Evidence map›Paper›PMID 30531870›Full record

ArticleNature genetics2019

A map of constrained coding regions in the human genome.

James M Havrilla, Brent S Pedersen, Ryan M Layer, Aaron R Quinlan

Abstract read
In one paragraph

Article in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers.

0numbers the graph read from it
0cells of the map it votes in
153citing 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

153 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Haplotype analysis and molecular marker development for the cold tolerance gene OsCTS11 at the seedling stage of rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

93 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

4 authors.

James M HavrillaDepartment of Human Genetics, University of Utah, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0002-8388-1362
Brent S PedersenDepartment of Human Genetics, University of Utah, Salt Lake City, UT, USA.
Ryan M LayerBioFrontiers Institute, University of Colorado, Boulder, CO, USA.ORCID http://orcid.org/0000-0002-5823-3232
Aaron R QuinlanDepartment of Human Genetics, University of Utah, Salt Lake City, UT, USA. aaronquinlan@gmail.com.ORCID http://orcid.org/0000-0003-1756-0859

Funding

Monitoring tumor subclonal heterogeneity over time and spaceU24CA209999 · NCI · UNIVERSITY OF UTAH · PI MARTH, GABOR T, QUINLAN, AARON R · 2016 to 2020
$3.9M
New algorithms and tools for large-scale genomic analysesR01HG006693 · NHGRI · UNIVERSITY OF VIRGINIA · PI QUINLAN, AARON R · 2012 to 2018
$3.1M
A powerful web-based discovery platform for rare disease geneticsR01HG009141 · NHGRI · BROAD INSTITUTE, INC. · PI QUINLAN, AARON R, REHM, HEIDI L · 2017 to 2020
$2.9M
Analysis of genomics datasets at a massive scaleR01GM121459 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI HANSEN, KASPER DANIEL · 2017 to 2021
$2.3M
Software for exploring all forms of genetic variation in any speciesR01GM124355 · NIGMS · UNIVERSITY OF UTAH · PI QUINLAN, AARON R · 2017 to 2020
$1.8M
A scalable, integrative, multi-omic analysis platformR00HG009532 · NHGRI · UNIVERSITY OF COLORADO · PI LAYER, RYAN M · 2018 to 2020
$671k
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
A scalable, integrative, multi-omic analysis platformK99HG009532 · NHGRI · UNIVERSITY OF UTAH · PI LAYER, RYAN M · 2017 to 2018
$209k
NCI NIH HHS U24 CA209999NHGRI NIH HHS K99 HG009532NHGRI NIH HHS R00 HG009532NHGRI NIH HHS R01 HG006693NHGRI NIH HHS R01 HG009141NIGMS NIH HHS R01 GM124355NIH HHS K99HG009532NIH HHS R01GM124355NIH HHS R01HG006693NIH HHS R01HG009141NIH HHS S10 OD020069NIH HHS U24CA209999
6 · The paper itself

Abstract

Deep catalogs of genetic variation from thousands of humans enable the detection of intraspecies constraint by identifying coding regions with a scarcity of variation. While existing techniques summarize constraint for entire genes, single gene-wide metrics conceal regional constraint variability within each gene. Therefore, we have created a detailed map of constrained coding regions (CCRs) by leveraging variation observed among 123,136 humans from the Genome Aggregation Database. The most constrained CCRs are enriched for pathogenic variants in ClinVar and mutations underlying developmental disorders. CCRs highlight protein domain families under high constraint and suggest unannotated or incomplete protein domains. The highest-percentile CCRs complement existing variant prioritization methods when evaluating de novo mutations in studies of autosomal dominant disease. Finally, we identify highly constrained CCRs within genes lacking known disease associations. This observation suggests that CCRs may identify regions under strong purifying selection that, when mutated, cause severe developmental phenotypes or embryonic lethality.

Indexed as

Chromosome MappingDevelopmental DisabilitiesGenome, HumanHumansMutationOpen Reading Frames

Identifiers

PMID30531870
PMCPMC6589356

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.