The chromosome-level genome and functional database accelerate research about biosynthesis of secondary metabolites in Rosa roxburghii.

Rosa roxburghii Tratt, a valuable plant in China with long history, is famous for its fruit. It possesses various secondary metabolites, such as L-ascorbic acid (vitamin C), alkaloids and poly saccharides, which make it a high nutritional and medicinal value. Here we characterized the chromosome-level genome sequence of R. roxburghii, comprising seven pseudo-chromosomes with a total size of 531 Mb and a heterozygosity of 0.25%. We also annotated 45,226 coding gene loci after masking repeat elements. Orthologs for 90.1% of the Complete Single-Copy BUSCOs were found in the R. roxburghii annotation. By aligning with protein sequences from public platform, we annotated 85.89% genes from R. roxburghii. Comparative genomic analysis revealed that R. roxburghii diverged from Rosa chinensis approximately 5.58 to 13.17 million years ago, and no whole-genome duplication event occurred after the divergence from eudicots. To fully utilize this genomic resource, we constructed a genomic database RroFGD with various analysis tools. Otherwise, 69 enzyme genes involved in L-ascorbate biosynthesis were identified and a key enzyme in the biosynthesis of vitamin C, GDH (L-Gal-1-dehydrogenase), is used as an example to introduce the functions of the database. This genome and database will facilitate the future investigations into gene function and molecular breeding in R. roxburghii.

DhuFAP: a platform for gene functional analysis in Dendrobium huoshanense.

BACKGROUND: Dendrobium huoshanense, a traditional medicinal and food plant, has a rich history of use. Recently, its genome was decoded, offering valuable insights into gene function. However, there is no comprehensive gene functional analysis platform for D. huoshanense. RESULT: To address this, we created a platform for gene function analysis and comparison in D. huoshanense (DhuFAP). Using 69 RNA-seq samples, we constructed a gene co-expression network and annotated D. huoshanense genes by aligning sequences with public protein databases. Our platform contained tools like Blast, gene set enrichment analysis, heatmap analysis, sequence extraction, and JBrowse. Analysis revealed co-expression of transcription factors (C2H2, GRAS, NAC) with genes encoding key enzymes in alkaloid biosynthesis. We also showcased the reliability and applicability of our platform using Chalcone synthases (CHS). CONCLUSION: DhuFAP ( www.gzybioinformatics.cn/DhuFAP ) and its suite of tools represent an accessible and invaluable resource for researchers, enabling the exploration of functional information pertaining to D. huoshanense genes. This platform stands poised to facilitate significant biological discoveries in this domain.

ASAP: a platform for gene functional analysis in Angelica sinensis.

BACKGROUND: Angelica sinensis (Danggui), a renowned medicinal orchid, has gained significant recognition for its therapeutic effects in treating a wide range of ailments. Genome information serves as a valuable resource, enabling researchers to gain a deeper understanding of gene function. In recent times, the availability of chromosome-level genomes for A. sinensis has opened up vast opportunities for exploring gene functionality. Integrating multiomics data can allow researchers to unravel the intricate mechanisms underlying gene function in A. sinensis and further enhance our knowledge of its medicinal properties. RESULTS: In this study, we utilized genomic and transcriptomic data to construct a coexpression network for A. sinensis. To annotate genes, we aligned them with sequences from various databases, such as the NR, TAIR, trEMBL, UniProt, and SwissProt databases. For GO and KEGG annotations, we employed InterProScan and GhostKOALA software. Additionally, gene families were predicted using iTAK, HMMER, OrholoFinder, and KEGG annotation. To facilitate gene functional analysis in A. sinensis, we developed a comprehensive platform that integrates genomic and transcriptomic data with processed functional annotations. The platform includes several tools, such as BLAST, GSEA, Heatmap, JBrowse, and Sequence Extraction. This integrated resource and approach will enable researchers to explore the functional aspects of genes in A. sinensis more effectively. CONCLUSION: We developed a platform, named ASAP, to facilitate gene functional analysis in A. sinensis. ASAP ( www.gzybioinformatics.cn/ASAP ) offers a comprehensive collection of genome data, transcriptome resources, and analysis tools. This platform serves as a valuable resource for researchers conducting gene functional research in their projects, providing them with the necessary data and tools to enhance their studies.

PlantCHRs: A comprehensive database of plant chromatin remodeling factors.

The Snf2 protein family is a group of ATP-dependent chromatin remodeling factors (CHRs) that play an essential role in gene expression regulation. In plants, Snf2 is involved in growth, development, as well as stress resistance. However, only a very limited number of experimentally validated Snf2 have been identified and reported, while the majority remaining undiscovered in most species . In this study, we predicted 3135 Snf2 proteins and 8398 chromatin remodeling complex (CRC) subunits in diverse plant species, and constructed the Plant Chromatin Remodeling Factors Database (PlantCHRs, http://www.functionalgenomics.cn/PlantCHRs/), which provide a comprehensive resource for researchers to access information about plant CHRs. We also developed an online tool capable of predicting CHRs and CRC subunits. Moreover, we investigated the distribution of Snf2 proteins in different species and observed a significant increase in the number of Snf2 proteins and the diversity of the Snf2 subfamily during the evolution, highlighting their evolutionary importance. By analyzing the expression patterns of the Snf2 genes in different tissues of maize and Arabidopsis, we found that the Snf2 proteins may show some conservation across different species in regulating plant growth and development. Over the all, we established a comprehensive database for plant CHRs, which will facilitate the researches on plant chromatin remodeling.

Lipopolysaccharide (LPS) extracted from Bacteroides vulgatus effectively prevents LPS extracted from Escherichia coli from inducing epithelial­mesenchymal transition.

Pathological epithelial­mesenchymal transition (EMT) has been shown to fulfill a key role in the development and progression of a variety of lung diseases. It has been demonstrated that the inflammatory microenvironment is a decisive factor in inducing pathological EMT. Hexacylated lipopolysaccharide (LPS) [or proacylated lipopolysaccharide (P­LPS), which functions as proinflammatory lipopolysaccharide] is one of the most effective Toll­like receptor 4 (TLR4) agonists. Furthermore, the pentacylated and tetracylated form of lipopolysaccharide (or A­LPS, which functions as anti­inflammatory lipopolysaccharide) has been shown to elicit competitive antagonistic effects against the pro­inflammatory activity of P­LPS. At present, it remains unclear whether LPS extracted from Bacteroides vulgatus (BV­LPS) can prevent LPS extracted from Escherichia coli (EC­LPS) from inducing pathological EMT. In the present study, A549 cells and C57BL/6 mice lung tissue were both induced by EC­LPS (P­LPS) and BV­LPS (A­LPS), either alone or in combination. The anticipated anti­inflammatory effects of BV­LPS were analyzed by examining the lung coefficient, lung pathology, A549 cell morphology and expression levels both of the inflammatory cytokines, IL­1ß, IL­6 and TNF­α and of the EMT signature proteins, epithelial cadherin (E­cadherin), α­smooth muscle actin (α­SMA) and vimentin. In addition, the expression levels of TLR4, bone morphogenic protein and activin membrane­bound inhibitor (BAMBI) and Snail were detected and the possible mechanism underlying how BV­LPS may prevent EC­LPS­induced EMT was analyzed. The results obtained showed that the morphology of the A549 cells was significantly polarized, the lung index was significantly increased, the alveolar structure was collapsed and the expression levels of IL­1ß, IL­6, TNF­α, α­SMA, vimentin, TLR4 and Snail in both lung tissue and A549 cells were significantly increased, whereas those of E­cadherin and BAMBI were significantly decreased. Treatment with BV­LPS in combination with EC­LPS was found to reverse these changes. In conclusion, the present study demonstrated that BV­LPS is able to effectively prevent EC­LPS­induced EMT in A549 cells and in mouse lung tissue and furthermore, the underlying mechanism may be associated with inhibition of the TLR4/BAMBI/Snail signaling pathway.

RoseAP: an analytical platform for gene function of Rosa rugosa.

Rosa rugosa, a perennial shrub belonging to family Rosaceae, is a well-known ornamental plant. Its petals contain an abundance of essential oils and anthocyanins with enormous economic and health benefits when used as edible or cosmetic ingredients. The whole genome of R. rugosa was sequenced in 2021, which provided opportunities and challenges for gene regulation. However, many gene functions remain unknown. Therefore, an analytical platform named RoseAP (http://www.gzybioinformatics.cn/RoseAP/index.php) for the functional analysis of R. rugosa genes was constructed. It improved the gene annotation rate by integrating and analyzing genomic and transcriptomic datasets. First, 38,815 genes, covering 97.76% of the coding genes, were annotated functionally and structurally using a variety of algorithms and rules. Second, a total of 33 transcriptome samples were integrated, including 23 samples from our lab and 10 samples from the SRA database. A co-expression network containing approximately 29,657 positive or negative gene pairs, covering 74.7% of the coding genes, was constructed based on PCC and MR algorithms. Network analysis revealed that the DFR function was closely related to anthocyanin metabolism. It demonstrated the reliability of the network. Several SAUR genes of R. rugosa shared similar expression patterns. RoseAP was used to determine the sequence, structure, functional annotation, expression profile, regulatory network, and functional modules at the transcriptional and protein levels by inputting gene IDs. In addition, auxiliary analytical tools, including BLAST, gene set enrichment, orthologue conversion, gene sequence extraction, gene expression value extraction, and JBrowse, were utilized. Regular updates to RoseAP are expected to facilitate mining of gene function and promote genetic improvement in R. rugosa.

GelFAP v2.0: an improved platform for Gene functional analysis in Gastrodia elata.

BACKGROUND: Gastrodia elata (tianma), a well-known medicinal orchid, is widely used to treat various kinds of diseases with its dried tuber. In recent years, new chromosome-level genomes of G.elata have been released in succession, which offer an enormous resource pool for understanding gene function. Previously we have constructed GelFAP for gene functional analysis of G.elata. As genomes are updated and transcriptome data is accumulated, collection data in GelFAP cannot meet the need of researchers. RESULTS: Based on new chromosome-level genome and transcriptome data, we constructed co-expression network of G. elata, and then we annotated genes by aligning with sequences from NR, TAIR, Uniprot and Swissprot database. GO (Gene Ontology) and KEGG (Kyoto Encylopaedia of Genes and Genomes) annotations were predicted by InterProScan and GhostKOALA software. Gene families were further predicted by iTAK (Plant Transcription factor and Protein kinase Identifier and Classifier), HMMER (hidden Markov models), InParanoid. Finally, we developed an improved platform for gene functional analysis in G. elata (GelFAP v2.0) by integrating new genome, transcriptome data and processed functional annotation. Several tools were also introduced to platform including BLAST (Basic Local Alignment Search Tool), GSEA (Gene Set Enrichment Analysis), Heatmap, JBrowse, Motif analysis and Sequence extraction. Based on this platform, we found that the flavonoid biosynthesis might be regulated by transcription factors (TFs) such as MYB, HB and NAC. We also took C4H and GAFP4 as examples to show the usage of our platform. CONCLUSION: An improved platform for gene functional analysis in G. elata (GelFAP v2.0, www.gzybioinformatics.cn/Gelv2 ) was constructed, which provides better genome data, more transcriptome resources and more analysis tools. The updated platform might be preferably benefit researchers to carry out gene functional research for their project.

GURFAP: A Platform for Gene Function Analysis in Glycyrrhiza Uralensis.

Glycyrrhiza uralensis (Licorice), which belongs to Leguminosae, is famous for the function of pharmacologic action and natural sweetener with its dried roots and rhizomes. In recent years, the whole-genome sequence of G. uralensis has been completed, which will help to lay the foundation for the study of gene function. Here, we integrated the available genomic and transcriptomic data of G. uralensis and constructed the G. uralensis gene co-expression network. We then annotated gene functions of G. uralensis via aligning with public databases. Furthermore, gene families of G. uralensis were predicted by tools including iTAK (Plant Transcription factor and Protein kinase Identifier and Classifier), HMMER (hidden Markov models), InParanoid, and PfamScan. Finally, we constructed a platform for gene function analysis in G. uralensis (GURFAP, www.gzybioinfoormatics.cn/GURFAP). For analyzed and predicted gene function, we introduced various tools including BLAST (Basic local alignment search tool), GSEA (Gene set enrichment analysis), Motif, Heatmap, and JBrowse. Our analysis based on this platform indicated that the biosynthesis of glycyrrhizin might be regulated by MYB and bHLH. We also took CYP88D6, CYP72A154, and bAS gene in the synthesis pathway of glycyrrhizin as examples to demonstrate the reliability and availability of our platform. Our platform GURFAP will provide convenience for researchers to mine the gene function of G. uralensis and thus discover more key genes involved in the biosynthetic pathway of active ingredients.

PlantGSAD: a comprehensive gene set annotation database for plant species.

With the accumulation of massive data sets from high-throughput experiments and the rapid emergence of new types of omics data, gene sets have become more diverse and essential for the refinement of gene annotation at multidimensional levels. Accordingly, we collected and defined 236 007 gene sets across different categories for 44 plant species in the Plant Gene Set Annotation Database (PlantGSAD). These gene sets were divided into nine main categories covering many functional subcategories, such as trait ontology, co-expression modules, chromatin states, and liquid-liquid phase separation. The annotations from the collected gene sets covered all of the genes in the Brassicaceae species Arabidopsis and Poaceae species Oryza sativa. Several GSEA tools are implemented in PlantGSAD to improve the efficiency of the analysis, including custom SEA for a flexible strategy based on customized annotations, SEACOMPARE for the cross-comparison of SEA results, and integrated visualization features for ontological analysis that intuitively reflects their parent-child relationships. In summary, PlantGSAD provides numerous gene sets for multiple plant species and highly efficient analysis tools. We believe that PlantGSAD will become a multifunctional analysis platform that can be used to predict and elucidate the functions and mechanisms of genes of interest. PlantGSAD is publicly available at http://systemsbiology.cau.edu.cn/PlantGSEAv2/.

LjaFGD: Lonicera japonica functional genomics database.

Lonicera japonica Thunb., a traditional Chinese herb, has been used for treating human diseases for thousands of years. Recently, the genome of L. japonica has been decoded, providing valuable information for research into gene function. However, no comprehensive database for gene functional analysis and mining is available for L. japonica. We therefore constructed LjaFGD (www.gzybioinformatics.cn/LjaFGD and bioinformatics.cau.edu.cn/LjaFGD), a database for analyzing and comparing gene function in L. japonica. We constructed a gene co-expression network based on 77 RNA-seq samples, and then annotated genes of L. japonica by alignment against protein sequences from public databases. We also introduced several tools for gene functional analysis, including Blast, motif analysis, gene set enrichment analysis, heatmap analysis, and JBrowse. Our co-expression network revealed that MYB and WRKY transcription factor family genes were co-expressed with genes encoding key enzymes in the biosynthesis of chlorogenic acid and luteolin in L. japonica. We used flavonol synthase 1 (LjFLS1) as an example to show the reliability and applicability of our database. LjaFGD and its various associated tools will provide researchers with an accessible platform for retrieving functional information on L. japonica genes to further biological discovery.

GelFAP: Gene Functional Analysis Platform for Gastrodia elata.

Gastrodia elata, also named Tianma, is a valuable traditional Chinese herbal medicine. It has numerous important pharmacological roles such as in sedation and lowering blood pressure and as anticonvulsant and anti-aging, and it also has effects on the immune and cardiovascular systems. The whole genome sequencing of G. elata has been completed in recent years, which provides a strong support for the construction of the G. elata gene functional analysis platform. Therefore, in our research, we collected and processed 39 transcriptome data of G. elata and constructed the G. elata gene co-expression networks, then we identified functional modules by the weighted correlation network analysis (WGCNA) package. Furthermore, gene families of G. elata were identified by tools including HMMER, iTAK, PfamScan, and InParanoid. Finally, we constructed a gene functional analysis platform for G. elata . In our platform, we introduced functional analysis tools such as BLAST, gene set enrichment analysis (GSEA), and cis-elements (motif) enrichment analysis tool. In addition, we analyzed the co-expression relationship of genes which might participate in the biosynthesis of gastrodin and predicted 19 mannose-binding lectin antifungal proteins of G. elata. We also introduced the usage of the G. elata gene function analysis platform (GelFAP) by analyzing CYP51G1 and GFAP4 genes. Our platform GelFAP may help researchers to explore the gene function of G. elata and make novel discoveries about key genes involved in the biological processes of gastrodin.

Coexpression Analysis Reveals Dynamic Modules Regulating the Growth and Development of Cirri in the Rattans (Calamus simplicifolius and Daemonorops jenkinsiana).

Rattan is regarded as one of the major non-timber forest products, second only to wood and bamboo, worldwide. Although the published genomes of Calamus simplicifolius and Daemonorops jenkinsiana have facilitated genome-wide gene functional analyses, coexpression networks (CENs) provide more comprehensive and complete annotations of gene function at the transcriptome level. Thus, we analyzed the CENs of the two rattans, C. simplicifolius and D. jenkinsiana, by integrating the genome sequences and analyzing in-house transcriptome data from different development stages of their cirri using a well-developed strategy. A total of 3,504 and 3,027 functional modules were identified in C. simplicifolius and D. jenkinsiana, respectively, based on a combination of CENs, gene family classification, and function enrichment tools. These modules covered the major developmental processes, including photosynthesis, lignin biosynthesis, flavonoid biosynthesis, and phenylpropanoid biosynthesis. Reference annotations were refined using CENs and functional modules. Moreover, we obtained novel insights into the regulation of cirrus growth and development in rattans. Furthermore, Rattan-NET (http://rattan.bamboogdb.org/), an online database with analysis tools for gene set enrichment analysis, module enrichment, network comparison analysis, and cis-element analysis, was constructed for the easy analysis of gene function and regulation modules involved in the growth and development of cirri in rattans.

AppleMDO: A Multi-Dimensional Omics Database for Apple Co-Expression Networks and Chromatin States.

As an economically important crop, apple is one of the most cultivated fruit trees in temperate regions worldwide. Recently, a large number of high-quality transcriptomic and epigenomic datasets for apple were made available to the public, which could be helpful in inferring gene regulatory relationships and thus predicting gene function at the genome level. Through integration of the available apple genomic, transcriptomic, and epigenomic datasets, we constructed co-expression networks, identified functional modules, and predicted chromatin states. A total of 112 RNA-seq datasets were integrated to construct a global network and a conditional network (tissue-preferential network). Furthermore, a total of 1,076 functional modules with closely related gene sets were identified to assess the modularity of biological networks and further subjected to functional enrichment analysis. The results showed that the function of many modules was related to development, secondary metabolism, hormone response, and transcriptional regulation. Transcriptional regulation is closely related to epigenetic marks on chromatin. A total of 20 epigenomic datasets, which included ChIP-seq, DNase-seq, and DNA methylation analysis datasets, were integrated and used to classify chromatin states. Based on the ChromHMM algorithm, the genome was divided into 620,122 fragments, which were classified into 24 states according to the combination of epigenetic marks and enriched-feature regions. Finally, through the collaborative analysis of different omics datasets, the online database AppleMDO (http://bioinformatics.cau.edu.cn/AppleMDO/) was established for cross-referencing and the exploration of possible novel functions of apple genes. In addition, gene annotation information and functional support toolkits were also provided. Our database might be convenient for researchers to develop insights into the function of genes related to important agronomic traits and might serve as a reference for other fruit trees.

AtSPX1-mediated transcriptional regulation during leaf senescence in Arabidopsis thaliana.

Leaf senescence is the final stage of leaf growth, a highly coordinated and complicated process. Phosphorus as an essential macronutrient for plant growth is remobilized from senescing leaves to other vigorous parts of the plant. In this study, through data mining, we found some phosphate starvation induced genes such as AtSPX1, were significantly induced in aging leaves in Arabidopsis. We applied a reverse genetics approach to investigate the phenotypes of transgenic plants and mutant plants, and the results showed that the overexpression of AtSPX1 accelerated leaf senescence, suppressed Pi accumulation, promoted SA production and H2O2 levels in leaves, while the mutant lines of AtSPX1 showed slightly delayed leaf senescence. We conducted RNA-seq-based transcriptome analysis together with GO and GSEA enrichment analyses for transgenic vs. wild-type plants to elucidate the possible underlying regulatory mechanism. The 558 genes that were up-regulated in the overexpression plants 35S::AtSPX1/WT, were significantly enriched in the process of leaf senescence, Pi starvation responses and SA signaling pathways, as were the target genes of some transcription factors such as WRKYs and NACs. In a word, we characterized AtSPX1 as a key regulator, which mediated the crosstalks among leaf senescence, Pi starvation and SA signaling pathways in Arabidopsis thaliana.

croFGD: Catharanthus roseus Functional Genomics Database.

Catharanthus roseus is a medicinal plant, which can produce monoterpene indole alkaloid (MIA) metabolites with biological activity and is rich in vinblastine and vincristine. With release of the scaffolded genome sequence of C. roseus, it is necessary to annotate gene functions on the whole-genome level. Recently, 53 RNA-seq datasets are available in public with different tissues (flower, root, leaf, seedling, and shoot) and different treatments (MeJA, PnWB infection and yeast elicitor). We used in-house data process pipeline with the combination of PCC and MR algorithms to construct a co-expression network exploring multi-dimensional gene expression (global, tissue preferential, and treat response) through multi-layered approaches. In the meanwhile, we added miRNA-target pairs, predicted PPI pairs into the network and provided several tools such as gene set enrichment analysis, functional module enrichment analysis, and motif analysis for functional prediction of the co-expression genes. Finally, we have constructed an online croFGD database (http://bioinformatics.cau.edu.cn/croFGD/). We hope croFGD can help the communities to study the C. roseus functional genomics and make novel discoveries about key genes involved in some important biological processes.

PlantEAR: Functional Analysis Platform for Plant EAR Motif-Containing Proteins.

The Ethylene-responsive element binding factor-associated Amphiphilic Repression (EAR) motifs, which were initially identified in members of the Arabidopsis ethylene response factor (ERF) family, are transcriptional repression motifs in plants and are defined by the consensus sequence patterns of either LxLxL or DLNxxP. EAR motif-containing proteins can function as transcription repressors, thus interacting with co-repressors, such as TOPLESS and AtSAP18, affecting the structure of chromatin by histone modifications and thereby repressing gene transcription. EAR motif-containing proteins are highly conserved across diverse plant species and play important roles in hormone signal transduction, stress responses and development, but they have not been identified in most plants. In this study, we identified 20,542 EAR motif-containing proteins from 71 plant species based on a Hidden Markov Model and orthologous gene search, and then we constructed a functional analysis platform for plant EAR motif-containing proteins (PlantEAR, http://structuralbiology.cau.edu.cn/plantEAR) by integrating a variety of functional annotations and processed data. Several tools were provided as functional support for EAR motif-containing proteins, such as browse, search, co-expression and protein-protein interaction (PPI) network analysis as well as cis-element analysis and gene set enrichment analysis (GSEA). In addition, basing on the identified EAR motif-containing proteins, we also explored their distribution in various species and found that the numbers of EAR motif-containing proteins showed an increasing trend in evolution from algae to angiosperms.