Introducing M-GCTA a Software Package to Estimate Maternal (or Paternal) Genetic Effects on Offspring Phenotypes

Zhen Qiao, Jie Zheng, Øyvind Helgeland, Marc Vaudel, Stefan Johansson, Pål R. Njølstad, George Davey Smith, Nicole M. Warrington, David M. Evans*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
216 Downloads (Pure)

Abstract

There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.

Original languageEnglish
Pages (from-to)51-66
Number of pages16
JournalBehavior Genetics
Volume50
Early online date6 Sept 2019
DOIs
Publication statusPublished - 1 Jan 2020

Keywords

  • SNP heritability
  • Heritability
  • G-REML
  • Paternal effects
  • Maternal effects
  • M-GCTA

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