Sequence-based population structure, relatedness, and inbreeding estimates for forensic autosomal STR markers

Area of Science:

• Forensic Science
• Population Genetics
• Genomics

Background:

• Next-generation sequencing (NGS) methods are increasingly adopted in forensic science.
• Existing population genetic parameters require updates for NGS-derived DNA data.
• Accurate population data is essential for reliable DNA evidence interpretation in forensic investigations.

Purpose of the Study:

• To provide updated population genetic parameter estimates for autosomal short tandem repeat (STR) data generated using sequencing technologies.
• To expand upon initial work with a larger sample size for more robust estimates.
• To assess population structure and relatedness within the studied population using NGS data.

Main Methods:

• Analysis of autosomal STR data generated by sequencing technologies.
• Estimation of population structure and relatedness parameters.
• Evaluation of the impact of inbreeding on forensic calculations.

Main Results:

• Provides updated estimates of population structure and relatedness for autosomal STRs from sequencing data.
• Discusses the influence of inbreeding on forensic calculations.
• Highlights the potential advantages of genotypic-based over allelic-based estimates in forensic contexts.

Conclusions:

• The study provides essential updated population genetic data for the forensic community transitioning to NGS methods.
• Genotypic-based estimates may offer a more accurate approach for forensic calculations compared to allelic-based estimates, especially considering inbreeding.
• These findings support the reliable evaluation of DNA evidence using advanced sequencing technologies in forensic investigations.