medRxivGenetic & Genomic MedicinePreprint
Whole genome sequencing identifies common and rare structural variants contributing to hematologic traits in the NHLBI TOPMed program
Marsha M. WheeleriD, Adrienne M. StilpiD, Shuquan RaoiD, Bjarni V. HalldórssoniD, Doruk BeyteriD, Jia WeniD, Anna V. MikhaylovaiD, Caitlin McHughiD, John LaneiD, Min-Zhi JiangiD, Laura M. RaffieldiD, Goo JuniD, Fritz Joachim SedlazeckiD, Ginger MetcalfiD, Yao YaoiD, Joshua C. BisiD, Nathalie ChamiiD, Paul S. de VriesiD, Pinkal M. DesaiiD, James S. FloydiD, Yan Lin GaoiD, Kai KammersiD, Wonji KimiD, Jee‐Young MooniD, Aakrosh RataniD, , Alex P. ReineriD
Abstract
Genome-wide association studies (GWAS) have identified thousands of single nucleotide variants and small indels that contribute to the genetic architecture of hematologic traits. While structural variants (SVs) are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of SVs to quantitative blood cell trait variation is unknown. Here we utilized SVs detected from whole genome sequencing (WGS) in ancestrally diverse participants of the NHLBI TOPMed program (N=50,675). Using single variant tests, we assessed the association of common and rare SVs with red cell-, white cell-, and platelet-related quantitative traits. The results show 33 independent SVs (23 common and 10 rare) reaching genome-wide significance. The majority of significant association signals (N=27) replicated in independent datasets from deCODE genetics and the UK BioBank. Moreover, most trait-associated SVs (N=24) are within 1Mb of previously-reported GWAS loci. SV analyses additionally discovered an association between a complex structural variant on 17p11.2 and white blood cell-related phenotypes. Based on functional annotation, the majority of significant SVs are located in non-coding regions (N=26) and predicted to impact regulatory elements and/or local chromatin domain boundaries in blood cells. We predict that several trait-associated SVs represent the causal variant. This is supported by genome-editing experiments which provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.
- organism: human
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 5
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