Inspecting close maternal relatedness: Towards better mtDNA population samples in forensic databases

Area of Science:

• Genetics
• Population Genetics
• Forensic Science

Background:

• Mitochondrial DNA (mtDNA) is a vital genetic marker in various research fields.
• Ensuring high-quality sequence data through validation and inspection is critical for comparability and accurate interpretation.
• Existing efforts to expand population samples for understanding human mtDNA variation often utilize convenience samples, potentially compromising data quality.

Purpose of the Study:

• To introduce an additional quality control measure for mtDNA data.
• To mitigate bias in population samples caused by the inclusion of related individuals.
• To enhance the representativeness of population samples for mtDNA studies.

Main Methods:

• Integration of autosomal short tandem repeat (STR) markers with mitochondrial DNA (mtDNA) information.
• Utilizing STR analysis to identify individuals sharing mitochondrial haplotypes.
• Employing pedigree construction and software-assisted likelihood ratio calculations to detect maternally related individuals.

Main Results:

• A novel method for identifying and excluding closely maternally related individuals from mtDNA population samples.
• Demonstration of how combining STR and mtDNA data improves sample quality.
• Discussion of scenarios where related individuals may be permissible within a dataset.

Conclusions:

• The combined STR and mtDNA approach serves as an effective quality control measure.
• This method contributes to more accurate and representative population genetic datasets.
• The enhanced quality control supports more reliable mtDNA data for forensic, migration, and medical genetics applications.