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1.
BMC Bioinformatics ; 22(1): 428, 2021 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-34496744

RESUMO

BACKGROUND: RNA regulates a variety of biological functions by interacting with other molecules. The ligand often binds in the RNA pocket to trigger structural changes or functions. Thus, it is essential to explore and visualize the RNA pocket to elucidate the structural and recognition mechanism for the RNA-ligand complex formation. RESULTS: In this work, we developed one user-friendly bioinformatics tool, RPocket. This database provides geometrical size, centroid, shape, secondary structure element for RNA pocket, RNA-ligand interaction information, and functional sites. We extracted 240 RNA pockets from 94 non-redundant RNA-ligand complex structures. We developed RPDescriptor to calculate the pocket geometrical property quantitatively. The geometrical information was then subjected to RNA-ligand binding analysis by incorporating the sequence, secondary structure, and geometrical combinations. This new approach takes advantage of both the atom-level precision of the structure and the nucleotide-level tertiary interactions. The results show that the higher-level topological pattern indeed improves the tertiary structure prediction. We also proposed a potential mechanism for RNA-ligand complex formation. The electrostatic interactions are responsible for long-range recognition, while the Van der Waals and hydrophobic contacts for short-range binding and optimization. These interaction pairs can be considered as distance constraints to guide complex structural modeling and drug design. CONCLUSION: RPocket database would facilitate RNA-ligand engineering to regulate the complex formation for biological or medical applications. RPocket is available at http://zhaoserver.com.cn/RPocket/RPocket.html .


Assuntos
Biologia Computacional , RNA , Sítios de Ligação , Ligantes , Estrutura Secundária de Proteína , RNA/genética
2.
BMC Bioinformatics ; 22(Suppl 3): 431, 2021 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-34496763

RESUMO

BACKGROUND: RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods can not effectively apply protein sequence information with different sequence lengths to the prediction process due to the constraint of the self model when predicting the RNA secondary structure. In addition, there is a large difference between the number of paired bases and the number of unpaired bases in the RNA sequences, which means the problem of positive and negative sample imbalance is easy to make the model fall into a local optimum. To solve the above problems, this paper proposes a variable-length dynamic bidirectional Gated Recurrent Unit(VLDB GRU) model. The model can accept sequences with different lengths through the introduction of flag vector. The model can also make full use of the base information before and after the predicted base and can avoid losing part of the information due to truncation. Introducing a weight vector to predict the RNA training set by dynamically adjusting each base loss function solves the problem of balanced sample imbalance. RESULTS: The algorithm proposed in this paper is compared with the existing algorithms on five representative subsets of the data set RNA STRAND. The experimental results show that the accuracy and Matthews correlation coefficient of the method are improved by 4.7% and 11.4%, respectively. CONCLUSIONS: The flag vector introduced allows the model to effectively use the information before and after the protein sequence; the introduced weight vector solves the problem of unbalanced sample balance. Compared with other algorithms, the LVDB GRU algorithm proposed in this paper has the best detection results.


Assuntos
Redes Neurais de Computação , RNA , Algoritmos , Conformação de Ácido Nucleico , Estrutura Secundária de Proteína , RNA/genética
3.
Nanoscale ; 13(30): 12848-12853, 2021 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-34477769

RESUMO

Nucleic acid nanostructures are promising biomaterials for the delivery of homologous gene therapy drugs. Herein, we report a facile strategy for the construction of target mRNA (scaffold) and antisense (staple strands) co-assembled RNA/DNA hybrid "origami" for efficient gene therapy. In our design, the mRNA was folded into a chemically well-defined nanostructure through RNA-DNA hybridization with high yield. After the incorporation of an active cell-targeting aptamer, the tailored RNA/DNA hybrid origami demonstrated efficient cellular uptake and controllable release of antisenses in response to intracellular RNase H digestion. The biocompatible RNA/DNA origami (RDO) elicited a noticeable inhibition of cell proliferation based on the silencing of the tumor-associated gene polo-like kinase 1 (PLK1). This RDO-based nanoplatform provides a novel strategy for the further development of gene therapy.


Assuntos
Nanoestruturas , RNA , DNA/genética , Terapia Genética , Conformação de Ácido Nucleico , Hibridização de Ácido Nucleico , RNA/genética
4.
BMC Bioinformatics ; 22(Suppl 10): 419, 2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34479487

RESUMO

BACKGROUND: RNA velocity is a novel and powerful concept which enables the inference of dynamical cell state changes from seemingly static single-cell RNA sequencing (scRNA-seq) data. However, accurate estimation of RNA velocity is still a challenging problem, and the underlying kinetic mechanisms of transcriptional and splicing regulations are not fully clear. Moreover, scRNA-seq data tend to be sparse compared with possible cell states, and a given dataset of estimated RNA velocities needs imputation for some cell states not yet covered. RESULTS: We formulate RNA velocity prediction as a supervised learning problem of classification for the first time, where a cell state space is divided into equal-sized segments by directions as classes, and the estimated RNA velocity vectors are considered as ground truth. We propose Velo-Predictor, an ensemble learning pipeline for predicting RNA velocities from scRNA-seq data. We test different models on two real datasets, Velo-Predictor exhibits good performance, especially when XGBoost was used as the base predictor. Parameter analysis and visualization also show that the method is robust and able to make biologically meaningful predictions. CONCLUSION: The accurate result shows that Velo-Predictor can effectively simplify the procedure by learning a predictive model from gene expression data, which could help to construct a continous landscape and give biologists an intuitive picture about the trend of cellular dynamics.


Assuntos
RNA , Análise de Célula Única , Perfilação da Expressão Gênica , Aprendizado de Máquina , RNA/genética , Análise de Sequência de RNA , Sequenciamento Completo do Exoma
5.
Molecules ; 26(15)2021 Jul 22.
Artigo em Inglês | MEDLINE | ID: mdl-34361572

RESUMO

RNA molecules participate in many important biological processes, and they need to fold into well-defined secondary and tertiary structures to realize their functions. Like the well-known protein folding problem, there is also an RNA folding problem. The folding problem includes two aspects: structure prediction and folding mechanism. Although the former has been widely studied, the latter is still not well understood. Here we present a deep reinforcement learning algorithms 2dRNA-Fold to study the fastest folding paths of RNA secondary structure. 2dRNA-Fold uses a neural network combined with Monte Carlo tree search to select residue pairing step by step according to a given RNA sequence until the final secondary structure is formed. We apply 2dRNA-Fold to several short RNA molecules and one longer RNA 1Y26 and find that their fastest folding paths show some interesting features. 2dRNA-Fold is further trained using a set of RNA molecules from the dataset bpRNA and is used to predict RNA secondary structure. Since in 2dRNA-Fold the scoring to determine next step is based on possible base pairings, the learned or predicted fastest folding path may not agree with the actual folding paths determined by free energy according to physical laws.


Assuntos
Aprendizado de Máquina , Modelos Moleculares , Dobramento de RNA , RNA , Software , RNA/química , RNA/genética
6.
Int J Mol Sci ; 22(16)2021 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-34445123

RESUMO

Atherosclerosis represents one of the major causes of death globally. The high mortality rates and limitations of current therapeutic modalities have urged researchers to explore potential alternative therapies. The clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR/Cas9) system is commonly deployed for investigating the genetic aspects of Atherosclerosis. Besides, advances in CRISPR/Cas system has led to extensive options for researchers to study the pathogenesis of this disease. The recent discovery of Cas9 variants, such as dCas9, Cas9n, and xCas9 have been established for various applications, including single base editing, regulation of gene expression, live-cell imaging, epigenetic modification, and genome landscaping. Meanwhile, other Cas proteins, such as Cas12 and Cas13, are gaining popularity for their applications in nucleic acid detection and single-base DNA/RNA modifications. To date, many studies have utilized the CRISPR/Cas9 system to generate disease models of atherosclerosis and identify potential molecular targets that are associated with atherosclerosis. These studies provided proof-of-concept evidence which have established the feasibility of implementing the CRISPR/Cas system in correcting disease-causing alleles. The CRISPR/Cas system holds great potential to be developed as a targeted treatment for patients who are suffering from atherosclerosis. This review highlights the advances in CRISPR/Cas systems and their applications in establishing pathogenetic and therapeutic role of specific genes in atherosclerosis.


Assuntos
Aterosclerose/genética , Sistemas CRISPR-Cas/genética , Animais , DNA/genética , Epigênese Genética/genética , Edição de Genes/métodos , Expressão Gênica/genética , Genoma/genética , Humanos , RNA/genética , RNA Guia/genética
7.
Int J Mol Sci ; 22(16)2021 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-34445259

RESUMO

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.


Assuntos
Algoritmos , Bases de Dados de Ácidos Nucleicos , Anotação de Sequência Molecular , Motivos de Nucleotídeos , RNA/química , Software , RNA/genética , Fluxo de Trabalho
8.
Int J Mol Sci ; 22(16)2021 Aug 23.
Artigo em Inglês | MEDLINE | ID: mdl-34445809

RESUMO

A universal feature of retroelement propagation is the formation of distinct nucleoprotein complexes mediated by the Gag capsid protein. The Ty1 retrotransposon Gag protein from Saccharomyces cerevisiae lacks sequence homology with retroviral Gag, but is functionally related. In addition to capsid assembly functions, Ty1 Gag promotes Ty1 RNA dimerization and cyclization and initiation of reverse transcription. Direct interactions between Gag and retrotransposon genomic RNA (gRNA) are needed for Ty1 replication, and mutations in the RNA-binding domain disrupt nucleation of retrosomes and assembly of functional virus-like particles (VLPs). Unlike retroviral Gag, the specificity of Ty1 Gag-RNA interactions remain poorly understood. Here we use microscale thermophoresis (MST) and electrophoretic mobility shift assays (EMSA) to analyze interactions of immature and mature Ty1 Gag with RNAs. The salt-dependent experiments showed that Ty1 Gag binds with high and similar affinity to different RNAs. However, we observed a preferential interaction between Ty1 Gag and Ty1 RNA containing a packaging signal (Psi) in RNA competition analyses. We also uncover a relationship between Ty1 RNA structure and Gag binding involving the pseudoknot present on Ty1 gRNA. In all likelihood, the differences in Gag binding affinity detected in vitro only partially explain selective Ty1 RNA packaging into VLPs in vivo.


Assuntos
Produtos do Gene gag/genética , Ligação Proteica/genética , RNA/genética , Retroelementos/genética , Dimerização , Retroviridae/genética , Saccharomyces cerevisiae/genética
9.
Nat Commun ; 12(1): 5152, 2021 08 26.
Artigo em Inglês | MEDLINE | ID: mdl-34446707

RESUMO

The immunological features that distinguish COVID-19-associated acute respiratory distress syndrome (ARDS) from other causes of ARDS are incompletely understood. Here, we report the results of comparative lower respiratory tract transcriptional profiling of tracheal aspirate from 52 critically ill patients with ARDS from COVID-19 or from other etiologies, as well as controls without ARDS. In contrast to a "cytokine storm," we observe reduced proinflammatory gene expression in COVID-19 ARDS when compared to ARDS due to other causes. COVID-19 ARDS is characterized by a dysregulated host response with increased PTEN signaling and elevated expression of genes with non-canonical roles in inflammation and immunity. In silico analysis of gene expression identifies several candidate drugs that may modulate gene expression in COVID-19 ARDS, including dexamethasone and granulocyte colony stimulating factor. Compared to ARDS due to other types of viral pneumonia, COVID-19 is characterized by impaired interferon-stimulated gene (ISG) expression. The relationship between SARS-CoV-2 viral load and expression of ISGs is decoupled in patients with COVID-19 ARDS when compared to patients with mild COVID-19. In summary, assessment of host gene expression in the lower airways of patients reveals distinct immunological features of COVID-19 ARDS.


Assuntos
COVID-19/genética , RNA/genética , Síndrome do Desconforto Respiratório/genética , Traqueia/imunologia , Adulto , Idoso , Idoso de 80 Anos ou mais , COVID-19/imunologia , COVID-19/virologia , Estudos de Casos e Controles , Estudos de Coortes , Estado Terminal , Citocinas/genética , Citocinas/imunologia , Feminino , Perfilação da Expressão Gênica , Humanos , Masculino , Pessoa de Meia-Idade , RNA/metabolismo , Síndrome do Desconforto Respiratório/imunologia , Síndrome do Desconforto Respiratório/virologia , SARS-CoV-2/fisiologia , Análise de Sequência de RNA
10.
Medicine (Baltimore) ; 100(29): e26648, 2021 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-34398021

RESUMO

BACKGROUND: Endometrial carcinoma (EC) has become a common gynecologic malignancy with a high mortality. The m6A regulators have been identified to be closely associated with multiple human cancers including EC. However, the CpG methylation signature related to m6A regulators in EC remains unclear. METHOD: The methylation profiles of EC patients including cancer samples and adjacent normal samples were obtained from The Cancer Genome Atlas (TCGA) database. The CpG sites in 20 m6A regulators were identified. Univariate Cox regression and LASSO Cox regression analysis were used to screen key CpG sites which were located at m6A regulators and significantly related to the prognosis of EC. The predictive model for EC prognosis was constructed, and multivariate Cox regression analysis was applied to explore whether the risk score derived from the model could function as an independent signature for EC prognosis. Meanwhile, a nomogram model was constructed by combing the independent prognostic signatures for prediction of the long-term survival in EC patients. RESULTS: A total of 396 CpG sites located at 20 m6A regulators were identified. A specific predictive model for EC prognosis based on 7 optimal CpG sites was constructed, which presented good performance in prognosis prediction of EC patients. Moreover, risk score was determined to be an independent signature both in the training set and validation set. By bringing in three independent prognostic factors (age, risk score, and TNM stage), the nomogram was constructed and could effectively predict the 3- and 5-year survival rates of EC patients. CONCLUSION: Our study suggested that the CpG sites located at m6A regulators might be considered as potential prognostic signatures for EC patients.


Assuntos
Adenosina/análogos & derivados , Neoplasias do Endométrio/mortalidade , Adenosina/genética , Adenosina/metabolismo , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , China , Neoplasias do Endométrio/genética , Neoplasias do Endométrio/metabolismo , Feminino , Regulação Neoplásica da Expressão Gênica , Humanos , Metilação , Pessoa de Meia-Idade , Nomogramas , Valor Preditivo dos Testes , Prognóstico , Modelos de Riscos Proporcionais , RNA/genética , Análise de Sobrevida
11.
Nat Commun ; 12(1): 5113, 2021 08 25.
Artigo em Inglês | MEDLINE | ID: mdl-34433821

RESUMO

SARS-CoV-2 is a major threat to global health. Here, we investigate the RNA structure and RNA-RNA interactions of wildtype (WT) and a mutant (Δ382) SARS-CoV-2 in cells using Illumina and Nanopore platforms. We identify twelve potentially functional structural elements within the SARS-CoV-2 genome, observe that subgenomic RNAs can form different structures, and that WT and Δ382 virus genomes fold differently. Proximity ligation sequencing identify hundreds of RNA-RNA interactions within the virus genome and between the virus and host RNAs. SARS-CoV-2 genome binds strongly to mitochondrial and small nucleolar RNAs and is extensively 2'-O-methylated. 2'-O-methylation sites are enriched in viral untranslated regions, associated with increased virus pair-wise interactions, and are decreased in host mRNAs upon virus infection, suggesting that the virus sequesters methylation machinery from host RNAs towards its genome. These studies deepen our understanding of the molecular and cellular basis of SARS-CoV-2 pathogenicity and provide a platform for targeted therapy.


Assuntos
COVID-19/virologia , Interações entre Hospedeiro e Microrganismos , RNA Viral/metabolismo , RNA/metabolismo , SARS-CoV-2/fisiologia , COVID-19/genética , COVID-19/metabolismo , COVID-19/fisiopatologia , Metilação de DNA , Genoma Viral , Humanos , Conformação de Ácido Nucleico , RNA/química , RNA/genética , RNA Viral/química , RNA Viral/genética , SARS-CoV-2/química , SARS-CoV-2/genética
12.
Nat Commun ; 12(1): 4934, 2021 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-34400638

RESUMO

Rhodopsin (RHO) gene mutations are a common cause of autosomal dominant retinitis pigmentosa (ADRP). The need to suppress toxic protein expression together with mutational heterogeneity pose challenges for treatment development. Mirtrons are atypical RNA interference effectors that are spliced from transcripts as short introns. Here, we develop a novel mirtron-based knockdown/replacement gene therapy for the mutation-independent treatment of RHO-related ADRP, and demonstrate efficacy in a relevant mammalian model. Splicing and potency of rhodopsin-targeting candidate mirtrons are initially determined, and a mirtron-resistant codon-modified version of the rhodopsin coding sequence is validated in vitro. These elements are then combined within a single adeno-associated virus (AAV) and delivered subretinally in a RhoP23H knock-in mouse model of ADRP. This results in significant mouse-to-human rhodopsin RNA replacement and is associated with a slowing of retinal degeneration. This provides proof of principle that synthetic mirtrons delivered by AAV are capable of reducing disease severity in vivo.


Assuntos
Terapia Genética , RNA/genética , Retinite Pigmentosa/genética , Retinite Pigmentosa/terapia , Animais , Dependovirus/genética , Modelos Animais de Doenças , Técnicas de Silenciamento de Genes , Vetores Genéticos , Células HEK293 , Humanos , Camundongos , MicroRNAs/genética , MicroRNAs/metabolismo , RNA/metabolismo , Interferência de RNA , Splicing de RNA , Retina , Degeneração Retiniana , Rodopsina/genética , Rodopsina/metabolismo
13.
PLoS One ; 16(8): e0255690, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34351984

RESUMO

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against nasopharyngeal swab specimens and found saliva methods require further optimization to match this gold standard. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.


Assuntos
Teste para COVID-19/métodos , RNA Viral/isolamento & purificação , SARS-CoV-2/genética , Adulto , COVID-19/diagnóstico , Feminino , Humanos , Masculino , Programas de Rastreamento/métodos , RNA/genética , RNA/isolamento & purificação , RNA Viral/genética , Reação em Cadeia da Polimerase em Tempo Real/métodos , Robótica/métodos , Saliva/química , Manejo de Espécimes/métodos
14.
World J Surg Oncol ; 19(1): 241, 2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34389000

RESUMO

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m6A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m6A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear. CASE PRESENTATION: The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy. CONCLUSION: SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Adenosina/análogos & derivados , Biomarcadores Tumorais/genética , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/terapia , Células Endoteliais , Regulação Neoplásica da Expressão Gênica , Humanos , Imunoterapia , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/terapia , Metilação , Prognóstico , RNA/genética , Microambiente Tumoral
15.
Nat Commun ; 12(1): 4908, 2021 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-34389711

RESUMO

C9ORF72 hexanucleotide GGGGCC repeat expansion is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Repeat-containing RNA mediates toxicity through nuclear granules and dipeptide repeat (DPR) proteins produced by repeat-associated non-AUG translation. However, it remains unclear how the intron-localized repeats are exported and translated in the cytoplasm. We use single molecule imaging approach to examine the molecular identity and spatiotemporal dynamics of the repeat RNA. We demonstrate that the spliced intron with G-rich repeats is stabilized in a circular form due to defective lariat debranching. The spliced circular intron, instead of pre-mRNA, serves as the translation template. The NXF1-NXT1 pathway plays an important role in the nuclear export of the circular intron and modulates toxic DPR production. This study reveals an uncharacterized disease-causing RNA species mediated by repeat expansion and demonstrates the importance of RNA spatial localization to understand disease etiology.


Assuntos
Proteína C9orf72/genética , Núcleo Celular/metabolismo , Íntrons/genética , Biossíntese de Proteínas/genética , RNA/genética , Transporte Ativo do Núcleo Celular/genética , Esclerose Amiotrófica Lateral/genética , Esclerose Amiotrófica Lateral/metabolismo , Proteína C9orf72/metabolismo , Linhagem Celular Tumoral , Núcleo Celular/genética , Expansão das Repetições de DNA/genética , Dipeptídeos/genética , Dipeptídeos/metabolismo , Demência Frontotemporal/genética , Demência Frontotemporal/metabolismo , Predisposição Genética para Doença/genética , Células HEK293 , Humanos , Microscopia de Fluorescência , Proteínas de Transporte Nucleocitoplasmático/genética , Proteínas de Transporte Nucleocitoplasmático/metabolismo , RNA/metabolismo , Proteínas de Ligação a RNA/genética , Proteínas de Ligação a RNA/metabolismo , Reação em Cadeia da Polimerase Via Transcriptase Reversa , Transdução de Sinais/genética
16.
Mol Cell ; 81(16): 3368-3385.e9, 2021 08 19.
Artigo em Inglês | MEDLINE | ID: mdl-34375583

RESUMO

The mechanistic understanding of nascent RNAs in transcriptional control remains limited. Here, by a high sensitivity method methylation-inscribed nascent transcripts sequencing (MINT-seq), we characterized the landscapes of N6-methyladenosine (m6A) on nascent RNAs. We uncover heavy but selective m6A deposition on nascent RNAs produced by transcription regulatory elements, including promoter upstream antisense RNAs and enhancer RNAs (eRNAs), which positively correlates with their length, inclusion of m6A motif, and RNA abundances. m6A-eRNAs mark highly active enhancers, where they recruit nuclear m6A reader YTHDC1 to phase separate into liquid-like condensates, in a manner dependent on its C terminus intrinsically disordered region and arginine residues. The m6A-eRNA/YTHDC1 condensate co-mixes with and facilitates the formation of BRD4 coactivator condensate. Consequently, YTHDC1 depletion diminished BRD4 condensate and its recruitment to enhancers, resulting in inhibited enhancer and gene activation. We propose that chemical modifications of eRNAs together with reader proteins play broad roles in enhancer activation and gene transcriptional control.


Assuntos
Adenosina/análogos & derivados , Proteínas de Ciclo Celular/genética , Proteínas do Tecido Nervoso/genética , Fatores de Processamento de RNA/genética , RNA/genética , Fatores de Transcrição/genética , Adenosina/genética , Elementos Facilitadores Genéticos/genética , Regulação da Expressão Gênica/genética , Humanos , Metilação , Elementos Reguladores de Transcrição/genética , Ativação Transcricional/genética
17.
Methods Mol Biol ; 2351: 25-39, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34382182

RESUMO

Post-transcriptional processing strongly affects the stability and the relative quantification of RNA molecules, so that steady-state levels of mature RNA, such as mRNAs, rarely reflect accurately the rate of in situ transcription in nuclei by RNA polymerases (RNAPs). The "Global Run-on Sequencing (GRO-Seq)" method, developed in 2008, combines the nuclear run-on assay with next-generation deep sequencing to detect nascent RNA levels to annotate the positions, the relative levels and the orientation of transcriptionally engaged RNA polymerase II (RNAPII) molecules genome-wide. Thus, GRO-Seq is a powerful method to infer mechanistic insights into the multiple levels of transcriptional regulation such as promoter-proximal pausing of RNAP, bidirectional transcription, and enhancer activity. Here, we describe a protocol for mammalian cells that can reliably detect low abundant nascent RNA from both coding and noncoding genomic regions. This protocol can easily be adapted for most mammalian cells to define the transcriptionally active regions of the genome and to measure dynamic transcriptional responses with high sensitivity upon external stimuli.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , RNA Polimerase II/metabolismo , Análise de Sequência de RNA/métodos , Transcrição Genética , Elementos Facilitadores Genéticos , Reação em Cadeia da Polimerase , Regiões Promotoras Genéticas , Controle de Qualidade , RNA/genética , RNA/isolamento & purificação , RNA não Traduzido/genética
18.
BMC Bioinformatics ; 22(Suppl 9): 281, 2021 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-34433409

RESUMO

BACKGROUND: It is important to understand the composition of cell type and its proportion in intact tissues, as changes in certain cell types are the underlying cause of disease in humans. Although compositions of cell type and ratios can be obtained by single-cell sequencing, single-cell sequencing is currently expensive and cannot be applied in clinical studies involving a large number of subjects. Therefore, it is useful to apply the bulk RNA-Seq dataset and the single-cell RNA dataset to deconvolute and obtain the cell type composition in the tissue. RESULTS: By analyzing the existing cell population prediction methods, we found that most of the existing methods need the cell-type-specific gene expression profile as the input of the signature matrix. However, in real applications, it is not always possible to find an available signature matrix. To solve this problem, we proposed a novel method, named DCap, to predict cell abundance. DCap is a deconvolution method based on non-negative least squares. DCap considers the weight resulting from measurement noise of bulk RNA-seq and calculation error of single-cell RNA-seq data, during the calculation process of non-negative least squares and performs the weighted iterative calculation based on least squares. By weighting the bulk tissue gene expression matrix and single-cell gene expression matrix, DCap minimizes the measurement error of bulk RNA-Seq and also reduces errors resulting from differences in the number of expressed genes in the same type of cells in different samples. Evaluation test shows that DCap performs better in cell type abundance prediction than existing methods. CONCLUSION: DCap solves the deconvolution problem using weighted non-negative least squares to predict cell type abundance in tissues. DCap has better prediction results and does not need to prepare a signature matrix that gives the cell-type-specific gene expression profile in advance. By using DCap, we can better study the changes in cell proportion in diseased tissues and provide more information on the follow-up treatment of diseases.


Assuntos
Perfilação da Expressão Gênica , RNA , Humanos , RNA/genética , RNA-Seq , Análise de Sequência de RNA , Sequenciamento Completo do Exoma
19.
Mo Med ; 118(4): 340-345, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34373669

RESUMO

Most neurodegenerative disorders afflict the ageing population and are often incurable. Therefore, therapeutic development is a major focus in biomedical research. We highlight a new class of drugs, RNA molecules, to control gene expression and decrease neurotoxicity. Their efficacy is shown in pre-clinical studies, clinical trials and in cases of approved patient treatment. As the number of RNA-based strategies increases, so does the promise of targeting more disease-associated genes through a variety of different mechanisms.


Assuntos
Doenças Neurodegenerativas , Humanos , Doenças Neurodegenerativas/genética , Doenças Neurodegenerativas/terapia , RNA/genética
20.
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