Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

Involvement of MicroRNAs in the Hypersensitive Response of Capsicum Plants to the Capsicum Chlorosis Virus at Elevated Temperatures

The orthotospovirus capsicum chlorosis virus (CaCV) is an important pathogen affecting capsicum plants. Elevated temperatures may affect disease progression and pose a potential challenge to capsicum production. To date, CaCV-resistant capsicum breeding lines have been established; however, the impact of an elevated temperature of 35 °C on this genetic resistance remains unexplored. Thus, this study aimed to investigate how high temperature (HT) influences the response of CaCV-resistant capsicum to the virus. Phenotypic analysis revealed a compromised resistance in capsicum plants grown at HT, with systemic necrotic spots appearing in 8 out of 14 CaCV-infected plants. Molecular analysis through next-generation sequencing identified 105 known and 83 novel microRNAs (miRNAs) in CaCV-resistant capsicum plants. Gene ontology revealed that phenylpropanoid and lignin metabolic processes, regulated by Can-miR408a and Can- miR397, are likely involved in elevated-temperature-mediated resistance-breaking responses. Additionally, real-time PCR validated an upregulation of Can-miR408a and Can-miR397 by CaCV infection at HT; however, only the Laccase 4 transcript, targeted by Can-miR397, showed a tendency of negative correlation with this miRNA. Overall, this study provides the first molecular insights into how elevated temperature affects CaCV resistance in capsicum plants and reveals the potential role of miRNA in temperature-sensitive tospovirus resistance.

Forefronts and hotspots evolution of the nanomaterial application in anti-tumor immunotherapy: a scientometric analysis

BACKGROUND

Tumor immunotherapy can not only eliminate the primary lesion, but also produce long-term immune memory, effectively inhibiting tumor metastasis and recurrence. However, immunotherapy also showed plenty of limitations in clinical practice. In recent years, the combination of nanomaterials and immunotherapy has brought new light for completely eliminating tumors with its fabulous anti-tumor effects and negligible side effects.

METHODS

The Core Collection of Web of Science (WOSCC) was used to retrieve and obtain relevant literatures on antitumor nano-immunotherapy since the establishment of the WOSCC. Bibliometrix, VOSviewer, CiteSpace, GraphPad Prism, and Excel were adopted to perform statistical analysis and visualization. The annual output, active institutions, core journals, main authors, keywords, major countries, key documents, and impact factor of the included journals were evaluated.

RESULTS

A total of 443 related studies were enrolled from 2004 to 2022, and the annual growth rate of articles reached an astonishing 16.85%. The leading countries in terms of number of publications were China and the United States. Journal of Controlled Release, Biomaterials, Acta Biomaterialia, Theranostics, Advanced Materials, and ACS Nano were core journals publishing high-quality literature on the latest advances in the field. Articles focused on dendritic cells and drug delivery accounted for a large percentage in this field. Key words such as regulatory T cells, tumor microenvironment, immune checkpoint blockade, drug delivery, photodynamic therapy, photothermal therapy, tumor-associated macrophages were among the hottest themes with high maturity. Dendritic cells, vaccine, and T cells tend to become the popular and emerging research topics in the future.

CONCLUSIONS

The combined treatment of nanomaterials and antitumor immunotherapy, namely antitumor nano-immunotherapy has been paid increasing attention. Antitumor nano-immunotherapy is undergoing a transition from simple to complex, from phenotype to mechanism.

GERDH: an interactive multi-omics database for cross-species data mining in horticultural crops

Horticultural plants contribute immensely to the quality of human's life. The rapid development of omics studies on horticultural plants has resulted in large volumes of valuable growth- and development-related data. Genes that are essential for growth and development are highly conserved in evolution. Cross-species data mining reduces the impact of species heterogeneity and has been extensively used for conserved gene identification. Owing to the lack of a comprehensive database for cross-species data mining using multi-omics data from all horticultural plant species, the current resources in this field are far from satisfactory. Here, we introduce GERDH (https://dphdatabase.com), a database platform for cross-species data mining among horticultural plants, based on 12 961 uniformly processed publicly available omics libraries from more than 150 horticultural plant accessions, including fruits, vegetables and ornamental plants. Important and conserved genes that are essential for a specific biological process can be obtained by cross-species analysis module with interactive web-based data analysis and visualization. Moreover, GERDH is equipped with seven online analysis tools, including gene expression, in-species analysis, epigenetic regulation, gene co-expression, enrichment/pathway and phylogenetic analysis. By interactive cross-species analysis, we identified key genes contributing to postharvest storage. By gene expression analysis, we explored new functions of CmEIN3 in flower development, which was validated by transgenic chrysanthemum analysis. We believe that GERDH will be a useful resource for key gene identification and will allow for omics big data to be more available and accessible to horticultural plant community members.

The Multiverse of Plant Small RNAs: How Can We Explore It?

Plant small RNAs (sRNAs) are a heterogeneous group of noncoding RNAs with a length of 20–24 nucleotides that are widely studied due to their importance as major regulators in various biological processes. sRNAs are divided into two main classes—microRNAs (miRNAs) and small interfering RNAs (siRNAs)—which differ in their biogenesis and functional pathways. Their identification and enrichment with new structural variants would not be possible without the use of various high-throughput sequencing (NGS) techniques, allowing for the detection of the total population of sRNAs in plants. Classifying sRNAs and predicting their functional role based on such high-performance datasets is a nontrivial bioinformatics task, as plants can generate millions of sRNAs from a variety of biosynthetic pathways. Over the years, many computing tools have been developed to meet this challenge. Here, we review more than 35 tools developed specifically for plant sRNAs over the past few years and explore some of their basic algorithms for performing tasks related to predicting, identifying, categorizing, and quantifying individual sRNAs in plant samples, as well as visualizing the results of these analyzes. We believe that this review will be practical for biologists who want to analyze their plant sRNA datasets but are overwhelmed by the number of tools available, thus answering the basic question of how to choose the right one for a particular study.

MicroRNA-mediated bioengineering for climate-resilience in crops

Global projections on the climate change and the dynamic environmental perturbations indicate severe impacts on food security in general, and crop yield, vigor and the quality of produce in particular. Sessile plants respond to environmental challenges such as salt, drought, temperature, heavy metals at transcriptional and/or post-transcriptional levels through the stress-regulated network of pathways including transcription factors, proteins and the small non-coding endogenous RNAs. Amongs these, the miRNAs have gained unprecedented attention in recent years as key regulators for modulating gene expression in plants under stress. Hence, tailoring of miRNAs and their target pathways presents a promising strategy for developing multiple stress-tolerant crops. Plant stress tolerance has been successfully achieved through the over expression of microRNAs such as Os-miR408, Hv-miR82 for drought tolerance; OsmiR535A and artificial DST miRNA for salinity tolerance; and OsmiR535 and miR156 for combined drought and salt stress. Examples of miR408 overexpression also showed improved efficiency of irradiation utilization and carbon dioxide fixation in crop plants. Through this review, we present the current understanding about plant miRNAs, their roles in plant growth and stress-responses, the modern toolbox for identification, characterization and validation of miRNAs and their target genes including in silico tools, machine learning and artificial intelligence. Various approaches for up-regulation or knock-out of miRNAs have been discussed. The main emphasis has been given to the exploration of miRNAs for development of bioengineered climate-smart crops that can withstand changing climates and stressful environments, including combination of stresses, with very less or no yield penalties.