Abstract
Identity-by-descent (IBD), the detection of shared segments inherited from a common ancestor, is a fundamental concept in genomics with broad applications in the characterization and analysis of genomes. While historically the concept of IBD was extensively utilized through linkage analyses and in studies of founder populations, applications of IBD-based methods subsided during the genome-wide association study era. This was primarily due to the computational expense of IBD detection, which becomes increasingly relevant as the field moves toward the analysis of biobank-scale datasets that encompass individuals from highly diverse backgrounds. To address these computational barriers, the past several years have seen new methodological advances enabling IBD detection for datasets in the hundreds of thousands to millions of individuals, enabling novel analyses at an unprecedented scale. Here, we describe the latest innovations in IBD detection and describe opportunities for the application of IBD-based methods across a broad range of questions in the field of genomics.
Highlights
The rapid growth and increasing availability of biobank-scale datasets has led to their increased utilization in human genetics studies, the demographic and evolutionary forces that underly genomic patterns within these data are often overlooked
Leveraging properties of IBD allows researchers to infer a vast amount of information about a population’s demographic history (Carmi et al, 2013; Palamara and Pe’er, 2013; Nait Saada et al, 2020), allowing for evolutionary and pedigree-derived insights that can aid in the interpretation of genetic variation
All genetic variants affecting traits are influenced by the combination of the evolutionary forces of selection and genetic drift
Summary
The rapid growth and increasing availability of biobank-scale datasets has led to their increased utilization in human genetics studies, the demographic and evolutionary forces that underly genomic patterns within these data are often overlooked. Standard genetic analytical frameworks often overlook the fine-scale population structure relevant to the segregation of rare variants, despite their role in common, complex diseases becoming increasingly apparent (Hernandez et al, 2019; Taliun et al, 2021) For these reasons, there is an increasing need for novel methods that can account for demographic substructure driving patterns of variation across the site frequency spectrum in large, diverse cohorts (Gravel et al, 2011). Leveraging properties of IBD allows researchers to infer a vast amount of information about a population’s demographic history (Carmi et al, 2013; Palamara and Pe’er, 2013; Nait Saada et al, 2020), allowing for evolutionary and pedigree-derived insights that can aid in the interpretation of genetic variation Identifying these shared segments from a recent common ancestor can enrich for shared patterns of rare variation, due to the relationship between allele age and frequency (Slatkin and Rannala, 2000). We explore the population genomic principles governing patterns of IBD sharing, past and recent methods for detecting IBD in population scale data, and downstream applications in contemporary human genomics
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