Evidence map›Paper›PMID 30962618›Full record

ReviewNature genetics2019

Measuring intolerance to mutation in human genetics.

Zachary L Fuller, Jeremy J Berg, Hakhamanesh Mostafavi, Guy Sella, Molly Przeworski

Abstract readReview
In one paragraph

Review in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

93 citing papers in PubMed.

  1. Article
  2. Dynamics of mutators of arbitrary dominance in humans.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Accessible, realistic genome simulation with selection using stdpopsim.bioRxiv : the preprint server for biology · 2025
    Article
  19. Article
  20. Review

33 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zachary L FullerDepartment of Biological Sciences, Columbia University, New York, NY, USA. zlf2101@columbia.edu.ORCID http://orcid.org/0000-0003-4765-9227
Jeremy J BergDepartment of Biological Sciences, Columbia University, New York, NY, USA.
Hakhamanesh MostafaviDepartment of Biological Sciences, Columbia University, New York, NY, USA.ORCID http://orcid.org/0000-0002-1060-2844
Guy SellaDepartment of Biological Sciences, Columbia University, New York, NY, USA.
Molly PrzeworskiDepartment of Biological Sciences, Columbia University, New York, NY, USA.

Funding

Core Research Computing FacilityG20RR030893 · NCRR · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI PURDY, MICHAEL · 2010 to 2010
$10.0M
The population genetics of disease risk and other quantitative traitsR01GM115889 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI SELLA, GUY · 2015 to 2025
$2.9M
Natural selection in recent human evolutionR01GM121372 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI PRZEWORSKI, MOLLY F · 2017 to 2020
$1.6M
Characterizing and Mapping Deleterious Mutations in HumansF32GM128318 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI FULLER, ZACHARY L · 2018 to 2020
$188k
Population genetic modeling of the genetic architecture of complex diseaseF32GM126787 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI BERG, JEREMY JACKSON · 2018 to 2018
$55k
NCRR NIH HHS G20 RR030893NIGMS NIH HHS F32 GM126787NIGMS NIH HHS F32 GM128318NIGMS NIH HHS R01 GM115889NIGMS NIH HHS R01 GM121372
6 · The paper itself

Abstract

In numerous applications, from working with animal models to mapping the genetic basis of human disease susceptibility, knowing whether a single disrupting mutation in a gene is likely to be deleterious is useful. With this goal in mind, a number of measures have been developed to identify genes in which protein-truncating variants (PTVs), or other types of mutations, are absent or kept at very low frequency in large population samples-genes that appear 'intolerant' to mutation. One measure in particular, the probability of being loss-of-function intolerant (pLI), has been widely adopted. This measure was designed to classify genes into three categories, null, recessive and haploinsufficient, on the basis of the contrast between observed and expected numbers of PTVs. Such population-genetic approaches can be useful in many applications. As we clarify, however, they reflect the strength of selection acting on heterozygotes and not dominance or haploinsufficiency.

Indexed as

MutationAnimalsGene FrequencyGenes, RecessiveGenetic DriftGenetics, PopulationHaploinsufficiencyHeterozygoteHumansLoss of Function MutationModels, GeneticSelection, Genetic

Identifiers

PMID30962618
PMCPMC6615471

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.