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1.
RNA ; 29(5): 705-712, 2023 05.
Artigo em Inglês | MEDLINE | ID: mdl-36759126

RESUMO

N6-methyladenosine (m6A) is a widely studied and abundant RNA modification. The m6A mark regulates the fate of RNAs in various ways, which in turn drives changes in cell physiology, development, and disease pathology. Over the last decade, numerous methods have been developed to map and quantify m6A sites genome-wide through deep sequencing. Alternatively, m6A levels can be quantified from a population of RNAs using techniques such as liquid chromatography-mass spectrometry or thin layer chromatography. However, many methods for quantifying m6A levels involve extensive protocols and specialized data analysis, and often only a few samples can be handled in a single experiment. Here, we developed a simple method for determining relative m6A levels in mRNA populations from various sources based on an enzyme-linked immunosorbent-based assay (m6A-ELISA). We have optimized various steps of m6A-ELISA, such as sample preparation and the background signal resulting from the primary antibody. We validated the method using mRNA populations from budding yeast and mouse embryonic stem cells. The full protocol takes less than a day, requiring only 25 ng of mRNA. The m6A-ELISA protocol is quick, cost-effective, and scalable, making it a valuable tool for determining relative m6A levels in samples from various sources that could be adapted to detect other mRNA modifications.


Assuntos
Anticorpos , RNA , Animais , Camundongos , RNA Mensageiro/genética , RNA/genética , Ensaio de Imunoadsorção Enzimática
2.
Nat Commun ; 12(1): 7198, 2021 12 10.
Artigo em Inglês | MEDLINE | ID: mdl-34893601

RESUMO

RNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. In recent years, a growing number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework that identifies modifications from these data. Our strategy compares an RNA sample of interest against a non-modified control sample, not requiring a training set and allowing the use of replicates. We show that Nanocompore can detect different RNA modifications with position accuracy in vitro, and we apply it to profile m6A in vivo in yeast and human RNAs, as well as in targeted non-coding RNAs. We confirm our results with orthogonal methods and provide novel insights on the co-occurrence of multiple modified residues on individual RNA molecules.


Assuntos
Sequenciamento por Nanoporos/métodos , Nanoporos , RNA/metabolismo , Análise de Sequência de RNA/métodos , Sequência de Bases , Biologia Computacional , Perfilação da Expressão Gênica , Técnicas Genéticas , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , RNA/isolamento & purificação , Processamento Pós-Transcricional do RNA , Software , Transcriptoma
3.
Front Genet ; 11: 398, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32508872

RESUMO

A flurry of methods has been developed in recent years to identify N6-methyladenosine (m6A) sites across transcriptomes at high resolution. This raises the need to understand both the common features and those that are unique to each method. Here, we complement the analyses presented in the original papers by reviewing their various technical aspects and comparing the overlap between m6A-methylated messenger RNAs (mRNAs) identified by each. Specifically, we examine eight different methods that identify m6A sites in human cells with high resolution: two antibody-based crosslinking and immunoprecipitation (CLIP) approaches, two using endoribonuclease MazF, one based on deamination, two using Nanopore direct RNA sequencing, and finally, one based on computational predictions. We contrast the respective datasets and discuss the challenges in interpreting the overlap between them, including a prominent expression bias in detected genes. This overview will help guide researchers in making informed choices about using the available data and assist with the design of future experiments to expand our understanding of m6A and its regulation.

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