A convenient system for highly specific and sensitive detection of miRNA expression

A Comprehensive Analysis of Northern versus Liquid Hybridization Assays for mRNAs, Small RNAs, and miRNAs Using a Non-Radiolabeled Approach

Northern blotting (NB), a gold standard for RNA detection, has lost its charm due to its hands-on nature, need for good quality RNA, and radioactivity. With the emergence of the field of microRNAs (miRNAs), the necessity for sensitive and quantitative NBs has again emerged. Here, we developed highly sensitive yet non-radiolabeled, fast, economical NB, and liquid hybridization (LH) assays without radioactivity or specialized reagents like locked nucleic acid (LNA)- or digoxigenin-labeled probes for mRNAs/small RNAs, especially miRNAs using biotinylated probes. An improvised means of hybridizing oligo probes along with efficient transfer, cross-linking, and signal enhancement techniques was employed. Important caveats of each assay were elaborated upon, especially issues related to probe biotinylation, use of exonuclease, and bioimagers not reported earlier. We demonstrate that, while the NBs were sensitive for mRNAs and small RNAs, our LH protocol could efficiently detect these and miRNAs using less than 10-100 times the total amount of RNA, a sensitivity comparable to radiolabeled probes. Compared to NBs, LH was a faster, more sensitive, and specific approach for mRNA/small RNA/miRNA detection. A comparison of present work with six seminal studies is presented along with detailed protocols for easy reproducibility. Overall, our study provides effective platforms to study large and small RNAs in a sensitive, efficient, and cost-effective manner.

qPCR multiplex detection of microRNA and messenger RNA in a single reaction

Reverse Transcription-Quantitative PCR (RT-qPCR) is one of the standards for analytical measurement of different RNA species in biological models. However, current Reverse Transcription (RT) based priming strategies are unable to synthesize differing RNAs and ncRNAs especially miRNAs, within a single tube. We present a new methodology, referred to as RNAmp, that measures in parallel miRNA and mRNA expression. We demonstrate this in various cell lines, then evaluate clinical utility by quantifying several miRNAs and mRNA simultaneously in sera. PCR efficiency in RNAmp was estimated between 1.8 and 1.9 which is comparable to standard miRNA and random primer RT approaches. Furthermore, when using RNAmp to detect selected mRNA and miRNAs, the quantification cycle (Cq) was several cycles lower. This low volume single-tube duplex protocol reduces technical variation and reagent usage and is suitable for uniform analysis of single or multiple miRNAs and/or mRNAs within a single qPCR reaction.

Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection

Background

MicroRNAs (miRNAs) are noncoding RNA molecules heavily involved in human tumors, in which few of them circulating the human body. Finding a tumor-associated signature of miRNA, that is, the minimum miRNA entities to be measured for discriminating both different types of cancer and normal tissues, is of utmost importance. Feature selection techniques applied in machine learning can help however they often provide naive or biased results.

Results

An ensemble feature selection strategy for miRNA signatures is proposed. miRNAs are chosen based on consensus on feature relevance from high-accuracy classifiers of different typologies. This methodology aims to identify signatures that are considerably more robust and reliable when used in clinically relevant prediction tasks. Using the proposed method, a 100-miRNA signature is identified in a dataset of 8023 samples, extracted from TCGA. When running eight-state-of-the-art classifiers along with the 100-miRNA signature against the original 1046 features, it could be detected that global accuracy differs only by 1.4%. Importantly, this 100-miRNA signature is sufficient to distinguish between tumor and normal tissues. The approach is then compared against other feature selection methods, such as UFS, RFE, EN, LASSO, Genetic Algorithms, and EFS-CLA. The proposed approach provides better accuracy when tested on a 10-fold cross-validation with different classifiers and it is applied to several GEO datasets across different platforms with some classifiers showing more than 90% classification accuracy, which proves its cross-platform applicability.

Conclusions

The 100-miRNA signature is sufficiently stable to provide almost the same classification accuracy as the complete TCGA dataset, and it is further validated on several GEO datasets, across different types of cancer and platforms. Furthermore, a bibliographic analysis confirms that 77 out of the 100 miRNAs in the signature appear in lists of circulating miRNAs used in cancer studies, in stem-loop or mature-sequence form. The remaining 23 miRNAs offer potentially promising avenues for future research.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3050-8) contains supplementary material, which is available to authorized users.

qPCR-based methods for expression analysis of miRNAs

Several approaches for miRNA expression analysis have been developed in recent years. In this article, we provide an updated and comprehensive review of available qPCR-based methods for miRNA expression analysis and discuss their advantages and disadvantages. Existing techniques involve the use of stem-loop reverse transcriptase-PCR, polyadenylation of RNAs, ligation of adapters or RT with complex primers, using universal or miRNA-specific qPCR primers and/or probes. Many of these methods are oriented towards the expression analysis of mature miRNAs and few are designed for the study of pre-miRNAs and pri-miRNAs. We also discuss findings from articles that compare results from existing methods. Finally, we suggest key points for the improvement of available techniques and for the future development of additional methods.

sRNAPrimerDB: comprehensive primer design and search web service for small non-coding RNAs

MOTIVATION

Small non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs), play key roles in many biological processes. However, only a few tools can be used to develop the optimal primer or probe design for the expression profile of small ncRNAs. Here, we developed sRNAPrimerDB, the first automated primer designing and query web service for small ncRNAs.

RESULTS

The primer online designing module of sRNAPrimerDB is composed of primer design algorithms and quality evaluation of the polymerase chain reaction (PCR) primer. Five types of primers, namely, generic or specific reverse transcription primers, specific PCR primers pairs, TaqMan probe, double-hairpin probe and hybridization probe for different small ncRNA detection methods, can be designed and searched using this service. The quality of PCR primers is further evaluated using melting temperature, primer dimer, hairpin structure and specificity. Moreover, the sequence and size of each amplicon are also provided for the subsequent experiment verification. At present, 531 306 and 2 941 669 primer pairs exist across 223 species for miRNAs and piRNAs, respectively, according to sRNAPrimerDB. Several primers designed by sRNAPrimerDB are further successfully validated by subsequent experiments.

AVAILABILITY AND IMPLEMENTATION

sRNAPrimerDB is a valuable platform that can be used to detect small ncRNAs. This module can be publicly accessible at http://www.srnaprimerdb.com or http://123.57.239.141.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Differential expression of microRNAs and potential targets under drought stress in barley

Drought is a crucial environmental constraint limiting crop production in many parts of the world. microRNA (miRNA) based gene regulation has been shown to act in several pathways, including crop response to drought stress. Sequence based profiling and computational analysis have revealed hundreds of miRNAs and their potential targets in different plant species under various stress conditions, but few have been biologically verified. In this study, 11 candidate miRNAs were tested for their expression profiles in barley. Differences in accumulation of only four miRNAs (Ath-miR169b, Osa-miR1432, Hv-miRx5 and Hv-miR166b/c) were observed between drought-treated and well-watered barley in four genotypes. miRNA targets were predicted using degradome analysis of two, different genotypes, and genotype-specific target cleavage was observed. Inverse correlation of mature miRNA accumulation with miRNA target transcripts was also genotype dependent under drought treatment. Drought-responsive miRNAs accumulated predominantly in mesophyll tissues. Our results demonstrate genotype-specific miRNA regulation under drought stress and evidence for their role in mediating expression of target genes for abiotic stress response in barley.