SERRATE (SE) plays an important role in many biological processes and underbiotic stress resistance. However, little about the control of SE has beenclarified. Here we present a method named native chromatin-associated proteomeaffinity by CRISPR-dCas9 (CASPA-dCas9) to holistically capture native regulatorsof the SE locus. Several key regulatory factors including PHYTOCHROME RAPIDLYREGULATED 2 (PAR2), WRKY DNA-binding protein 19 (WRKY19) and the MYB-familyprotein MYB27 of SE are identified. MYB27 recruits the long non-coding RNA-PRC2(SEAIR-PRC2) complex for H3K27me3 deposition on exon 1 of SE and subsequentlyrepresses SE expression, while PAR2-MYB27 interaction inhibits both the bindingof MYB27 on the SE promoter and the recruitment of SEAIR-PRC2 by MYB27. Theinteraction between PAR2 and MYB27 fine-tunes the SE expression level atdifferent developmental stages. In addition, PAR2 and WRKY19 synergisticallypromote SE expression for pathogen resistance. Collectively, our resultsdemonstrate an efficient method to capture key regulators of target genes anduncover the precise regulatory mechanism for SE.

doi: 10.1038/s41477-023-01575-x PubMed: 38168608 Google Scholar

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The plant genome produces an extremely large collection of long noncoding RNAs(lncRNAs) that are generally expressed in a context-specific manner and havepivotal s in regulation of diverse biological processes. Here we mapped thetranscriptional rogeneity of lncRNAs and their associated gene regulatorynetworks at single-cell retion. We generated a comprehensive cell atlas atthe whole-organism level by integra analysis of 28 published single-cellRNA-sequencing (scRNA-seq) datasets from Arabiis juvenile seedlings. We thenprovided an in-depth analysis of cell type-related ln signatures that showsconsistent expression patterns with canonical protein-coding markers. Wefurther demonstrated that the cell-type specific expression of lncRNAs elyexplains their tissue specificity. In addition, we predicted gene regulatorynetw based on motif enrichment and co-expression analysis of lncRNAs andmRNAs, and idened putative transcription factors orchestrating the celltype-specific lncRNA expres. The above analysis results are available at thesingle cell-based plant lncRNA atlatabase (scPLAD;https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstr thepower of integrative single-cell data analysis applied to plant lncRNA biologyarovides fundamental insights into lncRNA expression specificity andassociated gene lation.

doi: 10.1016/j.xplc.2023.100717 PubMed: 37715446 Google Scholar

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Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic diseaserefractory to all targeted and immune therapies. However, our understanding ofPDAC microenvironment especially the metastatic microenvironment is very limitedpartly due to the inaccessibility to metastatic tumor tissues. Here, we presentthe single-cell transcriptomic landscape of synchronously resected PDAC primarytumors and matched liver metastases. We perform comparative analysis on bothcellular composition and functional phenotype between primary and metastatictumors. Tumor cells exhibit distinct transcriptomic profile in liver metastasiswith clearly defined evolutionary routes from cancer cells in primary tumor. Wealso identify specific subtypes of stromal and immune cells critical to theformation of the pro-tumor microenvironment in metastatic lesions, includingRGS5+ cancer-associated fibroblasts, CCL18+ lipid-associated macrophages,S100A8+ neutrophils and FOXP3+ regulatory T cells. Cellular interactome analysisfurther reveals that the lack of tumor-immune cell interaction in metastatictissues contributes to the formation of the immunosuppressive microenvironment.Our study provides a comprehensive characterization of the transcriptionallandscape of PDAC liver metastasis.

doi: 10.1038/s41467-023-40727-7 PubMed: 37612267 Google Scholar

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Single-cell RNA sequencing (scRNA-seq) has significantly accelerated theexperimental characterization of distinct cell lineages and types in complextissues and organisms. Cell-type annotation is of great importance in most ofthe scRNA-seq analysis pipelines. However, manual cell-type annotation heavilyrelies on the quality of scRNA-seq data and marker genes, and therefore can belaborious and time-consuming. Furthermore, the heterogeneity of scRNA-seqdatasets poses another challenge for accurate cell-type annotation, such as thebatch effect induced by different scRNA-seq protocols and samples. To overcomethese limitations, here we propose a novel pipeline, termed TripletCell, forcross-species, cross-protocol and cross-sample cell-type annotation. Wedeveloped a cell embedding and dimension-reduction module for the featureextraction (FE) in TripletCell, namely TripletCell-FE, to leverage the deepmetric learning-based algorithm for the relationships between the reference geneexpression matrix and the query cells. Our experimental studies on 21 datasets(covering nine scRNA-seq protocols, two species and three tissues) demonstratethat TripletCell outperformed state-of-the-art approaches for cell-typeannotation. More importantly, regardless of protocols or species, TripletCellcan deliver outstanding and robust performance in annotating different types ofcells. TripletCell is freely available at https://github.com/liuyan3056/TripletCell. We believe that TripletCell is areliable computational tool for accurately annotating various cell types usingscRNA-seq data and will be instrumental in assisting the generation of novelbiological hypotheses in cell biology.

doi: 10.1093/bib/bbad132 PubMed: 37080771 Google Scholar

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Reactive astrocytes play an important role in neurological diseases, but theirmolecular and functional phenotypes in epilepsy are unclear. Here, we show thatin patients with temporal lobe epilepsy (TLE) and mouse models of epilepsy,excessive lipid accumulation in astrocytes leads to the formation oflipid-accumulated reactive astrocytes (LARAs), a new reactive astrocyte subtypecharacterized by elevated APOE expression. Genetic knockout of APOE inhibitedLARA formation and seizure activities in epileptic mice. Single-nucleus RNAsequencing in TLE patients confirmed the existence of a LARA subpopulation witha distinct molecular signature. Functional studies in epilepsy mouse models andhuman brain slices showed that LARAs promote neuronal hyperactivity and diseaseprogression. Targeting LARAs by intervention with lipid transport and metabolismcould thus provide new therapeutic options for drug-resistant TLE.

doi: 10.1038/s41593-023-01288-6 PubMed: 36941428 Google Scholar

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SERRATE (SE) is a core protein for microRNA (miRNA) biogenesis as well as formRNA alternative splicing. Investigating the regulatory mechanism of SEexpression is hence critical to understanding its detailed function in diversebiological processes. However, little about the control of SE expression hasbeen clarified, especially through long noncoding RNA (lncRNA). Here, weidentified an antisense intragenic lncRNA transcribed from the 3' end of SE,named SEAIRa. SEAIRa repressed SE expression, which in turn led to serratedleaves. SEAIRa recruited plant U-box proteins PUB25/26 with unreported RNAbinding ability and a ubiquitin-like protein related to ubiquitin 1 (RUB1) forH2A monoubiquitination (H2Aub) at exon 11 of SE. In addition, PUB25/26 helpedcleave SEAIRa and release the 5' domain fragment, which recruited the PRC2complex for H3 lysine 27 trimethylation (H3K27me3) deposition at the first exonof SE. The distinct modifications of H2Aub and H3K27me3 at different sites ofthe SE locus cooperatively suppressed SE expression. Collectively, our resultsuncover an epigenetic mechanism mediated by the lncRNA SEAIRa that modulates SEexpression, which is indispensable for plant growth and development.

doi: 10.1073/pnas.2216062120 PubMed: 36857348 Google Scholar

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Single-cell omics technologies provide an unprecedented opportunity to deciphermolecular mechanisms underlying various biological processes in a cellularheterogeneity manner. The emergence of such techniques promotes the explorationof lncRNAs, which are known to be tissue- and cell-specific noncodingtranscripts involving the regulation of multiple important cellular processes.In this review, we introduce the advancement of lncRNA studies which benefitfrom single-cell omics data analysis. We discuss the expression heterogeneity oflncRNAs, their cell-type specificity and associated gene regulatory networks(GRNs) from a single-cell perspective. We also summarized the state-of-the-artsingle-cell omics resources and tools for the construction of single-cell GRNs(scGRNs) that could be potentially used for lncRNA functional study. Finally, wehighlight the challenges and prospective for scGRN exploration in lncRNAbiology.

doi: 10.1016/j.csbj.2022.08.003 PubMed: 36051880 Google Scholar

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Plant genomes encode a complex and evolutionary diverse regulatory grammar that forms the basis for most life on earth. A wealth of regulome and epigenome data have been generated in various plant species, but no common, standardized resource is available so far for biologists. Here, we present ChIP-Hub, an integrative web-based platform in the ENCODE standards that bundles >10,000 publicly available datasets reanalyzed from >40 plant species, allowing visualization and meta-analysis. We manually curate the datasets through assessing ~540 original publications and comprehensively evaluate their data quality. As a proof of concept, we extensively survey the co-association of different regulators and construct a hierarchical regulatory network under a broad developmental context. Furthermore, we show how our annotation allows to investigate the dynamic activity of tissue-specific regulatory elements (promoters and enhancers) and their underlying sequence grammar. Finally, we analyze the function and conservation of tissue-specific promoters, enhancers and chromatin states using comparative genomics approaches. Taken together, the ChIP-Hub platform and the analysis results provide rich resources for deep exploration of plant ENCODE. ChIP-Hub is available at https://biobigdata.nju.edu.cn/ChIPHub/.

doi: 10.1038/s41467-022-30770-1 PubMed: 35701419 Google Scholar

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Hibiscus hamabo is a semi-mangrove species with strong tolerance to salt andwaterlogging stress. However, the molecular basis and mechanisms that underliethis strong adaptability to harsh environments remain poorly understood. Here,we assembled a high-quality, chromosome-level genome of this semi-mangrove plantand analyzed its transcriptome under different stress treatments to revealregulatory responses and mechanisms. Our analyses suggested that H. hamabo hasundergone two recent successive polyploidy events, a whole-genome duplicationfollowed by a whole-genome triplication, resulting in an unusually large genenumber (107鈥?09 genes). Comparison of the H. hamabo genome with that of itsclose relative Hibiscus cannabinus, which has not experienced a recent WGT,indicated that genes associated with high stress resistance have beenpreferentially preserved in the H. hamabo genome, suggesting an underlyingassociation between polyploidy and stronger stress resistance. Transcriptomicdata indicated that genes in the roots and leaves responded differently tostress. In roots, genes that regulate ion channels involved in biosynthetic andmetabolic processes responded quickly to adjust the ion concentration andprovide metabolic products to protect root cells, whereas no such rapid responsewas observed from genes in leaves. Using co-expression networks, potentialstress resistance genes were identified for use in future functionalinvestigations. The genome sequence, along with several transcriptome datasets,provide insights into genome evolution and the mechanism of salt andwaterlogging tolerance in H. hamabo, suggesting the importance ofpolyploidization for environmental adaptation.

doi: 10.1093/hr/uhac067 PubMed: 35480957 Google Scholar

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Psoriasis is a complex chronic inflammatory skin disease with unclear molecular mechanisms. We found that the Src homology-2 domain-containing protein tyrosine phosphatase-2 (SHP2) was highly expressed in both psoriatic patients and imiquimod (IMQ)-induced psoriasis-like mice. Also, the SHP2 allosteric inhibitor SHP099 reduced pro-inflammatory cytokine expression in PBMCs taken from psoriatic patients. Consistently, SHP099 significantly ameliorated IMQ-triggered skin inflammation in mice. Single-cell RNA sequencing of murine skin demonstrated that SHP2 inhibition impaired skin inflammation in myeloid cells, especially macrophages. Furthermore, IMQ-induced psoriasis-like skin inflammation was significantly alleviated in myeloid cells (monocytes, mature macrophages, and granulocytes)-but not dendritic cells conditional SHP2 knockout mice. Mechanistically, SHP2 promoted the trafficking of toll-like receptor 7 (TLR7) from the Golgi to the endosome in macrophages by dephosphorylating TLR7 at Tyr1024, boosting the ubiquitination of TLR7 and NF-魏B-mediated skin inflammation. Importantly, Tlr7 point-mutant knock-in mice showed an attenuated psoriasis-like phenotype compared to wild-type littermates following IMQ treatment. Collectively, our findings identify SHP2 as a novel regulator of psoriasis and suggest that SHP2 inhibition may be a promising therapeutic approach for psoriatic patients.

doi: 10.15252/emmm.202114455 PubMed: 34936223 Google Scholar

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doi: 10.1111/pbi.13675 PubMed: 34310056 Google Scholar

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Nucleotide-binding leucine-rich-repeat (NLR) genes comprise the largest familyof plant disease-resistance genes. Angiosperm NLR genes are phylogeneticallydivided into the TNL, CNL, and RNL subclasses. NLR copy numbers and subclasscomposition vary tremendously across angiosperm genomes. However, theevolutionary associations between genomic NLR content and ecological adaptation,or between NLR content and signal transduction components, are poorlycharacterized because of limited genome availability. In this study, weestablished an angiosperm NLR atlas (ANNA, https://biobigdata.nju.edu.cn/ANNA/)that includes NLR genes from over 300 angiosperm genomes. Using ANNA, werevealed that NLR copy numbers differ up to 66-fold among closely relatedspecies owing to rapid gene loss and gain. Interestingly, NLR contraction wasassociated with adaptations to aquatic, parasitic, and carnivorous lifestyles.The convergent NLR reduction in aquatic plants resembles the lack of NLRexpansion during the long-term evolution of green algae before the colonizationof land. A co-evolutionary pattern between NLR subclasses and plant immunepathway components was also identified, suggesting that immune pathwaydeficiencies may drive TNL loss. Finally, we identified a conserved TNL lineagethat may function independently of the EDS1-SAG101-NRG1 module. Collectively,these findings provide new insights into the evolution of NLR genes in thecontext of ecological adaptation and genome content variation.

doi: 10.1016/j.molp.2021.08.001 PubMed: 34364002 Google Scholar

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Lamin proteins in animals are implicated in important nuclear functions,including chromatin organization, signalling transduction, gene regulation andcell differentiation. Nuclear Matrix Constituent Proteins (NMCPs) are laminanalogues in plants, but their regulatory functions remain largely unknown. Wereport that OsNMCP1 is localized at the nuclear periphery in rice (Oryza sativa)and induced by drought stress. OsNMCP1 overexpression resulted in a deeper andthicker root system, and enhanced drought resistance compared to the wild-typecontrol. An assay for transposase accessible chromatin with sequencing(ATAC-seq) analysis revealed that OsNMCP1-overexpression altered chromatinaccessibility in hundreds of genes related to drought resistance and rootgrowth, including OsNAC10, OsERF48, OsSGL, SNAC1 and OsbZIP23. OsNMCP1 caninteract with SWITCH/SUCROSE NONFERMENTING (SWI/SNF) chromatin remodellingcomplex subunitOsSWI3C. The reported drought resistance or root growth-relatedgenes that were positively regulated by OsNMCP1 were negatively regulated byOsSWI3C under drought stress conditions, and OsSWI3C overexpression led todecreased drought resistance. We propose that the interaction between OsNMCP1and OsSWI3C under drought stress conditions may lead to the release of OsSWI3Cfrom the SWI/SNF gene silencing complex, thus changing chromatin accessibilityin the genes related to root growth and drought resistance.

doi: 10.1111/nph.16518 PubMed: 32129897 Google Scholar

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BACKGROUND: Adaptation to drought-prone environments requires robust root architecture. Genotypes with a more vigorous root system have the potential to better adapt to soils with limited moisture content. However, root architecture is complex at both, phenotypic and genetic level. Customized mapping panels in combination with efficient screenings methods can resolve the underlying genetic factors of root traits. RESULTS: A mapping panel of 233 spring barley genotypes was evaluated for root and shoot architecture traits under non-stress and osmotic stress. A genome-wide association study elucidated 65 involved genomic regions. Among them were 34 root-specific loci, eleven hotspots with associations to up to eight traits and twelve stress-specific loci. A list of candidate genes was established based on educated guess. Selected genes were tested for associated polymorphisms. By this, 14 genes were identified as promising candidates, ten remained suggestive and 15 were rejected. The data support the important role of flowering time genes, including HvPpd-H1, HvCry2, HvCO4 and HvPRR73. Moreover, seven root-related genes, HERK2, HvARF04, HvEXPB1, PIN5, PIN7, PME5 and WOX5 are confirmed as promising candidates. For the QTL with the highest allelic effect for root thickness and plant biomass a homologue of the Arabidopsis Trx-m3 was revealed as the most promising candidate. CONCLUSIONS: This study provides a catalogue of hotspots for seedling growth, root and stress-specific genomic regions along with candidate genes for future potential incorporation in breeding attempts for enhanced yield potential, particularly in drought-prone environments. Root architecture is under polygenic control. The co-localization of well-known major genes for barley development and flowering time with QTL hotspots highlights their importance for seedling growth. Association analysis revealed the involvement of HvPpd-H1 in the development of the root system. The co-localization of root QTL with HERK2, HvARF04, HvEXPB1, PIN5, PIN7, PME5 and WOX5 represents a starting point to explore the roles of these genes in barley. Accordingly, the genes HvHOX2, HsfA2b, HvHAK2, and Dhn9, known to be involved in abiotic stress response, were located within stress-specific QTL regions and await future validation.

doi: 10.1186/s12870-019-1828-5 PubMed: 31122195 Google Scholar

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Floral homeotic transcription factors (TFs) act in a combinatorial manner to specify the organ identities in the flower. However, the architecture and thefunction of the gene regulatory network (GRN) controlling floral organ specification is still poorly understood. In particular, the interconnections of homeotic TFs, microRNAs (miRNAs) and other factors controlling organ initiation and growth have not been studied systematically so far. Here, using a combination of genome-wide TF binding, mRNA and miRNA expression data, we reconstruct the dynamic GRN controlling floral meristem development and organ differentiation. We identify prevalent feed-forward loops (FFLs) mediated by floral homeotic TFs and miRNAs that regulate common targets. Experimental validation of a coherent FFL shows that petal size is controlled by the SEPALLATA3-regulated miR319/TCP4 module. We further show that combinatorial DNA-binding of homeotic factors and selected other TFs is predictive of organ-specific patterns of gene expression. Our results provide a valuable resource for studying molecular regulatory processes underlying floral organ specification in plants.

doi: 10.1038/s41467-018-06772-3 PubMed: 30382087 Google Scholar

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In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3-0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield.

doi: 10.1038/s41598-018-31977-3 PubMed: 30258057 Google Scholar

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Deoxyribonuclease I (DNase I)-hypersensitive site sequencing (DNase-seq) has been widely used to determine chromatin accessibility and its underlying regulatory lexicon. However, exploring DNase-seq data requires sophisticated downstream bioinformatics analyses. In this study, we first review computational methods for all of the major steps in DNase-seq data analysis, including experimental design, quality control, read alignment, peak calling, annotation of cis-regulatory elements, genomic footprinting and visualization. The challenges associated with each step are highlighted. Next, we provide a practical guideline and a computational pipeline for DNase-seq data analysis by integrating some of these tools. We also discuss the competing techniques and the potential applications of this pipeline for the analysis of analogous experimental data. Finally, we discuss the integration of DNase-seq with other functional genomics techniques.

doi: 10.1093/bib/bby057 PubMed: 30010713 Google Scholar

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Floret development is critical for grain setting in wheat (Triticum aestivum), but more than 50% of grain yield potential (based on the maximum number of floret primordia) is lost during the stem elongation phase (SEP, from the terminal spikelet stage to anthesis). Dynamic plant (e.g., leaf area, plant height) and floret (e.g., anther and ovary size) growth and its connection with grain yield traits (e.g., grain number and width) are not clearly understood. In this study, for the first time, we dissected the SEP into seven stages to investigate plant (first experiment) and floret (second experiment) growth in greenhouse- and field-grown wheat. In the first experiment, the values of various plant growth trait indices at different stages were generally consistent between field and greenhouse and were independent of the environment. However, at specific stages, some traits significantly differed between the two environments. In the second experiment, phenotypic and genotypic similarity analysis revealed that grain number and size corresponded closely to ovary size at anthesis, suggesting that ovary size is strongly associated with grain number and size. Moreover, principal component analysis (PCA) showed that the top six principal components PCs explained 99.13, 98.61, 98.41, 98.35, and 97.93% of the total phenotypic variation at the green anther, yellow anther, tipping, heading, and anthesis stages, respectively. The cumulative variance explained by the first PC decreased with floret growth, with the highest value detected at the green anther stage (88.8%) and the lowest at the anthesis (50.09%). Finally, ovary size at anthesis was greater in wheat accessions with early release years than in accessions with late release years, and anther/ovary size shared closer connections with grain number/size traits at the late vs. early stages of floral development. Our findings shed light on the dynamic changes in plant and floret growth-related traits in wheat and the effects of the environment on these traits.

doi: 10.3389/fpls.2018.00330 PubMed: 29599792 Google Scholar

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Floral organ identities in plants are specified by the combinatorial action of homeotic master regulatory transcription factors. However, how these factors achieve their regulatory specificities is still largely unclear. Genome-wide in vivo DNA binding data show that homeotic MADS domain proteins recognize partly distinct genomic regions, suggesting that DNA binding specificity contributes to functional differences of homeotic protein complexes. We used in vitro systematic evolution of ligands by exponential enrichment followed by high-throughput DNA sequencing (SELEX-seq) on several floral MADS domain protein homo- and heterodimers to measure their DNA binding specificities. We show that specification of reproductive organs is associated with distinct binding preferences of a complex formed by SEPALLATA3 and AGAMOUS. Binding specificity is further modulated by different binding site spacing preferences. Combination of SELEX-seq and genome-wide DNA binding data allows differentiation between targets in specification of reproductive versus perianth organs in the flower. We validate the importance of DNA binding specificity for organ-specific gene regulation by modulating promoter activity through targeted mutagenesis. Our study shows that intrafamily protein interactions affect DNA binding specificity of floral MADS domain proteins. Differential DNA binding of MADS domain protein complexes plays a role in the specificity of target gene regulation.

doi: 10.1105/tpc.17.00145 PubMed: 28733422 Google Scholar

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BACKGROUND: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. RESULTS: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. CONCLUSIONS: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

doi: 10.1186/s13007-016-0144-4 PubMed: 27843484 Google Scholar

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Flower development is a model system to understand organ specification in plants. The identities of different types of floral organs are specified by homeotic MADS transcription factors that interact in a combinatorial fashion. Systematic identification of DNA-binding sites and target genes of these key regulators show that they have shared and unique sets of target genes. DNA binding by MADS proteins is not based on 'simple' recognition of a specific DNA sequence, but depends on DNA structure and combinatorial interactions. Homeotic MADS proteins regulate gene expression via alternative mechanisms, one of which may be to modulate chromatin structure and accessibility in their target gene promoters.

doi: 10.1016/j.pbi.2015.12.004 PubMed: 26802807 Google Scholar

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Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.

doi: 10.1093/jxb/erv271 PubMed: 26044092 Google Scholar

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Anther and ovary development play an important role in grain setting, a crucial factor determining wheat (Triticum aestivum L.) yield. One aim of this study was to determine the heritability of anther and ovary size at different positions within a spikelet at seven floral developmental stages and conduct a variance components analysis. Relationships between anther and ovary size and other traits were also assessed. The thirty central European winter wheat genotypes used in this study were based on reduced height (Rht) and photoperiod sensitivity (Ppd) genes with variable genetic backgrounds. Identical experimental designs were conducted in a greenhouse and field simultaneously. Heritability of anther and ovary size indicated strong genetic control. Variance components analysis revealed that anther and ovary sizes of floret 3 (i.e. F3, the third floret from the spikelet base) and floret 4 (F4) were more sensitive to the environment compared with those in floret 1 (F1). Good correlations were found between spike dry weight and anther and ovary size in both greenhouse and field, suggesting that anther and ovary size are good predictors of each other, as well as spike dry weight in both conditions. Relationships between spike dry weight and anther and ovary size at F3/4 positions were stronger than at F1, suggesting that F3/4 anther and ovary size are better predictors of spike dry weight. Generally, ovary size showed a closer relationship with spike dry weight than anther size, suggesting that ovary size is a more reliable predictor of spike dry weight.

doi: 10.1093/jxb/erv117 PubMed: 25821074 Google Scholar

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Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.

doi: 10.1105/tpc.114.129601 PubMed: 25501589 Google Scholar

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BACKGROUND: Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species. RESULTS: In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks. CONCLUSIONS: Gene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange.

doi: 10.1186/s12870-014-0213-7 PubMed: 25091279 Google Scholar

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Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

doi: 10.1371/journal.pone.0087723 PubMed: 24489955 Google Scholar

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Pandemic H1N1/2009 viruses have been stabilized in swine herds, and some strains display higher pathogenicity than the human-origin isolates. In this study, high-throughput RNA sequencing (RNA-seq) is applied to explore the systemic transcriptome responses of the mouse lungs infected by swine (Jia6/10) and human (LN/09) H1N1/2009 viruses. The transcriptome data show that Jia6/10 activates stronger virus-sensing signals, such as the toll-like receptor, RIG-I like receptor and NOD-like receptor signalings, as well as a stronger NF-魏B and JAK-STAT signals, which play significant roles in inducing innate immunity. Most cytokines and interferon-stimulated genes show higher expression lever in Jia/06 infected groups. Meanwhile, virus Jia6/10 activates stronger production of reactive oxygen species, which might further promote higher mutation rate of the virus genome. Collectively, our data reveal that the swine-origin pandemic H1N1/2009 virus elicits a stronger innate immune reaction and pro-oxidation stimulation, which might relate closely to the increasing pathogenicity.

doi: 10.1038/srep01601 PubMed: 23549303 Google Scholar

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Oranges are an important nutritional source for human health and have immense economic value. Here we present a comprehensive analysis of the draft genome of sweet orange (Citrus sinensis). The assembled sequence covers 87.3% of the estimated orange genome, which is relatively compact, as 20% is composed of repetitive elements. We predicted 29,445 protein-coding genes, half of which are in the heterozygous state. With additional sequencing of two more citrus species and comparative analyses of seven citrus genomes, we present evidence to suggest that sweet orange originated from a backcross hybrid between pummelo and mandarin. Focused analysis on genes involved in vitamin C metabolism showed that GalUR, encoding the rate-limiting enzyme of the galacturonate pathway, is significantly upregulated in orange fruit, and the recent expansion of this gene family may provide a genomic basis. This draft genome represents a valuable resource for understanding and improving many important citrus traits in the future.

doi: 10.1038/ng.2472 PubMed: 23179022 Google Scholar

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Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a 'Gene Set Analysis' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.

doi: 10.1093/nar/gkr823 PubMed: 22058132 Google Scholar

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Small RNAs (sRNAs), largely known as microRNAs (miRNAs) and short interfering RNAs (siRNAs), emerged as the critical components of genetic and epigenetic regulation in eukaryotic genomes. In animals, a sizable portion of miRNAs reside within the introns of protein-coding genes, designated as mirtron genes. Recently, high-throughput sequencing (HTS) revealed a huge amount of sRNAs that derived from introns in plants, such as the monocot rice (Oryza sativa). However, the biogenesis and the biological functions of this kind of sRNAs remain elusive. Here, we performed a genome-scale survey of intron-derived sRNAs in rice based on HTS data. Several introns were found to have great potential to form internal hairpin structures, and the short hairpins could generate miRNAs while the larger ones could produce siRNAs. Furthermore, 22 introns, termed "sirtrons," were identified from the rice protein-coding genes. The single-stranded sirtrons produced a diverse set of siRNAs from long hairpin structures. These sirtron-derived siRNAs are dominantly 21 nt, 22 nt, and 24 nt in length, whose production relied on DCL4, DCL2, and DCL3, respectively. We also observed a strong tendency for the sirtron-derived siRNAs to be coexpressed with their host genes. Finally, the 24-nt siRNAs incorporated with Argonaute 4 (AGO4) could direct DNA methylation on their host genes. In this regard, homeostatic self-regulation between intron-derived siRNAs and their host genes was proposed.

doi: 10.1261/rna.2589011 PubMed: 21518803 Google Scholar

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BACKGROUND: RNA editing is a transcript-based layer of gene regulation. To date, no systemic study on RNA editing of plant nuclear genes has been reported. Here, a transcriptome-wide search for editing sites in nuclear transcripts of Arabidopsis (Arabidopsis thaliana) was performed. RESULTS: MPSS (massively parallel signature sequencing) and PARE (parallel analysis of RNA ends) data retrieved from public databases were utilized, focusing on one-base-conversion editing. Besides cytidine (C)-to-uridine (U) editing in mitochondrial transcripts, many nuclear transcripts were found to be diversely edited. Interestingly, a sizable portion of these nuclear genes are involved in chloroplast- or mitochondrion-related functions, and many editing events are tissue-specific. Some editing sites, such as adenosine (A)-to-U editing loci, were found to be surrounded by peculiar elements. The editing events of some nuclear transcripts are highly enriched surrounding the borders between coding sequences (CDSs) and 3' untranslated regions (UTRs), suggesting site-specific editing. Furthermore, RNA editing is potentially implicated in new start or stop codon generation, and may affect alternative splicing of certain protein-coding transcripts. RNA editing in the precursor microRNAs (pre-miRNAs) of ath-miR854 family, resulting in secondary structure transformation, implies its potential role in microRNA (miRNA) maturation. CONCLUSIONS: To our knowledge, the results provide the first global view of RNA editing in plant nuclear transcripts.

doi: 10.1186/1471-2164-11-S4-S12 PubMed: 21143795 Google Scholar

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MicroRNAs (miRNAs), one type of small RNAs (sRNAs) in plants, play an essential role in gene regulation. Several miRNA databases were established; however, successively generated new datasets need to be collected, organized and analyzed. To this end, we have constructed a plant miRNA knowledge base (PmiRKB) that provides four major functional modules. In the 'SNP' module, single nucleotide polymorphism (SNP) data of seven Arabidopsis (Arabidopsis thaliana) accessions and 21 rice (Oryza sativa) subspecies were collected to inspect the SNPs within pre-miRNAs (precursor microRNAs) and miRNA-target RNA duplexes. Depending on their locations, SNPs can affect the secondary structures of pre-miRNAs, or interactions between miRNAs and their targets. A second module, 'Pri-miR', can be used to investigate the tissue-specific, transcriptional contexts of pre- and pri-miRNAs (primary microRNAs), based on massively parallel signature sequencing data. The third module, 'MiR-Tar', was designed to validate thousands of miRNA-target pairs by using parallel analysis of RNA end (PARE) data. Correspondingly, the fourth module, 'Self-reg', also used PARE data to investigate the metabolism of miRNA precursors, including precursor processing and miRNA- or miRNA*-mediated self-regulation effects on their host precursors. PmiRKB can be freely accessed at http://bis.zju.edu.cn/pmirkb/.

doi: 10.1093/nar/gkq721 PubMed: 20719744 Google Scholar

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Since the beginning of this century, microRNAs (miRNAs), which are tiny RNA molecules, have become one of the major research topics on gene expression regulation in both animals and plants. The major task of miRNA study is to elucidate how the miRNAs are expressed in vivo, how they exert regulatory effects on their targets, and how they can be qualitatively or quantitatively cloned. For these purposes, the methodology of miRNA study has been developed and significantly improved in recent years. The focus here is on a number of powerful methods for plant miRNA research including bioinformatics tools and experimental approaches being used for upstream or downstream analysis of miRNAs or miRNA cloning. Some discrepancies exist in the miRNA research methodology between plants and animals, for example, 5' modified RACE (Rapid Amplification of cDNA Ends) can be used for cleavage target validation only in plants. However, numerous common methods are shared by these two miRNA research areas. Thus, this review will enhance our understanding of miRNA research methodology in organisms.

doi: 10.1093/jxb/erq087 PubMed: 20388745 Google Scholar

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MicroRNA (miRNA), recently recognized as a critical post-transcriptional modulator of gene expression, is involved in numerous biological processes in both animals and plants. Although eudicots and monocots, such as the model plants Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), possess distinct root systems, several homologous miRNA families are reported to be involved in root growth control in both plants. Consistent with recent notion that numerous signaling pathways are implicated in root development, these miRNAs are implicated in auxin signaling, nutrition metabolism, or stress response and have potential role in mediating the signal interactions. However, a recapitulative representation of these results is especially desired. This review provides a global view of the involvement of miRNAs in root development focusing on the two plants, Arabidopsis and rice. Based on current research advances, several innovative mechanisms of miRNA transcription, feedback regulatory circuit between miRNAs and transcription factors (TFs), and miRNA-mediated signal interactions are also discussed.

doi: 10.1016/j.bbrc.2010.01.129 PubMed: 20138828 Google Scholar

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Auxin is one of the central hormones in plants, and auxin response factor (ARF) is a key regulator in the early auxin response. MicroRNAs (miRNAs) play an essential role in auxin signal transduction, but knowledge remains limited about the regulatory network between miRNAs and protein-coding genes (e.g. ARFs) involved in auxin signalling. In this study, we used a novel auxin-resistant rice mutant with plethoric root defects to investigate the miRNA expression patterns using microarray analysis. A number of miRNAs showed reduced auxin sensitivity in the mutant compared with the wild type, consistent with the auxin-resistant phenotype of the mutant. Four miRNAs with significantly altered expression patterns in the mutant were further confirmed by Northern blot, which supported our microarray data. Clustering analysis revealed some novel auxin-sensitive miRNAs in roots. Analysis of miRNA duplication and expression patterns suggested the evolutionary conservation between miRNAs and protein-coding genes. MiRNA promoter analysis suggested the possibility that most plant miRNAs might share the similar transcriptional mechanisms with other non-plant eukaryotic genes transcribed by RNA polymerase II. Auxin response elements were proved to be more frequently present in auxin-related miRNA promoters. Comparative analysis of miRNA and protein-coding gene expression datasets uncovered many reciprocally expressed miRNA-target pairs, which could provide some hints for miRNA downstream analysis. Based on these findings, we also proposed a feedback circuit between miRNA(s) and ARF(s). The results presented here could serve as the basis for further in-depth studies of plant miRNAs involved in auxin signalling.

doi: 10.1007/s00425-009-0994-3 PubMed: 19655164 Google Scholar

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Key transcription factors (TFs) controlling the morphogenesis of flowers and leaves have been identified in the model plant Arabidopsis thaliana. Recent genome-wide approaches based on chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) enable systematic identification of genome-wide TF binding sites (TFBSs) of these regulators. Here, we describe a computational pipeline for analyzing ChIP-seq data to identify TFBSs and to characterize gene regulatory networks (GRNs) with applications to the regulatory studies of flower development. In particular, we provide step-by-step instructions on how to download, analyze, visualize, and integrate genome-wide data in order to construct GRNs for beginners of bioinformatics. The practical guide presented here is ready to apply to other similar ChIP-seq datasets to characterize GRNs of interest.

doi: 10.1007/978-1-4939-7125-1_16 PubMed: 28623590 Google Scholar

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Genomics and phenomics are two fundamentally important branches of biological sciences, and they stand at both ends of the multiple 鈥渙mics鈥?families. A central goal of current biology is to establish complete functional links between the genome and phenome, the so-called genotype鈥損henotype map. Recent advances in high-throughput and high-dimensional genotyping and phenotyping technologies enable us to uncover the casual networks inside the 鈥渂lack box鈥?that lies between genotypes and phenotypes using the principles of genome-wide association studies (GWAS). Application of GWAS and analogous methodologies and incorporation of multiple omics data begin to unravel the contribution of genetic variation to phenotypic diversity. Integrating 鈥渙mics鈥?data at broad levels by using the systems-biology approach is paramount to further bridging the gaps between genomics and phenomics and eventually making accurate predictions of phenotypes based on genetic contribution.

doi: 10.1007/978-3-642-41281-3_11 Google Scholar

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