Takeshi Obayashi

Omics-based identification of Arabidopsis Myb transcription factors regulating aliphatic glucosinolate biosynthesis

Understanding plant metabolism as an integrated system is essential for metabolic engineering aimed at the effective production of compounds useful to human life and the global environment. The “omics” approach integrates transcriptome and metabolome data into a single data set and can lead to the identification of unknown genes and their regulatory networks involved in metabolic pathways of interest. One of the intriguing, although poorly described metabolic pathways in plants is the biosynthesis of glucosinolates (GSLs), a group of bioactive secondary products derived from amino acids that are found in the family Brassicaceae. Here we report the discovery of two R2R3-Myb transcription factors that positively control the biosynthesis of GSLs in Arabidopsis thaliana by an integrated omics approach. Combined transcriptome coexpression analysis of publicly available, condition-independent data and the condition-specific (i.e., sulfur-deficiency) data identified Myb28 and Myb29 as candidate transcription factor genes specifically involved in the regulation of aliphatic GSL production. Analysis of a knockout mutant and ectopic expression of the gene demonstrated that Myb28 is a positive regulator for basal-level production of aliphatic GSLs. Myb29 presumably plays an accessory function for methyl jasmonate-mediated induction of a set of aliphatic GSL biosynthetic genes. Overexpression of Myb28 in Arabidopsis-cultured suspension cells, which do not normally synthesize GSLs, resulted in the production of large amounts of GSLs, suggesting the possibility of efficient industrial production of GSLs by manipulation of these transcription factors. A working model for regulation of GSL production involving these genes, renamed Production of Methionine-Derived Glucosinolate (PMG) 1 and 2, are postulated.

ATTED-II provides coexpressed gene networks for Arabidopsis

ATTED-II (http://atted.jp) is a database of gene coexpression in Arabidopsis that can be used to design a wide variety of experiments, including the prioritization of genes for functional identification or for studies of regulatory relationships. Here, we report updates of ATTED-II that focus especially on functionalities for constructing gene networks with regard to the following points: (i) introducing a new measure of gene coexpression to retrieve functionally related genes more accurately, (ii) implementing clickable maps for all gene networks for step-by-step navigation, (iii) applying Google Maps API to create a single map for a large network, (iv) including information about protein–protein interactions, (v) identifying conserved patterns of coexpression and (vi) showing and connecting KEGG pathway information to identify functional modules. With these enhanced functions for gene network representation, ATTED-II can help researchers to clarify the functional and regulatory networks of genes in Arabidopsis.

12-oxo-phytodienoic acid triggers expression of a distinct set of genes and plays a role in wound-induced gene expression in Arabidopsis.

Jasmonic acid (JA) and methyl jasmonate (MeJA), collectively known as JAs, regulate diverse physiological processes in plants, including the response to wounding. Recent reports suggest that a cyclopentenone precursor of JA, 12-oxo-phytodienoic acid (OPDA), can also induce gene expression. However, little is known about the physiological significance of OPDA-dependent gene expression. We used microarray analysis of approximately 21,500 Arabidopsis (Arabidopsis thaliana) genes to compare responses to JA, MeJA, and OPDA treatment. Although many genes responded identically to both OPDA and JAs, we identified a set of genes (OPDA-specific response genes [ORGs]) that specifically responded to OPDA but not to JAs. ORGs primarily encoded signaling components, transcription factors, and stress response-related genes. One-half of the ORGs were induced by wounding. Analysis using mutants deficient in the biosynthesis of JAs revealed that OPDA functions as a signaling molecule in the wounding response. Unlike signaling via JAs, OPDA signaling was CORONATINE INSENSITIVE 1 independent. These results indicate that an OPDA signaling pathway functions independently of JA/MeJA signaling and is required for the wounding response in Arabidopsis.

ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis

Publicly available database of co-expressed gene sets would be a valuable tool for a wide variety of experimental designs, including targeting of genes for functional identification or for regulatory investigation. Here, we report the construction of an Arabidopsis thaliana trans-factor and cis-element prediction database (ATTED-II) that provides co-regulated gene relationships based on co-expressed genes deduced from microarray data and the predicted cis elements. ATTED-II () includes the following features: (i) lists and networks of co-expressed genes calculated from 58 publicly available experimental series, which are composed of 1388 GeneChip data in A.thaliana; (ii) prediction of cis-regulatory elements in the 200 bp region upstream of the transcription start site to predict co-regulated genes amongst the co-expressed genes; and (iii) visual representation of expression patterns for individual genes. ATTED-II can thus help researchers to clarify the function and regulation of particular genes and gene networks.

PROTEIN SUBCELLULAR LOCALIZATION PREDICTION WITH WOLF PSORT

We present a new program for predicting protein subcellular localization from amino acid sequence. WoLF PSORT is a major update to the PSORTII program, based on new sequence

ATTED-II Updates: Condition-Specific Gene Coexpression to Extend Coexpression Analyses and Applications to a Broad Range of Flowering Plants

ATTED-II (http://atted.jp) is a gene coexpression database for a wide variety of experimental designs, such as prioritizations of genes for functional identification and analyses of the regulatory relationships among genes. Here, we report updates of ATTED-II focusing on two new features: condition-specific coexpression and homologous coexpression with rice. To analyze a broad range of biological phenomena, it is important to collect data under many diverse experimental conditions, but the meaning of coexpression can become ambiguous under these conditions. One approach to overcome this difficulty is to calculate the coexpression for each set of conditions with a clear biological meaning. With this viewpoint, we prepared five sets of experimental conditions (tissue, abiotic stress, biotic stress, hormones and light conditions), and users can evaluate the coexpression by employing comparative gene lists and switchable gene networks. We also developed an interactive visualization system, using the Cytoscape web system, to improve the network representation. As the second update, rice coexpression is now available. The previous version of ATTED-II was specifically developed for Arabidopsis, and thus coexpression analyses for other useful plants have been difficult. To solve this problem, we extended ATTED-II by including comparison tables between Arabidopsis and rice. This representation will make it possible to analyze the conservation of coexpression among flowering plants. With the ability to investigate condition-specific coexpression and species conservation, ATTED-II can help researchers to clarify the functional and regulatory networks of genes in a broad array of plant species.

Rank of Correlation Coefficient as a Comparable Measure for Biological Significance of Gene Coexpression

Information regarding gene coexpression is useful to predict gene function. Several databases have been constructed for gene coexpression in model organisms based on a large amount of publicly available gene expression data measured by GeneChip platforms. In these databases, Pearsons correlation coefficients (PCCs) of gene expression patterns are widely used as a measure of gene coexpression. Although the coexpression measure or GeneChip summarization method affects the performance of the gene coexpression database, previous studies for these calculation procedures were tested with only a small number of samples and a particular species. To evaluate the effectiveness of coexpression measures, assessments with large-scale microarray data are required. We first examined characteristics of PCC and found that the optimal PCC threshold to retrieve functionally related genes was affected by the method of gene expression database construction and the target gene function. In addition, we found that this problem could be overcome when we used correlation ranks instead of correlation values. This observation was evaluated by large-scale gene expression data for four species: Arabidopsis, human, mouse and rat.

COXPRESdb: a database of coexpressed gene networks in mammals

A database of coexpressed gene sets can provide valuable information for a wide variety of experimental designs, such as targeting of genes for functional identification, gene regulation and/or protein–protein interactions. Coexpressed gene databases derived from publicly available GeneChip data are widely used in Arabidopsis research, but platforms that examine coexpression for higher mammals are rather limited. Therefore, we have constructed a new database, COXPRESdb (coexpressed gene database) (http://coxpresdb.hgc.jp), for coexpressed gene lists and networks in human and mouse. Coexpression data could be calculated for 19 777 and 21 036 genes in human and mouse, respectively, by using the GeneChip data in NCBI GEO. COXPRESdb enables analysis of the four types of coexpression networks: (i) highly coexpressed genes for every gene, (ii) genes with the same GO annotation, (iii) genes expressed in the same tissue and (iv) user-defined gene sets. When the networks became too big for the static picture on the web in GO networks or in tissue networks, we used Google Maps API to visualize them interactively. COXPRESdb also provides a view to compare the human and mouse coexpression patterns to estimate the conservation between the two species.

Gene Expression Profiling of the Tetrapyrrole Metabolic Pathway in Arabidopsis with a Mini-Array System

Tetrapyrrole compounds, such as chlorophylls, hemes, and phycobilins, are synthesized in many enzymatic steps. For regulation of the tetrapyrrole metabolic pathway, it is generally considered that several specific isoforms catalyzing particular enzymatic steps control the flow of tetrapyrrole intermediates by differential regulation of gene expression depending on environmental and developmental factors. However, the coordination of such regulatory steps and orchestration of the overall tetrapyrrole metabolic pathway are still poorly understood. In this study, we developed an original mini-array system, which enables the expression profiling of each gene involved in tetrapyrrole biosynthesis simultaneously with high sensitivity. With this system, we performed a transcriptome analysis of Arabidopsis seedlings in terms of the onset of greening, endogenous rhythm, and developmental control. Data presented here clearly showed that based on their expression profiles at the onset of greening, genes involved in tetrapyrrole biosynthesis can be classified into four categories, in which genes are coordinately regulated to control the biosynthesis. Moreover, genes in the same group were similarly controlled in an endogenous rhythmic manner but also by a developmental program. The physiological significance of these gene clusters is discussed.

ATTED-II in 2016: A Plant Coexpression Database Towards Lineage-Specific Coexpression

ATTED-II (http://atted.jp) is a coexpression database for plant species with parallel views of multiple coexpression data sets and network analysis tools. The user can efficiently find functional gene relationships and design experiments to identify gene functions by reverse genetics and general molecular biology techniques. Here, we report updates to ATTED-II (version 8.0), including new and updated coexpression data and analysis tools. ATTED-II now includes eight microarray- and six RNA sequencing-based coexpression data sets for seven dicot species (Arabidopsis, field mustard, soybean, barrel medick, poplar, tomato and grape) and two monocot species (rice and maize). Stand-alone coexpression analyses tend to have low reliability. Therefore, examining evolutionarily conserved coexpression is a more effective approach from the viewpoints of reliability and evolutionary importance. In contrast, the reliability of species-specific coexpression data remains poor. Our assessment scores for individual coexpression data sets indicated that the quality of the new coexpression data sets in ATTED-II is higher than for any previous coexpression data set. In addition, five species (Arabidopsis, soybean, tomato, rice and maize) in ATTED-II are now supported by both microarray- and RNA sequencing-based coexpression data, which has increased the reliability. Consequently, ATTED-II can now provide lineage-specific coexpression information. As an example of the use of ATTED-II to explore lineage-specific coexpression, we demonstrate monocot- and dicot-specific coexpression of cell wall genes. With the expanded coexpression data for multilevel evaluation, ATTED-II provides new opportunities to investigate lineage-specific evolution in plants.