COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations.

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 analysis tools. Here, we report COXPRESdb version 8, which has been enhanced with new features for an overview, summary, and individual examination of coexpression relationships: CoexMap to display coexpression on a genome scale, pathway enrichment analysis to summarize the function of coexpressed genes, and CoexPub to bridges coexpression and existing knowledge. COXPRESdb also facilitates downstream analyses such as interspecies comparisons by integrating RNAseq and microarray coexpression data in a union-type gene coexpression. COXPRESdb strongly support users with the new coexpression data and enhanced functionality.

ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components.

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 has two advantages. First, omitting principal components with low contribution rates reduces the main contributors of noise. Second, balancing large differences in contribution rates enables considering various sample conditions entirely. In addition, based on RNAseq- and microarray-based coexpression data, we provide species-representative, integrated coexpression information to enhance the efficiency of interspecies comparison of the coexpression data. These coexpression data are provided as a standardized z-score to facilitate integrated analysis with different data sources. We believe that with these improvements, ATTED-II is more valuable and powerful for supporting interspecies comparative studies and integrated analyses using heterogeneous data.

Lipid Pathway Databases with a Focus on Algae.

Pathways of lipid biosynthesis are highly complex and have been established in model organisms such as Arabidopsis thaliana and Chlamydomonas reinhardtii, whereas in other organisms, we need bioinformatic tools to map individual enzymes onto reference pathways. In this chapter, we explain representative tools that are useful in identifying algal orthologs of lipid biosynthetic enzymes and finding new enzymes that are possibly involved in the pathway of interest. All descriptions in this chapter refer to in silico (i.e., computer-based) methods rather than laboratory experiments.

Lipid remodeling regulator 1 (LRL1) is differently involved in the phosphorus-depletion response from PSR1 in Chlamydomonas reinhardtii.

The elucidation of lipid metabolism in microalgae has attracted broad interest, as their storage lipid, triacylglycerol (TAG), can be readily converted into biofuel via transesterification. TAG accumulates in the form of oil droplets, especially when cells undergo nutrient deprivation, such as for nitrogen (N), phosphorus (P), or sulfur (S). TAG biosynthesis under N-deprivation has been comprehensively studied in the model microalga Chlamydomonas reinhardtii, during which TAG accumulates dramatically. However, the resulting rapid breakdown of chlorophyll restricts overall oil yield productivity and causes cessation of cell growth. In contrast, P-deprivation results in oil accumulation without disrupting chloroplast integrity. We used a reverse genetics approach based on co-expression analysis to identify a transcription factor (TF) that is upregulated under P-depleted conditions. Transcriptomic analysis revealed that the mutants showed repression of genes typically associated with lipid remodeling under P-depleted conditions, such as sulfoquinovosyl diacylglycerol 2 (SQD2), diacylglycerol acyltransferase (DGTT1), and major lipid droplet protein (MLDP). As accumulation of sulfoquinovosyl diacylglycerol and TAG were suppressed in P-depleted mutants, we designated the protein as lipid remodeling regulator 1 (LRL1). LRL1 mutants showed slower growth under P-depletion. Moreover, cell size in the mutant was significantly reduced, and TAG and starch accumulation per cell were decreased. Transcriptomic analysis also suggested the repression of several genes typically upregulated in adaptation to P-depletion that are associated with the cell cycle and P and lipid metabolism. Thus, our analysis of LRL1 provides insights into P-allocation and lipid remodeling under P-depleted conditions in C. reinhardtii. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The sequencing data were made publicly available under the BioProject Accession number PRJDB6733 and an accession number LC488724 at the DNA Data Bank of Japan (DDBJ). The data is available at https://trace.ddbj.nig.ac.jp/BPSearch/bioproject?acc=PRJDB6733; http://getentry.ddbj.nig.ac.jp/getentry/na/LC488724. The metabolome data were made publicly available and can be accessed at http://metabolonote.kazusa.or.jp/SE195:/; http://webs2.kazusa.or.jp/data/nur/.

COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference.

The advent of RNA-sequencing and microarray technologies has led to rapid growth of transcriptome data generated for a wide range of organisms, under various cellular, organ and individual conditions. Since the number of possible combinations of intercellular and extracellular conditions is almost unlimited, cataloging all transcriptome conditions would be an immeasurable challenge. Gene coexpression refers to the similarity of gene expression patterns under various conditions, such as disease states, tissue types, and developmental stages. Since the quality of gene coexpression data depends on the quality and quantity of transcriptome data, timely usage of the growing data is key to promoting individual research in molecular biology. COXPRESdb (http://coxpresdb.jp) is a database providing coexpression information for 11 animal species. One characteristic feature of COXPRESdb is its ability to compare multiple coexpression data derived from different transcriptomics technologies and different species, which strongly reduces false positive relationships in individual gene coexpression data. Here, we summarized the current version of this database, including 23 coexpression platforms with the highest-level quality till date. Using various functionalities in COXPRESdb, the new coexpression data would support a broader area of research from molecular biology to medical sciences.

ATTED-II in 2018: A Plant Coexpression Database Based on Investigation of the Statistical Property of the Mutual Rank Index.

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 coexpression platforms for nine plant species, including seven species supported by both microarray- and RNA sequencing (RNAseq)-based coexpression data. Two independent sources of coexpression data enable the assessment of the reproducibility of coexpression. The latest coexpression data for Arabidopsis (Ath-m.c7-1 and Ath-r.c3-0) showed the highest reproducibility (Jaccard coefficient = 0.13) among previous coexpression data in ATTED-II. We also investigated the statistical basis of the mutual rank (MR) index as a coexpression measure by bootstrap sampling of experimental units. We found that the error distribution of the logit-transformed MR index showed normality with equal variances for each coexpression platform. Because the MR error was strongly correlated with the number of samples for the coexpression data, typical confidence intervals for the MR index can be estimated for any coexpression platform. These new, high-quality coexpression data can be analyzed with any tool in ATTED-II and combined with external resources to obtain insight into plant biology.

Arabinogalactan Proteins Accumulate in the Cell Walls of Searching Hyphae of the Stem Parasitic Plants, Cuscuta campestris and Cuscuta japonica.

Stem parasitic plants (Cuscuta spp.) develop a specialized organ called a haustorium to penetrate their hosts' stem tissues. To reach the vascular tissues of the host plant, the haustorium needs to overcome the physical barrier of the cell wall, and the parasite-host interaction via the cell wall is a critical process. However, the cell wall components responsible for the establishment of parasitic connections have not yet been identified. In this study, we investigated the spatial distribution patterns of cell wall components at a parasitic interface using parasite-host complexes of Cuscuta campestris-Arabidopsis thaliana and Cuscuta japonica-Glycine max. We focused on arabinogalactan proteins (AGPs), because AGPs accumulate in the cell walls of searching hyphae of both C. campestris and C. japonica. We found more AGPs in elongated haustoria than in pre haustoria, indicating that AGP accumulation is developmentally regulated. Using in situ hybridization, we identified five genes in C. campestris that encode hyphal-expressed AGPs that belong to the fasciclin-like AGP (FLA) family, which were named CcFLA genes. Three of the five CcFLA genes were expressed in the holdfast, which develops on the Cuscuta stem epidermis at the attachment site for the host's stem epidermis. Our results suggest that AGPs are involved in hyphal elongation and adhesion to host cells, and in the adhesion between the epidermal tissues of Cuscuta and its host.

Root-Knot and Cyst Nematodes Activate Procambium-Associated Genes in Arabidopsis Roots.

Developmental plasticity is one of the most striking features of plant morphogenesis, as plants are able to vary their shapes in response to environmental cues. Biotic or abiotic stimuli often promote organogenesis events in plants not observed under normal growth conditions. Root-knot nematodes (RKNs) are known to parasitize multiple species of rooting plants and to induce characteristic tissue expansion called galls or root-knots on the roots of their hosts by perturbing the plant cellular machinery. Galls contain giant cells (GCs) and neighboring cells, and the GCs are a source of nutrients for the parasitizing nematode. Highly active cell proliferation was observed in galls. However, the underlying mechanisms that regulate the symptoms triggered by the plant-nematode interaction have not yet been elucidated. In this study, we deciphered the molecular mechanism of gall formation with an in vitro infection assay system using RKN Meloidogyne incognita, and the model plant Arabidopsis thaliana. By taking advantages of this system, we performed next-generation sequencing-based transcriptome profiling, and found that the expression of procambium identity-associated genes were enriched during gall formation. Clustering analyses with artificial xylogenic systems, together with the results of expression analyses of the candidate genes, showed a significant correlation between the induction of gall cells and procambium-associated cells. Furthermore, the promoters of several procambial marker genes such as ATHB8, TDR and WOX4 were activated not only in M. incognita-induced galls, but similarly in M. javanica induced-galls and Heterodera schachtii-induced syncytia. Our findings suggest that phytoparasitic nematodes modulate the host's developmental regulation of the vascular stem cells during gall formation.

Co-expressed Pathways DataBase for Tomato: a database to predict pathways relevant to a query gene.

BACKGROUND: Gene co-expression, the similarity of gene expression profiles under various experimental conditions, has been used as an indicator of functional relationships between genes, and many co-expression databases have been developed for predicting gene functions. These databases usually provide users with a co-expression network and a list of strongly co-expressed genes for a query gene. Several of these databases also provide functional information on a set of strongly co-expressed genes (i.e., provide biological processes and pathways that are enriched in these strongly co-expressed genes), which is generally analyzed via over-representation analysis (ORA). A limitation of this approach may be that users can predict gene functions only based on the strongly co-expressed genes. RESULTS: In this study, we developed a new co-expression database that enables users to predict the function of tomato genes from the results of functional enrichment analyses of co-expressed genes while considering the genes that are not strongly co-expressed. To achieve this, we used the ORA approach with several thresholds to select co-expressed genes, and performed gene set enrichment analysis (GSEA) applied to a ranked list of genes ordered by the co-expression degree. We found that internal correlation in pathways affected the significance levels of the enrichment analyses. Therefore, we introduced a new measure for evaluating the relationship between the gene and pathway, termed the percentile (p)-score, which enables users to predict functionally relevant pathways without being affected by the internal correlation in pathways. In addition, we evaluated our approaches using receiver operating characteristic curves, which concluded that the p-score could improve the performance of the ORA. CONCLUSIONS: We developed a new database, named Co-expressed Pathways DataBase for Tomato, which is available at http://cox-path-db.kazusa.or.jp/tomato . The database allows users to predict pathways that are relevant to a query gene, which would help to infer gene functions.

Plant Aurora kinases interact with and phosphorylate transcription factors.

Aurora kinase (AUR) is a well-known mitotic serine/threonine kinase that regulates centromere formation, chromosome segregation, and cytokinesis in eukaryotes. In addition to regulating mitotic events, AUR has been shown to regulate protein dynamics during interphase in animal cells. In contrast, there has been no identification and characterization of substrates and/or interacting proteins during interphase in plants. The Arabidopsis thaliana genome encodes three AUR paralogues, AtAUR1, AtAUR2, and AtAUR3. Among them, AtAUR1 and AtAUR2 are considered to function redundantly. Here, we confirmed that both AtAUR1 and AtAUR3 are localized in the nucleus and cytoplasm during interphase, suggesting that they have functions during interphase. To identify novel interacting proteins, we used AlphaScreen to target 580 transcription factors (TFs) that are mainly functional during interphase, using recombinant A. thaliana TFs and AtAUR1 or AtAUR3. We found 133 and 32 TFs had high potential for interaction with AtAUR1 and AtAUR3, respectively. The highly AtAUR-interacting TFs were involved in various biological processes, suggesting the functions of the AtAURs during interphase. We found that AtAUR1 and AtAUR3 showed similar interaction affinity to almost all TFs. However, in some cases, the interaction affinity differed substantially between the two AtAUR homologues. These results suggest that AtAUR1 and AtAUR3 have both redundant and distinct functions through interactions with TFs. In addition, database analysis revealed that most of the highly AtAUR-interacting TFs contained a detectable phosphopeptide that was consistent with the consensus motifs for human AURs, suggesting that these TFs are substrates of the AtAURs. The AtAURs phosphorylated several highly interacting TFs in the AlphaScreen in vitro. Overall, in line with the regulation of TFs through interaction, our results indicate the possibility of phosphoregulation of several TFs by the AtAURs (280/300).

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.

ALCOdb: Gene Coexpression Database for Microalgae.

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 red alga Cyanidioschyzon merolae. Users can retrieve coexpression information for genes of interest through three unique data pages: (i) Coexpressed Gene List; (ii) Gene Information; and (iii) Coexpressed Gene Network. In addition to the basal coexpression information, ALCOdb also provides several advanced functionalities such as an expression profile viewer and a differentially expressed gene search tool. Using these user interfaces, we demonstrated that our gene coexpression data have the potential to detect functionally related genes and are useful in extrapolating the biological roles of uncharacterized genes. ALCOdb will facilitate molecular and biochemical studies of microalgal biological phenomena, such as lipid metabolism and organelle development, and promote the evolutionary understanding of plant cellular systems.

Comparison of Gene Coexpression Profiles and Construction of Conserved Gene Networks to Find Functional Modules.

BACKGROUND: Computational approaches toward gene annotation are a formidable challenge, now that many genome sequences have been determined. Each gene has its own function, but complicated cellular functions are achieved by sets of genes. Therefore, sets of genes with strong functional relationships must be identified. For this purpose, the similarities of gene expression patterns and gene sequences have been separately utilized, although the combined information will provide a better solution. RESULT & DISCUSSION: We propose a new method to find functional modules, by comparing gene coexpression profiles among species. A coexpression pattern is represented as a list of coexpressed genes with each guide gene. We compared two coexpression lists, one from a human guide gene and the other from a homologous mouse gene, and defined a measure to evaluate the similarity between the lists. Based on this coexpression similarity, we detected the highly conserved genes, and constructed human gene networks with conserved coexpression between human and mouse. Some of the tightly coupled genes (modules) showed clear functional enrichment, such as immune system and cell cycle, indicating that our method could identify functionally related genes without any prior knowledge. We also found a few functional modules without any annotations, which may be good candidates for novel functional modules. All of the comparisons are available at the http://v1.coxsimdb.info web database.

COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems.

The COXPRESdb (http://coxpresdb.jp) provides gene coexpression relationships for animal species. Here, we report the updates of the database, mainly focusing on the following two points. For the first point, we added RNAseq-based gene coexpression data for three species (human, mouse and fly), and largely increased the number of microarray experiments to nine species. The increase of the number of expression data with multiple platforms could enhance the reliability of coexpression data. For the second point, we refined the data assessment procedures, for each coexpressed gene list and for the total performance of a platform. The assessment of coexpressed gene list now uses more reasonable P-values derived from platform-specific null distribution. These developments greatly reduced pseudo-predictions for directly associated genes, thus expanding the reliability of coexpression data to design new experiments and to discuss experimental results.

Molecular and cellular features of murine craniofacial and trunk neural crest cells as stem cell-like cells.

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. We identified up-regulation of genes linked to carcinogenesis in cNCCs that were not previously reported to be related to NCCs, which was considered to be, an interesting feature in regard with carcinogenic potentials of NCCs such as melanoma and neuroblastoma. Wnt signal related genes were statistically up-regulated in cNCCs, also suggesting potential involvement of cNCCs in carcinogenesis. We also noticed intense expression of mesenchymal and neuronal markers in cNCCs and tNCCs, respectively. Consistent results were obtained from in vitro sphere-forming and differentiation assays. These results were in accordance with previous notion about differential potentials of cNCCs and tNCCs. We thus propose that sorting NCCs from P0-Cre/floxed-EGFP mice might be useful for the basic and translational research of NCCs. Furthermore, these newly-identified genes up-regulated in cNCC would provide helpful information on NC-originating tumors, developmental disorders in NCC derivatives, and potential applications of NCCs in regenerative medicine.