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Resolving intra-repeat variation in medically relevant VNTRs from short-read sequencing data using the cardiovascular risk gene LPA as a model.
Di Maio, Silvia; Zöscher, Peter; Weissensteiner, Hansi; Forer, Lukas; Schachtl-Riess, Johanna F; Amstler, Stephan; Streiter, Gertraud; Pfurtscheller, Cathrin; Paulweber, Bernhard; Kronenberg, Florian; Coassin, Stefan; Schönherr, Sebastian.
Afiliación
  • Di Maio S; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Zöscher P; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Weissensteiner H; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Forer L; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Schachtl-Riess JF; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Amstler S; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Streiter G; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Pfurtscheller C; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Paulweber B; Department of Internal Medicine I, Paracelsus Medical University/Salzburger Landeskliniken, Salzburg, Austria.
  • Kronenberg F; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Coassin S; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  • Schönherr S; Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria. sebastian.schoenherr@i-med.ac.at.
Genome Biol ; 25(1): 167, 2024 06 26.
Article en En | MEDLINE | ID: mdl-38926899
ABSTRACT

BACKGROUND:

Variable number tandem repeats (VNTRs) are highly polymorphic DNA regions harboring many potentially disease-causing variants. However, VNTRs often appear unresolved ("dark") in variation databases due to their repetitive nature. One particularly complex and medically relevant VNTR is the KIV-2 VNTR located in the cardiovascular disease gene LPA which encompasses up to 70% of the coding sequence.

RESULTS:

Using the highly complex LPA gene as a model, we develop a computational approach to resolve intra-repeat variation in VNTRs from largely available short-read sequencing data. We apply the approach to six protein-coding VNTRs in 2504 samples from the 1000 Genomes Project and developed an optimized method for the LPA KIV-2 VNTR that discriminates the confounding KIV-2 subtypes upfront. This results in an F1-score improvement of up to 2.1-fold compared to previously published strategies. Finally, we analyze the LPA VNTR in > 199,000 UK Biobank samples, detecting > 700 KIV-2 mutations. This approach successfully reveals new strong Lp(a)-lowering effects for KIV-2 variants, with protective effect against coronary artery disease, and also validated previous findings based on tagging SNPs.

CONCLUSIONS:

Our approach paves the way for reliable variant detection in VNTRs at scale and we show that it is transferable to other dark regions, which will help unlock medical information hidden in VNTRs.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Repeticiones de Minisatélite Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2024 Tipo del documento: Article País de afiliación: Austria Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Repeticiones de Minisatélite Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2024 Tipo del documento: Article País de afiliación: Austria Pais de publicación: Reino Unido