Evaluation of Bioinformatics Approaches for Next-Generation Sequencing Analysis of microRNAs with a Toxicogenomics Study Design

Hepatitis B Virus and microRNAs: A Bioinformatics Approach

In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis. Consequently, miRNAs are considered a promising biomarker for diagnostic, prognostic, and treatment response. The dynamics of miRNAs during HBV infection are multifaceted, influenced by host variability and miRNA interactions. Given the ability of miRNAs to target multiple messenger RNA (mRNA), understanding the viral-host (human) interplay is complex but essential to develop novel clinical applications. Therefore, bioinformatics can help to analyze, identify, and interpret a vast amount of miRNA data. This review explores the bioinformatics tools available for viral and host miRNA research. Moreover, we introduce a brief overview focusing on the role of miRNAs during HBV infection. In this way, this review aims to help the selection of the most appropriate bioinformatics tools based on requirements and research goals.

miRNA Studies in Glaucoma: A Comprehensive Review of Current Knowledge and Future Perspectives

Glaucoma, a neurodegenerative disorder that leads to irreversible blindness, remains a challenge because of its complex nature. MicroRNAs (miRNAs) are crucial regulators of gene expression and are associated with glaucoma and other diseases. We aimed to review and discuss the advantages and disadvantages of miRNA-focused molecular studies in glaucoma through discussing their potential as biomarkers for early detection and diagnosis; offering insights into molecular pathways and mechanisms; and discussing their potential utility with respect to personalized medicine, their therapeutic potential, and non-invasive monitoring. Limitations, such as variability, small sample sizes, sample specificity, and limited accessibility to ocular tissues, are also addressed, underscoring the need for robust protocols and collaboration. Reproducibility and validation are crucial to establish the credibility of miRNA research findings, and the integration of bioinformatics tools for miRNA database creation is a valuable component of a comprehensive approach to investigate miRNA aberrations in patients with glaucoma. Overall, miRNA research in glaucoma has provided significant insights into the molecular mechanisms of the disease, offering potential biomarkers, diagnostic tools, and therapeutic targets. However, addressing challenges such as variability and limited tissue accessibility is essential, and further investigations and validation will contribute to a deeper understanding of the functional significance of miRNAs in glaucoma.

Assessment of microRNA profiles in small extracellular vesicles isolated from bovine colostrum with different immunoglobulin G concentrations

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The RNA concentration in sEV isolated from bovine colostrum was highest using the combination of the miRCURY Cell/Urine/CSF and miRNeasy Mini kits.

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The top 50 miRNA were the same using miRDeep2 and sRNAbench, predominated by let-7b, let-7a-5p, miR-30a-5p, and miR-148a.

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Predicted target genes of the top 50 miRNA regulate PI3K-Akt and MAPK signaling pathways, axon guidance, and focal adhesion.

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The abundance of miR-27a-3p was higher in colostrum with high IgG concentrations.

The consumption of bovine colostrum by newborn calves during the first days of life is essential to ensure the transfer of passive immunity. In addition to critical IgG, colostrum also contains non-IgG biomolecules, including microRNA (miRNA). The present study investigated the profiles of miRNA in small extracellular vesicles (sEV) isolated from bovine colostrum with high (256.5 ± 5.7 mg/mL, mean ± standard deviation, n = 4) and low (62.8 ± 3.6 mg/mL, n = 4) concentrations of IgG. Different combination of sEV extraction methods and bioinformatic pipelines (miRDeep2 and sRNAbench) for miRNA analysis were evaluated. Results showed that miRCURY exosome Cell/Urine/CSF and miRNeasy Mini kits yielded the highest RNA concentration. The miRNA-seq data analysis showed miRDeep2 yielded more comprehensive miRNAome compared with sRNAbench (527 versus 392 unique miRNA), whereas 389 shared miRNA were identified using both approaches. The profiles of top 50 miRNA were the same using both approaches, and their abundance contributed to 91.7% and 94.3% of total abundance of miRNA using miRDeep2 and sRNAbennch, respectively. These core miRNA were predicted to target 2,655 genes, which regulate 78 KEGG (Kyoto Encyclopedia of Genes and Genomes) level-3 pathways including PI3K-Akt and MAPK signaling pathway, axon guidance, and focal adhesion. The expression profiles of sEV-associated miRNA were similar between high- and low-IgG colostrum samples, despite the fact that the abundance of miR-27a-3p was higher in colostrum with high concentrations of IgG. In conclusion, a core miRNAome in bovine colostrum may play a role in regulating health and developmental stages in neonatal calves, independent of IgG concentration.

Identification and expression analysis of ten novel small non-coding RNAs (sncRNAs) in cancer cells using a high-throughput sequencing approach

Non-coding RNAs are characterized as RNA molecules, which lack the capacity to encode protein structures and appear to include a level of internal signals. Moreover, they control various stages of gene expression, thus controlling the cell physiology and development. In this study, we implemented a high-throughput sequencing approach based on the primary semi-conductor technology and computational tools, in order to identity novel small non-coding RNAs. Fourteen human cancer cell lines were cultured, and RNA samples were enriched for small RNAs following semi-conductor next generation sequencing (NGS). Bioinformatics analysis of NGS data revealed the existence of several classes of ncRNAs using the miRDeep* and CPSS 2.0 software. To investigate the existence of the predicted non-coding RNA sequences in cDNA pools of cell lines, a developed qPCR-based assay was implemented. The structure of each novel small ncRNA was visualized, using the RNAfold algorithm. Our results support the existence of twenty (20) putative new small ncRNAs, ten (10) of which have had their expression experimentally validated and presented differential profiles in cancerous and normal cells. A deeper comprehension of the ncRNAs interactive network and its role in cancer can therefore be translated into a wide range of clinical applications. Despite this progress, further scientific research from different perspectives and in different fields is needed, so that the riddle of the human transcriptome can be solved.

Regulation of angiogenesis by microRNAs in cancer

MicroRNAs (miRs) are endogenous, small, non‑coding RNA molecules with ~22 nucleotides, and are involved in regulating the expression of multiple genes and controlling cellular functions. miRs serve key roles in angiogenesis by regulating the proliferation, differentiation, apoptosis and migration of endothelial cells. Regulation of angiogenesis is essential for several physiological and pathological processes, particularly for tumor development and progression. Therefore, it is important to investigate the roles served by miRs in angiogenesis as this may aid in discovering novel strategies for treating tumors via modulating angiogenesis. In this review, miRNA biogenesis, regulation and functions are described with new information and corresponding references. In particular, the latest advances in the role of various miRs and their target genes involved in tumor angiogenesis were updated. Next, different signaling pathways by which miRNAs could be regulated in different types of tumor progression were addressed. Furthermore, the potential clinical value of miRs as biomarkers for diagnosing and monitoring the response to therapy, as well as their ability to regulate tumor angiogenesis and the mechanism underlying this regulation, were investigated.

Micro-RNA: The darkhorse of cancer

The discovery of micro RNAs (miRNA) in cancer has opened up new vistas for researchers in recent years. Micro RNAs area set of small, endogenous, highly conserved, non-coding RNAs that control the expression of about 30% genes at post-transcriptional levels. Typically, microRNAs impede the translation and stability of messenger RNAs (mRNA), control genes associated with cellular processes namely inflammation, cell cycle regulation, stress response, differentiation, apoptosis, and migration. Compelling findings revealed that miRNA mutations or disruption correspond to diverse human cancers and suggest that miRNAs can function as tumor suppressors or oncogenes. Here we summarize the literature on these master regulators in clinical settings from last three decades as both abrupt cancer therapeutics and as an approach to sensitize tumors to chemotherapy. This review highlights (I) the prevailing perception of miRNA genomics, biogenesis, as well as function; (II) the significant advancements in regulatory mechanisms in the expression of carcinogenic genes; and (III) explains, how miRNA is utilized as a diagnostic and prognostic biomarker for the disease stage indicating survival as well as therapeutic targets in cancer.

Evaluation and application of tools for the identification of known microRNAs in plants

MicroRNAs (miRNAs), endogenous non-coding RNA regulators, post-transcriptionally inhibit the expression of their target genes. Several tools have been developed for predicting annotated known miRNAs, but there is no consensus about how to select the most suitable method for any given species. In this study, eight miRNA prediction tools (mirnovo, miRPlant, miRDeep-P2, miRExpress, miRkwood, miRDeep2, miR-PREFeR, and sRNAbench) were selected for evaluation. High-throughput small RNA sequencing data from four plant species (including C3 and C4 species, and both monocots and dicots, i.e., Arabidopsis thaliana, Oryza sativa, Triticum aestivum, and Zea mays) were used for the analysis. The sensitivity, accuracy, area under the curve, consistency, duration, and RAM usage of the known miRNA predictions were evaluated for each tool. The miRNA annotations were obtained using miRBase and sRNAanno. Algorithms, such as random forest, BLAST, and receiver operating characteristic curves, were used to evaluate accuracy. Of the tools evaluated, sRNAbench was found to be the most accurate, miRDeep-P2 was the most sensitive, miRDeep-P2 was the fastest, and miRkwood had the highest memory usage. Due to its large genome size, only three tools were able to successfully predict known miRNAs in wheat (Triticum aestivum). Our results enable us to recommend the tool best suited to a variety of researcher needs, which we hope will reduce confusion and enhance future work.

Integration of miRNAs, Degradome, and Transcriptome Omics Uncovers a Complex Regulatory Network and Provides Insights Into Lipid and Fatty Acid Synthesis During Sesame Seed Development

Sesame (Sesamum indicum L.) has always been known as a health-promoting oilseed crop because of its nutrient-rich oil. In recent years, studies have focused on lipid and fatty acid (FA) biosynthesis in various plants by high-throughput sequencing. Here, we integrated transcriptomics, small RNAs, and the degradome to establish a comprehensive reserve intensive on key regulatory micro RNA (miRNA)-targeting circuits to better understand the transcriptional and translational regulation of the oil biosynthesis mechanism in sesame seed development. Deep sequencing was performed to differentially express 220 miRNAs, including 65 novel miRNAs, in different developmental periods of seeds. GO and integrated KEGG analysis revealed 32 pairs of miRNA targets with negatively correlated expression profiles, of which 12 miRNA-target pairs were further confirmed by RT-PCR. In addition, a regulatory co-expression network was constructed based on the differentially expressed gene (DEG) profiles. The FAD2, LOC10515945, LOC105161564, and LOC105162196 genes were clustered into groups that regulate the accumulation of unsaturated fatty acid (UFA) biosynthesis. The results provide a unique advanced molecular platform for the study of lipid and FA biosynthesis, and this study may serve as a new theoretical reference to obtain increased levels of UFA from higher-quality sesame seed cultivars and other plants.

Detection of disease-associated microRNAs - application for autism spectrum disorders

Autism spectrum disorders (ASD) diagnostic procedure still lacks a uniform biological marker. This review gathers the information on microRNAs (miRNAs) specifically as a possible source of biomarkers of ASD. Extracellular vesicles, and their subset of exosomes, are believed to be a tool of cell-to-cell communication, and they are increasingly considered to be carriers of such a marker. The interest in studying miRNAs in extracellular vesicles grows in all fields of study and therefore should not be omitted in the field of neurodevelopmental disorders. The summary of miRNAs associated with brain cells and ASD either studied directly in the tissue or biofluids are gathered in this review. The heterogeneity in findings from different studies points out the fact that unified methods should be established, beginning with the determination of the accurate patient and control groups, through to sample collection, processing, and storage conditions. This review, based on the available literature, proposes the standardized approach to obtain the results that would not be affected by technical factors. Nowadays, the method of high-throughput sequencing seems to be the most optimal to analyze miRNAs. This should be followed by the uniformed bioinformatics procedure to avoid misvalidation. At the end, the proper validation of the obtained results is needed. With such an approach as is described in this review, it would be possible to obtain a reliable biomarker that would characterize the presence of ASD.

Computational Methods and Software Tools for Functional Analysis of miRNA Data

miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs.

Cell-cycle dependence of transcriptome gene modules: comparison of regression lines

The transcriptome consists of various gene modules that can be mutually dependent, and ignoring these dependencies may lead to misinterpretation. The most important problem is module dependence on cell-cycle activity. Using meta-analysis of over 30 000 single-cell transcriptomes, we show gene module dependencies on cell-cycle signature, which can be consistently observed in various normal and cancer cells. Transcript levels of receptors, plasma membrane, and differentiation-related genes are negatively regressed on cell-cycle signature. Pluripotency, stress response, DNA repair, chromatin remodeling, proteasomal protein degradation, protein network connectivity, and unicellular evolutionary origin are regressed positively. These effects cannot be explained by partial overlap of corresponding gene sets because they remain if the overlapped genes were removed. We propose a visual analysis of gene module-specific regression lines as complement to an uncurated enrichment analysis. The different lines for a same gene module indicate different cell conditions. The approach is tested on several problems (polyploidy, pluripotency, cancer, phylostratigraphy). Intriguingly, we found variation in cell-cycle activity, which is independent of cell progression through the cycle. The upregulation of G2/M checkpoint genes with downregulation of G2/M transition and cytokinesis is revealed in polyploid cells. A temporal increase in cell-cycle activity at transition from pluripotent to more differentiated state is found in human embryonic stem cells. The upregulation of unicellular interactome cluster in human cancers is shown in single cells with control for cell-cycle activity. The greater scatter around regression line in cancer cells suggests greater heterogeneity caused by deviation from a line of normal cells.

RATEmiRs: the rat atlas of tissue-specific and enriched miRNAs for discerning baseline expression exclusivity of candidate biomarkers

MicroRNAs (miRNAs) are small RNAs that regulate mRNA expression and have been targeted as biomarkers of organ damage and disease. To explore the utility of miRNAs to assess injury to specific tissues, a tissue atlas of miRNA abundance was constructed. The Rat Atlas of Tissue-specific and Enriched miRNAs (RATEmiRs) catalogues miRNA sequencing data from 21 and 23 tissues in male and female Sprague-Dawley rats, respectively. RATEmiRs identifies tissue-enriched (TE), tissue-specific (TS), or organ-specific (OS) miRNAs via comparisons of one or more tissue or organ vs others. We provide a brief overview of RATEmiRs and present how to use it to detect miRNA expression abundance of candidate biomarkers as well as to compare the expression of miRNAs between rat and human. The database is available at https://www.niehs.nih.gov/ratemirs/.

Comparison of RNA-Seq and Microarray Gene Expression Platforms for the Toxicogenomic Evaluation of Liver From Short-Term Rat Toxicity Studies

Gene expression profiling is a useful tool to predict and interrogate mechanisms of toxicity. RNA-Seq technology has emerged as an attractive alternative to traditional microarray platforms for conducting transcriptional profiling. The objective of this work was to compare both transcriptomic platforms to determine whether RNA-Seq offered significant advantages over microarrays for toxicogenomic studies. RNA samples from the livers of rats treated for 5 days with five tool hepatotoxicants (α-naphthylisothiocyanate/ANIT, carbon tetrachloride/CCl₄, methylenedianiline/MDA, acetaminophen/APAP, and diclofenac/DCLF) were analyzed with both gene expression platforms (RNA-Seq and microarray). Data were compared to determine any potential added scientific (i.e., better biological or toxicological insight) value offered by RNA-Seq compared to microarrays. RNA-Seq identified more differentially expressed protein-coding genes and provided a wider quantitative range of expression level changes when compared to microarrays. Both platforms identified a larger number of differentially expressed genes (DEGs) in livers of rats treated with ANIT, MDA, and CCl₄ compared to APAP and DCLF, in agreement with the severity of histopathological findings. Approximately 78% of DEGs identified with microarrays overlapped with RNA-Seq data, with a Spearman’s correlation of 0.7 to 0.83. Consistent with the mechanisms of toxicity of ANIT, APAP, MDA and CCl₄, both platforms identified dysregulation of liver relevant pathways such as Nrf2, cholesterol biosynthesis, eiF2, hepatic cholestasis, glutathione and LPS/IL-1 mediated RXR inhibition. RNA-Seq data showed additional DEGs that not only significantly enriched these pathways, but also suggested modulation of additional liver relevant pathways. In addition, RNA-Seq enabled the identification of non-coding DEGs that offer a potential for improved mechanistic clarity. Overall, these results indicate that RNA-Seq is an acceptable alternative platform to microarrays for rat toxicogenomic studies with several advantages. Because of its wider dynamic range as well as its ability to identify a larger number of DEGs, RNA-Seq may generate more insight into mechanisms of toxicity. However, more extensive reference data will be necessary to fully leverage these additional RNA-Seq data, especially for non-coding sequences.