Parent-of-Origin inference for biobanks

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Parent-of-Origin inference for biobanks. / Hofmeister, Robin J.; Rubinacci, Simone; Ribeiro, Diogo M.; Buil, Alfonso; Kutalik, Zoltán; Delaneau, Olivier.

In: Nature Communications, Vol. 13, 6668, 2022.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Hofmeister, RJ, Rubinacci, S, Ribeiro, DM, Buil, A, Kutalik, Z & Delaneau, O 2022, 'Parent-of-Origin inference for biobanks', Nature Communications, vol. 13, 6668. https://doi.org/10.1038/s41467-022-34383-6

APA

Hofmeister, R. J., Rubinacci, S., Ribeiro, D. M., Buil, A., Kutalik, Z., & Delaneau, O. (2022). Parent-of-Origin inference for biobanks. Nature Communications, 13, [6668]. https://doi.org/10.1038/s41467-022-34383-6

Vancouver

Hofmeister RJ, Rubinacci S, Ribeiro DM, Buil A, Kutalik Z, Delaneau O. Parent-of-Origin inference for biobanks. Nature Communications. 2022;13. 6668. https://doi.org/10.1038/s41467-022-34383-6

Author

Hofmeister, Robin J. ; Rubinacci, Simone ; Ribeiro, Diogo M. ; Buil, Alfonso ; Kutalik, Zoltán ; Delaneau, Olivier. / Parent-of-Origin inference for biobanks. In: Nature Communications. 2022 ; Vol. 13.

Bibtex

@article{3aad1724adf84e64b554870fd207e66c,
title = "Parent-of-Origin inference for biobanks",
abstract = "Studies on parent-of-origin effects have been limited in terms of sample size due to lack of parental genomes or known genealogies. Here, the authors develop a method to infer the parent-of-origin of an individual alleles in biobank-scale datasets, without requiring parental genomes or prior knowledge of genealogy, allowing discovery of parent-of-origin effects with an unprecedented sample size.Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.",
keywords = "IMPRINTED REGION, TELOMERE LENGTH, GENETIC-LOCI, ASSOCIATION, VARIANTS, MOTIF",
author = "Hofmeister, {Robin J.} and Simone Rubinacci and Ribeiro, {Diogo M.} and Alfonso Buil and Zolt{\'a}n Kutalik and Olivier Delaneau",
year = "2022",
doi = "10.1038/s41467-022-34383-6",
language = "English",
volume = "13",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Parent-of-Origin inference for biobanks

AU - Hofmeister, Robin J.

AU - Rubinacci, Simone

AU - Ribeiro, Diogo M.

AU - Buil, Alfonso

AU - Kutalik, Zoltán

AU - Delaneau, Olivier

PY - 2022

Y1 - 2022

N2 - Studies on parent-of-origin effects have been limited in terms of sample size due to lack of parental genomes or known genealogies. Here, the authors develop a method to infer the parent-of-origin of an individual alleles in biobank-scale datasets, without requiring parental genomes or prior knowledge of genealogy, allowing discovery of parent-of-origin effects with an unprecedented sample size.Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.

AB - Studies on parent-of-origin effects have been limited in terms of sample size due to lack of parental genomes or known genealogies. Here, the authors develop a method to infer the parent-of-origin of an individual alleles in biobank-scale datasets, without requiring parental genomes or prior knowledge of genealogy, allowing discovery of parent-of-origin effects with an unprecedented sample size.Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.

KW - IMPRINTED REGION

KW - TELOMERE LENGTH

KW - GENETIC-LOCI

KW - ASSOCIATION

KW - VARIANTS

KW - MOTIF

U2 - 10.1038/s41467-022-34383-6

DO - 10.1038/s41467-022-34383-6

M3 - Journal article

C2 - 36335127

VL - 13

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

M1 - 6668

ER -

ID: 334018789