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Considerations for the Implementation of Massively Parallel Sequencing into Routine Kinship Analysis.

Lucinda Davenport1, Laurence Devesse1, Somruetai Satmun1

  • 1King's Forensics, Department of Analytical, Environmental and Forensic Sciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 9NH, UK.

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|March 28, 2025
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Summary
This summary is machine-generated.

Massively parallel sequencing (MPS) offers advanced kinship analysis beyond capillary electrophoresis (CE). This study outlines workflow adaptations for MPS, ensuring accurate genetic relationship testing with sequence-based data.

Keywords:
forensic geneticskinship analysiskinship caseworklikelihood ratiomassively parallel sequencingmicrohaplotypesnext generation sequencingpopulation databasessequence allele nomenclaturesequence-based STR analysis

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Area of Science:

  • Forensic genetics
  • Molecular biology
  • Bioinformatics

Background:

  • Forensic DNA typing traditionally uses capillary electrophoresis (CE)-based short tandem repeat (STR) analysis for kinship investigations.
  • CE-based STR analysis has limitations in resolving complex or distant genetic relationships.
  • Massively parallel sequencing (MPS) is emerging as a powerful alternative for forensic genetic marker analysis, including kinship.

Purpose of the Study:

  • To adapt existing data analysis workflows for kinship testing to accommodate Massively Parallel Sequencing (MPS) methodologies.
  • To ensure the full potential of MPS is realized in routine forensic casework while maintaining data integrity.
  • To provide a framework for laboratories implementing MPS for kinship analysis.

Main Methods:

  • Utilized empirical data from MPS analysis of forensically relevant STRs and single nucleotide polymorphisms (SNPs).
  • Incorporated real-world case experience to identify necessary workflow modifications.
  • Developed adaptations for sequence-based data analysis compatible with existing kinship software.

Main Results:

  • Identified four key considerations for adapting CE-based workflows to MPS: allele nomenclature, mutational event accounting, population databases, and rare allele frequency handling.
  • Presented methods for addressing the unique properties of sequence-based data in kinship analysis.
  • Outlined statistical adjustments for genetic linkage within expanded MPS marker sets.

Conclusions:

  • This work provides essential guidance for laboratories transitioning to MPS for routine kinship analysis.
  • The proposed framework addresses data analysis and statistical interpretation challenges specific to MPS.
  • Implementation of these adaptations will enhance the accuracy and scope of forensic kinship testing.