Prioritizing and selecting likely novel miRNAs from NGS data.

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

Deep characterization of blood cell miRNomes by NGS.

A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders.

BACKGROUND: While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians. METHODS: We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments. RESULTS: We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates.

Influence of the confounding factors age and sex on microRNA profiles from peripheral blood.

BACKGROUND: MicroRNAs (miRNAs) measured from blood samples are promising minimally invasive biomarker candidates that have been extensively studied in several case-control studies. However, the influence of age and sex as confounding variables remains largely unknown. METHODS: We systematically explored the impact of age and sex on miRNAs in a cohort of 109 physiologically unaffected individuals whose blood was characterized by microarray technology (stage 1). We also investigated an independent cohort from a different institution consisting of 58 physiologically unaffected individuals having a similar mean age but with a smaller age distribution. These samples were measured by use of high-throughput sequencing (stage 2). RESULTS: We detected 318 miRNAs that were significantly correlated with age in stage 1 and, after adjustment for multiple testing of 35 miRNAs, remained statistically significant. Regarding sex, 144 miRNAs showed significant dysregulation. Here, no miRNA remained significant after adjustment for multiple testing. In the high-throughput datasets of stage 2, we generally observed a smaller number of significant associations, mainly as an effect of the smaller cohort size and age distribution. Nevertheless, we found 7 miRNAs that were correlated with age, of which 5 were concordant with stage 1. CONCLUSIONS: The age distribution of individuals recruited for case-control studies needs to be carefully considered, whereas sex may be less confounding. To support the translation of miRNAs into clinical application, we offer a web-based application (http://www.ccb.uni-saarland.de/mirnacon) to test individual miRNAs or miRNA signatures for their likelihood of being influenced.