Aim: Leukocyte immunoglobulin-like receptors (LILRs) are encoded within the leukocyte receptor complex (LRC) on human chromosome 19, and are expressed by a range of immune cell types, including natural killer (NK) cells, dendritic cells, and T cells, and perform immunomodulatory roles critical to maintaining self-tolerance. Despite their broad distribution and important immune function, large-scale analysis of LILR genomic variation has been limited by features of the gene complex such as structural complexity and extensive sequence homology. While a handful of population-level studies have examined single nucleotide polymorphism (SNP) variation in the LILRs, there is a paucity of published work examining full gene variation at population level. In this study, we seek to reveal variation in the LILR genes beyond the limited data reflected in the existing literature.
Methods: Since the LILR gene complex shows high nucleotide polymorphism and extensive homology between genes, a conventional bioinformatics workflow of short-read sequencing, alignment, and variant calling is insufficient to capture all variation at a high resolution. Here, we present a bioinformatics pipeline adapted from the novel the PING pipeline (Marin et al. 2021, 2023), which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput LILR sequence analysis from short-read data.
Results: We present an overview of LILR variation in two cohorts of healthy individuals of European- and African American ancestry (N=450 and 344, respectively). Our findings reveal extensive variation in the LILR genes for the two population groups across the full gene, as well as copy number variation. We find extensive diversity in both coding and noncoding regions, resulting in many unique allotypes not previously reported, including alleles that are both unique to each population as well as shared across populations.
Conclusion: Our study addresses the knowledge gap that exists in the study of full gene variation of LILR genes. These findings should serve to provide a foundation for further studies seeking to better understand the evolutionary history of LILR variation and its role in human health and disease.
