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A genomic mutational constraint map using variation in 76,156 human genomes

Chen, S. ; Groop, L. LU ; Melander, O. LU orcid ; Nilsson, P.M. LU ; Smith, J. Gustav LU ; MacArthur, D.G. and Karczewski, K.J. (2024) In Nature 625(7993). p.92-100
Abstract
The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders 1–4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)—the largest public open-access human genome allele frequency reference dataset—and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of... (More)
The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders 1–4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)—the largest public open-access human genome allele frequency reference dataset—and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Chromosome Mapping, Gene Frequency, Genetic Variation, Genome, Human, Genomics, Humans, Mutation, allele, DNA, gene expression, genome, mutation, protein, triangulation, article, gene frequency, genetic variation, human, human genome, natural selection, open reading frame, chromosomal mapping, genetics, genomics
in
Nature
volume
625
issue
7993
pages
9 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85180828283
  • pmid:38057664
ISSN
0028-0836
DOI
10.1038/s41586-023-06045-0
language
English
LU publication?
yes
id
5805be33-cb32-4cb2-90b6-d452ba9c5735
date added to LUP
2024-03-04 15:00:27
date last changed
2024-04-03 03:32:28
@article{5805be33-cb32-4cb2-90b6-d452ba9c5735,
  abstract     = {{The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders 1–4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)—the largest public open-access human genome allele frequency reference dataset—and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.}},
  author       = {{Chen, S. and Groop, L. and Melander, O. and Nilsson, P.M. and Smith, J. Gustav and MacArthur, D.G. and Karczewski, K.J.}},
  issn         = {{0028-0836}},
  keywords     = {{Chromosome Mapping; Gene Frequency; Genetic Variation; Genome, Human; Genomics; Humans; Mutation; allele; DNA; gene expression; genome; mutation; protein; triangulation; article; gene frequency; genetic variation; human; human genome; natural selection; open reading frame; chromosomal mapping; genetics; genomics}},
  language     = {{eng}},
  number       = {{7993}},
  pages        = {{92--100}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature}},
  title        = {{A genomic mutational constraint map using variation in 76,156 human genomes}},
  url          = {{http://dx.doi.org/10.1038/s41586-023-06045-0}},
  doi          = {{10.1038/s41586-023-06045-0}},
  volume       = {{625}},
  year         = {{2024}},
}