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RNA-seq03:21

RNA-seq

12.1K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
12.1K
Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

1.4K
Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
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RNA Interference01:23

RNA Interference

28.1K
RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
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RNA Structure01:23

RNA Structure

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Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
79.2K
RNA Stability01:53

RNA Stability

35.8K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
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RNA Splicing01:32

RNA Splicing

60.7K
Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
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Video Experimental Relacionado

Updated: Feb 7, 2026

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq
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Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq

Published on: July 10, 2019

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Evaluación comparativa de herramientas de RNA-seq para aplicaciones de diagnóstico del mundo real

Sarah Silverstein, Kaushik Ganapathy, Sandra Donkervoort

    Research square
    |February 6, 2026
    PubMed
    Resumen

    Las herramientas de secuenciación de ARN (RNA-seq) ayudan en el diagnóstico de enfermedades neuromusculares pediátricas raras mediante el análisis de empalmes aberrantes y la expresión génica. Si bien son valiosas, estas herramientas computacionales complementan, en lugar de reemplazar, el análisis tradicional de secuenciación de ADN para diagnósticos definitivos.

    Palabras clave:
    secuenciación de ARNdiagnóstico genéticoenfermedades neuromusculares pediátricasanálisis computacionalinterpretación de variantes

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    Área de la Ciencia:

    • Genómica
    • Biología Computacional
    • Neurología Pediátrica

    Sus antecedentes:

    • Las enfermedades neuromusculares pediátricas exhiben una diversidad genética y clínica significativa.
    • Muchos casos permanecen sin diagnosticar a pesar de las pruebas moleculares avanzadas.
    • La secuenciación de ARN (RNA-seq) ofrece el potencial de descubrir los impactos funcionales de las variantes genéticas, pero su análisis sistemático está en evolución.

    Objetivo del estudio:

    • Evaluar el rendimiento de las herramientas computacionales de código abierto para el análisis de datos de RNA-seq en el diagnóstico de enfermedades neuromusculares pediátricas.
    • Establecer las mejores prácticas para la utilización de herramientas de análisis de RNA-seq en un entorno de diagnóstico clínico.
    • Identificar nuevos candidatos diagnósticos en casos previamente no diagnosticados.

    Principales métodos:

    • Evaluación comparativa de ocho herramientas de análisis de RNA-seq (empalme, expresión, desequilibrio alélico) utilizando 97 muestras diagnosticadas.
    • Desarrollo de un conjunto de verdad para categorizar variantes patógenas basadas en efectos transcriptómicos.
    • Aplicación de estrategias optimizadas de análisis de RNA-seq a 74 muestras de pacientes no diagnosticados.

    Principales resultados:

    • Las herramientas computacionales identificaron 28 diagnósticos en 68 probandos previamente diagnosticados con eventos de ARN aberrantes.
    • Las herramientas de análisis de empalmes fueron las que más contribuyeron, mientras que las herramientas de desequilibrio alélico proporcionaron diagnósticos únicos.
    • Las tasas de falsos positivos variaron, siendo más altas para el análisis de empalmes y más bajas para las herramientas de análisis de expresión.

    Conclusiones:

    • Las herramientas de análisis de RNA-seq pueden acelerar la interpretación de variantes en el diagnóstico genético de enfermedades neuromusculares pediátricas.
    • Estas herramientas sirven como un complemento valioso, no como un reemplazo, del análisis manual de datos de secuenciación de ADN.
    • Se necesita un mayor refinamiento de las estrategias de análisis de RNA-seq para maximizar el rendimiento diagnóstico.