Plant Science

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.

Rhamnogalacturonan-II (RG-II) is one of the least studied domains of pectin, primarily due to its low abundance, the lack of reliable antibodies, and the complexity of its structure. The present study builds upon existing protocols and procedures used to analyse RG-II in tissues where it is more abundant, combining and adapting them for the isolation of RG-II from Arabidopsis seed mucilage—a structure previously thought to lack RG-II. By applying these adapted methods, we first confirmed the presence of RG-II in seed mucilage and subsequently succeeded in isolating it from a tissue where it is typically present in low abundance, thereby enabling future studies on this previously overlooked component.

In many plant species, self-incompatibility (SI) is a mechanism that inhibits inbreeding. SI is gametophytic in the Solanaceae, with specificity determined by S-ribonucleases (S-RNases) in the pistil and S-locus F-box proteins (SLFs) in the pollen. The role of these proteins has been studied extensively in the Solanaceae, often using Petunia as a model. Using degenerate PCR and Sanger sequencing, this protocol identified three SLF sequences from self-incompatible diploid potato (Solanum okadae). While SLFs are well-characterized in model species like Petunia, there is limited sequence data and no standardized protocols for identifying SLFs in non-model species such as S. okadae, hindering broader insights into SI across the Solanaceae. This protocol fills that gap by using degenerate PCR and Sanger sequencing with primers designed from conserved Petunia SLF regions to identify SLF sequences in S. okadae. SLF sequences from 10 distinct Solanaceae members sharing maximum identity with the S2-haplotype of Petunia were used to design two pairs of primers targeting different regions of the target sequence. PCR amplification using designed degenerate primers yielded amplicons that were directly sequenced and joined together to get the partial SLF sequence. It was observed that the S. okadae shared an orthologous relation with the Petunia SLF according to the phylogenetic analysis. These SLFs could be used in future SI breakdown experiments via the competitive interaction route. This protocol, including the primer design, is novel for detecting SLF sequences in S. okadae.

The identification of chemical compounds that affect intracellular processes has greatly contributed to the understanding of developmental regulation in plants. In this protocol, we describe a method for identifying chemical compounds that affect cold-regulated gene expression in Arabidopsis thaliana. Specifically, we generated Arabidopsis plants harboring a COLD-REGULATED 15A (COR15A) promoter::luciferase (COR15Apro::LUC) construct and grew them in a submerged liquid culture. Using a single true leaf excised from COR15Apro::LUC plants and 96-well culture plates, we performed high-throughput screening of chemical compounds that inhibit cold-induction of COR15Apro::LUC. Luciferase activity was detected using a microplate reader and a chemiluminescence imaging device. This protocol can be easily used for the identification of chemical compounds that regulate other processes, being versatile with respect to equipment.