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

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.