Abstract

A total of 1327 platinum-quality mitochondrial DNA haplotypes from United States (U.S.) populations were generated using a robust, semi-automated next-generation sequencing (NGS) workflow with rigorous quality control (QC). The laboratory workflow involved long-range PCR to minimize the co-amplification of nuclear mitochondrial DNA segments (NUMTs), PCR-free library preparation to reduce amplification bias, and high-coverage Illumina MiSeq sequencing to produce an average per-sample read depth of 1000 × for low-frequency (5%) variant detection. Point heteroplasmies below 10% frequency were confirmed through replicate amplification, and length heteroplasmy was quantitatively assessed using a custom read count analysis tool. Data analysis involved a redundant, dual-analyst review to minimize errors in haplotype reporting with additional QC checks performed by EMPOP. Applying these methods, eight sample sets were processed from five U.S. metapopulations (African American, Caucasian, Hispanic, Asian American, and Native American) corresponding to self-reported identity at the time of sample collection. Population analyses (e.g., haplotype frequencies, random match probabilities, and genetic distance estimates) were performed to evaluate the eight datasets, with over 95% of haplotypes unique per dataset. The platinum-quality mitogenome haplotypes presented in this study will enable forensic statistical calculations and thereby support the usage of mitogenome sequencing in forensic laboratories.

Highlights

  • Advances in next-generation sequencing (NGS) technologies allow for efficient whole-mitochondrial-genome sequence analysis of high-quality and degraded DNA samples [1,2,3,4]

  • The samples used in this study were obtained from the following three sources: the Analytical Genetic Testing Center located in Colorado (AGTC-CO), National Institute of Standards and Technology (NIST), and the Department of Defense Serum Repository (DoDSR)

  • A total of 32 samples (19 AGTC-CO, 3 NIST, and 10 DoDSR) were excluded from the finalized datasets after reprocessing attempts resulted in failed data (18) or mixed profiles (14)

Read more

Summary

Introduction

Advances in next-generation sequencing (NGS) technologies allow for efficient whole-mitochondrial-genome (mitogenome) sequence analysis of high-quality and degraded DNA samples [1,2,3,4]. NGS generates large amounts of data per sample and high read depth, which allows for increased sensitivity [3,5,6]. The use of automated processing in NGS, especially for library preparation, reduces hands-on time and decreases the risk of human error (e.g., contamination and sample switches) [7]. The identification and removal of nuclear mitochondrial DNA segments (NUMTs) is possible in NGS analysis using bioinformatic tools to investigate phasing of variants along parsed sequence reads and to perform multiple reference sequence alignment [11,12].

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call