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Variación de la tasa y errores de secuencia recurrentes en filogenética a escala pandémica

Nicola De Maio1, Myrthe Willemsen2,3, Samuel Martin2

  • 1European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, UK. demaio@ebi.ac.uk.

Nature methods
|February 9, 2026
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio mejora la inferencia filogenética para millones de genomas de patógenos, mejorando la precisión al tener en cuenta la variación de la tasa de mutación y los errores de secuencia. Esto proporciona una historia evolutiva confiable para virus como el SARS-CoV-2.

Palabras clave:
filogenéticaSARS-CoV-2evolucióngenómicaCOVID-19árbol filogenéticoalineación de secuenciastasa de mutaciónerrores de secuenciahomoplasias

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Área de la Ciencia:

  • Genómica
  • Biología Evolutiva
  • Biología Computacional

Sus antecedentes:

  • Los análisis filogenéticos de genomas de patógenos son cruciales para comprender la evolución y la transmisión, especialmente durante pandemias como la COVID-19.
  • Los métodos recientes permiten la inferencia filogenética a escala pandémica, analizando millones de genomas.
  • Las homoplasias debidas a mutaciones recurrentes y errores introducen incertidumbre y sesgos en la reconstrucción filogenética.

Objetivo del estudio:

  • Desarrollar algoritmos y modelos que mejoren el rendimiento computacional y la precisión de la filogenética a escala pandémica.
  • Abordar los desafíos que plantean la variación de la tasa de mutación y los errores de secuencia recurrentes en grandes conjuntos de datos genómicos.

Principales métodos:

  • Desarrollo de algoritmos y modelos novedosos para la inferencia filogenética.
  • Incorporación de métodos para identificar y tener en cuenta la variación de la tasa de mutación.
  • Implementación de estrategias para detectar y corregir errores de secuencia recurrentes.

Principales resultados:

  • Se lograron mejoras sustanciales en el rendimiento computacional y la precisión de la filogenética a escala pandémica.
  • Se reconstruyó una alineación de secuencias y un árbol filogenético confiables y disponibles públicamente.
  • El análisis incluyó más de 2 millones de genomas de coronavirus 2 del síndrome respiratorio agudo severo (SARS-CoV-2).

Conclusiones:

  • Los métodos desarrollados proporcionan un enfoque más preciso y computacionalmente eficiente para la filogenética de datos genómicos a gran escala.
  • El árbol filogenético reconstruido ofrece información sobre la historia evolutiva y la propagación global del SARS-CoV-2 hasta febrero de 2023.
  • Este trabajo mejora nuestra capacidad para rastrear y comprender la evolución de los patógenos durante las crisis de salud mundiales.