Tohoku University · Biochemistry, Genetics and Molecular Biology
Professor Takeshi Obayashi's research lab specializes in computational plant biology and systems genetics, focusing on gene coexpression networks and regulatory element prediction in plants. The lab develops advanced bioinformatics databases such as ATTED-II and COXPRESdb to enable functional genomics research by integrating large-scale transcriptomic data from microarrays and RNA-Seq across multiple species. Their work emphasizes methodological innovation in coexpression analysis, including noise reduction through principal component analysis and cross-species comparative coexpression to uncover evolutionary dynamics in gene regulation. The lab also extends its resources to higher animals, contributing to human and mouse gene network databases for translational research.
Figures are computed from collected data and may differ slightly.
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 follo
ATTED-II (http://atted.jp) is a coexpression database for plant species to aid in the discovery of relationships of unknown genes within a species. As an advanced coexpression analysis method, multispecies comparisons have the potential to detect alterations in gene relationships within an evolutionary context. However, determining the validity of comparative coexpression studies is difficult without quantitative assessments of the quality of coexpression data. ATTED-II (version 9) provides 16 c
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, Pearson's 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
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
ATTED-II (https://atted.jp) is a gene coexpression database for nine plant species based on publicly available RNAseq and microarray data. One of the challenges in constructing condition-independent coexpression data based on publicly available gene expression data is managing the inherent sampling bias. Here, we report ATTED-II version 11, wherein we adopted a coexpression calculation methodology to balance the samples using principal component analysis and ensemble calculation. This approach h
ATTED-II (http://atted.jp) is a database of coexpressed genes that was originally developed to identify functionally related genes in Arabidopsis and rice. Herein, we describe an updated version of ATTED-II, which expands this resource to include additional agriculturally important plants. To improve the quality of the coexpression data for Arabidopsis and rice, we included more gene expression data from microarray and RNA sequencing studies. The RNA sequencing-based coexpression data now cover
Publicly available databases of coexpressed gene sets are a valuable resource for a wide variety of experimental studies, including gene targeting for functional identification, and for investigations of regulatory mechanisms or protein-protein interaction networks. Although coexpressed gene databases are becoming more and more popular in the field of plant biology, those with animal data are rather limited, possibly due to the lower reliability of the coexpression data. The original COXPRESdb (
Coexpressed gene databases are valuable resources for identifying new gene functions or functional modules in metabolic pathways and signaling pathways. Although coexpressed gene databases are a fundamental platform in the field of plant biology, their use in animal studies is relatively limited. The COXPRESdb (http://coxpresdb.jp) provides coexpression relationships for multiple animal species, as comparisons of coexpressed gene lists can enhance the reliability of gene coexpression determinati
In the era of energy and food shortage, microalgae have gained much attention as promising sources of biofuels and food ingredients. However, only a small fraction of microalgal genes have been functionally characterized. Here, we have developed the Algae Gene Coexpression database (ALCOdb; http://alcodb.jp), which provides gene coexpression information to survey gene modules for a function of interest. ALCOdb currently supports two model algae: the green alga Chlamydomonas reinhardtii and the r
Gene coexpression is synchronization of gene expression across many cellular and environmental conditions and is widely used to infer the biological function of genes. Gene coexpression information is complex, comprising a complete graph of all genes in the genome, and requires appropriate visualization and analysis tools. Since its initial release in 2007, the animal gene expression database COXPRESdb (https://coxpresdb.jp) has been continuously improved by adding new gene coexpression data and
The distinctive features of plant organs are primarily determined by organ-specific gene expression. We analyzed the expression specificity of 8809 genes in 7 organs of Arabidopsis using a cDNA macroarray system. Using relative expression (RE) values between organs, many known and unknown genes specifically expressed in each organ were identified. We also analyzed the organ specificity of various gene groups using the GRE (group relative expression) value, the average of the REs of all genes in
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The outstanding differentiation capacities and easier access from adult tissues, cells derived from neural crest cells (NCCs) have fascinated scientists in developmental biology and regenerative medicine. Differentiation potentials of NCCs are known to depend on their originating regions. Here, we report differential molecular features between craniofacial (cNCCs) and trunk (tNCCs) NCCs by analyzing transcription profiles and sphere forming assays of NCCs from P0-Cre/floxed-EGFP mouse embryos. W
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