A comparative analysis dataset for improving genuine SNP identification in ancient maize aDNA

Area of Science:

• Ancient DNA (aDNA) research
• Paleogenomics
• Crop domestication studies

Background:

• Maize (Zea mays) aDNA is crucial for understanding its domestication, evolution, and gene flow.
• Accurate single nucleotide polymorphism (SNP) discovery in aDNA requires addressing post-mortem damage (PMD) and selecting appropriate analytical tools and read depth.
• Standardized methods for aDNA analysis in maize are currently lacking.

Purpose of the Study:

• To re-analyze existing ancient maize DNA datasets using different pipelines and criteria.
• To evaluate the impact of various post-mortem damage (PMD) correction methods and read depth settings on single nucleotide polymorphism (SNP) discovery.
• To provide a valuable resource and guidance for improving the quality of ancient maize DNA analyses.

Main Methods:

• Re-analysis of previously published ancient maize DNA data.
• Application of two distinct post-mortem damage (PMD) correction approaches: Rm5nt and NoChange.
• Processing of data using three different analysis tools: GATK, angsd, and pileupCaller.
• Evaluation under three read depth criteria: 2X, 5X, and 10X.

Main Results:

• Different analytical pipelines and read depth criteria significantly impact single nucleotide polymorphism (SNP) calls in ancient maize DNA.
• The choice of post-mortem damage (PMD) handling strategy influences the reliability of SNP discovery.
• The re-analyzed dataset serves as a benchmark for assessing analytical approaches in ancient maize genomics.

Conclusions:

• Standardized approaches are needed for robust ancient maize DNA analysis.
• Careful selection of analytical pipelines, PMD correction methods, and read depth is critical for accurate SNP discovery.
• This study offers a foundation for enhancing the quality and comparability of future ancient maize aDNA research.