Different classes of small RNAs (sRNAs) refine the expression of numerous genes in higher eukaryotes by directing protein partners to complementary nucleic acids, where they mediate gene silencing. Plants encode a unique class of sRNAs, called trans-acting small interfering RNAs (tasiRNAs), which post-transcriptionally regulate protein-coding transcripts, as do microRNAs (miRNAs), and both sRNA classes control development through their targets. TasiRNA biogenesis requires multiple components of the siRNA pathway and also miRNAs. But while 21mer siRNAs originating from transgenes can mediate silencing across several cell layers, miRNA action seems spatially restricted to the producing or closely surrounding cells.
We have previously described the isolation of a genetrap reporter line for TAS3a, the major locus producing AUXIN RESPONS FACTOR (ARF)-regulating tasiRNAs in the Arabidopsis shoot. Its activity is limited to the adaxial (upper) side of leaf primordia, thus spatially isolated from ARF-activities, which are located in the abaxial (lower) side. We show here by in situ hybridization and reporter fusions that the silencing activities of ARF-regulating tasiRNAs are indeed manifested non-cell autonomously to spatially control ARF activities.
Endogenous tasiRNAs are thus mediators of a mobile developmental signal and might provide effective gene silencing at a distance beyond the reach of most miRNAs.
In higher eukaryotes, small RNAs play a role in regulating gene expression. Overexpression (OE) lines of Arabidopsis thaliana purple acid phosphatase 2 (AtPAP2) were shown to grow faster and exhibit higher ATP and sugar contents. Leaf microarray studies showed that many genes involved in microRNAs (miRNAs) and trans-acting siRNAs (tasiRNAs) biogenesis were significantly changed in the fast-growing lines. In this study, the sRNA profiles of the leaf and the root of 20-day-old plants were sequenced and the impacts of high energy status on sRNA expression were analyzed.
9-13 million reads from each library were mapped to genome. miRNAs, tasiRNAs and natural antisense transcripts-generated small interfering RNAs (natsiRNAs) were identified and compared between libraries. In the leaf of OE lines, 15 known miRNAs increased in abundance and 9 miRNAs decreased in abundance, whereas in the root of OE lines, 2 known miRNAs increased in abundance and 9 miRNAs decreased in abundance. miRNAs with increased abundance in the leaf and root samples of both OE lines (miR158b and miR172a/b) were predicted to target mRNAs coding for Dof zinc finger protein and Apetala 2 (AP2) proteins, respectively. Furthermore, a significant change in the miR173-tasiRNAs-PPR/TPR network was observed in the leaves of both OE lines.
In this study, the impact of high energy content on the sRNA profiles of Arabidopsis is reported. While the abundance of many stress-induced miRNAs is unaltered, the abundance of some miRNAs related to plant growth and development (miR172 and miR319) is elevated in the fast-growing lines. An induction of miR173-tasiRNAs-PPR/TPR network was also observed in the OE lines. In contrast, only few cis- and trans-natsiRNAs are altered in the fast-growing lines.
Chloroplasts; Mitochondria; miRNAs; MORF; PPR; tasiRNAs and natsiRNAs
In plants, small interfering RNAs (siRNAs) can trigger a silencing signal that may spread within a tissue to adjacent cells or even systemically to other organs. Movement of the signal is initially limited to a few cells, but in some cases the signal can be amplified and travel over larger distances. How far silencing initiated by other classes of plant small RNAs (sRNAs) than siRNAs can extend has been less clear. Using a system based on the silencing of the CH42 gene, we have tracked the mobility of silencing signals initiated in phloem companion cells by artificial microRNAs (miRNA) and trans-acting siRNA (tasiRNA) that have the same primary sequence. In this system, both the ta-siRNA and the miRNA act at a distance. Non-autonomous effects of the miRNA can be triggered by several different miRNA precursors deployed as backbones. While the tasiRNA also acts non-autonomously, it has a much greater range than the miRNA or hairpin-derived siRNAs directed against CH42, indicating that biogenesis can determine the non-autonomous effects of sRNAs. In agreement with this hypothesis, the silencing signals initiated by different sRNAs differ in their genetic requirements.
Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.
Small non-coding RNAs (21 to 24 nucleotides) regulate a number of developmental processes in plants and animals by silencing genes using multiple mechanisms. Among these, the most conserved classes are microRNAs (miRNAs) and small interfering RNAs (siRNAs), both of which are produced by RNase III-like enzymes called Dicers. Many plant miRNAs play critical roles in nutrient homeostasis, developmental processes, abiotic stress and pathogen responses. Currently, only 70 miRNA have been identified in soybean.
We utilized Illumina's SBS sequencing technology to generate high-quality small RNA (sRNA) data from four soybean (Glycine max) tissues, including root, seed, flower, and nodules, to expand the collection of currently known soybean miRNAs. We developed a bioinformatics pipeline using in-house scripts and publicly available structure prediction tools to differentiate the authentic mature miRNA sequences from other sRNAs and short RNA fragments represented in the public sequencing data.
The combined sequencing and bioinformatics analyses identified 129 miRNAs based on hairpin secondary structure features in the predicted precursors. Out of these, 42 miRNAs matched known miRNAs in soybean or other species, while 87 novel miRNAs were identified. We also predicted the putative target genes of all identified miRNAs with computational methods and verified the predicted cleavage sites in vivo for a subset of these targets using the 5' RACE method. Finally, we also studied the relationship between the abundance of miRNA and that of the respective target genes by comparison to Solexa cDNA sequencing data.
Our study significantly increased the number of miRNAs known to be expressed in soybean. The bioinformatics analysis provided insight on regulation patterns between the miRNAs and their predicted target genes expression. We also deposited the data in a soybean genome browser based on the UCSC Genome Browser architecture. Using the browser, we annotated the soybean data with miRNA sequences from four tissues and cDNA sequencing data. Overlaying these two datasets in the browser allows researchers to analyze the miRNA expression levels relative to that of the associated target genes. The browser can be accessed at http://digbio.missouri.edu/soybean_mirna/.
Tobamoviruses encode a silencing suppressor that binds small RNA (sRNA) duplexes
in vitro and supposedly in vivo to
counteract antiviral silencing. Here, we used sRNA deep-sequencing combined with
transcriptome profiling to determine the global impact of tobamovirus infection
on Arabidopsis sRNAs and their mRNA targets. We found that
infection of Arabidopsis plants with Oilseed rape
mosaic tobamovirus causes a global size-specific enrichment of
miRNAs, ta-siRNAs, and other phased siRNAs. The observed patterns of sRNA
enrichment suggest that in addition to a role of the viral silencing suppressor,
the stabilization of sRNAs might also occur through association with unknown
host effector complexes induced upon infection. Indeed, sRNA enrichment concerns
primarily 21-nucleotide RNAs with a 5′-terminal guanine. Interestingly,
ORMV infection also leads to accumulation of novel miRNA-like sRNAs from miRNA
precursors. Thus, in addition to canonical miRNAs and miRNA*s, miRNA
precursors can encode additional sRNAs that may be functional under specific
conditions like pathogen infection. Virus-induced sRNA enrichment does not
correlate with defects in miRNA-dependent ta-siRNA biogenesis nor with global
changes in the levels of mRNA and ta-siRNA targets suggesting that the enriched
sRNAs may not be able to significantly contribute to the normal activity of
pre-loaded RISC complexes. We conclude that tobamovirus infection induces the
stabilization of a specific sRNA pool by yet unknown effector complexes. These
complexes may sequester viral and host sRNAs to engage them in yet unknown
mechanisms involved in plant:virus interactions.
Small non-coding RNAs (sRNAs) are regarded as important regulators in prokaryotes and play essential roles in diverse cellular processes. Xanthomonas oryzae pathovar oryzae (Xoo) is an important plant pathogenic bacterium which causes serious bacterial blight of rice. However, little is known about the number, genomic distribution and biological functions of sRNAs in Xoo.
Here, we performed a systematic screen to identify sRNAs in the Xoo strain PXO99. A total of 850 putative non-coding RNA sequences originated from intergenic and gene antisense regions were identified by cloning, of which 63 were also identified as sRNA candidates by computational prediction, thus were considered as Xoo sRNA candidates. Northern blot hybridization confirmed the size and expression of 6 sRNA candidates and other 2 cloned small RNA sequences, which were then added to the sRNA candidate list. We further examined the expression profiles of the eight sRNAs in an hfq deletion mutant and found that two of them showed drastically decreased expression levels, and another exhibited an Hfq-dependent transcript processing pattern. Deletion mutants were obtained for seven of the Northern confirmed sRNAs, but none of them exhibited obvious phenotypes. Comparison of the proteomic differences between three of the ΔsRNA mutants and the wild-type strain by two-dimensional gel electrophoresis (2-DE) analysis showed that these sRNAs are involved in multiple physiological and biochemical processes.
We experimentally verified eight sRNAs in a genome-wide screen and uncovered three Hfq-dependent sRNAs in Xoo. Proteomics analysis revealed Xoo sRNAs may take part in various metabolic processes. Taken together, this work represents the first comprehensive screen and functional analysis of sRNAs in rice pathogenic bacteria and facilitates future studies on sRNA-mediated regulatory networks in this important phytopathogen.
Small RNAs (sRNAs) are 20–25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci.
To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus.
CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques.
CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.
small RNA; sRNA; microRNA; miRNA; high throughput sequencing; sRNA loci; expression level; pattern; sRNAome
MicroRNAs (miRNAs) are small RNAs (sRNAs) approximately 21 nucleotides in length that negatively control gene expression by cleaving or inhibiting the translation of target gene transcripts. Within this context, miRNAs and siRNAs are coming to the forefront as molecular mediators of gene regulation in plant responses to annual temperature cycling and cold stress. For this reason, we chose to identify and characterize the conserved and non-conserved miRNA component of peach (Prunus persica (L.) Batsch) focusing our efforts on both the recently released whole genome sequence of peach and sRNA transcriptome sequences from two tissues representing non-dormant leaves and dormant leaf buds. Conserved and non-conserved miRNAs, and their targets were identified. These sRNA resources were used to identify cold-responsive miRNAs whose gene targets co-localize with previously described QTLs for chilling requirement (CR).
Analysis of 21 million peach sRNA reads allowed us to identify 157 and 230 conserved and non-conserved miRNA sequences. Among the non-conserved miRNAs, we identified 205 that seem to be specific to peach. Comparative genome analysis between peach and Arabidopsis showed that conserved miRNA families, with the exception of miR5021, are similar in size. Sixteen of these conserved miRNA families are deeply rooted in land plant phylogeny as they are present in mosses and/or lycophytes. Within the other conserved miRNA families, five families (miR1446, miR473, miR479, miR3629, and miR3627) were reported only in tree species (Populustrichocarpa, Citrus trifolia, and Prunus persica). Expression analysis identified several up-regulated or down-regulated miRNAs in winter buds versus young leaves. A search of the peach proteome allowed the prediction of target genes for most of the conserved miRNAs and a large fraction of non-conserved miRNAs. A fraction of predicted targets in peach have not been previously reported in other species. Several conserved and non-conserved miRNAs and miRNA-regulated genes co-localize with Quantitative Trait Loci (QTLs) for chilling requirement (CR-QTL) and bloom date (BD-QTL).
In this work, we identified a large set of conserved and non-conserved miRNAs and describe their evolutionary footprint in angiosperm lineages. Several of these miRNAs were induced in winter buds and co-localized with QTLs for chilling requirement and bloom date thus making their gene targets potential candidates for mediating plant responses to cold stress. Several peach homologs of genes participating in the regulation of vernalization in Arabidopsis were identified as differentially expressed miRNAs targets, potentially linking these gene activities to cold responses in peach dormant buds. The non-conserved miRNAs may regulate cellular, physiological or developmental processes specific to peach and/or other tree species.
microRNAs; Distribution; Expression; Cold stress; Chilling requirement; Bud development
The importance of small RNA (sRNA) regulators has been recognized across all domains of life. In bacteria, sRNAs typically control the expression of virulence and stress response genes via antisense base pairing with mRNA targets. Originally dubbed “non-coding RNAs,” a number of bacterial antisense sRNAs have been found to encode functional proteins. Although very few of these dual-function sRNAs have been characterized, they have been found in both gram-negative and gram-positive organisms. Among the few known examples, the functions and mechanisms of regulation by dual-function sRNAs are variable. Some dual-function sRNAs depend on the RNA chaperone Hfq for base pairing-dependent regulation (riboregulation); this feature appears so far exclusive to gram-negative bacterial sRNAs. Other variations can be found in the spatial organization of the coding region with respect to the riboregulation determinants. How the functions of encoded proteins relate to riboregulation is for the most part not understood. However, in one case it appears that there is physiological redundancy between protein and riboregulation functions. This mini-review focuses on the two best-studied bacterial dual-function sRNAs: RNAIII from Staphylococcus aureus and SgrS from Escherichia coli and includes a discussion of what is known about the structure, function and physiological roles of these sRNAs as well as what questions remain outstanding.
Hfq; RNAIII; glucose phosphate stress; SgrS; riboregulation
Small non-coding RNAs (sRNAs) are widespread effectors of post-transcriptional gene regulation in bacteria. Currently extensive information exists on the sRNAs of Listeria monocytogenes expressed during growth in extracellular environments. We used deep sequencing of cDNAs obtained from fractioned RNA (<500 nt) isolated from extracellularly growing bacteria and from L. monocytogenes infected macrophages to catalog the sRNA repertoire during intracellular bacterial growth. Here, we report on the discovery of 150 putative regulatory RNAs of which 71 have not been previously described. A total of 29 regulatory RNAs, including small non-coding antisense RNAs, are specifically expressed intracellularly. We validated highly expressed sRNAs by northern blotting and demonstrated by the construction and characterization of isogenic mutants of rli31, rli33-1 and rli50* for intracellular expressed sRNA candidates, that their expression is required for efficient growth of bacteria in macrophages. All three mutants were attenuated when assessed for growth in mouse and insect models of infection. Comparative genomic analysis revealed the presence of lineage specific sRNA candidates and the absence of sRNA loci in genomes of naturally occurring infection-attenuated bacteria, with additional loss in non-pathogenic listerial genomes. Our analyses reveal extensive sRNA expression as an important feature of bacterial regulation during intracellular growth.
Transcription factors (TFs), microRNAs (miRNAs), small interfering RNAs (siRNAs) and other functional non-coding small RNAs (sRNAs) are important gene regulators. Comparison of sRNA expression profiles between transgenic barley over-expressing a drought tolerant TF (TaDREB3) and non-transgenic control barley revealed many group-specific sRNAs. In addition, 42% of the shared sRNAs were differentially expressed between the two groups (|log2| >1). Furthermore, TaDREB3-derived sRNAs were only detected in transgenic barley despite the existence of homologous genes in non-transgenic barley. These results demonstrate that the TF strongly affects the expression of sRNAs and siRNAs could in turn affect the TF stability. The TF also affects size distribution and abundance of sRNAs including miRNAs. About half of the sRNAs in each group were derived from chloroplast. A sRNA derived from tRNA-His(GUG) encoded by the chloroplast genome is the most abundant sRNA, accounting for 42.2% of the total sRNAs in transgenic barley and 28.9% in non-transgenic barley. This sRNA, which targets a gene (TC245676) involved in biological processes, was only present in barley leaves but not roots. 124 and 136 miRNAs were detected in transgenic and non-transgenic barley, respectively. miR156 was the most abundant miRNA and up-regulated in transgenic barley, while miR168 was the most abundant miRNA and up-regulated in non-transgenic barley. Eight out of 20 predicted novel miRNAs were differentially expressed between the two groups. All the predicted novel miRNA targets were validated using a degradome library. Our data provide an insight into the effect of TF on the expression of sRNAs in barley.
The rice blast fungus, Magnaporthe oryzae is a destructive pathogen of rice and other related crops, causing significant yield losses worldwide. Endogenous small RNAs (sRNAs), including small interfering RNAs (siRNAs) and microRNAs (miRNAs) are critical components of gene regulation in many eukaryotic organisms. Recently several new species of sRNAs have been identified in fungi. This fact along with the availability of genome sequence makes M. oryzae a compelling target for sRNA profiling. We have examined sRNA species and their biosynthetic genes in M. oryzae, and the degree to which these elements regulate fungal stress responses. To this end, we have characterized sRNAs under different physiological stress conditions, which had not yet been examined in this fungus.
The resulting libraries are composed of more than 37 million total genome matched reads mapping to intergenic regions, coding sequences, retrotransposons, inverted, tandem, and other repeated regions of the genome with more than half of the small RNAs arising from intergenic regions. The 24 nucleotide (nt) size class of sRNAs was predominant. A comparison to transcriptional data of M. oryzae undergoing the same physiological stresses indicates that sRNAs play a role in transcriptional regulation for a small subset of genes. Support for this idea comes from generation and characterization of mutants putatively involved in sRNAs biogenesis; our results indicate that the deletion of Dicer-like genes and an RNA-Dependent RNA Polymerase gene increases the transcriptional regulation of this subset of genes, including one involved in virulence.
Various physiological stressors and in planta conditions alter the small RNA profile of the rice blast fungus. Characterization of sRNA biosynthetic mutants helps to clarify the role of sRNAs in transcriptional control.
Small RNA; Magnaporthe oryzae; Rice blast fungus; siRNA
Bacterial small non-coding RNA (sRNA) plays an important role in post-transcriptional gene regulation. Although the number of annotated sRNA is steadily increasing, their functional characterization is still lagging behind. Various computational strategies for finding sRNA–mRNA interactions, and thus putative sRNA targets, were developed. Most of them suffer from a high false positive rate. Here, we present a qualitative model to simulate the effect of an sRNA on the translation initiation of a potential target. Information about the ribosome–mRNA interaction, sRNA–mRNA interaction and expression information from deep sequencing experiments is integrated to calculate the change in translation initiation complex formation, as a proxy for translational activity. This model can be used to post-evaluate predicted targets, hence condensing the list of potential targets. We show that our translation initiation model, under the influence of an sRNA, can successfully simulate thirteen out of fifteen tested sRNA–mRNA interactions in a qualitative manner. To show the gain in specificity, we applied our method to a target search for the Escherichia coli sRNA RyhB. Compared with simple target prediction without post-evaluation, we reduce the number of targets to less than one fourth potential targets, considerably reducing the burden of experimental validation.
sRNA; sRNA target prediction; translation initiation
Small non-coding RNAs (smRNAs) are known to have major roles in gene regulation in eukaryotes. In plants, knowledge of the biogenesis and mechanisms of action of smRNA classes including microRNAs (miRNAs), short interfering RNAs (siRNAs), and trans-acting siRNAs (tasiRNAs) has been gained mostly through studies with Arabidopsis. In recent years, high throughput sequencing of smRNA populations has enabled extension of knowledge from model systems to plants with larger, more complex genomes. Soybean (Glycine max) now has many genomics resources available including a complete genome sequence and predicted gene models. Relatively little is known, however, about the full complement of its endogenous smRNAs populations and the silenced genes.
Using Illumina sequencing and computational analysis, we characterized eight smRNA populations from multiple tissues and organs of soybean including developing seed and vegetative tissues. A total of 41 million raw sequence reads collapsed into 135,055 unique reads were mapped to the soybean genome and its predicted cDNA gene models. Bioinformatic analyses were used to distinguish miRNAs and siRNAs and to determine their genomic origins and potential target genes. In addition, we identified two soybean TAS3 gene homologs, the miRNAs that putatively guide cleavage of their transcripts, and the derived tasiRNAs that could target soybean genes annotated as auxin response factors. Tissue-differential expression based on the flux of normalized miRNA and siRNA abundances in the eight smRNA libraries was evident, some of which was confirmed by smRNA blotting. Our global view of these smRNA populations also revealed that the size classes of smRNAs varied amongst different tissues, with the developing seed and seed coat having greater numbers of unique smRNAs of the 24-nt class compared to the vegetative tissues of germinating seedlings. The 24-nt class is known to be derived from repetitive elements including transposons. Detailed analysis of the size classes associated with ribosomal RNAs and transposable element families showed greater diversity of smRNAs in the 22- and 24-nt size classes.
The flux of endogenous smRNAs within multiple stages and tissues of seed development was contrasted with vegetative tissues of soybean, one of the dominant sources of protein and oil in world markets. The smRNAs varied in size class, complexity of origins, and possible targets. Sequencing revealed tissue-preferential expression for certain smRNAs and expression differences among closely related miRNA family members.
During early vertebrate development, various small non-coding RNAs (sRNAs) such as MicroRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs) are dynamically expressed for orchestrating the maternal-to-zygotic transition (MZT). Systematic analysis of expression profiles of zebrafish small RNAome will be greatly helpful for understanding the sRNA regulation during embryonic development.
We first determined the expression profiles of sRNAs during eight distinct stages of early zebrafish development by sRNA-seq technology. Integrative analyses with a new computational platform of CSZ (characterization of small RNAome for zebrafish) demonstrated an sRNA class transition from piRNAs to miRNAs as development proceeds. We observed that both the abundance and diversity of miRNAs are gradually increased, while the abundance is enhanced more dramatically than the diversity during development. However, although both the abundance and diversity of piRNAs are gradually decreased, the diversity was firstly increased then rapidly decreased. To evaluate the computational accuracy, the expression levels of four known miRNAs were experimentally validated. We also predicted 25 potentially novel miRNAs, whereas two candidates were verified by Northern blots.
Taken together, our analyses revealed the piRNA to miRNA transition as a conserved mechanism in zebrafish, although two different types of sRNAs exhibit distinct expression dynamics in abundance and diversity, respectively. Our study not only generated a better understanding for sRNA regulations in early zebrafish development, but also provided a useful platform for analyzing sRNA-seq data. The CSZ was implemented in Perl and freely downloadable at: http://csz.biocuckoo.org.
Deep sequencing; miRNA; piRNA; Zebrafish; Embryonic development
Small RNAs (sRNAs) are a class of short (20–25 nt) non-coding RNAs that play important regulatory roles in gene expression. An essential first step in understanding their function is to confidently identify sRNA targets. In plants, several classes of sRNAs such as microRNAs (miRNAs) and trans-acting small interfering RNAs have been shown to bind with near-perfect complementarity to their messenger RNA (mRNA) targets, generally leading to cleavage of the mRNA. Recently, a high-throughput technique known as Parallel Analysis of RNA Ends (PARE) has made it possible to sequence mRNA cleavage products on a large-scale. Computational methods now exist to use these data to find targets of conserved and newly identified miRNAs. Due to speed limitations such methods rely on the user knowing which sRNA sequences are likely to target a transcript. By limiting the search to a tiny subset of sRNAs it is likely that many other sRNA/mRNA interactions will be missed. Here, we describe a new software tool called PAREsnip that allows users to search for potential targets of all sRNAs obtained from high-throughput sequencing experiments. By searching for targets of a complete ‘sRNAome’ we can facilitate large-scale identification of sRNA targets, allowing us to discover regulatory interaction networks.
Small RNAs (sRNA), including microRNAs (miRNA) and small interfering RNAs (siRNA), are produced abundantly in plants and animals and function in regulating gene expression or in defense against virus or viroid infection. Analysis of siRNA profiles upon virus infection in plant may allow for virus identification, strain differentiation, and de novo assembly of virus genomes. In the present study, four suspected virus-infected tomato samples collected in the U.S. and Mexico were used for sRNA library construction and deep sequencing. Each library generated between 5–7 million sRNA reads, of which more than 90% were from the tomato genome. Upon in-silico subtraction of the tomato sRNAs, the remaining highly enriched, virus-like siRNA pools were assembled with or without reference virus or viroid genomes. A complete genome was assembled for Potato spindle tuber viroid (PSTVd) using siRNA alone. In addition, a near complete virus genome (98%) also was assembled for Pepino mosaic virus (PepMV). A common mixed infection of two strains of PepMV (EU and US1), which shared 82% of genome nucleotide sequence identity, also could be differentially assembled into their respective genomes. Using de novo assembly, a novel potyvirus with less than 60% overall genome nucleotide sequence identity to other known viruses was discovered and its full genome sequence obtained. Taken together, these data suggest that the sRNA deep sequencing technology will likely become an efficient and powerful generic tool for virus identification in plants and animals.
Small RNAs (sRNAs) are common and effective modulators of gene expression in eukaryotic organisms. To characterize the sRNAs expressed during rice seed development, massively parallel signature sequencing (MPSS) was performed, resulting in the obtainment of 797 399 22-nt sequence signatures, of which 111 161 are distinct ones. Analysis on the distributions of sRNAs on chromosomes showed that most sRNAs originate from interspersed repeats that mainly consist of transposable elements, suggesting the major function of sRNAs in rice seeds is transposon silencing. Through integrative analysis, 26 novel miRNAs and 12 miRNA candidates were identified. Further analysis on the expression profiles of the known and novel miRNAs through hybridizing the generated chips revealed that most miRNAs were expressed preferentially in one or two rice tissues. Detailed comparison of the expression patterns of miRNAs and corresponding target genes revealed the negative correlation between them, while few of them are positively correlated. In addition, differential accumulations of miRNAs and corresponding miRNA*s suggest the functions of miRNA*s other than being passenger strands of mature miRNAs, and in regulating the miRNA functions.
Over the past years, small non-coding RNAs (sRNAs) emerged as important modulators of gene expression in bacteria. Guided by partial sequence complementarity, these sRNAs interact with target mRNAs and eventually affect transcript stability and translation. The physiological function of sRNAs depends on the protein Hfq, which binds sRNAs in the cell and promotes the interaction with their mRNA targets. This important physiological function of Hfq as a central hub of sRNA-mediated regulation made it one of the most intensely studied proteins in bacteria. Recently, a new model for sRNA binding by Hfq has been proposed that involves the direct recognition of the sRNA 3′ end and interactions of the sRNA body with the lateral RNA-binding surface of Hfq. This review summarizes the current understanding of the RNA binding properties of Hfq and its (s)RNA complexes. Moreover, the implications of the new binding model for sRNA-mediated regulation are discussed.
3′ end recognition; LSm ring; RNA chaperone; RNA degradation; crystal structure; gene regulation; non-coding RNAs; prokaryotes
Direct cloning and parallel sequencing, an extremely powerful method for microRNA (miRNA) discovery, has not yet been applied to bacterial transcriptomes. Here we present sRNA-Seq, an unbiased method that allows for interrogation of the entire small, non-coding RNA (sRNA) repertoire in any prokaryotic or eukaryotic organism. This method includes a novel treatment that depletes total RNA fractions of highly abundant tRNAs and small subunit rRNA, thereby enriching the starting pool for sRNA transcripts with novel functionality. As a proof-of-principle, we applied sRNA-Seq to the human pathogen Vibrio cholerae. Our results provide information, at unprecedented depth, on the complexity of the sRNA component of a bacterial transcriptome. From 407 039 sequence reads, all 20 known V. cholerae sRNAs, 500 new, putative intergenic sRNAs and 127 putative antisense sRNAs were identified in a limited number of growth conditions examined. In addition, characterization of a subset of the newly identified transcripts led to the identification of a novel sRNA regulator of carbon metabolism. Collectively, these results strongly suggest that the number of sRNAs in bacteria has been greatly underestimated and that future efforts to analyze bacterial transcriptomes will benefit from direct cloning and parallel sequencing experiments aided by 5S/tRNA depletion.
Small non-coding RNAs (sRNAs) that act as regulators of gene expression have been identified in all kingdoms of life, including microRNA (miRNA) and small interfering RNA (siRNA) in eukaryotic cells. Numerous sRNAs identified in Salmonella are encoded by genes located at Salmonella pathogenicity islands (SPIs) that are commonly found in pathogenic strains. Whether these sRNAs are important for Salmonella pathogenesis and virulence in animals has not been reported. In this study, we provide the first direct evidence that a pathogenicity island-encoded sRNA, IsrM, is important for Salmonella invasion of epithelial cells, intracellular replication inside macrophages, and virulence and colonization in mice. IsrM RNA is expressed in vitro under conditions resembling those during infection in the gastrointestinal tract. Furthermore, IsrM is found to be differentially expressed in vivo, with higher expression in the ileum than in the spleen. IsrM targets the mRNAs coding for SopA, a SPI-1 effector, and HilE, a global regulator of the expression of SPI-1 proteins, which are major virulence factors essential for bacterial invasion. Mutations in IsrM result in disregulation of expression of HilE and SopA, as well as other SPI-1 genes whose expression is regulated by HilE. Salmonella with deletion of isrM is defective in bacteria invasion of epithelial cells and intracellular replication/survival in macrophages. Moreover, Salmonella with mutations in isrM is attenuated in killing animals and defective in growth in the ileum and spleen in mice. Our study has shown that IsrM sRNA functions as a pathogenicity island-encoded sRNA directly involved in Salmonella pathogenesis in animals. Our results also suggest that sRNAs may represent a distinct class of virulence factors that are important for bacterial infection in vivo.
Regulated expression of virulence factors is essential for infection by human pathogens such as Salmonella. Small non-coding RNAs (sRNAs) that act as regulators of gene expression have been identified in all kingdoms of life, and many sRNAs in Salmonella are encoded by genes located at Salmonella pathogenicity islands commonly found in pathogenic strains. In this study, we demonstrated that a pathogenicity island-encoded sRNA directly targets the expression of both a global regulator of virulence genes as well as a specific virulence factor critical for Salmonella pathogenesis. The sRNA is important for Salmonella invasion of epithelial cells, replication inside macrophages, and virulence/colonization in mice, representing the first example of a pathogenicity island-encoded sRNA that is directly involved in Salmonella pathogenesis in vivo. Our study suggests that sRNA may function as a distinct class of virulence factors that significantly contribute to bacterial infection in vivo. Furthermore, our results raise the possibility of developing new strategies against bacterial infection by preventing the expression of regulatory sRNAs.
Chinese fir (Cunninghamia lanceolata) is an important timber species that accounts for 20–30% of the total commercial timber production in China. However, the available genomic information of Chinese fir is limited, and this severely encumbers functional genomic analysis and molecular breeding in Chinese fir. Recently, major advances in transcriptome sequencing have provided fast and cost-effective approaches to generate large expression datasets that have proven to be powerful tools to profile the transcriptomes of non-model organisms with undetermined genomes.
In this study, the transcriptomes of nine tissues from Chinese fir were analyzed using the Illumina HiSeq™ 2000 sequencing platform. Approximately 40 million paired-end reads were obtained, generating 3.62 gigabase pairs of sequencing data. These reads were assembled into 83,248 unique sequences (i.e. Unigenes) with an average length of 449 bp, amounting to 37.40 Mb. A total of 73,779 Unigenes were supported by more than 5 reads, 42,663 (57.83%) had homologs in the NCBI non-redundant and Swiss-Prot protein databases, corresponding to 27,224 unique protein entries. Of these Unigenes, 16,750 were assigned to Gene Ontology classes, and 14,877 were clustered into orthologous groups. A total of 21,689 (29.40%) were mapped to 119 pathways by BLAST comparison against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The majority of the genes encoding the enzymes in the biosynthetic pathways of cellulose and lignin were identified in the Unigene dataset by targeted searches of their annotations. And a number of candidate Chinese fir genes in the two metabolic pathways were discovered firstly. Eighteen genes related to cellulose and lignin biosynthesis were cloned for experimental validating of transcriptome data. Overall 49 Unigenes, covering different regions of these selected genes, were found by alignment. Their expression patterns in different tissues were analyzed by qRT-PCR to explore their putative functions.
A substantial fraction of transcript sequences was obtained from the deep sequencing of Chinese fir. The assembled Unigene dataset was used to discover candidate genes of cellulose and lignin biosynthesis. This transcriptome dataset will provide a comprehensive sequence resource for molecular genetics research of C. lanceolata.
Chinese fir; De novo assembly; RNA-Seq; Transcriptome; Cellulose and lignin biosynthesis; Gene expression
Small non-coding RNAs (sRNAs) emerge as exquisite molecules that are guided for transcriptional and posttranscriptional gene regulation in eukaryotes. As one class of most important sRNAs in plants, trans-acting small interfering RNAs (ta-siRNAs) initiate from microRNA (miRNA) – mediated cleavage of TAS gene transcripts and subsequently are stabilized by SUPPRESSOR OF GENE SILENCING3 (SGS3) and converted to double–stranded RNA (dsRNA) by the actions of RNA-DEPENDENT RNA POLYMERASE6 (RDR6). Generally, these dsRNAs are processed by DICER-LIKE4 (DCL4) and recruited into ARGONAUTE 1 (AGO1) complexes to posttranscriptionally regulate target genes by mRNA cleavage in trans. In a recent study, we discovered a non-canonical ta-siRNAs pathway: Starting from the miRNA-guided cleavage site, the dsRNAs are processed by DCL1 into 21-nt siRNAs, which associate with AGO4/6 complexes to direct DNA methylation in cis. Together with previous results that miRNAs can be produced by DCL3, loaded into AGO4 and trigger epigenetically regulation of target genes, these findings indicate much complex biogenesis, effector and action pathways exist in plant sRNAs kingdom.
ta-siRNA; DCL; AGO; DNA methylation; non-canonical pathway
Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of erythromycin. In this paper, we describe the systematic prediction and analysis of small non-coding RNAs (sRNAs) in S. erythraea, with the aim to elucidate sRNA-mediated regulation of secondary metabolite biosynthesis. In silico and deep-sequencing technologies were applied to predict sRNAs in S. erythraea. Six hundred and forty-seven potential sRNA loci were identified, of which 382 cis-encoded antisense RNA are complementary to protein-coding regions and 265 predicted transcripts are located in intergenic regions. Six candidate sRNAs (sernc292, sernc293, sernc350, sernc351, sernc361, and sernc389) belong to four gene clusters (tpc3, pke, pks6, and nrps5) that are involved in secondary metabolite biosynthesis. Deep-sequencing data showed that the expression of all sRNAs in the strain HL3168 E3 (E3) was higher than that in NRRL23338 (M), except for sernc292 and sernc361 expression. The relative expression of six sRNAs in strain M and E3 were validated by qRT-PCR at three different time points (24, 48, and 72 h). The results showed that, at each time point, the transcription levels of sernc293, sernc350, sernc351, and sernc389 were higher in E3 than in M, with the largest difference observed at 72 h, whereas no signals for sernc292 and sernc361 were detected. sernc293, sernc350, sernc351, and sernc389 probably regulate iron transport, terpene metabolism, geosmin synthesis, and polyketide biosynthesis, respectively. The major significance of this study is the successful prediction and identification of sRNAs in genomic regions close to the secondary metabolism-related genes in S. erythraea. A better understanding of the sRNA-target interaction would help to elucidate the complete range of functions of sRNAs in S. erythraea, including sRNA-mediated regulation of erythromycin biosynthesis.