ArticleBMC genomics2015
A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- ODBAE: a high-performance model identifying complex phenotypes in high-dimensional biological datasets.Communications biology · 2025Article
- Evolutionary Quantitative Genetics of Genomic Imprinting.Genetics · 2019Article
- A powerful parent-of-origin effects test for qualitative traits on X chromosome in general pedigrees.BMC bioinformatics · 2018Article
- Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle.BMC genomics · 2017Article
- Genomic prediction using models with dominance and imprinting effects for backfat thickness and average daily gain in Danish Duroc pigs.Genetics, selection, evolution : GSE · 2016Article
- Incorporating parent-of-origin effects in whole-genome prediction of complex traits.Genetics, selection, evolution : GSE · 2016Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic imprinting is an epigenetic mechanism that can lead to differential gene expression depending on the parent-of-origin of a received allele. While most studies on imprinting address its underlying molecular mechanisms or attempt at discovering genomic regions that might be subject to imprinting, few have focused on the amount of phenotypic variation contributed by such epigenetic process. In this report, we give a brief review of a one-locus imprinting model in a quantitative genetics framework, and provide a decomposition of the genetic variance according to this model. Analytical deductions from the proposed imprinting model indicated a non-negligible contribution of imprinting to genetic variation of complex traits. Also, we performed a whole-genome scan analysis on mouse body mass index (BMI) aiming at revealing potential consequences when existing imprinting effects are ignored in genetic analysis.
results10,021 SNP markers were used to perform a whole-genome single marker regression on mouse BMI using an additive and an imprinting model. Markers significant for imprinting indicated that BMI is subject to imprinting. Marked variance changed from 1.218 ×10(-4) to 1.842 ×10(-4) when imprinting was considered in the analysis, implying that one third of marked variance would be lost if existing imprinting effects were not accounted for. When both marker and pedigree information were used, estimated heritability increased from 0.176 to 0.195 when imprinting was considered.
conclusionsWhen a complex trait is subject to imprinting, using an additive model that ignores this phenomenon may result in an underestimate of additive variability, potentially leading to wrong inferences about the underlying genetic architecture of that trait. This could be a possible factor explaining part of the missing heritability commonly observed in genome-wide association studies (GWAS).
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