SNP-based heritability and selection analyses: Improved models and new results

Doug Speed, Anubhav Kaphle, David J Balding

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperReviewResearchpeer-review

12 Citations (Scopus)
74 Downloads (Pure)

Abstract

Complex-trait genetics has advanced dramatically through methods to estimate the heritability tagged by SNPs, both genome-wide and in genomic regions of interest such as those defined by functional annotations. The models underlying many of these analyses are inadequate, and consequently many SNP-heritability results published to date are inaccurate. Here, we review the modelling issues, both for analyses based on individual genotype data and association test statistics, highlighting the role of a low-dimensional model for the heritability of each SNP. We use state-of-art models to present updated results about how heritability is distributed with respect to functional annotations in the human genome, and how it varies with allele frequency, which can reflect purifying selection. Our results give finer detail to the picture that has emerged in recent years of complex trait heritability widely dispersed across the genome. Confounding due to population structure remains a problem that summary statistic analyses cannot reliably overcome. Also see the video abstract here: https://youtu.be/WC2u03V65MQ.

Original languageEnglish
Article number2100170
JournalBioEssays
Volume44
Issue5
Pages (from-to)e2100170
ISSN0265-9247
DOIs
Publication statusPublished - May 2022

Keywords

  • complex traits
  • gene function
  • genetic epidemiology
  • heritability
  • kinship
  • PARTITIONING HERITABILITY
  • STATISTICS
  • PREDICTION
  • DISEASES
  • GENETIC CORRELATION
  • ARCHITECTURE
  • MISSING HERITABILITY
  • VARIANCE
  • LD SCORE REGRESSION
  • GENOME-WIDE ASSOCIATION

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