The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs

Upstream regulator of genomic imprinting in rice endosperm is a small RNA-associated chromatin remodeler

Genomic imprinting is observed in endosperm, a placenta-like seed tissue, where transposable elements (TEs) and repeat-derived small RNAs (sRNAs) mediate epigenetic changes in plants. In imprinting, uniparental gene expression arises due to parent-specific epigenetic marks on one allele but not on the other. The importance of sRNAs and their regulation in endosperm development or in imprinting is poorly understood in crops. Here we show that a previously uncharacterized CLASSY (CLSY)-family chromatin remodeler named OsCLSY3 is essential for rice endosperm development and imprinting, acting as an upstream player in the sRNA pathway. Comparative transcriptome and genetic analysis indicated its endosperm-preferred expression and its likely paternal imprinted nature. These important features are modulated by RNA-directed DNA methylation (RdDM) of tandemly arranged TEs in its promoter. Upon perturbation of OsCLSY3 in transgenic lines, we observe defects in endosperm development and a loss of around 70% of all sRNAs. Interestingly, well-conserved endosperm-specific sRNAs (siren) that are vital for reproductive fitness in angiosperms are also dependent on OsCLSY3. We observed that many imprinted genes and seed development-associated genes are under the control of OsCLSY3. These results support an essential role of OsCLSY3 in rice endosperm development and imprinting, and propose similar regulatory strategies involving CLSY3 homologs among other cereals.

Identification of plant microRNAs using convolutional neural network

MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Convenient Analysis Tools (SRICATs). SRICATs encompasses all the necessary steps for plant miRNA analysis. Our results indicate that SRICATs outperforms currently popular software tools on the test data from five plant species. For non-commercial users, SRICATs is freely available at https://sourceforge.net/projects/sricats.

Benchmarking of bioinformatics tools for NGS-based microRNA profiling with RT-qPCR method

MicroRNAs are vital gene expression regulators, extensively studied worldwide. The large-scale characterization of miRNAomes is possible using next-generation sequencing (NGS). This technology offers great opportunities, but these cannot be fully exploited without proper and comprehensive bioinformatics analysis. This may be achieved by the use of reliable dedicated software; however, different programs may generate divergent results, leading to additional discrepancies. Thus, the aim of this study was to compare three bioinformatic algorithms dedicated to NGS-based microRNA profiling and validate them using an alternative method, namely RT-qPCR. The comparison analysis revealed differences in the number and sets of identified miRNAs. The qPCR confirmed the expression of the investigated microRNAs. The correlation analysis of NGS and qPCR measurements showed strong and significant coefficients for a subset of the tested miRNAs, including those detected by all three algorithms. Single miRNA variants (isomiRs) showed different levels of correlation with the qPCR data. The obtained results revealed the good performance of all tested programs, despite the observed differences. Moreover, they implied that some specific miRNAs may be differentially estimated using NGS technology and the qPCR method, regardless of the used bioinformatics software. These discrepancies may stem from many factors, including the composition of the isomiR profile, their abundance, length, and investigated species. In conclusion, in this study, we shed light on the bioinformatics aspects of miRNAome profiling, elucidating its complexity and pinpointing potential features influencing validation. Thus, qPCR validation results should be open to interpretation when not fully concordant with NGS results until further, additional analyses are conducted.

RA-induced prominence-specific response resulted in distinctive regulation of Wnt and osteogenesis

Proper retinoic acid (RA) signaling is essential for normal craniofacial development. Both excessive RA and RA deficiency in early embryonic stage may lead to a variety of craniofacial malformations, for example, cleft palate, which have been investigated extensively. Dysregulated Wnt and Shh signaling were shown to underlie the pathogenesis of RA-induced craniofacial defects. In our present study, we showed a spatiotemporal-specific effect of RA signaling in regulating early development of facial prominences. Although inhibited Wnt activities was observed in E12.5/E13.5 mouse palatal shelves, early exposure of excessive RA induced Wnt signaling and Wnt-related gene expression in E11.5/E12.5 mouse embryonic frontonasal/maxillary processes. A conserved regulatory network of miR-484-Fzd5 was identified to play critical roles in RA-regulated craniofacial development using RNA-seq. In addition, subsequent osteogenic/chondrogenic differentiation were differentially regulated in discrete mouse embryonic facial prominences in response to early RA induction, demonstrated using both in vitro and in vivo analyses.

tiny-count: a counting tool for hierarchical classification and quantification of small RNA-seq reads with single-nucleotide precision

Summary

tiny-count is a highly flexible counting tool that allows for hierarchical classification and quantification of small RNA reads from high-throughput sequencing data. Selection rules can be used to filter reads by 5' nucleotide, length, position of alignments in relation to reference features, and by the number of mismatches to reference sequences. tiny-count can quantify reads aligned to a genome or directly to small RNA or transcript sequences. With tiny-count, users can quantify a single class of small RNAs or multiple classes in parallel. tiny-count can resolve distinct classes of small RNAs, for example, piRNAs and siRNAs, produced from the same locus. It can distinguish small RNA variants, such as miRNAs and isomiRs, with single-nucleotide precision. tRNA, rRNA, and other RNA fragments can also be quantified. tiny-count can be run alone or as part of tinyRNA, a workflow that provides a basic all-in-one command line-based solution for small RNA-seq data analysis, with documentation and statistics generated at each step for accurate and reproducible results.

Availability and implementation

tiny-count and other tinyRNA tools are implemented in Python, C++, Cython, and R, and the workflow is coordinated with CWL. tiny-count and tinyRNA are free and open-source software distributed under the GPLv3 license. tiny-count can be installed via Bioconda (https://anaconda.org/bioconda/tiny-count) and both tiny-count and tinyRNA documentation and software downloads are available at https://github.com/MontgomeryLab/tinyRNA. Reference data, including genome and feature information, for certain species can be found at https://www.MontgomeryLab.org.

Plant polymerase IV sensitizes chromatin through histone modifications to preclude spread of silencing into protein-coding domains

Across eukaryotes, gene regulation is manifested via chromatin states roughly distinguished as heterochromatin and euchromatin. The establishment, maintenance, and modulation of the chromatin states is mediated using several factors including chromatin modifiers. However, factors that avoid the intrusion of silencing signals into protein-coding genes are poorly understood. Here we show that a plant specific paralog of RNA polymerase (Pol) II, named Pol IV, is involved in avoidance of facultative heterochromatic marks in protein-coding genes, in addition to its well-established functions in silencing repeats and transposons. In its absence, H3K27 trimethylation (me3) mark intruded the protein-coding genes, more profoundly in genes embedded with repeats. In a subset of genes, spurious transcriptional activity resulted in small(s) RNA production, leading to post-transcriptional gene silencing. We show that such effects are significantly pronounced in rice, a plant with a larger genome with distributed heterochromatin compared with Arabidopsis Our results indicate the division of labor among plant-specific polymerases, not just in establishing effective silencing via sRNAs and DNA methylation but also in influencing chromatin boundaries.

Indian Himalayan natural Arabidopsis thaliana accessions with abolished miR158 levels exhibit robust miR173-initiated trans-acting cascade silencing

Small RNAs (sRNAs) such as microRNAs (miRNAs) and small interfering RNAs (siRNAs) are short 20-24-nucleotide non-coding RNAs. They are key regulators of gene expression in plants and other organisms. Several 22-nucleotide miRNAs trigger biogenesis cascades of trans-acting secondary siRNAs, which are involved in various developmental and stress responses. Here we show that Himalayan Arabidopsis thaliana accessions having natural mutations in the miR158 locus exhibit robust cascade silencing of the pentatricopeptide repeat (PPR)-like locus. Furthermore, we show that these cascade sRNAs trigger tertiary silencing of a gene involved in transpiration and stomatal opening. The natural deletions or insertions in MIR158 led to improper processing of miR158 precursors, thereby blocking synthesis of mature miR158. Reduced miR158 levels led to increased levels of its target, a pseudo-PPR gene that is targeted by tasiRNAs generated by the miR173 cascade in other accessions. Using sRNA datasets derived from Indian Himalayan accessions, as well as overexpression and knockout lines of miR158, we show that absence of miR158 led to buildup of pseudo-PPR-derived tertiary sRNAs. These tertiary sRNAs mediated robust silencing of a gene involved in stomatal closure in Himalayan accessions lacking miR158 expression. We functionally validated the tertiary phasiRNA that targets NHX2, which encodes a Na⁺ -K⁺ /H⁺ antiporter protein, thereby regulating transpiration and stomatal conductance. Overall, we report the role of the miRNA-TAS-siRNA-pseudogene-tertiary phasiRNA-NHX2 pathway in plant adaptation.

Application of annotation-agnostic RNA sequencing data analysis tools for biomarker discovery in liquid biopsy

RNA sequencing analysis is an important field in the study of extracellular vesicles (EVs), as these particles contain a variety of RNA species that may have diagnostic, prognostic and predictive value. Many of the bioinformatics tools currently used to analyze EV cargo rely on third-party annotations. Recently, analysis of unannotated expressed RNAs has become of interest, since these may provide complementary information to traditional annotated biomarkers or may help refine biological signatures used in machine learning by including unknown regions. Here we perform a comparative analysis of annotation-free and classical read-summarization tools for the analysis of RNA sequencing data generated for EVs isolated from persons with amyotrophic lateral sclerosis (ALS) and healthy donors. Differential expression analysis and digital-droplet PCR validation of unannotated RNAs also confirmed their existence and demonstrates the usefulness of including such potential biomarkers in transcriptome analysis. We show that find-then-annotate methods perform similarly to standard tools for the analysis of known features, and can also identify unannotated expressed RNAs, two of which were validated as overexpressed in ALS samples. We demonstrate that these tools can therefore be used for a stand-alone analysis or easily integrated into current workflows and may be useful for re-analysis as annotations can be integrated post hoc.

Dynamic Regulation of Grapevine's microRNAs in Response to Mycorrhizal Symbiosis and High Temperature

MicroRNAs (miRNAs) are non-coding small RNAs that play crucial roles in plant development and stress responses and can regulate plant interactions with beneficial soil microorganisms such as arbuscular mycorrhizal fungi (AMF). To determine if root inoculation with distinct AMF species affected miRNA expression in grapevines subjected to high temperatures, RNA-seq was conducted in leaves of grapevines inoculated with either Rhizoglomus irregulare or Funneliformis mosseae and exposed to a high-temperature treatment (HTT) of 40 °C for 4 h per day for one week. Our results showed that mycorrhizal inoculation resulted in a better plant physiological response to HTT. Amongst the 195 identified miRNAs, 83 were considered isomiRs, suggesting that isomiRs can be biologically functional in plants. The number of differentially expressed miRNAs between temperatures was higher in mycorrhizal (28) than in non-inoculated plants (17). Several miR396 family members, which target homeobox-leucine zipper proteins, were only upregulated by HTT in mycorrhizal plants. Predicted targets of HTT-induced miRNAs in mycorrhizal plants queried to STRING DB formed networks for Cox complex, and growth and stress-related transcription factors such as SQUAMOSA promoter-binding-like-proteins, homeobox-leucine zipper proteins and auxin receptors. A further cluster related to DNA polymerase was found in R. irregulare inoculated plants. The results presented herein provide new insights into miRNA regulation in mycorrhizal grapevines under heat stress and can be the basis for functional studies of plant-AMF-stress interactions.

Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for the analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = Read length - 40% Adapter length; (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

Degradome Assisted Plant MicroRNA Prediction Under Alternative Annotation Criteria

Current microRNA (miRNA) prediction methods are generally based on annotation criteria that tend to miss potential functional miRNAs. Recently, new miRNA annotation criteria have been proposed that could lead to improvements in miRNA prediction methods in plants. Here, we investigate the effect of the new criteria on miRNA prediction in Arabidopsis thaliana and present a new degradome assisted functional miRNA prediction approach. We investigated the effect by applying the new criteria, and a more permissive criteria on miRNA prediction using existing miRNA prediction tools. We also developed an approach to miRNA prediction that is assisted by the functional information extracted from the analysis of degradome sequencing. We demonstrate the improved performance of degradome assisted miRNA prediction compared to unassisted prediction and evaluate the approach using miRNA differential expression analysis. We observe how the miRNA predictions fit under the different criteria and show a potential novel miRNA that has been missed within Arabidopsis thaliana. Additionally, we introduce a freely available software 'PAREfirst' that employs the degradome assisted approach. The study shows that some miRNAs could be missed due to the stringency of the former annotation criteria, and combining a degradome assisted approach with more permissive miRNA criteria can expand confident miRNA predictions.

Parasitic plant small RNA analyses unveil parasite-specific signatures of microRNA retention, loss, and gain

Parasitism is a successful life strategy that has evolved independently in several families of vascular plants. The genera Cuscuta and Orobanche represent examples of the two profoundly different groups of parasites: one parasitizing host shoots and the other infecting host roots. In this study, we sequenced and described the overall repertoire of small RNAs from Cuscuta campestris and Orobanche aegyptiaca. We showed that C. campestris contains a number of novel microRNAs (miRNAs) in addition to a conspicuous retention of miRNAs that are typically lacking in other Solanales, while several typically conserved miRNAs seem to have become obsolete in the parasite. One new miRNA appears to be derived from a horizontal gene transfer event. The exploratory analysis of the miRNA population (exploratory due to the absence of a full genomic sequence for reference) from the root parasitic O. aegyptiaca also revealed a loss of a number of miRNAs compared to photosynthetic species from the same order. In summary, our study shows partly similar evolutionary signatures in the RNA silencing machinery in both parasites. Our data bear proof for the dynamism of this regulatory mechanism in parasitic plants.

CRISPR/Cas9-mediated fine-tuning of miRNA expression in tetraploid potato

MicroRNAs (miRNAs) are small noncoding RNAs, which modulate the abundance and spatiotemporal accumulation of target mRNAs at transcriptional and post-transcriptional levels and through that play important roles in several biological processes in plants. Here we show that in polyploid species, CRISPR/Cas9 system can be used for fine-tuning of miRNA expression, which can have broader range of applications compared to knock-out mutants. We established the complete pipeline for CRISPR-Cas9-mediated modulation of miRNA expression in potato. It consists of (1) design and assembly of dual sgRNA CRISPR/Cas9 constructs, (2) transient transfection of protoplasts following fast and efficient screening by high resolution melting analysis to select functional sgRNAs, and (3) stable transformation of potato explants with functional sgRNAs and selection of regenerated transgenic lines with desired mutations and desired miRNA abundance based on sequencing and RT-qPCR. We show that miRNA-editing using dual sgRNA approach results in different types of mutations among transgenic lines but also in different alleles of the same plant, which are target site-dependent. The most frequent were short deletions, but we also detected 1-nt insertions (T or G), deletions between two sgRNAs and larger deletions. miRNA abundance correlates with the frequency and type of introduced mutations, as more extensive mutations in more alleles result in lower miRNA abundance. Interestingly, some mutated loci can generate alternative miRNAs, now novel targets were however predicted for those. In all transgenic lines with Cas9 expression, we detected mutations, suggesting high efficiency of Cas9-editing. We confirmed the miRNA-editing efficiency of our optimised approach in two different potato genotypes and three different loci.

A plant tethering system for the functional study of protein-RNA interactions in vivo

The sorting of RNA transcripts dictates their ultimate post-transcriptional fates, such as translation, decay or degradation by RNA interference (RNAi). This sorting of RNAs into distinct fates is mediated by their interaction with RNA-binding proteins. While hundreds of RNA binding proteins have been identified, which act to sort RNAs into different pathways is largely unknown. Particularly in plants, this is due to the lack of reliable protein-RNA artificial tethering tools necessary to determine the mechanism of protein action on an RNA in vivo. Here we generated a protein-RNA tethering system which functions on an endogenous Arabidopsis RNA that is tracked by the quantitative flowering time phenotype. Unlike other protein-RNA tethering systems that have been attempted in plants, our system circumvents the inadvertent triggering of RNAi. We successfully in vivo tethered a protein epitope, deadenylase protein and translation factor to the target RNA, which function to tag, decay and boost protein production, respectively. We demonstrated that our tethering system (1) is sufficient to engineer the downstream fate of an RNA, (2) enables the determination of any protein's function upon recruitment to an RNA, and (3) can be used to discover new interactions with RNA-binding proteins.

Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis

Exosomes carry molecules of great biological and clinical interest, such as miRNAs. The contents of exosomes vary between healthy controls and cancer patients. Therefore, miRNAs and other molecules transported in exosomes are considered a potential source of diagnostic and prognostic biomarkers in cancer. Many miRNAs have been detected in recent years. Consequently, a substantial amount of miRNA-related data comparing patients and healthy individuals is available, which contributes to a better understanding of the initiation, development, malignancy, and metastasis of cancer using non-invasive sampling procedures. However, a re-analysis of available ncRNA data is rare. This study used available data about miRNAs in exosomes comparing healthy individuals and cancer patients to identify possible global changes related to the presence of cancer. A robust transcriptomic analysis identified two common miRNAs (miR-495-3p and miR-543) deregulated in five cancer datasets. They had already been implicated in different cancers but not reported in exosomes circulating in blood. The study also examined their target genes and the implications of these genes for functional processes.

Regulatory role of microRNAs (miRNAs) in the recent development of abiotic stress tolerance of plants

MicroRNAs (miRNAs) are a distinct groups of single-stranded non-coding, tiny regulatory RNAs approximately 20-24 nucleotides in length. miRNAs negatively influence gene expression at the post-transcriptional level and have evolved considerably in the development of abiotic stress tolerance in a number of model plants and economically important crop species. The present review aims to deliver the information on miRNA-mediated regulation of the expression of major genes or Transcription Factors (TFs), as well as genetic and regulatory pathways. Also, the information on adaptive mechanisms involved in plant abiotic stress responses, prediction, and validation of targets, computational tools, and databases available for plant miRNAs, specifically focus on their exploration for engineering abiotic stress tolerance in plants. The regulatory function of miRNAs in plant growth, development, and abiotic stresses consider in this review, which uses high-throughput sequencing (HTS) technologies to generate large-scale libraries of small RNAs (sRNAs) for conventional screening of known and novel abiotic stress-responsive miRNAs adds complexity to regulatory networks in plants. The discoveries of miRNA-mediated tolerance to multiple abiotic stresses, including salinity, drought, cold, heat stress, nutritional deficiency, UV-radiation, oxidative stress, hypoxia, and heavy metal toxicity, are highlighted and discussed in this review.

Biogenesis, Functions, Interactions, and Resources of Non-Coding RNAs in Plants

Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. With advances in RNA sequencing technology and computational methods, bioinformatics resources continue to emerge and update rapidly, including workflow for in silico ncRNA analysis, up-to-date platforms, databases, and tools dedicated to ncRNA identification and functional annotation. In this review, we aim to describe the biogenesis, biological functions, and interactions with DNA, RNA, protein, and microorganism of five major regulatory ncRNAs (miRNA, siRNA, tsRNA, circRNA, lncRNA) in plants. Then, we systematically summarize tools for analysis and prediction of plant ncRNAs, as well as databases. Furthermore, we discuss the silico analysis process of these ncRNAs and present a protocol for step-by-step computational analysis of ncRNAs. In general, this review will help researchers better understand the world of ncRNAs at multiple levels.

The miRNome function transitions from regulating developmental genes to transposable elements during pollen maturation

Animal and plant microRNAs (miRNAs) are essential for the spatio-temporal regulation of development. Together with this role, plant miRNAs have been proposed to target transposable elements (TEs) and stimulate the production of epigenetically active small interfering RNAs. This activity is evident in the plant male gamete containing structure, the male gametophyte or pollen grain. How the dual role of plant miRNAs, regulating both genes and TEs, is integrated during pollen development and which mRNAs are regulated by miRNAs in this cell type at a genome-wide scale are unknown. Here, we provide a detailed analysis of miRNA dynamics and activity during pollen development in Arabidopsis thaliana using small RNA and degradome parallel analysis of RNA end high-throughput sequencing. Furthermore, we uncover miRNAs loaded into the two main active Argonaute (AGO) proteins in the uninuclear and mature pollen grain, AGO1 and AGO5. Our results indicate that the developmental progression from microspore to mature pollen grain is characterized by a transition from miRNAs targeting developmental genes to miRNAs regulating TE activity.

MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts

BACKGROUND

Total-RNA sequencing (total-RNA-seq) allows the simultaneous study of both the coding and the non-coding transcriptome. Yet, computational pipelines have traditionally focused on particular biotypes, making assumptions that are not fullfilled by total-RNA-seq datasets. Transcripts from distinct RNA biotypes vary in length, biogenesis, and function, can overlap in a genomic region, and may be present in the genome with a high copy number. Consequently, reads from total-RNA-seq libraries may cause ambiguous genomic alignments, demanding for flexible quantification approaches.

RESULTS

Here we present Multi-Graph count (MGcount), a total-RNA-seq quantification tool combining two strategies for handling ambiguous alignments. First, MGcount assigns reads hierarchically to small-RNA and long-RNA features to account for length disparity when transcripts overlap in the same genomic position. Next, MGcount aggregates RNA products with similar sequences where reads systematically multi-map using a graph-based approach. MGcount outputs a transcriptomic count matrix compatible with RNA-sequencing downstream analysis pipelines, with both bulk and single-cell resolution, and the graphs that model repeated transcript structures for different biotypes. The software can be used as a python module or as a single-file executable program.

CONCLUSIONS

MGcount is a flexible total-RNA-seq quantification tool that successfully integrates reads that align to multiple genomic locations or that overlap with multiple gene features. Its approach is suitable for the simultaneous estimation of protein-coding, long non-coding and small non-coding transcript concentration, in both precursor and processed forms. Both source code and compiled software are available at https://github.com/hitaandrea/MGcount .

SARS-CoV-2-Encoded MiRNAs Inhibit Host Type I Interferon Pathway and Mediate Allelic Differential Expression of Susceptible Gene

Infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the rapid spread of coronavirus disease 2019 (COVID-19), has generated a public health crisis worldwide. The molecular mechanisms of SARS-CoV-2 infection and virus–host interactions are still unclear. In this study, we identified four unique microRNA-like small RNAs encoded by SARS-CoV-2. SCV2-miR-ORF1ab-1-3p and SCV2-miR-ORF1ab-2-5p play an important role in evasion of type I interferon response through targeting several genes in type I interferon signaling pathway. Particularly worth mentioning is that highly expressed SCV2-miR-ORF1ab-2-5p inhibits some key genes in the host innate immune response, such as IRF7, IRF9, STAT2, OAS1, and OAS2. SCV2-miR-ORF1ab-2-5p has also been found to mediate allelic differential expression of COVID-19-susceptible gene OAS1. In conclusion, these results suggest that SARS-CoV-2 uses its miRNAs to evade the type I interferon response and links the functional viral sequence to the susceptible genetic background of the host.

Reprogramming of RNA silencing triggered by cucumber mosaic virus infection in Arabidopsis

BACKGROUND

RNA silencing has an important role mediating sequence-specific virus resistance in plants. The complex interaction of viruses with RNA silencing involves the loading of viral small interfering RNAs (vsiRNAs) into its host ARGONAUTE (AGO) proteins. As a side effect of their antiviral activity, vsiRNAs loading into AGO proteins can also mediate the silencing of endogenous genes. Here, we analyze at the genome-wide level both aspects of the interference of cucumber mosaic virus (CMV) with the RNA silencing machinery of Arabidopsis thaliana.

RESULTS

We observe CMV-derived vsiRNAs affect the levels of endogenous sRNA classes. Furthermore, we analyze the incorporation of vsiRNAs into AGO proteins with a described antiviral role and the viral suppressor of RNA silencing (VSR) 2b, by combining protein immunoprecipitation with sRNA high-throughput sequencing. Interestingly, vsiRNAs represent a substantial percentage of AGO-loaded sRNAs and displace other endogenous sRNAs. As a countermeasure, the VSR 2b loaded vsiRNAs and mRNA-derived siRNAs, which affect the expression of the genes they derive from. Additionally, we analyze how vsiRNAs incorporate into the endogenous RNA silencing pathways by exploring their target mRNAs using parallel analysis of RNA end (PARE) sequencing, which allow us to identify vsiRNA-targeted genes genome-wide.

CONCLUSIONS

This work exemplifies the complex relationship of RNA viruses with the endogenous RNA silencing machinery and the multiple aspects of virus resistance and virulence that this interaction induces.

Comprehensive Analysis of microRNAs in Human Adult Erythropoiesis

MicroRNAs (miRNAs) are small non-coding RNAs, which play an important role in various cellular and developmental processes. The study of miRNAs in erythropoiesis is crucial to uncover the cellular pathways that are modulated during the different stages of erythroid differentiation. Using erythroid cells derived from human CD34+ hematopoietic stem and progenitor cells (HSPCs)and small RNA sequencing, our study unravels the various miRNAs involved in critical cellular pathways in erythroid maturation. We analyzed the occupancy of erythroid transcription factors and chromatin accessibility in the promoter and enhancer regions of the differentially expressed miRNAs to integrate miRNAs in the transcriptional circuitry of erythropoiesis. Analysis of the targets of the differentially expressed miRNAs revealed novel pathways in erythroid differentiation. Finally, we described the application of Clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-Cas9) based editing of miRNAs to study their function in human erythropoiesis.

An siRNA-guided ARGONAUTE protein directs RNA polymerase V to initiate DNA methylation

In mammals and plants, cytosine DNA methylation is essential for the epigenetic repression of transposable elements and foreign DNA. In plants, DNA methylation is guided by small interfering RNAs (siRNAs) in a self-reinforcing cycle termed RNA-directed DNA methylation (RdDM). RdDM requires the specialized RNA polymerase V (Pol V), and the key unanswered question is how Pol V is first recruited to new target sites without pre-existing DNA methylation. We find that Pol V follows and is dependent on the recruitment of an AGO4-clade ARGONAUTE protein, and any siRNA can guide the ARGONAUTE protein to the new target locus independent of pre-existing DNA methylation. These findings reject long-standing models of RdDM initiation and instead demonstrate that siRNA-guided ARGONAUTE targeting is necessary, sufficient and first to target Pol V recruitment and trigger the cycle of RdDM at a transcribed target locus, thereby establishing epigenetic silencing.

Establishment of Repertoire of Placentome-Associated MicroRNAs and Their Appearance in Blood Plasma Could Identify Early Establishment of Pregnancy in Buffalo (Bubalus bubalis)

Precise early pregnancy diagnosis in dairy animals is of utmost importance for an efficient dairy production system. Not detecting a dairy animal pregnant sufficiently early after the breeding results to extending the unproductive time of their milk production cycle and causes substantial economic loss for a dairy producer. At present, the most conventional and authentic pregnancy confirmation practice in cows and buffaloes is rectal palpation of the reproductive organs at Days 35–40 after insemination, which sometime leads to considering an animal as false pregnant. Other alternative methods available for early pregnancy diagnosis lack either accuracy or reproducibility or require elaborate instrumentation and laboratory setup not feasible to practice at farmers’ doorstep. The present study was aimed at establishment of the microRNA (miRNA) repertoire of the placentome in buffaloes, which could capture the event of the cross talk between a growing embryo and a dam, through fetal cotyledons and maternal caruncles, and thus could hint at the early pregnancy establishment event in ruminants. Total RNA was isolated from buffalo placentome tissues during early stages of pregnancy (at Day < 25 and Days 30–35), and global small RNA analysis was performed by using Illumina single-end read chemistry and Bubalus bubalis genome. A total of 2,199 miRNAs comprising 1,620 conserved and 579 non-conserved miRNAs were identified. Stringent functional miRNA selection criteria could predict 20 miRNAs worth evaluating for their abundance in the plasma of pregnant, non-pregnant, cyclic non-bred, and non-cyclic prepubertal animals. Eight of them (viz., miR-195-5p, miR-708-3p, miR-379-5p, miR-XX1, miR-XX2, miR-130a-3p, miR-200a-3p, and miR-27) displayed typical abundance patterns in the plasma samples of the animals on Day 19 as well as Day 25 post-insemination, thus making them ambiguous candidates for early pregnancy detection. Similarly, higher abundance of miR-200a-3p and miR130a-3p in non-pregnant animals was indicative of their utility for detecting the animals as not pregnant. Most interestingly, miR-XX1 and miR-XX2 were very characteristically abundant only in pregnant animals. In silico target prediction analysis confirmed that these two miRNAs are important regulators of cyclooxygenase-2 (COX-2) and cell adhesion molecule-2 (CADM-2), both of which play a significant role in the implantation process during feto-maternal cross talk. We interpret that circulatory miR-XX1 and miR-XX2 in blood plasma could be the potential biomarkers for early pregnancy detection in buffaloes.

noisyR: enhancing biological signal in sequencing datasets by characterizing random technical noise

High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimizing technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.

Sorghum's Whole-Plant Transcriptome and Proteome Responses to Drought Stress: A Review

Sorghum is a cereal crop with key agronomic traits of drought and heat stress tolerance, making it an ideal food and industrial commodity for hotter and more arid climates. These stress tolerances also present a useful scientific resource for studying the molecular basis for environmental resilience. Here we provide an extensive review of current transcriptome and proteome works conducted with laboratory, greenhouse, or field-grown sorghum plants exposed to drought, osmotic stress, or treated with the drought stress-regulatory phytohormone, abscisic acid. Large datasets from these studies reveal changes in gene/protein expression across diverse signaling and metabolic pathways. Together, the emerging patterns from these datasets reveal that the overall functional classes of stress-responsive genes/proteins within sorghum are similar to those observed in equivalent studies of other drought-sensitive model species. This highlights a monumental challenge of distinguishing key regulatory genes/proteins, with a primary role in sorghum adaptation to drought, from genes/proteins that change in expression because of stress. Finally, we discuss possible options for taking the research forward. Successful exploitation of sorghum research for implementation in other crops may be critical in establishing climate-resilient agriculture for future food security.

Diterpenoid anthraquinones as chemopreventive agents altered microRNA and transcriptome expressions in cancer cells

OBJECTIVE

Cryptotanshinone (CPT) and dihydrotanshinone (DHT) are diterpenoid anthraquinone compounds extracted from traditional Chinese herbal medicine (TCM). Recent studies have shown that CPT regulates the signal transduction pathways via microRNA (miRNA) alterations. However, few studies have investigated the role of DHT in miRNA alterations affecting cell-signaling pathways. This study aimed to investigate the miRNA alterations and post-transcriptional regulation activities of DHT in comparison to CPT.

METHODS

HepG2 and HT-29 cells were treated with DHT or CPT for 72 h. MiRNA, transcription factor encoding mRNA, and downstream gene expression were determined using real-time quantitative PCR. Protein expression was analyzed using western blotting.

RESULTS

The results revealed that CPT and DHT targeted cell proliferation and apoptosis signaling pathways via miR-15a-5p, miR-27a-5p, miR-100-5p, and miR-200a-5p alterations.In silico target predictions showed that downregulation of epidermal growth factor receptor (EGFR) mRNA expression by DHT might also suppress the expression of STAT family proteins and lead to anti-proliferation effects. We also found that, compared to CPT, DHT might possess higher potency in cell growth regulation via multi-miRNA and transcription factor alterations.

CONCLUSION

This study revealed that CPT and DHT targeted cell proliferation and apoptosis signaling pathways via alterations in miRNAs and transcription factors. In addition, the findings of this study suggest that DHT is more potent than CPT in cancer chemopreventive activities. Therefore, DHT at a low dose is a TCM compound with less toxic side effects and may contribute to the development of natural medicine as a potential cancer chemopreventive agent.

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

Turnip mosaic virus in oilseed rape activates networks of sRNA-mediated interactions between viral and host genomes

Virus-induced plant diseases in cultivated plants cause important damages in yield. Although the mechanisms of virus infection are intensely studied at the cell biology level, only little is known about the molecular dialog between the invading virus and the host genome. Here we describe a combinatorial genome-wide approach to identify networks of sRNAs-guided post-transcriptional regulation within local Turnip mosaic virus (TuMV) infection sites in Brassica napus leaves. We show that the induction of host-encoded, virus-activated small interfering RNAs (vasiRNAs) observed in virus-infected tissues is accompanied by site-specific cleavage events on both viral and host RNAs that recalls the activity of small RNA-induced silencing complexes (RISC). Cleavage events also involve virus-derived siRNA (vsiRNA)–directed cleavage of target host transcripts as well as cleavage of viral RNA by both host vasiRNAs and vsiRNAs. Furthermore, certain coding genes act as virus-activated regulatory hubs to produce vasiRNAs for the targeting of other host genes. The observations draw an advanced model of plant-virus interactions and provide insights into the complex regulatory networking at the plant-virus interface within cells undergoing early stages of infection.

Pitzalis et al. use replicative RNAseq, small RNA (sRNA)seq, and parallel analysis of RNA ends (PARE)seq analysis to identify networks of sRNAs-guided post-transcriptional regulation within local Turnip mosaic virus infection sites. This study provides insights into the complex regulatory networking at the plantvirus interface within cells undergoing early stages of infection.

Identification of mRNA Degradome Variation Dependent on Divergent Muscle Mass in Different Pig Breeds

The search is still on for the molecular processes associated with the development and metabolism of skeletal muscles. Selection conducted in farm animals is focused on high muscle mass because it delivers higher economic profit. The present study aimed to shed light on mRNA degradome signals that could be characteristic for molecular processes associated with an abundance of muscle mass and to identify miRNA regulatory networks controlling these processes in pigs applying next-generation-sequencing (NGS). In the study, over 10,000 degraded transcripts were identified per sample, with the highest abundance for genes encoding mitochondrial proteins (COXs, NDs, CYTB, ATP6 and ATP8). Moreover, only 26% of the miRNA targets were found within this degraded transcript pool, which suggested for miRNAs other molecular mechanism at different level of gene expression than mRNA degradation. On the other hand, a small share of the identified degraded transcripts associated with miRNA regulation suggests a different mechanism of mRNA degradation for identified degraded transcropts. Subsequently, most of the miRNA gene degraded targets, such as ENO3, CKM, CRYAB and ADAM19 encode proteins involved in the muscle mass control. The present study showed an interesting dependence between miRNAs and their targets. Nevertheless, the complete view of the miRNA regulatory network could be a subject of further advanced research, which would employ a miRNA transfection procedure in skeletal muscle cell cultures.

NATpare: a pipeline for high-throughput prediction and functional analysis of nat-siRNAs

Natural antisense transcript-derived small interfering RNAs (nat-siRNAs) are a class of functional small RNA (sRNA) that have been found in both plant and animals kingdoms. In plants, these sRNAs have been shown to suppress the translation of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex (RISC) to their sequence-specific mRNA target(s). Current computational tools for classification of nat-siRNAs are limited in number and can be computationally infeasible to use. In addition, current methods do not provide any indication of the function of the predicted nat-siRNAs. Here, we present a new software pipeline, called NATpare, for prediction and functional analysis of nat-siRNAs using sRNA and degradome sequencing data. Based on our benchmarking in multiple plant species, NATpare substantially reduces the time required to perform prediction with minimal resource requirements allowing for comprehensive analysis of nat-siRNAs in larger and more complex organisms for the first time. We then exemplify the use of NATpare by identifying tissue and stress specific nat-siRNAs in multiple Arabidopsis thaliana datasets.

PAREameters: a tool for computational inference of plant miRNA-mRNA targeting rules using small RNA and degradome sequencing data

MicroRNAs (miRNAs) are short, non-coding RNAs that modulate the translation-rate of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to sequence-specific targets. In plants, this typically results in cleavage and subsequent degradation of the mRNA. Degradome sequencing is a high-throughput technique developed to capture cleaved mRNA fragments and thus can be used to support miRNA target prediction. The current criteria used for miRNA target prediction were inferred on a limited number of experimentally validated A. thaliana interactions and were adapted to fit these specific interactions; thus, these fixed criteria may not be optimal across all datasets (organisms, tissues or treatments). We present a new tool, PAREameters, for inferring targeting criteria from small RNA and degradome sequencing datasets. We evaluate its performance using a more extensive set of experimentally validated interactions in multiple A. thaliana datasets. We also perform comprehensive analyses to highlight and quantify the differences between subsets of miRNA-mRNA interactions in model and non-model organisms. Our results show increased sensitivity in A. thaliana when using the PAREameters inferred criteria and that using data-driven criteria enables the identification of additional interactions that further our understanding of the RNA silencing pathway in both model and non-model organisms.

The role of microRNAs in the legume-Rhizobium nitrogen-fixing symbiosis

Under nitrogen starvation, most legume plants form a nitrogen-fixing symbiosis with Rhizobium bacteria. The bacteria induce the formation of a novel organ called the nodule in which rhizobia reside as intracellular symbionts and convert atmospheric nitrogen into ammonia. During this symbiosis, miRNAs are essential for coordinating the various plant processes required for nodule formation and function. miRNAs are non-coding, endogenous RNA molecules, typically 20-24 nucleotides long, that negatively regulate the expression of their target mRNAs. Some miRNAs can move systemically within plant tissues through the vascular system, which mediates, for example, communication between the stem/leaf tissues and the roots. In this review, we summarize the growing number of miRNAs that function during legume nodulation focusing on two model legumes, Lotus japonicus and Medicago truncatula, and two important legume crops, soybean (Glycine max) and common bean (Phaseolus vulgaris). This regulation impacts a variety of physiological processes including hormone signaling and spatial regulation of gene expression. The role of mobile miRNAs in regulating legume nodule number is also highlighted.

Arabidopsis RNA Polymerase IV generates 21-22 nucleotide small RNAs that can participate in RNA-directed DNA methylation and may regulate genes

The plant-specific RNA Polymerase IV (Pol IV) transcribes heterochromatic regions, including many transposable elements (TEs), with the well-described role of generating 24 nucleotide (nt) small interfering RNAs (siRNAs). These siRNAs target DNA methylation back to TEs to reinforce the boundary between heterochromatin and euchromatin. In the male gametophytic phase of the plant life cycle, pollen, Pol IV switches to generating primarily 21-22 nt siRNAs, but the biogenesis and function of these siRNAs have been enigmatic. In contrast to being pollen-specific, we identified that Pol IV generates these 21-22 nt siRNAs in sporophytic tissues, likely from the same transcripts that are processed into the more abundant 24 nt siRNAs. The 21-22 nt forms are specifically generated by the combined activities of DICER proteins DCL2/DCL4 and can participate in RNA-directed DNA methylation. These 21-22 nt siRNAs are also loaded into ARGONAUTE1 (AGO1), which is known to function in post-transcriptional gene regulation. Like other plant siRNAs and microRNAs incorporated into AGO1, we find a signature of genic mRNA cleavage at the predicted target site of these siRNAs, suggesting that Pol IV-generated 21-22 nt siRNAs may function to regulate gene transcript abundance. Our data provide support for the existing model that in pollen Pol IV functions in gene regulation. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

Small noncoding RNA discovery and profiling with sRNAtools based on high-throughput sequencing

Small noncoding RNAs (sRNA/sncRNAs) are generated from different genomic loci and play important roles in biological processes, such as cell proliferation and the regulation of gene expression. Next-generation sequencing (NGS) has provided an unprecedented opportunity to discover and quantify diverse kinds of sncRNA, such as tRFs (tRNA-derived small RNA fragments), phasiRNAs (phased, secondary, small-interfering RNAs), Piwi-interacting RNA (piRNAs) and plant-specific 24-nt short interfering RNAs (siRNAs). However, currently available web-based tools do not provide approaches to comprehensively analyze all of these diverse sncRNAs. This study presents a novel integrated platform, sRNAtools (https://bioinformatics.caf.ac.cn/sRNAtools), that can be used in conjunction with high-throughput sequencing to identify and functionally annotate sncRNAs, including profiling microRNAss, piRNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs and rRNAs and discovering isomiRs, tRFs, phasiRNAs and plant-specific 24-nt siRNAs for up to 21 model organisms. Different modules, including single case, batch case, group case and target case, are developed to provide users with flexible ways of studying sncRNA. In addition, sRNAtools supports different ways of uploading small RNA sequencing data in a very interactive queue system, while local versions based on the program package/Docker/virtureBox are also available. We believe that sRNAtools will greatly benefit the scientific community as an integrated tool for studying sncRNAs.

A benchmarking of pipelines for detecting ncRNAs from RNA-Seq data

Next-Generation Sequencing (NGS) is a high-throughput technology widely applied to genome sequencing and transcriptome profiling. RNA-Seq uses NGS to reveal RNA identities and quantities in a given sample. However, it produces a huge amount of raw data that need to be preprocessed with fast and effective computational methods. RNA-Seq can look at different populations of RNAs, including ncRNAs. Indeed, in the last few years, several ncRNAs pipelines have been developed for ncRNAs analysis from RNA-Seq experiments. In this paper, we analyze eight recent pipelines (iSmaRT, iSRAP, miARma-Seq, Oasis 2, SPORTS1.0, sRNAnalyzer, sRNApipe, sRNA workbench) which allows the analysis not only of single specific classes of ncRNAs but also of more than one ncRNA classes. Our systematic performance evaluation aims at guiding users to select the appropriate pipeline for processing each ncRNA class, focusing on three key points: (i) accuracy in ncRNAs identification, (ii) accuracy in read count estimation and (iii) deployment and ease of use.

The RNA workbench 2.0: next generation RNA data analysis

RNA has become one of the major research topics in molecular biology. As a central player in key processes regulating gene expression, RNA is in the focus of many efforts to decipher the pathways that govern the transition of genetic information to a fully functional cell. As more and more researchers join this endeavour, there is a rapidly growing demand for comprehensive collections of tools that cover the diverse layers of RNA-related research. However, increasing amounts of data, from diverse types of experiments, addressing different aspects of biological questions need to be consolidated and integrated into a single framework. Only then is it possible to connect findings from e.g. RNA-Seq experiments and methods for e.g. target predictions. To address these needs, we present the RNA Workbench 2.0 , an updated online resource for RNA related analysis. With the RNA Workbench we created a comprehensive set of analysis tools and workflows that enables researchers to analyze their data without the need for sophisticated command-line skills. This update takes the established framework to the next level, providing not only a containerized infrastructure for analysis, but also a ready-to-use platform for hands-on training, analysis, data exploration, and visualization. The new framework is available at https://rna.usegalaxy.eu , and login is free and open to all users. The containerized version can be found at https://github.com/bgruening/galaxy-rna-workbench.