RESUMO
MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure from a raw RNA sequence is a long-standing unsolved problem, which after decades of almost unchanged performance has now re-emerged due to deep learning. Traditional RNA secondary structure prediction algorithms have been mostly based on thermodynamic models and dynamic programming for free energy minimization. More recently deep learning methods have shown competitive performance compared with the classical ones, but there is still a wide margin for improvement. RESULTS: In this work we present sincFold, an end-to-end deep learning approach, that predicts the nucleotides contact matrix using only the RNA sequence as input. The model is based on 1D and 2D residual neural networks that can learn short- and long-range interaction patterns. We show that structures can be accurately predicted with minimal physical assumptions. Extensive experiments were conducted on several benchmark datasets, considering sequence homology and cross-family validation. sincFold was compared with classical methods and recent deep learning models, showing that it can outperform the state-of-the-art methods.
Assuntos
Biologia Computacional , Aprendizado Profundo , Conformação de Ácido Nucleico , RNA , RNA/química , RNA/genética , Biologia Computacional/métodos , Algoritmos , Redes Neurais de Computação , TermodinâmicaRESUMO
The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.
Assuntos
Conformação de Ácido Nucleico , Desnaturação de Ácido Nucleico , Termodinâmica , Temperatura de Transição , RNA/química , RNA/genética , Software , Algoritmos , Hibridização de Ácido Nucleico/métodosRESUMO
SUMMARY: Overexpression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in various tumor tissues and cell lines was found to promote tumor cell proliferation, migration, and invasion. However, the role of MALAT1 in gastric cancer (GC) is still unclear. We aimed to investigate the correlation between long-chain non-coding RNAs (lncRNAs), MALAT1, MicroRNAs (miRNA) and vascular endothelial growth factor A (VEGFA) in gastric cancer and to disclose underlying mechanism. The correlation between MALAT1 levels and clinical features was analyzed by bioinformatics data and human samples. The expression of MALAT1 was down regulated in AGS cells to detect the cell proliferation, migration, and invasion characteristics, as well as the effects on signal pathways. Furthermore, we validated the role of MALAT1/miR-330-3p axis in GC by dual luciferase reporter gene assays. Expression of MALAT1 was higher in cancer tissues than in para-cancerous tissues. The high MALAT1 level predicted malignancy and worse prognosis. Down-regulation of MALAT1 expression in AGS cells inhibited cell proliferation, migration, and invasion by targeting VEGFA. By dual luciferase reporter gene assay and miR-330-3p inhibitor treatment, we demonstrate that MALAT1 sponged miR-330-3p in GC, leading to VEGFA upregulation and activation of the mTOR signaling pathway. The MALAT1/miR-330-3p axis regulates VEGFA through the mTOR signaling pathway and promotes the growth and metastasis of gastric cancer.
Se descubrió que la sobreexpresión del transcrito 1 de adenocarcinoma de pulmón asociado a metástasis (MALAT1) en varios tejidos tumorales y líneas celulares promueve la proliferación, migración e invasión de células tumorales. Sin embargo, el papel de MALAT1 en el cáncer gástrico (CG) aún no está claro. Nuestro objetivo fue investigar la correlación entre los ARN no codificantes de cadena larga (lncRNA), MALAT1, los microARN (miARN) y el factor de crecimiento endotelial vascular A (VEGFA) en el cáncer gástrico y revelar el mecanismo subyacente. La correlación entre los niveles de MALAT1 y las características clínicas se analizó mediante datos bioinformáticos y muestras humanas. La expresión de MALAT1 se reguló negativamente en las células AGS para detectar las características de proliferación, migración e invasión celular, así como los efectos sobre las vías de señales. Además, validamos el papel del eje MALAT1/miR- 330-3p en GC mediante ensayos de genes indicadores de luciferasa dual. La expresión de MALAT1 fue mayor en tejidos cancerosos que en tejidos paracancerosos. El alto nivel de MALAT1 predijo malignidad y peor pronóstico. La regulación negativa de la expresión de MALAT1 en células AGS inhibió la proliferación, migración e invasión celular al apuntar a VEGFA. Mediante un ensayo de gen indicador de luciferasa dual y un tratamiento con inhibidor de miR-330-3p, demostramos que MALAT1 esponjaba miR-330-3p en GC, lo que lleva a la regulación positiva de VEGFA y la activación de la vía de señalización mTOR. El eje MALAT1/miR-330-3p regula VEGFA a través de la vía de señalización mTOR y promueve el crecimiento y la metástasis del cáncer gástrico.
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Humanos , Neoplasias Gástricas/genética , Neoplasias Gástricas/patologia , Fator A de Crescimento do Endotélio Vascular , Serina-Treonina Quinases TOR , RNA Longo não Codificante , RNA/genética , Transdução de Sinais , Regulação Neoplásica da Expressão Gênica , Movimento Celular , Western Blotting , Apoptose , Genes Reporter , Proliferação de Células , Reação em Cadeia da Polimerase em Tempo Real , Invasividade NeoplásicaRESUMO
Circular RNAs (circRNAs) are noncoding singlestranded covalently closed RNA molecules that are considered important as regulators of gene expression at the transcriptional and posttranscriptional levels. These molecules have been implicated in the initiation and progression of multiple human diseases, ranging from cancer to inflammatory and metabolic diseases, including diabetes mellitus and its vascular complications. The present article aimed to review the current knowledge on the biogenesis and functions of circRNAs, as well as their role in cell processes associated with diabetic nephropathy. In addition, novel potential interactions between circRNAs expressed in renal cells exposed to highglucose concentrations and the transcription factors cJun and cFos are reported.
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Diabetes Mellitus , Nefropatias Diabéticas , Neoplasias , Humanos , RNA Circular/genética , RNA Circular/metabolismo , Nefropatias Diabéticas/genética , RNA/genética , Neoplasias/genética , Regulação da Expressão GênicaRESUMO
A subset of circular RNAs (circRNAs) and linear RNAs have been proposed to 'sponge' or block microRNA activity. Additionally, certain RNAs induce microRNA destruction through the process of Target RNA-Directed MicroRNA Degradation (TDMD), but whether both linear and circular transcripts are equivalent in driving TDMD is unknown. Here, we studied whether circular/linear topology of endogenous and artificial RNA targets affects TDMD. Consistent with previous knowledge that Cdr1as (ciRS-7) circular RNA protects miR-7 from Cyrano-mediated TDMD, we demonstrate that depletion of Cdr1as reduces miR-7 abundance. In contrast, overexpression of an artificial linear version of Cdr1as drives miR-7 degradation. Using plasmids that express a circRNA with minimal co-expressed cognate linear RNA, we show differential effects on TDMD that cannot be attributed to the nucleotide sequence, as the TDMD properties of a sequence often differ when in a circular versus linear form. By analysing RNA sequencing data of a neuron differentiation system, we further detect potential effects of circRNAs on microRNA stability. Our results support the view that RNA circularity influences TDMD, either enhancing or inhibiting it on specific microRNAs.
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MicroRNAs , Estabilidade de RNA , RNA Circular , MicroRNAs/genética , MicroRNAs/metabolismo , RNA/genética , RNA/metabolismo , RNA Circular/metabolismo , Humanos , Animais , CamundongosRESUMO
Molecular dynamics simulations have proved extremely useful in investigating the functioning of proteins with atomic-scale resolution. Many applications to the study of RNA also exist, and their number increases by the day. However, implementing MD simulations for RNA molecules in solution faces challenges that the MD practitioner must be aware of for the appropriate use of this tool. In this chapter, we present the fundamentals of MD simulations, in general, and the peculiarities of RNA simulations, in particular. We discuss the strengths and limitations of the technique and provide examples of its application to elucidate small RNA's performance.
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Simulação de Dinâmica Molecular , Proteínas , RNA Mensageiro , Proteínas/metabolismo , RNA/genética , Conformação ProteicaRESUMO
High-throughput sequencing has had an enormous impact on small RNA research during the past decade. However, sequencing only offers a one-dimensional view of the transcriptome and is often highly biased. Additionally, the 'sequence, map and annotate' approach, used widely in small RNA research, can lead to flawed interpretations of the data, lacking biological plausibility, due in part to database issues. Even in the absence of technical biases, the loss of three-dimensional information is a major limitation to understanding RNA stability, turnover and function. For example, noncoding RNA-derived fragments seem to exist mainly as dimers, tetramers or as nicked forms of their parental RNAs, contrary to widespread assumptions. In this perspective, we will discuss main sources of bias during small RNA-sequencing, present several useful bias-reducing strategies and provide guidance on the interpretation of small RNA-sequencing results, with emphasis on RNA fragmentomics. As sequencing offers a one-dimensional projection of a four-dimensional reality, prior structure-level knowledge is often needed to make sense of the data. Consequently, while less-biased sequencing methods are welcomed, integration of orthologous experimental techniques is also strongly recommended.
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RNA não Traduzido , RNA , RNA/genética , RNA/química , RNA não Traduzido/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Sequência de RNA/métodos , TranscriptomaRESUMO
It is widely accepted that the earliest RNA molecules were folded into hairpins or mini-helixes. Herein, we depict the 2D and 3D conformations of those earliest RNA molecules with only RNY triplets, which Eigen proposed as the primeval genetic code. We selected 26 species (13 bacteria and 13 archaea). We found that the free energy of RNY hairpins was consistently lower than that of their corresponding shuffled controls. We found traces of the three ribosomal RNAs (16S, 23S, and 5S), tRNAs, 6S RNA, and the RNA moieties of RNase P and the signal recognition particle. Nevertheless, at this stage of evolution there was no genetic code (as seen in the absence of the peptidyl transferase centre and any vestiges of the anti-Shine-Dalgarno sequence). Interestingly, we detected the anticodons of both glycine (GCC) and threonine (GGU) in the hairpins of proto-tRNA.
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Evolução Molecular , Código Genético , RNA de Transferência/genética , RNA/genética , Bactérias/genéticaRESUMO
Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.