Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

IsoSeek for unbiased and UMI-informed sequencing of miRNAs from low input samples at single-nucleotide resolution

Besides canonical microRNAs (miRNAs), sequence-based variations called isomiRs have biological relevance and diagnostic potential; however, accurate calling of these post-transcriptional modifications is challenging, especially for low input samples. Here, we present IsoSeek, a sequencing protocol that reduces ligation and PCR amplification bias and improves the accuracy of miRNA detection in low input samples. We describe steps for using randomized adapters combined with unique molecular identifiers (UMI), library quantification, and sequencing, followed by detailed procedures for data processing and analysis. For complete details on the use and execution of this protocol, please refer to C. Gómez-Martín et al. (2023)1 and Van Eijndhoven et al. (2021).2.

HSV-1 miRNAs are post-transcriptionally edited in latently infected human ganglia

IMPORTANCE

Herpes simplex virus 1 is an important human pathogen that has been intensively studied for many decades. Nevertheless, the molecular mechanisms regulating its establishment, maintenance, and reactivation from latency are poorly understood. Here, we show that HSV-1-encoded miR-H2 is post-transcriptionally edited in latently infected human tissues. Hyperediting of viral miRNAs increases the targeting potential of these miRNAs and may play an important role in regulating latency. We show that the edited miR-H2 can target ICP4, an essential viral protein. Interestingly, we found no evidence of hyperediting of its homolog, miR-H2, which is expressed by the closely related virus HSV-2. The discovery of post-translational modifications of viral miRNA in the latency phase suggests that these processes may also be important for other non-coding viral RNA in the latency phase, including the intron LAT, which in turn may be crucial for understanding the biology of this virus.

Interferon-Alpha Decreases Cancer Stem Cell Properties and Modulates Exosomes in Malignant Melanoma

Malignant melanoma (MM) can spread to other organs and is resistant in part due to the presence of cancer stem cell subpopulations (CSCs). While a controversial high dose of interferon-alpha (IFN-α) has been used to treat non-metastatic high-risk melanoma, it comes with undesirable side effects. In this study, we evaluated the effect of low and high doses of IFN-α on CSCs by analyzing ALDH activity, side population and specific surface markers in established and patient-derived primary cell lines. We also assessed the clonogenicity, migration and tumor initiation capacities of IFN-α treated CSCs. Additionally, we investigated genomic modulations related to stemness properties using microRNA sequencing and microarrays. The effect of IFN-α on CSCs-derived exosomes was also analyzed using NanoSight and liquid chromatography (LC-HRMS)-based metabolomic analysis, among others. Our results showed that even low doses of IFN-α reduced CSC formation and stemness properties, and led to a significant decrease in the ability to form tumors in mice xenotransplants. IFN-α also modulated the expression of genes and microRNAs involved in several cancer processes and metabolomics of released exosomes. Our work suggests the utility of low doses of interferon, combined with the analysis of metabolic biomarkers, as a potential clinical approach against the aggressiveness of CSCs in melanoma.

Interferon-Alpha Decreases Cancer Stem Cell Properties and Modulates Exosomes in Malignant Melanoma

Malignant melanoma (MM) can spread to other organs and is resistant in part due to the presence of cancer stem cell subpopulations (CSCs). While a controversial high dose of interferon-alpha (IFN-α) has been used to treat non-metastatic high-risk melanoma, it comes with undesirable side effects. In this study, we evaluated the effect of low and high doses of IFN-α on CSCs by analyzing ALDH activity, side population and specific surface markers in established and patient-derived primary cell lines. We also assessed the clonogenicity, migration and tumor initiation capacities of IFN-α treated CSCs. Additionally, we investigated genomic modulations related to stemness properties using microRNA sequencing and microarrays. The effect of IFN-α on CSCs-derived exosomes was also analyzed using NanoSight and liquid chromatography (LC-HRMS)-based metabolomic analysis, among others. Our results showed that even low doses of IFN-α reduced CSC formation and stemness properties, and led to a significant decrease in the ability to form tumors in mice xenotransplants. IFN-α also modulated the expression of genes and microRNAs involved in several cancer processes and metabolomics of released exosomes. Our work suggests the utility of low doses of interferon, combined with the analysis of metabolic biomarkers, as a potential clinical approach against the aggressiveness of CSCs in melanoma.

NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods

RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.

Reassessment of miRNA variant (isomiRs) composition by small RNA sequencing

IsomiRs, sequence variants of mature microRNAs, are usually detected and quantified using high-throughput sequencing. Many examples of their biological relevance have been reported, but sequencing artifacts identified as artificial variants might bias biological inference and therefore need to be ideally avoided. We conducted a comprehensive evaluation of 10 different small RNA sequencing protocols, exploring both a theoretically isomiR-free pool of synthetic miRNAs and HEK293T cells. We calculated that, with the exception of two protocols, less than 5% of miRNA reads can be attributed to library preparation artifacts. Randomized-end adapter protocols showed superior accuracy, with 40% of true biological isomiRs. Nevertheless, we demonstrate concordance across protocols for selected miRNAs in non-templated uridyl additions. Notably, NTA-U calling and isomiR target prediction can be inaccurate when using protocols with poor single-nucleotide resolution. Our results highlight the relevance of protocol choice for biological isomiRs detection and annotation, which has key potential implications for biomedical applications.

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

sRNAtoolbox: Dockerized Analysis of Small RNA Sequencing Data in Model and Non-model Species

The current versions of the microRNA databases MiRgeneDB, miRBase, and PmiREN contain annotations for a total of 358 different species. Public repositories, however, host small RNA sequencing data for over 800 species. This discrepancy implies that microRNA research is also very active in species that neither have an available high-quality genome assembly nor annotations for microRNAs or other types of noncoding genes. These cases are particularly challenging to analyze because reference sequences need to be collected from different sources and processed and formatted appropriately so that the dedicated small RNA analysis tools can make use of them. In this protocol we describe how small RNA sequencing data can be easily analyzed by means of a dockerized version of the well-established sRNAtoolbox/sRNAbench small RNA tools. We outline the analysis of two publicly available datasets to demonstrate basic aspects like the preparation of the local database, expression profiling, or differential expression analysis as well as more advanced features such as quantification of exogenous RNA content and data analysis in non-model species.

Comprehensive, integrative genomic analysis of microRNA expression profiles in different tissues of two wheat cultivars with different traits

Wheat is one of the most important food sources on Earth. MicroRNAs (miRNA) play important roles in wheat productivity. To identify wheat miRNAs, we constructed and sequenced sRNA libraries from leaves and roots of two wheat cultivars (RAC875 and Kukri) with many different traits. Given that available miRNA wheat complement in the plant-specific database PmiREN ( https://pmiren.com ) does not include root tissues and root-associated miRNAs might thus be missing, we performed first the prediction of novel miRNAs using the sRNAbench tool. We found a total of 150 putatively novel miRNA genes with expression of both arms from 289 unique mature sequences and nearly 30% of all miRNA reads in roots corresponded to novel miRNAs. In contrast, this figure in leaves dropped to under 3%, confirming the undersampling of roots in the complement of known miRNAs. By using 120 publicly available wheat datasets, 598 Zea mays small RNA libraries, 64 plant species genomes, wheat degradome library, and functional enrichment analysis, a subset of novel miRNAs were confirmed as bona-fide miRNAs. Of the total 605 miRNAs identified in this study inclusive of 316 known miRNAs, 528 miRNAs were shared by both cultivars, 429 miRNAs were shared by both root tissues and 329 miRNAs were shared by both leaf tissues. In addition, 32 miRNAs were specific to Kukri while 45 miRNAs were specific to RAC875. These miRNAs had diverse functions, such as regulation of gene transcription, protein translation, energy metabolism, and cell cycle progression. Our data provide a genome-wide miRNA expression profile in these two wheat cultivars and help functional studies of wheat genomics.

Decoding Gene Expression Signatures Underlying Vegetative to Inflorescence Meristem Transition in the Common Bean

The tropical common bean (Phaseolus vulgaris L.) is an obligatory short-day plant that requires relaxation of the photoperiod to induce flowering. Similar to other crops, photoperiod-induced floral initiation depends on the differentiation and maintenance of meristems. In this study, the global changes in transcript expression profiles were analyzed in two meristematic tissues corresponding to the vegetative and inflorescence meristems of two genotypes with different sensitivities to photoperiods. A total of 3396 differentially expressed genes (DEGs) were identified, and 1271 and 1533 were found to be up-regulated and down-regulated, respectively, whereas 592 genes showed discordant expression patterns between both genotypes. Arabidopsis homologues of DEGs were identified, and most of them were not previously involved in Arabidopsis floral transition, suggesting an evolutionary divergence of the transcriptional regulatory networks of the flowering process of both species. However, some genes belonging to the photoperiod and flower development pathways with evolutionarily conserved transcriptional profiles have been found. In addition, the flower meristem identity genes APETALA1 and LEAFY, as well as CONSTANS-LIKE 5, were identified as markers to distinguish between the vegetative and reproductive stages. Our data also indicated that the down-regulation of the photoperiodic genes seems to be directly associated with promoting floral transition under inductive short-day lengths. These findings provide valuable insight into the molecular factors that underlie meristematic development and contribute to understanding the photoperiod adaptation in the common bean.

isomiRdb: microRNA expression at isoform resolution

A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients' samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.

Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients.

METHODS

EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC.

RESULTS

A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86.

CONCLUSIONS

This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.

Bioinformatic Analysis of Ixodes ricinus Long Non-Coding RNAs Predicts Their Binding Ability of Host miRNAs

Ixodes ricinus ticks are distributed across Europe and are a vector of tick-borne diseases. Although I. ricinus transcriptome studies have focused exclusively on protein coding genes, the last decade witnessed a strong increase in long non-coding RNA (lncRNA) research and characterization. Here, we report for the first time an exhaustive analysis of these non-coding molecules in I. ricinus based on 131 RNA-seq datasets from three different BioProjects. Using this data, we obtained a consensus set of lncRNAs and showed that lncRNA expression is stable among different studies. While the length distribution of lncRNAs from the individual data sets is biased toward short length values, implying the existence of technical artefacts, the consensus lncRNAs show a more homogeneous distribution emphasizing the importance to incorporate data from different sources to generate a solid reference set of lncRNAs. KEGG enrichment analysis of host miRNAs putatively targeting lncRNAs upregulated upon feeding showed that these miRNAs are involved in several relevant functions for the tick-host interaction. The possibility that at least some tick lncRNAs act as host miRNA sponges was further explored by identifying lncRNAs with many target regions for a given host miRNA or sets of host miRNAs that consistently target lncRNAs together. Overall, our findings suggest that lncRNAs that may act as sponges have diverse biological roles related to the tick–host interaction in different tissues.

Selective isolation of extracellular vesicles from minimally processed human plasma as a translational strategy for liquid biopsies

Background

Intercellular communication is mediated by extracellular vesicles (EVs), as they enclose selectively packaged biomolecules that can be horizontally transferred from donor to recipient cells. Because all cells constantly generate and recycle EVs, they provide accurate timed snapshots of individual pathophysiological status. Since blood plasma circulates through the whole body, it is often the biofluid of choice for biomarker detection in EVs. Blood collection is easy and minimally invasive, yet reproducible procedures to obtain pure EV samples from circulating biofluids are still lacking. Here, we addressed central aspects of EV immunoaffinity isolation from simple and complex matrices, such as plasma.

Methods

Cell-generated EV spike-in models were isolated and purified by size-exclusion chromatography, stained with cellular dyes and characterized by nano flow cytometry. Fluorescently-labelled spike-in EVs emerged as reliable, high-throughput and easily measurable readouts, which were employed to optimize our EV immunoprecipitation strategy and evaluate its performance. Plasma-derived EVs were captured and detected using this straightforward protocol, sequentially combining isolation and staining of specific surface markers, such as CD9 or CD41. Multiplexed digital transcript detection data was generated using the Nanostring nCounter platform and evaluated through a dedicated bioinformatics pipeline.

Results

Beads with covalently-conjugated antibodies on their surface outperformed streptavidin-conjugated beads, coated with biotinylated antibodies, in EV immunoprecipitation. Fluorescent EV spike recovery evidenced that target EV subpopulations can be efficiently retrieved from plasma, and that their enrichment is dependent not only on complex matrix composition, but also on the EV surface phenotype. Finally, mRNA profiling experiments proved that distinct EV subpopulations can be captured by directly targeting different surface markers. Furthermore, EVs isolated with anti-CD61 beads enclosed mRNA expression patterns that might be associated to early-stage lung cancer, in contrast with EVs captured through CD9, CD63 or CD81. The differential clinical value carried within each distinct EV subset highlights the advantages of selective isolation.

Conclusions

This EV isolation protocol facilitated the extraction of clinically useful information from plasma. Compatible with common downstream analytics, it is a readily implementable research tool, tailored to provide a truly translational solution in routine clinical workflows, fostering the inclusion of EVs in novel liquid biopsy settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-022-00404-1.

Transcriptomic analysis of the tick midgut and salivary gland responses upon repeated blood-feeding on a vertebrate host

Ticks are blood-feeding arthropods that use the components of their salivary glands to counter the host’s hemostatic, inflammatory, and immune responses. The tick midgut also plays a crucial role in hematophagy. It is responsible for managing blood meals (storage and digestion) and protecting against host immunity and pathogen infections. Previous transcriptomic studies revealed the complexity of tick sialomes (salivary gland transcriptomes) and mialomes (midgut transcriptomes) which encode for protease inhibitors, lipocalins (histamine-binding proteins), disintegrins, enzymes, and several other tick-specific proteins. Several studies have demonstrated that mammalian hosts acquire tick resistance against repeated tick bites. Consequently, there is an urgent need to uncover how tick sialomes and mialomes respond to resistant hosts, as they may serve to develop novel tick control strategies and applications. Here, we mimicked natural repeated tick bites in a laboratory setting and analyzed gene expression dynamics in the salivary glands and midguts of adult female ticks. Rabbits were subjected to a primary (feeding on a naive host) and a secondary infestation of the same host (we re-exposed the hosts but to other ticks). We used single salivary glands and midguts dissected from individual siblings adult pathogen-free female Ixodes ricinus to reduce genetic variability between individual ticks. The comprehensive analysis of 88 obtained RNA-seq data sets allows us to provide high-quality annotated sialomes and mialomes from individual ticks. Comparisons between fed/unfed, timepoints, and exposures yielded as many as 3000 putative differentially expressed genes (DEG). Interestingly, when classifying the exposure DEGs by means of a clustering approach we observed that the majority of these genes show increased expression at early feeding time-points in the mid-gut of re-exposed ticks. The existence of clearly defined groups of genes with highly similar responses to re-exposure suggests the existence of molecular swiches. In silico functional analysis shows that these early feeding reexposure response genes form a dense interaction network at protein level being related to virtually all aspects of gene expression regulation and glycosylation. The processed data is available through an easy-to-use database-associated webpage (https://arn.ugr.es/IxoriDB/) that can serve as a valuable resource for tick research.

Quantitative proteomics analysis reveals core and variable tick salivary proteins at the tick-vertebrate host interface

Few studies have examined tick proteomes, how they adapt to their environment, and their roles in the parasite-host interactions that drive tick infestation and pathogen transmission. Here we used a proteomics approach to screen for biologically and immunologically relevant proteins acting at the tick-host interface during tick feeding and, as proof of principle, measured host antibody responses to some of the discovered candidates. We used a label-free quantitative proteomic workflow to study salivary proteomes of (i) wild Ixodes ricinus ticks fed on different hosts; (ii) wild or laboratory ticks fed on the same host; and (iii) adult ticks co-fed with nymphs. Our results reveal high and stable expression of several protease inhibitors and other tick-specific proteins under different feeding conditions. Most pathways functionally enriched in sialoproteomes were related to proteolysis, endopeptidase, and amine-binding activities. The generated catalog of tick salivary proteins enabled the selection of six candidate secreted immunogenic peptides for rabbit immunizations, three of which induced strong and durable antigen-specific antibody responses in rabbits. Furthermore, rabbits exposed to ticks mounted immune responses against the candidate peptides/proteins, confirming their expression at the tick-vertebrate interface. Our approach provides insights into tick adaptation strategies to different feeding conditions and promising candidates for developing anti-tick vaccines or markers of exposure of vertebrate hosts to tick bites.

The limits of human microRNA annotation have been met

Over the last few years, the number of microRNAs in the human genome has become a controversially debated issue. Several publications reported thousands of putative novel microRNAs not included in the curated microRNA gene database MirGeneDB and the repository miRBase. Recently, by using sequencing of ∼300 human tissues and cell lines, the human RNA atlas, an expanded inventory of human RNA annotations, was published, reporting thousands of putative microRNAs. We, the developers of established microRNA prediction tools and hosts of MirGeneDB, raise concerns about the frequently applied prediction and functional validation strategies, briefly discussing the drawbacks of false positive detections. By means of quantifying well-established biogenesis-derived features, we show that the reported novel microRNAs essentially represent false-positives and argue that the human microRNA complement, at about 550 microRNA genes, is already near complete. Output of available tools must be curated as false predictions will misguide scientists looking for biomarkers or therapeutic targets.

sRNAbench and sRNAtoolbox 2022 update: accurate miRNA and sncRNA profiling for model and non-model organisms

The NCBI Sequence Read Archive currently hosts microRNA sequencing data for over 800 different species, evidencing the existence of a broad taxonomic distribution in the field of small RNA research. Simultaneously, the number of samples per miRNA-seq study continues to increase resulting in a vast amount of data that requires accurate, fast and user-friendly analysis methods. Since the previous release of sRNAtoolbox in 2019, 55 000 sRNAbench jobs have been submitted which has motivated many improvements in its usability and the scope of the underlying annotation database. With this update, users can upload an unlimited number of samples or import them from Google Drive, Dropbox or URLs. Micro- and small RNA profiling can now be carried out using high-confidence Metazoan and plant specific databases, MirGeneDB and PmiREN respectively, together with genome assemblies and libraries from 441 Ensembl species. The new results page includes straightforward sample annotation to allow downstream differential expression analysis with sRNAde. Unassigned reads can also be explored by means of a new tool that performs mapping to microbial references, which can reveal contamination events or biologically meaningful findings as we describe in the example. sRNAtoolbox is available at: https://arn.ugr.es/srnatoolbox/.

Digital multiplexed analysis of circular RNAs in FFPE and fresh non‐small cell lung cancer specimens

Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.

Functional characterization of the tomato HAIRPLUS gene reveals the implication of the epigenome in the control of glandular trichome formation

Trichomes are specialised epidermal cells developed in the aerial surface of almost every terrestrial plant. These structures form physical barriers, which combined with their capability of synthesis of complex molecules, prevent plagues from spreading and confer trichomes a key role in the defence against herbivores. In this work, the tomato gene HAIRPLUS (HAP) that controls glandular trichome density in tomato plants was characterised. HAP belongs to a group of proteins involved in histone tail modifications although some also bind methylated DNA. HAP loss of function promotes epigenomic modifications in the tomato genome reflected in numerous differentially methylated cytosines and causes transcriptomic changes in hap mutant plants. Taken together, these findings demonstrate that HAP links epigenome remodelling with multicellular glandular trichome development and reveal that HAP is a valuable genomic tool for pest resistance in tomato breeding.

MirGeneDB 2.1: toward a complete sampling of all major animal phyla

We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.

Extracellular vesicle miRNA predict FDG-PET status in patients with classical Hodgkin Lymphoma

Minimally-invasive tools to assess tumour presence and burden may improve clinical management. FDG-PET (metabolic) imaging is the current gold standard for interim response assessment in patients with classical Hodgkin Lymphoma (cHL), but this technique cannot be repeated frequently. Here we show that microRNAs (miRNA) associated with tumour-secreted extracellular vesicles (EVs) in the circulation of cHL patients may improve response assessment. Small RNA sequencing and qRT-PCR reveal that the relative abundance of cHL-expressed miRNAs, miR-127-3p, miR-155-5p, miR-21-5p, miR-24-3p and let-7a-5p is up to hundred-fold increased in plasma EVs of cHL patients pre-treatment when compared to complete metabolic responders (CMR). Notably, in partial responders (PR) or treatment-refractory cases (n = 10) the EV-miRNA levels remain elevated. In comparison, tumour specific copy number variations (CNV) were detected in cell-free DNA of 8 out of 10 newly diagnosed cHL patients but not in patients with PR. Combining EV-miR-127-3p and/or EV-let-7a-5p levels, with serum TARC (a validated protein cHL biomarker), increases the accuracy for predicting PET-status (n = 129) to an area under the curve of 0.93 (CI: 0.87-0.99), 93.5% sensitivity, 83.8/85.0% specificity and a negative predictive value of 96%. Thus the level of tumour-associated miRNAs in plasma EVs is predictive of metabolic tumour activity in cHL patients. Our findings suggest that plasma EV-miRNA are useful for detection of small residual lesions and may be applied as serial response prediction tool.

geno5mC: A Database to Explore the Association between Genetic Variation (SNPs) and CpG Methylation in the Human Genome

Genetic variation, gene expression and DNA methylation influence each other in a complex way. To study the impact of sequence variation and DNA methylation on gene expression, we generated geno⁵mC, a database that contains statistically significant SNP-CpG associations that are biologically classified either through co-localization with known regulatory regions (promoters and enhancers), or through known correlations with the expression levels of nearby genes. The SNP rs727563 can be used to illustrate the usefulness of this approach. This SNP has been associated with inflammatory bowel disease through GWAS, but it is not located near any gene related to this phenotype. However, geno⁵mC reveals that rs727563 is associated with the methylation state of several CpGs located in promoter regions of genes reported to be involved in inflammatory processes. This case exemplifies how geno⁵mC can be used to infer relevant and previously unknown interactions between described disease-associated SNPs and their functional targets.

Emerging roles of non-coding RNAs in vector-borne infections

Non-coding RNAs (ncRNAs) are nucleotide sequences that are known to assume regulatory roles previously thought to be reserved for proteins. Their functions include the regulation of protein activity and localization and the organization of subcellular structures. Sequencing studies have now identified thousands of ncRNAs encoded within the prokaryotic and eukaryotic genomes, leading to advances in several fields including parasitology. ncRNAs play major roles in several aspects of vector-host-pathogen interactions. Arthropod vector ncRNAs are secreted through extracellular vesicles into vertebrate hosts to counteract host defense systems and ensure arthropod survival. Conversely, hosts can use specific ncRNAs as one of several strategies to overcome arthropod vector invasion. In addition, pathogens transmitted through vector saliva into vertebrate hosts also possess ncRNAs thought to contribute to their pathogenicity. Recent studies have addressed ncRNAs in vectors or vertebrate hosts, with relatively few studies investigating the role of ncRNAs derived from pathogens and their involvement in establishing infections, especially in the context of vector-borne diseases. This Review summarizes recent data focusing on pathogen-derived ncRNAs and their role in modulating the cellular responses that favor pathogen survival in the vertebrate host and the arthropod vector, as well as host ncRNAs that interact with vector-borne pathogens.

mirnaQC: a webserver for comparative quality control of miRNA-seq data

Although miRNA-seq is extensively used in many different fields, its quality control is frequently restricted to a PhredScore-based filter. Other important quality related aspects like microRNA yield, the fraction of putative degradation products (such as rRNA fragments) or the percentage of adapter-dimers are hard to assess using absolute thresholds. Here we present mirnaQC, a webserver that relies on 34 quality parameters to assist in miRNA-seq quality control. To improve their interpretability, quality attributes are ranked using a reference distribution obtained from over 36 000 publicly available miRNA-seq datasets. Accepted input formats include FASTQ and SRA accessions. The results page contains several sections that deal with putative technical artefacts related to library preparation, sequencing, contamination or yield. Different visualisations, including PCA and heatmaps, are available to help users identify underlying issues. Finally, we show the usefulness of this approach by analysing two publicly available datasets and discussing the different quality issues that can be detected using mirnaQC.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

MOTIVATION

MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods.

RESULTS

To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification.

AVAILABILITY AND IMPLEMENTATION

https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

sRNAbench and sRNAtoolbox 2019: intuitive fast small RNA profiling and differential expression

Since the original publication of sRNAtoolbox in 2015, small RNA research experienced notable advances in different directions. New protocols for small RNA sequencing have become available to address important issues such as adapter ligation bias, PCR amplification artefacts or to include internal controls such as spike-in sequences. New microRNA reference databases were developed with different foci, either prioritizing accuracy (low number of false positives) or completeness (low number of false negatives). Additionally, other small RNA molecules as well as microRNA sequence and length variants (isomiRs) have continued to gain importance. Finally, the number of microRNA sequencing studies deposited in GEO nearly triplicated from 2014 (280) to 2018 (764). These developments imply that fast and easy-to-use tools for expression profiling and subsequent downstream analysis of miRNA-seq data are essential to many researchers. Key features in this sRNAtoolbox release include addition of all major RNA library preparation protocols to sRNAbench and improvements in sRNAde, a tool that summarizes several aspects of small RNA sequencing studies including the detection of consensus differential expression. A special emphasis was put on the user-friendliness of the tools, for instance sRNAbench now supports parallel launching of several jobs to improve reproducibility and user time efficiency.

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/.

liqDB: a small-RNAseq knowledge discovery database for liquid biopsy studies

MiRNAs are important regulators of gene expression and are frequently deregulated under pathologic conditions. They are highly stable in bodily fluids which makes them feasible candidates to become minimally invasive biomarkers. In fact, several studies already proposed circulating miRNA-based biomarkers for different types of neoplastic, cardiovascular and degenerative diseases. However, many of these studies rely on small RNA sequencing experiments that are based on different RNA extraction and processing protocols, rendering results incomparable. We generated liqDB, a database for liquid biopsy small RNA sequencing profiles that provides users with meaningful information to guide their small RNA liquid biopsy research and to overcome technical and conceptual problems. By means of a user-friendly web interface, miRNA expression profiles from 1607 manually annotated samples can be queried and explored at different levels. Result pages include downloadable expression matrices, differential expression analysis, most stably expressed miRNAs, cluster analysis and relevant visualizations by means of boxplots and heatmaps. We anticipate that liqDB will be a useful tool in liquid biopsy research as it provides a consistently annotated large compilation of experiments together with tools for reproducible analysis, comparison and hypothesis generation. LiqDB is available at http://bioinfo5.ugr.es/liqdb.

Transcriptional Dynamics and Candidate Genes Involved in Pod Maturation of Common Bean (Phaseolus vulgaris L.)

Pod maturation of common bean relies upon complex gene expression changes, which in turn are crucial for seed formation and dispersal. Hence, dissecting the transcriptional regulation of pod maturation would be of great significance for breeding programs. In this study, a comprehensive characterization of expression changes has been performed in two common bean cultivars (ancient and modern) by analyzing the transcriptomes of five developmental pod stages, from fruit setting to maturation. RNA-seq analysis allowed for the identification of key genes shared by both accessions, which in turn were homologous to known Arabidopsis maturation genes and furthermore showed a similar expression pattern along the maturation process. Gene- expression changes suggested a role in promoting an accelerated breakdown of photosynthetic and ribosomal machinery associated with chlorophyll degradation and early activation of alpha-linolenic acid metabolism. A further study of transcription factors and their DNA binding sites revealed three candidate genes whose functions may play a dominant role in regulating pod maturation. Altogether, this research identifies the first maturation gene set reported in common bean so far and contributes to a better understanding of the dynamic mechanisms of pod maturation, providing potentially useful information for genomic-assisted breeding of common bean yield and pod quality attributes.

GENE-60. THE EPITRANSCRIPTOMIC CODE IN LGG: METABOLICALLY REPROGRAMMED IDH-MUTANT GLIOMAS ALTER tRNA MODIFICATION LANDSCAPE

BACKGROUND

Diffuse lower grade gliomas (LGGs) are generally slow growing primary central nervous system tumors that occur in early adult life. The prevalence of isocitrate dehydrogenase (IDH) mutations is high in LGG, and induces excess production of the oncometabolite 2-hydroxyglutarate (2-HG). These gain-of-function mutations play a key role in promoting metabolic reprogramming of the cancer cell that affects activity of α-KG dependent demethylases. Inhibition of DNA demethylase activity leads to glioma with a CpG island methylator phenotype (G-CIMP). Whether the activity of RNA demethylases and methylation status of tRNAs in LGG are modulated by changes in IDH-status is unknown. AIM: To investigate whether IDH mutations play a role in reprogramming of tRNA modifications in adult glioma.

MATERIALS AND METHODS

We combined small RNAseq and LC-MS/MS analysis to identify distinct tRNA processing patterns and methylation signatures in LGG tissues. To address important experimental bottlenecks that limit RNAseq-based detection of tRNA and possibly other modified small noncoding RNAs, we employed a tailored small RNAseq method with validation of specific methylation sites by mass-spectrometry.

RESULTS

Our customized small RNAseq approach yielded >100 fold increase in sequencing reads per tRNA type, thereby dramatically improving tRNA detection when compared to currently used small RNAseq approaches. Moreover, LC-MS/MS analysis revealed a higher abundance of modified nucleosides in tRNA from IDH-mutant LGG compared to IDH-wildtype LGG. Analysis of tRNA from IDH-mutant and IDH-wildtype LGG using the combination of our tailored small RNAseq and LC-MS/MS methodology demonstrated strong differential tRNA expression, tRFs processing and tRNA methylation.

CONCLUSION

We described an approach that makes use of tailored small RNA sequencing combined with mass-spectrometry that enables insights into cancer driven alterations in tRNA methylation patterns and differential tRNA processing signatures. Our data implies that tumor metabolic reprogramming deregulates tRNA methylation, contributing to an altered epitranscriptomic code in IDH-mutant LGG.

Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation

The promoter region of around 70% of all genes in the human genome is overlapped by a CpG island (CGI). CGIs have known functions in the transcription initiation and outstanding compositional features like high G+C content and CpG ratios when compared to the bulk DNA. We have shown before that CGIs manifest as clusters of CpGs in mammalian genomes and can therefore be detected using clustering methods. These techniques have several advantages over sliding window approaches which apply compositional properties as thresholds. In this protocol we show how to determine local (CpG islands) and global (distance distribution) clustering properties of CG dinucleotides and how to generalize this analysis to any k-mer or combinations of it. In addition, we illustrate how to easily cross the output of a CpG island prediction algorithm with our methylation database to detect differentially methylated CGIs. The analysis is given in a step-by-step protocol and all necessary programs are implemented into a virtual machine or, alternatively, the software can be downloaded and easily installed.

Putting patients at the center of kidney care transitions: PREPARE NOW, a cluster randomized controlled trial

Care for patients transitioning from chronic kidney disease to kidney failure often falls short of meeting patients' needs. The PREPARE NOW study is a cluster randomized controlled trial studying the effectiveness of a pragmatic health system intervention, 'Patient Centered Kidney Transition Care,' a multi-component health system intervention designed to improve patients' preparation for kidney failure treatment. Patient-Centered Kidney Transition Care provides a suite of new electronic health information tools (including a disease registry and risk prediction tools) to help providers recognize patients in need of Kidney Transitions Care and focus their attention on patients' values and treatment preferences. Patient-Centered Kidney Transition Care also adds a 'Kidney Transitions Specialist' to the nephrology health care team to facilitate patients' self-management empowerment, shared-decision making, psychosocial support, care navigation, and health care team communication. The PREPARE NOW study is conducted among eight [8] outpatient nephrology clinics at Geisinger, a large integrated health system in rural Pennsylvania. Four randomly selected nephrology clinics employ the Patient Centered Kidney Transitions Care intervention while four clinics employ usual nephrology care. To assess intervention effectiveness, patient reported, biomedical, and health system outcomes are collected annually over a period of 36 months via telephone questionnaires and electronic health records. The PREPARE NOW Study may provide needed evidence on the effectiveness of patient-centered health system interventions to improve nephrology patients' experiences, capabilities, and clinical outcomes, and it will guide the implementation of similar interventions elsewhere.

TRIAL REGISTRATION

NCT02722382.

Identification and characterisation of a previously unknown drought tolerance-associated microRNA in barley

Drought is the most serious abiotic stress, and causes crop losses on a worldwide scale. The present study identified a previously unknown microRNA (designated as hvu-miRX) of 21 nucleotides (nt) in length in barley. Its precursor (designated pre-miRX) and primary transcript (designated pri-miRX) were also identified, with lengths of 73 and 559 nt, respectively. The identified upstream sequence of pri-miRX contained both the TATA box and the CAAT box, which are both required for initiation of transcription. Transient promoter activation assays showed that the core promoter region of pri-miRX ranged 500 nt from the transcription start site. In transgenic barley overexpression of the wheat DREB3 transcription factor (TaDREB3) caused hvu-miRX to be highly expressed as compared with the same miRNA in non-transgenic barley. However, the high expression was not directly associated with TaDREB3. Genomic analysis revealed that the hvu-miRX gene was a single copy located on the short arm of chromosome 2 and appeared to be only conserved in Triticeae, but not in other plant species. Notably, transgenic barley that overexpressed hvu-miRX showed drought tolerance. Degradome library analysis and other tests showed that hvu-miRX targeted various genes including transcription factors via the cleavage mode. Our data provides an excellent opportunity to develop drought stress tolerant cereals using hvu-miRX.

sRNAtoolboxVM: Small RNA Analysis in a Virtual Machine

High-throughput sequencing (HTS) data for small RNAs (noncoding RNA molecules that are 20-250 nucleotides in length) can now be routinely generated by minimally equipped wet laboratories; however, the bottleneck in HTS-based research has shifted now to the analysis of such huge amount of data. One of the reasons is that many analysis types require a Linux environment but computers, system administrators, and bioinformaticians suppose additional costs that often cannot be afforded by small to mid-sized groups or laboratories. Web servers are an alternative that can be used if the data is not subjected to privacy issues (what very often is an important issue with medical data). However, in any case they are less flexible than stand-alone programs limiting the number of workflows and analysis types that can be carried out.We show in this protocol how virtual machines can be used to overcome those problems and limitations. sRNAtoolboxVM is a virtual machine that can be executed on all common operating systems through virtualization programs like VirtualBox or VMware, providing the user with a high number of preinstalled programs like sRNAbench for small RNA analysis without the need to maintain additional servers and/or operating systems.

Identification of tomato miRNAs responsive to root colonization by endophytic Pochonia chlamydosporia

The molecular mechanisms active during the endophytic phase of the fungus Pochonia chlamydosporia are still poorly understood. In particular, few data are available on the links between the endophyte and the root response, as modulated by noncoding small RNAs. In this study, we describe the microRNAs (miRNAs) that are differentially expressed (DE) in the roots of tomato, colonized by P. chlamydosporia. A genome-wide NGS expression profiling of small RNAs in roots, either colonized or not by the fungus, showed 26 miRNAs upregulated in inoculated roots. Their predicted target genes are involved in the plant information processing system, which recognizes, percepts, and transmits signals, with higher representations in processes such as apoptosis and plant defense regulation. RNAseq data showed that predicted miRNA target genes were downregulated in tomato roots after 4, 7, 10, and 21 days post P. chlamydosporia inoculation. The differential expression of four miRNAs was further validated using qPCR analysis. The P. chlamydosporia endophytic lifestyle in tomato roots included an intricate network of miRNAs and targets. Data provide a first platform of DE tomato miRNAs after P. chlamydosporia colonization. They indicated that several miRNAs are involved in the host response to the fungus, playing important roles for its recognition as a symbiotic microorganism, allowing endophytism by modulating the host defense reaction. Data also indicated that endophytism affects tRNA fragmentation. This is the first study on miRNAs induced by P. chlamydosporia endophytism and related development regulation effects in Solanum lycopersicum.

On the presence and immunoregulatory functions of extracellular microRNAs in the trematode Fasciola hepatica

Liver flukes represent a paraphyletic group of endoparasitic flatworms that significantly affect man either indirectly due to economic damage on livestock or directly as pathogens. A range of studies have focussed on how these macroscopic organisms can evade the immune system and live inside a hostile environment such as the mammalian liver and bile ducts. Recently, microRNAs, a class of short noncoding gene regulators, have been proposed as likely candidates to play roles in this scenario. MicroRNAs (miRNAs) are key players in development and pathogenicity and are highly conserved between metazoans: identical miRNAs can be found in flatworms and mammalians. Interestingly, miRNAs are enriched in extracellular vesicles (EVs) which are secreted by most cells. EVs constitute an important mode of parasite/host interaction, and recent data illustrate that miRNAs play a vital part. We have demonstrated the presence of miRNAs in the EVs of the trematode species Dicrocoelium dendriticum and Fasciola hepatica (Fhe) and identified potential immune-regulatory miRNAs with targets in the host. After our initial identification of miRNAs expressed by F. hepatica, an assembled genome and additional miRNA data became available. This has enabled us to update the known complement of miRNAs in EVs and speculate on potential immune-regulatory functions that we review here.

In silico target network analysis of de novo-discovered, tick saliva-specific microRNAs reveals important combinatorial effects in their interference with vertebrate host physiology

The hard tick Ixodes ricinus is an important disease vector whose salivary secretions mediate blood-feeding success on vertebrate hosts, including humans. Here we describe the expression profiles and downstream analysis of de novo-discovered microRNAs (miRNAs) expressed in I. ricinus salivary glands and saliva. Eleven tick-derived libraries were sequenced to produce 67,375,557 Illumina reads. De novo prediction yielded 67 bona fide miRNAs out of which 35 are currently not present in miRBase. We report for the first time the presence of microRNAs in tick saliva, obtaining furthermore molecular indicators that those might be of exosomal origin. Ten out of these microRNAs are at least 100 times more represented in saliva. For the four most expressed microRNAs from this subset, we analyzed their combinatorial effects upon their host transcriptome using a novel in silico target network approach. We show that only the inclusion of combinatorial effects reveals the functions in important pathways related to inflammation and pain sensing. A control set of highly abundant microRNAs in both saliva and salivary glands indicates no significant pathways and a far lower number of shared target genes. Therefore, the analysis of miRNAs from pure tick saliva strongly supports the hypothesis that tick saliva miRNAs can modulate vertebrate host homeostasis and represents the first direct evidence of tick miRNA-mediated regulation of vertebrate host gene expression at the tick-host interface. As such, the herein described miRNAs may support future drug discovery and development projects that will also experimentally question their predicted molecular targets in the vertebrate host.

Thiourea priming enhances salt tolerance through co-ordinated regulation of microRNAs and hormones in Brassica juncea

Activation of stress tolerance mechanisms demands transcriptional reprogramming. Salt stress, a major threat to plant growth, enhances ROS production and affects transcription through modulation of miRNAs and hormones. The present study delineates salt stress ameliorating action of thiourea (TU, a ROS scavenger) in Brassica juncea and provides mechanistic link between redox, microRNA and hormones. The ameliorative potential of TU towards NaCl stress was related with its ability to decrease ROS accumulation in roots and increase Na⁺ accumulation in shoots. Small RNA sequencing revealed enrichment of down-regulated miRNAs in NaCl + TU treated roots, indicating transcriptional activation. Ranking analysis identified three key genes including BRX4, CBL10 and PHO1, showing inverse relationship with corresponding miRNA expression, which were responsible for TU mediated stress mitigation. Additionally, ABA level was consistently higher till 24 h in NaCl, while NaCl + TU treated roots showed only transient increase at 4 h suggesting an effective stress management. Jasmonate and auxin levels were also increased, which prioritized defence and facilitated root growth, respectively. Thus, the study highlights redox as one of the "core" components regulating miRNA and hormone levels, and also strengthens the use of TU as a redox priming agent for imparting crop resilience to salt stress.

NGSmethDB 2017: enhanced methylomes and differential methylation

The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to exploit the advantages of the new genome assembly models. The samples were all profiled under constant parameter settings, thus enabling comparative downstream analyses. Besides a significant increase in the number of samples, NGSmethDB now includes two additional data-types, which are a valuable resource for the discovery of methylation epigenetic biomarkers: (i) differentially methylated single-cytosines; and (ii) methylation segments (i.e. genome regions of homogeneous methylation). The NGSmethDB back-end is now based on MongoDB, a NoSQL hierarchical database using JSON-formatted documents and dynamic schemas, thus accelerating sample comparative analyses. Besides conventional database dumps, track hubs were implemented, which improved database access, visualization in genome browsers and comparative analyses to third-part annotations. In addition, the database can be also accessed through a RESTful API. Lastly, a Python client and a multiplatform virtual machine allow for program-driven access from user desktop. This way, private methylation data can be compared to NGSmethDB without the need to upload them to public servers. Database website: http://bioinfo2.ugr.es/NGSmethDB.

Generation of different sizes and classes of small RNAs in barley is locus, chromosome and/or cultivar-dependent

Background

Various small RNA (sRNA) sizes and varieties have been identified, but their relationship as well as relationship with their origins and allocations have not been well understood or investigated.

Results

By comparing sRNAs generated from two barley cultivars, Golden Promise (GP) and Pallas, we identified that the generation of different sizes and types of sRNAs in barley was locus-, chromosome- and/or cultivar-dependent. 20-nt sRNAs mainly comprising miRNAs and chloroplast-derived sRNAs were significantly over-expressed in Pallas vs. GP on chromosomes 3H and 6H. MiRNAs-enriched 21-nt sRNAs were significantly over-expressed in Pallas vs. GP only on chromosome 4H. On chromosome 5H this size of sRNAs was significantly under-expressed in Pallas, so were 22-nt sRNAs mainly comprising miRNAs and repeat-derived sRNAs. 24-nt sRNAs mostly derived from repeats were evenly distributed in all chromosomes and expressed similarly between GP and Pallas. Unlike other sizes of sRNAs, 24-nt sRNAs were little conserved in other plant species. Abundant sRNAs were mostly generated from 3’ terminal regions of chromosome 1H and 5’ terminal regions of chromosome 5H. Over-expressed miRNAs in GP vs. Pallas primarily function in stress responses and iron-binding.

Conclusions

Our study indicates that 23−24-nt sRNAs may be linked to repressive chromatin modifications and function in genome stability while 20−21-nt sRNAs may be important for the cultivar specificity. This study provides a novel insight into the mechanism of sRNA expression and function in barley.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3023-5) contains supplementary material, which is available to authorized users.

sRNAtoolbox: an integrated collection of small RNA research tools

Small RNA research is a rapidly growing field. Apart from microRNAs, which are important regulators of gene expression, other types of functional small RNA molecules have been reported in animals and plants. MicroRNAs are important in host-microbe interactions and parasite microRNAs might modulate the innate immunity of the host. Furthermore, small RNAs can be detected in bodily fluids making them attractive non-invasive biomarker candidates. Given the general broad interest in small RNAs, and in particular microRNAs, a large number of bioinformatics aided analysis types are needed by the scientific community. To facilitate integrated sRNA research, we developed sRNAtoolbox, a set of independent but interconnected tools for expression profiling from high-throughput sequencing data, consensus differential expression, target gene prediction, visual exploration in a genome context as a function of read length, gene list analysis and blast search of unmapped reads. All tools can be used independently or for the exploration and downstream analysis of sRNAbench results. Workflows like the prediction of consensus target genes of parasite microRNAs in the host followed by the detection of enriched pathways can be easily established. The web-interface interconnecting all these tools is available at http://bioinfo5.ugr.es/srnatoolbox

Integrated microRNA, mRNA, and protein expression profiling reveals microRNA regulatory networks in rat kidney treated with a carcinogenic dose of aristolochic acid

Background

Aristolochic Acid (AA), a natural component of Aristolochia plants that is found in a variety of herbal remedies and health supplements, is classified as a Group 1 carcinogen by the International Agency for Research on Cancer. Given that microRNAs (miRNAs) are involved in cancer initiation and progression and their role remains unknown in AA-induced carcinogenesis, we examined genome-wide AA-induced dysregulation of miRNAs as well as the regulation of miRNAs on their target gene expression in rat kidney.

Results

We treated rats with 10 mg/kg AA and vehicle control for 12 weeks and eight kidney samples (4 for the treatment and 4 for the control) were used for examining miRNA and mRNA expression by deep sequencing, and protein expression by proteomics. AA treatment resulted in significant differential expression of miRNAs, mRNAs and proteins as measured by both principal component analysis (PCA) and hierarchical clustering analysis (HCA). Specially, 63 miRNAs (adjusted p value < 0.05 and fold change > 1.5), 6,794 mRNAs (adjusted p value < 0.05 and fold change > 2.0), and 800 proteins (fold change > 2.0) were significantly altered by AA treatment. The expression of 6 selected miRNAs was validated by quantitative real-time PCR analysis. Ingenuity Pathways Analysis (IPA) showed that cancer is the top network and disease associated with those dysregulated miRNAs. To further investigate the influence of miRNAs on kidney mRNA and protein expression, we combined proteomic and transcriptomic data in conjunction with miRNA target selection as confirmed and reported in miRTarBase. In addition to translational repression and transcriptional destabilization, we also found that miRNAs and their target genes were expressed in the same direction at levels of transcription (169) or translation (227). Furthermore, we identified that up-regulation of 13 oncogenic miRNAs was associated with translational activation of 45 out of 54 cancer-related targets.

Conclusions

Our findings suggest that dysregulated miRNA expression plays an important role in AA-induced carcinogenesis in rat kidney, and that the integrated approach of multiple profiling provides a new insight into a post-transcriptional regulation of miRNAs on their target repression and activation in a genome-wide scale.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1516-2) contains supplementary material, which is available to authorized users.

Differential expression of microRNAs and other small RNAs in barley between water and drought conditions

Drought is a major constraint to crop production, and microRNAs (miRNAs) play an important role in plant drought tolerance. Analysis of miRNAs and other classes of small RNAs (sRNAs) in barley grown under water and drought conditions reveals that drought selectively regulates expression of miRNAs and other classes of sRNAs. Low-expressed miRNAs and all repeat-associated siRNAs (rasiRNAs) tended towards down-regulation, while tRNA-derived sRNAs (tsRNAs) had the tendency to be up-regulated, under drought. Antisense sRNAs (putative siRNAs) did not have such a tendency under drought. In drought-tolerant transgenic barley overexpressing DREB transcription factor, most of the low-expressed miRNAs were also down-regulated. In contrast, tsRNAs, rasiRNAs and other classes of sRNAs were not consistently expressed between the drought-treated and transgenic plants. The differential expression of miRNAs and siRNAs was further confirmed by Northern hybridization and quantitative real-time PCR (qRT-PCR). Targets of the drought-regulated miRNAs and siRNAs were predicted, identified by degradome libraries and confirmed by qRT-PCR. Their functions are diverse, but most are involved in transcriptional regulation. Our data provide insight into the expression profiles of miRNAs and other sRNAs, and their relationship under drought, thereby helping understand how miRNAs and sRNAs respond to drought stress in cereal crops.