Identification of novel non-coding RNAs using profiles of short sequence reads from next generation sequencing data

<p>Abstract</p> <p>Background</p> <p>The increasing interest in small non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs) and recent advances in sequencing technology have yielded large numbers of short (18-32 nt) RNA sequences from different organisms, some of which are derived from small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs). We observed that these short ncRNAs frequently cover the entire length of annotated snoRNAs or tRNAs, which suggests that other loci specifying similar ncRNAs can be identified by clusters of short RNA sequences.</p> <p>Results</p> <p>We combined publicly available datasets of tens of millions of short RNA sequence tags from <it>Drosophila melanogaster</it>, and mapped them to the <it>Drosophila </it>genome. Approximately 6 million perfectly mapping sequence tags were then assembled into 521,302 tag-contigs (TCs) based on tag overlap. Most transposon-derived sequences, exons and annotated miRNAs, tRNAs and snoRNAs are detected by TCs, which show distinct patterns of length and tag-depth for different categories. The typical length and tag-depth of snoRNA-derived TCs was used to predict 7 previously unrecognized box H/ACA and 26 box C/D snoRNA candidates. We also identified one snRNA candidate and 86 loci with a high number of tags that are yet to be annotated, 7 of which have a particular 18mer motif and are located in introns of genes involved in development. A subset of new snoRNA candidates and putative ncRNA candidates was verified by Northern blot.</p> <p>Conclusions</p> <p>In this study, we have introduced a new approach to identify new members of known classes of ncRNAs based on the features of TCs corresponding to known ncRNAs. A large number of the identified TCs are yet to be examined experimentally suggesting that many more novel ncRNAs remain to be discovered.</p

Detecting exosomes specifically: a multiplexed device based on alternating current electrohydrodynamic induced nanoshearing

Exosomes show promise as non-invasive biomarkers for cancers, but their effective capture and specific detection is a significant challenge. Herein, we report a multiplexed microfluidic device for highly specific capture and detection of multiple exosome targets using a tuneable alternating current electrohydrodynamic (ac-EHD) methodology - referred to as nanoshearing. In our system, electrical body forces generated by ac-EHD act within nanometers of an electrode surface (i.e., within the electrical layer) to generate nanoscaled fluid flow which enhances the specificity of capture and also reduce nonspecific adsorption of weakly bound molecules from the electrode surface. This approach demonstrates the analysis of exosomes derived from cells expressing human epidermal growth factor receptor 2 (HER2) and prostate specific antigen (PSA), and exhibits a 5-fold detection enhancement compared to hydrodynamic flow based assays. The device was also sensitive enough to detect approximately 2750 exosomes/µL (n = 3) and also capable of specifically isolating exosomes from breast cancer patient samples. We believe this approach can potentially find its relevance as a simple and rapid quantification tool to analyze exosome targets in biological applications

Expression of distinct RNAs from 3′ untranslated regions

The 3′ untranslated regions (3′UTRs) of eukaryotic genes regulate mRNA stability, localization and translation. Here, we present evidence that large numbers of 3′UTRs in human, mouse and fly are also expressed separately from the associated protein-coding sequences to which they are normally linked, likely by post-transcriptional cleavage. Analysis of CAGE (capped analysis of gene expression), SAGE (serial analysis of gene expression) and cDNA libraries, as well as microarray expression profiles, demonstrate that the independent expression of 3′UTRs is a regulated and conserved genome-wide phenomenon. We characterize the expression of several 3′UTR-derived RNAs (uaRNAs) in detail in mouse embryos, showing by in situ hybridization that these transcripts are expressed in a cell- and subcellular-specific manner. Our results suggest that 3′UTR sequences can function not only in cis to regulate protein expression, but also intrinsically and independently in trans, likely as noncoding RNAs, a conclusion supported by a number of previous genetic studies. Our findings suggest novel functions for 3′UTRs, as well as caution in the use of 3′UTR sequence probes to analyze gene expression

Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer.

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.This project has been supported by a grant from Cancer Australia. The Mayo Clinic GWAS was supported by R01CA114343 (Haplotype-based genome screen for ovarian cancer loci). The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith. The AOCS was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, the National Health and Medical Research Council (NHMRC) of Australia (grants 400281, 400413), Cancer Council Victoria, Cancer Council Queensland, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, and Cancer Council Tasmania. G. Chenevix-Trench is a Senior Principal Research fellow of the NHMRC. Y. Lu is funded by NHMRC grant 496675, S. MacGregor is supported by an NHMRC career development award, S. Edwards and J. French are supported by Fellowships from the National Breast Cancer Foundation (NBCF) Australia. The QIMR Berghofer groups were supported by NHMRC project grants (1051698 to SM and 1058415 to SLE and JDF) and a Weekend to End Women’s Cancer Research Grant (to SLE). A deFazio is funded by the University of Sydney Cancer Research Fund and A deFazio and PR Harnett are funded by the Cancer Institute NSW through the Sydney-West Translational Cancer Research Centre. B. Gao is supported by NHMRC and Cancer Institute NSW scholarship. KBM and MO’R are funded by CR-UK. The Bavarian study (BAV) was supported by ELAN Funds of the University of Erlangen-Nuremberg. HSK would like to thank Ira Schwaab for her tireless work on sample preparation. The Belgian study (BEL) was funded by Nationaal Kankerplan and we would like to thank Gilian Peuteman, Thomas Van Brussel and Dominiek Smeets for technical assistance. The Japanese study (JPN) was funded by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare. The International Collaborative Ovarian Neoplasm study (ICON)7 trial team would like to thank the Medical Research Council (MRC) Clinical Trial Unit (CTU) at the University of London (UCL), the ICON7 Translational Research Sub-group, and the University of Leeds for their work on the coordination of samples and data from the ICON7 trial. The LAX study (Women’s Cancer Program) was supported by the American Cancer Society Early Detection Professorship (120950-SIOP-06-258-06-COUN) and Entertainment Industry Foundation. Funding for MALOVA (MAL) was provided by research grant RO1 CA 61107 from the National Cancer Institute, Bethesda, MD; research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project. The Mayo Clinic study (MAYO) was supported by R01 CA122443, P50 CA136393. The Oregon study (ORE) was funded by the Sherie Hildreth Ovarian Cancer Research Fund and the OHSU Foundation. We would like to thank all members of Scottish Gynaecological Clinical Trials group and the SCOTROC1 investigators. SCOTROC1 (SRO) was funded by Cancer Research UK, and the SCOTROC biological studies were supported by Cancer Research UK (grant C536/A6689). RSH receives support from NIH/NIGMS grant K08GM089941, NIH/NCI grant R21 CA139278, NIH/NIGMS grant UO1GM61393, University of Chicago Cancer Center Support Grant (#P30 CA14599) and Breast Cancer SPORE Career Development Award.This is the final version of the article. It first appeared from Impact Journals via http://dx.doi.org/10.18632/oncotarget.704

Methods used for noncoding RNAs analysis

Noncoding RNAs are RNA species that do not encode for proteins, and the majority of the human transcriptome is dominated by ncRNA. Recent extensive genomic and transcriptomic analyses have identified many different classes and sizes of ncRNA. They are now understood to be critical to the overall functioning, growth, development, and differentiation of cells. Differential expression and tissue specificity of many ncRNAs have been reported in normal development and disease states including cancer. Lack of functional ncRNAs may also lead to cancer progression. Therefore noncoding transcripts as biomarkers may be used in either predictive or prognostic ways. As such, over the past 15 years they have emerged as key biomarkers in cancer pathology, relating to both early detection and molecular subtyping. Due to important functional roles of ncRNAs in various cancers, the requirement for technologies used in the field is rapidly increasing. This chapter classifies ncRNAs based on their sizes, and describes methods applied for the identification and characterization of ncRNAs. It outlines key methods used for the purification of good quality RNA, various detection methods, analysis of gene expression as well as techniques that can applied for functional characterization of ncRNA. It also highlights critical steps and options to provide a general guide for ncRNA analysis

Next-Generation Molecular Discovery: From Bottom-Up In Vivo and In Vitro Approaches to In Silico Top-Down Approaches for Therapeutics Neogenesis

Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered “bottom-up” approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of “big data” and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure—when accompanied by high-quality experimental data for model training—has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this

Detecting Exosomes Specifically: a Microfluidic Approach Based on Alternating Current Electrohydrodynamic Induced Nanoshearing

We report a multiplexed microfluidic device for highly specific capture and detection of multiple exosome targets using a tuneable alternating current electrohydrodynamics (ac-EHD) forces - referred to as nanoshearing [1,2]. These forces generated within few nanometers of an electrode surface (i.e., double layer) to generate nanoscaled fluid flow that enhances the specificity of capture and also remove the nonspecifically adsorbed species from the electrode surface. To demonstrate the utility of this phenomenon, we present data on purpose-built microfluidic devices that employ ac-EHD induced surface shear forces to specifically capture exosomes isolated from complex biological fluids (e.g., cell culture media, serum etc.) [3]

A multiplex microplatform for the detection of multiple DNA methylation events using gold-DNA affinity

We report a new multiplexed strategy for the electrochemical detection of regional DNA methylation across multiple regions. Using the sequence dependent affinity of bisulfite treated DNA towards gold surfaces, the method integrates the high sensitivity of a micro-fabricated multiplex device comprising a microarray of gold electrodes, with the powerful multiplexing capability of multiplex-PCR. The synergy of this combination enables the monitoring of the methylation changes across several genomic regions simultaneously from as low as 500 pg mu l(-1) of DNA with no sequencing requirement