Highlights
- •A novel study of performing genotype imputation across disjoint genetic marker sets based on a 1000 Genomes SNP-STR haplotype panel.
- •Genotype imputation has great application potential for extracting genetic information associated with STRs.
- •Match score analysis after genotype imputation may help for individual identification.
Abstract
Short tandem repeat polymorphism (STR)-based individual identification is a popular
and reliable method in many forensic applications. However, STRs still frequently
fail to find any matched records. In such cases, if known STRs could provide more
information, it would be very helpful to solve specific problems. Genotype imputation
has long been used in the study of single nucleotide polymorphisms (SNPs) and has
recently been introduced into forensic fields. The idea is that, through a reference
haplotype panel containing SNPs and STRs, we can obtain unknown genetic information
through genotype imputation based on known STR or SNP genotypes. Several recent studies
have already demonstrated this exciting idea, and a 1000 Genomes SNP-STR haplotype
panel has also been released. To further study the performance of genotype imputation
in forensic fields, we collected STR, microhaplotype (MH) and SNP array genotypes
from Chinese Han population individuals and then performed genotype imputation analysis
based on the released reference panel. As a result, the average locus imputation accuracy
was ∼83 % (or ∼70 %) when SNPs in the SNP array (or MH SNPs) were imputed from STRs,
and was ∼30 % when highly polymorphic markers (STRs and MHs) were imputed from each
other. When STRs were imputed from SNP array, the average locus imputation accuracy
increased to ∼48 %. After analyzing the match scores between real STRs and the STRs
imputed from SNPs, ∼80 % of studied STR records can be connected to corresponding
SNP records, which may help for individual identification. Our results indicate that
genotype imputation has great potential for forensic applications.
Keywords
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Article info
Publication history
Published online: October 17, 2022
Accepted:
October 14,
2022
Received in revised form:
October 8,
2022
Received:
March 26,
2022
Identification
Copyright
© 2022 Elsevier B.V. All rights reserved.
