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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
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RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
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El uso de la inteligencia artificial para documentar la virusfera de ARN oculto

Xin Hou1, Yong He2, Pan Fang2

  • 1National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, State Key Laboratory for Biocontrol, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China.

Cell
|October 10, 2024
PubMed
Resumen
Este resumen es generado por máquina.

Una nueva herramienta de aprendizaje profundo, LucaProt, identifica virus de ARN altamente divergentes mediante el análisis de secuencias de ARN polimerasa dependientes de ARN. Este descubrimiento amplía nuestra comprensión de la virósfera global y la diversidad de virus en los ecosistemas.

Palabras clave:
El virus del ARNInteligencia artificialaprendizaje profundoLa evoluciónMetatranscriptomía y sus derivadosModelo de lenguaje de proteínasel viromaDescubrimiento de virus

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Área de la Ciencia:

  • Virología
  • La bioinformática
  • La genómica

Sus antecedentes:

  • Las herramientas metagenómicas a menudo no logran detectar virus de ARN altamente divergentes.
  • La ARN polimerasa dependiente del ARN (RdRP) es una enzima clave para la replicación del virus del ARN.

Objetivo del estudio:

  • Desarrollar una nueva herramienta computacional para descubrir secuencias de virus de ARN altamente divergentes.
  • Caracterizar la diversidad y distribución de nuevos virus de ARN en varios ecosistemas globales.

Principales métodos:

  • Desarrollo de LucaProt, un algoritmo de aprendizaje profundo que integra información secuencial y estructural.
  • Análisis de 10.487 metatranscriptomas de diversos entornos del mundo.
  • Validación de nuevas secuencias virales mediante RT-PCR y secuenciación de ARN/ADN.

Principales resultados:

  • Identificación de 161,979 especies potenciales de virus de ARN y 180 supergrupos de virus de ARN.
  • Descubrimiento de genomas de virus de ARN excepcionalmente largos (hasta 47.250 nucleótidos) y estructuras genómicas complejas.
  • Detección de nuevos virus de ARN en diversos entornos como el aire, las aguas termales y las fuentes hidrotermales.

Conclusiones:

  • LucaProt mejora significativamente el descubrimiento de virus de ARN divergentes.
  • El estudio revela la vasta escala de la virósfera global de ARN y su distribución ecológica.
  • Las herramientas computacionales son cruciales para la documentación completa del viroma de ARN global.