Ancestry adjustment improves genome-wide estimates of regional intolerance

Tristan J. Hayeck, Nicholas Stong, Evan Baugh, Ryan Dhindsa, Tychele N. Turner, Ayan Malakar, Timothy L. Mosbruger, Grace Tzun Wen Shaw, Yuncheng Duan, Iuliana Ionita-Laza, David Goldstein, Andrew S. Allen

Research output: Contribution to journalArticlepeer-review


Genomic regions subject to purifying selection are more likely to carry disease-causing mutations than regions not under selection. Cross species conservation is often used to identify such regions but with limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, genetic intolerance looks for depletion of variation relative to expectation within a species, allowing species-specific features to be identified. When estimating the intolerance of noncoding sequence, methods strongly leverage variant frequency distributions. As the expected distributions depend on ancestry, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating ancestry in intolerance estimation greatly improved variant classification. We provide a genome-wide intolerance map that is conditional on ancestry and likely to be particularly valuable for variant prioritization.

Original languageEnglish
Issue number2
StatePublished - May 31 2022


  • evolution
  • genetic epidemiology
  • genetic intolerance
  • intolerance to variation
  • negative selection
  • population genetics
  • statistical genetics


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