcriptome analysis tools and genome-wide, gene-indexed mutant collections have been generated for rice, the functions of only a handful of rice genes have been revealed thus far. Functional genomics approaches to studying crop plants like rice are much more labor-intensive and difficult in terms of maintaining the plants than when studying Arabidopsis, a model dicot. Here, we describe an efficient method for dissecting gene function in rice and other crop plants. We identified light response-related phenotypes for ten genes, the functions for which were previously unknown in rice. We also carried out co-expression analysis of 72 genes involved in specific biochemical pathways connected in lines carrying mutations in these ten genes. This analysis led to the identification of a novel set of genes likely involved in these pathways. The rapid progress of functional genomics in crops will significantly contribute to overcoming a food crisis in the near future.