WheatCENet (Comparing Co-expression Networks of allohexaploid Wheat and its progenitors) database integrated 425 transcriptomic datasets (112 for Triticum aestivum (AABBDD), 153 for Triticum dicoccoides (AABB), 76 for Triticum urartu (AA), 42 for Aegilops tauschii (DD) from public databases to construct four global (T. aestivum, T. dicoccoides, T. urartu, and Ae. tauschii) and two T. aestivum conditional (tissue-specific and stress-treatment) co-expression network based on the PCC and MR algorithms.
We also collected comprehensive functional annotations (for example, Gene family, Ontology, miRNA, Metabolic pathway and so on) to predict gene functions. Besides, we provided analysis tools like GSEA, GO, module and motif analysis to analyze the possible function of gene sets and some basic tools like ID conversion, BLAST, sequence/FPKM extract. We hope that our database might help plant research communities to identify wheat functional genes or modules that regulate important agronomic traits.
How to cite:
Li, et al. "WheatCENet: A Database for Comparative Co-expression Networks Analysis of Allohexaploid Wheat and Its Progenitors." Genomics, Proteomics & Bioinformatics (doi: 10.1016/j.gpb.2022.04.007). [Link]
|Basic tools||Quick Search||Gene search (detail information about gene), ortholog search (rice and arabidopsis) and Function search (Pfam, Gene Ontology, Functional module) .
|Co-expression Network||Network search (four global or two conditional); Network comparison (compare networks between two species or global and conditional); Ortholog network Comparison among three species.|
|BLAST analysis||Gene, CDS, protein sequence can be used. |
|ID conversion||ID conversion of different genome versions.|
|FPKM extract||Gene expression profile can be extracted or visualized by this tools.|
|Sequence extract||Retrieve sequence by genomic interval or gene id.|
|UCSC genome browser||Epigenomics data of T. aestivum and RNA-seq data of T. dicoccoides can be visualized.|
|Analysis tools||Gene Sets Analysis||These gene sets are divided into 5 categories, including GO gene sets (G1), Gene Family based gene sets (G2), Pathway gene sets (G3), Target gene sets (G4), other ontology gene sets (G5) based on PlantGSEA/PlantGSAD.
|GO analysis||Gene ontology analysis can be used to predict the function of gene sets.|
|Motif analysis||motif analysis can be used to predict the binding site of sequence or gene.|
|Module analysis||module analysis can be used to predict the function of gene sets based on co-expression network.|