Applications of Machine Learning in miRNA Discovery and Target Prediction.
TL;DR: The application of ML approaches in miRNA discovery and target prediction with functions and future prospective is described and the implementation of a new era of computational methodologies in this direction would initiate further advanced levels of discoveries in mi RNA.
Abstract: MicroRNA (miRNA) is a small non-coding molecule that is involved in gene regulation and RNA silencing by complementary on their targets. Experimental methods for target prediction can be time-consuming and expensive. Thus, the application of the computational approach is implicated to enlighten these complications with experimental studies. However, there is still a need for an optimized approach in miRNA biology. Therefore, machine learning (ML) would initiate a new era of research in miRNA biology towards potential diseases biomarker. In this article, we described the application of ML approaches in miRNA discovery and target prediction with functions and future prospective. The implementation of a new era of computational methodologies in this direction would initiate further advanced levels of discoveries in miRNA.
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24 Dec 2020
TL;DR: In this article, a review summarizes the key strategies for miRNA target identification and all the experimental procedures for verifying the authenticity of the identified miRNA-mRNA target pairs, including high-throughput technologies, in order to find the best approach for validation.
Abstract: MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in both animals and plants. By pairing to microRNA responsive elements (mREs) on target mRNAs, miRNAs play gene-regulatory roles, producing remarkable changes in several physiological and pathological processes. Thus, the identification of miRNA-mRNA target interactions is fundamental for discovering the regulatory network governed by miRNAs. The best way to achieve this goal is usually by computational prediction followed by experimental validation of these miRNA-mRNA interactions. This review summarizes the key strategies for miRNA target identification. Several tools for computational analysis exist, each with different approaches to predict miRNA targets, and their number is constantly increasing. The major algorithms available for this aim, including Machine Learning methods, are discussed, to provide practical tips for familiarizing with their assumptions and understanding how to interpret the results. Then, all the experimental procedures for verifying the authenticity of the identified miRNA-mRNA target pairs are described, including High-Throughput technologies, in order to find the best approach for miRNA validation. For each strategy, strengths and weaknesses are discussed, to enable users to evaluate and select the right approach for their interests.
64 citations
TL;DR: In this paper , a review of miRNA-mediated regulation of the expression of major genes or Transcription Factor (TFs), as well as genetic and regulatory pathways is presented, focusing on their exploration for engineering abiotic stress tolerance in plants.
18 citations
TL;DR: In this paper , the main factors of therapeutic miRNA are discussed, and the dosage of miRNA administration remains unclear, and ways to address this issue are proposed, which will allow further developments and innovations to achieve safe therapeutic tools.
Abstract: MicroRNA (miRNA) is regarded as a prominent genetic regulator, as it can fine‐tune an entire biological pathway by targeting multiple target genes. This characteristic makes miRNAs promising therapeutic tools to reinstate cell functions that are disrupted as a consequence of diseases. Currently, miRNA replacement by miRNA mimics and miRNA inhibition by anti‐miRNA oligonucleotides are the main approaches to utilizing miRNA molecules for therapeutic purposes. Nevertheless, miRNA‐based therapeutics are hampered by major issues such as off‐target effects, immunogenicity, and uncertain delivery platforms. Over the past few decades, several innovative approaches have been established to minimize off‐target effects, reduce immunostimulation, and provide efficient transfer to the target cells in which these molecules exert their function. Recent achievements have led to the testing of miRNA‐based drugs in clinical trials, and these molecules may become next‐generation therapeutics for medical intervention. Despite the achievement of exciting milestones, the dosage of miRNA administration remains unclear, and ways to address this issue are proposed. Elucidating the current status of the main factors of therapeutic miRNA would allow further developments and innovations to achieve safe therapeutic tools.
12 citations
TL;DR: The results have identified candidate genes and pathways related to the underlying molecular mechanism of NB and provide a new perspective for NB research and treatment.
Abstract: Neuroblastomas (NB) are childhood malignant tumors originating in the sympathetic nervous system. MicroRNAs (miRNAs) play an essential regulatory role in tumorigenesis and development. In this study, NB miRNA and mRNA expression profile data in the Gene Expression Omnibus database were used to screen for differentially expressed miRNAs (DEMs) and genes (DEGs). We used the miRTarBase and miRSystem databases to predict the target genes of the DEMs, and we selected target genes that overlapped with the DEGs as candidate genes for further study. Annotations, visualization, and the DAVID database were used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the candidate genes. Additionally, the protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed and visualized using the STRING database and Cytoscape, and the hub modules were analyzed for function and pathway enrichment using the DAVID database and BiNGO plug-in. 107 DEMs and 1139 DEGs were identified from the miRNA and mRNA chips, respectively. 4390 overlapping target genes were identified using the two databases, and 405 candidate genes which intersected with the DEGs were selected. These candidate genes were enriched in 363 GO terms and 24 KEGG pathways. By constructing a PPI network and a miRNA-mRNA regulatory network, three hub miRNAs (hsa-miR-30e-5p, hsa-miR-15a, and hsa-miR-16) were identified. The target genes of the hub miRNAs were significantly enriched in the following pathways: microRNAs in cancer, the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, and the cell cycle. In summary, our results have identified candidate genes and pathways related to the underlying molecular mechanism of NB. These findings provide a new perspective for NB research and treatment.
8 citations
TL;DR: This report is the first to identify miRNAs in raspberry, and adds novel mi RNAs to the raspberry transcriptome, providing a useful resource for the further elucidation of the functional roles of miRNas in raspberry growth and development.
Abstract: MicroRNAs (miRNAs) are a class of small endogenous RNAs that play important regulatory roles in plants by negatively affecting gene expression. Studies on the identification of miRNAs and their functions in various plant species and organs have significantly contributed to plant development research. In the current study, we utilized high-throughput sequencing to detect the miRNAs in the root, stem, and leaf tissues of raspberry (Rubus idaeus). A total of more than 35 million small RNA reads ranging in size from 18 to 35 nucleotides were obtained, with 147 known miRNAs and 542 novel miRNAs identified among the three organs. Sequence verification and the relative expression profiles of the six known miRNAs were investigated by stem-loop quantitative real-time PCR. Furthermore, the potential target genes of the known and novel miRNAs were predicted and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway annotation. Enrichment analysis of the GO-associated biological processes and molecular functions revealed that these target genes were potentially involved in a wide range of metabolic pathways and developmental processes. Moreover, the miRNA target prediction revealed that most of the targets predicted as transcription factor-coding genes are involved in cellular and metabolic processes. This report is the first to identify miRNAs in raspberry. The detected miRNAs were analyzed by cluster analysis according to their expression, which revealed that these conservative miRNAs are necessary for plant functioning. The results add novel miRNAs to the raspberry transcriptome, providing a useful resource for the further elucidation of the functional roles of miRNAs in raspberry growth and development.
8 citations
References
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TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
31,015 citations
"Applications of Machine Learning in..." refers background in this paper
...Therefore, several databases have been developed in past few decades that provide functional information of miRNA such as DAVID [29] which is a knowledge-based visualization of functional annotation of miRNA....
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TL;DR: Two small lin-4 transcripts of approximately 22 and 61 nt were identified in C. elegans and found to contain sequences complementary to a repeated sequence element in the 3' untranslated region (UTR) of lin-14 mRNA, suggesting that lin- 4 regulates lin- 14 translation via an antisense RNA-RNA interaction.
11,932 citations
"Applications of Machine Learning in..." refers background in this paper
...discovered miRNA in the nematode Caenorhabditis elegans as lin-4 [3, 4]....
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TL;DR: An update of the miRBase database is described, including the collation and use of deep sequencing data sets to assign levels of confidence to miR base entries, and a high confidence subset of miR Base entries are provided, based on the pattern of mapped reads.
Abstract: We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.
4,705 citations
TL;DR: Small non-coding RNAs that function as guide molecules in RNA silencing are involved in nearly all developmental and pathological processes in animals and their dysregulation is associated with many human diseases.
Abstract: MicroRNAs (miRNAs) are small non-coding RNAs that function as guide molecules in RNA silencing. Targeting most protein-coding transcripts, miRNAs are involved in nearly all developmental and pathological processes in animals. The biogenesis of miRNAs is under tight temporal and spatial control, and their dysregulation is associated with many human diseases, particularly cancer. In animals, miRNAs are ∼22 nucleotides in length, and they are produced by two RNase III proteins--Drosha and Dicer. miRNA biogenesis is regulated at multiple levels, including at the level of miRNA transcription; its processing by Drosha and Dicer in the nucleus and cytoplasm, respectively; its modification by RNA editing, RNA methylation, uridylation and adenylation; Argonaute loading; and RNA decay. Non-canonical pathways for miRNA biogenesis, including those that are independent of Drosha or Dicer, are also emerging.
4,256 citations
"Applications of Machine Learning in..." refers background in this paper
...In translational repression, miRNA sequence aligns partially to a binding region of their target gene that resists the binding of ribosomes to the target gene resulting in the inhibition of synthesis of the polypeptide [6, 7]....
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TL;DR: In this article, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties of nucleic acids based on carefully measured thermodynamic parameters.
Abstract: Background
Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.
3,620 citations