An endogenous small interfering RNA pathway in Drosophila

Drosophila endogenous small RNAs are categorized according to their mechanisms of biogenesis and the Argonaute protein to which they bind. MicroRNAs are a class of ubiquitously expressed RNAs of 22 nucleotides in length, which arise from structured precursors through the action of Drosha - Pasha and Dicer- 1-Loquacious complexes(1-7). These join Argonaute-1 to regulate gene expression(8,9). A second endogenous small RNA class, the Piwi-interacting RNAs, bind Piwi proteins and suppress transposons(10,11). Piwi- interacting RNAs are restricted to the gonad, and at least a subset of these arises by Piwi- catalysed cleavage of single-stranded RNAs12,13. Here we show that Drosophila generates a third small RNA class, endogenous small interfering RNAs, in both gonadal and somatic tissues. Production of these RNAs requires Dicer- 2, but a subset depends preferentially on Loquacious(1,4,5) rather than the canonical Dicer- 2 partner, R2D2 ( ref. 14). Endogenous small interfering RNAs arise both from convergent transcription units and from structured genomic loci in a tissue- specific fashion. They predominantly join Argonaute- 2 and have the capacity, as a class, to target both protein- coding genes and mobile elements. These observations expand the repertoire of small RNAs in Drosophila, adding a class that blurs distinctions based on known biogenesis mechanisms and functional roles

Complement-Mediated Virus Infectivity Neutralisation by HLA Antibodies Is Associated with Sterilising Immunity to SIV Challenge in the Macaque Model for HIV/AIDS.

Sterilising immunity is a desired outcome for vaccination against human immunodeficiency virus (HIV) and has been observed in the macaque model using inactivated simian immunodeficiency virus (SIV). This protection was attributed to antibodies specific for cell proteins including human leucocyte antigens (HLA) class I and II incorporated into virions during vaccine and challenge virus preparation. We show here, using HLA bead arrays, that vaccinated macaques protected from virus challenge had higher serum antibody reactivity compared with non-protected animals. Moreover, reactivity was shown to be directed against HLA framework determinants. Previous studies failed to correlate serum antibody mediated virus neutralisation with protection and were confounded by cytotoxic effects. Using a virus entry assay based on TZM-bl cells we now report that, in the presence of complement, serum antibody titres that neutralise virus infectivity were higher in protected animals. We propose that complement-augmented virus neutralisation is a key factor in inducing sterilising immunity and may be difficult to achieve with HIV/SIV Env-based vaccines. Understanding how to overcome the apparent block of inactivated SIV vaccines to elicit anti-envelope protein antibodies that effectively engage the complement system could enable novel anti-HIV antibody vaccines that induce potent, virolytic serological response to be developed

A framework for automated enrichment of functionally significant inverted repeats in whole genomes

<p>Abstract</p> <p>Background</p> <p>RNA transcripts from genomic sequences showing dyad symmetry typically adopt hairpin-like, cloverleaf, or similar structures that act as recognition sites for proteins. Such structures often are the precursors of non-coding RNA (ncRNA) sequences like microRNA (miRNA) and small-interfering RNA (siRNA) that have recently garnered more functional significance than in the past. Genomic DNA contains hundreds of thousands of such inverted repeats (IRs) with varying degrees of symmetry. But by collecting statistically significant information from a known set of ncRNA, we can sort these IRs into those that are likely to be functional.</p> <p>Results</p> <p>A novel method was developed to scan genomic DNA for partially symmetric inverted repeats and the resulting set was further refined to match miRNA precursors (pre-miRNA) with respect to their density of symmetry, statistical probability of the symmetry, length of stems in the predicted hairpin secondary structure, and the GC content of the stems. This method was applied on the <it>Arabidopsis thaliana</it> genome and validated against the set of 190 known Arabidopsis pre-miRNA in the miRBase database. A preliminary scan for IRs identified 186 of the known pre-miRNA but with 714700 pre-miRNA candidates. This large number of IRs was further refined to 483908 candidates with 183 pre-miRNA identified and further still to 165371 candidates with 171 pre-miRNA identified (i.e. with 90% of the known pre-miRNA retained).</p> <p>Conclusions</p> <p>165371 candidates for potentially functional miRNA is still too large a set to warrant wet lab analyses, such as northern blotting, on all of them. Hence additional filters are needed to further refine the number of candidates while still retaining most of the known miRNA. These include detection of promoters and terminators, homology analyses, location of candidate relative to coding regions, and better secondary structure prediction algorithms. The software developed is designed to easily accommodate such additional filters with a minimal experience in Perl.</p

Identification and analysis of miRNAs in human breast cancer and teratoma samples using deep sequencing

<p>Abstract</p> <p>Background</p> <p>MiRNAs play important roles in cellular control and in various disease states such as cancers, where they may serve as markers or possibly even therapeutics. Identifying the whole repertoire of miRNAs and understanding their expression patterns is therefore an important goal.</p> <p>Methods</p> <p>Here we describe the analysis of 454 pyrosequencing of small RNA from four different tissues: Breast cancer, normal adjacent breast, and two teratoma cell lines. We developed a pipeline for identifying new miRNAs, emphasizing extracting and retaining as much data as possible from even noisy sequencing data. We investigated differential expression of miRNAs in the breast cancer and normal adjacent breast samples, and systematically examined the mature sequence end variability of miRNA compared to non-miRNA loci.</p> <p>Results</p> <p>We identified five novel miRNAs, as well as two putative alternative precursors for known miRNAs. Several miRNAs were differentially expressed between the breast cancer and normal breast samples. The end variability was shown to be significantly different between miRNA and non-miRNA loci.</p> <p>Conclusion</p> <p>Pyrosequencing of small RNAs, together with a computational pipeline, can be used to identify miRNAs in tumor and other tissues. Measures of miRNA end variability may in the future be incorporated into the discovery pipeline as a discriminatory feature. Breast cancer samples show a distinct miRNA expression profile compared to normal adjacent breast.</p

The mir-51 Family of microRNAs Functions in Diverse Regulatory Pathways in Caenorhabditis elegans

The mir-51 family of microRNAs (miRNAs) in C. elegans are part of the deeply conserved miR-99/100 family. While loss of all six family members (mir-51-56) in C. elegans results in embryonic lethality, loss of individual mir-51 family members results in a suppression of retarded developmental timing defects associated with the loss of alg-1. The mechanism of this suppression of developmental timing defects is unknown. To address this, we characterized the function of the mir-51 family in the developmental timing pathway. We performed genetic analysis and determined that mir-51 family members regulate the developmental timing pathway in the L2 stage upstream of hbl-1. Loss of the mir-51 family member, mir-52, suppressed retarded developmental timing defects associated with the loss of let-7 family members and lin-46. Enhancement of precocious defects was observed for mutations in lin-14, hbl-1, and mir-48(ve33), but not later acting developmental timing genes. Interestingly, mir-51 family members showed genetic interactions with additional miRNA-regulated pathways, which are regulated by the let-7 and mir-35 family miRNAs, lsy-6, miR-240/786, and miR-1. Loss of mir-52 likely does not suppress miRNA-regulated pathways through an increase in miRNA biogenesis or miRNA activity. We found no increase in the levels of four mature miRNAs, let-7, miR-58, miR-62 or miR-244, in mir-52 or mir-52/53/54/55/56 mutant worms. In addition, we observed no increase in the activity of ectopic lsy-6 in the repression of a downstream target in uterine cells in worms that lack mir-52. We propose that the mir-51 family functions broadly through the regulation of multiple targets, which have not yet been identified, in diverse regulatory pathways in C. elegans

Repertoire of microRNAs in Epithelial Ovarian Cancer as Determined by Next Generation Sequencing of Small RNA cDNA Libraries

MicroRNAs (miRNAs) are small regulatory RNAs that are implicated in cancer pathogenesis and have recently shown promise as blood-based biomarkers for cancer detection. Epithelial ovarian cancer is a deadly disease for which improved outcomes could be achieved by successful early detection and enhanced understanding of molecular pathogenesis that leads to improved therapies. A critical step toward these goals is to establish a comprehensive view of miRNAs expressed in epithelial ovarian cancer tissues as well as in normal ovarian surface epithelial cells.We used massively parallel pyrosequencing (i.e., "454 sequencing") to discover and characterize novel and known miRNAs expressed in primary cultures of normal human ovarian surface epithelium (HOSE) and in tissue from three of the most common histotypes of ovarian cancer. Deep sequencing of small RNA cDNA libraries derived from normal HOSE and ovarian cancer samples yielded a total of 738,710 high-quality sequence reads, generating comprehensive digital profiles of miRNA expression. Expression profiles for 498 previously annotated miRNAs were delineated and we discovered six novel miRNAs and 39 candidate miRNAs. A set of 124 miRNAs was differentially expressed in normal versus cancer samples and 38 miRNAs were differentially expressed across histologic subtypes of ovarian cancer. Taqman qRT-PCR performed on a subset of miRNAs confirmed results of the sequencing-based study.This report expands the body of miRNAs known to be expressed in epithelial ovarian cancer and provides a useful resource for future studies of the role of miRNAs in the pathogenesis and early detection of ovarian cancer

A miRNA-Target Prediction Case Study

Giansanti, V., Castelli, M., Beretta, S., & Merelli, I. (2019). Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study. In V. V. Krzhizhanovskaya, M. H. Lees, P. M. A. Sloot, J. J. Dongarra, J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, ... R. Lam (Eds.), Computational Science – ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part III (pp. 31-44). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11538 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22744-9_3MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is important to identify their targets and, to this purpose, different tools were proposed to solve this problem. However, their results can be very different, so the community is now moving toward the deployment of integration tools, which should be able to perform better than the single ones. As Machine and Deep Learning algorithms are now in their popular years, we developed different classifiers from both areas to verify their ability to recognize possible miRNA-mRNA interactions and evaluated their performance, showing the potentialities and the limits that those algorithms have in this field. Here, we apply two deep learning classifiers and three different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performance when the evaluation scores are taken into account.authorsversionpublishe

An “In-Depth” Description of the Small Non-coding RNA Population of Schistosoma japonicum Schistosomulum

Parasitic flatworms of the genus Schistosoma are the causative agents of schistosomiasis, which afflicts more than 200 million people yearly in tropical regions of South America, Asia and Africa. A promising approach to the control of this and many other diseases involves the application of our understanding of small non-coding RNA function to the design of safe and effective means of treatment. In a previous study, we identified five conserved miRNAs from the adult stage of Schistosoma japonicum. Here, we applied Illumina Solexa high-throughput sequencing methods (deep sequencing) to investigate the small RNAs expressed in S. japonicum schistosomulum (3 weeks post-infection). This has allowed us to examine over four million sequence reads including both frequently and infrequently represented members of the RNA population. Thus we have identified 20 conserved miRNA families that have orthologs in well-studied model organisms and 16 miRNA that appear to be specific to Schistosoma. We have also observed minor amounts of heterogeneity in both 3′ and 5′ terminal positions of some miRNA as well as RNA fragments resulting from the processing of miRNA precursor. An investigation of the genomic arrangement of the 36 identified miRNA revealed that seven were tightly linked in two clusters. We also identified members of the small RNA population whose structure indicates that they are part of an endogenously derived RNA silencing pathway, as evidenced by their extensive complementarities with retrotransposon and retrovirus-related Pol polyprotein from transposon

Deep Sequencing of Human Nuclear and Cytoplasmic Small RNAs Reveals an Unexpectedly Complex Subcellular Distribution of miRNAs and tRNA 3′ Trailers

MicroRNAs (miRNAs) are ∼22-nt small non-coding regulatory RNAs that have generally been considered to regulate gene expression at the post-transcriptional level in the cytoplasm. However, recent studies have reported that some miRNAs localize to and function in the nucleus.To determine the number of miRNAs localized to the nucleus, we systematically investigated the subcellular distribution of small RNAs (sRNAs) by independent deep sequencing sequenced of the nuclear and cytoplasmic pools of 18- to 30-nucleotide sRNAs from human cells. We identified 339 nuclear and 324 cytoplasmic known miRNAs, 300 of which overlap, suggesting that the majority of miRNAs are imported into the nucleus. With the exception of a few miRNAs evidently enriched in the nuclear pool, such as the mir-29b, the ratio of miRNA abundances in the nuclear fraction versus in the cytoplasmic fraction vary to some extent. Moreover, our results revealed that a large number of tRNA 3′trailers are exported from the nucleus and accumulate in the cytoplasm. These tRNA 3′ trailers accumulate in a variety of cell types, implying that the biogenesis of tRNA 3′ trailers is conserved and that they have a potential functional role in vertebrate cells.Our results provide the first comprehensive view of the subcellular distribution of diverse sRNAs and new insights into the roles of miRNAs and tRNA 3′ trailers in the cell