International Journal of Molecular Sciences

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13 pages, 1303 KiB

Open AccessArticle

LE-MDCAP: A Computational Model to Prioritize Causal miRNA-Disease Associations

by Zhou Huang, Yu Han, Leibo Liu, Qinghua Cui and Yuan Zhou

Int. J. Mol. Sci. 2021, 22(24), 13607; https://doi.org/10.3390/ijms222413607 - 19 Dec 2021

Cited by 4 | Viewed by 2229

Abstract

MicroRNAs (miRNAs) are associated with various complex human diseases and some miRNAs can be directly involved in the mechanisms of disease. Identifying disease-causative miRNAs can provide novel insight in disease pathogenesis from a miRNA perspective and facilitate disease treatment. To date, various computational [...] Read more.

MicroRNAs (miRNAs) are associated with various complex human diseases and some miRNAs can be directly involved in the mechanisms of disease. Identifying disease-causative miRNAs can provide novel insight in disease pathogenesis from a miRNA perspective and facilitate disease treatment. To date, various computational models have been developed to predict general miRNA-disease associations, but few models are available to further prioritize causal miRNA-disease associations from non-causal associations. Therefore, in this study, we constructed a Levenshtein-Distance-Enhanced miRNA-disease Causal Association Predictor (LE-MDCAP), to predict potential causal miRNA-disease associations. Specifically, Levenshtein distance matrixes covering the sequence, expression and functional miRNA similarities were introduced to enhance the previous Gaussian interaction profile kernel-based similarity matrix. LE-MDCAP integrated miRNA similarity matrices, disease semantic similarity matrix and known causal miRNA-disease associations to make predictions. For regular causal vs. non-disease association discrimination task, LF-MDCAP achieved area under the receiver operating characteristic curve (AUROC) of 0.911 and 0.906 in 10-fold cross-validation and independent test, respectively. More importantly, LE-MDCAP prominently outperformed the previous MDCAP model in distinguishing causal versus non-causal miRNA-disease associations (AUROC 0.820 vs. 0.695). Case studies performed on diabetic retinopathy and hsa-mir-361 also validated the accuracy of our model. In summary, LE-MDCAP could be useful for screening causal miRNA-disease associations from general miRNA-disease associations. Full article

(This article belongs to the Special Issue RNA Informatics)

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19 pages, 2597 KiB

Open AccessArticle

Developing an Updated Strategy for Estimating the Free-Energy Parameters in RNA Duplexes

by Wayne K. Dawson, Amiu Shino, Gota Kawai and Ella Czarina Morishita

Int. J. Mol. Sci. 2021, 22(18), 9708; https://doi.org/10.3390/ijms22189708 - 8 Sep 2021

Cited by 4 | Viewed by 2435

Abstract

For the last 20 years, it has been common lore that the free energy of RNA duplexes formed from canonical Watson–Crick base pairs (bps) can be largely approximated with dinucleotide bp parameters and a few simple corrective constants that are duplex independent. Additionally, [...] Read more.

For the last 20 years, it has been common lore that the free energy of RNA duplexes formed from canonical Watson–Crick base pairs (bps) can be largely approximated with dinucleotide bp parameters and a few simple corrective constants that are duplex independent. Additionally, the standard benchmark set of duplexes used to generate the parameters were GC-rich in the shorter duplexes and AU-rich in the longer duplexes, and the length of the majority of the duplexes ranged between 6 and 8 bps. We were curious if other models would generate similar results and whether adding longer duplexes of 17 bps would affect the conclusions. We developed a gradient-descent fitting program for obtaining free-energy parameters—the changes in Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS), and the melting temperature (Tm)—directly from the experimental melting curves. Using gradient descent and a genetic algorithm, the duplex melting results were combined with the standard benchmark data to obtain bp parameters. Both the standard (Turner) model and a new model that includes length-dependent terms were tested. Both models could fit the standard benchmark data; however, the new model could handle longer sequences better. We developed an updated strategy for fitting the duplex melting data. Full article

(This article belongs to the Special Issue RNA Informatics)

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15 pages, 2531 KiB

Open AccessArticle

Detecting and Profiling Endogenous RNA G-Quadruplexes in the Human Transcriptome

by Rongxin Zhang, Yajun Liu, Xingxing Zhang, Ke Xiao, Yue Hou, Hongde Liu and Xiao Sun

Int. J. Mol. Sci. 2021, 22(15), 8012; https://doi.org/10.3390/ijms22158012 - 27 Jul 2021

Cited by 2 | Viewed by 2702

Abstract

G-quadruplexes are the non-canonical nucleic acid structures that are preferentially formed in G-rich regions. This structure has been shown to be associated with many biological functions. Regardless of the broad efforts on DNA G-quadruplexes, we still have limited knowledge on RNA G-quadruplexes, especially [...] Read more.

G-quadruplexes are the non-canonical nucleic acid structures that are preferentially formed in G-rich regions. This structure has been shown to be associated with many biological functions. Regardless of the broad efforts on DNA G-quadruplexes, we still have limited knowledge on RNA G-quadruplexes, especially in a transcriptome-wide manner. Herein, by integrating the DMS-seq and the bioinformatics pipeline, we profiled and depicted the RNA G-quadruplexes in the human transcriptome. The genes that contain RNA G-quadruplexes in their specific regions are significantly related to immune pathways and the COVID-19-related gene sets. Bioinformatics analysis reveals the potential regulatory functions of G-quadruplexes on miRNA targeting at the scale of the whole transcriptome. In addition, the G-quadruplexes are depleted in the putative, not the real, PAS-strong poly(A) sites, which may weaken the possibility of such sites being the real cleaved sites. In brief, our study provides insight into the potential function of RNA G-quadruplexes in post-transcription. Full article

(This article belongs to the Special Issue RNA Informatics)

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12 pages, 2157 KiB

Open AccessArticle

Evaluation of Oxford Nanopore MinION RNA-Seq Performance for Human Primary Cells

by Ilaria Massaiu, Paola Songia, Mattia Chiesa, Vincenza Valerio, Donato Moschetta, Valentina Alfieri, Veronika A. Myasoedova, Michael Schmid, Luca Cassetta, Gualtiero I. Colombo, Yuri D’Alessandra and Paolo Poggio

Int. J. Mol. Sci. 2021, 22(12), 6317; https://doi.org/10.3390/ijms22126317 - 12 Jun 2021

Cited by 8 | Viewed by 6561

Abstract

Transcript sequencing is a crucial tool for gaining a deep understanding of biological processes in diagnostic and clinical medicine. Given their potential to study novel complex eukaryotic transcriptomes, long-read sequencing technologies are able to overcome some limitations of short-read RNA-Seq approaches. Oxford Nanopore [...] Read more.

Transcript sequencing is a crucial tool for gaining a deep understanding of biological processes in diagnostic and clinical medicine. Given their potential to study novel complex eukaryotic transcriptomes, long-read sequencing technologies are able to overcome some limitations of short-read RNA-Seq approaches. Oxford Nanopore Technologies (ONT) offers the ability to generate long-read sequencing data in real time via portable protein nanopore USB devices. This work aimed to provide the user with the number of reads that should be sequenced, through the ONT MinION platform, to reach the desired accuracy level for a human cell RNA study. We sequenced three cDNA libraries prepared from poly-adenosine RNA of human primary cardiac fibroblasts. Since the runs were comparable, they were combined in a total dataset of 48 million reads. Synthetic datasets with different sizes were generated starting from the total and analyzed in terms of the number of identified genes and their expression levels. As expected, an improved sensitivity was obtained, increasing the sequencing depth, particularly for the non-coding genes. The reliability of expression levels was assayed by (i) comparison with PCR quantifications of selected genes and (ii) by the implementation of a user-friendly multiplexing method in a single run. Full article

(This article belongs to the Special Issue RNA Informatics)

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12 pages, 466 KiB

Open AccessArticle

A Web Server for Designing Molecular Switches Composed of Two Interacting RNAs

by Akito Taneda and Kengo Sato

Int. J. Mol. Sci. 2021, 22(5), 2720; https://doi.org/10.3390/ijms22052720 - 8 Mar 2021

Cited by 1 | Viewed by 2322

Abstract

The programmability of RNA–RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. [...] Read more.

The programmability of RNA–RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. Although multi-objective optimization is a powerful technique that explores a vast solution space without empirical weights between design objectives, to date, no web service for multi-objective design of RNA switches that utilizes RNA–RNA interaction has been proposed. We developed a web server, which is based on a multi-objective design algorithm called MODENA, to design two interacting RNAs that form a complex in silico. By predicting the secondary structures with RactIP during the design process, we can design RNAs that form a joint secondary structure with an external pseudoknot. The energy barrier upon the complex formation is modeled by an interaction seed that is optimized in the design algorithm. We benchmarked the RNA switch design approaches (MODENA+RactIP and MODENA+RNAcofold) for the target structures based on natural RNA-RNA interactions. As a result, MODENA+RactIP showed high design performance for the benchmark datasets. Full article

(This article belongs to the Special Issue RNA Informatics)

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Review

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24 pages, 1916 KiB

Open AccessReview

Biogenesis, Functions, Interactions, and Resources of Non-Coding RNAs in Plants

by Haoyu Chao, Yueming Hu, Liang Zhao, Saige Xin, Qingyang Ni, Peijing Zhang and Ming Chen

Int. J. Mol. Sci. 2022, 23(7), 3695; https://doi.org/10.3390/ijms23073695 - 28 Mar 2022

Cited by 14 | Viewed by 4720

Abstract

Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. [...] Read more.

Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. With advances in RNA sequencing technology and computational methods, bioinformatics resources continue to emerge and update rapidly, including workflow for in silico ncRNA analysis, up-to-date platforms, databases, and tools dedicated to ncRNA identification and functional annotation. In this review, we aim to describe the biogenesis, biological functions, and interactions with DNA, RNA, protein, and microorganism of five major regulatory ncRNAs (miRNA, siRNA, tsRNA, circRNA, lncRNA) in plants. Then, we systematically summarize tools for analysis and prediction of plant ncRNAs, as well as databases. Furthermore, we discuss the silico analysis process of these ncRNAs and present a protocol for step-by-step computational analysis of ncRNAs. In general, this review will help researchers better understand the world of ncRNAs at multiple levels. Full article

(This article belongs to the Special Issue RNA Informatics)

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16 pages, 1910 KiB

Open AccessReview

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

by Andrés Rincón-Riveros, Duvan Morales, Josefa Antonia Rodríguez, Victoria E. Villegas and Liliana López-Kleine

Int. J. Mol. Sci. 2021, 22(21), 11397; https://doi.org/10.3390/ijms222111397 - 22 Oct 2021

Cited by 18 | Viewed by 4154

Abstract

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from [...] Read more.

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included. Full article

(This article belongs to the Special Issue RNA Informatics)

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19 pages, 42303 KiB

Open AccessReview

Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures

by Reeki Emrizal, Hazrina Yusof Hamdani and Mohd Firdaus-Raih

Int. J. Mol. Sci. 2021, 22(16), 8553; https://doi.org/10.3390/ijms22168553 - 9 Aug 2021

Cited by 2 | Viewed by 2496

Abstract

The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs [...] Read more.

The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule’s functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database. Full article

(This article belongs to the Special Issue RNA Informatics)

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