SFGD: a comprehensive platform for mining functional information from soybean transcriptome data and its use in identifying acyl-lipid metabolism pathways

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.

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.

Genetic and Genomic Resources for Soybean Breeding Research

Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop 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.

An evolutionary population structure model reveals pleiotropic effects of GmPDAT for traits related to seed size and oil content in soybean

Seed oil traits in soybean that are of benefit to human nutrition and health have been selected for during crop domestication. However, these domesticated traits have significant differences across various evolutionary types. In this study, we found that the integration of evolutionary population structure (evolutionary types) with genome-wide association studies increased the power of gene detection, and it identified one locus for traits related to seed size and oil content on chromosome 13. This domestication locus, together with another one in a 200-kb region, was confirmed by the GEMMA and EMMAX software. The candidate gene, GmPDAT, had higher expressional levels in high-oil and large-seed accessions than in low-oil and small-seed accessions. Overexpression lines had increased seed size and oil content, whereas RNAi lines had decreased seed size and oil content. The molecular mechanism of GmPDAT was deduced based on results from linkage analysis for triacylglycerols and on histocytological comparisons of transgenic soybean seeds. Our results illustrate a new approach for identifying domestication genes with pleiotropic effects.

New insights into Arabidopsis transcriptome complexity revealed by direct sequencing of native RNAs

Arabidopsis thaliana transcriptomes have been extensively studied and characterized under different conditions. However, most of the current ‘RNA-sequencing’ technologies produce a relatively short read length and demand a reverse-transcription step, preventing effective characterization of transcriptome complexity. Here, we performed Direct RNA Sequencing (DRS) using the latest Oxford Nanopore Technology (ONT) with exceptional read length. We demonstrate that the complexity of the A. thaliana transcriptomes has been substantially under-estimated. The ONT direct RNA sequencing identified novel transcript isoforms at both the vegetative (14-day old seedlings, stage 1.04) and reproductive stages (stage 6.00–6.10) of development. Using in-house software called TrackCluster, we determined alternative transcription initiation (ATI), alternative polyadenylation (APA), alternative splicing (AS), and fusion transcripts. More than 38 500 novel transcript isoforms were identified, including six categories of fusion-transcripts that may result from differential RNA processing mechanisms. Aided by the Tombo algorithm, we found an enrichment of m5C modifications in the mobile mRNAs, consistent with a recent finding that m5C modification in mRNAs is crucial for their long-distance movement. In summary, ONT DRS offers an advantage in the identification and functional characterization of novel RNA isoforms and RNA base modifications, significantly improving annotation of the A. thaliana genome.

Overcoming collinearity in path analysis of soybean [Glycine max (L.) Merr.] grain oil content

Path analysis allows understanding the direct and indirect effects among traits. Multicollinearity in correlation matrices may cause a bias in path analysis estimates. This study aimed to: a) understand the correlation among soybean traits and estimate their direct and indirect effects on gain oil content; b) verify the efficiency of ridge path analysis and trait culling to overcome colinearity. Three different matrices with different levels of collinearity were obtained by trait culling. Ridge path analysis was performed on matrices with strong collinearity; otherwise, a traditional path analysis was performed. The same analyses were run on a simulated dataset. Trait culling was applied to matrix R originating the matrices R1 and R2. Path analysis for matrices R1 and R2 presented a high determination coefficient (0.856 and 0.832, respectively) and low effect of the residual variable (0.379 and 0.410 respectively). Ridge path analysis presented low determination coefficient (0.657) and no direct effects greater than the effects of the residual variable (0.585). Trait culling was more effective to overcome collinearity. Mass of grains, number of nodes, and number of pods are promising for indirect selection for oil content.

PCSD: a plant chromatin state database

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.

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.

Homeostasis in the soybean miRNA396-GRF network is essential for productive soybean cyst nematode infections

Heterodera glycines, the soybean cyst nematode, penetrates soybean roots and migrates to the vascular cylinder where it forms a feeding site called the syncytium. MiRNA396 (miR396) targets growth-regulating factor (GRF) genes, and the miR396-GRF1/3 module is a master regulator of syncytium development in model cyst nematode H. schachtii infection of Arabidopsis. Here, we investigated whether this regulatory system operates similarly in soybean roots and is likewise important for H. glycines infection. We found that a network involving nine MIR396 and 23 GRF genes is important for normal development of soybean roots and that GRF function is specified in the root apical meristem by miR396. All MIR396 genes are down-regulated in the syncytium during its formation phase while, specifically, 11 different GRF genes are up-regulated. The switch to the syncytium maintenance phase coincides with up-regulation of MIR396 and down-regulation of the 11 GRF genes specifically via post-transcriptional regulation by miR396. Furthermore, interference with the miR396-GRF6/8-13/15-17/19 regulatory network, through either overexpression or knockdown experiments, does not affect the number of H. glycines juveniles that enter the vascular cylinder to initiate syncytia, but specifically inhibits efficient H. glycines development to adult females. Therefore, homeostasis in the miR396-GRF6/8-13/15-17/19 regulatory network is essential for productive H. glycines infections.

An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus

BACKGROUND

Rapeseed (Brassica napus L.) and soybean (Glycine max L.) seeds are rich in both protein and oil, which are major sources of biofuels and nutrition. Although the difference in seed oil content between soybean (~ 20%) and rapeseed (~ 40%) exists, little is known about its underlying molecular mechanism.

RESULTS

An integrated omics analysis was performed in soybean, rapeseed, Arabidopsis (Arabidopsis thaliana L. Heynh), and sesame (Sesamum indicum L.), based on Arabidopsis acyl-lipid metabolism- and carbon metabolism-related genes. As a result, candidate genes and their transcription factors and microRNAs, along with phylogenetic analysis and co-expression network analysis of the PEPC gene family, were found to be largely associated with the difference between the two species. First, three soybean genes (Glyma.13G148600, Glyma.13G207900 and Glyma.12G122900) co-expressed with GmPEPC1 are specifically enriched during seed storage protein accumulation stages, while the expression of BnPEPC1 is putatively inhibited by bna-miR169, and two genes BnSTKA and BnCKII are co-expressed with BnPEPC1 and are specifically associated with plant circadian rhythm, which are related to seed oil biosynthesis. Then, in de novo fatty acid synthesis there are rapeseed-specific genes encoding subunits β-CT (BnaC05g37990D) and BCCP1 (BnaA03g06000D) of heterogeneous ACCase, which could interfere with synthesis rate, and β-CT is positively regulated by four transcription factors (BnaA01g37250D, BnaA02g26190D, BnaC01g01040D and BnaC07g21470D). In triglyceride synthesis, GmLPAAT2 is putatively inhibited by three miRNAs (gma-miR171, gma-miR1516 and gma-miR5775). Finally, in rapeseed there was evidence for the expansion of gene families, CALO, OBO and STERO, related to lipid storage, and the contraction of gene families, LOX, LAH and HSI2, related to oil degradation.

CONCLUSIONS

The molecular mechanisms associated with differences in seed oil content provide the basis for future breeding efforts to improve seed oil content.

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.

Co-expression Gene Network Analysis and Functional Module Identification in Bamboo Growth and Development

Bamboo is one of the fastest-growing non-timber forest plants. Moso bamboo (Phyllostachys edulis) is the most economically valuable bamboo in Asia, especially in China. With the release of the whole-genome sequence of moso bamboo, there are increasing demands for refined annotation of bamboo genes. Recently, large amounts of bamboo transcriptome data have become available, including data on the multiple growth stages of tissues. It is now feasible for us to construct co-expression networks to improve bamboo gene annotation and reveal the relationships between gene expression and growth traits. We integrated the genome sequence of moso bamboo and 78 transcriptome data sets to build genome-wide global and conditional co-expression networks. We overlaid the gene expression results onto the network with multiple dimensions (different development stages). Through combining the co-expression network, module classification and function enrichment tools, we identified 1,896 functional modules related to bamboo development, which covered functions such as photosynthesis, hormone biosynthesis, signal transduction, and secondary cell wall biosynthesis. Furthermore, an online database (http://bioinformatics.cau.edu.cn/bamboo) was built for searching the moso bamboo co-expression network and module enrichment analysis. Our database also includes cis-element analysis, gene set enrichment analysis, and other tools. In summary, we integrated public and in-house bamboo transcriptome data sets and carried out co-expression network analysis and functional module identification. Through data mining, we have yielded some novel insights into the regulation of growth and development. Our established online database might be convenient for the bamboo research community to identify functional genes or modules with important traits.

Meta-analysis and transcriptome profiling reveal hub genes for soybean seed storage composition during seed development

Soybean is an important crop providing edible oil and protein source. Soybean oil and protein contents are quantitatively inherited and significantly affected by environmental factors. In this study, meta-analysis was conducted based on soybean physical maps to integrate quantitative trait loci (QTLs) from multiple experiments in different environments. Meta-QTLs for seed oil, fatty acid composition, and protein were identified. Of them, 11 meta-QTLs were located on hot regions for both seed oil and protein. Next, we selected 4 chromosome segment substitution lines with different seed oil and protein contents to characterize their 3 years of phenotype selection in the field. Using strand-specific RNA-sequencing analysis, we profile the time-course transcriptome patterns of soybean seeds at early maturity, middle maturity, and dry seed stages. Pairwise comparison and K-means clustering analysis revealed 7,482 differentially expressed genes and 45 expression patterns clusters. Weighted gene coexpression network analysis uncovered 46 modules of gene expression patterns. The 2 most significant coexpression networks were visualized, and 7 hub genes were identified that were involved in soybean oil and seed storage protein accumulation processes. Our results provided a transcriptome dataset for soybean seed development, and the candidate hub genes represent a foundation for further research.

Melonet-DB, a Grand RNA-Seq Gene Expression Atlas in Melon (Cucumis melo L.)

Melon (Cucumis melo L.) is an important Cucurbitaceae crop produced worldwide, exhibiting wide genetic variations and comprising both climacteric and non-climacteric fruit types. The muskmelon cultivar "'Earl's favorite Harukei-3 (Harukei-3)"' known for its sweetness and rich aroma is used for breeding of high-grade muskmelon in Japan. We conducted RNA sequencing (RNA-seq) transcriptome studies in 30 different tissues of the 'Harukei-3' melon. These included root, stems, leaves, flowers, regenerating callus and ovaries, in addition to the flesh and peel sampled at seven stages of fruit development. The expression patterns of 20,752 genes were determined with fragments per kilobase of transcript per million fragments sequenced (FPKM) >1 in at least one tissue. Principal component analysis distinguished 30 melon tissues based on the global gene expression profile and, further, the weighted gene correlation network analysis classified melon genes into 45 distinct coexpression groups. Some coexpression groups exhibited tissue-specific gene expression. Furthermore, we developed and published web application tools designated "'Gene expression map viewer"' and "'Coexpression viewer"' on our website Melonet-DB (http://melonet-db.agbi.tsukuba.ac.jp/) to promote functional genomics research in melon. By using both tools, we analyzed melon homologs of tomato fruit ripening regulators such as E8, RIPENING-INHIBITOR (RIN) and NON-RIPENING (NOR). The "'Coexpression viewer"' clearly distinguished fruit ripening-associated melon RIN/NOR/CNR homologs from those expressed in other tissues. In addition, several other MADS-box, NAM/ATAF/CUC (NAC) and homeobox transcription factor genes were identified as fruit ripening-associated genes. Our tools provide useful information for research not only on melon but also on other fleshy fruit plants.

Genome-wide mapping of DNase I hypersensitive sites reveals chromatin accessibility changes in Arabidopsis euchromatin and heterochromatin regions under extended darkness

Light, as the energy source in photosynthesis, is essential for plant growth and development. Extended darkness causes dramatic gene expression changes. In this study, we applied DNase-seq (DNase I hypersensitive site sequencing) to study changes of chromatin accessibility in euchromatic and heterochromatic regions under extended darkness in Arabidopsis. We generated 27 Gb DNase-seq and 67.6 Gb RNA-seq data to investigate chromatin accessibility changes and global gene expression under extended darkness and control condition in Arabidopsis. We found that ~40% DHSs (DNaseI hypersensitive sites) were diminished under darkness. In non-TE regions, the majority of DHS-changed genes were DHS-diminished under darkness. A total of 519 down-regulated genes were associated with diminished DHSs under darkness, mainly involved in photosynthesis process and retrograde signaling, and were regulated by chloroplast maintenance master regulators such as GLK1. In TE regions, approximately half of the DHS-changed TEs were DHS-increased under darkness and were primarily associated with the LTR/Gypsy retrotransposons in the heterochromatin flanking the centromeres. In contrast, DHS-diminished TEs under darkness were enriched in Copia, LINE, and MuDR dispersed across chromosomes. Together, our results indicated that extended darkness resulted in more increased chromatin compaction in euchromatin and decompaction in heterochromatin, thus further leading to gene expression changes in Arabidopsis.

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80-85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.

Functional Characterization of a Putative Glycine max ELF4 in Transgenic Arabidopsis and Its Role during Flowering Control

Flowering is an important trait in major crops like soybean due to its direct relation to grain production. The circadian clock mediates the perception of seasonal changes in day length and temperature to modulate flowering time. The circadian clock gene EARLY FLOWERING 4 (ELF4) was identified in Arabidopsis thaliana and is believed to play a key role in the integration of photoperiod, circadian regulation, and flowering. The molecular circuitry that comprises the circadian clock and flowering control in soybeans is just beginning to be understood. To date, insufficient information regarding the soybean negative flowering regulators exist, and the biological function of the soybean ELF4 (GmELF4) remains unknown. Here, we investigate the ELF4 family members in soybean and functionally characterize a GmELF4 homologous gene. The constitutive overexpression of GmELF4 delayed flowering in Arabidopsis, showing the ELF4 functional conservation among plants as part of the flowering control machinery. We also show that GmELF4 alters the expression of Arabidopsis key flowering time genes (AtCO and AtFT), and this down-regulation is the likely cause of flowering delay phenotypes. Furthermore, we identified the GmELF4 network genes to infer the participation of GmELF4 in soybeans. The data generated in this study provide original insights for comprehending the role of the soybean circadian clock ELF4 gene as a negative flowering controller.

Selection for a Zinc-Finger Protein Contributes to Seed Oil Increase during Soybean Domestication

Seed oil is a momentous agronomical trait of soybean (Glycine max) targeted by domestication in breeding. Although multiple oil-related genes have been uncovered, knowledge of the regulatory mechanism of seed oil biosynthesis is currently limited. We demonstrate that the seed-preferred gene GmZF351, encoding a tandem CCCH zinc finger protein, is selected during domestication. Further analysis shows that GmZF351 facilitates oil accumulation by directly activating WRINKLED1, BIOTIN CARBOXYL CARRIER PROTEIN2, 3-KETOACYL-ACYL CARRIER PROTEIN SYNTHASE III, DIACYLGLYCEROL O-ACYLTRANSFERASE1, and OLEOSIN2 in transgenic Arabidopsis (Arabidopsis thaliana) seeds. Overexpression of GmZF351 in transgenic soybean also activates lipid biosynthesis genes, thereby accelerating seed oil accumulation. The ZF351 haplotype from the cultivated soybean group and the wild soybean (Glycine soja) subgroup III correlates well with high gene expression level, seed oil contents and promoter activity, suggesting that selection of GmZF351 expression leads to increased seed oil content in cultivated soybean. Our study provides novel insights into the regulatory mechanism for seed oil accumulation, and the manipulation of GmZF351 may have great potential in the improvement of oil production in soybean and other related crops.

Co-expression network analyses identify functional modules associated with development and stress response in Gossypium arboreum

Cotton is an economically important crop, essential for the agriculture and textile industries. Through integrating transcriptomic data, we discovered that multi-dimensional co-expression network analysis was powerful for predicting cotton gene functions and functional modules. Here, the recently available transcriptomic data on Gossypium arboreum, including data on multiple growth stages of tissues and stress treatment samples were applied to construct a co-expression network exploring multi-dimensional expression (development and stress) through multi-layered approaches. Based on differential gene expression and network analysis, a fibre development regulatory module of the gene GaKNL1 was found to regulate the second cell wall through repressing the activity of REVOLUTA, and a tissue-selective module of GaJAZ1a was examined in response to water stress. Moreover, comparative genomics analysis of the JAZ1-related regulatory module revealed high conservation across plant species. In addition, 1155 functional modules were identified through integrating the co-expression network, module classification and function enrichment tools, which cover functions such as metabolism, stress responses, and transcriptional regulation. In the end, an online platform was built for network analysis (http://structuralbiology.cau.edu.cn/arboreum), which could help to refine the annotation of cotton gene function and establish a data mining system to identify functional genes or modules with important agronomic traits.

ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium

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.

Soybean GmDREBL Increases Lipid Content in Seeds of Transgenic Arabidopsis

A DREB-type transcription factor gene GmDREBL has been characterized for its functions in oil accumulation in seeds. The gene is specifically expressed in soybean seeds. The GmDREBL is localized in nucleus and has transcriptional activation ability. Overexpression of GmDREBL increased the fatty acid content in the seeds of transgenic Arabidopsis plants. GmDREBL can bind to the promoter region of WRI1 to activate its expression. Several other genes in the fatty acid biosynthesis pathway were also enhanced in the GmDREBL-transgenic plants. The GmDREBL can be up-regulated by GmABI3 and GmABI5. Additionally, overexpression of GmDREBL significantly promoted seed size in transgenic plants compared to that of WT plants. Expression of the DREBL is at higher level on the average in cultivated soybeans than that in wild soybeans. The promoter of the DREBL may have been subjected to selection during soybean domestication. Our results demonstrate that GmDREBL participates in the regulation of fatty acid accumulation by controlling the expression of WRI1 and its downstream genes, and manipulation of the gene may increase the oil contents in soybean plants. Our study provides novel insights into the function of DREB-type transcription factors in oil accumulation in addition to their roles in stress response.

The differential expression of soybean [Glycine max (L.) Merrill] WRKY genes in response to water deficit

Drought is today, and perhaps even more in the future, the main challenge for grain crops, resulting in a drastic yield reduction. Thus, it is of great interest to obtain soybean genotypes tolerant to water deficit. The drought tolerance trait is difficult to obtain through classical breeding due to its polygenic basis. In this context, genetic engineering is presented as a way to achieve this attribute. The ability to modulate the expression of many genes placed the transcription factors as promising biotechnological targets to develop stress tolerant cultivars. The WRKY proteins form a large family of transcription factors that are involved in important physiological and biochemical processes in plants, including the response to water deficit. In this study, the expression pattern determined by qPCR showed that, GmWRKY6, GmWRKY46, GmWRKY56, GmWRKY106 and GmWRKY149 genes are differentially expressed between a drought tolerant and a susceptible soybean genotype in water stress conditions. The in silico promoter and coexpression analysis indicate that these genes act in a stress physiological background.

Histone modifications facilitate the coexpression of bidirectional promoters in rice

Background

Bidirectional gene pairs are highly abundant and mostly co-regulated in eukaryotic genomes. The structural features of bidirectional promoters (BDPs) have been well studied in yeast, humans and plants. However, the underlying mechanisms responsible for the coexpression of BDPs remain understudied, especially in plants.

Results

Here, we characterized chromatin features associated with rice BDPs. Several unique chromatin features were present in rice BDPs but were missing from unidirectional promoters (UDPs), including overrepresented active histone marks, canonical nucleosomes and underrepresented H3K27me3. In particular, overrepresented active marks (H3K4ac, H4K12ac, H4K16ac, H3K4me2 and H3K36me3) were truly overrepresented in type I BDPs but not in the other two BDPs, based on a Kolmogorov-Smirnov test.

Conclusions

Our analyses indicate that active marks (H3K4ac, H4K12ac, H4K16ac, H3K4me3, H3K9ac and H3K27ac) may coordinate with repressive marks (H3K27me3 and H3K9me1/3) to build a unique chromatin structure that favors the coregulation of bidirectional gene pairs. Thus, our findings help to enhance the understanding of unique epigenetic mechanisms that regulate bidirectional gene pairs and may improve the manipulation of gene pairs for crop bioengineering.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3125-0) contains supplementary material, which is available to authorized users.

SorghumFDB: sorghum functional genomics database with multidimensional network analysis

Sorghum (Sorghum bicolor [L.] Moench) has excellent agronomic traits and biological properties, such as heat and drought-tolerance. It is a C₄ grass and potential bioenergy-producing plant, which makes it an important crop worldwide. With the sorghum genome sequence released, it is essential to establish a sorghum functional genomics data mining platform. We collected genomic data and some functional annotations to construct a sorghum functional genomics database (SorghumFDB). SorghumFDB integrated knowledge of sorghum gene family classifications (transcription regulators/factors, carbohydrate-active enzymes, protein kinases, ubiquitins, cytochrome P450, monolignol biosynthesis related enzymes, R-genes and organelle-genes), detailed gene annotations, miRNA and target gene information, orthologous pairs in the model plants Arabidopsis, rice and maize, gene loci conversions and a genome browser. We further constructed a dynamic network of multidimensional biological relationships, comprised of the co-expression data, protein–protein interactions and miRNA-target pairs. We took effective measures to combine the network, gene set enrichment and motif analyses to determine the key regulators that participate in related metabolic pathways, such as the lignin pathway, which is a major biological process in bioenergy-producing plants.

Database URL:http://structuralbiology.cau.edu.cn/sorghum/index.html.

Landscape of genomic diversity and trait discovery in soybean

Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces, and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered, and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity, and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution, and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Network-assisted crop systems genetics: network inference and integrative analysis

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years.

Tissue-specific expression of a soybean hypersensitive-induced response (HIR) protein gene promoter

A Glycine max gene encoding a putative protein similar to hypersensitive-induced response proteins (HIR) was identified as a gene with preferred expressions in flowers and developing seeds by whole transcriptome gene expression profiling. Its promoter gm-hir1 was cloned and revealed to strongly express a fluorescence reporter gene primarily in integuments, anther tapetum, and seed coat with unique tissue-specificity. Expression in the inner integument was apparent prior to pollination, while expression in the outer integument started to develop from the micropylar end outward as the embryo matured. A 5'-deletion study showed that the promoter can be truncated to 600 bp long relative to the translation start site without affecting expression. A positive regulatory element was identified between 600 and 481 bp that controls expression in the inner integument, with no noticeable effect on expression in the outer integument or tapetum. Additionally, removal of the 5'UTR intron had no effect on levels or location of gm-hir1 expression while truncation to 370 bp resulted in a complete loss of expression suggesting that elements controlling both the outer integument and tapetum expression are located within the 481-370 bp region.

Expanding Omics Resources for Improvement of Soybean Seed Composition Traits

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.