The plant noncoding transcriptome: a versatile environmental sensor

Update on functional analysis of long non-coding RNAs in common crops

With the rapid advances in next-generation sequencing technology, numerous non-protein-coding transcripts have been identified, including long noncoding RNAs (lncRNAs), which are functional RNAs comprising more than 200 nucleotides. Although lncRNA-mediated regulatory processes have been extensively investigated in animals, there has been considerably less research on plant lncRNAs. Nevertheless, multiple studies on major crops showed lncRNAs are involved in crucial processes, including growth and development, reproduction, and stress responses. This review summarizes the progress in the research on lncRNA roles in several major crops, presents key strategies for exploring lncRNAs in crops, and discusses current challenges and future prospects. The insights provided in this review will enhance our comprehension of lncRNA functions in crops, with potential implications for improving crop genetics and breeding.

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure

MOTIVATION

Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure from a raw RNA sequence is a long-standing unsolved problem, which after decades of almost unchanged performance has now re-emerged due to deep learning. Traditional RNA secondary structure prediction algorithms have been mostly based on thermodynamic models and dynamic programming for free energy minimization. More recently deep learning methods have shown competitive performance compared with the classical ones, but there is still a wide margin for improvement.

RESULTS

In this work we present sincFold, an end-to-end deep learning approach, that predicts the nucleotides contact matrix using only the RNA sequence as input. The model is based on 1D and 2D residual neural networks that can learn short- and long-range interaction patterns. We show that structures can be accurately predicted with minimal physical assumptions. Extensive experiments were conducted on several benchmark datasets, considering sequence homology and cross-family validation. sincFold was compared with classical methods and recent deep learning models, showing that it can outperform the state-of-the-art methods.

Underground communication: Long non-coding RNA signaling in the plant rhizosphere

Long non-coding RNAs (lncRNAs) have emerged as integral gene-expression regulators underlying plant growth, development, and adaptation. To adapt to the heterogeneous and dynamic rhizosphere, plants use interconnected regulatory mechanisms to optimally fine-tune gene-expression-governing interactions with soil biota, as well as nutrient acquisition and heavy metal tolerance. Recently, high-throughput sequencing has enabled the identification of plant lncRNAs responsive to rhizosphere biotic and abiotic cues. Here, we examine lncRNA biogenesis, classification, and mode of action, highlighting the functions of lncRNAs in mediating plant adaptation to diverse rhizosphere factors. We then discuss studies that reveal the significance and target genes of lncRNAs during developmental plasticity and stress responses at the rhizobium interface. A comprehensive understanding of specific lncRNAs, their regulatory targets, and the intricacies of their functional interaction networks will provide crucial insights into how these transcriptomic switches fine-tune responses to shifting rhizosphere signals. Looking ahead, we foresee that single-cell dissection of cell-type-specific lncRNA regulatory dynamics will enhance our understanding of the precise developmental modulation mechanisms that enable plant rhizosphere adaptation. Overcoming future challenges through multi-omics and genetic approaches will more fully reveal the integral roles of lncRNAs in governing plant adaptation to the belowground environment.

Biological Activity of Artificial Plant Peptides Corresponding to the Translational Products of Small ORFs in Primary miRNAs and Other Long "Non-Coding" RNAs

Generally, lncPEPs (peptides encoded by long non-coding RNAs) have been identified in many plant species of several families and in some animal species. Importantly, molecular mechanisms of the miPEPs (peptides encoded by primary microRNAs, pri-miRNAs) are often poorly understood in different flowering plants. Requirement for the additional studies in these directions is highlighted by alternative findings concerning positive regulation of pri-miRNA/miRNA expression by synthetic miPEPs in plants. Further extensive studies are also needed to understand the full set of their roles in eukaryotic organisms. This review mainly aims to consider the available data on the regulatory functions of the synthetic miPEPs. Studies of chemically synthesized miPEPs and analyzing the fine molecular mechanisms of their functional activities are reviewed. Brief description of the studies to identify lncORFs (open reading frames of long non-coding RNAs) and the encoded protein products is also provided.

COOLAIR and PRC2 function in parallel to silence FLC during vernalization

Noncoding transcription induces chromatin changes that can mediate environmental responsiveness, but the causes and consequences of these mechanisms are still unclear. Here, we investigate how antisense transcription (termed COOLAIR) interfaces with Polycomb Repressive Complex 2 (PRC2) silencing during winter-induced epigenetic regulation of Arabidopsis FLOWERING LOCUS C (FLC). We use genetic and chromatin analyses on lines ineffective or hyperactive for the antisense pathway in combination with computational modeling to define the mechanisms underlying FLC repression. Our results show that FLC is silenced through pathways that function with different dynamics: a COOLAIR transcription-mediated pathway capable of fast response and in parallel a slow PRC2 switching mechanism that maintains each allele in an epigenetically silenced state. Components of both the COOLAIR and PRC2 pathways are regulated by a common transcriptional regulator (NTL8), which accumulates by reduced dilution due to slow growth at low temperature. The parallel activities of the regulatory steps, and their control by temperature-dependent growth dynamics, create a flexible system for registering widely fluctuating natural temperature conditions that change year on year, and yet ensure robust epigenetic silencing of FLC.