Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy

Computational identification of protein-protein interactions in rice based on the predicted rice interactome network

Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network (PRIN; http://bis.zju.edu.cn/prin/) presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice (GO annotation, subcellular localization prediction, and gene expression), we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box domain-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.

Use of intercellular washing fluid to investigate the secreted proteome of the rice-Magnaporthe interaction

Early interactions between invading penetration hyphae of the pathogenic fungus Magnaporthe oryzae and rice cells occur at the apoplast, the free diffusional space outside the plasma membrane of leaves. After initial colonization, intercellular hyphae are again in intimate contact with the rice apoplast. While several studies have looked at proteomics in rice-Magnaporthe interactions, none have focused on apoplast localized proteins. We adjusted a protocol for intercellular washing fluids (IWF) to rice leaves infected with Magnaporthe oryzae for proteomic analysis. In our IWF extract, we identified several proteins associated with compatible or incompatible pathogen interactions. Three DUF26 domain proteins were identified as changing in abundance 12 h after inoculation, confirming DUF26 domain-containing proteins are among early, pathogen stress-responsive proteins induced by infection with Magnaporthe oryzae. A Magnaporthe cyclophilin, previously identified as a virulence factor was also identified in the intercellular washing fluid.

Os11Gsk gene from a wild rice, Oryza rufipogon improves yield in rice

Chromosomal segments from wild rice species Oryza rufipogon, introgressed into an elite indica rice restorer line (KMR3) using molecular markers, resulted in significant increase in yield. Here we report the transcriptome analysis of flag leaves and fully emerged young panicles of one of the high yielding introgression lines IL50-7 in comparison to KMR3. A 66-fold upregulated gene Os11Gsk, which showed no transcript in KMR3 was highly expressed in O. rufipogon and IL50-7. A 5-kb genomic region including Os11Gsk and its flanking regions could be PCR amplified only from IL50-7, O. rufipogon, japonica varieties of rice-Nipponbare and Kitaake but not from the indica varieties, KMR3 and Taichung Native-1. Three sister lines of IL50-7 yielding higher than KMR3 showed presence of Os11Gsk, whereas the gene was absent in three other ILs from the same cross having lower yield than KMR3, indicating an association of the presence of Os11Gsk with high yield. Southern analysis showed additional bands in the genomic DNA of O. rufipogon and IL50-7 with Os11Gsk probe. Genomic sequence analysis of ten highly co-expressed differentially regulated genes revealed that two upregulated genes in IL50-7 were derived from O. rufipogon and most of the downregulated genes were either from KMR3 or common to KMR3, IL50-7, and O. rufipogon. Thus, we show that Os11Gsk is a wild rice-derived gene introduced in KMR3 background and increases yield either by regulating expression of functional genes sharing homology with it or by causing epigenetic modifications in the introgression line.

Expression profile in rice panicle: insights into heat response mechanism at reproductive stage

Rice at reproductive stage is more sensitive to environmental changes, and little is known about the mechanism of heat response in rice panicle. Here, using rice microarray, we provided a time course gene expression profile of rice panicle at anther developmental stage 8 after 40°C treatment for 0 min, 20 min, 60 min, 2 h, 4 h, and 8 h. The identified differentially expressed genes were mainly involved in transcriptional regulation, transport, cellular homeostasis, and stress response. The predominant transcription factor gene families responsive to heat stress were Hsf, NAC, AP2/ERF, WRKY, MYB, and C(2)H(2). KMC analysis discovered the time-dependent gene expression pattern under heat stress. The motif co-occurrence analysis on the promoters of genes from an early up-regulated cluster showed the important roles of GCC box, HSE, ABRE, and CE3 in response to heat stress. The regulation model central to ROS combined with transcriptome and ROS quantification data in rice panicle indicated the great importance to maintain ROS balance and the existence of wide cross-talk in heat response. The present study increased our understanding of the heat response in rice panicle and provided good candidate genes for crop improvement.

Comprehensive analysis of tandem amino acid repeats from ten angiosperm genomes

BACKGROUND

The presence of tandem amino acid repeats (AARs) is one of the signatures of eukaryotic proteins. AARs were thought to be frequently involved in bio-molecular interactions. Comprehensive studies that primarily focused on metazoan AARs have suggested that AARs are evolving rapidly and are highly variable among species. However, there is still controversy over causal factors of this inter-species variation. In this work, we attempted to investigate this topic mainly by comparing AARs in orthologous proteins from ten angiosperm genomes.

RESULTS

Angiosperm AAR content is positively correlated with the GC content of the protein coding sequence. However, based on observations from fungal AARs and insect AARs, we argue that the applicability of this kind of correlation is limited by AAR residue composition and species' life history traits. Angiosperm AARs also tend to be fast evolving and structurally disordered, supporting the results of comprehensive analyses of metazoans. The functions of conserved long AARs are summarized. Finally, we propose that the rapid mRNA decay rate, alternative splicing and tissue specificity are regulatory processes that are associated with angiosperm proteins harboring AARs.

CONCLUSIONS

Our investigation suggests that GC content is a predictor of AAR content in the protein coding sequence under certain conditions. Although angiosperm AARs lack conservation and 3D structure, a fraction of the proteins that contain AARs may be functionally important and are under extensive regulation in plant cells.

Meta-analysis of the expression profiles of the Arabidopsis ESCRT machinery

The Endosomal Sorting Complex Required for Transport (ESCRT) machinery is a set of multi-protein complexes that are well conserved among all eukaryotes and mediate a remarkable array of cellular processes including late endosome/multivesicular body (MVB) formation, retroviral particle release, and membrane abscission during cytokinesis. While the molecular mechanisms underlying ESCRT function have been relatively well characterized in yeasts and mammals, far less is known about ESCRT in plants. In this study, we utilized publicly-available microarray, massively parallel signature sequencing (MPSS) and proteome data sets in order to survey the expression profiles of many of the components of the Arabidopsis thaliana ESCRT machinery. Overall, the results indicate that ESCRT expression in Arabidopsis is highly dynamic across a wide range of organs, tissues and treatments, consistent with the complex interplay that likely exists between the spatial and temporal regulation of the ESCRT machinery and the diverse array of roles that ESCRT participates in during plant growth and development.

Transcriptional dynamics during cell wall removal and regeneration reveals key genes involved in cell wall development in rice

Efficient and cost-effective conversion of plant biomass to usable forms of energy requires a thorough understanding of cell wall biosynthesis, modification and degradation. To elucidate these processes, we assessed the expression dynamics during enzymatic removal and regeneration of rice cell walls in suspension cells over time. In total, 928 genes exhibited significant up-regulation during cell wall removal, whereas, 79 genes were up-regulated during cell wall regeneration. Both gene sets are enriched for kinases, transcription factors and genes predicted to be involved in cell wall-related functions. Integration of the gene expression datasets with a catalog of known and/or predicted biochemical pathways from rice, revealed metabolic and hormonal pathways involved in cell wall degradation and regeneration. Rice lines carrying Tos17 mutations in genes up-regulated during cell wall removal exhibit dwarf phenotypes. Many of the genes up-regulated during cell wall development are also up-regulated in response to infection and environmental perturbations indicating a coordinated response to diverse types of stress.

Screening and identification of seed-specific genes using digital differential display tools combined with microarray data from common wheat

Background

Wheat is one of the most important cereal crops for human beings, with seeds being the tissue of highly economic value. Various morphogenetic and metabolic processes are exclusively associated with seed maturation. The goal of this study was to screen and identify genes specifically expressed in the developing seed of wheat with an integrative utilization of digital differential display (DDD) and available online microarray databases.

Results

A total of 201 unigenes were identified as the results of DDD screening and microarray database searching. The expressions of 6 of these were shown to be seed-specific by qRT-PCR analysis. Further GO enrichment analysis indicated that seed-specific genes were mainly associated with defense response, response to stress, multi-organism process, pathogenesis, extracellular region, nutrient reservoir activity, enzyme inhibitor activity, antioxidant activity and oxidoreductase activity. A comparison of this set of genes with the rice (Oryza sativa) genome was also performed and approximately three-fifths of them have rice counterparts. Between the counterparts, around 63% showed similar expression patterns according to the microarray data.

Conclusions

In conclusion, the DDD screening combined with microarray data analysis is an effective strategy for the identification of seed-specific expressed genes in wheat. These seed-specific genes screened during this study will provide valuable information for further studies about the functions of these genes in wheat.

Rice functional genomics research: progress and implications for crop genetic improvement

Rice is a staple food crop and has become a reference of monocot plant for functional genomic research. With the availability of high quality rice genome sequence, there has been rapid accumulation of functional genomic resources, including: large mutant libraries by T-DNA insertion, transposon tagging, and chemical mutagenesis; global expression profiles of the genes in the entire life cycle of rice growth and development; full-length cDNAs for both indica and japonica rice; sequences from resequencing large numbers of diverse germplasm accessions. Such resource development has greatly accelerated gene cloning. By the end of 2010, over 600 genes had been cloned using various methods. Many of the genes control agriculturally useful traits such as yield, grain quality, resistances to biotic and abiotic stresses, and nutrient-use efficiency, thus have potential utility in crop genetic improvement. This review was aimed to provide a comprehensive summary of such progress. We also presented our perspective for future studies.

Synergistic use of plant-prokaryote comparative genomics for functional annotations

BACKGROUND

Identifying functions for all gene products in all sequenced organisms is a central challenge of the post-genomic era. However, at least 30-50% of the proteins encoded by any given genome are of unknown or vaguely known function, and a large number are wrongly annotated. Many of these 'unknown' proteins are common to prokaryotes and plants. We set out to predict and experimentally test the functions of such proteins. Our approach to functional prediction integrates comparative genomics based mainly on microbial genomes with functional genomic data from model microorganisms and post-genomic data from plants. This approach bridges the gap between automated homology-based annotations and the classical gene discovery efforts of experimentalists, and is more powerful than purely computational approaches to identifying gene-function associations.

RESULTS

Among Arabidopsis genes, we focused on those (2,325 in total) that (i) are unique or belong to families with no more than three members, (ii) occur in prokaryotes, and (iii) have unknown or poorly known functions. Computer-assisted selection of promising targets for deeper analysis was based on homology-independent characteristics associated in the SEED database with the prokaryotic members of each family. In-depth comparative genomic analysis was performed for 360 top candidate families. From this pool, 78 families were connected to general areas of metabolism and, of these families, specific functional predictions were made for 41. Twenty-one predicted functions have been experimentally tested or are currently under investigation by our group in at least one prokaryotic organism (nine of them have been validated, four invalidated, and eight are in progress). Ten additional predictions have been independently validated by other groups. Discovering the function of very widespread but hitherto enigmatic proteins such as the YrdC or YgfZ families illustrates the power of our approach.

CONCLUSIONS

Our approach correctly predicted functions for 19 uncharacterized protein families from plants and prokaryotes; none of these functions had previously been correctly predicted by computational methods. The resulting annotations could be propagated with confidence to over six thousand homologous proteins encoded in over 900 bacterial, archaeal, and eukaryotic genomes currently available in public databases.

Natural diversity and adaptation in plant secondary metabolism

Technological advances in metabolomics, transcriptomics and genomics have facilitated the detection of genes that contribute to diversification in plant secondary metabolism. Statistical tools from molecular population genetics may help in evaluating whether the corresponding genes or genomic regions carry a signature of selection and answering the question of whether novel compounds are 'adaptive'. Gene duplication fuels diversification in plant secondary metabolism and the evolutionary mechanism for adaptation may follow a path of neofunctionalization subsequent to gene duplication, or gene duplication may occur subsequent to--and resolve--an adaptive conflict present in a single ancestral gene sequence.

PRIN: a predicted rice interactome network

Background

Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa.

Results

To better understand the interactions of proteins in Oryza sativa, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.

Conclusions

PRIN is the first well annotated protein interaction database for the important model plant Oryza sativa. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.

PRIN is available online at http://bis.zju.edu.cn/prin/.

Towards establishment of a rice stress response interactome

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%-60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein-protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance.

Prediction of new abiotic stress genes in Arabidopsis thaliana and Oryza sativa according to enumeration-based statistical analysis

Plants undergo an extensive change in gene regulation during abiotic stress. It is of great agricultural importance to know which genes are affected during stress response. The genome sequence of a number of plant species has been determined, among them Arabidopsis and Oryza sativa, whose genome has been annotated most completely as of yet, and are well-known organisms widely used as experimental systems. This paper applies a statistical algorithm for predicting new stress-induced motifs and genes by analyzing promoter sets co-regulated by abiotic stress in the previously mentioned two species. After identifying characteristic putative regulatory motif sequence pairs (dyads) in the promoters of 125 stress-regulated Arabidopsis genes and 87 O. sativa genes, these dyads were used to screen the entire Arabidopsis and O. sativa promoteromes to find related stress-induced genes whose promoters contained a large number of these dyads found by our algorithm. We were able to predict a number of putative dyads, characteristic of a large number of stress-regulated genes, some of them newly discovered by our algorithm and serve as putative transcription factor binding sites. Our new motif prediction algorithm comes complete with a stand-alone program. This algorithm may be used in motif discovery in the future in other species. The more than 1,200 Arabidopsis and 1,700 Orzya sativa genes found by our algorithm are good candidates for further experimental studies in abiotic stress.

OryzaExpress: an integrated database of gene expression networks and omics annotations in rice

Similarity of gene expression profiles provides important clues for understanding the biological functions of genes, biological processes and metabolic pathways related to genes. A gene expression network (GEN) is an ideal choice to grasp such expression profile similarities among genes simultaneously. For GEN construction, the Pearson correlation coefficient (PCC) has been widely used as an index to evaluate the similarities of expression profiles for gene pairs. However, calculation of PCCs for all gene pairs requires large amounts of both time and computer resources. Based on correspondence analysis, we developed a new method for GEN construction, which takes minimal time even for large-scale expression data with general computational circumstances. Moreover, our method requires no prior parameters to remove sample redundancies in the data set. Using the new method, we constructed rice GENs from large-scale microarray data stored in a public database. We then collected and integrated various principal rice omics annotations in public and distinct databases. The integrated information contains annotations of genome, transcriptome and metabolic pathways. We thus developed the integrated database OryzaExpress for browsing GENs with an interactive and graphical viewer and principal omics annotations (http://riceball.lab.nig.ac.jp/oryzaexpress/). With integration of Arabidopsis GEN data from ATTED-II, OryzaExpress also allows us to compare GENs between rice and Arabidopsis. Thus, OryzaExpress is a comprehensive rice database that exploits powerful omics approaches from all perspectives in plant science and leads to systems biology.

Identification of rhizome-specific genes by genome-wide differential expression analysis in Oryza longistaminata

BACKGROUND

Rhizomatousness is a key component of perenniality of many grasses that contribute to competitiveness and invasiveness of many noxious grass weeds, but can potentially be used to develop perennial cereal crops for sustainable farmers in hilly areas of tropical Asia. Oryza longistaminata, a perennial wild rice with strong rhizomes, has been used as the model species for genetic and molecular dissection of rhizome development and in breeding efforts to transfer rhizome-related traits into annual rice species. In this study, an effort was taken to get insights into the genes and molecular mechanisms underlying the rhizomatous trait in O. longistaminata by comparative analysis of the genome-wide tissue-specific gene expression patterns of five different tissues of O. longistaminata using the Affymetrix GeneChip Rice Genome Array.

RESULTS

A total of 2,566 tissue-specific genes were identified in five different tissues of O. longistaminata, including 58 and 61 unique genes that were specifically expressed in the rhizome tips (RT) and internodes (RI), respectively. In addition, 162 genes were up-regulated and 261 genes were down-regulated in RT compared to the shoot tips. Six distinct cis-regulatory elements (CGACG, GCCGCC, GAGAC, AACGG, CATGCA, and TAAAG) were found to be significantly more abundant in the promoter regions of genes differentially expressed in RT than in the promoter regions of genes uniformly expressed in all other tissues. Many of the RT and/or RI specifically or differentially expressed genes were located in the QTL regions associated with rhizome expression, rhizome abundance and rhizome growth-related traits in O. longistaminata and thus are good candidate genes for these QTLs.

CONCLUSION

The initiation and development of the rhizomatous trait in O. longistaminata are controlled by very complex gene networks involving several plant hormones and regulatory genes, different members of gene families showing tissue specificity and their regulated pathways. Auxin/IAA appears to act as a negative regulator in rhizome development, while GA acts as the activator in rhizome development. Co-localization of the genes specifically expressed in rhizome tips and rhizome internodes with the QTLs for rhizome traits identified a large set of candidate genes for rhizome initiation and development in rice for further confirmation.

Field transcriptome revealed critical developmental and physiological transitions involved in the expression of growth potential in japonica rice

BACKGROUND

Plant growth depends on synergistic interactions between internal and external signals, and yield potential of crops is a manifestation of how these complex factors interact, particularly at critical stages of development. As an initial step towards developing a systems-level understanding of the biological processes underlying the expression of overall agronomic potential in cereal crops, a high-resolution transcriptome analysis of rice was conducted throughout life cycle of rice grown under natural field conditions.

RESULTS

A wide range of gene expression profiles based on 48 organs and tissues at various developmental stages identified 731 organ/tissue specific genes as well as 215 growth stage-specific expressed genes universally in leaf blade, leaf sheath, and root. Continuous transcriptome profiling of leaf from transplanting until harvesting further elucidated the growth-stage specificity of gene expression and uncovered two major drastic changes in the leaf transcriptional program. The first major change occurred before the panicle differentiation, accompanied by the expression of RFT1, a putative florigen gene in long day conditions, and the downregulation of the precursors of two microRNAs. This transcriptome change was also associated with physiological alterations including phosphate-homeostasis state as evident from the behavior of several key regulators such as miR399. The second major transcriptome change occurred just after flowering, and based on analysis of sterile mutant lines, we further revealed that the formation of strong sink, i.e., a developing grain, is not the major cause but is rather a promoter of this change.

CONCLUSIONS

Our study provides not only the genetic basis for functional genomics in rice but also new insight into understanding the critical physiological processes involved in flowering and seed development, that could lead to novel strategies for optimizing crop productivity.

Design, validation and annotation of transcriptome-wide oligonucleotide probes for the oligochaete annelid Eisenia fetida

High density oligonucleotide probe arrays have increasingly become an important tool in genomics studies. In organisms with incomplete genome sequence, one strategy for oligo probe design is to reduce the number of unique probes that target every non-redundant transcript through bioinformatic analysis and experimental testing. Here we adopted this strategy in making oligo probes for the earthworm Eisenia fetida, a species for which we have sequenced transcriptome-scale expressed sequence tags (ESTs). Our objectives were to identify unique transcripts as targets, to select an optimal and non-redundant oligo probe for each of these target ESTs, and to annotate the selected target sequences. We developed a streamlined and easy-to-follow approach to the design, validation and annotation of species-specific array probes. Four 244K-formatted oligo arrays were designed using eArray and were hybridized to a pooled E. fetida cRNA sample. We identified 63,541 probes with unsaturated signal intensities consistently above the background level. Target transcripts of these probes were annotated using several sequence alignment algorithms. Significant hits were obtained for 37,439 (59%) probed targets. We validated and made publicly available 63.5K oligo probes so the earthworm research community can use them to pursue ecological, toxicological, and other functional genomics questions. Our approach is efficient, cost-effective and robust because it (1) does not require a major genomics core facility; (2) allows new probes to be easily added and old probes modified or eliminated when new sequence information becomes available, (3) is not bioinformatics-intensive upfront but does provide opportunities for more in-depth annotation of biological functions for target genes; and (4) if desired, EST orthologs to the UniGene clusters of a reference genome can be identified and selected in order to improve the target gene specificity of designed probes. This approach is particularly applicable to organisms with a wealth of EST sequences but unfinished genome.

RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions

Elucidating the function of all predicted genes in rice remains as the ultimate goal in cereal genomics in order to ensure the development of improved varieties that will sustain an expanding world population. We constructed a gene expression database (RiceXPro, URL: http://ricexpro.dna.affrc.go.jp/) to provide an overview of the transcriptional changes throughout the growth of the rice plant in the field. RiceXPro contains two data sets corresponding to spatiotemporal gene expression profiles of various organs and tissues, and continuous gene expression profiles of leaf from transplanting to harvesting. A user-friendly web interface enables the extraction of specific gene expression profiles by keyword and chromosome search, and basic data analysis, thereby providing useful information as to the organ/tissue and developmental stage specificity of expression of a particular gene. Analysis tools such as t-test, calculation of fold change and degree of correlation facilitate the comparison of expression profiles between two random samples and the prediction of function of uncharacterized genes. As a repository of expression data encompassing growth in the field, this database can provide baseline information of genes that underlie various agronomically important traits in rice.

The Rice Kinase Phylogenomics Database: a guide for systematic analysis of the rice kinase super-family

Determination of gene function is particularly problematic when studying large-gene families because redundancy limits the ability to assess the contributions of individual genes experimentally. Phylogenomics is a phylogenetic approach used in comparative genomics to predict the biological functions of members of large gene-families by assessing the similarity among gene products. In this report, we describe the application of the Rice Kinase Database for elucidating functions of individual members of this gene family.

Coordinated regulation of gene expression for carotenoid metabolism in Chlamydomonas reinhardtii

Carotenoids are important plant pigments for both light harvesting and photooxidation protection. Using the model system of the unicellular green alga Chlamydomonas reinhardtii, we characterized the regulation of gene expression for carotenoid metabolism by quantifying changes in the transcript abundance of dxs, dxr and ipi in the plastidic methylerythritol phosphate pathway and of ggps, psy, pds, lcyb and bchy, directly involved in carotenoid metabolism, under different photoperiod, light and metabolite treatments. The expression of these genes fluctuated with light/dark shifting. Light treatment also promoted the accumulation of transcripts of all these genes. Of the genes studied, dxs, ggps and lcyb displayed the typical circadian pattern by retaining a rhythmic fluctuation of transcript abundance under both constant light and constant dark entrainments. The expression of these genes could also be regulated by metabolic intermediates. For example, ggps was significantly suppressed by a geranylgeranyl pyrophosphate supplement and ipi was upregulated by isopentenyl pyrophosphate. Furthermore, CrOr, a C. reinhardtii homolog of the recently characterized Or gene that accounts for carotenoid accumulation, also showed co-expression with carotenoid biosynthetic genes such as pds and lcyb. Our data suggest a coordinated regulation on carotenoid metabolism in C. reinhardtii at the transcriptional level.

Shared probe design and existing microarray reanalysis using PICKY

BACKGROUND

Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations.

RESULTS

PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users.

CONCLUSIONS

Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

The submergence tolerance regulator Sub1A mediates stress-responsive expression of AP2/ERF transcription factors

We previously characterized the rice (Oryza sativa) Submergence1 (Sub1) locus encoding three ethylene-responsive factor (ERF) transcriptional regulators. Genotypes carrying the Sub1A-1 allele are tolerant of prolonged submergence. To elucidate the mechanism of Sub1A-1-mediated tolerance, we performed transcriptome analyses comparing the temporal submergence response of Sub1A-1-containing tolerant M202(Sub1) with the intolerant isoline M202 lacking this gene. We identified 898 genes displaying Sub1A-1-dependent regulation. Integration of the expression data with publicly available metabolic pathway data identified submergence tolerance-associated pathways governing anaerobic respiration, hormone responses, and antioxidant systems. Of particular interest were a set of APETALA2 (AP2)/ERF family transcriptional regulators that are associated with the Sub1A-1-mediated response upon submergence. Visualization of expression patterns of the AP2/ERF superfamily members in a phylogenetic context resolved 12 submergence-regulated AP2/ERFs into three putative functional groups: (1) anaerobic respiration and cytokinin-mediated delay in senescence via ethylene accumulation during submergence (three ERFs); (2) negative regulation of ethylene-dependent gene expression (five ERFs); and (3) negative regulation of gibberellin-mediated shoot elongation (four ERFs). These results confirm that the presence of Sub1A-1 impacts multiple pathways of response to submergence.

A dynamic gene expression atlas covering the entire life cycle of rice

Growth and development of a plant are controlled by programmed expression of suits of genes at the appropriate time, tissue and abundance. Although genomic resources have been developed rapidly in recent years in rice, a model plant for cereal genome research, data of gene expression profiling are still insufficient to relate the developmental processes to transcriptomes, leaving a large gap between the genome sequence and phenotype. In this study, we generated genome-wide expression data by hybridizing 190 Affymetrix GeneChip Rice Genome Arrays with RNA from 39 tissues collected throughout the life cycle of the rice plant from two varieties, Zhenshan 97 and Minghui 63. Analyses of the global transcriptomes revealed many interesting features of dynamic patterns of gene expression across the tissues and stages. In total, 38 793 probe sets were detected as expressed and 69% of the expressed transcripts showed significantly variable expression levels among tissues/organs. We found that similarity of transcriptomes among organs corresponded well to their developmental relatedness. About 5.2% of the expressed transcripts showed tissue-specific expression in one or both varieties and 22.7% of the transcripts exhibited constitutive expression including 19 genes with high and stable expression in all the tissues. This dataset provided a versatile resource for plant genomic research, which can be used for associating the transcriptomes to the developmental processes, understanding the regulatory network of these processes, tracing the expression profile of individual genes and identifying reference genes for quantitative expression analyses.

Evolution of serine carboxypeptidase-like acyltransferases in the monocots

The serine carboxypeptidases are a large family of proteases. in higher plants some members of this family have diversified and adopted new functions as acyltransferases required for the synthesis of natural products. we recently reported the first serine carboxypeptidase-like (scpl) acyltransferase enzyme to be characterized from monocotyledonous plants.1 This enzyme, AsSCPL1, is required for acylation of antimicrobial terpenes (avenacins) that are produced in the roots of oat (Avena spp.) and that provide protection against soil-borne pathogens. The SCPL acyltransferase enzyme family has undergone substantial expansion following the divergence of monocots and dicots. Here we discuss the evolution of this SCPL enzyme family in monocots, their contribution to metabolic diversity, and the roles of these enzymes in biotic and abiotic stress tolerance.

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

BACKGROUND

The transcriptional regulatory network involved in low temperature response leading to acclimation has been established in Arabidopsis. In japonica rice, which can only withstand transient exposure to milder cold stress (10 degrees C), an oxidative-mediated network has been proposed to play a key role in configuring early responses and short-term defenses. The components, hierarchical organization and physiological consequences of this network were further dissected by a systems-level approach.

RESULTS

Regulatory clusters responding directly to oxidative signals were prominent during the initial 6 to 12 hours at 10 degrees C. Early events mirrored a typical oxidative response based on striking similarities of the transcriptome to disease, elicitor and wounding induced processes. Targets of oxidative-mediated mechanisms are likely regulated by several classes of bZIP factors acting on as1/ocs/TGA-like element enriched clusters, ERF factors acting on GCC-box/JAre-like element enriched clusters and R2R3-MYB factors acting on MYB2-like element enriched clusters.Temporal induction of several H2O2-induced bZIP, ERF and MYB genes coincided with the transient H2O2 spikes within the initial 6 to 12 hours. Oxidative-independent responses involve DREB/CBF, RAP2 and RAV1 factors acting on DRE/CRT/rav1-like enriched clusters and bZIP factors acting on ABRE-like enriched clusters. Oxidative-mediated clusters were activated earlier than ABA-mediated clusters.

CONCLUSION

Genome-wide, physiological and whole-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress and developmental responses leads to modulated growth and vigor maintenance contributing to a delay of plastic injuries.

Direct calibration of PICKY-designed microarrays

Background

Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples.

Results

Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website under the PICKY Download area.

Conclusion

PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

Microarrays and high-throughput transcriptomic analysis in species with incomplete availability of genomic sequences

Microarrays produce a measurement of gene expression based on the relative measures of dye intensities that correspond to the amount of target RNA. This technology is fast developing and its application is expanding from Homo sapiens to a wide number of species, where enough information on sequences and annotations exist. Anyway, the number of species for which a dedicated platform exists is not high. The use of heterologous array hybridization, screening for gene expression in one species using an array developed for another one, is still quite frequent, even though cross-species microarray hybridization has raised many arguments. Some methods which are high throughput and do not rely on knowledge of the DNA/RNA sequence exist, namely serial analysis of gene expression (SAGE), Massively Parallel Signature Sequencing (MPSS) and deep sequencing of full transcriptome. Although very powerful, particularly the latter, they are still quite costly and cumbersome methods. In some species where genome sequences are largely unknown, several anonymous sequences are deposited in gene banks as a result of Expressed Sequence Tags (ESTs) sequencing projects. The ESTs databases represent a valuable knowledge that can be exploited with some bioinformatic effort to build species-specific microarrays. We present here a method of high-density in situ synthesized microarrays starting from available EST sequences in, Ovis aries. Our data indicate that the method is very efficient and can be easily extended to other species of which genetic sequences are present in public databases, but neglected so far with advanced devices like microarrays. As a perspective, the approach can be applied also to species of which no sequences are available to date, thanks to high-throughput deep sequencing methods.

[A place in tears]

Alternative splicing creates a diversity of gene products in higher eukaryotes. Twenty-five percent (1,583/6,371) of predicted alternatively spliced transcripts can be detected using the NSF45K rice whole-genome oligonucleotide array. We used the NSF45K array to assess differential expression patterns of 507 loci showing at least a twofold change in expression between light- and dark-grown seedlings. At least 42% of these loci show evidence of alternative splicing in aerial seedling tissue of Oryza sativa ssp. japonica cv. Nipponbare. Most alternative splice forms display the same pattern of regulation as the primary, or most highly expressed, transcript; however, splice forms for ten loci, represented by 35 oligos, display opposite expression patterns in the light vs. dark. We found similar evidence of alternative splicing events in Affymetrix microarray data for Nipponbare rice treated with the causative agent of fungal rice blast, Magnaporthe grisea. This strategy for analyzing alternative splicing in microarray data will enable delineation of the diversity of splicing in rice.

Construction of a rice glycosyltransferase phylogenomic database and identification of rice-diverged glycosyltransferases

Glycosyltransferases (GTs; EC 2.4.x.y) constitute a large group of enzymes that form glycosidic bonds through transfer of sugars from activated donor molecules to acceptor molecules. GTs are critical to the biosynthesis of plant cell walls, among other diverse functions. Based on the Carbohydrate-Active enZymes (CAZy) database and sequence similarity searches, we have identified 609 potential GT genes (loci) corresponding to 769 transcripts (gene models) in rice (Oryza sativa), the reference monocotyledonous species. Using domain composition and sequence similarity, these rice GTs were classified into 40 CAZy families plus an additional unknown class. We found that two Pfam domains of unknown function, PF04577 and PF04646, are associated with GT families GT61 and GT31, respectively. To facilitate functional analysis of this important and large gene family, we created a phylogenomic Rice GT Database (http://ricephylogenomics.ucdavis.edu/cellwalls/gt/). Through the database, several classes of functional genomic data, including mutant lines and gene expression data, can be displayed for each rice GT in the context of a phylogenetic tree, allowing for comparative analysis both within and between GT families. Comprehensive digital expression analysis of public gene expression data revealed that most ( approximately 80%) rice GTs are expressed. Based on analysis with Inparanoid, we identified 282 'rice-diverged' GTs that lack orthologs in sequenced dicots (Arabidopsis thaliana, Populus tricocarpa, Medicago truncatula, and Ricinus communis). Combining these analyses, we identified 33 rice-diverged GT genes (45 gene models) that are highly expressed in above-ground, vegetative tissues. From the literature and this analysis, 21 of these loci are excellent targets for functional examination toward understanding and manipulating grass cell wall qualities. Study of the remainder may reveal aspects of hormone and protein metabolism that are critical for rice biology. This list of 33 genes and the Rice GT Database will facilitate the study of GTs and cell wall synthesis in rice and other plants.