Detecting tandem repeat variants in coding regions using code-adVNTR

Park J, Bakhtiari M, Popp B, Wiesener M, Bafna V (2022)

Publication Type: Journal article

Publication year: 2022

Journal

iScience Elsevier

Book Volume: 25

Article Number: 104785

Journal Issue: 8

DOI: 10.1016/j.isci.2022.104785

Abstract

The human genome contains more than one million tandem repeats (TRs), DNA sequences containing multiple approximate copies of a motif repeated contiguously. TRs account for significant genetic variation, with 50 + diseases attributed to changes in motif number. A few diseases have been to be caused by small indels in variable number tandem repeats (VNTRs) including poly-cystic kidney disease type 1 (MCKD1) and monogenic type 1 diabetes. However, small indels in VNTRs are largely unexplored mainly due to the long and complex structure of VNTRs with multiple motifs. We developed a method, code-adVNTR, that utilizes multi-motif hidden Markov models to detect both, motif count variation and small indels, within VNTRs. In simulated data, code-adVNTR outperformed GATK-HaplotypeCaller in calling small indels within large VNTRs. We used code-adVNTR to characterize coding VNTRs in the 1000 genomes data identifying many population-specific variants, and to reliably call MUC1 mutations for MCKD1.

Authors with CRIS profile

Bernt Popp Lehrstuhl für Humangenetik Michael Wiesener Professur für Innere Medizin (Nephrologie)

Involved external institutions

University of California, San Diego

United States (USA) (US)

How to cite

APA:

Park, J., Bakhtiari, M., Popp, B., Wiesener, M., & Bafna, V. (2022). Detecting tandem repeat variants in coding regions using code-adVNTR. iScience, 25(8). https://doi.org/10.1016/j.isci.2022.104785

MLA:

Park, Jonghun, et al. "Detecting tandem repeat variants in coding regions using code-adVNTR." iScience 25.8 (2022).

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