A Walkthrough to the Use of GreeNC: The Plant lncRNA Database

Comprehensive transcriptomic analysis of two RIL parents with contrasting salt responsiveness identifies polyadenylated and non-polyadenylated flower lncRNAs in chickpea

Salinity severely affects the yield of chickpea. Understanding the role of lncRNAs can shed light on chickpea salt tolerance mechanisms. However, because lncRNAs are encoded by multiple sites within the genome, their classification to reveal functional versatility at the transcriptional and the post-transcriptional levels is challenging. To address this, we deep sequenced 24 salt-challenged flower transcriptomes from two parental genotypes of a RIL population that significantly differ in salt tolerance ability. The transcriptomes for the first time included 12 polyadenylated and 12 non-polyadenylated RNA libraries to a sequencing depth of ~50 million reads. The ab initio transcriptome assembly comprised ~34 082 transcripts from three biological replicates of salt-tolerant (JG11) and salt-sensitive (ICCV2) flowers. A total of 9419 lncRNAs responding to salt stress were identified, 2345 of which were novel lncRNAs specific to chickpea. The expression of poly(A+) lncRNAs and naturally antisense transcribed RNAs suggest their role in post-transcriptional modification and gene silencing. Notably, 178 differentially expressed lncRNAs were induced in the tolerant genotype but repressed in the sensitive genotype. Co-expression network analysis revealed that the induced lncRNAs interacted with the FLOWERING LOCUS (FLC), chromatin remodelling and DNA methylation genes, thus inducing flowering during salt stress. Furthermore, 26 lncRNAs showed homology with reported lncRNAs such as COOLAIR, IPS1 and AT4, thus confirming the role of chickpea lncRNAs in controlling flowering time as a crucial salt tolerance mechanism in tolerant chickpea genotype. These robust set of differentially expressed lncRNAs provide a deeper insight into the regulatory mechanisms controlled by lncRNAs under salt stress.

MILNP: Plant lncRNA-miRNA Interaction Prediction Based on Improved Linear Neighborhood Similarity and Label Propagation

Knowledge of the interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) is the basis of understanding various biological activities and designing new drugs. Previous computational methods for predicting lncRNA-miRNA interactions lacked for plants, and they suffer from various limitations that affect the prediction accuracy and their applicability. Research on plant lncRNA-miRNA interactions is still in its infancy. In this paper, we propose an accurate predictor, MILNP, for predicting plant lncRNA-miRNA interactions based on improved linear neighborhood similarity measurement and linear neighborhood propagation algorithm. Specifically, we propose a novel similarity measure based on linear neighborhood similarity from multiple similarity profiles of lncRNAs and miRNAs and derive more precise neighborhood ranges so as to escape the limits of the existing methods. We then simultaneously update the lncRNA-miRNA interactions predicted from both similarity matrices based on label propagation. We comprehensively evaluate MILNP on the latest plant lncRNA-miRNA interaction benchmark datasets. The results demonstrate the superior performance of MILNP than the most up-to-date methods. What's more, MILNP can be leveraged for isolated plant lncRNAs (or miRNAs). Case studies suggest that MILNP can identify novel plant lncRNA-miRNA interactions, which are confirmed by classical tools. The implementation is available on https://github.com/HerSwain/gra/tree/MILNP.

A vast pool of lineage-specific microproteins encoded by long non-coding RNAs in plants

Pervasive transcription of eukaryotic genomes results in expression of long non-coding RNAs (lncRNAs) most of which are poorly conserved in evolution and appear to be non-functional. However, some lncRNAs have been shown to perform specific functions, in particular, transcription regulation. Thousands of small open reading frames (smORFs, <100 codons) located on lncRNAs potentially might be translated into peptides or microproteins. We report a comprehensive analysis of the conservation and evolutionary trajectories of lncRNAs-smORFs from the moss Physcomitrium patens across transcriptomes of 479 plant species. Although thousands of smORFs are subject to substantial purifying selection, the majority of the smORFs appear to be evolutionary young and could represent a major pool for functional innovation. Using nanopore RNA sequencing, we show that, on average, the transcriptional level of conserved smORFs is higher than that of non-conserved smORFs. Proteomic analysis confirmed translation of 82 novel species-specific smORFs. Numerous conserved smORFs containing low complexity regions (LCRs) or transmembrane domains were identified, the biological functions of a selected LCR-smORF were demonstrated experimentally. Thus, microproteins encoded by smORFs are a major, functionally diverse component of the plant proteome.

The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new transcripts identified each year. However, only a small subset of lncRNAs has been characterized functionally thus far. To aid investigating the mechanisms of action by which new lncRNAs act, bioinformatic tools and databases are invaluable. Here, we review a selection of computational tools and databases for the in silico analysis of lncRNAs, including tissue-specific expression, protein coding potential, subcellular localization, structural conformation, and interaction partners. The assembled lncRNA toolkit is aimed primarily at experimental researchers as a useful starting point to guide wet-lab experiments, mainly containing multi-functional, user-friendly interfaces. With more and more new lncRNA analysis tools available, it will be essential to provide continuous updates and maintain the availability of key software in the future.

Long noncoding RNAs shape transcription in plants

The advent of novel high-throughput sequencing techniques has revealed that eukaryotic genomes are massively transcribed although only a small fraction of RNAs exhibits protein-coding capacity. In the last years, long noncoding RNAs (lncRNAs) have emerged as regulators of eukaryotic gene expression in a wide range of molecular mechanisms. Plant lncRNAs can be transcribed by alternative RNA polymerases, acting directly as long transcripts or can be processed into active small RNAs. Several lncRNAs have been recently shown to interact with chromatin, DNA or nuclear proteins to condition the epigenetic environment of target genes or modulate the activity of transcriptional complexes. In this review, we will summarize the recent discoveries about the actions of plant lncRNAs in the regulation of gene expression at the transcriptional level.