reductase protein. This result also supports our hypothesis that other gene family members can compensate for the mutation. Despites these observations, we can not rule out the possibility that the absence of phenotype is due to non-optimal environmental conditions [44]. In summary, we identified phenotypic changes in rice lines carrying mutations in 10 out of 20 unique genes or genes that were the most predominantly light-induced members of their respective families. In contrast, we discovered only one phenotypic change among the lines carrying mutations in the 17 other genes that either showed inconsistently light-induced expression among different microarray data sets or were not the predominantly light-induced members of their respective gene families (Table S3). Microarray data were very useful as criteria for prioritizing candidate genes for functional analyses. Consideration of the expression patterns of all the genes within a gene family is an effective way to approach study of the functions of gene family members [14]. Validation of Our Strategy using Arabidopsis Functional Profiling Data Functional profiling of genes related to the phytochrome- mediated signaling pathway in Arabidopsis was recently carried out [3]. We used this data set to further test the usefulness of our method (see Materials and Methods). Thirty two genes were selected for this functional profiling analysis. Of these, mutants in seven genes displayed statistically significant photomorphogenic phenotypes. Except for one gene (At2g46970) whose gene expression profiling data was not available, we found that six genes were either unique sequences or the predominantly expressed gene family member in the red light. In contrast, mutations in the remaining 25 genes showed less significant photomorphogenic phenotypes; thirteen of them displayed mild or severe defects in photoresponsiveness and 12 did not showed distinguishable phenotypes (Figure S6) [3]. Of these, 10 genes were not the predominantly expressed gene family member in the red light whereas 13 genes (except two genes; At3g21550 and At3g21330 whose gene expression profiling data was not available) were either unique sequences or the predominantly expressed gene family member in the light (Figure S6). Thus, this functional profiling analysis in Arabidopsis also indicates that predominantly expressed gene family members as well as unique genes are good targets for functional validation. Identification of Relationships among 13 Biochemical Pathways Mutant phenotypes clearly suggest functions for targeted genes and also for the pathways those genes are associated with. Therefore, understanding relationships among multiple pathways containing mutants defective in the plant’s response to light will help us elucidate the light response. To do this, we identified genes among various pathways that were co-expressed with the 10 genes for which we had identified mutant phenotypes in this study. We found that ten pathways (http://www.gramene.org/pathway/) involved 7 of the genes for which we had identified mutants (Figure 4; Table S4). Sixty nine genes in these 10 pathways were selected as described in Materials and Methods. Additionally, three single-step reactions unlinked to any of these pathways but involving the other three genes for which we identified mutant phenotypes in this study, U4 (Os02g57030), U5 (Os03g04470), and Ca1 (P2-1, Os1g45274) were also included in this analysis (see Table 2). All together, 72 genes involved in the 10 pathways and three reactions were selected for hierarchical clustering analysis (Table Functional Analysis of Singleton and Gene Families S4). Then, we selected 10 datasets with which to carry out the analysis (Table S4): log2 fold change values of NSF45K light vs. dark and four different types of light vs. dark datasets generated by BGI/Yale array [49], and log2 fold change values of five different tissues vs. cultured cells [50]. We selected candidate genes in each pathway that are unique or are the predominantly light-induced gene family member (except several steps not represented by predominantly light-induced gene family members). We found that gene expression patterns of 67 out of the 72 genes are light- inducible in at least two of the light treatments (Figure 4). Fifty-five genes have GO terms in the cellular component category and 46 of them have a chloroplast GO term in the cellular component category. Seven genes are predicted to have role in the mitochondrion (Figure 4). Most of the genes used for the clustering analysis are predicted to perform their light response-related function in chloroplasts or mitochondria (Figure 4). As a result of the hierarchical clustering analysis we identified 10 gene clusters (Figure 4). As has been previously reported [50,51,52], co- expression analysis is useful for revealing functionally coherent groups of genes. We next looked for relationships among different pathways by utilizing Cytoscape software to analyze the results we obtained from our co-expression analysis (see Materials and Methods). Cytoscape is an open source software for integrating biomolecular interaction networks with high-throughput expression data [51]. The results of this analysis are shown in Figure S7. First, cluster III (purple lines in Figure 4 and Figure S7) contained 3 components of PSI, one of PS II, three from the photorespiratory pathway, one from the ammonia assimilation pathway, and one from the chlorophyll biosynthetic pathway. Of these, ferredoxin-dependent glutamine:2-oxoglutarate aminotrans- ferase (Fd-GOGAT, U11) couples with glutamine synthetase 2 (GS2) for assimilating ammonium produced by photorespiration [33,52]. In Figure 4 and Figure 5, the Fd-GOGAT gene (U11), which generates glutamate at step 2 of the ammonia assimilation pathway is co-expressed with the PS I and PS II components Os08g44680, Os12g23200, Os07g25430, and Os01g64960. GS2 (OS04g56400) at step 1 of this pathway is co-expressed with other PS I and PS II components (Os09g30340 and Os08g10020). PS I and PS II supplies ATP for the reaction of GS2 and reduced ferredoxin (Fdrd) for Fd-GOGAT [53]. This dependency of the ammonia assimilation pathway on photosynthesis is supported by the co-regulation of several PS I and PS II components with two genes in the ammonia assimilation pathway (Figure 4, Figure 5, and Figure S7). The photorespiratory pathway is known to be tightly correlated with nitrogen cycles [54]. Co-expression patterns of genes encoding three early steps of the photorespiratory pathway with the Fd-GOGAT gene suggest a close relationship of photorespira- tion with the ammonia assimilation pathway (purple lines in Figure 4, Figure 5 and Figure S7). This makes sense because the ammonia assimilation pathway plays a role in preventing loss of ammonia, which is generated from step 6 of the photorespiratory pathway by refixing it to glutamate [53,55,56]. Furthermore, the resulting amino acid (i.e. glutamate) reacts with glycine to synthesize glutathione in the peroxisome, suggesting that this pathway is important for protecting photosynthetic apparatus (e.g. PS II) from toxins such as free radicals [55]. Also, co-regulation of genes in the three early steps of the photorespiratory pathway with several PS I and II components suggests that oxygen generated by photosynthesis triggers the photorespiration pathway [57,58]. Co- regulation of genes involved in photosynthesis, ammonia assim- ilation and photorespiration can explain their coordinated functions [56]. PLoS Genetics | www.plosgenetics.org 9 August 2008 | Volume 4 | Issue 8 | e1000164