Mutant Resources in Rice for Functional Genomics of the Grasses

Rice (Oryza sativa) is the reference genome for the grasses, including cereals. The complete genome sequence lays the foundation for comparative genomics to the other grasses based on genome structure and individual gene function (Devos, 2005; International Rice Genome Sequencing Project, 2005). The basic complement of monocot genes in rice can be examined by functional genomics studies because of the many advantages of rice as a system for genetic analysis, as well as the worldwide development of resources. The analysis of mutants by forward and reverse genetics approaches is an effective way to study gene function. Knockout (KO) mutations, which abolish gene expression and display a phenotype, provide a direct causal relationship between the gene sequence and its biological function. However, not all gene mutations display a KO mutant phenotype, primarily due to gene redundancy, because plant genomes have been shown to have large segmental genomic duplications, as well as tandem duplications of gene families (Yu et al., 2005; Sterck et al., 2007). In many cases, the redundancy is partial or unequal, due to overlap in expression of duplicated genes (Briggs et al., 2006), or the gene activity is required only under some specific conditions, such as biotic/abiotic stresses where the mutant phenotype can be observed. The use of molecular tags or DNA insertions, such as transposons or T-DNA, is favored for mutations because their genome positions can be easily monitored to determine the correlations between tagged genes and phenotypes. The limitations in identifying gene functions by KO mutations alone are resolved by employing heterologous DNA insertions with engineered properties to monitor the expression of tagged genes using entrapment vectors or to alter the expression of tagged genes using activation tagging (Pereira, 2000). The International Rice Functional Genomics Consortium, combined with many national programs, set a goal to generate mutant resources toward discovering the function of all rice genes, primarily through reverse genetics approaches (Hirochika et al., 2004). This resource update describes the generation of over 200,000 insertion flanking sequence tags (FSTs), which tag two-thirds of the predicted protein-coding genes, with one-half of the protein-coding genes estimated to have knockout mutations. The insertion sequences comprise the endogenous Tos17 retrotransposon showing the highest insertion rate in exons, as well as engineered maize (Zea mays) Ds/dSpm transposons and Agrobacterium T-DNA, which function as enhancer trap (ET), gene trap (GT), or activation tags (ATs). In addition, chemical and physical mutagen-derived mutant populations have been developed that are available for TILLING and other high-throughput screens. The extensive number and variety of mutant resources described here for rice are very amenable for dissecting the functions of genes of interest in other grasses. With the sequencing of plant genomes, it was recognized that insertion mutants indexed by their position in the genome would be very suitable for systematic analysis of annotated genes by reverse genetics (Parinov and Sundaresan, 2000). Arabidopsis (Arabidopsis thaliana) genome sequence-indexed mutants can now be found in databases (http://signal.salk.edu/Source/AtTOME_Data_Source.html), which comprise a total of 379,674 inserts tagging 30,280 of the predicted 33,003 genes. In rice, the two-component maize transposon Ac-Ds (Chin et al., 1999; Upadhyaya et al., 2002; Greco et al., 2003; Kolesnik et al., 2004) and En/Spm-dSpm (Greco et al., 2004; Kumar et al., 2008) systems have been well characterized, and good genetic selection schemes have been developed to select for transpositional activity useful for large-scale mutagenesis (Hirochika et al., 2004; Zhu et al., 2007). In addition, the endogenous rice Tos17 retrotransposon is active in specific genotypes and conditions and is an effective insertion mutagen in the rice genome (Miyao et al., 2003). The development of efficient protocols for rice transformation has helped in the generation of a large number of transgenic rice plants bearing low-copy T-DNA insertions (Jeon et al., 2000; Sallaud et al., 2003). In addition to KO or loss-of-function mutagenesis, the engineering of transposon and T-DNA constructs offers immense flexibility in fashioning the insertion sequences to detect adjacent gene expression or activate the expression of adjacent genes by activation tagging, resulting in gain-of-function mutations. These modified insertions can contribute to gene function discovery of redundant genes and those having lethal mutant effects. To facilitate the analysis of genes based on their expression patterns, GT and ET constructs have been designed that carry a reporter gene and can display the expression pattern of an adjacent trapped gene (Sundaresan et al., 1995). The reporter gene pattern in ET inserts reflects the adjacent plant gene enhancer activity, and in GT inserts the adjacent gene promoter activity. ET and GT constructs have been used in both T-DNA and Ac-Ds transposons in rice, yielding interesting gene expression patterns and entrapped genes, which support their widespread generation and use for complementing KO mutagenesis (Hirochika et al., 2004; An et al., 2005). T-DNA AT populations have been developed using vectors with cauliflower mosaic virus 35S enhancer multimers, the inserts characterized by FSTs and phenomic data for forward and reverse genetics screens (Jeong et al., 2002; Chern et al., 2007; Hsing et al., 2007; Wan et al., 2009). Recently, an Ac-Ds AT system has also been developed (Qu et al., 2008) using convenient markers for selection of multiple transposants from a few starter transformed lines. In both these AT systems, activation of adjacent genes is observed, albeit 52.7% of the T-DNA lines and 20.8% of the Ds tags activate adjacent genes, which can be as far away as 10 kb from the AT enhancer. Chemical agents, such as ethyl methanesulfonate (EMS), methyl nitrosourea, and diepoxybutane, or physical methods like fast-neutron, γ-rays, and ion beam irradiation can cause a high density of mutations that can saturate the genome (Hirochika et al., 2004). Mutant populations have been generated in rice in which the point mutations can be screened by TILLING and larger deletions by PCR-based screens (Wu et al., 2005; Till et al., 2007). The IR64 (Wu et al., 2005) and the Nipponbare (Till et al., 2007) populations, as well as other unpublished populations also shown in Table I Mutant resources, contributors, and databases DEB, Diepoxybutane; EMS, ethyl methanesulfonate; CIRAD, Centre de Coopération Internationale en Recherche Agronomique pour le Développement; CNRS, Centre National de la Recherche Scientifique; INRA, Institut National de la Recherche Agronomique; IPMB, Institute of Plant and Microbial Biology; IRD, Institut de Recherche pour le Développement; IRRI, International Rice Research Institute; NIAS, National Institute of Agrobiological Sciences; POSTECH, Pohang University of Science and Technology; SIPP, Shanghai Institute of Plant Physiology and Ecology. Based on searching current project database, future plans, and subject to seed availability. Selected lines from gene-specific PCR screens. Mutant resources, contributors, and databases DEB, Diepoxybutane; EMS, ethyl methanesulfonate; CIRAD, Centre de Coopération Internationale en Recherche Agronomique pour le Développement; CNRS, Centre National de la Recherche Scientifique; INRA, Institut National de la Recherche Agronomique; IPMB, Institute of Plant and Microbial Biology; IRD, Institut de Recherche pour le Développement; IRRI, International Rice Research Institute; NIAS, National Institute of Agrobiological Sciences; POSTECH, Pohang University of Science and Technology; SIPP, Shanghai Institute of Plant Physiology and Ecology. Based on searching current project database, future plans, and subject to seed availability. Selected lines from gene-specific PCR screens. The first rice genes identified by insertional mutagenesis were with Tos17 in a forward genetics screen for viviparous mutants (Agrawal et al., 2001), and simultaneously in a reverse genetics screen for inserts in phytochrome A genes (Takano et al., 2001). With T-DNA, genes were identified by forward screens (Jung et al., 2003), by reverse genetics PCR-based screens for mutations in specific genes (Lee et al., 2003), as well as expression-based GT screens (Kang et al., 2005). Likewise, the maize Ac-Ds transposon system also yielded tagged genes (Zhu et al., 2003, 2004). Because the complete genome sequence became available, the generation of FST information of mutant populations has made the mutants more accessible to address biological questions. Table I shows the different mutant populations available and the FSTs that can be screened for inserts in genes of interest. Such queries can be made in silico, thus providing a convenient way to assess mutant populations around the world. The Ds and dSpm insertions are generated by transposition from a few starter transformed lines that can be scaled up for genome saturation and do not directly result from a regeneration process (Kolesnik et al., 2004; van Enckevort et al., 2005; Upadhyaya et al., 2006; He et al., 2007; Park et al., 2007; Qu et al., 2008). The FST resource of the endogenous Tos17 retrotransposon are generated by regeneration process in Nipponbare (Miyao et al., 2003), which also accompanies Agrobacterium transformation of T-DNA yielding additional Tos17 insertions (Piffanelli et al., 2007). The T-DNA insertions with FSTs in various genetic backgrounds comprise an extensive diverse resource (Chen et al., 2003; Sallaud et al., 2004; Jeong et al., 2006; Zhang et al., 2006; Hsing et al., 2007). The generation of insertions accompanied by a regeneration phase, such as for T-DNA and Tos17, can result in a high frequency of untagged mutations in the background that can complicate genetic analysis of the mutants (H. Leung and E. Guiderdoni, unpublished data). To alleviate this problem, genetic segregation analysis and the use of multiple mutants of the gene are useful. Transposon inserts have a much lower frequency of background mutations, leading to many genes identified by forward screens (Zhu et al., 2007), and the use of reversions that restore the wild-type phenotype is a convenient approach to prove gene-phenotype relationships. To facilitate the identification of insertion mutations in genes using available FST information, a number of project database Web sites are available as shown in Table I. In addition, functional genomics databases are available, such as RiceGE/SIGnAL (http://signal.salk.edu/cgi-bin/RiceGE), OryGenesDB (http://orygenesdb.cirad.fr), and Gramene (http://www.gramene.org), where the FST information has been collated and mutants can found for inserts in genes of interest. These databases link rice genes to other grass genes and thus direct functional queries to the rice mutant resources. Distribution of insertion positions within genic regions in rice. The three classes of insertion mutagens: endogenous Tos17 retrotransposon, Agrobacterium T-DNA, and maize cut-and-paste transposons (Ds and dSpm), shown with their insertion positions in different parts of genes with color code shown alongside. The numbers of individual insertion types in genes in relation to the total number of insertions are entered below the insertion name. Datasets from the following resources (Table I) were used: Ds, CSIRO, KRDD/GNU, OSTID, UCD; dSpm, UCD; T-DNA, CIRAD, POSTECH, RMD, SHIP, TRIM, ZJU; Tos17, CIRAD and NIAS. 500-bp upstream and downstream regions correspond to sequences upstream and downstream of the transcription unit (start site to site of termination). See Supplemental Table S1 for more information. The size of rice mutant populations generated is large and diverse to suit many functional genomics objectives in the grasses. The number of insertion mutants needed to tag every gene in rice has been estimated to be between 180,698 to 460,000 (Hirochika et al., 2004). At present, the positions of over 200,000 inserts have been determined by FSTs with KO mutations predicted for 50% of the protein-coding genes. Thus, mutants of the remaining genes are required, many of them smaller genes with a lower mutation frequency. Although the total available mutants are >2,000,000 (Table I), the cataloging of the mutants by FSTs is limiting because of the manual manipulations and costs involved. However, new methods of high-throughput sequencing of multidimensional DNA pools should be able to assess the genome positions in a more cost-effective way. In addition, the chemical/physical mutagen-derived mutants would be accessible by the next generation high-throughput genotyping technologies. For those genes still inaccessible to mutation, probably due to small size, lethality, or genome position, more directed gene-specific methods using RNAi silencing would be very useful. The following materials are available in the online version of this article. Supplemental Figure S1. Gene size and distribution of insertion mutations. Supplemental Figure S2. GO-slim molecular function categories of all tagged genes. Supplemental Figure S3. GO-slim biological process categories of all tagged genes. Supplemental Table S1. Genomic distribution and statistics of rice inserts. Supplemental Materials and Methods S1. Datasets and analysis.