Determining the impact of putative loss-of-function variants in protein-coding genes

Autor: Mike Jin, Suganthi Balasubramanian, Mark Gerstein, Konrad J. Karczewski, Yao Fu, Jeremy Liu, Daniel G. MacArthur, Patrick McGillivray, Mayur Pawashe
Jazyk: angličtina
Rok vydání: 2017
Předmět:
DOI: 10.1101/106468
Popis: Variants predicted to result in the loss of function (LoF) of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (Annotation of Loss-of-Function Transcripts), a method to annotate and predict the disease-causing potential of LoF variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between LoF variants deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo pLoF variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in > 6,500 cancer exomes shows that pLoF variants predicted to be deleterious by ALoFT are enriched in known driver genes.
Databáze: OpenAIRE