Identification of small non-coding RNAs from mitochondria and chloroplasts

Small non-protein-coding RNAs (ncRNAs) have been identified in a wide spectrum of organisms ranging from bacteria to humans. In eukarya, systematic searches for ncRNAs have so far been restricted to the nuclear or cytosolic compartments of cells. Whether or not small stable non-coding RNA species also exist in cell organelles, in addition to tRNAs or ribosomal RNAs, is unknown. We have thus generated cDNA libraries from size-selected mammalian mitochondrial RNA and plant chloroplast RNA and searched for small ncRNA species in these two types of DNA-containing cell organelles. In total, we have identified 18 novel candidates for organellar ncRNAs in these two cellular compartments and confirmed expression of six of them by northern blot analysis or RNase A protection assays. Most candidate ncRNA genes map to intergenic regions of the organellar genomes. As found previously in bacteria, the presumptive ancestors of present-day chloroplasts and mitochondria, we also observed examples of antisense ncRNAs that potentially could target organelle-encoded mRNAs. The structural features of the identified ncRNAs as well as their possible cellular functions are discussed. The absence from our libraries of abundant small RNA species that are not encoded by the organellar genomes suggests that the import of RNAs into cell organelles is of very limited significance or does not occur at all.     

Identification of new small non-coding RNAs from tobacco and Arabidopsis

Small non-coding RNAs (ncRNAs) have typically been searched in fully sequenced genomes using one of two approaches-experimental or computational. We developed a mixed method, using both types of information, which has the advantage of applying bio-computing methods to actually expressed sequences. Our method allowed the identification of new small ncRNAs in Arabidopsis thaliana and in the unfinished genome of Nicotiana tabacum. We constructed a N. tabacum cDNA library from small RNAs ranging from 20 to 30 nucleotides (nt). The sequences from 73 unique clones were compared to the A. thaliana genome and to all plant sequences using a pattern-matching approach (program Patbank). Thus, we selected 15 clones from the library corresponding mostly to A. thaliana or N. tabacum non-coding sequences. By Northern blot analyses, we confirmed the presence of most RNA candidates in Arabidopsis and in Nicotiana sylvestris with a size range of 21-100 nt. To gain more insight into the possible genesis of 21-24 nt sequences, stable folding of sRNAs with their flanking regions were predicted with the software MIRFOLD dedicated to the folding of microRNAs (miRNA). Stable hairpins structures were observed for some putative miRNAs.     

Computational approaches for the discovery of bacterial small RNAs

Recent work has uncovered a growing number of bacterial small RNAs (sRNAs), some of which have been shown to regulate critical cellular processes. Computational approaches, in combination with experiments, have played an important role in the discovery of these sRNAs. In this article, we first give an overview of different computational approaches for genome-wide prediction of sRNAs. These approaches have led to the discovery of several novel sRNAs, however the regulatory roles are not yet known for a majority of these sRNAs. By contrast, several recent studies have highlighted the inverse problem where the functional role of the sRNA is already known and the challenge is to identify its genomic location. The focus of this article is on computational tools and strategies for identifying these specific sRNAs which function as key components of known regulatory pathways.     

Experimental approaches to identify non-coding RNAs

Cellular RNAs that do not function as messenger RNAs (mRNAs), transfer RNAs (tRNAs) or ribosomal RNAs (rRNAs) comprise a diverse class of molecules that are commonly referred to as non-protein-coding RNAs (ncRNAs). These molecules have been known for quite a while, but their importance was not fully appreciated until recent genome-wide searches discovered thousands of these molecules and their genes in a variety of model organisms. Some of these screens were based on biocomputational prediction of ncRNA candidates within entire genomes of model organisms. Alternatively, direct biochemical isolation of expressed ncRNAs from cells, tissues or entire organisms has been shown to be a powerful approach to identify ncRNAs both at the level of individual molecules and at a global scale. In this review, we will survey several such wet-lab strategies, i.e. direct sequencing of ncRNAs, shotgun cloning of small-sized ncRNAs (cDNA libraries), microarray analysis and genomic SELEX to identify novel ncRNAs, and discuss the advantages and limits of these approaches.     

Identification of small RNAs in diverse bacterial species

Small, non-coding bacterial RNAs (sRNAs) have been shown to regulate a plethora of biological processes. Up until recently, most sRNAs had been identified and characterized in E. coli. However, in the past few years, dozens of sRNAs have been discovered in a wide variety of bacterial species. Whereas numerous sRNAs have been isolated or detected through experimental approaches, most have been identified in predictive bioinformatic searches. Recently developed computational tools have greatly facilitated the efficient prediction of sRNAs in diverse species. Although the number of known sRNAs has dramatically increased in recent years, many challenges in the identification and characterization of sRNAs lie ahead.     

CoRAL: predicting non-coding RNAs from small RNA-sequencing data

The surprising observation that virtually the entire human genome is transcribed means we know little about the function of many emerging classes of RNAs, except their astounding diversities. Traditional RNA function prediction methods rely on sequence or alignment information, which are limited in their abilities to classify the various collections of non-coding RNAs (ncRNAs). To address this, we developed Classification of RNAs by Analysis of Length (CoRAL), a machine learning-based approach for classification of RNA molecules. CoRAL uses biologically interpretable features including fragment length and cleavage specificity to distinguish between different ncRNA populations. We evaluated CoRAL using genome-wide small RNA sequencing data sets from four human tissue types and were able to classify six different types of RNAs with ∼80% cross-validation accuracy. Analysis by CoRAL revealed that microRNAs, small nucleolar and transposon-derived RNAs are highly discernible and consistent across all human tissue types assessed, whereas long intergenic ncRNAs, small cytoplasmic RNAs and small nuclear RNAs show less consistent patterns. The ability to reliably annotate loci across tissue types demonstrates the potential of CoRAL to characterize ncRNAs using small RNA sequencing data in less well-characterized organisms.     

Identification of small non-coding RNAs in the planarian Dugesia japonica via deep sequencing

Freshwater planarian flatworm possesses an extraordinary ability to regenerate lost body parts after amputation; it is perfect organism model in regeneration and stem cell biology. Recently, small RNAs have been an increasing concern and studied in many aspects, including regeneration and stem cell biology, among others. In the current study, the large-scale cloning and sequencing of sRNAs from the intact and regenerative planarian Dugesia japonica are reported. Sequence analysis shows that sRNAs between 18nt and 40nt are mainly microRNAs and piRNAs. In addition, 209 conserved miRNAs and 12 novel miRNAs are identified. Especially, a better screening target method, negative-correlation relationship of miRNAs and mRNA, is adopted to improve target prediction accuracy. Similar to miRNAs, a diverse population of piRNAs and changes in the two samples are also listed. The present study is the first to report on the important role of sRNAs during planarian Dugesia japonica regeneration.     

链球菌非编码小RNA研究进展

非编码小RNA(Small non-coding RNA,sRNA)是一种存在于原核和真核生物中的新型调控RNA,长度约为40～500个核苷酸。作为一类关键的调控因子,sRNA通过与靶mRNA或蛋白质结合来调控细胞内的基因表达。大部分细菌sRNA在大肠杆菌等革兰氏阴性菌中被发现并研究,但近十年来越来越多的sRNA在革兰氏阳性菌中被逐步发现。作为一类革兰氏阳性菌,链球菌属中sRNA目前研究主要集中在毒力调节,鲜有其他调控的报道。本文总结了链球菌中sRNA的最新进展,并介绍其主要功能和机理,以期为细菌sRNA研究提供借鉴。     

Diversity of endogenous small non-coding RNAs in Oryza sativa

Small non-coding RNAs play important roles in regulating cell functions by controlling mRNA turnover and translational repression in eukaryotic cells. Here we isolated 162 endogenous small RNA molecules from Oryza sativa, which ranged from 16 to 35 nt in length. Further analysis indicated that they represented a diversity of small RNA molecules, including 17 microRNAs (miRNAs), 30 tiny non-coding RNAs (tncRNAs) and 20 repeat-associated small interfering RNAs (rasiRNAs). Among 17 miRNAs, 13 were novel miRNA candidates and their potential targets were important regulatory genes in the rice genome. We also found that a cluster of small RNAs, including many rasiRNAs, matched to a nuclear DNA fragment that evolutionarily derived from chloroplast. These results demonstrate clearly the existence of distinct types of small RNAs in rice and further suggest that small RNAs may control gene regulation through diverse mechanisms.     

细菌中非编码小RNA的筛选及鉴定

细菌非编码小RNA(small non-coding RNA,sRNA)是一类长度在50-200个核苷酸,不编码蛋白质的RNA.它们通过碱基配对识别靶标mRNA,在转录后水平调节基因的表达,是细菌代谢、毒力和适应环境压力的重要调节因子.近年来,随着生物信息学和RNA组学技术应用于细菌sRNA的筛选,sRNA已被证实存在于大肠埃希杆菌(Escherichia coli),铜绿假单胞菌(Pseudomonas aeruginosa)、霍乱弧菌(Vibrio cholerae)等细菌中,是细菌基因调控中新的调节因子.本文对细菌中非编码小RNA的筛选和鉴定技术作一个简要论述.     

Identification of cyanobacterial non-coding RNAs by comparative genome analysis

Background  

Whole genome sequencing of marine cyanobacteria has revealed an unprecedented degree of genomic variation and streamlining. With a size of 1.66 megabase-pairs, Prochlorococcus sp. MED4 has the most compact of these genomes and it is enigmatic how the few identified regulatory proteins efficiently sustain the lifestyle of an ecologically successful marine microorganism. Small non-coding RNAs (ncRNAs) control a plethora of processes in eukaryotes as well as in bacteria; however, systematic searches for ncRNAs are still lacking for most eubacterial phyla outside the enterobacteria.