The agriGO platform, which has been serving the scientific community for >10 years, specifically focuses on gene ontology (GO) enrichment analyses of plant and agricultural species. We continuously maintain and update the databases and accommodate the various requests of our global users. Here, we present our updated agriGO that has a largely expanded number of supporting species (394) and datatypes (865). In addition, a larger number of species have been classified into groups covering crops, vegetables, fish, birds and insects closely related to the agricultural community. We further improved the computational efficiency, including the batch analysis and P-value distribution (PVD), and the user-friendliness of the web pages. More visualization features were added to the platform, including SEACOMPARE (cross comparison of singular enrichment analysis), direct acyclic graph (DAG) and Scatter Plots, which can be merged by choosing any significant GO term. The updated platform agriGO v2.0 is now publicly accessible at http://systemsbiology.cau.edu.cn/agriGOv2/.

Gene Set Enrichment Analysis (GSEA) is a powerful method for interpreting biological meaning of a list of genes by computing the overlaps with various previously defined gene sets. As one of the most widely used annotations for defining gene sets, Gene Ontology (GO) system has been used in many enrichment analysis tools. EasyGO and agriGO, two GO enrichment analysis toolkits developed by our laboratory, have gained extensive usage and citations since their releases because of their effective performance and consistent maintenance. Responding to the increasing demands of more comprehensive analysis from the users, we developed a web server as an important component of our bioinformatics analysis toolkit, named PlantGSEA, which is based on GSEA method and mainly focuses on plant organisms. In PlantGSEA, 20 290 defined gene sets deriving from different resources were collected and used for GSEA analysis. The PlantGSEA currently supports gene locus IDs and Affymatrix microarray probe set IDs from four plant model species (Arabidopsis thaliana, Oryza sativa, Zea mays and Gossypium raimondii). The PlantGSEA is an efficient and user-friendly web server, and now it is publicly accessible at http://structuralbiology.cau.edu.cn/PlantGSEA.

Root hairs are an extensive structure of root epidermal cells and are critical for nutrient acquisition, soil anchorage, and environmental interactions in sessile plants. The phytohormone ethylene (ET) promotes root hair growth and also mediates the effects of different signals that stimulate hair cell development. However, the molecular basis of ET-induced root hair growth remains poorly understood. Here, we show that ET-activated transcription factor ETHYLENE-INSENSITIVE 3 (EIN3) physically interacts with ROOT HAIR DEFECTIVE 6 (RHD6), a well-documented positive regulator of hair cells, and that the two factors directly coactivate the hair length-determining gene () to promote root hair elongation. Transcriptome analysis further revealed the parallel roles of the regulator pairs EIN3/EIL1 (EIN3-LIKE 1) and RHD6/RSL1 (RHD6-LIKE 1). EIN3/EIL1 and RHD6/RSL1 coordinately enhance root hair initiation by selectively regulating a subset of core root hair genes. Thus, our work reveals a key transcriptional complex consisting of EIN3/EIL1 and RHD6/RSL1 in the control of root hair initiation and elongation, and provides a molecular framework for the integration of environmental signals and intrinsic regulators in modulating plant organ development.

Genome-wide maps of chromatin states have become a powerful representation of genome annotation and regulatory activity. We collected public and in-house plant epigenomic data sets and applied a Hidden Markov Model to define chromatin states, which included 290 553 (36 chromatin states), 831 235 (38 chromatin states) and 3 936 844 (26 chromatin states) segments across the whole genome of Arabidopsis thaliana, Oryza sativa and Zea mays, respectively. We constructed a Plant Chromatin State Database (PCSD, http://systemsbiology.cau.edu.cn/chromstates) to integrate detailed information about chromatin states, including the features and distribution of states, segments in states and related genes with segments. The self-organization mapping (SOM) results for these different chromatin signatures and UCSC Genome Browser for visualization were also integrated into the PCSD database. We further provided differential SOM maps between two epigenetic marks for chromatin state comparison and custom tools for new data analysis. The segments and related genes in SOM maps can be searched and used for motif and GO analysis, respectively. In addition, multi-species integration can be used to discover conserved features at the epigenomic level. In summary, our PCSD database integrated the identified chromatin states with epigenetic features and may be beneficial for communities to discover causal functions hidden in plant chromatin.

The first ncRNA found was an alanine tRNA in baker's yeast, and the first detected microRNAs (miRNAs) promoted ncRNA research to a whole new level. Research on ncRNAs in animals has focused on the medical field, while in plant scientists are more concerned with improving agronomic traits. In 2010, we constructed a plant miRNA database named PMRD to meet the demand for miRNA research in plants. To provide a way to do fundamental research on plant ncRNAs and take full advantage of tremendous public resources, we designed an updated platform called plant ncRNA database (PNRD) based on its predecessor PMRD, which is accessible at http://structuralbiology.cau.edu.cn/PNRD. We collected a total of 25739 entries of 11 different types of ncRNAs from 150 plant species. Targets of miRNAs were extended to 178138 pairs in 46 species, while the number of miRNA expression profiles reached 35. Improvements in PNRD are not only the larger amounts of data, but also better service, such as a more user-friendly interface, more multifunctional and browsing options and more background data for users to download. We also integrated currently prevalent technologies and toolkits to strengthen the capability of the database and provide a one-stop service for scientific users.

While previous studies have shown that histone modifications could influence plant growth and development by regulating gene transcription, knowledge about the relationships between these modifications and gene expression is still limited. This study used chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq), to investigate the genome-wide distribution of four histone modifications: di and trimethylation of H3K4 (H3K4me2 and H3K4me3) and acylation of H3K9 and H3K27 (H3K9ac and H3K27ac) in Oryza sativa L. japonica. By analyzing published DNase-Seq data, this study explored DNase-Hypersensitive (DH) sites along the rice genome. The histone marks appeared mainly in generic regions and were enriched around the transcription start sites (TSSs) of genes. This analysis demonstrated that the four histone modifications and the DH sites were all associated with active transcription. Furthermore, the four histone modifications were highly concurrent with transcript regions-a promising feature that was used to predict missing genes in the rice gene annotation. The predictions were further validated by experimentally confirming the transcription of two predicted missing genes. Moreover, a sequence motif analysis was constructed in order to identify the DH sites and many putative transcription factor binding sites.

Plant genera with both diploid and polyploid species are a common evolutionary occurrence. Polyploids, especially allopolyploids such as cotton and wheat, are a great model system for heterosis research. Here, we have integrated genome sequences and transcriptome data of Gossypium species to construct co-expression networks and identified functional modules from different cotton species, including 1155 and 1884 modules in G. arboreum and G. hirsutum, respectively. We overlayed the gene expression results onto the co-expression network. We further provided network comparison analysis for orthologous genes across the diploid and allotetraploid Gossypium. We also constructed miRNA-target networks and predicted PPI networks for both cotton species. Furthermore, we integrated in-house ChIP-seq data of histone modification (H3K4me3) together with cis-element analysis and gene sets enrichment analysis tools for studying possible gene regulatory mechanism in Gossypium species. Finally, we have constructed an online ccNET database (http://structuralbiology.cau.edu.cn/gossypium) for comparative gene functional analyses at a multi-dimensional network and epigenomic level across diploid and polyploid Gossypium species. The ccNET database will be beneficial for community to yield novel insights into gene/module functions during cotton development and stress response, and might be useful for studying conservation and diversity in other polyploid plants, such as T. aestivum and Brassica napus.

As a histone variant, H2A.Z is highly conserved among species and plays a significant role in diverse cellular processes. Here, we generated genome-wide maps of H2A.Z in Oryza sativa (rice) callus and seedling by combining chromatin immunoprecipitation using H2A.Z antibody and high-throughput sequencing. We found a significantly high peak and a small peak of H2A.Z distributed at the 5' and 3' ends of highly expressed genes, respectively. H2A.Z was also associated with inactive genes in both tissues. H3 lysine 4 trimethylation was associated with H2A.Z deposition at the 5' end of expressed genes, and H3 lysine 27 trimethylation peaks were partially associated with H2A.Z. In summary, our study provides global analysis data for the distribution of H2A.Z in the rice genome. Our results demonstrate that the differential deposition of H2A.Z might play important roles in gene transcription during rice development.