Plant Science

CRISPR/Cas9-based genome editing is a powerful approach for functional genomics and bioenergy research in woody plants. However, conventional single guide RNA (gRNA) strategies predominantly generate small insertions or deletions that may not fully disrupt gene function and often require extensive sequencing for mutation identification. Here, we present an optimized protocol for the efficient generation of large-fragment deletion mutants in Populus tremula × P. alba clone INRA 717-1B4 using a dual-gRNA CRISPR/Cas9 system. Co-expression of two gRNAs flanking the target region induces double-strand breaks at both sites, enabling the deletion of the intervening genomic fragment, typically larger than 50 bp. This protocol describes step-by-step procedures for gRNA design, vector construction, Agrobacterium-mediated transformation, plant regeneration, and molecular validation. Using the PtFBX230 gene as a representative target, large deletions are readily identified by conventional PCR and agarose gel electrophoresis, enabling rapid and cost-effective genotyping. This protocol can be readily adopted to other loci in poplar and related woody species and provides a robust framework for generating null alleles to support functional genomics and bioenergy-related trait engineering in woody plants.

The canonical role of transfer RNAs (tRNAs) in protein synthesis has been extensively characterized; however, recent studies have uncovered novel functions for tRNA as a mediator of long-distance signaling in plants. Several studies have identified dicistronic tRNA-mRNA transcripts that contain a tRNA gene and an adjacent protein-coding gene (PCG) that are transcribed as a single unit. These transcripts are associated with RNA systemic mobility through the plant’s vascular tissues, potentially acting as non-cell-autonomous signaling messengers in coordinating development and stress responses. Here, we report a computational pipeline to detect dicistronic tRNA-mRNA transcripts from short-read next-generation RNA-sequencing datasets; to our knowledge, this is the only established pipeline for the systematic identification of such candidates in plants. The dicistronic RNA transcript version 2 (v2) described here improves on the earlier version DiRT v1 by expanding the repertoire of dicistronic transcripts detected to include tRNA-like structures (TLS) as well as functional tRNAs, which were already supported in the pipeline. The updated protocol also includes detection of dicistronic tRNA or TLS sequences within genomic features such as untranslated regions (UTRs). The accurate detection of both tRNAs and UTR-embedded tRNA-like sequences (TLS) is critical, as these RNA structures have been reported to function as mediators of long-distance RNA mobility. Furthermore, as NGS datasets are prone to sequencing artifacts and potential DNA contamination, we improved the pipeline’s statistical robustness by including read coverage of flanking intronic regions as a baseline control. To account for potential DNA contamination during RNA-seq library preparation, detected tRNA-mRNA transcripts are deemed as putatively dicistronic only if the coverage of their intergenic region is significantly higher (Student’s t-test, FDR < 0.05) than flanking intronic regions. Furthermore, the updated pipeline allows this statistical test to be applied to intronless and single-intron genes. Using this updated protocol, we identified novel tRNA and TLS dicistronic transcripts in both grapevine (Vitis spp. Ruggeri 140) and Arabidopsis thaliana datasets and validated in vitro using RT-PCR. We provide a fast and reliable method to detect dicistronic transcripts that can be applied to any short-read RNA-sequencing dataset, fast-tracking the functional characterization of these newly emerging transcripts.

While traditional kinetic studies of the cytochrome b₆f complex have frequently relied on measurements within the complex environment of intact leaves or whole-organism systems, such approaches can be limited by overlapping signals and physiological variables. This protocol advances existing frameworks by introducing a streamlined, multi-wavelength spectroscopic approach utilizing a reconstituted in vitro system to elucidate the inter-complex electron transfer kinetics between photosystem I and cytochrome b₆f. Utilizing the JTS-150 pulsed spectrometer, supplied with a Smart Lamp, we monitored the redox transitions of P700⁺ and Cytf by simultaneously measuring the absorbance changes of our isolated complexes system in six different wavelengths (546, 554, 563, 574, 705, and 740 nm). Kinetic analysis was divided into two phases: laser-induced flash kinetics and steady-state actinic induction. We resolved the second-order re-reduction of P700⁺ by plastocyanin, accounting for detector saturation constraints with a 2 ms post-flash delay. Steady-state measurements under actinic light revealed complex Cytf turnover, characterized by a double-exponential decay. Furthermore, dark relaxation kinetics were used to quantify ferredoxin-mediated re-reduction of the cytochrome pool. By allowing the incorporation of specific regulatory and inhibitory factors, this methodology sets the ground for the deconvolution of competing electron pathways. It can therefore be used as a robust framework for assessing the mechanism of regulatory processes on photosynthetic flux.

Pinpointing causal genes for complex traits from genome-wide association studies (GWAS) remains a central challenge in crop genetics, particularly in species with extensive linkage disequilibrium (LD) such as rice. Here, we present CisTrans-ECAS, a computational protocol that overcomes this limitation by integrating population genomics and transcriptomics. The method’s core principle is the decomposition of gene expression into two distinct components: a cis-expression component (cis-EC), regulated by local genetic variants, and a trans-expression component (trans-EC), influenced by distal genetic factors. By testing the association of both components with a phenotype, CisTrans-ECAS establishes a dual-evidence framework that substantially improves the reliability of causal inference. This protocol details the complete workflow, demonstrating its power not only to identify causal genes at loci with weak GWAS signals but also to systematically reconstruct gene regulatory networks. It provides a robust and powerful tool for advancing crop functional genomics and molecular breeding.

Biomolecular condensates organize cellular processes through liquid–liquid phase separation, creating membrane-less compartments enriched in specific proteins and RNAs. Understanding their RNA composition is essential for elucidating plant stress responses, yet capturing these transiently associated RNAs remains technically challenging. We present Turbo-RIP (TurboID-based proximity labeling with RNA immunopurification), a comprehensive protocol for identifying condensate-associated RNAs in plants. Turbo-RIP employs the biotin ligase TurboID to label proximal proteins at 22 °C, followed by formaldehyde crosslinking and streptavidin-based capture of protein–RNA complexes. We provide detailed procedures for three cloning strategies, transformation of Nicotiana benthamiana and Arabidopsis thaliana, validation of TurboID activity, and RNA recovery. The protocol successfully captured processing body–associated RNAs with minimal background. Turbo-RIP enables systematic mapping of RNA populations within plant condensates under diverse conditions. The protocol requires 3–5 days from sample preparation to RNA isolation, with construct validation taking 2–4 weeks. All procedures use standard laboratory equipment, making Turbo-RIP accessible for plant molecular biology laboratories.

A simple and effective method to identify genetic markers of yield response to nitrogen (N) fertilizer among maize hybrids is urgently needed. In this article, we describe a detailed methodology to identify genetic markers and develop associated assays for the prediction of yield N-response in maize. We first outline an in silico workflow to identify high-priority single-nucleotide polymorphism (SNP) markers from genome-wide association studies (GWAS). We then describe a detailed methodology to develop cleaved amplified polymorphic sequences (CAPS) and derived CAPS (dCAPS)-based assays to quickly and effectively test genetic marker subsets. This protocol is expected to provide a robust approach to determine N-response type among maize germplasm, including elite commercial varieties, allowing more appropriate on-farm N application rates, minimizing N fertilizer waste.

In plants, the apoplast contains a diverse set of proteins that underpin mechanisms for maintaining cell homeostasis, cell wall remodeling, cell signaling, and pathogen defense. Apoplast protein composition is highly regulated, primarily through the control of secretory traffic in response to endogenous and environmental factors. Dynamic changes in apoplast proteome facilitate plant survival in a changing climate. Even so, the apoplast proteome profiles in plants remain poorly characterized due to technological limitations. Recent progress in quantitative proteomics has significantly advanced the resolution of proteomic profiling in mammalian systems and has the potential for application in plant systems. In this protocol, we provide a detailed and efficient protocol for tandem mass tag (TMT)-based quantitative analysis of Arabidopsis thaliana secretory proteome to resolve dynamic changes in leaf apoplast proteome profiles. The protocol employs apoplast flush collection followed by protein cleaning using filter-aided sample preparation (FASP), protein digestion, TMT-labeling of peptides, and mass spectrometry (MS) analysis. Subsequent data analysis for peptide detection and quantification uses Proteome Discoverer software (PD) 3.0. Additionally, we have incorporated in silico–generated spectral libraries using PD 3.0, which enables rapid and efficient analysis of proteomic data. Our optimized protocol offers a robust framework for quantitative secretory proteomic analysis in plants, with potential applications in functional proteomics and the study of trafficking systems that impact plant growth, survival, and health.

Synthetic trans-acting small interfering RNAs (syn-tasiRNAs) are 21-nucleotide small RNAs designed to induce highly specific and efficient gene silencing in plants. Traditional approaches rely on the transgenic expression of ~1 kb TAS precursors, which limits their use in non-model species, under strict GMO regulations, and in size-constrained expression or delivery systems. This protocol describes a rapid workflow for the design, assembly, and delivery of syn-tasiRNAs derived from much shorter precursors, referred to as minimal precursors. The pipeline includes in silico design of highly specific syn-tasiRNA sequences, cloning of minimal precursors into plant expression or potato virus X (PVX)-based viral vectors through Golden Gate or Gibson assembly, and delivery to plants through Agrobacterium-mediated expression or by spraying crude extracts containing recombinant PVX expressing the minimal precursors. These methodologies make syn-tasiRNA-based tools more accessible and broadly applicable for plant research and biotechnology across diverse species and experimental contexts.

The study of RNA metabolism involves understanding how RNA molecules interact with specific RNA-binding proteins (RBPs). In plants, these interactions have traditionally been investigated using a variety of in vivo and in vitro approaches, such as electrophoretic mobility shift assays or the analysis of knockout mutants. More recently, immunoprecipitation-based techniques have been developed. Most of the available protocols rely on crosslinking procedures, magnetic beads, and RNA-seq as the final endpoint analysis. Here, we present a protocol developed to identify specific RNA targets that directly interact with known plant RBPs using GFP-Trap^® agarose (ChromoTek) for immunoprecipitation without the need for crosslinking or RNA-seq. Briefly, a GFP-tagged RNA-binding protein is expressed in plant tissue, protein extracts are incubated with the GFP-Trap^® agarose matrix, and the resulting complexes are isolated. Co-purified RNAs, specifically mRNAs, are then analyzed by RT-PCR to detect bound transcripts. This protocol was first implemented for the study of RNA–protein interaction in Arabidopsis thaliana. This approach presents high potential for analysis in other plant species as well as several advantages, such as its high specificity and low cost. Even though GFP-Trap^® magnetic agarose (ChromoTek) has been used in plant systems to detect RNA–protein interactions, the protocol presented here consists of an alternative that is straightforward to implement when both candidate RNAs and RNA-binding proteins are known, and it can be broadly applied to study RNA–protein interactions in other plant systems.

The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system is a widely used programmable nuclease system for gene modification in many organisms, including Physcomitrium patens. P. patens is a model species of moss plants, a basal land plant group, which has been extensively studied from the viewpoint of evolution and diversity of green plant lineages. So far, gene modifications by CRISPR/Cas9 in P. patens have been carried out exclusively by the polyethylene glycol (PEG)-mediated DNA transfer method, in which a transgene (or transgenes) is introduced into protoplast cells prepared from protonemal tissues. However, this PEG-mediated method requires a relatively large amount of transgene DNA (typically 30 µg for a single transformation), consists of many steps, and is time-consuming. Additionally, this PEG-mediated method has only been established in a few species of moss. In the current protocol, we succeeded in CRISPR/Cas9-induced targeted mutagenesis of P. patens genes by making good use of the biolistic method, which i) requires amounts of transgene DNA as low as 5 μg for each vector, ii) consists of fewer steps and is time-saving, and iii) is known to be applicable to a wide variety of species of plants.