Types Of sRNAs Research Articles

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction.

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

SRNAminer: A multifunctional toolkit for next-generation sequencing small RNA data mining in plants

Small RNAs (sRNAs), found extensively in plants, play an essential role in plant growth and development. Although various sRNA analysis tools have been developed for plants, the use of most of them depends on programming and command-line environments, which is a challenge for many wet-lab biologists. Furthermore, current sRNA analysis tools mostly focus on the analysis of certain type of sRNAs and are resource-intensive, normally demanding an immense amount of time and effort to learn the use of numerous tools or scripts and assemble them into a workable pipeline to get the final results. Here, we present sRNAminer, a powerful stand-alone toolkit with a user-friendly interface that integrates all common functions for the analysis of three major types of plant sRNAs: microRNAs (miRNAs), phased small interfering RNAs (phasiRNAs), and heterochromatic siRNAs (hc-siRNAs). We constructed a curated or “golden” set of MIRNA and PHAS loci, which was used to assess the performance of sRNAminer in comparison to other existing tools. The results showed that sRNAminer outperformed these tools in multiple aspects, highlighting its functionality. In addition, to enable an efficient evaluation of sRNA annotation results, we developed Integrative Genomics Viewer (IGV)-sRNA, a modified genome browser optimized from IGV and we incorporated it as a functional module in sRNAminer. IGV-sRNA can display a wealth of sRNA-specific features, enabling a more comprehensive understanding of sRNA data. sRNAminer and IGV-sRNA are both platform-independent software that can be run under all operating systems. They are now freely available at https://github.com/kli28/sRNAminer and https://gitee.com/CJchen/IGV-sRNA.

The apple Argonaute gene MdAGO1 modulates salt tolerance

Salinity is a significant environmental challenge that detrimentally affects the yield and quality of plants. The Argonaute (AGO) family proteins are core effectors of RNAi pathways in eukaryotes. Different AGOs bind different types of sRNAs and participate in different silencing pathways and physiological processes. The Argonaute1 (AGO1) protein binds microRNAs and post-transcriptionally inhibits gene expression in the cytoplasm. In addition, AGO1 directly binds to the promoter region of genes to promote transcription in the stress responses. In this study, we isolated the AGO family gene MdAGO1 from apple (Malus domestica). MdAGO1 encodes a protein located in the nucleus and cytoplasm. MdAGO1 expression was significantly induced by salt stress. We employed MdAGO1-RNAi transgenic apple plants, MdAGO1 overexpressing transgenic apple calli, and Arabidopsis thaliana to investigate the role of MdAGO1 in salt stress. We exposed all of the genotypes to salt stress and showed that MdAGO1 played a role in scavenging reactive oxygen species, maintaining ion balance, and increasing the accumulation of polyamines in the plants under salt stress. In addition, the MdAGO1-RNAi apple lines exhibited low photosynthetic capacity under salt stress. Taken together, these results reveal that MdAGO1 positively regulates apple salt tolerance.

Detection and Quantification of Small Noncoding RNAs in Marine Diatoms.

Endogenous small noncoding RNAs (sRNAs) are a large family of essential regulators of gene expression in both eukaryotes and prokaryotes. Various types of sRNAs with different size and mapping to different genome locations have been recently identified in diatoms, a successful group of phytoplankton in the marine environment. However, their biogenesis and regulatory function are still largely unknown and unexplored in these microalgae, also due to the lack of methods for their experimental analysis. Herein, we present a point-by-point description of the protocols for detection and quantification of sRNAs by Northern-blot analysis and quantitative stem-loop RT-PCR, established in the diatom molecular model specie Phaeodactylum tricornutum.

Finding differentially expressed sRNA-Seq regions with srnadiff.

Small RNAs (sRNAs) encompass a great variety of molecules of different kinds, such as microRNAs, small interfering RNAs, Piwi-associated RNA, among others. These sRNAs have a wide range of activities, which include gene regulation, protection against virus, transposable element silencing, and have been identified as a key actor in determining the development of the cell. Small RNA sequencing is thus routinely used to assess the expression of the diversity of sRNAs, usually in the context of differentially expression, where two conditions are compared. Tools that detect differentially expressed microRNAs are numerous, because microRNAs are well documented, and the associated genes are well defined. However, tools are lacking to detect other types of sRNAs, which are less studied, and whose precursor RNA is not well characterized. We present here a new method, called srnadiff, which finds all kinds of differentially expressed sRNAs. To the extent of our knowledge, srnadiff is the first tool that detects differentially expressed sRNAs without the use of external information, such as genomic annotation or additional sequences of sRNAs.

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants.

MicroRNAs (miRNAs) are 20- to 24-nucleotide (nt) endogenous small RNAs (sRNAs) extensively existing in plants and animals that play potent roles in regulating gene expression at the post-transcriptional level. Sequencing sRNA libraries by Next Generation Sequencing (NGS) methods has been widely employed to identify and analyze miRNA transcriptomes in the last decade, resulting in a rapid increase of miRNA discovery. However, two major challenges arise in plant miRNA annotation due to increasing depth of sequenced sRNA libraries as well as the size and complexity of plant genomes. First, many other types of sRNAs, in particular, short interfering RNAs (siRNAs) from sRNA libraries, are erroneously annotated as miRNAs by many computational tools. Second, it becomes an extremely time-consuming process for analyzing miRNA transcriptomes in plant species with large and complex genomes. To overcome these challenges, we recently upgraded miRDeep-P (a popular tool for miRNA transcriptome analyses) to miRDeep-P2 (miRDP2 for short) by employing a new filtering strategy, overhauling the scoring algorithm and incorporating newly updated plant miRNA annotation criteria. We tested miRDP2 against sequenced sRNA populations in five representative plants with increasing genomic complexity, including Arabidopsis, rice, tomato, maize and wheat. The results indicate that miRDP2 processed these tasks with very high efficiency. In addition, miRDP2 outperformed other prediction tools regarding sensitivity and accuracy. Taken together, our results demonstrate miRDP2 as a fast and accurate tool for analyzing plant miRNA transcriptomes, therefore a useful tool in helping the community better annotate miRNAs in plants.

Computational investigation of small RNAs in the establishment of root nodules and arbuscular mycorrhiza in leguminous plants.

Many small RNAs have been confirmed to play important roles in the development of root nodules and arbuscular mycorrhiza. In this study, we carried out the identification of certain small RNAs in leguminous plants (Medicago truncatula, soybean, peanut and common bean), such as miRNAs, tRFs and srRNAs, as well as the computational investigation of their regulations. Thirty miRNAs were predicted to be involved in establishing root nodules and mycorrhiza, and 12 of them were novel in common bean and peanut. The generation of tRFs in M. truncatula was not associated with tRNA gene frequencies and codon usage. Six tRFs exhibited different expressions in mycorrhiza and root nodules. Moreover, srRNA5.8S in M. truncatula was generated from the regions with relatively low conservation at the rRNA 3' terminal. The protein-protein interactions between the proteins encoded by the target genes of miRNAs, tRFs and srRNAs were computed. The regulation of these three types of sRNAs in the symbiosis between leguminous plants and microorganisms is not a single regulation of certain signaling or metabolic pathways but a global regulation for the plants to own growth or specific events in symbiosis.

Generation of different sizes and classes of small RNAs in barley is locus, chromosome and/or cultivar-dependent.

BackgroundVarious small RNA (sRNA) sizes and varieties have been identified, but their relationship as well as relationship with their origins and allocations have not been well understood or investigated.ResultsBy comparing sRNAs generated from two barley cultivars, Golden Promise (GP) and Pallas, we identified that the generation of different sizes and types of sRNAs in barley was locus-, chromosome- and/or cultivar-dependent. 20-nt sRNAs mainly comprising miRNAs and chloroplast-derived sRNAs were significantly over-expressed in Pallas vs. GP on chromosomes 3H and 6H. MiRNAs-enriched 21-nt sRNAs were significantly over-expressed in Pallas vs. GP only on chromosome 4H. On chromosome 5H this size of sRNAs was significantly under-expressed in Pallas, so were 22-nt sRNAs mainly comprising miRNAs and repeat-derived sRNAs. 24-nt sRNAs mostly derived from repeats were evenly distributed in all chromosomes and expressed similarly between GP and Pallas. Unlike other sizes of sRNAs, 24-nt sRNAs were little conserved in other plant species. Abundant sRNAs were mostly generated from 3’ terminal regions of chromosome 1H and 5’ terminal regions of chromosome 5H. Over-expressed miRNAs in GP vs. Pallas primarily function in stress responses and iron-binding.ConclusionsOur study indicates that 23−24-nt sRNAs may be linked to repressive chromatin modifications and function in genome stability while 20−21-nt sRNAs may be important for the cultivar specificity. This study provides a novel insight into the mechanism of sRNA expression and function in barley.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3023-5) contains supplementary material, which is available to authorized users.

Virus-derived small RNAs in the penaeid shrimp Fenneropenaeus chinensis during acute infection of the DNA virus WSSV.

Small interfering RNAs (siRNAs) and microRNAs (miRNAs) are two classes of small RNAs (sRNAs) that are critical for virus-host interplay via the RNA interference (RNAi) pathway. One virus-derived siRNA and numerous miRNAs has been reported for the double-stranded DNA virus white spot syndrome virus (WSSV), however, the expression profiles of these different types of sRNAs have not been assessed. Here, by sequencing the sRNAs and mRNAs of WSSV-infected Chinese shrimp (Fenneropenaeus chinensis), we found that the viral transcripts were universally targeted by WSSV-derived siRNAs, supporting a pivotal role for RNAi in the anti-viral immunity of shrimp. The genesis of WSSV-derived siRNAs was associated with long RNA structures. Moreover, by separating miRNAs from siRNAs, 12 WSSV miRNAs were identified. Investigation of conserved viral miRNA targets in different host species indicated the involvement of viral miRNAs in host immune responses. Collectively, our data provide new insights into the role of the RNAi pathway in the interplay between DNA viruses and crustaceans.

Ms1, a novel sRNA interacting with the RNA polymerase core in mycobacteria.

Small RNAs (sRNAs) are molecules essential for a number of regulatory processes in the bacterial cell. Here we characterize Ms1, a sRNA that is highly expressed in Mycobacterium smegmatis during stationary phase of growth. By glycerol gradient ultracentrifugation, RNA binding assay, and RNA co-immunoprecipitation, we show that Ms1 interacts with the RNA polymerase (RNAP) core that is free of the primary sigma factor (σA) or any other σ factor. This contrasts with the situation in most other species where it is 6S RNA that interacts with RNAP and this interaction requires the presence of σA. The difference in the interaction of the two types of sRNAs (Ms1 or 6S RNA) with RNAP possibly reflects the difference in the composition of the transcriptional machinery between mycobacteria and other species. Unlike Escherichia coli, stationary phase M. smegmatis cells contain relatively few RNAP molecules in complex with σA. Thus, Ms1 represents a novel type of small RNAs interacting with RNAP.

Major differences in microRNA quantification are platform and sequence dependent

Background Small RNAs (sRNAs) are known to play an important regulatory role in a wide range of organisms and biological processes through expression regulation of a diverse array of genes. Several classes of sRNA including plant microRNAs (miRNAs), small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs) carry an O-methyl modification at their 3 termini, and this is suspected to complicate their accurate quantification. miRNA precursors have been detected in cell lines and other tissues, where their amount does not necessarily correlate with the amount of their mature miRNA due to different regulation processes controlling their biogenesis. Methods currently used to identify and quantify sRNAs face unique challenges due to their short length, as well as the high sequence similarities between them. The correct identification, discrimination and profiling of the different types of sRNAs, including their available isoforms, are crucial for understanding of the regulatory networks they are involved in.

Small RNAs, DNA methylation and transposable elements in wheat

BackgroundMore than 80% of the wheat genome is composed of transposable elements (TEs). Since active TEs can move to different locations and potentially impose a significant mutational load, their expression is suppressed in the genome via small non-coding RNAs (sRNAs). sRNAs guide silencing of TEs at the transcriptional (mainly 24-nt sRNAs) and post-transcriptional (mainly 21-nt sRNAs) levels. In this study, we report the distribution of these two types of sRNAs among the different classes of wheat TEs, the regions targeted within the TEs, and their impact on the methylation patterns of the targeted regions.ResultsWe constructed an sRNA library from hexaploid wheat and developed a database that included our library and three other publicly available sRNA libraries from wheat. For five completely-sequenced wheat BAC contigs, most perfectly matching sRNAs represented TE sequences, suggesting that a large fraction of the wheat sRNAs originated from TEs. An analysis of all wheat TEs present in the Triticeae Repeat Sequence database showed that sRNA abundance was correlated with the estimated number of TEs within each class. Most of the sRNAs perfectly matching miniature inverted repeat transposable elements (MITEs) belonged to the 21-nt class and were mainly targeted to the terminal inverted repeats (TIRs). In contrast, most of the sRNAs matching class I and class II TEs belonged to the 24-nt class and were mainly targeted to the long terminal repeats (LTRs) in the class I TEs and to the terminal repeats in CACTA transposons. An analysis of the mutation frequency in potentially methylated sites revealed a three-fold increase in TE mutation frequency relative to intron and untranslated genic regions. This increase is consistent with wheat TEs being preferentially methylated, likely by sRNA targeting.ConclusionsOur study examines the wheat epigenome in relation to known TEs. sRNA-directed transcriptional and post-transcriptional silencing plays important roles in the short-term suppression of TEs in the wheat genome, whereas DNA methylation and increased mutation rates may provide a long-term mechanism to inactivate TEs.