Prioritizing and selecting likely novel miRNAs from NGS data

piRNA and miRNA Can Suppress the Expression of Multiple Sclerosis Candidate Genes

Multiple sclerosis (MS) is a common inflammatory demyelinating disease with a high mortality rate. MS is caused by many candidate genes whose specific involvement has yet to be established. The aim of our study was to identify endogenous miRNAs and piRNAs involved in the regulation of MS candidate gene expression using bioinformatic methods. A program was used to quantify the interaction of miRNA and piRNA nucleotides with mRNA of the target genes. We used 7310 miRNAs from three databases and 40,000 piRNAs. The mRNAs of the candidate genes revealed miRNA binding sites (BSs), which were located separately or formed clusters of BSs with overlapping nucleotide sequences. The miRNAs from the studied databases were generally bound to mRNAs in different combinations, but miRNAs from only one database were bound to the mRNAs of some genes. For the first time, a direct interaction between the complete sequence of piRNA nucleotides and the nucleotides of their mRNA BSs of target genes was shown. One to several clusters of BSs of miRNA and piRNA were identified in the mRNA of ADAM17, AHI1, CD226, EOMES, EVI5, IL12B, IL2RA, KIF21B, MGAT5, MLANA, SOX8, TNFRSF1A, and ZBTB46 MS candidate genes. These piRNAs form the expression regulation system of the MS candidate genes to coordinate the synthesis of their proteins. Based on these findings, associations of miRNAs, piRNAs, and candidate genes for MS diagnosis are recommended.

MirDIP 5.2: tissue context annotation and novel microRNA curation

MirDIP is a well-established database that aggregates microRNA-gene human interactions from multiple databases to increase coverage, reduce bias, and improve usability by providing an integrated score proportional to the probability of the interaction occurring. In version 5.2, we removed eight outdated resources, added a new resource (miRNATIP), and ran five prediction algorithms for miRBase and mirGeneDB. In total, mirDIP 5.2 includes 46 364 047 predictions for 27 936 genes and 2734 microRNAs, making it the first database to provide interactions using data from mirGeneDB. Moreover, we curated and integrated 32 497 novel microRNAs from 14 publications to accelerate the use of these novel data. In this release, we also extend the content and functionality of mirDIP by associating contexts with microRNAs, genes, and microRNA-gene interactions. We collected and processed microRNA and gene expression data from 20 resources and acquired information on 330 tissue and disease contexts for 2657 microRNAs, 27 576 genes and 123 651 910 gene-microRNA-tissue interactions. Finally, we improved the usability of mirDIP by enabling the user to search the database using precursor IDs, and we integrated miRAnno, a network-based tool for identifying pathways linked to specific microRNAs. We also provide a mirDIP API to facilitate access to its integrated predictions. Updated mirDIP is available at https://ophid.utoronto.ca/mirDIP.

Genetic and Epigenetic Mechanisms Deregulate the CRL2pVHL Complex in Hepatocellular Carcinoma

Dysregulation of ubiquitin-proteasome pathway genes through copy number alteration, promoter hypomethylation, and miRNA deregulation is involved in cancer development and progression. Further characterizing alterations in these genes may uncover novel drug targets across a range of diseases in which druggable alterations are uncommon, including hepatocellular carcinoma (HCC). We analyzed 377 HCC and 59 adjacent non-malignant liver tissue samples, focusing on alterations to component genes of the widely studied CRL2^pVHL E3 ubiquitin ligase complex. mRNA upregulation of the component genes was common, and was correlated with DNA hypomethylation and copy number increase, but many tumours displayed overexpression that was not explained by either mechanism. Interestingly, we found 66 miRNAs, including 39 previously unannotated miRNAs, that were downregulated in HCC and predicted to target one or more CRL2^pVHL components. Several miRNAs, including hsa-miR-101-3p and hsa-miR-139-5p, were negatively correlated with multiple component genes, suggesting that miRNA deregulation may contribute to CRL2^pVHL overexpression. Combining miRNA and mRNA expression, DNA copy number, and methylation status into one multidimensional survival analysis, we found a significant association between greater numbers of alterations and poorer overall survival for multiple component genes. While the intricacies of CRL2^pVHL complex gene regulation require additional research, it is evident that multiple causes for the deregulation of these genes must be considered in HCC, including non-traditional mechanisms.

Non-Coding RNAs in Preeclampsia-Molecular Mechanisms and Diagnostic Potential

Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality worldwide. Defects in trophoblast invasion, differentiation of extravillous trophoblasts and spiral artery remodeling are key factors in PE development. Currently there are no predictive biomarkers clinically available for PE. Recent technological advancements empowered transcriptome exploration and led to the discovery of numerous non-coding RNA species of which microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most investigated. They are implicated in the regulation of numerous cellular functions, and as such are being extensively explored as potential biomarkers for various diseases. Altered expression of numerous lncRNAs and miRNAs in placenta has been related to pathophysiological processes that occur in preeclampsia. In the following text we offer summary of the latest knowledge of the molecular mechanism by which lnRNAs and miRNAs (focusing on the chromosome 19 miRNA cluster (C19MC)) contribute to pathophysiology of PE development and their potential utility as biomarkers of PE, with special focus on sample selection and techniques for the quantification of lncRNAs and miRNAs in maternal circulation.

miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale

Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2.

Profiling the small non-coding RNA transcriptome of the human placenta

Proper functioning of the human placenta is critical for maternal and fetal health. While microRNAs (miRNAs) are known to impact placental gene expression, the effects of other small non-coding RNAs (sncRNAs) on the placental transcriptome are not well-established, and are emerging topics in the study of environmental influence on fetal development and reproductive health. Here, we assembled a cohort of 30 placental chorionic villi samples of varying gestational ages (M ± SD = 23.7 ± 11.3 weeks) to delineate the human placental sncRNA transcriptome through small RNA sequence analysis. We observed expression of 1544 sncRNAs, which include 48 miRNAs previously unannotated in humans. Additionally, 18,003 miRNA variants (isomiRs) were identified from the 654 observed miRNA species. This characterization of the term and pre-term placental sncRNA transcriptomes provides data fundamental to future investigations of their regulatory functions in the human placenta, and the baseline expression pattern needed for identifying changes in response to environmental factors, or under disease conditions.

Reactivation of Multiple Fetal miRNAs in Lung Adenocarcinoma

MicroRNAs (miRNAs) play vital roles in the regulation of normal developmental pathways. However, cancer cells can co-opt these miRNAs, and the pathways that they regulate, to drive pro-tumourigenic phenotypes. Characterization of the miRNA transcriptomes of fetal organs is essential for identifying these oncofetal miRNAs, but it has been limited by fetal sample availability. As oncofetal miRNAs are absent from healthy adult lungs, they represent ideal targets for developing diagnostic and therapeutic strategies. We conducted small RNA sequencing of a rare collection of 25 human fetal lung (FL) samples and compared them to two independent cohorts (n = 140, n = 427), each comprised of adult non-neoplastic lung (ANL) and lung adenocarcinoma (LUAD) samples. We identified 13 oncofetal miRNAs that were expressed in FL and LUAD but not in ANL. These oncofetal miRNAs are potential biomarkers for LUAD detection (AUC = 0.963). Five of these miRNAs are derived from the imprinted C14MC miRNA cluster at the 14q32 locus, which has been associated with cancer development and abnormal fetal and placental development. Additionally, we observed the pulmonary expression of 44 previously unannotated miRNAs. The sequencing of these fetal lung samples also provides a baseline resource against which aberrant samples can be compared.

CoolMPS: evaluation of antibody labeling based massively parallel non-coding RNA sequencing

Results of massive parallel sequencing-by-synthesis vary depending on the sequencing approach. CoolMPS™ is a new sequencing chemistry that incorporates bases by labeled antibodies. To evaluate the performance, we sequenced 240 human non-coding RNA samples (dementia patients and controls) with and without CoolMPS. The Q30 value as indicator of the per base sequencing quality increased from 91.8 to 94%. The higher quality was reached across the whole read length. Likewise, the percentage of reads mapping to the human genome increased from 84.9 to 86.2%. For both technologies, we computed similar distributions between different RNA classes (miRNA, piRNA, tRNA, snoRNA and yRNA) and within the classes. While standard sequencing-by-synthesis allowed to recover more annotated miRNAs, CoolMPS yielded more novel miRNAs. The correlation between the two methods was 0.97. Evaluating the diagnostic performance, we observed lower minimal P-values for CoolMPS (adjusted P-value of 0.0006 versus 0.0004) and larger effect sizes (Cohen's d of 0.878 versus 0.9). Validating 19 miRNAs resulted in a correlation of 0.852 between CoolMPS and reverse transcriptase-quantitative polymerase chain reaction. Comparison to data generated with Illumina technology confirmed a known shift in the overall RNA composition. With CoolMPS we evaluated a novel sequencing-by-synthesis technology showing high performance for the analysis of non-coding RNAs.

IsoMiRmap-fast, deterministic, and exhaustive mining of isomiRs from short RNA-seq datasets

MOTIVATION

MicroRNA (miRNA) precursor arms give rise to multiple isoforms simultaneously called "isomiRs." IsomiRs from the same arm typically differ by a few nucleotides at either their 5´ or 3´ termini, or both. In humans, the identities and abundances of isomiRs depend on a person's sex, population of origin, race/ethnicity, and on tissue type, tissue state, and disease type/subtype. Moreover, nearly half of the time the most abundant isomiR differs from the miRNA sequence found in public databases. Accurate mining of isomiRs from deep sequencing data is thus important.

RESULTS

We developed isoMiRmap, a fast, standalone, user-friendly mining tool that identifies and quantifies all isomiRs by directly processing short RNA-seq datasets. IsoMiRmap is a portable "plug-and-play" tool, requires minimal setup, has modest computing and storage requirements, and can process an RNA-seq dataset with 50 million reads in just a few minutes on an average laptop. IsoMiRmap deterministically and exhaustively reports all isomiRs in a given deep sequencing dataset and quantifies them accurately (no double-counting). IsoMiRmap comprehensively reports all miRNA precursor locations from which an isomiR may be transcribed, tags as 'ambiguous' isomiRs whose sequences exist both inside and outside of the space of known miRNA sequences and reports the public identifiers of common single-nucleotide polymorphisms and documented somatic mutations that may be present in an isomiR. IsoMiRmap also identifies isomiRs with 3´ non-templated post-transcriptional additions. Compared to similar tools, isoMiRmap is the fastest, reports more bona fide isomiRs, and provides the most comprehensive information related to an isomiR's transcriptional origin.

AVAILABILITY

The codes for isoMiRmap are freely available at https://cm.jefferson.edu/isoMiRmap/ and https://github.com/TJU-CMC-Org/isoMiRmap/. IsomiR profiles for the datasets of the 1000 Genomes Project, spanning five population groups, and The Cancer Genome Atlas (TCGA), spanning 33 cancer studies, are also available at https://cm.jefferson.edu/isoMiRmap/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data

For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer's miRNAs.

A mouse tissue atlas of small noncoding RNA

We report a systematic unbiased analysis of small RNA molecule expression in 11 different tissues of the model organism mouse. We discovered uncharacterized noncoding RNA molecules and identified that ∼30% of total noncoding small RNA transcriptome are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. Distinct distribution patterns of small RNA across the body suggest the existence of tissue-specific mechanisms involved in noncoding RNA processing.

Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to “arm switching” between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.

Role of long noncoding RNA MEG3/miR-378/GRB2 axis in neuronal autophagy and neurological functional impairment in ischemic stroke

Autophagy has been shown to maintain neural system homeostasis during stroke. However, the molecular mechanisms underlying neuronal autophagy in ischemic stroke remain poorly understood. This study aims to investigate the regulatory mechanisms of the pathway consisting of MEG3 (maternally expressed gene 3), microRNA-378 (miR-378), and GRB2 (growth factor receptor-bound protein 2) in neuronal autophagy and neurological functional impairment in ischemic stroke. A mouse model of the middle cerebral artery occluded-induced ischemic stroke and an in vitro model of oxygen-glucose deprivation-induced neuronal injury were developed. To understand the role of the MEG3/miR-378/GRB2 axis in the neuronal regulation, the expression of proteins associated with autophagy in neurons was measured by Western blotting analysis, and neuron death was evaluated using a lactate dehydrogenase leakage rate test. First, it was found that the GRB2 gene, up-regulated in middle cerebral artery occluded-operated mice and oxygen-glucose deprivation-exposed neurons, was a target gene of miR-378. Next, miR-378 inhibited neuronal loss and neurological functional impairment in mice, as well as neuronal autophagy and neuronal death by silencing of GRB2. Confirmatory in vitro experiments showed that MEG3 could specifically bind to miR-378 and subsequently up-regulate the expression of GRB2, which in turn suppressed the activation of Akt/mTOR pathway. Taken together, these findings suggested that miR-378 might protect against neuronal autophagy and neurological functional impairment and proposed that a MEG3/miR-378/GRB2 regulatory axis contributed to better understanding of the pathophysiology of ischemic stroke.

A novel microRNA boosts hyper-β-oxidation of fatty acids in liver by impeding CEP350-mediated sequestration of PPARα and thus restricts chronic hepatitis C

Imbalance in lipid metabolism induces steatosis in liver during Chronic hepatitis C (CHC). Contribution of microRNAs in regulating lipid homoeostasis and liver disease progression is well established using small RNA-transcriptome data. Owing to the complexity in the development of liver diseases, the existence and functional importance of yet undiscovered regulatory miRNAs in disease pathogenesis was explored in this study using the unmapped sequences of the transcriptome data of HCV-HCC liver tissues following miRDeep2.pl pipeline. MicroRNA-c12 derived from the first intron of LGR5 of chromosome 12 was identified as one of the miRNA like sequences retrieved in this analysis that showed human specific origin. Northern blot hybridization has proved its existence in the hepatic cell line. Enrichment of premiR-c12 in dicer-deficient cells and miR-c12 in Ago2-RISC complex clearly suggested that it followed canonical miRNA biogenesis pathway and accomplished its regulatory function. Expression of this miRNA was quite low in CHC tissues than normal liver implying HCV-proteins might be regulating its biogenesis. Promoter scanning and ChIP analysis further revealed that under expression of p53 and hyper-methylation of STAT3 binding site upon HCV infection restricted its expression in CHC tissues. Centrosomal protein 350 (CEP350), which sequestered PPARα, was identified as one of the targets of miR-c12 using Miranda and validated by luciferase assay/western blot analysis. Furthermore, reduced triglyceride accumulation and enhanced PPARα mediated transcription of β-oxidation genes upon restoration of miR-c12 in liver cells suggested its role in lipid catabolism. Thus this study is reporting miR-c12 for the first time and showed its' protective role during chronic HCV infection.

MirGeneDB 2.0: the metazoan microRNA complement

Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database - MirGeneDB - to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.

The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals

The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.

Upgrading the Repertoire of miRNAs in Gastric Adenocarcinoma to Provide a New Resource for Biomarker Discovery

Recent studies have uncovered microRNAs (miRNAs) that have been overlooked in early genomic explorations, which show remarkable tissue- and context-specific expression. Here, we aim to identify and characterize previously unannotated miRNAs expressed in gastric adenocarcinoma (GA). Raw small RNA-sequencing data were analyzed using the miRMaster platform to predict and quantify previously unannotated miRNAs. A discovery cohort of 475 gastric samples (434 GA and 41 adjacent nonmalignant samples), collected by The Cancer Genome Atlas (TCGA), were evaluated. Candidate miRNAs were similarly assessed in an independent cohort of 25 gastric samples. We discovered 170 previously unannotated miRNA candidates expressed in gastric tissues. The expression of these novel miRNAs was highly specific to the gastric samples, 143 of which were significantly deregulated between tumor and nonmalignant contexts (p-adjusted < 0.05; fold change > 1.5). Multivariate survival analyses showed that the combined expression of one previously annotated miRNA and two novel miRNA candidates was significantly predictive of patient outcome. Further, the expression of these three miRNAs was able to stratify patients into three distinct prognostic groups (p = 0.00003). These novel miRNAs were also present in the independent cohort (43 sequences detected in both cohorts). Our findings uncover novel miRNA transcripts in gastric tissues that may have implications in the biology and management of gastric adenocarcinoma.

An estimate of the total number of true human miRNAs

While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

Small RNA and degradome deep sequencing reveal respective roles of cold-related microRNAs across Chinese wild grapevine and cultivated grapevine

Background

Chinese wild grapevine (Vitis amurensis) has remarkable cold stress tolerance, exceeding that of the common cultivated grapevine (Vitis vinifera L.).

Result

Here, we surveyed the expression dynamics of microRNAs (miRNAs) across Chinese wild grapevine (cv. Beibinghong) and cultivated grapevine (cv. Cabernet Sauvignon) under cold stress using high-throughput sequencing. We identified 186 known miRNAs in cultivated grape and 427 known miRNAs in Beibinghong. Of the identified miRNAs, 59 are conserved miRNAs orthologous in Cabernet Sauvignon and Beibinghong. In addition, 105 and 129 novel miRNAs were identified in Cabernet Sauvignon and Beibinghong, respectively. The expression of some miRNAs was related to cold stress both in Cabernet Sauvignon and Beibinghong. Many cold-related miRNAs in Cabernet Sauvignon and Beibinghong were predicted to target stress response-related genes such as MYB, WRKY, bHLH transcription factor genes, and heat shock protein genes. However, the expression tendency under cold treatment of many of these miRNAs was different between Cabernet Sauvignon and Beibinghong. Different modes of expression of cultivated and Chinese wild grape miRNAs were indicated in key pathways under cold stress by degradome, target prediction, GO, and KEGG analyses.

Conclusion

Our study indicated three likely reasons that led to the different cold stress tolerance levels of Cabernet Sauvignon and Beibinghong. Specifically, there may be (1) differential expression of orthologous miRNAs between cultivated grapevine and Chinese wild grape; (2) species-specific miRNAs or target genes; or (3) different regulatory models of miRNAs in cultivated and Chinese wild grape in some key pathways.

miRCarta: a central repository for collecting miRNA candidates

The continuous increase of available biological data as consequence of modern high-throughput technologies poses new challenges for analysis techniques and database applications. Especially for miRNAs, one class of small non-coding RNAs, many algorithms have been developed to predict new candidates from next-generation sequencing data. While the amount of publications describing novel miRNA candidates keeps steadily increasing, the current gold standard database for miRNAs - miRBase - has not been updated since June 2014. As a result, publications describing new miRNA candidates in the last three to five years might have a substantial overlap of candidates without noticing. With miRCarta we implemented a database to collect novel miRNA candidates and augment the information provided by miRBase. In the first stage, miRCarta is thought to be a highly sensitive collection of potential miRNA candidates with a high degree of analysis functionality, annotations and details on each miRNA. We added-besides the full content of the miRBase-12,857 human miRNA precursors to miRCarta. Users can match their own predictions to the entries of miRCarta to reduce potential redundancies in their studies. miRCarta provides the most comprehensive collection of human miRNAs and miRNA candidates to form a basis for further refinement and validation studies. The database is freely accessible at https://mircarta.cs.uni-saarland.de/.

Small RNA sequences derived from pre-microRNAs in the supraspliceosome

MicroRNAs (miRNAs) are short non-coding RNAs that negatively regulate the expression and translation of genes in healthy and diseased tissues. Herein, we characterize short RNAs from human HeLa cells found in the supraspliceosome, a nuclear dynamic machine in which pre-mRNA processing occurs. We sequenced small RNAs (<200 nt) extracted from the supraspliceosome, and identified sequences that are derived from 200 miRNAs genes. About three quarters of them are mature miRNAs, whereas the rest account for various defined regions of the pre-miRNA, and its hairpin-loop precursor. Out of these aligned sequences, 53 were undetected in cellular extract, and the abundance of additional 48 strongly differed from that in cellular extract. Notably, we describe seven abundant miRNA-derived sequences that overlap non-coding exons of their host gene. The rich collection of sequences identical to pre-miRNAs at the supraspliceosome suggests overlooked nuclear functions. Specifically, the abundant hsa-mir-99b may affect splicing of LINC01129 primary transcript through base-pairing with its exon-intron junction. Using suppression and overexpression experiments, we show that hsa-mir-7704 negatively regulates the level of the lncRNA HAGLR. We claim that in cases of extended base-pairing complementarity, such supraspliceosomal pre-miRNA sequences might have a role in transcription attenuation, maturation and processing.

Opportunities for microRNAs in the Crowded Field of Cardiovascular Biomarkers

Cardiovascular diseases exist across all developed countries. Biomarkers that can predict or diagnose diseases early in their pathogeneses can reduce their morbidity and mortality in afflicted individuals. microRNAs are small regulatory RNAs that modulate translation and have been identified as potential fluid-based biomarkers across numerous maladies. We describe the current state of cardiovascular disease biomarkers across a range of diseases, including myocardial infarction, acute coronary syndrome, myocarditis, hypertension, heart failure, heart transplantation, aortic stenosis, diabetic cardiomyopathy, atrial fibrillation, and sepsis. We present the current understanding of microRNAs as possible biomarkers in these categories and where their best opportunities exist to enter clinical practice.

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity

The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( https://mircarta.cs.uni-saarland.de ).

MicroRNA in diagnosis and therapy monitoring of early-stage triple-negative breast cancer

Breast cancer is a heterogeneous disease with distinct molecular subtypes including the aggressive subtype triple-negative breast cancer (TNBC). We compared blood-borne miRNA signatures of early-stage basal-like (cytokeratin-CK5-positive) TNBC patients to age-matched controls. The miRNAs of TNBC patients were assessed prior to and following platinum-based neoadjuvant chemotherapy (NCT). After an exploratory genome-wide study on 21 cases and 21 controls using microarrays, the identified signatures were verified independently in two laboratories on the same and a new cohort by RT-qPCR. We differentiated the blood of TNBC patients before NCT from controls with 84% sensitivity. The most significant miRNA for this diagnostic classification was miR-126-5p (two tailed t-test p-value of 1.4 × 10⁻⁵). Validation confirmed the microarray results for all tested miRNAs. Comparing cancer patients prior to and post NCT highlighted 321 significant miRNAs (among them miR-34a, p-value of 1.2 × 10⁻²³). Our results also suggest that changes in miRNA expression during NCT may have predictive potential to predict pathological complete response (pCR). In conclusion we report that miRNA expression measured from blood facilitates early and minimally-invasive diagnosis of basal-like TNBC. We also demonstrate that NCT has a significant influence on miRNA expression. Finally, we show that blood-borne miRNA profiles monitored over time have potential to predict pCR.

miRge 2.0 for comprehensive analysis of microRNA sequencing data

Background

miRNAs play important roles in the regulation of gene expression. The rapidly developing field of microRNA sequencing (miRNA-seq; small RNA-seq) needs comprehensive, robust, user-friendly and standardized bioinformatics tools to analyze these large datasets. We present miRge 2.0, in which multiple enhancements were made towards these goals.

Results

miRge 2.0 has become more comprehensive with increased functionality including a novel miRNA detection method, A-to-I editing analysis, integrated standardized GFF3 isomiR reporting, and improved alignment to miRNAs. The novel miRNA detection method uniquely uses both miRNA hairpin sequence structure and composition of isomiRs resulting in higher specificity for potential miRNA identification. Using known miRNA data, our support vector machine (SVM) model predicted miRNAs with an average Matthews correlation coefficient (MCC) of 0.939 over 32 human cell datasets and outperformed miRDeep2 and miRAnalyzer regarding phylogenetic conservation. The A-to-I editing detection strongly correlated with a reference dataset with adjusted R² = 0.96. miRge 2.0 is the most up-to-date aligner with custom libraries to both miRBase v22 and MirGeneDB v2.0 for 6 species: human, mouse, rat, fruit fly, nematode and zebrafish; and has a tool to create custom libraries. For user-friendliness, miRge 2.0 is incorporated into bcbio-nextgen and implementable through Bioconda.

Conclusions

miRge 2.0 is a redesigned, leading miRNA RNA-seq aligner with several improvements and novel utilities. miRge 2.0 is freely available at: https://github.com/mhalushka/miRge.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2287-y) contains supplementary material, which is available to authorized users.

Expanding the miRNA Transcriptome of Human Kidney and Renal Cell Carcinoma

Despite advancements in therapeutic strategies, diagnostic and prognostic molecular markers of kidney cancer remain scarce, particularly in patients who do not harbour well-defined driver mutations. Recent evidence suggests that a large proportion of the human noncoding transcriptome has escaped detection in early genomic explorations. Here, we undertake a large-scale analysis of small RNA-sequencing data from both clear cell renal cell carcinoma (ccRCC) and nonmalignant samples to generate a robust set of miRNAs that remain unannotated in kidney tissues. We find that these novel kidney miRNAs are also expressed in renal cancer cell lines. Moreover, these sequences are differentially expressed between ccRCC and matched nonmalignant tissues, implicating their involvement in ccRCC biology and potential utility as tumour-specific markers of disease. Indeed, we find some of these miRNAs to be significantly associated with patient survival. Finally, target prediction and subsequent pathway analysis reveals that miRNAs previously unannotated in kidney tissues may target genes involved in ccRCC tumourigenesis and disease biology. Taken together, our results represent a new resource for the study of kidney cancer and underscore the need to characterize the unexplored areas of the transcriptome.

Small ncRNA-Seq Results of Human Tissues: Variations Depending on Sample Integrity

BACKGROUND

Although mature miRNAs are relatively stable in vivo, RNA degradation can have a substantial influence on small noncoding RNA (sncRNA) profiles.

METHODS

Using different tissue storage conditions and RNA isolation procedures, we analyzed the integrity and quality of RNA isolates from human lung and heart tissues. We sequenced a total of 64 RNA samples and quantified the effect of RNA degradation, DNA contamination, and other confounding factors on the sncRNA-seq data. Besides microRNAs, other noncoding RNA species (piRNAs, tRNAs, snoRNAs, rRNAs) were investigated.

RESULTS

Consistent with previous results, we found that the tissue specificity of microRNAs is generally well preserved. The distribution of microRNA isoforms was similar to the distribution of canonical forms. New miRNAs were more frequently discovered in degraded samples. sncRNA Reads generated from degraded samples mapped frequently to piRNAs, tRNAs, snoRNAs, or scaRNAs. Sequencing reads that were depleted of sncRNAs showed an increased mapping frequency to bacterial species.

CONCLUSIONS

Our data emphasize the importance of sample integrity, especially for next-generation sequencing (NGS)-based high-throughput sncRNA profiles. For the prediction of novel miRNAs in particular, only samples with the highest RNA integrity should be used in order to avoid identification of false "miRNAs."

Large-scale discovery of previously undetected microRNAs specific to human liver

MicroRNAs (miRNAs) are crucial regulators of gene expression in normal development and cellular homeostasis. While miRNA repositories contain thousands of unique sequences, they primarily contain molecules that are conserved across several tissues, largely excluding lineage and tissue-specific miRNAs. By analyzing small non-coding RNA sequencing data for abundance and secondary RNA structure, we discovered 103 miRNA candidates previously undescribed in liver tissue. While expression of some of these unannotated sequences is restricted to non-malignant tissue, downregulation of most of the sequences was detected in liver tumors, indicating their importance in the maintenance of liver homeostasis. Furthermore, target prediction revealed the involvement of the unannotated miRNA candidates in fatty-acid metabolism and tissue regeneration, which are key pathways in liver biology. Here, we provide a comprehensive analysis of the undiscovered liver miRNA transcriptome, providing new resources for a deeper exploration of organ-specific biology and disease.

Dysregulation of miRNA and its potential therapeutic application in schizophrenia

Although it is generally believed that genetic and developmental factors play critical roles in pathogenesis of schizophrenia, however, the precise etiological mechanism of schizophrenia remains largely unknown. Over past decades, miRNAs have emerged as an essential post-transcriptional regulator in gene expression regulation. The importance of miRNA in brain development and neuroplasticity has been well-established. Abnormal expression and dysfunction of miRNAs are known to involve in the pathophysiology of many neuropsychiatric diseases including schizophrenia. In this review, we summarized the recent findings in the schizophrenia-associated dysregulation of miRNA and functional roles in the development and pathogenesis of schizophrenia. We also discussed the potential therapeutic implications of miRNA regulation in the illness.

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs

The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.

A comprehensive, cell specific microRNA catalogue of human peripheral blood

With this study, we provide a comprehensive reference dataset of detailed miRNA expression profiles from seven types of human peripheral blood cells (NK cells, B lymphocytes, cytotoxic T lymphocytes, T helper cells, monocytes, neutrophils and erythrocytes), serum, exosomes and whole blood. The peripheral blood cells from buffy coats were typed and sorted using FACS/MACS. The overall dataset was generated from 450 small RNA libraries using high-throughput sequencing. By employing a comprehensive bioinformatics and statistical analysis, we show that 3′ trimming modifications as well as composition of 3′ added non-templated nucleotides are distributed in a lineage-specific manner—the closer the hematopoietic progenitors are, the higher their similarities in sequence variation of the 3′ end. Furthermore, we define the blood cell-specific miRNA and isomiR expression patterns and identify novel cell type specific miRNA candidates. The study provides the most comprehensive contribution to date towards a complete miRNA catalogue of human peripheral blood, which can be used as a reference for future studies. The dataset has been deposited in GEO and also can be explored interactively following this link: http://134.245.63.235/ikmb-tools/bloodmiRs.

Micro-ribonucleic acids and extracellular vesicles repertoire in the spent culture media is altered in women undergoing In Vitro Fertilization

MicroRNAs (miRNAs) are class of small RNA molecules with major impact on gene regulation. We analyzed the potential of miRNAs secreted from pre-implantation embryos into the embryonic culture media as biomarkers to predict successful pregnancy. Using microarray analysis, we profiled the miRNome of the 56 spent culture media (SCM) after embryos transfer and found a total of 621 miRNAs in the SCM. On average, we detected 163 miRNAs in SCM of samples with failed pregnancies, but only 149 SCM miRNAs of embryos leading to pregnancies. MiR-634 predicted an embryo transfer leading to a positive pregnancy with an accuracy of 71% and a sensitivity of 85%. Among the 621 miRNAs, 102 (16.4%) showed a differential expression between positive and negative outcome of pregnancy with miR-29c-3p as the most significantly differentially expressed miRNA. The number of extracellular vehicles was lower in SCM with positive outcomes (3.8 × 10⁹/mL EVs), as compared to a negative outcome (7.35 × 10⁹/mL EVs) possibly explaining the reduced number of miRNAs in the SCM associated with failed pregnancies. The analysis of the miRNome in the SCM of couples undergoing fertility treatment lays the ground towards development of biomarkers to predict successful pregnancy and towards understanding the role of embryonic miRNAs found in the SCM.

Toward the human cellular microRNAome

MicroRNAs are short RNAs that serve as regulators of gene expression and are essential components of normal development as well as modulators of disease. MicroRNAs generally act cell-autonomously, and thus their localization to specific cell types is needed to guide our understanding of microRNA activity. Current tissue-level data have caused considerable confusion, and comprehensive cell-level data do not yet exist. Here, we establish the landscape of human cell-specific microRNA expression. This project evaluated 8 billion small RNA-seq reads from 46 primary cell types, 42 cancer or immortalized cell lines, and 26 tissues. It identified both specific and ubiquitous patterns of expression that strongly correlate with adjacent superenhancer activity. Analysis of unaligned RNA reads uncovered 207 unknown minor strand (passenger) microRNAs of known microRNA loci and 495 novel putative microRNA loci. Although cancer cell lines generally recapitulated the expression patterns of matched primary cells, their isomiR sequence families exhibited increased disorder, suggesting DROSHA- and DICER1-dependent microRNA processing variability. Cell-specific patterns of microRNA expression were used to de-convolute variable cellular composition of colon and adipose tissue samples, highlighting one use of these cell-specific microRNA expression data. Characterization of cellular microRNA expression across a wide variety of cell types provides a new understanding of this critical regulatory RNA species.

Technical Stability and Biological Variability in MicroRNAs from Dried Blood Spots: A Lung Cancer Therapy-Monitoring Showcase

BACKGROUND

Different work flows have been proposed to use miRNAs as blood-borne biomarkers. In particular, the method used for collecting blood from patients can considerably influence the diagnostic results.

METHODS

We explored whether dried blood spots (DBSs) facilitate stable miRNA measurements and compared its technical stability with biological variability. First, we tested the stability of DBS samples by generating from 1 person 18 whole-genome-wide miRNA profiles of DBS samples that were exposed to different temperature and humidity conditions. Second, we investigated technical reproducibility by performing 7 replicates of DBS again from 1 person. Third, we investigated DBS samples from 53 patients with lung cancer undergoing different therapies. Across these 3 stages, 108 genome-wide miRNA profiles from DBS were generated and evaluated biostatistically.

RESULTS

In the stability analysis, we observed that temperature and humidity had an overall limited influence on the miRNomes (average correlation between the different conditions of 0.993). Usage of a silica gel slightly diminished DBS' technical reproducibility. The 7 technical replicates had an average correlation of 0.996. The correlation with whole-blood PAXGene miRNomes of the same individual was remarkable (correlation of 0.88). Finally, evaluation of the samples from the 53 patients with lung cancer exposed to different therapies showed that the biological variations exceeded the technical variability significantly (P &lt; 0.0001), yielding 51 dysregulated miRNAs.

CONCLUSIONS

We present a stable work flow for profiling of whole miRNomes on the basis of samples collected from DBS. Biological variations exceeded technical variations significantly. DBS-based miRNA profiles will potentially further the translational character of miRNA biomarker studies.

Bias in recent miRBase annotations potentially associated with RNA quality issues

Although microRNAs are supposed to be stable in-vivo, degradation processes potentially blur our knowledge on the small oligonucleotides. We set to quantify the effect of degradation on microRNAs in mouse to identify causes for distorted microRNAs patterns. In liver, we found 298, 99 and 8 microRNAs whose expression significantly correlated to RNA integrity, storage time at room temperature and storage time at 4 °C, respectively. Expression levels of 226 microRNAs significantly differed between liver samples with high RNA integrity compared to liver samples with low RNA integrity by more than two-fold. Especially the 157 microRNAs with increased expression in tissue samples with low RNA integrity were most recently added to miRBase. Testing potentially confounding sources, e.g. in-vitro degraded RNA depleted of small RNAs, we detected signals for 350 microRNAs, suggesting cross-hybridization of fragmented RNAs. Therefore, we conclude that especially microRNAs added in the latest miRBase versions might be artefacts due to RNA degradation. The results facilitate differentiation between degradation-resilient microRNAs, degradation-sensitive microRNAs, and likely erroneously annotated microRNAs. The latter were largely identified by NGS but not experimentally validated and can severely bias microRNA biomarker research and impact the value of microRNAs as diagnostic, prognostic or therapeutic tools.

Epigenetic Biomarkers and Cardiovascular Disease: Circulating MicroRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNA (20-25 nucleotides) involved in gene regulation. In recent years, miRNAs have emerged as a key epigenetic mechanism in the development and physiology of the cardiovascular system. These molecular species regulate basic functions in virtually all cell types, and are therefore directly associated with the pathophysiology of a large number of cardiovascular diseases. Since their relatively recent discovery in extracellular fluids, miRNAs have been studied as potential biomarkers of disease. A wide array of studies have proposed miRNAs as circulating biomarkers of different cardiovascular pathologies (eg, myocardial infarction, coronary heart disease, and heart failure, among others), which may have superior physicochemical and biochemical properties than the conventional protein indicators currently used in clinical practice. In the present review, we provide a brief introduction to the field of miRNAs, paying special attention to their potential clinical application. This includes their possible role as new diagnostic or prognostic biomarkers in cardiovascular disease.

miRNA assays in the clinical laboratory: workflow, detection technologies and automation aspects

microRNAs (miRNAs) are short non-coding RNA molecules that regulate gene expression in eukaryotes. Their differential abundance is indicative or even causative for a variety of pathological processes including cancer or cardiovascular disorders. Due to their important biological function, miRNAs represent a promising class of novel biomarkers that may be used to diagnose life-threatening diseases, and to monitor disease progression. Further, they may guide treatment selection or dosage of drugs. miRNAs from blood or derived fractions are particularly interesting candidates for routine laboratory applications, as they can be measured in most clinical laboratories already today. This assures a good accessibility of respective tests. Albeit their great potential, miRNA-based diagnostic tests have not made their way yet into the clinical routine, and hence no standardized workflows have been established to measure miRNAs for patients' benefit. In this review we summarize the detection technologies and workflow options that exist to measure miRNAs, and we describe the advantages and disadvantages of each of these options. Moreover, we also provide a perspective on data analysis aspects that are vital for translation of raw data into actionable diagnostic test results.

QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing

BACKGROUND

Genome-wide miRNA expression data can be used to study miRNA dysregulation comprehensively. Although many open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accurate miRNA quantification from large-scale miRNA-seq dataset. We implemented a pipeline called QuickMIRSeq for accurate quantification of known miRNAs and miRNA isoforms (isomiRs) from multiple samples simultaneously.

RESULTS

QuickMIRSeq considers the unique nature of miRNAs and combines many important features into its implementation. First, it takes advantage of high redundancy of miRNA reads and introduces joint mapping of multiple samples to reduce computational time. Second, it incorporates the strand information in the alignment step for more accurate quantification. Third, reads potentially arising from background noise are filtered out to improve the reliability of miRNA detection. Fourth, sequences aligned to miRNAs with mismatches are remapped to a reference genome to further reduce false positives. Finally, QuickMIRSeq generates a rich set of QC metrics and publication-ready plots.

CONCLUSIONS

The rich visualization features implemented allow end users to interactively explore the results and gain more insights into miRNA-seq data analyses. The high degree of automation and interactivity in QuickMIRSeq leads to a substantial reduction in the time and effort required for miRNA-seq data analysis.

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

Background

We present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques.

Results

Starting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to the miRBase. Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood.

Conclusions

While there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.

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.

Bias in High-Throughput Analysis of miRNAs and Implications for Biomarker Studies

A certain degree of bias in high-throughput molecular technologies including microarrays and next-generation sequencing (NGS) is known. To quantify the actual impact of the biomarker discovery platform on miRNA profiles, we first performed a meta-analysis: raw data of 1 539 microarrays and 705 NGS blood-borne miRNomes were statistically evaluated, suggesting a substantial influence of the technology on biomarker profiles. We observed highly significant dependency of the miRNA nucleotide composition on the expression level. Higher expression in NGS was discovered for uracil-rich miRNAs (p = 7 × 10(-37)), while high expression in microarrays was found predominantly for guanine-rich miRNAs (p = 3 × 10(-33)). To verify the findings, 10 identical replicates of one individual were measured using NGS and microarrays (2 525 miRNAs from miRBase version 21). Overall, we calculated a correlation coefficient of 0.414 for both technologies. Detailed analysis however revealed that the correlation was observed only for miRNAs in the early miRBase versions (<8). The majority of miRNAs (2 013 from miRBase version 8 onward) was not correlated between microarray and NGS. Specifically, we observed 67 miRNAs with a median read count above 10 in NGS, while they were not detected in any of the 10 replicated array experiments. In contrast, 234 miRNAs were discovered in all 10 replicated array measurements but were not found in any of the NGS experiments of the same individual. While the first group had average guanine content of 22%, the latter group consisted of 41% of this nucleotide. Selected concordant and discordant miRNAs were tested in quantitative real-time-polymerase chain reaction (RT-qPCR) experiments again of the same individual, providing further evidence for the substantial bias depending on the base composition. As a consequence, biomarkers that have been discovered by specific high-throughout technologies have to be carefully considered. Especially for validation of the platform, the selection of reasonable candidates is essential.