分子生物学

Thousands of RNAs are localized to specific subcellular locations, and these localization patterns are often required for optimal cell function. However, the sequences within RNAs that direct their transport are unknown for almost all localized transcripts. Similarly, the RNA content of most subcellular locations remains unknown. To facilitate the study of subcellular transcriptomes, we developed the RNA proximity labeling method OINC-seq. OINC-seq utilizes photoactivatable, spatially restricted RNA oxidation to specifically label RNA in proximity to a subcellularly localized bait protein. After labeling, these oxidative RNA marks are then read out via high-throughput sequencing due to their ability to induce predictable misincorporation events by reverse transcriptase. These induced mutations are then quantitatively assessed for each gene using our software package PIGPEN. The observed mutation rate for a given RNA species is therefore related to its proximity to the localized bait protein. This protocol describes procedures for assaying RNA localization via OINC-seq experiments as well as computational procedures for analyzing the resulting data using PIGPEN.

Transcriptional pausing dynamically regulates spatiotemporal gene expression during cellular differentiation, development, and environmental adaptation. Precise measurement of pausing duration, a critical parameter in transcriptional control, has been challenging due to limitations in resolution and confounding factors. We introduce Fast TV-PRO-seq, an optimized protocol built on time-variant precision run-on sequencing (TV-PRO-seq), which enables genome-wide, single-base resolution mapping of RNA polymerase II pausing times. Unlike standard PRO-seq, Fast TV-PRO-seq employs sarkosyl-free biotin-NTP run-on with time gradients and integrates on-bead enzymatic reactions to streamline workflows. Key improvements include (1) reducing experimental time from 4 to 2 days, (2) reducing cell input requirements, and (3) improved process efficiency and simplified command-line operations through the use of bash scripts.

The subcellular localization of RNA plays a critical role in various biological processes, including development and stress response. Proximity labeling eases the detection of localized transcripts and protein enrichment compared to previous techniques that rely on biochemical isolation of subcellular structures. The rapid reaction and small labeling radius of APEX2 make it an attractive alternative to other proximity labeling approaches, such as BioID. However, we found that standard protocols for APEX proximity labeling fail in human induced pluripotent stem cells. Moreover, standard protocols yield heterogeneous labeling of biomolecules across single cells in MCF10A breast epithelial cells. Our results indicate that low biotin permeability in these cell lines is the main cause for failed or inefficient labeling. This protocol outlines improved labeling by combining the rapid hydrogen peroxide-driven APEX2 reaction with the addition of a mild detergent during biotin incubation. This adaptation leads to efficient proximity labeling in hiPSCs and more homogeneous biotinylation across single cells in MCF10As. The adapted protocol extends the use of APEX2 proximity labeling to cell lines with poor biotin permeability.

The complexity of the human transcriptome poses significant challenges for complete annotation. Traditional RNA-seq, often limited by sensitivity and short read lengths, is frequently inadequate for identifying low-abundant transcripts and resolving complex populations of transcript isoforms. Direct long-read sequencing, while offering full-length information, suffers from throughput limitations, hindering the capture of low-abundance transcripts. To address these challenges, we introduce a targeted RNA enrichment strategy, rapid amplification of cDNA ends coupled with Nanopore sequencing (RACE-Nano-Seq). This method unravels the deep complexity of transcripts containing anchor sequences—specific regions of interest that might be exons of annotated genes, in silico predicted exons, or other sequences. RACE-Nano-Seq is based on inverse PCR with primers targeting these anchor regions to enrich the corresponding transcripts in both 5' and 3' directions. This method can be scaled for high-throughput transcriptome profiling by using multiplexing strategies. Through targeted RNA enrichment and full-length sequencing, RACE-Nano-Seq enables accurate and comprehensive profiling of low-abundance transcripts, often revealing complex transcript profiles at the targeted loci, both annotated and unannotated.

Osteoarthritis (OA) is the primary cause of joint impairment, particularly in the knee. The prevalence of OA has significantly increased, with knee OA being a major contributor whose pathogenesis remains unknown. Articular cartilage and the synovium play critical roles in OA, but extracting high-quality RNA from these tissues is challenging because of the high extracellular matrix content and low cellularity. This study aimed to identify the most suitable RNA isolation method for obtaining high-quality RNA from microquantities of guinea pig cartilage and synovial tissues, a relevant model for idiopathic OA. We compared the traditional TRIzol^® method with modifications to spin column–based methods (TRIspin-TRIzol^®/RNeasy^TM, RNeasy^TM kit, RNAqueous^TM kit, and Quick-RNA^TM Miniprep Plus kit), and an optimized RNA isolation protocol was developed to increase RNA yield and purity. The procedure involved meticulous sample collection, specialized tissue processing, and measures to minimize RNA degradation. RNA quality was assessed via spectrophotometry and RT–qPCR. The results demonstrated that among the tested methods, the Quick-RNA^TM Miniprep Plus kit with proteinase K treatment yielded the highest RNA purity, with A_260:280 ratios ranging from 1.9 to 2.0 and A_260:230 ratios between 1.6 and 2.0, indicating minimal to no salt contamination and RNA concentrations up to 240 ng/μL from ⁓20 mg of tissue. The preparation, storage, homogenization process, and choice of RNA isolation method are all critical factors in obtaining high-purity RNA from guinea pig cartilage and synovial tissues. Our developed protocol significantly enhances RNA quality and purity from micro-quantities of tissue, making it particularly effective for RTqPCR in resource-limited settings. Further refinements can potentially increase RNA yield and purity, but this protocol facilitates accurate gene expression analyses, contributing to a better understanding of OA pathogenesis and the development of therapeutic strategies.

N⁶-methyladenosine (m6A) is an abundant internal mRNA modification with roles in regulating cellular and organismal physiology, including development, differentiation, and disease. The deposition of m6A is highly regulated, with various m6A levels across different environmental conditions, cellular states, and cell types. Available methods for measuring bulk m6A levels are often time-consuming, have low throughput, and/or require specialized instrumentation or data analyses. Here, we present a detailed protocol for measuring bulk m6A levels in purified poly(A) RNA samples with m6A-ELISA using a standard-based approach. Critical steps of the protocol are highlighted and optimized, including poly(A) RNA quality controls and antibody specificity testing. The protocol is fast, scalable, adaptable, and cost-effective. It does not require specialized instrumentation, training, or skills in data analysis. We have successfully tested this protocol on mRNAs isolated from budding yeast and mouse cell lines.

Plant embryos are contained within seeds. Isolating them is crucial when endosperm and seed coat tissues interfere with the study of mutant genetic functions due to differing genotypes between maternal and embryonic tissues. RNA extraction from plant embryonic tissue presents particular challenges due to the high activity of RNases, the composition of the seed, and the risk of RNA degradation. The developmental stage of the embryo is a key aspect of successful isolation and RNA extraction due to the size and amount of tissue. Proper handling during RNA extraction is critical to maintain RNA integrity and prevent degradation. While commercial kits offer various methods for RNA extraction from embryos, homemade protocols provide valuable advantages, including cost-effectiveness and accessibility for labs with limited funding. Here, we present a simple and efficient protocol for extracting RNA from isolated Arabidopsis thaliana embryos at the torpedo/cotyledon stage using a homemade extraction buffer previously reported for styles of Nicotiana alata.

Human astroviruses pose a significant public health threat, especially to children, the elderly, and immunocompromised individuals. Nevertheless, these viruses remain largely understudied, with no approved antivirals or vaccines. This protocol focuses on leveraging reverse genetics (RG) and replicon systems to unravel the biology of MLB genotypes, a key group of neurotropic astroviruses. Using reverse genetics and replicon systems, we identified critical genetic deletions linked to viral attenuation and neurotropism, pushing forward vaccine development. We also uncovered novel replication mechanisms involving ER membrane interactions, opening doors to new antiviral targets. Reverse genetics and replicon systems are essential for advancing our understanding of astrovirus biology, identifying virulence factors, and developing effective treatments and vaccines to combat their growing public health impact.

Transfer RNAs (tRNAs), the essential adapter molecules in protein translation, undergo various post-transcriptional modifications. These modifications play critical roles in regulating tRNA folding, stability, and codon–anticodon interactions, depending on the modified position. Methods for detecting modified nucleosides in tRNAs include isotopic labeling combined with chromatography, antibody-based techniques, mass spectrometry, and high-throughput sequencing. Among these, high-performance liquid chromatography (HPLC) has been a cornerstone technique for analyzing modified nucleosides for decades. In this protocol, we provide a detailed, streamlined approach to purify and digest tRNAs from yeast cells and analyze the resulting nucleosides using HPLC. By assessing UV absorbance spectra and retention times, modified nucleosides can be reliably quantified with high accuracy. This method offers a simple, fast, and accessible alternative for studying tRNA modifications, especially when advanced technologies are unavailable.

Cellular communication relies on the intricate interplay of signaling molecules, which come together to form the cell–cell interaction (CCI) network that orchestrates tissue behavior. Researchers have shown that shallow neural networks can effectively reconstruct the CCI from the abundant molecular data captured in spatial transcriptomics (ST). However, in scenarios characterized by sparse connections and excessive noise within the CCI, shallow networks are often susceptible to inaccuracies, leading to suboptimal reconstruction outcomes. To achieve a more comprehensive and precise CCI reconstruction, we propose a novel method called triple-enhancement-based graph neural network (TENET). The TENET framework has been implemented and evaluated on both real and synthetic ST datasets. This protocol primarily introduces our network architecture and its implementation.