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Inferring compound heterozygosity from large-scale exome sequencing data

Guo, M.H. ; Groop, L. LU ; Haiman, C. ; Melander, O. LU orcid ; Nilsson, P.M. LU ; Smith, J.G. LU orcid and Samocha, K.E. (2024) In Nature Genetics 56(1). p.152-161
Abstract
Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed... (More)
Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed causal compound heterozygous variants. We provide a public resource of phasing estimates for coding variants and counts per gene of rare variants in trans that can aid interpretation of rare co-occurring variants in the context of recessive disease. © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc. (Less)
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author
; ; ; ; ; and
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Exome, Exome Sequencing, Genotype, High-Throughput Nucleotide Sequencing, Humans, article, controlled study, diagnosis, etiology, exome, gene, genetic variability, genotype, heterozygosity, human, whole exome sequencing, genetics, high throughput sequencing
in
Nature Genetics
volume
56
issue
1
pages
10 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85181415190
  • pmid:38057443
ISSN
1061-4036
DOI
10.1038/s41588-023-01608-3
language
English
LU publication?
yes
id
36337f65-7e66-4d36-a75c-ae2e712707c1
date added to LUP
2025-10-16 11:35:22
date last changed
2025-10-17 11:07:37
@article{36337f65-7e66-4d36-a75c-ae2e712707c1,
  abstract     = {{Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed causal compound heterozygous variants. We provide a public resource of phasing estimates for coding variants and counts per gene of rare variants in trans that can aid interpretation of rare co-occurring variants in the context of recessive disease. © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.}},
  author       = {{Guo, M.H. and Groop, L. and Haiman, C. and Melander, O. and Nilsson, P.M. and Smith, J.G. and Samocha, K.E.}},
  issn         = {{1061-4036}},
  keywords     = {{Exome; Exome Sequencing; Genotype; High-Throughput Nucleotide Sequencing; Humans; article; controlled study; diagnosis; etiology; exome; gene; genetic variability; genotype; heterozygosity; human; whole exome sequencing; genetics; high throughput sequencing}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{152--161}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Genetics}},
  title        = {{Inferring compound heterozygosity from large-scale exome sequencing data}},
  url          = {{http://dx.doi.org/10.1038/s41588-023-01608-3}},
  doi          = {{10.1038/s41588-023-01608-3}},
  volume       = {{56}},
  year         = {{2024}},
}