ChIP-Hub provides an integrative platform for exploring plant regulome

H3K36me3 regulates subsets of photosynthesis genes in Sorghum bicolor potentially by counteracting H3K27me3 or H2A.Z

H3K36me3, catalyzed by ASHH proteins, serves as a positive histone mark associated with gene expression and plays a crucial role in plant development. In our study, we identified that sorghum SbASHH2 exhibits H3K36 methyltransferase activity. Immunoprecipitation analysis revealed that H3K36me3 rarely co-occurs with H3K27me3, and genome-wide profiling of these two marks indicates a non-overlapping distribution across the sorghum genome, underscoring the antagonistic relationship between H3K36me3 and H3K27me3. Furthermore, we observed that H2A.Z is deposited near the transcription start site (TSS) of genes enriched with H3K36me3, while genes with H2A.Z deposition in the gene body lack H3K36me3, suggesting an interplay between H3K36me3 and H2A.Z deposition. Our findings show that the high expression of photosynthesis genes in leaves is closely linked to H3K36me3 deposition, with only a small subset involving the removal of H3K27me3 or eviction of H2A.Z. This implies that H3K36me3 activates specific subsets of photosynthesis genes by antagonizing H3K27me3 or H2A.Z. Additionally, we found that the deposition of H3K36me3 on most photosynthesis genes is neither specific to mesophyll (M) nor bundle sheath (BS) cells and is independent of light induction. Our results emphasize the significance of H3K36me3 in the regulation of photosynthesis genes and lay the groundwork for further investigation into the mechanisms by which H3K36me3 contributes to gene regulation.

Data reuse in agricultural genomics research: challenges and recommendations

The scientific community has long benefited from the opportunities provided by data reuse. Recognizing the need to identify the challenges and bottlenecks to reuse in the agricultural research community and propose solutions for them, the data reuse working group was started within the AgBioData consortium framework. Here, we identify the limitations of data standards, metadata deficiencies, data interoperability, data ownership, data availability, user skill level, resource availability, and equity issues, with a specific focus on agricultural genomics research. We propose possible solutions stakeholders could implement to mitigate and overcome these challenges and provide an optimistic perspective on the future of genomics and transcriptomics data reuse.

High-throughput capture of transcription factor-driven epigenome dynamics using PHILO ChIP-seq

Assessing the dynamics of chromatin features and transcription factor (TF) binding at scale remains a significant challenge in plants. Here, we present PHILO (Plant HIgh-throughput LOw input) ChIP-seq, a high-throughput ChIP-seq platform that enables the cost-effective and extensive capture of TF binding and genome-wide distributions of histone modifications. The PHILO ChIP-seq pipeline is adaptable to many plant species, requires very little starting material (1mg), and provides the option to use MNase (micrococcal nuclease) for chromatin fragmentation. By employing H3K9ac PHILO ChIP-seq on eight Arabidopsis thaliana jasmonic acid (JA) pathway mutants, with the simultaneous processing of over 100 samples, we not only recapitulated but also expanded the current understanding of the intricate interplay between the master TFs MYC2/3/4 and various chromatin regulators. Additionally, our analyses brought to light previously unknown histone acetylation patterns within the regulatory regions of MYC2 target genes in Arabidopsis, which is also conserved in tomato (Solanum lycopersicum). In summary, our PHILO ChIP-seq platform demonstrates its high effectiveness in investigating TF binding and chromatin dynamics on a large scale in plants, paving the way for the cost-efficient realization of complex experimental setups.

Characterization of the Cannabis sativa glandular trichome epigenome

BACKGROUND

The relationship between epigenomics and plant specialised metabolism remains largely unexplored despite the fundamental importance of epigenomics in gene regulation and, potentially, yield of products of plant specialised metabolic pathways. The glandular trichomes of Cannabis sativa are an emerging model system that produce large quantities of cannabinoid and terpenoid specialised metabolites with known medicinal and commercial value. To address this lack of epigenomic data, we mapped H3K4 trimethylation, H3K56 acetylation, H3K27 trimethylation post-translational modifications and the histone variant H2A.Z, using chromatin immunoprecipitation, in C. sativa glandular trichomes, leaf, and stem tissues. Corresponding transcriptomic (RNA-seq) datasets were integrated, and tissue-specific analyses conducted to relate chromatin states to glandular trichome specific gene expression.

RESULTS

The promoters of cannabinoid and terpenoid biosynthetic genes, specialised metabolite transporter genes, defence related genes, and starch and sucrose metabolism were enriched specifically in trichomes for histone marks H3K4me3 and H3K56ac, consistent with active transcription. We identified putative trichome-specific enhancer elements by identifying intergenic regions of H3K56ac enrichment, a histone mark that maintains enhancer accessibility, then associated these to putative target genes using the tissue specific gene transcriptomic data. Bi-valent chromatin loci specific to glandular trichomes, marked with H3K4 trimethylation and H3K27 trimethylation, were associated with genes of MAPK signalling pathways and plant specialised metabolism pathways, supporting recent hypotheses that implicate bi-valent chromatin in plant defence. The histone variant H2A.Z was largely found in intergenic regions and enriched in chromatin that contained genes involved in DNA homeostasis.

CONCLUSION

We report the first genome-wide histone post-translational modification maps for C. sativa glandular trichomes, and more broadly for glandular trichomes in plants. Our findings have implications in plant adaptation and stress responses and provide a basis for enhancer-mediated, targeted, gene transformation studies in plant glandular trichomes.

START domains generate paralog-specific regulons from a single network architecture

Functional divergence of transcription factors (TFs) has driven cellular and organismal complexity throughout evolution, but its mechanistic drivers remain poorly understood. Here we test for new mechanisms using CORONA (CNA) and PHABULOSA (PHB), two functionally diverged paralogs in the CLASS III HOMEODOMAIN LEUCINE ZIPPER (HD-ZIPIII) family of TFs. We show that virtually all genes bound by PHB ( ~ 99%) are also bound by CNA, ruling out occupation of distinct sets of genes as a mechanism of functional divergence. Further, genes bound and regulated by both paralogs are almost always regulated in the same direction, ruling out opposite regulation of shared targets as a mechanistic driver. Functional divergence of CNA and PHB instead results from differential usage of shared binding sites, with hundreds of uniquely regulated genes emerging from a commonly bound genetic network. Regulation of a given gene by CNA or PHB is thus a function of whether a bound site is considered 'responsive' versus 'non-responsive' by each paralog. Discrimination between responsive and non-responsive sites is controlled, at least in part, by their lipid binding START domain. This suggests a model in which HD-ZIPIII TFs use information integrated by their START domain to generate paralog-specific transcriptional outcomes from a shared network architecture. Taken together, our study identifies a mechanism of HD-ZIPIII TF paralog divergence and proposes the ubiquitously distributed START evolutionary module as a driver of functional divergence.

Comprehensive analysis of computational approaches in plant transcription factors binding regions discovery

Transcription factors (TFs) are regulatory proteins which bind to a specific DNA region known as the transcription factor binding regions (TFBRs) to regulate the rate of transcription process. The identification of TFBRs has been made possible by a number of experimental and computational techniques established during the past few years. The process of TFBR identification involves peak identification in the binding data, followed by the identification of motif characteristics. Using the same binding data attempts have been made to raise computational models to identify such binding regions which could save time and resources spent for binding experiments. These computational approaches depend a lot on what way they learn and how. These existing computational approaches are skewed heavily around human TFBRs discovery, while plants have drastically different genomic setup for regulation which these approaches have grossly ignored. Here, we provide a comprehensive study of the current state of the matters in plant specific TF discovery algorithms. While doing so, we encountered several software tools' issues rendering the tools not useable to researches. We fixed them and have also provided the corrected scripts for such tools. We expect this study to serve as a guide for better understanding of software tools' approaches for plant specific TFBRs discovery and the care to be taken while applying them, especially during cross-species applications. The corrected scripts of these software tools are made available at https://github.com/SCBB-LAB/Comparative-analysis-of-plant-TFBS-software.

Sugar transporter modulates nitrogen-determined tillering and yield formation in rice

Nitrogen (N) fertilizer application ensures crop production and food security worldwide. N-controlled boosting of shoot branching that is also referred as tillering can improve planting density for increasing grain yield of cereals. Here, we report that Sugar Transporter Protein 28 (OsSTP28) as a key regulator of N-responsive tillering and yield formation in rice. N supply inhibits the expression of OsSTP28, resulting in glucose accumulation in the apoplast of tiller buds, which in turn suppresses the expression of a transcriptional inhibitor ORYZA SATIVA HOMEOBOX 15 (OSH15) via an epigenetic mechanism to activate gibberellin 2-oxidases (GA2oxs)-facilitated gibberellin catabolism in shoot base. Thereby, OsSTP28-OSH15-GA2oxs module reduces the level of bioactive gibberellin in shoot base upon increased N supply, and consequently promotes tillering and grain yield. Moreover, we identify an elite allele of OsSTP28 that can effectively promote N-responsive tillering and yield formation, thus representing a valuable breeding target of N use efficiency improvement for agricultural sustainability.

Brassinosteroid signaling represses ZINC FINGER PROTEIN11 to regulate ovule development in Arabidopsis

Brassinosteroid (BR) signaling and the C-class MADS-box gene AGAMOUS (AG) play important roles in ovule development in Arabidopsis (Arabidopsis thaliana). However, how BR signaling integrates with AG functions to control the female reproductive process remains elusive. Here, we showed that the regulatory role of BR signaling in proper ovule development is mediated by the transcriptional repressor gene ZINC FINGER PROTEIN 11 (ZFP11), which is a direct target of AG. ZFP11 expression initiates from the placenta upon AG induction and becomes prominent in the funiculus of ovule primordia. Plants harboring zfp11 mutations showed reduced placental length with decreased ovule numbers and some aborted ovules. During ovule development, the transcription factor BRASSINAZOLE-RESISTANT 1 (BZR1), which functions downstream of BR signaling, inhibits ZFP11 expression in the chalaza and nucellus. Weakened BR signaling leads to stunted integuments in ovules, resulting from the direct repression of INNER NO OUTER (INO) and WUSCHEL (WUS) by extended ZFP11 expression in the chalaza and nucellus, respectively. In addition, the zfp11 mutant shows reduced sensitivity to BR biosynthesis inhibitors and can rescue outer integument defects in brassinosteroid insensitive 1 (bri1) mutants. Thus, the precise spatial regulation of ZFP11, which is activated by AG in the placenta and suppressed by BR signaling in the central and distal regions of ovules, is essential for ensuring sufficient ovule numbers and proper ovule formation.

Inference and prioritization of tissue-specific regulons in Arabidopsis and Oryza

A regulon refers to a group of genes regulated by a transcription factor binding to regulatory motifs to achieve specific biological functions. To infer tissue-specific gene regulons in Arabidopsis, we developed a novel pipeline named InferReg. InferReg utilizes a gene expression matrix that includes 3400 Arabidopsis transcriptomes to make initial predictions about the regulatory relationships between transcription factors (TFs) and target genes (TGs) using co-expression patterns. It further improves these anticipated interactions by integrating TF binding site enrichment analysis to eliminate false positives that are only supported by expression data. InferReg further trained a graph convolutional network with 133 transcription factors, supported by ChIP-seq, as positive samples, to learn the regulatory logic between TFs and TGs to improve the accuracy of the regulatory network. To evaluate the functionality of InferReg, we utilized it to discover tissue-specific regulons in 5 Arabidopsis tissues: flower, leaf, root, seed, and seedling. We ranked the activities of regulons for each tissue based on reliability using Borda ranking and compared them with existing databases. The results demonstrated that InferReg not only identified known tissue-specific regulons but also discovered new ones. By applying InferReg to rice expression data, we were able to identify rice tissue-specific regulons, showing that our approach can be applied more broadly. We used InferReg to successfully identify important regulons in various tissues of Arabidopsis and Oryza, which has improved our understanding of tissue-specific regulations and the roles of regulons in tissue differentiation and development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-024-00176-2.

aChIP is an efficient and sensitive ChIP-seq technique for economically important plant organs

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is crucial for profiling histone modifications and transcription factor binding throughout the genome. However, its application in economically important plant organs (EIPOs) such as seeds, fruits and flowers is challenging due to their sturdy cell walls and complex constituents. Here we present advanced ChIP (aChIP), an optimized method that efficiently isolates chromatin from plant tissues while simultaneously removing cell walls and cellular constituents. aChIP precisely profiles histone modifications in all 14 tested EIPOs and identifies transcription factor and chromatin-modifying enzyme binding sites. In addition, aChIP enhances ChIP efficiency, revealing numerous novel modified sites compared with previous methods in vegetative tissues. aChIP reveals the histone modification landscape for rapeseed dry seeds, highlighting the intricate roles of chromatin dynamics during seed dormancy and germination. Altogether, aChIP is a powerful, efficient and sensitive approach for comprehensive chromatin profiling in virtually all plant tissues, especially in EIPOs.

Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for ~15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.

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.

PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants

Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitation has resulted into underdevelopment of plant regulatory research and rampant use of Arabidopsis-like model species, generating misleading results. Here, we report a revolutionary transformers-based deep-learning approach, PTFSpot, which learns from TF structures and their binding regions' co-variability to bring a universal TF-DNA interaction model to detect TFBR with complete freedom from TF and species-specific models' limitations. During a series of extensive benchmarking studies over multiple experimentally validated data, it not only outperformed the existing software by >30% lead but also delivered consistently >90% accuracy even for those species and TF families that were never encountered during the model-building process. PTFSpot makes it possible now to accurately annotate TFBRs across any plant genome even in the total lack of any TF information, completely free from the bottlenecks of species and TF-specific models.

Nitrogen sensing and regulatory networks: it's about time and space

A plant's response to external and internal nitrogen signals/status relies on sensing and signaling mechanisms that operate across spatial and temporal dimensions. From a comprehensive systems biology perspective, this involves integrating nitrogen responses in different cell types and over long distances to ensure organ coordination in real time and yield practical applications. In this prospective review, we focus on novel aspects of nitrogen (N) sensing/signaling uncovered using temporal and spatial systems biology approaches, largely in the model Arabidopsis. The temporal aspects span: transcriptional responses to N-dose mediated by Michaelis-Menten kinetics, the role of the master NLP7 transcription factor as a nitrate sensor, its nitrate-dependent TF nuclear retention, its "hit-and-run" mode of target gene regulation, and temporal transcriptional cascade identified by "network walking." Spatial aspects of N-sensing/signaling have been uncovered in cell type-specific studies in roots and in root-to-shoot communication. We explore new approaches using single-cell sequencing data, trajectory inference, and pseudotime analysis as well as machine learning and artificial intelligence approaches. Finally, unveiling the mechanisms underlying the spatial dynamics of nitrogen sensing/signaling networks across species from model to crop could pave the way for translational studies to improve nitrogen-use efficiency in crops. Such outcomes could potentially reduce the detrimental effects of excessive fertilizer usage on groundwater pollution and greenhouse gas emissions.

Arabidopsis BBX14 is involved in high light acclimation and seedling development

The development of photosynthetically competent seedlings requires both light and retrograde biogenic signaling pathways. The transcription factor GLK1 functions at the interface between these pathways and receives input from the biogenic signal integrator GUN1. BBX14 was previously identified, together with GLK1, in a core module that mediates the response to high light (HL) levels and biogenic signals, which was studied by using inhibitors of chloroplast development. Our chromatin immunoprecipitation-Seq experiments revealed that BBX14 is a direct target of GLK1, and RNA-Seq analysis suggests that BBX14 may function as a regulator of the circadian clock. In addition, BBX14 plays a role in chlorophyll biosynthesis during early onset of light. Knockout of BBX14 results in a long hypocotyl phenotype dependent on a retrograde signal. Furthermore, the expression of BBX14 and BBX15 during biogenic signaling requires GUN1. Investigation of the role of BBX14 and BBX15 in GUN-type biogenic (gun) signaling showed that the overexpression of BBX14 or BBX15 caused de-repression of CA1 mRNA levels, when seedlings were grown on norflurazon. Notably, transcripts of the LHCB1.2 marker are not de-repressed. Furthermore, BBX14 is required to acclimate plants to HL stress. We propose that BBX14 is an integrator of biogenic signals and that BBX14 is a nuclear target of retrograde signals downstream of the GUN1/GLK1 module. However, we do not classify BBX14 or BBX15 overexpressors as gun mutants based on a critical evaluation of our results and those reported in the literature. Finally, we discuss a classification system necessary for the declaration of new gun mutants.

Systematic identification of wheat spike developmental regulators by integrated multi-omics, transcriptional network, GWAS, and genetic analyses

The spike architecture of wheat plays a crucial role in determining grain number, making it a key trait for optimization in wheat breeding programs. In this study, we used a multi-omic approach to analyze the transcriptome and epigenome profiles of the young spike at eight developmental stages, revealing coordinated changes in chromatin accessibility and H3K27me3 abundance during the flowering transition. We constructed a core transcriptional regulatory network (TRN) that drives wheat spike formation and experimentally validated a multi-layer regulatory module involving TaSPL15, TaAGLG1, and TaFUL2. By integrating the TRN with genome-wide association studies, we identified 227 transcription factors, including 42 with known functions and 185 with unknown functions. Further investigation of 61 novel transcription factors using multiple homozygous mutant lines revealed 36 transcription factors that regulate spike architecture or flowering time, such as TaMYC2-A1, TaMYB30-A1, and TaWRKY37-A1. Of particular interest, TaMYB30-A1, downstream of and repressed by WFZP, was found to regulate fertile spikelet number. Notably, the excellent haplotype of TaMYB30-A1, which contains a C allele at the WFZP binding site, was enriched during wheat breeding improvement in China, leading to improved agronomic traits. Finally, we constructed a free and open access Wheat Spike Multi-Omic Database (http://39.98.48.156:8800/#/). Our study identifies novel and high-confidence regulators and offers an effective strategy for dissecting the genetic basis of wheat spike development, with practical value for wheat breeding.

Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings. We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers. We further demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs, and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs. The analysis results are available at the single-cell-based plant lncRNA atlas database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

Application of Single-Cell Assay for Transposase-Accessible Chromatin with High Throughput Sequencing in Plant Science: Advances, Technical Challenges, and Prospects

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.

PPGR: a comprehensive perennial plant genomes and regulation database

Perennial woody plants hold vital ecological significance, distinguished by their unique traits. While significant progress has been made in their genomic and functional studies, a major challenge persists: the absence of a comprehensive reference platform for collection, integration and in-depth analysis of the vast amount of data. Here, we present PPGR (Resource for Perennial Plant Genomes and Regulation; https://ngdc.cncb.ac.cn/ppgr/) to address this critical gap, by collecting, integrating, analyzing and visualizing genomic, gene regulation and functional data of perennial plants. PPGR currently includes 60 species, 847 million protein-protein/TF (transcription factor)-target interactions, 9016 transcriptome samples under various environmental conditions and genetic backgrounds. Noteworthy is the focus on genes that regulate wood production, seasonal dormancy, terpene biosynthesis and leaf senescence representing a wealth of information derived from experimental data, literature mining, public databases and genomic predictions. Furthermore, PPGR incorporates a range of multi-omics search and analysis tools to facilitate browsing and application of these extensive datasets. PPGR represents a comprehensive and high-quality resource for perennial plants, substantiated by an illustrative case study that demonstrates its capacity in unraveling gene functions and shedding light on potential regulatory processes.

PlantPAN 4.0: updated database for identifying conserved non-coding sequences and exploring dynamic transcriptional regulation in plant promoters

PlantPAN 4.0 (http://PlantPAN.itps.ncku.edu.tw/) is an integrative resource for constructing transcriptional regulatory networks for diverse plant species. In this release, the gene annotation and promoter sequences were expanded to cover 115 species. PlantPAN 4.0 can help users characterize the evolutionary differences and similarities among cis-regulatory elements; furthermore, this system can now help in identification of conserved non-coding sequences among homologous genes. The updated transcription factor binding site repository contains 3428 nonredundant matrices for 18305 transcription factors; this expansion helps in exploration of combinational and nucleotide variants of cis-regulatory elements in conserved non-coding sequences. Additionally, the genomic landscapes of regulatory factors were manually updated, and ChIP-seq data sets derived from a single-cell green alga (Chlamydomonas reinhardtii) were added. Furthermore, the statistical review and graphical analysis components were improved to offer intelligible information through ChIP-seq data analysis. These improvements included easy-to-read experimental condition clusters, searchable gene-centered interfaces for the identification of promoter regions' binding preferences by considering experimental condition clusters and peak visualization for all regulatory factors, and the 20 most significantly enriched gene ontology functions for regulatory factors. Thus, PlantPAN 4.0 can effectively reconstruct gene regulatory networks and help compare genomic cis-regulatory elements across plant species and experiments.

Capture of regulatory factors via CRISPR-dCas9 for mechanistic analysis of fine-tuned SERRATE expression in Arabidopsis

SERRATE (SE) plays an important role in many biological processes and under biotic stress resistance. However, little about the control of SE has been clarified. Here we present a method named native chromatin-associated proteome affinity by CRISPR-dCas9 (CASPA-dCas9) to holistically capture native regulators of the SE locus. Several key regulatory factors including PHYTOCHROME RAPIDLY REGULATED 2 (PAR2), WRKY DNA-binding protein 19 (WRKY19) and the MYB-family protein 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 subsequently represses SE expression, while PAR2-MYB27 interaction inhibits both the binding of MYB27 on the SE promoter and the recruitment of SEAIR-PRC2 by MYB27. The interaction between PAR2 and MYB27 fine-tunes the SE expression level at different developmental stages. In addition, PAR2 and WRKY19 synergistically promote SE expression for pathogen resistance. Collectively, our results demonstrate an efficient method to capture key regulators of target genes and uncover the precise regulatory mechanism for SE.

IPOP: An Integrative Plant Multi-omics Platform for Cross-species Comparison and Evolutionary Study

The advent of high-throughput sequencing technologies has led to the production of a significant amount of omics data in plants, which serves as valuable assets for conducting cross-species multi-omics comparative analysis. Nevertheless, the current dearth of comprehensive platforms providing evolutionary annotation information and multi-species multi-omics data impedes users from systematically and efficiently performing evolutionary and functional analysis on specific genes. In order to establish an advanced plant multi-omics platform that provides timely, accurate, and high-caliber omics information, we collected 7 distinct types of omics data from 6 monocots, 6 dicots, and 1 moss, and reanalyzed these data using standardized pipelines. Additionally, we furnished homology information, duplication events, and phylostratigraphic stages of 13 species to facilitate evolutionary examination. Furthermore, the integrative plant omics platform (IPOP) is bundled with a variety of online analysis tools that aid users in conducting evolutionary and functional analysis. Specifically, the Multi-omics Integration Analysis tool is available to consolidate information from diverse omics sources, while the Transcriptome-wide Association Analysis tool facilitates the linkage of functional analysis with phenotype. To illustrate the application of IPOP, we conducted a case study on the YTH domain gene family, wherein we observed shared functionalities within orthologous groups and discerned variations in evolutionary patterns across these groups. To summarize, the IPOP platform offers valuable evolutionary insights and multi-omics data to the plant sciences community, effectively addressing the need for cross-species comparison and evolutionary research platforms. All data and modules within IPOP are freely accessible for academic purposes (http://omicstudio.cloud:4012/ipod/).

Integrating omics databases for enhanced crop breeding

Crop plant breeding involves selecting and developing new plant varieties with desirable traits such as increased yield, improved disease resistance, and enhanced nutritional value. With the development of high-throughput technologies, such as genomics, transcriptomics, and metabolomics, crop breeding has entered a new era. However, to effectively use these technologies, integration of multi-omics data from different databases is required. Integration of omics data provides a comprehensive understanding of the biological processes underlying plant traits and their interactions. This review highlights the importance of integrating omics databases in crop plant breeding, discusses available omics data and databases, describes integration challenges, and highlights recent developments and potential benefits. Taken together, the integration of omics databases is a critical step towards enhancing crop plant breeding and improving global food security.

Sea-ATI unravels novel vocabularies of plant active cistrome

The cistrome consists of all cis-acting regulatory elements recognized by transcription factors (TFs). However, only a portion of the cistrome is active for TF binding in a specific tissue. Resolving the active cistrome in plants remains challenging. In this study, we report the assay sequential extraction assisted-active TF identification (sea-ATI), a low-input method that profiles the DNA sequences recognized by TFs in a target tissue. We applied sea-ATI to seven plant tissues to survey their active cistrome and generated 41 motif models, including 15 new models that represent previously unidentified cis-regulatory vocabularies. ATAC-seq and RNA-seq analyses confirmed the functionality of the cis-elements from the new models, in that they are actively bound in vivo, located near the transcription start site, and influence chromatin accessibility and transcription. Furthermore, comparing dimeric WRKY CREs between sea-ATI and DAP-seq libraries revealed that thermodynamics and genetic drifts cooperatively shaped their evolution. Notably, sea-ATI can identify not only positive but also negative regulatory cis-elements, thereby providing unique insights into the functional non-coding genome of plants.

cisDynet: An integrated platform for modeling gene-regulatory dynamics and networks

Chromatin accessibility sequencing has been widely used for uncovering genetic regulatory mechanisms and inferring gene regulatory networks. However, effectively integrating large-scale chromatin accessibility datasets has posed a significant challenge. This is due to the lack of a comprehensive end-to-end solution, as many existing tools primarily emphasize data preprocessing and overlook downstream analyses. To bridge this gap, we have introduced cisDynet, a holistic solution that combines streamlined data preprocessing using Snakemake and R functions with advanced downstream analysis capabilities. cisDynet excels in conventional data analyses, encompassing peak statistics, peak annotation, differential analysis, motif enrichment analysis, and more. Additionally, it allows to perform sophisticated data exploration, such as tissue-specific peak identification, time course data modeling, integration of RNA-seq data to establish peak-to-gene associations, constructing regulatory networks, and conducting enrichment analysis of genome-wide association study (GWAS) variants. As a proof of concept, we applied cisDynet to reanalyze comprehensive ATAC-seq datasets across various tissues from the Encyclopedia of DNA Elements (ENCODE) project. The analysis successfully delineated tissue-specific open chromatin regions (OCRs), established connections between OCRs and target genes, and effectively linked these discoveries with 1861 GWAS variants. Furthermore, cisDynet was instrumental in dissecting the time course open chromatin data of mouse embryonic development, revealing the dynamic behavior of OCRs over developmental stages and identifying key transcription factors governing differentiation trajectories. In summary, cisDynet offers researchers a user-friendly solution that minimizes the need for extensive coding, ensures the reproducibility of results, and greatly simplifies the exploration of epigenomic data.

Genome-wide enhancer identification by massively parallel reporter assay in Arabidopsis

Enhancers are critical cis-regulatory elements controlling gene expression during cell development and differentiation. However, genome-wide enhancer characterization has been challenging due to the lack of a well-defined relationship between enhancers and genes. Function-based methods are the gold standard for determining the biological function of cis-regulatory elements; however, these methods have not been widely applied to plants. Here, we applied a massively parallel reporter assay on Arabidopsis to measure enhancer activities across the genome. We identified 4327 enhancers with various combinations of epigenetic modifications distinctively different from animal enhancers. Furthermore, we showed that enhancers differ from promoters in their preference for transcription factors. Although some enhancers are not conserved and overlap with transposable elements forming clusters, enhancers are generally conserved across thousand Arabidopsis accessions, suggesting they are selected under evolution pressure and could play critical roles in the regulation of important genes. Moreover, comparison analysis reveals that enhancers identified by different strategies do not overlap, suggesting these methods are complementary in nature. In sum, we systematically investigated the features of enhancers identified by functional assay in A. thaliana, which lays the foundation for further investigation into enhancers' functional mechanisms in plants.

AGAMOUS mediates timing of guard cell formation during gynoecium development

In Arabidopsis thaliana, stomata are composed of two guard cells that control the aperture of a central pore to facilitate gas exchange between the plant and its environment, which is particularly important during photosynthesis. Although leaves are the primary photosynthetic organs of flowering plants, floral organs are also photosynthetically active. In the Brassicaceae, evidence suggests that silique photosynthesis is important for optimal seed oil content. A group of transcription factors containing MADS DNA binding domains is necessary and sufficient to confer floral organ identity. Elegant models, such as the ABCE model of flower development and the floral quartet model, have been instrumental in describing the molecular mechanisms by which these floral organ identity proteins govern flower development. However, we lack a complete understanding of how the floral organ identity genes interact with the underlying leaf development program. Here, we show that the MADS domain transcription factor AGAMOUS (AG) represses stomatal development on the gynoecial valves, so that maturation of stomatal complexes coincides with fertilization. We present evidence that this regulation by AG is mediated by direct transcriptional repression of a master regulator of the stomatal lineage, MUTE, and show data that suggests this interaction is conserved among several members of the Brassicaceae. This work extends our understanding of the mechanisms underlying floral organ formation and provides a framework to decipher the mechanisms that control floral organ photosynthesis.

scPlant: A versatile framework for single-cell transcriptomic data analysis in plants

Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users. The scPlant pipeline is implemented with numerous functions for diverse analytical tasks, ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.

Promoter editing for the genetic improvement of crops

Gene expression plays a fundamental role in the regulation of agronomically important traits in crop plants. The genetic manipulation of plant promoters through genome editing has emerged as an effective strategy to create favorable traits in crops by altering the expression pattern of the pertinent genes. Promoter editing can be applied in a directed manner, where nucleotide sequences associated with favorable traits are precisely generated. Alternatively, promoter editing can also be exploited as a random mutagenic approach to generate novel genetic variations within a designated promoter, from which elite alleles are selected based on their phenotypic effects. Pioneering studies have demonstrated the potential of promoter editing in engineering agronomically important traits as well as in mining novel promoter alleles valuable for plant breeding. In this review, we provide an update on the application of promoter editing in crops for increased yield, enhanced tolerance to biotic and abiotic stresses, and improved quality. We also discuss several remaining technical bottlenecks and how this strategy may be better employed for the genetic improvement of crops in the future.

TSPTFBS 2.0: trans-species prediction of transcription factor binding sites and identification of their core motifs in plants

Introduction

An emerging approach using promoter tiling deletion via genome editing is beginning to become popular in plants. Identifying the precise positions of core motifs within plant gene promoter is of great demand but they are still largely unknown. We previously developed TSPTFBS of 265 Arabidopsis transcription factor binding sites (TFBSs) prediction models, which now cannot meet the above demand of identifying the core motif.

Methods

Here, we additionally introduced 104 maize and 20 rice TFBS datasets and utilized DenseNet for model construction on a large-scale dataset of a total of 389 plant TFs. More importantly, we combined three biological interpretability methods including DeepLIFT, in-silico tiling deletion, and in-silico mutagenesis to identify the potential core motifs of any given genomic region.

Results

For the results, DenseNet not only has achieved greater predictability than baseline methods such as LS-GKM and MEME for above 389 TFs from Arabidopsis, maize and rice, but also has greater performance on trans-species prediction of a total of 15 TFs from other six plant species. A motif analysis based on TF-MoDISco and global importance analysis (GIA) further provide the biological implication of the core motif identified by three interpretability methods. Finally, we developed a pipeline of TSPTFBS 2.0, which integrates 389 DenseNet-based models of TF binding and the above three interpretability methods.

Discussion

TSPTFBS 2.0 was implemented as a user-friendly web-server (http://www.hzau-hulab.com/TSPTFBS/), which can support important references for editing targets of any given plant promoters and it has great potentials to provide reliable editing target of genetic screen experiments in plants.

Characterization of Gene Regulatory Networks in Plants Using New Methods and Data Types

A major question in plant biology is to understand how plant growth, development, and environmental responses are controlled and coordinated by the activities of regulatory factors. Gene regulatory network (GRN) analyses require integrated approaches that combine experimental approaches with computational analyses. A wide range of experimental approaches and tools are now available, such as targeted perturbation of gene activities, quantitative and cell-type specific measurements of dynamic gene activities, and systematic analysis of the molecular 'hard-wiring' of the systems. At the computational level, different tools and databases are available to study regulatory sequences, including intuitive visualizations to explore data-driven gene regulatory networks in different plant species. Furthermore, advanced data integration approaches have recently been developed to efficiently leverage complementary regulatory data types and learn context-specific networks.

The ChIP-Hub Resource: Toward plantEncode

Recent advances in sequencing technologies lead to the generation of an enormous amount of regulome and epigenome data in a variety of plant species. However, a comprehensive standardized resource is so far not available. In this chapter, we present ChIP-Hub, an integrative platform that has been developed based on the ENCODE standards by collecting and reanalyzing regulatory genomic datasets from 41 plant species. The ChIP-hub website is introduced in this chapter, including information on detailed steps of searching, data download, and online analyses, which facilitates users to explore ChIP-Hub. We also provide a cross-species comparison of chromatin accessibility information that gives a thorough view of evolutionary regulatory networks in plants.

Epigenetic modifications: Allusive clues of lncRNA functions in plants

Long non-coding RNAs (lncRNAs) have been verified as flexible and important factors in various biological processes of multicellular eukaryotes, including plants. The respective intricate crosstalk among multiple epigenetic modifications has been examined to some extent. However, only a small proportion of lncRNAs has been functionally well characterized. Moreover, the relationship between lncRNAs and other epigenetic modifications has not been systematically studied. In this mini-review, we briefly summarize the representative biological functions of lncRNAs in developmental programs and environmental responses in plants. In addition, we particularly discuss the intimate relationship between lncRNAs and other epigenetic modifications, and we outline the underlying avenues and challenges for future research on plant lncRNAs.

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

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

Integration of multi-omics technologies for crop improvement: Status and prospects

With the rapid development of next-generation sequencing (NGS), multi-omics techniques have been emerging as effective approaches for crop improvement. Here, we focus mainly on addressing the current status and future perspectives toward omics-related technologies and bioinformatic resources with potential applications in crop breeding. Using a large amount of omics-level data from the functional genome, transcriptome, proteome, epigenome, metabolome, and microbiome, clarifying the interaction between gene and phenotype formation will become possible. The integration of multi-omics datasets with pan-omics platforms and systems biology could predict the complex traits of crops and elucidate the regulatory networks for genetic improvement. Different scales of trait predictions and decision-making models will facilitate crop breeding more intelligent. Potential challenges that integrate the multi-omics data with studies of gene function and their network to efficiently select desirable agronomic traits are discussed by proposing some cutting-edge breeding strategies for crop improvement. Multi-omics-integrated approaches together with other artificial intelligence techniques will contribute to broadening and deepening our knowledge of crop precision breeding, resulting in speeding up the breeding process.

CisCross: A gene list enrichment analysis to predict upstream regulators in Arabidopsis thaliana

Having DNA-binding profiles for a sufficient number of genome-encoded transcription factors (TFs) opens up the perspectives for systematic evaluation of the upstream regulators for the gene lists. Plant Cistrome database, a large collection of TF binding profiles detected using the DAP-seq method, made it possible for Arabidopsis. Here we re-processed raw DAP-seq data with MACS2, the most popular peak caller that leads among other ones according to quality metrics. In the benchmarking study, we confirmed that the improved collection of TF binding profiles supported a more precise gene list enrichment procedure, and resulted in a more relevant ranking of potential upstream regulators. Moreover, we consistently recovered the TF binding profiles that were missing in the previous collection of DAP-seq peak sets. We developed the CisCross web service (https://plamorph.sysbio.ru/ciscross/) that gives more flexibility in the analysis of potential upstream TF regulators for Arabidopsis thaliana genes.

Comparative transcriptomics identifies candidate genes involved in the evolutionary transition from dehiscent to indehiscent fruits in Lepidium (Brassicaceae)

BACKGROUND

Fruits are the seed-bearing structures of flowering plants and are highly diverse in terms of morphology, texture and maturation. Dehiscent fruits split open upon maturation to discharge their seeds while indehiscent fruits are dispersed as a whole. Indehiscent fruits evolved from dehiscent fruits several times independently in the crucifer family (Brassicaceae). The fruits of Lepidium appelianum, for example, are indehiscent while the fruits of the closely related L. campestre are dehiscent. Here, we investigate the molecular and genetic mechanisms underlying the evolutionary transition from dehiscent to indehiscent fruits using these two Lepidium species as model system.

RESULTS

We have sequenced the transcriptomes and small RNAs of floral buds, flowers and fruits of L. appelianum and L. campestre and analyzed differentially expressed genes (DEGs) and differently differentially expressed genes (DDEGs). DEGs are genes that show significantly different transcript levels in the same structures (buds, flowers and fruits) in different species, or in different structures in the same species. DDEGs are genes for which the change in expression level between two structures is significantly different in one species than in the other. Comparing the two species, the highest number of DEGs was found in flowers, followed by fruits and floral buds while the highest number of DDEGs was found in fruits versus flowers followed by flowers versus floral buds. Several gene ontology terms related to cell wall synthesis and degradation were overrepresented in different sets of DEGs highlighting the importance of these processes for fruit opening. Furthermore, the fruit valve identity genes FRUITFULL and YABBY3 were among the DEGs identified. Finally, the microRNA miR166 as well as the TCP transcription factors BRANCHED1 (BRC1) and TCP FAMILY TRANSCRIPTION FACTOR 4 (TCP4) were found to be DDEGs.

CONCLUSIONS

Our study reveals differences in gene expression between dehiscent and indehiscent fruits and uncovers miR166, BRC1 and TCP4 as candidate genes for the evolutionary transition from dehiscent to indehiscent fruits in Lepidium.

The evolutionary landscape and expression pattern of plant lincRNAs

Long intergenic non-coding RNAs (lincRNAs) are important regulators of cellular processes, including development and stress response. Many lincRNAs have been bioinformatically identified in plants, but their evolutionary dynamics and expression characteristics are still elusive. Here, we systematically identified thousands of lincRNAs in 26 plant species, including 6 non-flowering plants, investigated the conservation of the identified lincRNAs in different levels of plant lineages based on sequence and/or synteny homology and explored characteristics of the conserved lincRNAs during plant evolution and their co-expression relationship with protein-coding genes (PCGs). In addition to confirmation of the features well documented in literature for lincRNAs, such as species-specific, fewer exons, tissue-specific expression patterns and less abundantly expressed, we revealed that histone modification signals and/or binding sites of transcription factors were enriched in the conserved lincRNAs, implying their biological functionalities, as demonstrated by identifying conserved lincRNAs related to flower development in both the Brassicaceae and grass families and ancient lincRNAs potentially functioning in meristem development of non-flowering plants. Compared to PCGs, lincRNAs are more likely to be associated with transposable elements (TEs), but with different characteristics in different evolutionary lineages, for instance, the types of TEs and the variable level of association in lincRNAs with different conservativeness. Together, these results provide a comprehensive view on the evolutionary landscape of plant lincRNAs and shed new insights on the conservation and functionality of plant lincRNAs.