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.     

Reversal of BCRP-mediated multidrug resistance by stable expression of small interfering RNAs

Breast cancer resistance protein (BCRP) is an ATP-binding cassette multidrug transporter that confers resistance to various anticancer drugs like Mitoxantrone. Overexpression of BCRP confers multidrug resistance (MDR) in cancer cells and is a frequent impediment to successful chemotherapy. For stable reversal of BCRP-depending MDR by RNA interference technology, a hU6-RNA gene promoter-driven expression vector encoding anti-BCRP short hairpin RNA (shRNA) molecules was constructed. By treating endogenously and exogenously expresses high levels of BCRP cells with these constructs, expression of the targeted BCRP-encoding mRNA, and transport protein was inhibited completely. Furthermore, the accumulation of mitoxantrone in the anti-BCRP shRNA-treated cells increased. And the sensitivity to mitoxantrone of anti-BCRP shRNA-treated cells is increased 14.6-fold and 2.44-fold respectively compared to their control (P < 0.05). These data indicated that stable shRNA-mediated RNAi could be tremendously effective in reversing BCRP-mediated MDR and showed promises in overcoming MDR by gene therapeutic applications.     

Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.     

Non-coding RNAs: lessons from the small nuclear and small nucleolar RNAs

Recent advances have fuelled rapid growth in our appreciation of the tremendous number, diversity and biological importance of non-coding (nc)RNAs. Because ncRNAs typically function as ribonucleoprotein (RNP) complexes and not as naked RNAs, understanding their biogenesis is crucial to comprehending their regulation and function. The small nuclear and small nucleolar RNPs are two well studied classes of ncRNPs with elaborate assembly and trafficking pathways that provide paradigms for understanding the biogenesis of other ncRNPs.     

基于蓝藻全基因组原始数据的转座元件挖掘及组成分析

二代测序技术及全基因组多样性比较是现代生物学及信息科学研究的热点,对基因组中转座元件(Transposable element)的分析已成为基因组比较分析的重要组成部分。目前对于转座元件的种类、数量和组成的挖掘和分析一般是基于完全拼接后的全基因组序列,对在此之前的海量短片段序列后期处理及拼接仍是目前基因组研究的盲点,以转座元件为主的重复序列在拼接过程中也存在着不可避免的拼接误差或丢失,给转座元件系统的分析带来不确定。文章旨在建立一套分析流程,对铜绿微囊藻NIES 843全基因组构建的罗氏(Roche)公司454测序随机模拟原始数据集的转座元件(主要类型为插入序列:Insert sequence,IS)组成进行分析,结果表明,采用对核酸探针扫描后备选序列分成3组,并分设氨基酸检测阈值的方案分析得到的结果较为可靠,结果显示铜绿微囊藻NIES843的蓝藻转座元件占基因组比例的10.38%,归属于14个IS家族,66个IS亚家族。与之前基于完整拼接基因组数据的两套不同分析流程得到的结果相比,在丰度及家族/亚家族组成上无显著差异,在转座元件序列水平上也显示了高比例的相似性序列重叠,证实了本研究流程在基于高通量测序原始数据的转座元件分析方面具可靠性及实用性。     

Antiviral immunity directed by small RNAs

Plants and invertebrates can protect themselves from viral infection through RNA silencing. This antiviral immunity involves production of virus-derived small interfering RNAs (viRNAs) and results in specific silencing of viruses by viRNA-guided effector complexes. The proteins required for viRNA production as well as several key downstream components of the antiviral immunity pathway have been identified in plants, flies, and worms. Meanwhile, viral mechanisms to suppress this small RNA-directed immunity by viruses are being elucidated, thereby illuminating an ongoing molecular arms race that likely impacts the evolution of both viral and host genomes.     

Marine microbial community structure assessed from combined metagenomic analysis and ribosomal amplicon deep-sequencing

The microbial taxonomic composition of the three domains of life in two coastal plankton samples was assessed by random total community metagenomic sequencing and PCR-based rDNA amplicon deep-sequencing in order to compare the resulting diversity and investigate possible limitations and complementarities of each method. The various universal primer sets, used to amplify different hypervariable rDNA regions, revealed the same major high-level taxonomic groups in Bacteria and unicellular Eukaryota, and showed a scarce Archaea apparent richness. However, significant differences were found between the different primer sets (p-value < 0.05, with the Kolmogorov–Smirnov test), regarding both operational taxonomic unit (OTU) richness and relative abundance of the major high-level taxonomic groups detected. Based on the metagenomic approach, the phylum Bacteroidetes dominated the prokaryotic community, followed by Proteobacteria, while the detected eukaryotic unicellular taxa belonged to the groups of Alveolata, Fungi, Chlorophyta, Stramenopiles and Phaeophyceae. These groups were found to carry genes typically found in microbial communities, which are linked to DNA, RNA and protein metabolism and the synthesis of nucleotides, amino acids, carbohydrates and vitamins. Although our findings suggest that the total community metagenomic approach can provide a more comprehensive picture of the planktonic microbial community structure, a number of issues associated with this approach emerged. These issues include the still relatively high cost compared to amplicon sequencing, the possible low coverage of the full marine diversity, the insufficiency of databases for other gene markers than the small subunit gene, and the bias towards bacterial sequences because of their higher abundance relative to eukaryotes in marine environments.     

Large-scale analysis of small RNAs derived from traditional Chinese herbs in human tissues

Plant-derived microRNAs have recently been reported to function in human blood and tissues. Controversy was immediately raised due to possible contamination and the lack of large sample sizes. Here, we report thousands of unique small RNAs derived from traditional Chinese medicine(TCM) herbs found in human blood cells and mouse lung tissues using a large-scale analysis.We extracted small RNAs from decoctions of 10 TCM plants(Ban Zhi Lian, Chai Hu, Chuan Xin Lian, Di Ding Zi Jin, Huang Qin, Jin Yin Hua, Lian Qiao, Pu Gong Ying, Xia Ku Cao, and Yu Xing Cao) and obtained millions of RNA sequences from each herb. We also obtained RNA-Seq data from the blood cells of humans who consumed herbal decoctions and from the lung tissues of mice administered RNAs from herbal decoctions via oral gavage. We identified thousands of unique small RNA sequences in human blood cells and mouse lung tissues. Some of these identified small RNAs from Chuan Xin Lian and Hong Jing Tian could be mapped to the genomes of the herbs, confirming their TCM plant origin. Small RNAs derived from herbs regulate mammalian gene expression in a sequence-specific manner, and thus are a superior novel class of herbal drug components that hold great potential as oral gene-targeted therapeutics, highlighting the important role of herbgenomics in their development.     

Insights from the molecular docking aided interaction analysis of HfQ with small RNAs

Hfq, RNA binding protein, is widely found in most of the prokaryotes. It plays a key role in gene regulation by binding with small RNA and facilitates mRNA pairing there by suppress or boost translation according to RNA structures. Interaction between sRNAs and HfQ in Salmonella SL1344 were screened using Co-Immuno Precipitation (HfQ-CoIP) studies earlier. We have formulated an In silico approach, to model the 3D structures of 155 sRNA and studied their interactions with HfQ proteins. We have reported the key interacting PHE42, LEU7, VAL27, PHE39 and PRO21 residues of HfQ binds with many small RNAs. Further mutation of PHE42 in to ALA42 in HfQ leads to loss of sRNA binding efficiency. We have differentiated the interactions in to HfQ binding and non-binding sRNAs, based on Atomic Contact Energy and area. This methodology may be applied generically for functional grouping of small RNAs in any organism.     

Rotavirus gene silencing by small interfering RNAs

RNA interference is an evolutionarily conserved double-stranded RNA-triggered mechanism for suppressing gene expression. Rotaviruses, the leading cause of severe diarrhea in young children, are formed by three concentric layers of protein, from which the spike protein VP4 projects. Here, we show that a small interfering RNA corresponding to the VP4 gene efficiently inhibits the synthesis of this protein in virus-infected cells. A large proportion of infected cells had no detectable VP4 and the yield of viral progeny was reduced. Most of the virus particles purified from these cells were triple-layered, but lacked VP4, and were poorly infectious. We also show that VP4 might not be required for the last step of virus morphogenesis. The VP4 gene silencing was specific, since the synthesis of VP4 from rotavirus strains that differ in the target sequence was not affected. These findings offer the possibility of carrying out reverse genetics in rotaviruses.