摘要：SummaryThe 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 callMUC1mutations for MCKD1.Graphical abstractDisplay OmittedHighlights•Detection of coding variants in tandem repeats is confounded by ambiguous mapping•Our method, code-adVNTR, detects variants in coding VNTRs using multi-motif HMMs•code-adVNTR outperforms GATK-HaplotypeCaller on indel detection in tandem repeats•A known frameshift variant within a VNTR in MUC1 gene was accurately detectedGenetics; Genomics; Human genetics ; Molecular genetics
