Full-length tRNAs lacking a functional CCA tail are selectively sorted into the lumen of extracellular vesicles.

Small extracellular vesicles (sEVs) are heterogenous lipid membrane particles typically less than 200 nm in size and secreted by most cell types either constitutively or upon activation signals. sEVs isolated from biofluids contain RNAs, including small non-coding RNAs (ncRNAs), that can be either encapsulated within the EV lumen or bound to the EV surface. EV-associated microRNAs (miRNAs) are, despite a relatively low abundance, extensively investigated for their selective incorporation and their role in cell-cell communication. In contrast, the sorting of highly-structured ncRNA species is understudied, mainly due to technical limitations of traditional small RNA sequencing protocols. Here, we adapted ALL-tRNAseq to profile the relative abundance of highly structured and potentially methylated small ncRNA species, including transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and Y RNAs in bulk EV preparations. We determined that full-length tRNAs, typically 75 to 90 nucleotides in length, were the dominant small ncRNA species (>60% of all reads in the 18-120 nucleotides size-range) in all cell culture-derived EVs, as well as in human plasma-derived EV samples, vastly outnumbering 21 nucleotides-long miRNAs. Nearly all EV-associated tRNAs were protected from external RNAse treatment, indicating a location within the EV lumen. Strikingly, the vast majority of luminal-sorted, full-length, nucleobase modification-containing EV-tRNA sequences, harbored a dysfunctional 3' CCA tail, 1 to 3 nucleotides truncated, rendering them incompetent for amino acid loading. In contrast, in non-EV associated extracellular particle fractions (NVEPs), tRNAs appeared almost exclusively fragmented or 'nicked' into tRNA-derived small RNAs (tsRNAs) with lengths between 18 to 35 nucleotides. We propose that in mammalian cells, tRNAs that lack a functional 3' CCA tail are selectively sorted into EVs and shuttled out of the producing cell, offering a new perspective into the physiological role of secreted EVs and luminal cargo-selection.

Unlocking the effective alliance of ß-lapachone and hydroxytyrosol against triple-negative breast cancer cells.

Triple-negative breast cancer (TNBC) is characterised by its aggressiveness and resistance to chemotherapy, demanding the development of effective strategies against its unique characteristics. Derived from lapacho tree bark, ß-lapachone (ß-LP) selectively targets cancer cells with elevated levels of the detoxifying enzyme NQO1. Hydroxytyrosol (HT) is a phenolic compound derived from olive trees with important anticancer properties that include the inhibition of cancer stem cells (CSCs) and metastatic features in TNBC, as well as relevant antioxidant activities by mechanisms such as the induction of NQO1. We aimed to study whether these compounds could have synergistic anticancer activity in TNBC cells and the possible role of NQO1. For this pourpose, we assessed the impact of ß-LP (0.5 or 1.5 µM) and HT (50 and 100 µM) on five TNBC cell lines. We demonstrated that the combination of ß-LP and HT exhibits anti-proliferative, pro-apoptotic, and cell cycle arrest effects in several TNBC cells, including docetaxel-resistant TNBC cells. Additionally, it effectively inhibits the self-renewal and clonogenicity of CSCs, modifying their aggressive phenotype. However, the notable impact of the ß-LP-HT combination does not appear to be solely associated with the levels of the NQO1 protein and ROS. RNA-Seq analysis revealed that the combination's anticancer activity is linked to a strong induction of endoplasmic reticulum stress and apoptosis through the unfolded protein response. In conclusion, in this study, we demonstrated how the combination of ß-LP and HT could offer an affordable, safe, and effective approach against TNBC.

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.

Ageing-associated small RNA cargo of extracellular vesicles.

Previous work on murine models and humans demonstrated global as well as tissue-specific molecular ageing trajectories of RNAs. Extracellular vesicles (EVs) are membrane vesicles mediating the horizontal transfer of genetic information between different tissues. We sequenced small regulatory RNAs (sncRNAs) in two mouse plasma fractions at five time points across the lifespan from 2-18 months: (1) sncRNAs that are free-circulating (fc-RNA) and (2) sncRNAs bound outside or inside EVs (EV-RNA). Different sncRNA classes exhibit unique ageing patterns that vary between the fcRNA and EV-RNA fractions. While tRNAs showed the highest correlation with ageing in both fractions, rRNAs exhibited inverse correlation trajectories between the EV- and fc-fractions. For miRNAs, the EV-RNA fraction was exceptionally strongly associated with ageing, especially the miR-29 family in adipose tissues. Sequencing of sncRNAs and coding genes in fat tissue of an independent cohort of aged mice up to 27 months highlighted the pivotal role of miR-29a-3p and miR-29b-3p in ageing-related gene regulation that we validated in a third cohort by RT-qPCR.

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.

miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations.

MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in regulating diverse biological processes. Extracting functional insights from a list of miRNAs is challenging, as each miRNA can potentially interact with hundreds of genes. To address this challenge, we developed miEAA, a flexible and comprehensive miRNA enrichment analysis tool based on direct and indirect miRNA annotation. The latest release of miEAA includes a data warehouse of 19 miRNA repositories, covering 10 different organisms and 139 399 functional categories. We have added information on the cellular context of miRNAs, isomiRs, and high-confidence miRNAs to improve the accuracy of the results. We have also improved the representation of aggregated results, including interactive Upset plots to aid users in understanding the interaction among enriched terms or categories. Finally, we demonstrate the functionality of miEAA in the context of ageing and highlight the importance of carefully considering the miRNA input list. MiEAA is free to use and publicly available at https://www.ccb.uni-saarland.de/mieaa/.

Genome-Wide Analysis of microRNA Expression Profile in Roots and Leaves of Three Wheat Cultivars under Water and Drought Conditions.

Wheat is one of the most important food sources on Earth. MicroRNAs (miRNAs) play important roles in wheat productivity. To identify wheat miRNAs as well as their expression profiles under drought condition, we constructed and sequenced small RNA (sRNA) libraries from the leaves and roots of three wheat cultivars (Kukri, RAC875 and Excalibur) under water and drought conditions. A total of 636 known miRNAs and 294 novel miRNAs were identified, of which 34 miRNAs were tissue- or cultivar-specific. Among these, 314 were significantly regulated under drought conditions. miRNAs that were drought-regulated in all cultivars displayed notably higher expression than those that responded in a cultivar-specific manner. Cultivar-specific drought response miRNAs were mainly detected in roots and showed significantly different drought regulations between cultivars. By using wheat degradome library, 6619 target genes were identified. Many target genes were strongly enriched for protein domains, such as MEKHLA, that play roles in drought response. Targeting analysis showed that drought-downregulated miRNAs targeted more genes than drought-upregulated miRNAs. Furthermore, such genes had more important functions. Additionally, the genes targeted by drought-downregulated miRNAs had multiple interactions with each other, while the genes targeted by drought-upregulated miRNAs had no interactions. Our data provide valuable information on wheat miRNA expression profiles and potential functions in different tissues, cultivars and drought conditions.

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.

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.

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.

MicroRNA-4732-3p Is Dysregulated in Breast Cancer Patients with Cardiotoxicity, and Its Therapeutic Delivery Protects the Heart from Doxorubicin-Induced Oxidative Stress in Rats.

Anthracycline-induced cardiotoxicity is the most severe collateral effect of chemotherapy originated by an excess of oxidative stress in cardiomyocytes that leads to cardiac dysfunction. We assessed clinical data from patients with breast cancer receiving anthracyclines and searched for discriminating microRNAs between patients that developed cardiotoxicity (cases) and those that did not (controls), using RNA sequencing and regression analysis. Serum levels of 25 microRNAs were differentially expressed in cases versus controls within the first year after anthracycline treatment, as assessed by three different regression models (elastic net, Robinson and Smyth exact negative binomial test and random forest). MiR-4732-3p was the only microRNA identified in all regression models and was downregulated in patients that experienced cardiotoxicity. MiR-4732-3p was also present in neonatal rat cardiomyocytes and cardiac fibroblasts and was modulated by anthracycline treatment. A miR-4732-3p mimic was cardioprotective in cardiac and fibroblast cultures, following doxorubicin challenge, in terms of cell viability and ROS levels. Notably, administration of the miR-4732-3p mimic in doxorubicin-treated rats preserved cardiac function, normalized weight loss, induced angiogenesis, and decreased apoptosis, interstitial fibrosis and cardiac myofibroblasts. At the molecular level, miR-4732-3p regulated genes of TGFß and Hippo signaling pathways. Overall, the results indicate that miR-4732-3p is a novel biomarker of cardiotoxicity that has therapeutic potential against anthracycline-induced heart damage.

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 cofed 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 catalogue 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 antitick vaccines or markers of exposure of vertebrate hosts to tick bites.

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/.

Functional Enrichment Analysis of Regulatory Elements.

Statistical methods for enrichment analysis are important tools to extract biological information from omics experiments. Although these methods have been widely used for the analysis of gene and protein lists, the development of high-throughput technologies for regulatory elements demands dedicated statistical and bioinformatics tools. Here, we present a set of enrichment analysis methods for regulatory elements, including CpG sites, miRNAs, and transcription factors. Statistical significance is determined via a power weighting function for target genes and tested by the Wallenius noncentral hypergeometric distribution model to avoid selection bias. These new methodologies have been applied to the analysis of a set of miRNAs associated with arrhythmia, showing the potential of this tool to extract biological information from a list of regulatory elements. These new methods are available in GeneCodis 4, a web tool able to perform singular and modular enrichment analysis that allows the integration of heterogeneous information.

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.

miRTargetLink 2.0-interactive miRNA target gene and target pathway networks.

Which genes, gene sets or pathways are regulated by certain miRNAs? Which miRNAs regulate a particular target gene or target pathway in a certain physiological context? Answering such common research questions can be time consuming and labor intensive. Especially for researchers without computational experience, the integration of different data sources, selection of the right parameters and concise visualization can be demanding. A comprehensive analysis should be central to present adequate answers to complex biological questions. With miRTargetLink 2.0, we develop an all-in-one solution for human, mouse and rat miRNA networks. Users input in the unidirectional search mode either a single gene, gene set or gene pathway, alternatively a single miRNA, a set of miRNAs or an miRNA pathway. Moreover, genes and miRNAs can jointly be provided to the tool in the bidirectional search mode. For the selected entities, interaction graphs are generated from different data sources and dynamically presented. Connected application programming interfaces (APIs) to the tailored enrichment tools miEAA and GeneTrail facilitate downstream analysis of pathways and context-annotated categories of network nodes. MiRTargetLink 2.0 is freely accessible at https://www.ccb.uni-saarland.de/mirtargetlink2.

In Silico Analysis of Micro-RNA Sequencing Data.

High-throughput sequencing for micro-RNAs (miRNAs) to obtain expression estimates is a central method of molecular biology. Surprisingly, there are a number of different approaches to converting sequencing output into micro-RNA counts. Each has their own strengths and biases that impact on the final data that can be obtained from a sequencing run. This chapter serves to make the reader aware of the trade-offs one must consider in analyzing small RNA sequencing data. It then compares two methods, miRge2.0 and the sRNAbench and the steps utilized to output data from their tools.