Genetic dissection of the biotic stress response using a genome-scale gene network for rice

SLC25A19 is a novel prognostic biomarker related to immune invasion and ferroptosis in HCC

SLC25A19 is a mitochondrial thiamine pyrophosphate (TPP) carrier that mediates TPP entry into the mitochondria. SLC25A19 has been recognized to play a crucial role in many metabolic diseases, but its role in cancer has not been clearly reported. Based on clinical data from The Cancer Genome Atlas (TCGA), the following parameters were analyzed among HCC patients: SLC25A19 expression, enrichment analyses, immune infiltration, ferroptosis and prognosis analyses. In vitro, the SLC25A19 high expression was validated by qRT-PCR and Immunohistochemistry. Subsequently, a series of cell function experiments, including CCK8, EdU, clone formation, trans-well and scratch assays, were conducted to illustrate the effect of SLC25A19 on the growth and metastasis of cancer cells. Meanwhile, indicators related to ferroptosis were also detected. SCL25A19 is highly expressed in HCC and predicts a poor prognosis. Elevated SLC25A19 expression in HCC patients was markedly associated with T stage, pathological status (PS), tumor status (TS), histologic grade (HG), and AFP. Our results indicate that SLC25A19 has a generally good prognosis predictive and diagnostic ability. The results of gene enrichment analyses showed that SLC25A19 is significantly correlated with immune infiltration, fatty acid metabolism, and ferroptosis marker genes. In vitro experiments have confirmed that silencing SLC25A19 can significantly inhibit the proliferation and migration ability of cancer cells and induce ferroptosis in HCC. In conclusion, these findings indicate that SLC25A19 is novel prognostic biomarker related to immune invasion and ferroptosis in HCC, and it is an excellent candidate for therapeutic target against HCC.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Floral Development on Vitis vinifera Is Associated with MADS-Box Transcription Factors through the Transcriptional Regulation of VviZIP3

Several grapevine (Vitis vinifera L.) cultivars show a tendency to develop parthenocarpic seedless grapes, affecting fruit yield and quality. This reproductive disorder originates in defective ovule fertilization due to a failure in pollen tube growth. Zinc (Zn) is a crucial trace element, playing a vital role in various physiological and metabolic processes. It is particularly essential for the healthy growth of flowers and fruits. Insufficient zinc has been suggested as a potential reason for issues in this development process. This microelement is taken up through a mechanism that involves transporters, including the ZRT-IRT-like protein (ZIP) gene family, associated with the influx of Zn into the cell. In grapevines, 20 genes for ZIP-type transporters have been described. In this study, we analyzed the expression pattern of VviZIP3 during flower development and employ transgenic methods to assess its transcriptional regulation. Furthermore, through computational examination of the promoter region, we identified two CArG boxes, recognized as responsive elements to MADS transcription factors. These factors play a key role in shaping various components of a flower, such as pollen. Our investigation of the VviZIP3 promoter confirms the functionality of these CArG boxes. Overall, our results suggest that the increased expression of VviZIP3 during flowering is likely under the influence of MADS transcription factors.

Genome-Wide Identification of MADS-Box Genes in Taraxacum kok-saghyz and Taraxacum mongolicum: Evolutionary Mechanisms, Conserved Functions and New Functions Related to Natural Rubber Yield Formation

MADS-box transcription regulators play important roles in plant growth and development. However, very few MADS-box genes have been isolated in the genus Taraxacum, which consists of more than 3000 species. To explore their functions in the promising natural rubber (NR)-producing plant Taraxacum kok-saghyz (TKS), MADS-box genes were identified in the genome of TKS and the related species Taraxacum mongolicum (TM; non-NR-producing) via genome-wide screening. In total, 66 TkMADSs and 59 TmMADSs were identified in the TKS and TM genomes, respectively. From diploid TKS to triploid TM, the total number of MADS-box genes did not increase, but expansion occurred in specific subfamilies. Between the two genomes, a total of 11 duplications, which promoted the expansion of MADS-box genes, were identified in the two species. TkMADS and TmMADS were highly conserved, and showed good collinearity. Furthermore, most TkMADS genes exhibiting tissue-specific expression patterns, especially genes associated with the ABCDE model, were preferentially expressed in the flowers, suggesting their conserved and dominant functions in flower development in TKS. Moreover, by comparing the transcriptomes of different TKS lines, we identified 25 TkMADSs related to biomass formation and 4 TkMADSs related to NR content, which represented new targets for improving the NR yield of TKS.

Salicylic acid inhibits rice endocytic protein trafficking mediated by OsPIN3t and clathrin to affect root growth

Salicylic acid (SA) plays important roles in different aspects of plant development, including root growth, where auxin is also a major player by means of its asymmetric distribution. However, the mechanism underlying the effect of SA on the development of rice roots remains poorly understood. Here, we show that SA inhibits rice root growth by interfering with auxin transport associated with the OsPIN3t- and clathrin-mediated gene regulatory network (GRN). SA inhibits root growth as well as Brefeldin A-sensitive trafficking through a non-canonical SA signaling mechanism. Transcriptome analysis of rice seedlings treated with SA revealed that the OsPIN3t auxin transporter is at the center of a GRN involving the coat protein clathrin. The root growth and endocytic trafficking in both the pin3t and clathrin heavy chain mutants were SA insensitivity. SA inhibitory effect on the endocytosis of OsPIN3t was dependent on clathrin; however, the root growth and endocytic trafficking mediated by tyrphostin A23 (TyrA23) were independent of the pin3t mutant under SA treatment. These data reveal that SA affects rice root growth through the convergence of transcriptional and non-SA signaling mechanisms involving OsPIN3t-mediated auxin transport and clathrin-mediated trafficking as key components.

Biocuration of a Transcription Factors Network Involved in Submergence Tolerance during Seed Germination and Coleoptile Elongation in Rice (Oryza sativa)

Modeling biological processes and genetic-regulatory networks using in silico approaches provides a valuable framework for understanding how genes and associated allelic and genotypic differences result in specific traits. Submergence tolerance is a significant agronomic trait in rice; however, the gene-gene interactions linked with this polygenic trait remain largely unknown. In this study, we constructed a network of 57 transcription factors involved in seed germination and coleoptile elongation under submergence. The gene-gene interactions were based on the co-expression profiles of genes and the presence of transcription factor binding sites in the promoter region of target genes. We also incorporated published experimental evidence, wherever available, to support gene-gene, gene-protein, and protein-protein interactions. The co-expression data were obtained by re-analyzing publicly available transcriptome data from rice. Notably, this network includes OSH1, OSH15, OSH71, Sub1B, ERFs, WRKYs, NACs, ZFP36, TCPs, etc., which play key regulatory roles in seed germination, coleoptile elongation and submergence response, and mediate gravitropic signaling by regulating OsLAZY1 and/or IL2. The network of transcription factors was manually biocurated and submitted to the Plant Reactome Knowledgebase to make it publicly accessible. We expect this work will facilitate the re-analysis/re-use of OMICs data and aid genomics research to accelerate crop improvement.

An open source plant kinase chemogenomics set

One hundred twenty-nine protein kinases, selected to represent the diversity of the rice (Oryza sativa) kinome, were cloned and tested for expression in Escherichia coli. Forty of these rice kinases were purified and screened using differential scanning fluorimetry (DSF) against 627 diverse kinase inhibitors, with a range of structures and activities targeting diverse human kinases. Thirty-seven active compounds were then tested for their ability to modify primary root development in Arabidopsis. Of these, 14 compounds caused a significant reduction of primary root length compared with control plants. Two of these inhibitory compounds bind to the predicted orthologue of Arabidopsis PSKR1, one of two receptors for PSK, a small sulfated peptide that positively controls root development. The reduced root length phenotype could not be rescued by the exogenous addition of the PSK peptide, suggesting that chemical treatment may inhibit both PSKR1 and its closely related receptor PSKR2. Six of the compounds acting as root growth inhibitors in Arabidopsis conferred the same effect in rice. Compound RAF265 (CHIR-265), previously shown to bind the human kinase BRAF (B-Raf proto-oncogene, serine/threonine kinase), also binds to nine highly conserved rice kinases tested. The binding of human and rice kinases to the same compound suggests that human kinase inhibitor sets will be useful for dissecting the function of plant kinases.

Comparison of anther transcriptomes in response to cold stress at the reproductive stage between susceptible and resistant Japonica rice varieties

BACKGROUND

Rice is one of the most important cereal crops in the world but is susceptible to cold stress (CS). In this study, we carried out parallel transcriptomic analysis at the reproductive stage on the anthers of two Japonica rice varieties with contrasting CS resistance: cold susceptible Longjing11 (LJ11) and cold resistant Longjing25 (LJ25).

RESULTS

According to the obtained results, a total of 16,762 differentially expressed genes (DEGs) were identified under CS, including 7,050 and 14,531 DEGs in LJ25 and LJ11, respectively. Examining gene ontology (GO) enrichment identified 35 up- and 39 down-regulated biological process BP GO terms were significantly enriched in the two varieties, with 'response to heat' and 'response to cold' being the most enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 33 significantly enriched pathways. Only the carbon metabolism and amino acid biosynthesis pathways with down-regulated DEGs were enriched considerably in LJ11, while the plant hormone signal transduction pathway (containing 153 DEGs) was dramatically improved. Eight kinds of plant hormones were detected in the pathway, while auxin, abscisic acid (ABA), salicylic acid (SA), and ethylene (ETH) signaling pathways were found to be the top four pathways with the most DEGs. Furthermore, the protein-protein interaction (PPI) network analysis identified ten hub genes (co-expressed gene number ≥ 30), including six ABA-related genes. Various DEGs (such as OsDREB1A, OsICE1, OsMYB2, OsABF1, OsbZIP23, OsCATC, and so on) revealed distinct expression patterns among rice types when the DEGs between LJ11 and LJ25 were compared, indicating that they are likely responsible for CS resistance of rice in cold region.

CONCLUSION

Collectively, our findings provide comprehensive insights into complex molecular mechanisms of CS response and can aid in CS resistant molecular breeding of rice in cold regions.

Mechanism of Action of Ribosomally Synthesized and Post-Translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a natural product class that has undergone significant expansion due to the rapid growth in genome sequencing data and recognition that they are made by biosynthetic pathways that share many characteristic features. Their mode of actions cover a wide range of biological processes and include binding to membranes, receptors, enzymes, lipids, RNA, and metals as well as use as cofactors and signaling molecules. This review covers the currently known modes of action (MOA) of RiPPs. In turn, the mechanisms by which these molecules interact with their natural targets provide a rich set of molecular paradigms that can be used for the design or evolution of new or improved activities given the relative ease of engineering RiPPs. In this review, coverage is limited to RiPPs originating from bacteria.

Vitamin B1 THIAMIN REQUIRING1 synthase mediates the maintenance of chloroplast function by regulating sugar and fatty acid metabolism in rice

Vitamin B₁ (VB1), including thiamin, thiamin monophosphate (TMP), and thiamin pyrophosphate (TPP), is an essential micronutrient for all living organisms. Nevertheless, the precise function of VB1 in rice remains unclear. Here, we described a VB1 auxotrophic mutant, chlorotic lethal seedling (cles) from the mutation of OsTH1, which displayed collapsed chloroplast membrane system and decreased pigment content. OsTH1 encoded a phosphomethylpyrimidine kinase/thiamin-phosphate pyrophosphorylase, and was expressed in various tissues, especially in seedlings, leaves, and young panicles. The VB1 content in cles was markedly reduced, despite an increase in the expression of VB1 synthesis genes. The decreased TPP content affected the tricarboxylic acid cycle, pentose phosphate pathway, and de novo fatty acid synthesis, leading to a reduction in fatty acids (C16:0 and C18:0) and sugars (sucrose and glucose) of cles. Additionally, irregular expression of chloroplast membrane synthesis genes led to membrane collapse. We also found that alternative splicing and translation allowed OsTH1 to be localized to both chloroplast and cytosol. Our study revealed that OsTH1 was an essential enzyme in VB1 biosynthesis and played crucial roles in seedling growth and development by participating in fatty acid and sugar metabolism, providing new perspectives on VB1 function in rice.

Integration of probabilistic functional networks without an external Gold Standard

BACKGROUND

Probabilistic functional integrated networks (PFINs) are designed to aid our understanding of cellular biology and can be used to generate testable hypotheses about protein function. PFINs are generally created by scoring the quality of interaction datasets against a Gold Standard dataset, usually chosen from a separate high-quality data source, prior to their integration. Use of an external Gold Standard has several drawbacks, including data redundancy, data loss and the need for identifier mapping, which can complicate the network build and impact on PFIN performance. Additionally, there typically are no Gold Standard data for non-model organisms.

RESULTS

We describe the development of an integration technique, ssNet, that scores and integrates both high-throughput and low-throughout data from a single source database in a consistent manner without the need for an external Gold Standard dataset. Using data from Saccharomyces cerevisiae we show that ssNet is easier and faster, overcoming the challenges of data redundancy, Gold Standard bias and ID mapping. In addition ssNet results in less loss of data and produces a more complete network.

CONCLUSIONS

The ssNet method allows PFINs to be built successfully from a single database, while producing comparable network performance to networks scored using an external Gold Standard source and with reduced data loss.

Complex Networks of Prion-Like Proteins Reveal Cross Talk Between Stress and Memory Pathways in Plants

Prions are often considered as molecular memory devices, generating reproducible memory of a conformational change. Prion-like proteins (PrLPs) have been widely demonstrated to be present in plants, but their role in plant stress and memory remains unexplored. In this work, we report the widespread presence of PrLPs in plants through a comprehensive meta-analysis of 39 genomes representing major taxonomic groups. We find diverse functional roles associated with these proteins in various species and term the full complement of PrLPs in a genome as its "prionome." In particular, we found the rice prionome being significantly enriched in transposons/retrotransposons (Ts/RTRs) and identified over 60 rice PrLPs that were differentially regulated in stress and developmental responses. This prompted us to explore whether and to what extent PrLPs may build stress memory. By integrating the available rice interactome, transcriptome, and regulome data sets, we could find links between stress and memory pathways that would not have otherwise been discernible. Regulatory inferences derived from the superimposition of these data sets revealed a complex network and cross talk between PrLPs, transcription factors (TFs), and the genes involved in stress priming. This integrative meta-analysis connects transient and transgenerational memory mechanisms in plants with PrLPs, suggesting that plant memory may rely upon protein-based signals in addition to chromatin-based epigenetic signals. Taken together, our work provides important insights into the anticipated role of prion-like candidates in stress and memory, paving the way for more focused studies for validating the role of the identified PrLPs in memory acclimation.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

In silico analysis of functional linkage among arsenic induced MATE genes in rice

MATE genes play an important role in cellular detoxification processes. Nine MATE genes were identified by a transcriptomics study previously. Candidate gene prioritization was done where 29 new genes were found to interact with 09 guide genes. Therefore, a total of 38 genes were analyzed here to predict a concise model by gene prioritization study. Those genes were analyzed further in Rice Interactions Viewer programme, and based on high ICV, 10 new genes were found to interact among themselves at protein level. Surprisingly, only 05 genes were found to play a key role at protein level. These 15 genes were analyzed for their interaction with soil available inorganic arsenic species. Maximum expression levels were found mostly at young inflorescence and seed development stage for those genes. So, these genes may have a direct role in arsenic sequestration from cells and thereby providing safety to the developing embryo within the seed.

A massively parallel barcoded sequencing pipeline enables generation of the first ORFeome and interactome map for rice

Systematic mappings of protein interactome networks have provided invaluable functional information for numerous model organisms. Here we develop PCR-mediated Linkage of barcoded Adapters To nucleic acid Elements for sequencing (PLATE-seq) that serves as a general tool to rapidly sequence thousands of DNA elements. We validate its utility by generating the ORFeome for Oryza sativa covering 2,300 genes and constructing a high-quality protein-protein interactome map consisting of 322 interactions between 289 proteins, expanding the known interactions in rice by roughly 50%. Our work paves the way for high-throughput profiling of protein-protein interactions in a wide range of organisms.

A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies

Plants are foundational for global ecological and economic systems, but most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. By using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified previously unknown interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical for agriculture. We also observed plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers a cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.

Cytosolic GLUTAMINE SYNTHETASE1;1 Modulates Metabolism and Chloroplast Development in Roots

Nitrogen (N) is an essential macronutrient, and the final form of endogenous inorganic N is ammonium, which is assimilated by Gln synthetase (GS) into Gln. However, how the multiple isoforms of cytosolic GSs contribute to metabolic systems via the regulation of ammonium assimilation remains unclear. In this study, we compared the effects of two rice (Oryza sativa) cytosolic GSs, namely OsGS1;1 and OsGS1;2, on central metabolism in roots using reverse genetics, metabolomic and transcriptomic profiling, and network analyses. We observed (1) abnormal sugar and organic N accumulation and (2) significant up-regulation of genes associated with photosynthesis and chlorophyll biosynthesis in the roots of Osgs1;1 but not Osgs1;2 knockout mutants. Network analysis of the Osgs1;1 mutant suggested that metabolism of Gln was coordinated with the metabolic modules of sugar metabolism, tricarboxylic acid cycle, and carbon fixation. Transcript profiling of Osgs1;1 mutant roots revealed that expression of the rice sigma-factor (OsSIG) genes in the mutants were transiently upregulated. GOLDEN2-LIKE transcription factor-encoding genes, which are involved in chloroplast biogenesis in rice, could not compensate for the lack of OsSIGs in the Osgs1;1 mutant. Microscopic analysis revealed mature chloroplast development in Osgs1;1 roots but not in the roots of Osgs1;2, Osgs1;2-complemented lines, or the wild type. Thus, organic N assimilated by OsGS1;1 affects a broad range of metabolites and transcripts involved in maintaining metabolic homeostasis and plastid development in rice roots, whereas OsGS1;2 has a more specific role, affecting mainly amino acid homeostasis but not carbon metabolism.

Comparison of leaf transcriptome in response to Rhizoctonia solani infection between resistant and susceptible rice cultivars

Background

Sheath blight (SB), caused by Rhizoctonia solani, is a common rice disease worldwide. Currently, rice cultivars with robust resistance to R. solani are still lacking. To provide theoretic basis for molecular breeding of R. solani-resistant rice cultivars, the changes of transcriptome profiles in response to R. solani infection were compared between a moderate resistant cultivar (Yanhui-888, YH) and a susceptible cultivar (Jingang-30, JG).

Results

In the present study, 3085 differentially express genes (DEGs) were detected between the infected leaves and the control in JG, with 2853 DEGs in YH. A total of 4091 unigenes were significantly upregulated in YH than in JG before infection, while 3192 were significantly upregulated after infection. Further analysis revealed that YH and JG showed similar molecular responses to R. solani infection, but the responses were earlier in JG than in YH. Expression levels of trans-cinnamate 4-monooxygenase (C4H), ethylene-insensitive protein 2 (EIN2), transcriptome factor WRKY33 and the KEGG pathway plant-pathogen interaction were significantly affected by R. solani infection. More importantly, these components were all over-represented in YH cultivar than in JG cultivar before and/or after infection.

Conclusions

These genes possibly contribute to the higher resistance of YH to R. solani than JG and were potential target genes to molecularly breed R. solani-resistant rice cultivar.

Candidate genes expression profiling during wilting in chickpea caused by Fusarium oxysporum f. sp. ciceris race 5

Chickpea production may be seriously threatened by Fusarium wilt, a disease caused by the soil-borne fungus Fusarium oxysporum f. sp. ciceris. F. oxysporum race 5 is the most important race in the Mediterranean basin. Recently, the region responsible for resistance race 5 has been delimited within a region on chromosome 2 that spans 820 kb. To gain a better understanding of this genomic region, we used a transcriptomic approach based on quantitative real-time PCR to analyze the expression profiles of 22 selected candidate genes. We used a pair of near-isogenic lines (NILs) differing in their sensitivity to Fusarium race 5 (resistant vs susceptible) to monitor the transcriptional changes over a time-course experiment (24, 48, and 72 hours post inoculation, hpi). Qualitative differences occurred during the timing of regulation. A cluster of 12 genes were induced by the resistant NIL at 24 hpi, whereas a second cluster contained 9 genes induced by the susceptible NIL at 48 hpi. Their possible functions in the molecular defence of chickpea is discussed. Our study provides new insight into the molecular defence against Fusarium race 5 and demonstrates that development of NILs is a rich resource to facilitate the detection of candidate genes. The new genes regulated here may be useful against other Fusarium races.

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice

Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine mapping process to find the causal gene controlling the trait. With the availability of a rich assortment of genomic and functional genomic data, it is possible to develop a computational method to facilitate faster identification of causal genes. We developed QTG-Finder, a machine learning based algorithm to prioritize causal genes by ranking genes within a quantitative trait locus (QTL). Two predictive models were trained separately based on known causal genes in Arabidopsis and rice. An independent validation analysis showed that the models could recall about 64% of Arabidopsis and 79% of rice causal genes when the top 20% ranked genes were considered. The top 20% ranked genes can range from 10 to 100 genes, depending on the size of a QTL. The models can prioritize different types of traits though at different efficiency. We also identified several important features of causal genes including paralog copy number, being a transporter, being a transcription factor, and containing SNPs that cause premature stop codon. This work lays the foundation for systematically understanding characteristics of causal genes and establishes a pipeline to predict causal genes based on public data.

MaizeNet: a co-functional network for network-assisted systems genetics in Zea mays

Maize (Zea mays) has multiple uses in human food, animal fodder, starch and sweetener production and as a biofuel, and is accordingly the most extensively cultivated cereal worldwide. To enhance maize production, genetic factors underlying important agricultural traits, including stress tolerance and flowering, have been explored through forward and reverse genetics approaches. Co-functional gene networks are systems biology resources useful in identifying trait-associated genes in plants by prioritizing candidate genes. Here, we present MaizeNet (http://www.inetbio.org/maizenet/), a genome-scale co-functional network of Z. mays genes, and a companion web server for network-assisted systems genetics. We describe the validation of MaizeNet network quality and its ability to functionally predict molecular pathways and complex traits in maize. Furthermore, we demonstrate that MaizeNet-based prioritization of candidate genes can facilitate the identification of cell wall biosynthesis genes and detect network communities associated with flowering-time candidate genes derived from genome-wide association studies. The demonstrated gene prioritization and subnetwork analysis can be conducted by simply submitting maize gene models based on the commonly used B73 RefGen_v3 and the latest B73 RefGen_v4 reference genomes on the MaizeNet web server. MaizeNet-based network-assisted systems genetics will substantially accelerate the discovery of trait-associated genes for crop improvement.

Genome-Wide Analysis of the MADS-Box Transcription Factor Family in Solanum lycopersicum

MADS-box family genes encode transcription factors that are involved in multiple developmental processes in plants, especially in floral organ specification, fruit development, and ripening. However, a comprehensive analysis of tomato MADS-box family genes, which is an important model plant to study flower fruit development and ripening, remains obscure. To gain insight into the MADS-box genes in tomato, 131 tomato MADS-box genes were identified. These genes could be divided into five groups (Mα, Mβ, Mγ, Mδ, and MIKC) and were found to be located on all 12 chromosomes. We further analyzed the phylogenetic relationships among Arabidopsis and tomato, as well as the protein motif structure and exon–intron organization, to better understand the tomato MADS-box gene family. Additionally, owing to the role of MADS-box genes in floral organ identification and fruit development, the constitutive expression patterns of MADS-box genes at different stages in tomato development were identified. We analyzed 15 tomato MADS-box genes involved in floral organ identification and five tomato MADS-box genes related to fruit development by qRT-PCR. Collectively, our study provides a comprehensive and systematic analysis of the tomato MADS-box genes and would be valuable for the further functional characterization of some important members of the MADS-box gene family.

Variations in the Structure and Evolution of Rice WRKY Genes in Indica and Japonica Genotypes and their Co-expression Network in Mediating Disease Resistance

WRKY transcription factor (TF) family regulates many functions in plant growth and development and also during biotic and abiotic stress. In this study, 101 WRKY TF gene models in indica and japonica rice were used to conduct evolutionary analysis, gene structure analysis, and motif composition. Co-expression analysis was carried out first by selecting the differentially expressing genes that showed a significant change in response to the pathogens from Rice Oligonucleotide Array Database (ROAD). About 82 genes showed responses to infection by Magnaporthe oryzae or Xanthomonas oryzae pv. oryzae. Co-expression gene network was constructed using direct neighborhood and context associated inbuilt mode in RiceNetv2 tool. Only 41 genes showed interaction with 2299 non-WRKY genes. Variations exist in the structure and evolution of WRKY genes among indica and japonica genotypes which have important implications in their differential roles including disease resistance. WRKY genes mediate a complex networking and co-express along with other WRKY and non-WRKY genes to mediate resistance against fungal and bacterial pathogens in rice.

Unintended effects of transgenic rice revealed by transcriptome and metabolism

Genetically modified (GM) organisms have been developed for decades. However, unintended effects are the main concerns of safety assessment that needs to be carefully investigated. Here, eight varieties of GM rice that were developed in China were selected to assess the unintended effects through transcriptome and metabolism. There are 2892-8758 differentially expressed genes (DEGs) and 7-50 metabolites at significant level between GM varieties and their isogenic counterparts, which were far fewer than that between traditional rice varieties. The function enrichment analysis showed altered transcription in stress-related pathway and starch and sucrose metabolism. DEGs shared among eight GM samples constitute less than 1% of the genes in the genome, and none of them is reported more than four times. The insertion effect on the nearby gene expression and the associated metabolism is only restricted to 50 genes. All the results provide a comprehensive analysis of unintended effects and indication of difference in Chinese transgenic rice based on their backgrounds, transformation, and insertion elements.

Rice Genome-Scale Network Integration Reveals Transcriptional Regulators of Grass Cell Wall Synthesis

Grasses have evolved distinct cell wall composition and patterning relative to dicotyledonous plants. However, despite the importance of this plant family, transcriptional regulation of its cell wall biosynthesis is poorly understood. To identify grass cell wall-associated transcription factors, we constructed the Rice Combined mutual Ranked Network (RCRN). The RCRN covers >90% of annotated rice (Oryza sativa) genes, is high quality, and includes most grass-specific cell wall genes, such as mixed-linkage glucan synthases and hydroxycinnamoyl acyltransferases. Comparing the RCRN and an equivalent Arabidopsis network suggests that grass orthologs of most genetically verified eudicot cell wall regulators also control this process in grasses, but some transcription factors vary significantly in network connectivity between these divergent species. Reverse genetics, yeast-one-hybrid, and protoplast-based assays reveal that OsMYB61a activates a grass-specific acyltransferase promoter, which confirms network predictions and supports grass-specific cell wall synthesis genes being incorporated into conserved regulatory circuits. In addition, 10 of 15 tested transcription factors, including six novel Wall-Associated regulators (WAP1, WACH1, WAHL1, WADH1, OsMYB13a, and OsMYB13b), alter abundance of cell wall-related transcripts when transiently expressed. The results highlight the quality of the RCRN for examining rice biology, provide insight into the evolution of cell wall regulation, and identify network nodes and edges that are possible leads for improving cell wall composition.

An actin-depolymerizing factor from the halophyte smooth cordgrass, Spartina alterniflora (SaADF2), is superior to its rice homolog (OsADF2) in conferring drought and salt tolerance when constitutively overexpressed in rice

Actin-depolymerizing factors (ADFs) maintain the cellular actin network dynamics by regulating severing and disassembly of actin filaments in response to environmental cues. An ADF isolated from a monocot halophyte, Spartina alterniflora (SaADF2), imparted significantly higher level of drought and salinity tolerance when expressed in rice than its rice homologue OsADF2. SaADF2 differs from OsADF2 by a few amino acid residues, including a substitution in the regulatory phosphorylation site serine-6, which accounted for its weak interaction with OsCDPK6 (calcium-dependent protein kinase), thus resulting in an increased efficacy of SaADF2 and enhanced cellular actin dynamics. SaADF2 overexpression preserved the actin filament organization better in rice protoplasts under desiccation stress. The predicted tertiary structure of SaADF2 showed a longer F-loop than OsADF2 that could have contributed to higher actin-binding affinity and rapid F-actin depolymerization in vitro by SaADF2. Rice transgenics constitutively overexpressing SaADF2 (SaADF2-OE) showed better growth, relative water content, and photosynthetic and agronomic yield under drought conditions than wild-type (WT) and OsADF2 overexpressers (OsADF2-OE). SaADF2-OE preserved intact grana structure after prolonged drought stress, whereas WT and OsADF2-OE presented highly damaged and disorganized grana stacking. The possible role of ADF2 in transactivation was hypothesized from the comparative transcriptome analyses, which showed significant differential expression of stress-related genes including interacting partners of ADF2 in overexpressers. Identification of a complex, differential interactome decorating or regulating stress-modulated cytoskeleton driven by ADF isoforms will lead us to key pathways that could be potential target for genome engineering to improve abiotic stress tolerance in agricultural crops.

Comparison of gene co-networks analysis provide a systems view of rice (Oryza sativa L.) response to Tilletia horrida infection

The biotrophic soil-borne fungus Tilletia horrida causes rice kernel smut, an important disease affecting the production of rice male sterile lines in most hybrid rice growing regions of the world. There are no successful ways of controlling this disease and there has been little study of mechanisms of resistance to T. horrida. Based on transcriptional data of different infection time points, we found 23, 782 and 23, 718 differentially expressed genes (fragments per kilobase of transcript sequence per million, FPKM >1) in Jiangcheng 3A (resistant to T. horrida) and 9311A (susceptible to T. horrida), respectively. In order to illuminate the differential responses of the two rice male sterile lines to T. horrida, we identified gene co-expression modules using the method of weighted gene co-expression network analysis (WGCNA) and compared the different biological functions of gene co-expression networks in key modules at different infection time points. The results indicated that gene co-expression networks in the two rice genotypes were different and that genes contained in some modules of the two groups may play important roles in resistance to T. horrida, such as DTH8 and OsHop/Sti1a. Furthermore, these results provide a global view of the responses of two different phenotypes to T. horrida, and assist our understanding of the regulation of expression changes after T. horrida infection.

Shared and genetically distinct Zea mays transcriptome responses to ongoing and past low temperature exposure

BACKGROUND

Cold temperatures and their alleviation affect many plant traits including the abundance of protein coding gene transcripts. Transcript level changes that occur in response to cold temperatures and their alleviation are shared or vary across genotypes. In this study we identify individual transcripts and groups of functionally related transcripts that consistently respond to cold and its alleviation. Genes that respond differently to temperature changes across genotypes may have limited functional importance. We investigate if these genes share functions, and if their genotype-specific gene expression levels change in magnitude or rank across temperatures.

RESULTS

We estimate transcript abundances from over 22,000 genes in two unrelated Zea mays inbred lines during and after cold temperature exposure. Genotype and temperature contribute to many genes' abundances. Past cold exposure affects many fewer genes. Genes up-regulated in cold encode many cytokinin glucoside biosynthesis enzymes, transcription factors, signalling molecules, and proteins involved in diverse environmental responses. After cold exposure, protease inhibitors and cuticular wax genes are newly up-regulated, and environmentally responsive genes continue to be up-regulated. Genes down-regulated in response to cold include many photosynthesis, translation, and DNA replication associated genes. After cold exposure, DNA replication and translation genes are still preferentially downregulated. Lignin and suberin biosynthesis are newly down-regulated. DNA replication, reactive oxygen species response, and anthocyanin biosynthesis genes have strong, genotype-specific temperature responses. The ranks of genotypes' transcript abundances often change across temperatures.

CONCLUSIONS

We report a large, core transcriptome response to cold and the alleviation of cold. In cold, many of the core suite of genes are up or downregulated to control plant growth and photosynthesis and limit cellular damage. In recovery, core responses are in part to prepare for future stress. Functionally related genes are consistently and greatly up-regulated in a single genotype in response to cold or its alleviation, suggesting positive selection has driven genotype-specific temperature responses in maize.

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

A Core Regulatory Pathway Controlling Rice Tiller Angle Mediated by the LAZY1-Dependent Asymmetric Distribution of Auxin

Tiller angle in cereals is a key shoot architecture trait that strongly influences grain yield. Studies in rice (Oryza sativa) have implicated shoot gravitropism in the regulation of tiller angle. However, the functional link between shoot gravitropism and tiller angle is unknown. Here, we conducted a large-scale transcriptome analysis of rice shoots in response to gravistimulation and identified two new nodes of a shoot gravitropism regulatory gene network that also controls rice tiller angle. We demonstrate that HEAT STRESS TRANSCRIPTION FACTOR 2D (HSFA2D) is an upstream positive regulator of the LAZY1-mediated asymmetric auxin distribution pathway. We also show that two functionally redundant transcription factor genes, WUSCHEL RELATED HOMEOBOX6 (WOX6) and WOX11, are expressed asymmetrically in response to auxin to connect gravitropism responses with the control of rice tiller angle. These findings define upstream and downstream genetic components that link shoot gravitropism, asymmetric auxin distribution, and rice tiller angle. The results highlight the power of the high-temporal-resolution RNA-seq data set and its use to explore further genetic components controlling tiller angle. Collectively, these approaches will identify genes to improve grain yields by facilitating the optimization of plant architecture.

Unravelling miRNA regulation in yield of rice (Oryza sativa) based on differential network model

Rice (Oryza sativa L.) is one of the essential staple food crops and tillering, panicle branching and grain filling are three important traits determining the grain yield. Although miRNAs have been reported being regulating yield, no study has systematically investigated how miRNAs differentially function in high and low yield rice, in particular at a network level. This abundance of data from high-throughput sequencing provides an effective solution for systematic identification of regulatory miRNAs using developed algorithms in plants. We here present a novel algorithm, Gene Co-expression Network differential edge-like transformation (GRN-DET), which can identify key regulatory miRNAs in plant development. Based on the small RNA and RNA-seq data, miRNA-gene-TF co-regulation networks were constructed for yield of rice. Using GRN-DET, the key regulatory miRNAs for rice yield were characterized by the differential expression variances of miRNAs and co-variances of miRNA-mRNA, including osa-miR171 and osa-miR1432. Phytohormone cross-talks (auxin and brassinosteroid) were also revealed by these co-expression networks for the yield of rice.

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

Suppression of SlMBP15 Inhibits Plant Vegetative Growth and Delays Fruit Ripening in Tomato

MADS-box genes have been demonstrated to participate in a number of processes in tomato development, especially fruit ripening. In this study, we reported a novel MADS-box gene, SlMBP15, which is implicated in fruit ripening. Based on statistical analysis, the ripening time of SlMBP15-silenced tomato was delayed by 2-4 days compared with that of the wild-type (WT). The accumulation of carotenoids and biosynthesis of ethylene in fruits were decreased in SlMBP15-silenced tomato. Genes related to carotenoid and ethylene biosynthesis were greatly repressed. SlMBP15 can interact with RIN, a MADS-box regulator affecting the carotenoid accumulation and ethylene biosynthesis in tomato. In addition, SlMBP15-silenced tomato produced dark green leaves, and its plant height was reduced. The gibberellin (GA) content of transgenic plants was lower than that of the WT and GA biosynthesis genes were repressed. These results demonstrated that SlMBP15 not only positively regulated tomato fruit ripening but also affected the morphogenesis of the vegetative organs.

Target of rapamycin signaling orchestrates growth-defense trade-offs in plants

Plant defense to microbial pathogens is often accompanied by significant growth inhibition. How plants merge immune system function with normal growth and development is still poorly understood. Here, we investigated the role of target of rapamycin (TOR), an evolutionary conserved serine/threonine kinase, in the plant defense response. We used rice as a model system and applied a combination of chemical, genetic, genomic and cell-based analyses. We demonstrate that ectopic expression of TOR and Raptor (regulatory-associated protein of mTOR), a protein previously demonstrated to interact with TOR in Arabidopsis, positively regulates growth and development in rice. Transcriptome analysis of rice cells treated with the TOR-specific inhibitor rapamycin revealed that TOR not only dictates transcriptional reprogramming of extensive gene sets involved in central and secondary metabolism, cell cycle and transcription, but also suppresses many defense-related genes. TOR overexpression lines displayed increased susceptibility to both bacterial and fungal pathogens, whereas plants with reduced TOR signaling displayed enhanced resistance. Finally, we found that TOR antagonizes the action of the classic defense hormones salicylic acid and jasmonic acid. Together, these results indicate that TOR acts as a molecular switch for the activation of cell proliferation and plant growth at the expense of cellular immunity.

Transcriptional Network Analysis Reveals Drought Resistance Mechanisms of AP2/ERF Transgenic Rice

This study was designed to investigate at the molecular level how a transgenic version of rice "Nipponbare" obtained a drought-resistant phenotype. Using multi-omics sequencing data, we compared wild-type rice (WT) and a transgenic version (erf71) that had obtained a drought-resistant phenotype by overexpressing OsERF71, a member of the AP2/ERF transcription factor (TF) family. A comprehensive bioinformatics analysis pipeline, including TF networks and a cascade tree, was developed for the analysis of multi-omics data. The results of the analysis showed that the presence of OsERF71 at the source of the network controlled global gene expression levels in a specific manner to make erf71 survive longer than WT. Our analysis of the time-series transcriptome data suggests that erf71 diverted more energy to survival-critical mechanisms related to translation, oxidative response, and DNA replication, while further suppressing energy-consuming mechanisms, such as photosynthesis. To support this hypothesis further, we measured the net photosynthesis level under physiological conditions, which confirmed the further suppression of photosynthesis in erf71. In summary, our work presents a comprehensive snapshot of transcriptional modification in transgenic rice and shows how this induced the plants to acquire a drought-resistant phenotype.

Water-deficit-induced changes in transcription factor expression in maize seedlings

Plants tolerate water deficits by regulating gene networks controlling cellular and physiological traits to modify growth and development. Transcription factor (TF)-directed regulation of transcription within these gene networks is key to eliciting appropriate responses. In this study, reverse transcription quantitative PCR (RT-qPCR) was used to examine the abundance of 618 transcripts from 536 TF genes in individual root and shoot tissues of maize seedlings grown in vermiculite under well-watered (water potential of -0.02 MPa) and water-deficit conditions (water potentials of -0.3 and -1.6 MPa). A linear mixed model identified 433 TF transcripts representing 392 genes that differed significantly in abundance in at least one treatment, including TFs that intersect growth and development and environmental stress responses. TFs were extensively differentially regulated across stressed maize seedling tissues. Hierarchical clustering revealed TFs with stress-induced increased abundance in primary root tips that likely regulate root growth responses to water deficits, possibly as part of abscisic acid and/or auxin-dependent signaling pathways. Ten of these TFs were selected for validation in nodal root tips of drought-stressed field-grown plants (late V1 to early V2 stage). Changes in abundance of these TF transcripts under a field drought were similar to those observed in the seedling system.

Pathogenicity Genes in Ustilaginoidea virens Revealed by a Predicted Protein-Protein Interaction Network

Rice false smut, caused by Ustilaginoidea virens, produces significant losses in rice yield and grain quality and has recently emerged as one of the most important rice diseases worldwide. Despite its importance in rice production, relatively few studies have been conducted to illustrate the complex interactome and the pathogenicity gene interactions. Here a protein-protein interaction network of U. virens was built through two well-recognized approaches, interolog- and domain-domain interaction-based methods. A total of 20 217 interactions associated with 3305 proteins were predicted after strict filtering. The reliability of the network was assessed computationally and experimentally. The topology of the interactome network revealed highly connected proteins. A pathogenicity-related subnetwork involving up-regulated genes during early U. virens infection was also constructed, and many novel pathogenicity proteins were predicted in the subnetwork. In addition, we built an interspecies PPI network between U. virens and Oryza sativa, providing new insights for molecular interactions of this host-pathogen pathosystem. A web-based publicly available interactive database based on these interaction networks has also been released. In summary, a proteome-scale map of the PPI network was described for U. virens, which will provide new perspectives for finely dissecting interactions of genes related to its pathogenicity.

From Genes to Networks: Characterizing Gene-Regulatory Interactions in Plants

Plants, like other eukaryotes, have evolved complex mechanisms to coordinate gene expression during development, environmental response, and cellular homeostasis. Transcription factors (TFs), accompanied by basic cofactors and posttranscriptional regulators, are key players in gene-regulatory networks (GRNs). The coordinated control of gene activity is achieved by the interplay of these factors and by physical interactions between TFs and DNA. Here, we will briefly outline recent technological progress made to elucidate GRNs in plants. We will focus on techniques that allow us to characterize physical interactions in GRNs in plants and to analyze their regulatory consequences. Targeted manipulation allows us to test the relevance of specific gene-regulatory interactions. The combination of genome-wide experimental approaches with mathematical modeling allows us to get deeper insights into key-regulatory interactions and combinatorial control of important processes in plants.

PlaNet: Comparative Co-Expression Network Analyses for Plants

Functional relations between genes can be represented as networks. These networks have been successfully used to infer gene function and to mediate transfer of functional knowledge between species. Transcriptionally coordinated or co-expressed genes tend to be functionally related, which combined with availability of transcriptomic data for multiple plant species make the co-expression networks a useful resource for the plant community. In this chapter, we describe PlaNet ( www.gene2function.de ), a database that includes comparative analyses for co-expression networks of 11 plant species. We exemplify how the tools included in PlaNet can be used to predict gene function, transfer knowledge, and discover conserved and multiplied gene modules.

Brassinosteroid Mediated Cell Wall Remodeling in Grasses under Abiotic Stress

Unlike animals, plants, being sessile, cannot escape from exposure to severe abiotic stresses such as extreme temperature and water deficit. The dynamic structure of plant cell wall enables them to undergo compensatory changes, as well as maintain physical strength, with changing environments. Plant hormones known as brassinosteroids (BRs) play a key role in determining cell wall expansion during stress responses. Cell wall deposition differs between grasses (Poaceae) and dicots. Grass species include many important food, fiber, and biofuel crops. In this article, we focus on recent advances in BR-regulated cell wall biosynthesis and remodeling in response to stresses, comparing our understanding of the mechanisms in grass species with those in the more studied dicots. A more comprehensive understanding of BR-mediated changes in cell wall integrity in grass species will benefit the development of genetic tools to improve crop productivity, fiber quality and plant biomass recalcitrance.

Pan- and core- network analysis of co-expression genes in a model plant

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of 'pan-network' and 'core-network' representing union and intersection between a sizeable fractions of individual networks, respectively. We showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.

PoplarGene: poplar gene network and resource for mining functional information for genes from woody plants

Poplar is not only an important resource for the production of paper, timber and other wood-based products, but it has also emerged as an ideal model system for studying woody plants. To better understand the biological processes underlying various traits in poplar, e.g., wood development, a comprehensive functional gene interaction network is highly needed. Here, we constructed a genome-wide functional gene network for poplar (covering ~70% of the 41,335 poplar genes) and created the network web service PoplarGene, offering comprehensive functional interactions and extensive poplar gene functional annotations. PoplarGene incorporates two network-based gene prioritization algorithms, neighborhood-based prioritization and context-based prioritization, which can be used to perform gene prioritization in a complementary manner. Furthermore, the co-functional information in PoplarGene can be applied to other woody plant proteomes with high efficiency via orthology transfer. In addition to poplar gene sequences, the webserver also accepts Arabidopsis reference gene as input to guide the search for novel candidate functional genes in PoplarGene. We believe that PoplarGene (http://bioinformatics.caf.ac.cn/PoplarGene and http://124.127.201.25/PoplarGene) will greatly benefit the research community, facilitating studies of poplar and other woody plants.

Coexpression network analysis of the genes regulated by two types of resistance responses to powdery mildew in wheat

Powdery mildew disease caused by Blumeria graminis f. sp. tritici (Bgt) inflicts severe economic losses in wheat crops. A systematic understanding of the molecular mechanisms involved in wheat resistance to Bgt is essential for effectively controlling the disease. Here, using the diploid wheat Triticum urartu as a host, the genes regulated by immune (IM) and hypersensitive reaction (HR) resistance responses to Bgt were investigated through transcriptome sequencing. Four gene coexpression networks (GCNs) were developed using transcriptomic data generated for 20 T. urartu accessions showing IM, HR or susceptible responses. The powdery mildew resistance regulated (PMRR) genes whose expression was significantly correlated with Bgt resistance were identified, and they tended to be hubs and enriched in six major modules. A wide occurrence of negative regulation of PMRR genes was observed. Three new candidate immune receptor genes (TRIUR3_13045, TRIUR3_01037 and TRIUR3_06195) positively associated with Bgt resistance were discovered. Finally, the involvement of TRIUR3_01037 in Bgt resistance was tentatively verified through cosegregation analysis in a F2 population and functional expression assay in Bgt susceptible leaf cells. This research provides insights into the global network properties of PMRR genes. Potential molecular differences between IM and HR resistance responses to Bgt are discussed.

Tools of the trade: studying molecular networks in plants

Driven by recent technological improvements, genes can be now studied in a larger biological context. Genes and their protein products rarely operate as a single entity and large-scale mapping by protein-protein interactions can unveil the molecular complexes that form in the cell to carry out various functions. Expression analysis under multiple conditions, supplemented with protein-DNA binding data can highlight when genes are active and how they are regulated. Representing these data in networks and finding strongly connected sub-graphs has proven to be a powerful tool to predict the function of unknown genes. As such networks are gradually becoming available for various plant species, it becomes possible to study how networks evolve. This review summarizes currently available network data and related tools for plants. Furthermore we aim to provide an outlook of future analyses that can be done in plants based on work done in other fields.