MCENet: A database for maize conditional co-expression network and network characterization collaborated with multi-dimensional omics levels

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.

Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics

RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species.

Analyzing lignin biosynthesis pathways in rattan using improved co-expression networks of NACs and MYBs

BACKGROUND

The rattan is a valuable plant resource with multiple applications in tropical forests. Calamus simplicifolius and Daemonorops jenkinsiana are the two most representative rattan species, supplying over 95% of the raw materials for the rattan industry. Hence, the wood properties of both rattans have always attracted researchers' attention.

RESULTS

We re-annotated the genomes, obtained 81 RNA-Seq datasets, and developed an improved pipeline to increase the reliability of co-expression networks of both rattans. Based on the data and pipeline, co-expression relationships were detected in 11 NACs, 49 MYBs, and 86 lignin biosynthesis genes in C. simplicifolius and four NACs, 59 MYBs, and 76 lignin biosynthesis genes in D. jenkinsiana, respectively. Among these co-expression pairs, several genes had a close relationship to the development of wood properties. Additionally, we detected the enzyme gene on the lignin biosynthesis pathway was regulated by either NAC or MYB, while LACCASES was regulated by both NAC and MYB. For D. jenkinsiana, the lignin biosynthesis regulatory network was characterized by positive regulation, and MYB possible negatively regulate non-expressed lignin biosynthesis genes in stem tissues. For C. simplicifolius, NAC may positively regulate highly expressed genes and negatively regulate non-expressed lignin biosynthesis genes in stem tissues. Furthermore, we established core regulatory networks of NAC and MYB for both rattans.

CONCLUSIONS

This work improved the accuracy of rattan gene annotation by integrating an efficient co-expression network analysis pipeline, enhancing gene coverage and accuracy of the constructed network, and facilitating an understanding of co-expression relationships among NAC, MYB, and lignin biosynthesis genes in rattan and other plants.

Network and Evolutionary Analysis Reveals Candidate Genes of Membrane Trafficking Involved in Maize Seed Development and Immune Response

The plant membrane-trafficking system plays a crucial role in maintaining proper cellular functions and responding to various developmental and environmental cues. Thus far, our knowledge of the maize membrane-trafficking system is still limited. In this study, we systematically identified 479 membrane-trafficking genes from the maize genome using orthology search and studied their functions by integrating transcriptome and evolution analyses. These genes encode the components of coated vesicles, AP complexes, autophagy, ESCRTs, retromers, Rab GTPases, tethering factors, and SNAREs. The maize genes exhibited diverse but coordinated expression patterns, with 249 genes showing elevated expression in reproductive tissues. Further WGCNA analysis revealed that five COPII components and four Rab GTPases had high connectivity with protein biosynthesis during endosperm development and that eight components of autophagy, ESCRT, Rab, and SNARE were strongly co-upregulated with defense-related genes and/or with secondary metabolic processes to confer basal resistance to Fusarium graminearum. In addition, we identified 39 membrane-trafficking genes with strong selection signals during maize domestication and/or improvement. Among them, ZmSec23a and ZmVPS37A were selected for kernel oil production during improvement and pathogen resistance during domestication, respectively. In summary, these findings will provide important hints for future appreciation of the functions of membrane-trafficking genes in maize.

Gene Co-Expression Network Tools and Databases for Crop Improvement

Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.

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.

The genetic mechanism of heterosis utilization in maize improvement

BACKGROUND

In maize hybrid breeding, complementary pools of parental lines with reshuffled genetic variants are established for superior hybrid performance. To comprehensively decipher the genetics of heterosis, we present a new design of multiple linked F1 populations with 42,840 F1 maize hybrids, generated by crossing a synthetic population of 1428 maternal lines with 30 elite testers from diverse genetic backgrounds and phenotyped for agronomic traits.

RESULTS

We show that, although yield heterosis is correlated with the widespread, minor-effect epistatic QTLs, it may be resulted from a few major-effect additive and dominant QTLs in early developmental stages. Floral transition is probably one critical stage for heterosis formation, in which epistatic QTLs are activated by paternal contributions of alleles that counteract the recessive, deleterious maternal alleles. These deleterious alleles, while rare, epistatically repress other favorable QTLs. We demonstrate this with one example, showing that Brachytic2 represses the Ubiquitin3 locus in the maternal lines; in hybrids, the paternal allele alleviates this repression, which in turn recovers the height of the plant and enhances the weight of the ear. Finally, we propose a molecular design breeding by manipulating key genes underlying the transition from vegetative-to-reproductive growth.

CONCLUSION

The new population design is used to dissect the genetic basis of heterosis which accelerates maize molecular design breeding by diminishing deleterious epistatic interactions.

PSDX: A Comprehensive Multi-Omics Association Database of Populus trichocarpa With a Focus on the Secondary Growth in Response to Stresses

Populus trichocarpa (P. trichocarpa) is a model tree for the investigation of wood formation. In recent years, researchers have generated a large number of high-throughput sequencing data in P. trichocarpa. However, no comprehensive database that provides multi-omics associations for the investigation of secondary growth in response to diverse stresses has been reported. Therefore, we developed a public repository that presents comprehensive measurements of gene expression and post-transcriptional regulation by integrating 144 RNA-Seq, 33 ChIP-seq, and six single-molecule real-time (SMRT) isoform sequencing (Iso-seq) libraries prepared from tissues subjected to different stresses. All the samples from different studies were analyzed to obtain gene expression, co-expression network, and differentially expressed genes (DEG) using unified parameters, which allowed comparison of results from different studies and treatments. In addition to gene expression, we also identified and deposited pre-processed data about alternative splicing (AS), alternative polyadenylation (APA) and alternative transcription initiation (ATI). The post-transcriptional regulation, differential expression, and co-expression network datasets were integrated into a new P. trichocarpa Stem Differentiating Xylem (PSDX) database (http://forestry.fafu.edu.cn/db/SDX), which further highlights gene families of RNA-binding proteins and stress-related genes. The PSDX also provides tools for data query, visualization, a genome browser, and the BLAST option for sequence-based query. Much of the data is also available for bulk download. The availability of PSDX contributes to the research related to the secondary growth in response to stresses in P. trichocarpa, which will provide new insights that can be useful for the improvement of stress tolerance in woody plants.

HpeNet: Co-expression Network Database for de novo Transcriptome Assembly of Paeonia lactiflora Pall

The herbaceous peony (Paeonia lactiflora Pall.) is a well-known ornamental flowering and pharmaceutical plant found in China. Its high medicinal value has long been recognized by traditional Chinese medicine (as Radix paeoniae Alba and Radix paeoniae Rubra), and it has become economically valued for its oilseed in recent years; like other Paeonia species, it has been identified as a novel resource for the α-linolenic acid used in seed oil production. However, its genome has not yet been sequenced, and little transcriptome data on Paeonia lactiflora are available. To obtain a comprehensive transcriptome for Paeonia lactiflora, RNAs from 10 tissues of the Paeonia lactiflora Pall. cv Shaoyou17C were used for de novo assembly, and 416,062 unigenes were obtained. Using a homology search, it was found that 236,222 (approximately 57%) unigenes had at least one BLAST hit in one or more public data resources. The construction of co-expression networks is a feasible means for improving unigene annotation. Using in-house transcriptome data, we obtained a co-expression network covering 95.13% of the unigenes. Then we integrated co-expression network analyses and lipid-related pathway genes to study lipid metabolism in Paeonia lactiflora cultivars. Finally, we constructed the online database HpeNet (http://bioinformatics.cau.edu.cn/HpeNet) to integrate transcriptome data, gene information, the co-expression network, and so forth. The database can also be searched for gene details, gene functions, orthologous matches, and other data. Our online database may help the research community identify functional genes and perform research on Paeonia lactiflora more conveniently. We hope that de novo transcriptome assembly, combined with co-expression networks, can provide a feasible means to predict the gene function of species that do not have a reference genome.

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.

Alternative splicing and duplication of PI-like genes in maize

Alternative splicing and duplication provide the possibility of functional divergence of MADS-box genes. Compared with its Arabidopsis counterpart PI gene, Zmm16 in maize recruits a new role in carpel abortion and floral asymmetry, whereas the other two duplicated genes, Zmm18/29, have not yet been attributed to any function in flower development as a typical B class gene does. Here, alternatively spliced transcripts of three PI^L genes were analyzed, among which we described the candidate functional isoforms and analyzed the potential effects of alternative splicing (AS) on protein-protein interactions as well, then their phylogenetic relationships with orthologs in typical grasses were further analyzed. Furthermore, we compared the cis-acting elements specific for three maize PI^L genes, especially the elements related to methyl jasmonate (MeJA) and gibberellic acid (GA), both hormones involved in the sex-determination process in maize. Together with the results from the co-expression networks during reproductive organ development, we speculated that, due to duplication and alternative splicing, Zmm18/29 may play a role in GA- and MeJA-related developmental process. These results provide novel clues for experimental validation of the evolutional meaning of maize PI^L genes.

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.

Dissecting the Regulatory Network of Leaf Premature Senescence in Maize (Zea mays L.) Using Transcriptome Analysis of ZmELS5 Mutant

Leaf premature senescence largely determines maize (Zea mays L.) grain yield and quality. A natural recessive premature-senescence mutant was selected from the breeding population, and near-isogenic lines were constructed using Jing24 as the recurrent parent. In the near-isogenic lines, the dominant homozygous material was wild-type (WT), and the recessive material of early leaf senescence was the premature-senescence-type ZmELS5. To identify major genes and regulatory mechanisms involved in leaf senescence, a transcriptome analysis of the ZmELS5 and WT near-isogenic lines (NILs) was performed. A total of 8796 differentially expressed transcripts were identified between ZmELS5 and WT, including 3811 up-regulated and 4985 down-regulated transcripts. By combining gene ontology, Kyoto Encyclopedia of Genes and Genomes, gene set, and transcription factor enrichment analyses, key differentially expressed genes were screened. The senescence regulatory network was predicted based on these key differentially expressed genes, which indicated that the senescence process is mainly regulated by bHLH, WRKY, and AP2/EREBP family transcription factors, leading to the accumulations of jasmonic acid and ethylene. This causes stress responses and reductions in the chlorophyll a/b-binding protein activity level. Then, decreased ATP synthase activity leads to increased photosystem II photodamage, ultimately leading to leaf senescence.

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.