Narrow-sense heritability estimation of complex traits using identity-by-descent information

Abstract

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.

Rapid detection of identity-by-descent tracts for mega-scale datasets

“…Our method is far more sensitive than GERMLINE at identifying short segments, an observation found by others 32 . Identifying large segments is critical for inferring an unbiased tract length distribution, an observation required for IBD-based genetic relatedness matrices 33 , as well as population genetic inference 3 . While maintaining high sensitivity in short segments, we ensure that our method is not susceptible to false positives via genome shuffling 25 to create a putatively IBD-free dataset.…”

Accuracy of genomic selection and long‐term genetic gain for resistance to Verticillium wilt in strawberry

“…The 50K SNP array was developed by targeting sub‐genome specific DNA sequences physically anchored to the octoploid reference genome (Hardigan et al., 2020). The training population ( n = 388) was genotyped with the 50K SNP array, which yielded a dense, genome‐wide framework of sub‐genome specific DNA markers to support the genome‐wide association and genomic selection studies described in this paper (de los Campos, Sorensen, & Gianola, 2015; Evans et al., 2018; Goddard & Hayes, 2007; Hayes et al., 2009; Visscher, Hill, & Wray, 2008). Sub‐genome specific genotyping approaches are tractable and effective in strawberry because of the sheer abundance of DNA variants in elite and wild populations and exceptional frequency with which homeologous DNA sequences can be differentiated and aligned to the octoploid reference genome (Hardigan et al., 2020).…”

Quantifying the Power and Precision of QTL Analysis in Autopolyploids Under Bivalent and Multivalent Genetic Models

“…IBD information could also be used for other applications, e.g. , improved estimation of complex trait heritabilities (Evans et al 2018).…”