Experimental RNomics: identification of 140 candidates for small non-messenger RNAs in the plant Arabidopsis thaliana

BACKGROUND: Genomes from all organisms known to date express two types of RNA molecules: messenger RNAs (mRNAs), which are translated into proteins, and non-messenger RNAs, which function at the RNA level and do not serve as templates for translation. RESULTS: We have generated a specialized cDNA library from Arabidopsis thaliana to investigate the population of small non-messenger RNAs (snmRNAs) sized 50-500 nt in a plant. From this library, we identified 140 candidates for novel snmRNAs and investigated their expression, abundance, and developmental regulation. Based on conserved sequence and structure motifs, 104 snmRNA species can be assigned to novel members of known classes of RNAs (designated Class I snmRNAs), namely, small nucleolar RNAs (snoRNAs), 7SL RNA, U snRNAs, as well as a tRNA-like RNA. For the first time, 39 novel members of H/ACA box snoRNAs could be identified in a plant species. Of the remaining 36 snmRNA candidates (designated Class II snmRNAs), no sequence or structure motifs were present that would enable an assignment to a known class of RNAs. These RNAs were classified based on their location on the A. thaliana genome. From these, 29 snmRNA species located to intergenic regions, 3 located to intronic sequences of protein coding genes, and 4 snmRNA candidates were derived from annotated open reading frames. Surprisingly, 15 of the Class II snmRNA candidates were shown to be tissue-specifically expressed, while 12 are encoded by the mitochondrial or chloroplast genome. CONCLUSIONS: Our study has identified 140 novel candidates for small non-messenger RNA species in the plant A. thaliana and thereby sets the stage for their functional analysis.     

RNomics in Drosophila melanogaster: identification of 66 candidates for novel non-messenger RNAs

By generating a specialised cDNA library from four different developmental stages of Drosophila melanogaster, we have identified 66 candidates for small non-messenger RNAs (snmRNAs) and have confirmed their expression by northern blot analysis. Thirteen of them were expressed at certain stages of D.melanogaster development, only. Thirty-five species belong to the class of small nucleolar RNAs (snoRNAs), divided into 15 members from the C/D subclass and 20 members from the H/ACA subclass, which mostly guide 2'-O-methylation and pseudouridylation, respectively, of rRNA and snRNAs. These also include two outstanding C/D snoRNAs, U3 and U14, both functioning as pre-rRNA chaperones. Surprisingly, the sequence of the Drosophila U14 snoRNA reflects a major change of function of this snoRNA in Diptera relative to yeast and vertebrates. Among the 22 snmRNAs lacking known sequence and structure motifs, five were located in intergenic regions, two in introns, five in untranslated regions of mRNAs, eight were derived from open reading frames, and two were transcribed opposite to an intron. Interestingly, detection of two RNA species from this group implies that certain snmRNA species are processed from alternatively spliced pre-mRNAs. Surprisingly, a few snmRNA sequences could not be found on the published D.melanogaster genome, which might suggest that more snmRNA genes (as well as mRNAs) are hidden in unsequenced regions of the genome.     

RNomics: an experimental approach that identifies 201 candidates for novel, small, non-messenger RNAs in mouse

In mouse brain cDNA libraries generated from small RNA molecules we have identified a total of 201 different expressed RNA sequences potentially encoding novel small non-messenger RNA species (snmRNAs). Based on sequence and structural motifs, 113 of these RNAs can be assigned to the C/D box or H/ACA box subclass of small nucleolar RNAs (snoRNAs), known as guide RNAs for rRNA. While 30 RNAs represent mouse homologues of previously identified human C/D or H/ACA snoRNAs, 83 correspond to entirely novel snoRNAS: Among these, for the first time, we identified four C/D box snoRNAs and four H/ACA box snoRNAs predicted to direct modifications within U2, U4 or U6 small nuclear RNAs (snRNAs). Furthermore, 25 snoRNAs from either class lacked antisense elements for rRNAs or snRNAS: Therefore, additional snoRNA targets have to be considered. Surprisingly, six C/D box snoRNAs and one H/ACA box snoRNA were expressed exclusively in brain. Of the 88 RNAs not belonging to either snoRNA subclass, at least 26 are probably derived from truncated heterogeneous nuclear RNAs (hnRNAs) or mRNAS: Short interspersed repetitive elements (SINEs) are located on five RNA sequences and may represent rare examples of transcribed SINES: The remaining RNA species could not as yet be assigned either to any snmRNA class or to a part of a larger hnRNA/mRNA. It is likely that at least some of the latter will represent novel, unclassified snmRNAS:     

动物snmRNA的系统识别与鉴定

小分子非编码RNA(snmRNA)在调控基因的转录和转录后加工、细胞分化和个体发育、遗传和表观遗传等几乎所有的重要生命活动中发挥关键作用。建立和发展snmRNA研究技术,系统地发现和注释基因组中的snmRNA基因并阐明其生物学意义是当前RNA组学的首要任务。围绕snmRNA的系统识别与鉴定等问题,该文对近年来采用实验技术和计算机预测方法发掘snmRNA所取得的主要研究成果进行综述。     

Cloning and expression profiling of small RNAs expressed in the mouse ovary

Small noncoding RNAs have been suggested to play important roles in the regulation of gene expression across all species from plants to humans. To identify small RNAs expressed by the ovary, we generated mouse ovarian small RNA complementary DNA (srcDNA) libraries and sequenced 800 srcDNA clones. We identified 236 small RNAs including 122 microRNAs (miRNAs), 79 piwi-interacting RNAs (piRNAs), and 35 small nucleolar RNAs (snoRNAs). Among these small RNAs, 15 miRNAs, 74 piRNAs, and 21 snoRNAs are novel. Approximately 70% of the ovarian piRNAs are encoded by multicopy genes located within the repetitive regions, resembling previously identified repeat-associated small interference RNAs (rasiRNAs), whereas the remaining approximately 30% of piRNA genes are located in nonrepetitive regions of the genome with characteristics similar to the majority of piRNAs originally cloned from the testis. Since these two types of piRNAs display different structural features, we categorized them into two classes: repeat-associated piRNAs (rapiRNAs, equivalent of the rasiRNAs) and non-repeat-associated piRNAs (napiRNAs). Expression profiling analyses revealed that ovarian miRNAs were either ubiquitously expressed in multiple tissues or preferentially expressed in a few tissues including the ovary. Ovaries appear to express more rapiRNAs than napiRNAs, and sequence analyses support that both may be generated through the "ping-pong" mechanism. Unique expression and structural features of these ovarian small noncoding RNAs suggest that they may play important roles in the control of folliculogenesis and female fertility.     

Plant U13 orthologues and orphan snoRNAs identified by RNomics of RNA from Arabidopsis nucleoli

Small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs (scaRNAs) are non-coding RNAs whose main function in eukaryotes is to guide the modification of nucleotides in ribosomal and spliceosomal small nuclear RNAs, respectively. Full-length sequences of Arabidopsis snoRNAs and scaRNAs have been obtained from cDNA libraries of capped and uncapped small RNAs using RNA from isolated nucleoli from Arabidopsis cell cultures. We have identified 31 novel snoRNA genes (9 box C/D and 22 box H/ACA) and 15 new variants of previously described snoRNAs. Three related capped snoRNAs with a distinct gene organization and structure were identified as orthologues of animal U13snoRNAs. In addition, eight of the novel genes had no complementarity to rRNAs or snRNAs and are therefore putative orphan snoRNAs potentially reflecting wider functions for these RNAs. The nucleolar localization of a number of the snoRNAs and the localization to nuclear bodies of two putative scaRNAs was confirmed by in situ hybridization. The majority of the novel snoRNA genes were found in new gene clusters or as part of previously described clusters. These results expand the repertoire of Arabidopsis snoRNAs to 188 snoRNA genes with 294 gene variants.     

MicroRNAs对动物皮肤和毛发发育调控作用的研究进展

MicroRNAs是近年来发现的一类由19-25个核苷酸组成的非编码单链小RNA分子,它们通过与靶基因mRNA3’UTR结合抑制靶基因的翻译,在转录后水平调控基因表达.MicroRNAs参与了包括细胞分化、增殖和凋亡及免疫系统应答在内的一系列发育调控和生物学过程.最近研究发现MicroRNAs在多种哺乳动物皮肤中均表达,并参与了哺乳动物皮肤及毛发发育的调控过程,这些都为研究这个新颖的调控因子在干细胞生物学和发育生物学中的功能奠定了基础.本文综述了近年来MicroRNAs对哺乳动物皮肤和毛发发育调控作用的研究状况.     

Processing of the intron-encoded U16 and U18 snoRNAs: the conserved C and D boxes control both the processing reaction and the stability of the mature snoRNA.

A novel class of small nucleolar RNAs (snoRNAs), encoded in introns of protein coding genes and originating from processing of their precursor molecules, has recently been described. The L1 ribosomal protein (r-protein) gene of Xenopus laevis and its human homologue contain two snoRNAs, U16 and U18. It has been shown that these snoRNAs are excised from their intron precursors by endonucleolytic cleavage and that their processing is alternative to splicing. Two sequences, internal to the snoRNA coding region, have been identified as indispensable for processing the conserved boxes C and D. Competition experiments have shown that these sequences interact with diffusible factors which can bind both the pre-mRNA and the mature U16 snoRNA. Fibrillarin, which is known to associate with complexes formed on C and D boxes of other snoRNAs, is found in association with mature U16 RNA, as well as with its precursor molecules. This fact suggests that the complex formed on the pre-mRNA remains bound to U16 throughout all the processing steps. We also show that the complex formed on the C and D boxes is necessary to stabilize mature snoRNA.     

The small RNA expression profile of the developing murine urinary and reproductive systems

microRNAs (miRNAs) are small non-coding RNAs with fundamental roles in the regulation of gene expression. miRNAs assemble with Argonaute (Ago) proteins to miRNA-protein complexes (miRNPs), which interact with distinct binding sites on mRNAs and regulate gene expression. Specific miRNAs are key regulators of tissue and organ development and it has been shown in mammals that miRNAs are also involved in the pathogenesis of many diseases including cancer. Here, we have characterized the miRNA expression profile of the developing murine genitourinary system. Using a computational approach, we have identified several miRNAs that are specific for the analyzed tissues or the developmental stage. Our comprehensive miRNA expression atlas of the developing genitourinary system forms an invaluable basis for further functional in vivo studies.     

Efficient and specific knockdown of small non-coding RNAs in mammalian cells and in mice

Hundreds of small nuclear non-coding RNAs, including small nucleolar RNAs (snoRNAs), have been identified in different organisms, with important implications in regulating gene expression and in human diseases. However, functionalizing these nuclear RNAs in mammalian cells remains challenging, due to methodological difficulties in depleting these RNAs, especially snoRNAs. Here we report a convenient and efficient approach to deplete snoRNA, small Cajal body RNA (scaRNA) and small nuclear RNA in human and mouse cells by conventional transfection of chemically modified antisense oligonucleotides (ASOs) that promote RNaseH-mediated cleavage of target RNAs. The levels of all seven tested snoRNA/scaRNAs and four snRNAs were reduced by 80-95%, accompanied by impaired endogenous functions of the target RNAs. ASO-targeting is highly specific, without affecting expression of the host genes where snoRNAs are embedded in the introns, nor affecting the levels of snoRNA isoforms with high sequence similarities. At least five snoRNAs could be depleted simultaneously. Importantly, snoRNAs could be dramatically depleted in mice by systematic administration of the ASOs. Together, our findings provide a convenient and efficient approach to characterize nuclear non-coding RNAs in mammalian cells, and to develop antisense drugs against disease-causing non-coding RNAs.     

Mining small RNA sequencing data: a new approach to identify small nucleolar RNAs in Arabidopsis

Small nucleolar RNAs (snoRNAs) are noncoding RNAs that direct 2′-O-methylation or pseudouridylation on ribosomal RNAs or spliceosomal small nuclear RNAs. These modifications are needed to modulate the activity of ribosomes and spliceosomes. A comprehensive repertoire of snoRNAs is needed to expand the knowledge of these modifications. The sequences corresponding to snoRNAs in 18–26-nt small RNA sequencing data have been rarely explored and remain as a hidden treasure for snoRNA annotation. Here, we showed the enrichment of small RNAs at Arabidopsis snoRNA termini and developed a computational approach to identify snoRNAs on the basis of this characteristic. The approach successfully uncovered the full-length sequences of 144 known Arabidopsis snoRNA genes, including some snoRNAs with improved 5′- or 3′-end annotation. In addition, we identified 27 and 17 candidates for novel box C/D and box H/ACA snoRNAs, respectively. Northern blot analysis and sequencing data from parallel analysis of RNA ends confirmed the expression and the termini of the newly predicted snoRNAs. Our study especially expanded on the current knowledge of box H/ACA snoRNAs and snoRNA species targeting snRNAs. In this study, we demonstrated that the use of small RNA sequencing data can increase the complexity and the accuracy of snoRNA annotation.     

Distribution of U3 small nucleolar RNA and fibrillarin during early embryogenesis in Caenorhabditis elegans

U3 small nucleolar RNA (snoRNA) is one of the members of the box C/D class of snoRNA and is essential for ribosomal RNA (rRNA) processing to generate 18S rRNA in the nucleolus. Although U3 snoRNA is abundant, and is well conserved from yeast to mammals, the genes encoding U3 snoRNA in C. elegans have long remained unidentified. A recent RNomics study in C. elegans predicted five distinct U3 snoRNA genes. However, characterization of these candidates for U3 snoRNA has yet to be performed. In this study, we isolated and characterized four candidate RNAs for U3 snoRNA from the immunoprecipitated RNAs of C. elegans using an antibody against the 2,2,7-trimethylguanosine (TMG) cap. The sequences were identical to the predicted U3 sequences in the RNomics study. Here, we show the several lines of evidence that the isolated RNAs are the true U3 snoRNAs of C. elegans. Moreover, we report the novel expression pattern of U3 snoRNA and fibrillarin, which is an essential component of U3 small nucleolar ribonucleoprotein complex, during early embryo development of C. elegans. To our knowledge, this is the first observation of the inconsistent localization U3 snoRNA and fibrillarin during early embryogenesis, providing novel insight into the mechanisms of nucleologenesis and ribosome production during early embryogenesis.     

The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2′-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA–RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.