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At least 19 recordsLinked to original sources
PubMed2026

Risk governance of transgenic plants: bridging science, policy, and public trust.

Transgenic plants and genome editing technologies are revolutionizing agriculture through sustainable approaches to food security, pest management, and adaptation to climate change; but their widespread use is hampered by regulatory systems that are fragmented, ethics considerations, and an ongoing lack of trust from the general public. In contrast to other literature that evaluates regulation processes and public acceptance separately, our review paper introduces a new, holistic approach that includes both technical risk assessment from a scientific perspective, and Codex Alimentarius and OECD standards, and the socio-legal and judicial environment of how the national policy decisions are actually made. The paper provides a comparative, historical analysis of the key difference between product- and process-based risk governance in the USA, the EU, and India. Through the use of case studies with global significance like MON810 maize, Bt Brinjal, and the April 2024 Philippine Court of Appeals' order for cease-and-desist of Golden Rice, we discuss the increasing tension between administrative scientific approvals and precautionary judicial orders. We further explore the emerging exemptions to regulation of Site-Directed Nuclease (SDN-1 and SDN-2) genome edited crops which led to India's revolutionary 2025 commercialization of climate-resilient rice crops. Our review ends with a forward-looking approach to biotechnology regulation policy, making an appeal to shift from static historical dichotomies towards flexible risk-proportionate and internationally coordinated regulatory systems. Finally, we show that global success of agricultural biotechnology is not just about safety verification, but rather about establishment of transparent and communicable institutions that can transform scientific risk assessments into legitimate risk management decisions.

Plants, Genetically Modified↗
PubMed2026

DeepMASS v.2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites.

Determining the structures of unknown metabolites remains a fundamental bottleneck in plant metabolomics, as the vast chemical diversity of plant secondary metabolites far exceeds the coverage of existing spectral libraries. Here, we present DeepMASS v.2, a substantially enhanced platform for annotating unknown metabolites from liquid chromatography-tandem mass spectrometry data, designed to address this challenge at scale. DeepMASS v.2 leverages a semantic spectral representation model trained on millions of spectra from GNPS, NIST, and in-house resources. By integrating Spec2Vec-based embeddings with HNSW (hierarchical navigable small world) graph retrieval and a unified chemical space defined by molecular fingerprints, DeepMASS v.2 identifies structurally related neighbors of unknown spectra and ranks candidate structures according to their proximity to the predicted structural neighborhoods within chemical space. Benchmarking against Critical Assessment of Small Molecule Identification datasets and a curated natural product collection demonstrated that DeepMASS v.2 outperforms state-of-the-art in silico annotation tools, including SIRIUS, CFM-ID, MetFrag, and MS-Finder. Importantly, DeepMASS v.2 maintains strong performance for metabolites absent from spectral libraries, highlighting its capacity to annotate genuinely unknown compounds. Application of DeepMASS v.2 to large-scale plant metabolomics datasets demonstrated its ability to expand accessible metabolome coverage. Implemented as an intuitive web platform, DeepMASS v.2 provides the community with a scalable, interpretable, and high-throughput solution for structural annotation, enabling more comprehensive characterization of plant chemical diversity and accelerating natural product discovery in molecular plant science. The DeepMASS v.2 web server is publicly available at http://deepmass.cn.

Metabolomics↗
PubMed2026

Have we entered a 'post-model' era in plant biology?

Models such as arabidopsis (Arabidopsis thaliana) have underpinned genomic and physiological research in plant science. Advances in genome sequencing, pangenomics, and genome editing have prompted claims of a 'post-model' era, with model-crops and crops such as rice and bread wheat combining agricultural relevance with experimental tractability. We argue that the 'simplicity-to-complexity' approach remains valid, although model systems have evolved. Arabidopsis remains indispensable for interpreting multi-omics data, testing developmental hypotheses, and generating mechanistic insights difficult to obtain in crops. Linking these strengths to model-crops adds translational value by bridging discovery and breeding, while niche models such as Brachypodium distachyon and legumes address grass cell wall biology and nitrogen fixation. Future progress depends on diverse species with complementary strengths across fundamental and applied plant biology.

arabidopsis↗
PubMed2025

A melon (Cucumis melo) homologue of REPRESSOR OF PHOTOSYNTHETIC GENES prevents chloroplast differentiation in the fruit flesh.

Fruit flesh color in melon can be orange, green or white, depending on the accumulation of the orange carotenoid β-carotene or / and green chlorophylls. The dominant allele of Green flesh (Gf) causes orange melons, but in the absence of this allele the flesh of ripe melon can be white or green depending on the White flesh (Wf) locus, being white dominant over green. The identity of Wf has remained unclear despite several candidates have been proposed. Here we identified Wf by fine mapping of a segregating population derived from the white-fleshed variety Piel de Sapo (PS, gf gf / Wf Wf) and the orange-fleshed Védrantais (VED, Gf Gf / wf wf). Wf corresponds to the gene MELO3C003098, herein referred to as CmRPGE1 as it encodes a fruit-specific homologue of REPRESSOR OF PHOTOSYNTHETIC GENES (RPGE) microproteins. Similar to RPGE homologues from other plants, overexpression of the PS allele (CmRPGE1 PS ) caused a pale green leaf phenotype in Nicotiana benthamiana and Arabidopsis thaliana. By contrast, a 10-nucleotide deletion in the VED allele (CmRPGE1 VED ) resulted in a loss of RPGE function. The active CmRPGE1PS microprotein interacts with a fruit-localized melon homologue of ARABIDOPSIS PSEUDO-RESPONSE REGULATOR2 (APRR2), a GARP family transcription factor. Binding of CmRPGE1PS retains the melon APRR2 homologue in the cytosol, hence preventing the regulation of target genes involved in chloroplast biogenesis. In green fruit cultivars, the non-functional CmRPGE1VED allele allows APRR2 to perform its function, leading to chloroplast development and consequently a green flesh phenotype.

Biological Sciences – Plant Biology↗
PubMed2026

Protocol to predict gene expression from transcriptomic data using PREDICT.

Linking DNA sequence variation to context-specific transcriptional programs is a critical challenge in regulatory genomics, especially for non-model organisms. Here, we present PREDICT, a modular Python package for discovering cis-regulatory elements and transcription factor binding motifs. We describe steps to identify enriched k-mers from differentially expressed genes, map them to known motifs, quantify their impact on gene expression, and visualize motif co-occurrences. PREDICT provides a robust, k-mer-based approach to uncover regulatory logic in diverse genomic systems. For complete details on the use and execution of this protocol, please refer to Yen et al. and Liu et al.1,2.

Gene Expression Profiling↗
PubMed2026

Protocol to improve isoform-level quantification of low-abundance transcripts via STALARD pre-amplification.

STALARD (selective target amplification for low-abundance RNA detection) enables isoform-level quantification of low-abundance RNAs using conventional laboratory equipment. Here, we describe steps for RNA isolation, primer design, reverse transcription, selective target amplification, and downstream analysis. The protocol couples selective pre-amplification with a quantitative reverse-transcription PCR (RT-qPCR) readout and optional nanopore sequencing. Using 1 μg input RNA and 12 pre-amplification cycles, STALARD reduces Cq values by approximately 10-12 cycles, bringing the target into a reliably quantifiable range. For complete details on the use and execution of this protocol, please refer to Jeong et al.1.

Gene Expression↗
PubMed2026

Sechium edule: Phytochemistry, Biological Activities, Potential Health Effects, Food-Industry Applications, and Future Perspectives.

Sechium edule (Jacq.) Sw. (chayote), a neglected and underutilized Cucurbitaceae crop widely cultivated across tropical and subtropical regions, has drawn growing interest as a source of health-promoting food components. This review critically synthesizes studies published between 2000 and 2026 on its botanical features, genome characterization, nutritional value, phytochemistry, bioactivities, safety, and food-industry applications, based on literature retrieved from PubMed, Scopus, Web of Science, ScienceDirect, and the Cochrane Library. Different plant parts (fruits, leaves, seeds, tuberous roots, and peels) contain diverse bioactive compounds, including flavonoids, phenolic acids, cucurbitacins, pectin polysaccharides, and carotenoids. Reported bioactivities include antioxidant, anti-inflammatory, hypoglycemic, cardioprotective, antiproliferative, and geroprotective effects, mediated in part through Nrf2-mediated antioxidant signaling and sirtuin (SIRT1/3/5/6) upregulation. Notably, a systematic meta-analysis demonstrated a significant reduction in serum glucose (MD = -20.56; 95% CI: -29.35 to -11.77) and HbA1c following three months of chayote intake in patients with metabolic syndrome and type 2 diabetes. Industrially, chayote has been developed into fermented products, starch- and peel-derived bioactive films, ultrasound-extracted pectin, α-amylase inhibitory seed protein isolates, and probiotic encapsulation systems. Recent genomic work has further revealed a chromosome-level genome assembly, whole-genome duplication events, and a domestication history tracing to Mexico's Oaxaca region. Collectively, this evidence positions chayote as a promising underutilized resource for food, nutraceutical, and biomedical use, while highlighting key gaps: the need for standardized clinical trials, bioavailability studies, and comprehensive safety evaluation.

Sechium edule↗
PubMedDate not supplied

Engineering control technology in polyvinyl chloride polymerization plants.

The National Institute for Occupational Safety and Health, Division of Physical Sciences and Engineering has initiated a research program in control technology. The objective of this program is to facilitate the implementation of effective preventative measures in order to prevent occupational illness. The plastics and resins industry control technology assessment has recently been completed. The objectives of this study were to document and evaluate effective control technology for plastics and resins polymerization plants. Particular emphasis was given to PVC polymerization processes, since the relatively recent lowering in the personal exposure limit for vinyl chloride monomer (VCM) to an 8-hour 1-ppm time-weighted average has required the application of state-of-the-art controls. The present paper contains a summary of the control technology that was found to be effective in controlling VCM in processes manufacturing PVC by suspension, bulk, and dispersion polymerization. Controls necessary for VCM include process and equipment modification, isolation, local and general ventilation, work practices, personal protective equipment, workplace monitoring systems, employee/employer education, and on-going effort by both workers and management. All of these components must function together as an integrated coordinated system in order to assure worker protection under normal operating conditions or under conditions of process upset or maintenance.

Chemical Industry↗