Characterization of a novel unliked 12 X-STR typing assay for forensic purposes in an admixed Rio de Janeiro population sample

X-STR analysis offers novel pathways for exploring both paternal and maternal lineages, which is particularly valuable in parenthood testing where standard methods fail. Despite being limited in availability, these markers show promise in improving forensic analyses, especially with emerging technology such as Massively Parallel Sequencing (MPS). This study introduces a new X-STRs multiplex system that could increase discrimination power in complex cases, expanding marker diversity and complementing traditional markers. We selected 12 X-STR loci (DXS61071, DXS97199, DXS12310, DXS14221, DXS33963, DXS39152, DXS44734, DXS54471, DXS68748, DXS70370, DXS13932, and DXS14986) for the assay. Genomic DNA was extracted from 100 unrelated males and 104 females, in a sample population from Rio de Janeiro, amplified with custom-designed primers and subjected to capillary gel electrophoresis and MPS. Forensic efficiency evaluation revealed high values of the combined power of discrimination in males (cPDM ≥ 0.999999997) and females (cPDF ≥ 0.999999999999995), as well as combined paternity exclusion (cPE ≥ 0.99999). Among these markers, two exhibit high polymorphism, with multiple isoalleles distinguishable by their sequences, using MPS technology. The incorporation of these new X-STR markers multiplex system in conjunction with MPS analysis could potentially increase the power of discrimination in forensic analysis for mixtures and complex cases.

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Publication Details

Journal
Genetics and Molecular Biology
Published
2025-12-01
DOI
https://doi.org/10.1590/1678-4685-gmb-2025-0015
Primary Topic
Forensic and Genetic Research
Type
article
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article

Characterization of a novel unliked 12 X-STR typing assay for forensic purposes in an admixed Rio de Janeiro population sample

Rosane Silva, Maria Clara da Costa Simas, Rodrigo S. Moura‐Neto, Isadora Mello
Genetics and Molecular Biology
Forensic and Genetic Research
article

Characterization of a novel unliked 12 X-STR typing assay for forensic purposes in an admixed Rio de Janeiro population sample

Rosane Silva, Maria Clara da Costa Simas, Rodrigo S. Moura‐Neto, Isadora Mello
article en

Abstract

X-STR analysis offers novel pathways for exploring both paternal and maternal lineages, which is particularly valuable in parenthood testing where standard methods fail. Despite being limited in availability, these markers show promise in improving forensic analyses, especially with emerging technology such as Massively Parallel Sequencing (MPS). This study introduces a new X-STRs multiplex system that could increase discrimination power in complex cases, expanding marker diversity and complementing traditional markers. We selected 12 X-STR loci (DXS61071, DXS97199, DXS12310, DXS14221, DXS33963, DXS39152, DXS44734, DXS54471, DXS68748, DXS70370, DXS13932, and DXS14986) for the assay. Genomic DNA was extracted from 100 unrelated males and 104 females, in a sample population from Rio de Janeiro, amplified with custom-designed primers and subjected to capillary gel electrophoresis and MPS. Forensic efficiency evaluation revealed high values of the combined power of discrimination in males (cPDM ≥ 0.999999997) and females (cPDF ≥ 0.999999999999995), as well as combined paternity exclusion (cPE ≥ 0.99999). Among these markers, two exhibit high polymorphism, with multiple isoalleles distinguishable by their sequences, using MPS technology. The incorporation of these new X-STR markers multiplex system in conjunction with MPS analysis could potentially increase the power of discrimination in forensic analysis for mixtures and complex cases.

Genetics and Molecular BiologyVol. 48(4)
Universidade Federal do Rio de Janeiro (BR)
Openalex Percentile: Top 59%
Forensic and Genetic Research
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Characterization of a novel unliked 12 X-STR typing assay for forensic purposes in an admixed Rio de Janeiro population sample — Rosane Silva, Maria Clara da Costa Simas, et al. · Genetics and Molecular Biology (2025) | TGRS Research Map | TGRS