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The role of functional data in interpreting the effects of genetic variation

Progress in DNA-sequencing technologies has provided a catalogue of millions of DNA variants in the human population, but characterization of the functional effects of these variants has lagged far behind. For example, sequencing of tumor samples is driving an urgent need to classify whether or not...

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Detalles Bibliográficos
Autores principales: Young, David L., Fields, Stanley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710221/
https://www.ncbi.nlm.nih.gov/pubmed/26543197
http://dx.doi.org/10.1091/mbc.E15-03-0153
Descripción
Sumario:Progress in DNA-sequencing technologies has provided a catalogue of millions of DNA variants in the human population, but characterization of the functional effects of these variants has lagged far behind. For example, sequencing of tumor samples is driving an urgent need to classify whether or not mutations seen in cancers affect disease progression or treatment effectiveness or instead are benign. Furthermore, mutations can interact with genetic background and with environmental effects. A new approach, termed deep mutational scanning, has enabled the quantitative assessment of the effects of thousands of mutations in a protein. However, this type of experiment is carried out in model organisms, tissue culture, or in vitro; typically addresses only a single biochemical function of a protein; and is generally performed under a single condition. The current challenge lies in using these functional data to generate useful models for the phenotypic consequences of genetic variation in humans.