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This month we present a Focus on methods for studying noncoding RNA and future directions for deciphering the regulatory roles of noncoding RNA. The confetti conceptually illustrates the broad diversity of noncoding RNA and the complexity of their biological implications.
Research interest in noncoding RNAs and their biological implications in a variety of cellular contexts has been growing. In this issue, we present a series of pieces discussing recent method advances and future directions for deciphering the regulatory roles of noncoding RNAs.
Recent studies have revealed multifaceted roles of long noncoding RNAs (lncRNAs) in gene regulation, accompanying an increased understanding of lncRNA processing, localization, interacting macromolecules and structural modules. Here, progress and recently developed technological advances for understanding lncRNA biogenesis, modes of action and cellular phenotypes are highlighted, and challenges and opportunities towards higher-resolution and in vivo studies in this field are discussed.
In recent years, the number of annotated noncoding RNAs (ncRNAs) and RNA-binding proteins (RBPs) has increased dramatically. The wide range of RBPs identified highlights the enormous potential for RNA in virtually all aspects of cell biology, from transcriptional regulation to metabolic control. Yet, there is a growing gap between what is possible and what has been demonstrated to be functionally important. Here we highlight recent methodological developments in the study of RNA–protein interactions, discuss the challenges and opportunities for exploring their functional roles, and provide our perspectives on what is needed to bridge the gap in this rapidly expanding field.
Nanopore direct RNA sequencing (DRS) reads continuous native RNA strands. Early adopters have used this technology to document nucleotide modifications and 3′ polyadenosine tails on RNA strands without added chemistry steps. Individual strands ranging in length from 70 to 26,000 nucleotides have been sequenced. In our opinion, broader acceptance of nanopore DRS by molecular biologists and cell biologists will be accelerated by higher basecall accuracy and lower RNA input requirements.
Researchers explore the unique and puzzling photostability of DNA FluoroCubes. Moreover, they improve the probes’ performance and highlight their diverse applicability.
Scanning transmission electron microscopy (STEM) techniques reveal atomic-resolution details of organic and inorganic materials. The application of STEM to biological vitrified specimens under low-dose cryogenic imaging conditions demonstrates that STEM also achieves near-atomic-resolution 3D structures of biological macromolecules.
RNA molecules designed by citizen scientists and probed in high-throughput experiments highlighted discrepancies among RNA folding algorithms in their ability to predict RNA structure ensembles. These datasets were used to train a new algorithm that demonstrated improved performance in a collection of independent datasets, including viral genomic RNAs and mRNAs probed in cells.
Joint profiling of multiple modalities in the same cell is challenging. We developed a method with a modular design to enable the simultaneous detection of chromatin accessibility and the transcriptome within single cells with flexible throughput.
BIONIC (Biological Network Integration using Convolutions) is a scalable deep learning network integration approach that learns and combines diverse data representations across a range of biological network types to consolidate knowledge of gene function. BIONIC outperforms existing integration approaches by capturing biological information more comprehensively and with greater accuracy than previously possible.
A genetically encoded green fluorescent sensor for oxytocin, MTRIAOT, offers an opportunity to perform real-time recording of brain oxytocin dynamics in living animals.
In vivo, forces applied to molecular interactions between T cells and antigen-presenting cells are essential for specific foreign antigen recognition. A new technology, BATTLES, applies force to thousands of T cells interacting with tens of candidate antigens to identify antigens capable of efficient T cell activation. The method improves throughput over current methods that profile force-dependent interactions.
A tissue engineering method using a 3D scaffolding enables the generation of an artificial human thymus from inducible pluripotent stem cells (iPSCs). The artificial thymus can be used to study human T cell development in hematopoietic humanized mice.
This Review summarizes recent methodological advances in experimental and computational tools developed in studying RNA structures, which provides a bridge for communication between both experimentalists and computational experts.
A machine learning competition results in tools for labeling protein patterns of single cells in images with population labels. The winners improve the state of the art and provide strategies to deal with weak classification challenges.
SVision is a deep-learning-based method that can sensitively and accurately detect and characterize complex structural variants using long-read sequencing data.
The EternaBench dataset of synthetic RNA constructs was used to directly compare RNA secondary structure prediction software packages on ensemble-oriented prediction tasks and used to train the EternaFold model for improved performance.
Event-driven acquisition uses neural-network-based recognition of specific biological events to trigger switching between slow and fast super-resolution imaging, enriching the capture of interesting events with high spatiotemporal resolution.
Event-triggered STED is an automated approach that can initiate 2D or 3D STED imaging of specific regions in biological samples after detection of an event of interest. This approach can help maximize observations in live cell imaging and enable discovery.
TracX improves the accuracy of single-cell tracking by using a fingerprinting approach to measure the similarity between cells in two consecutive images. The approach is applicable across modalities and enables biological discovery.
A fluorescent sensor for oxytocin called MTRIAOT has been developed. The sensor’s capabilities are demonstrated in fiber photometry measurements in freely behaving mice.