cLD: Rare-variant linkage disequilibrium between genomic regions identifies novel genomic interactions

Dinghao Wang, Deshan Perera, Jingni He, Chen Cao, Pathum Kossinna, Qing Li, William Zhang, Xingyi Guo, Alexander Platt, Jingjing Wu and Qingrun Zhang

PLOS Genetics, 2023, vol. 19, issue 12, 1-21

Abstract: Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.Author summary: Linkage disequilibrium (LD) is a crucial concept in genetics, but current methods of measuring LD are not reliable for rare variants. In our study, we introduce a new statistic called cumulative LD (cLD) that captures the linkage disequilibrium between genetic regions containing rare variants, which are often unanalyzed. We demonstrate that cLD is a stable statistic and show through simulations using real data that it is more reliable than traditional LD for rare variants.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgen00:1011074

DOI: 10.1371/journal.pgen.1011074

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