Abstract
Variable Number Tandem Repeats (VNTRs) account for a significant amount of human genetic variation. VNTRs have been implicated in both Mendelian and Complex disorders, but are largely ignored by whole genome analysis pipelines due to the complexity of genotyping and the computational expense. We describe adVNTR-NN, a method that uses shallow neural networks for fast read recruitment. On 55X whole genome data, adVNTR-NN genotyped each VNTR in less than 18 cpu-seconds, while maintaining 100% accuracy on 76% of VNTRs.
We used adVNTR-NN to genotype 10,264 VNTRs in 652 individuals from the GTEx project and associated VNTR length with gene expression in 46 tissues. We identified 163 ‘eVNTR’ loci that were significantly associated with gene expression. Of the 22 eVNTRs in blood where independent data was available, 21 (95%) were replicated in terms of significance and direction of association. 49% of the eVNTR loci showed a strong and likely causal impact on the expression of genes and 80% had maximum effect size at least 0.3. The impacted genes have important role in complex phenotypes including Alzheimer’s, obesity and familial cancers. Our results point to the importance of studying VNTRs for understanding the genetic basis of complex diseases.
Competing Interest Statement
V.B. is a co-founder, serves on the scientific advisory board, and has equity interest in Boundless Bio, inc. (BB) and Digital Proteomics, LLC (DP), and receives income from DP and BB. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. BB and DP were not involved in the research presented here.
