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La variación reguladora genética en las poblaciones informa el análisis del transcriptoma en enfermedades raras

  • 0New York Genome Center, New York, NY, USA. pejman@scripps.edu tlappalainen@nygenome.org.
Clinical Neuroscience (new York, N.y.) +

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12 de octubre de 2019

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12 de octubre de 2019

Ver abstracta en PubMed

Resumen

Este resumen es generado por máquina.

Desarrollamos ANEVA para analizar la variación de la dosis genética a partir de datos de ARN, mejorando el diagnóstico de enfermedades raras. ANEVA-DOT detecta con precisión las variantes patógenas, ayudando en el diagnóstico de trastornos genéticos mediante la secuenciación del transcriptoma.

Área De La Ciencia

  • La genómica
  • La bioinformática
  • La genética humana

Sus Antecedentes

  • Los datos del transcriptoma ofrecen información sobre los efectos de las variantes genéticas raras.
  • Los datos de expresión alélica (AE) proporcionan una base para cuantificar la variación de la dosis génica.

Objetivo Del Estudio

  • Introducir el ANEVA (análisis de la variación de expresión) para cuantificar la variación genética en la dosis de genes a partir de los datos de AE de la población.
  • Desarrollar y validar ANEVA-DOT, una prueba de valores atípicos de dosificación utilizando datos de AE para el diagnóstico de enfermedades raras.

Principales Métodos

  • Se aplicó el ANEVA a los datos de expresión genotípica de los tejidos (GTEx) para estimar la variación de la dosis génica.
  • Utilizó ANEVA-DOT en datos de AE de 70 pacientes con enfermedad muscular mendeliana.
  • Estimaciones de varianza correlacionadas con restricción genética selectiva.

Principales Resultados

  • Las estimaciones de la varianza ANEVA son robustas y se correlacionan con la restricción genética selectiva.
  • ANEVA-DOT identificó con precisión las variantes patógenas en los casos de enfermedad muscular mendeliana.
  • Logrado un diagnóstico confirmado y varios nuevos diagnósticos potenciales en pacientes.

Conclusiones

  • ANEVA proporciona un método sólido para cuantificar la variación de la dosis de genes a partir de los datos de AE.
  • ANEVA-DOT detecta eficazmente las variantes patógenas, mejorando el diagnóstico de enfermedades raras.
  • La integración de ANEVA-DOT en las tuberías de diagnóstico puede mejorar la utilidad de los datos de secuenciación de ARN.

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