EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways

Genome-wide expression analysis of vegetative organs during developmental and herbicide-induced whole plant senescence in Arabidopsis thaliana

BACKGROUND

Whole plant senescence represents the final stage in the life cycle of annual plants, characterized by the decomposition of aging organs and transfer of nutrients to seeds, thereby ensuring the survival of next generation. However, the transcriptomic profile of vegetative organs during this death process remains to be fully elucidated, especially regarding the distinctions between natural programmed death and artificial sudden death induced by herbicide.

RESULTS

Differential genes expression analysis using RNA-seq in leaves and roots of Arabidopsis thaliana revealed that natural senescence commenced in leaves at 45-52 days after planting, followed by roots initiated at 52-60 days. Additionally, both organs exhibited similarities with artificially induced senescence by glyphosate. Transcription factors Rap2.6L and WKRY75 appeared to serve as central mediators of regulatory changes during natural senescence, as indicated by co-expression networks. Furthermore, the upregulation of RRTF1, exclusively observed during natural death, suggested its role as a regulator of jasmonic acid and reactive oxygen species (ROS) responses, potentially triggering nitrogen recycling in leaves, such as the glutamate dehydrogenase (GDH) shunt. Root senescence was characterized by the activation of AMT2;1 and GLN1;3, facilitating ammonium availability for root-to-shoot translocation, likely under the regulation of PDF2.1.

CONCLUSIONS

Our study offers valuable insights into the transcriptomic interplay between phytohormones and ROS during whole plant senescence. We observed distinct regulatory networks governing nitrogen utilization in leaf and root senescence processes. Furthermore, the efficient allocation of energy from vegetative organs to seeds emerges as a critical determinant of population sustainability of annual Arabidopsis.

Conserved plant transcriptional responses to microgravity from two consecutive spaceflight experiments

Introduction

Understanding how plants adapt to the space environment is essential, as plants will be a valuable component of long duration space missions. Several spaceflight experiments have focused on transcriptional profiling as a means of understanding plant adaptation to microgravity. However, there is limited overlap between results from different experiments. Differences in experimental conditions and hardware make it difficult to find a consistent response across experiments and to distinguish the primary effects of microgravity from other spaceflight effects.

Methods

Plant Signaling (PS) and Plant RNA Regulation (PRR) were two separate spaceflight experiments conducted on the International Space Station utilizing the European Modular Cultivation System (EMCS). The EMCS provided a lighted environment for plant growth with centrifugal capabilities providing an onboard 1 g control.

Results and discussion

An RNA-Seq analysis of shoot samples from PS and PRR revealed a significant overlap of genes differentially expressed in microgravity between the two experiments. Relative to onboard 1 g controls, genes involved in transcriptional regulation, shoot development, and response to auxin and light were upregulated in microgravity in both experiments. Conversely, genes involved in defense response, abiotic stress, Ca++ signaling, and cell wall modification were commonly downregulated in both datasets. The downregulation of stress responses in microgravity in these two experiments is interesting as these pathways have been previously observed as upregulated in spaceflight compared to ground controls. Similarly, we have observed many stress response genes to be upregulated in the 1 g onboard control compared to ground reference controls; however these genes were specifically downregulated in microgravity. In addition, we analyzed the sRNA landscape of the 1 g and microgravity (μ g) shoot samples from PRR. We identified three miRNAs (miR319c, miR398b, and miR8683) which were upregulated in microgravity, while several of their corresponding target genes were found to be downregulated in microgravity. Interestingly, the downregulated target genes are enriched in those encoding chloroplast-localized enzymes and proteins. These results uncover microgravity unique transcriptional changes and highlight the validity and importance of an onboard 1 g control.

Nitrate-responsive transcriptome analysis of rice RGA1 mutant reveals the role of G-protein alpha subunit in negative regulation of nitrogen-sensitivity and use efficiency

KEY MESSAGE

Nitrate-responsive transcriptomic, phenotypic and physiological analyses of rice RGA1 mutant revealed many novel RGA1-regulated genes/processes/traits related to nitrogen use efficiency, and provided robust genetic evidence of RGA1-regulation of NUE. Nitrogen (N) use efficiency (NUE) is important for sustainable agriculture. G-protein signalling was implicated in N-response/NUE in rice, but needed firm genetic characterization of the role of alpha subunit (RGA1). The knock-out mutant of RGA1 in japonica rice exhibited lesser nitrate-dose sensitivity than the wild type (WT), in yield and NUE. We, therefore, investigated its genomewide nitrate-response relative to WT. It revealed 3416 differentially expressed genes (DEGs), including 719 associated with development, grain yield and phenotypic traits for NUE. The upregulated DEGs were related to photosynthesis, chlorophyll, tetrapyrrole and porphyrin biosynthesis, while the downregulated DEGs belonged to cellular protein metabolism and transport, small GTPase signalling, cell redox homeostasis, etc. We validated 26 nitrate-responsive DEGs across functional categories by RT-qPCR. Physiological validation of nitrate-response in the mutant and the WT at 1.5 and 15 mM doses revealed higher chlorophyll and stomatal length but decreased stomatal density, conductance and transpiration. The consequent increase in photosynthesis and water use efficiency may have contributed to better yield and NUE in the mutant, whereas the WT was N-dose sensitive. The mutant was not as N-dose-responsive as the WT in shoot/root growth, productive tillers and heading date, but equally responsive as WT in total N and protein content. The RGA1 mutant was less impacted by higher N-dose or salt stress in terms of yield, protein content, photosynthetic performance, relative water content, water use efficiency and catalase activity. PPI network analyses revealed known NUE-related proteins as RGA1 interactors. Therefore, RGA1 negatively regulates N-dose sensitivity and NUE in rice.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

Tomato POLLEN DEFICIENT 2 encodes a G-type lectin receptor kinase required for viable pollen grain formation

Pollen development is a crucial biological process indispensable for seed set in flowering plants and for successful crop breeding. However, little is known about the molecular mechanisms regulating pollen development in crop species. This study reports a novel male-sterile tomato mutant, pollen deficient 2 (pod2), characterized by the production of non-viable pollen grains and resulting in the development of small parthenocarpic fruits. A combined strategy of mapping-by-sequencing and RNA interference-mediated gene silencing was used to prove that the pod2 phenotype is caused by the loss of Solanum lycopersicum G-type lectin receptor kinase II.9 (SlG-LecRK-II.9) activity. In situ hybridization of floral buds showed that POD2/SlG-LecRK-II.9 is specifically expressed in tapetal cells and microspores at the late tetrad stage. Accordingly, abnormalities in meiosis and tapetum programmed cell death in pod2 occurred during microsporogenesis, resulting in the formation of four dysfunctional microspores leading to an aberrant microgametogenesis process. RNA-seq analyses supported the existence of alterations at the final stage of microsporogenesis, since we found tomato deregulated genes whose counterparts in Arabidopsis are essential for the normal progression of male meiosis and cytokinesis. Collectively, our results revealed the essential role of POD2/SlG-LecRK-II.9 in regulating tomato pollen development.

Mysteries of gene regulation: Promoters are not the sole triggers of gene expression

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TF binding peaks were widely distributed in nonpromoters, especially downstream regions of transcription termination sites.

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Exons of non-coding regions were the prominent regions of TF binding.

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TAD boundaries were colocalized with activating histone marks and TF binding.

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Genes with distinct functions demonstrated substantially different behaviors in cis-regulation and epigenetic signatures.

Cis-regulatory elements of promoters are essential for gene regulation by transcription factors (TFs). However, the regulatory roles of nonpromoter regions, TFs, and epigenetic marks remain poorly understood in plants. In this study, we characterized the cis-regulatory regions of 53 TFs and 19 histone marks in 328 chromatin immunoprecipitation (ChIP-seq) datasets from Arabidopsis. The genome-wide maps indicated that both promoters and regions around the transcription termination sites of protein-coding genes recruit the most TFs. The maps also revealed a diverse of histone combinations. The analysis suggested that exons play critical roles in the regulation of non-coding genes. Additionally, comparative analysis between heat-stress-responsive and nonresponsive genes indicated that the genes with distinct functions also exhibited substantial differences in cis-regulatory regions, histone regulation, and topologically associating domain (TAD) boundary organization. By integrating multiple high-throughput sequencing datasets, this study generated regulatory models for protein-coding genes, non-coding genes, and TAD boundaries to explain the complexity of transcriptional regulation.

Approaches in Gene Coexpression Analysis in Eukaryotes

Simple Summary

Genes whose expression levels rise and fall similarly in a large set of samples, may be considered coexpressed. Gene coexpression analysis refers to the en masse discovery of coexpressed genes from a large variety of transcriptomic experiments. The type of biological networks that studies gene coexpression, known as Gene Coexpression Networks, consist of an undirected graph depicting genes and their coexpression relationships. Coexpressed genes are clustered in smaller subnetworks, the predominant biological roles of which can be determined through enrichment analysis. By studying well-annotated gene partners, the attribution of new roles to genes of unknown function or assumption for participation in common metabolic pathways can be achieved, through a guilt-by-association approach. In this review, we present key issues in gene coexpression analysis, as well as the most popular tools that perform it.

Abstract

Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied extensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensible account of the steps required for performing a complete gene coexpression analysis in eukaryotic organisms. We comment on the use of RNA-Seq vs. microarrays, as well as the best practices for GCN construction. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.

Evolution of 14-3-3 Proteins in Angiosperm Plants: Recurring Gene Duplication and Loss

14-3-3 proteins are key regulatory factors in plants and are involved in a broad range of physiological processes. We addressed the evolutionary history of 14-3-3s from 46 angiosperm species, including basal angiosperm Amborella and major lineage of monocotyledons and eudicotyledons. Orthologs of Arabidopsis isoforms were detected. There were several rounds of duplication events in the evolutionary history of the 14-3-3 protein family in plants. At least four subfamilies (iota, epsilon, kappa, and psi) formed as a result of ancient duplication in a common ancestor of angiosperm plants. Recent duplication events followed by gene loss in plant lineage, among others Brassicaceae, Fabaceae, and Poaceae, further shaped the high diversity of 14-3-3 isoforms in plants. Coexpression data showed that 14-3-3 proteins formed different functional groups in different species. In some species, evolutionarily related groups of 14-3-3 proteins had coexpressed together under certain physiological conditions, whereas in other species, closely related isoforms expressed in the opposite manner. A possible explanation is that gene duplication and loss is accompanied by functional plasticity of 14-3-3 proteins.

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

While bacteria can be beneficial to our health, their deadly pathogenic potential has been an ever-present concern exacerbated by the emergence of drug-resistant strains. As such, there is a pressing urgency for an enhanced understanding of their gene function and regulation, which could mediate the development of novel antimicrobials. Transcriptomic analyses have been established as insightful and indispensable to the functional characterization of genes and identification of new biological pathways, but in the context of bacterial studies, they remain limited to species-specific datasets. To address this, we integrated the genomic and transcriptomic data of the 17 most notorious and researched bacterial pathogens, creating bacteria.guru, an interactive database that can identify, visualize, and compare gene expression profiles, coexpression networks, functionally enriched clusters, and gene families across species. Through illustrating antibiotic resistance mechanisms in P. aeruginosa, we demonstrate that bacteria.guru could potentially aid in discovering multi-faceted antibiotic targets and, overall, facilitate future bacterial research. AVAILABILITY: The database and coexpression networks are freely available from https://bacteria.guru/. Sample annotations can be found in the supplemental data.