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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↗
PubMed1993

A cytometric exercise in plant DNA histograms, with 2C values for 70 species.

An introduction is given to the literature concerning methods and objectives for cytometric DNA analysis of plant nuclei. This area has gained relevance with applications in plant breeding and seed production industries, where laboratories unfamiliar with cytometry are adopting the method. An extensive graphical guide to interpreting DNA histograms and their problems is given. Conversely, cytometry laboratories unfamiliar with plant sciences will find herein a guide, and references, to adapt their methods to plant material. A table of 2C values reassessed by flow cytometry for 70 plant species, plus the genome composition (GC%) in many instances, is also included.

Cell Cycle↗
PubMed1989

Cytochemical localization of beta-(1----4)-D-glucans in plant and fungal cells using an exoglucanase-gold complex.

An exoglucanase (exo-1,4-beta-glucanase), purified from a cellulase produced by the fungus Trichoderma harzianum, was tagged with colloidal gold particles and applied on plant and fungal tissue sections for localizing beta-(1----4)-linked glucans. The present review reports the conditions required for the preparation of this enzyme-gold complex and for its application in transmission electron microscopy. The exoglucanase-gold complex was found to be a powerful probe for labelling accurately cellulosic glucans in tissues processed under conventional procedures. This approach represents a promising alternative to previous methods such as autoradiography or subtractive cytochemistry in the study of wall topochemistry. It will undoubtedly acquire increasing applicability and relevance in various fields of plant science including physiology and pathology.

Carbohydrate Sequence↗
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↗
PubMed1993

Commercialization of genetically engineered crops.

More abundant harvests from insect- and disease-resistant crops, vine-ripened tomatoes, or less oily potato chips or french fries are some of the benefits that will result from single gene improvements under development today. These single gene traits will be combined with the best new varieties produced by traditional plant breeding and will accelerate the pace and the scope of our ability to develop even better and more productive crops in the future. The initial group of genetic improvements were first field tested in 1987, improved upon over the past 6 years, and are finally approaching the first commercial sales over the next 3 to 4 years. The key hurdles from discovery of a promising lead to a commercial product trait include: (i) gene cloning and expression; (ii) product development; (iii) field testing; (iv) breeding into multiple elite varieties; (v) product characterization and regulatory review; (vi) public acceptance; and (vii) marketing. The expense and risk to bring transformed crops to market successfully is significantly higher than for traditionally developed new varieties. The high value of some single gene targets and the possibility for patent protection of the processes and final products provide the incentive for private investment in this area. The value to farmers, consumers, the environment and society in general is very high because the problems being solved are those that have resisted previous attempts through conventional means. Public investment in basic plant science research and private investment in product development is a powerful combination for continual improvement in lowering the cost and improving the quality of the world's food supply.

Agriculture↗
PubMed1994

Novel gene expression system for plant cells based on induction of alpha-amylase promoter by carbohydrate starvation.

The 5' regulatory region and putative signal sequence of a rice alpha-amylase gene, alpha Amy8, was fused to a bacterial gene encoding beta-glucuronidase (GUS) and introduced into rice, tobacco, and potato via Agrobacterium-mediated transformation systems. Expression of this chimeric gene in suspension cells of transgenic plants was suppressed by the presence of sucrose in the medium and induced by its absence. Induction or suppression of GUS expression in transgenic rice could be reversed by the deprivation or replenishment, respectively, of sucrose in the medium. The expressed GUS fusion protein was translocated to the endoplasmic reticulum, modified by glycosylation, and secreted into the culture medium of transgenic cells. In the presence of a glycosylation inhibitor, tunicamycin, the enzymatically active form of GUS was assembled in the endoplasmic reticulum. The yield of GUS secreted by transgenic cells was estimated to be as high as 40% of total secreted proteins. The reversible induction of the alpha-amylase promoter in culture cells by sugar level in the medium provides an excellent inducible expression system for basic research in plant science. Combination of the alpha-amylase promoter and signal sequence also offers a novel approach for large scale production of low cost, easily purified, secreted recombinant proteins.

Amino Acid Sequence↗
PubMed1994

In vivo imaging of the interior of Tradescantia zebrina leaves by optical cross-correlation interferometry.

Using optical correlation interferometry, a novel method for plant sciences, we in imaged in vivo the z-direction, perpendicular to the leaf surface, through Tradescantia zebrina leaves. Non-invasively we determined number of major cell layers, followed the time sequence of decrease in cell z-axis after exposure of tissues to high salt, and observed disruption of cells caused by freezing and thawing.

Interferometry↗
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↗
PubMed1988

The use of ultrathin-layer polyacrylamide gel isoelectric focusing in two-dimensional analysis of plant and fungal proteins.

Although use of ultrathin polyacrylamide gel isoelectric focusing in the first dimension of two-dimensional analysis bestows a number of advantages, it has been little used by the plant science community. Nonstandardization along with problems unique to the format have probably delayed wider adoption. Relevant parameters were therefore tested in order to optimize resolution, reproducibility, economy and ease of use. Ultrathin-layer gels (200 microns in this study) used in the first dimension require a semirigid backing for support. Widely available matte-finished thin polyester film without chemical pretreatment was found to bind the gel adequately. The gel adheres to the film through all processing steps, yet, if desired, can be easily transferred to Whatman 3MM paper for special applications such as Western blotting. The ultrathin first-dimensional gels can be quickly dried on the polyester backing for convenient handling and long term storage. Strips cut from the dried gel for use in the second dimension are more easily manipulated than their tube format counterparts. The difficulty of disrupting and recovering microsamples of labeled leaf and root tissue prompted the invention of an efficient and simple communition device. An economical and efficient silver stain process is also described. This analytical technique was applied in an attempt to detect resistance gene products in different genetic backgrounds of maize. Although the ultrathin flatbed format provides as good as or better resolution than the tube gel system, the level of sensitivity was still inadequate to reveal the apparently rare resistance gene product.

Electrophoresis, Polyacrylamide Gel↗
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↗
PubMed1990

Intra and inter-person sources of variability in fat intake in a feeding trial of 14 men.

An impediment to analyzing the effect of nutritional factors on biologic processes or health status in human populations arises from the relatively small dietary differences that exist between individuals in relation to large periodic fluctuations in dietary intake and the imprecision with which diet is normally assessed. We report here on characteristics of dietary variability in a group of 14 young men who successfully completed an intervention study specifically designed to create large differences in fat intake between baseline and two dietary intervention-periods each lasting two months (during which safflower and coconut oil supplements were given). We found that in the second supplemental phase of the intervention inter-person sources of variability were greatly increased over the low-fat baseline values. For proportion of calories as fat it increased to 64.2% of total variance from 21.6% without supplementation; for saturated fatty acids, 47.3% from 17.7%; for polyunsaturated fatty acids, 62.4% from 22.8%; and for the P:S ratio, 71.5% from 21.6%. During the first intervention phase we observed only moderate changes. Reasons for the intervention phase differences in effect, implications for feeding trials designed to look at dietary fat effects, and the need for future studies aimed at clarifying these results are discussed.

Adult↗
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↗