Poster Presentation The 43rd Lorne Conference on Protein Structure and Function 2018

Predicting missense variant consequences using an integrated genomics and structural biology approach (#231)

Michael Silk 1
  1. University of Melbourne, Parkville, VICTORIA, Australia

Over the past decade, gene panel and exome sequencing have become widely used in genetic diagnostics. Unfortunately, the vast majority of identified variants are of unknown significance. Predicting the functional consequences of variants remains a significant challenge, with current approaches of limited use in distinguishing pathogenic from benign. Missense variants are especially challenging, as a single amino acid change can have a broad range of effects on interactions and protein structure.

Using gnomAD[1], the largest database of human standing variation, we have created a sequence-based measure of intolerance to missense variation across over 18,000 unique genes named the Missense Tolerance Ratio (MTR) [2]. We demonstrate that patient-ascertained variants preferentially clustered in intolerant, low scoring MTR regions, and could be used to help accurately identify variants responsible for epilepsy.

Interestingly, more intolerant regions were also observed to cluster within the protein tertiary structures. Evolutionary conservation has been widely used in the identification of important functional residues and interaction sites. This is, however, often limited by insufficient sampling of protein functional space in natural evolution. We propose that MTR scores, as a measure of variation within a population, provide a more sensitive measure to detect regions under tight evolutionary control without these biases.

We are combing our MTR estimates with protein tertiary structure properties to create a novel and more sensitive measure of intolerance for use in genomic analysis and to identify novel functionally important structural and functional features. We have made the MTR viewer freely available through a user-friendly website at

  1. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, O’Donnell-Luria AH, Ware JS, Hill AJ, Cummings BB, et al. 2016. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536: 285–291
  2. Traynelis J,* Silk M,* Wang Q, Berkovic SF, Liu L, Ascher DB, Balding DJ, Petrovski S (2017). Optimizing genomic medicine in epilepsy through a gene-customized approach to missense variant interpretation. Genome Research