Benchmarking software tools for trimming adapters and merging next-generation sequencing data for ancient DNA.

Area of Science:

• Ancient DNA research
• Bioinformatics
• Genomics

Background:

• Ancient DNA (aDNA) is highly degraded, yielding short sequences.
• High-throughput sequencing reads often contain adapter sequences that require removal.
• Adapter sequences can interfere with downstream aDNA analyses.

Purpose of the Study:

• To evaluate the accuracy of commonly used bioinformatics tools for adapter trimming and read merging in ancient DNA.
• To assess the impact of different tools on downstream ancient DNA analyses.
• To identify optimal tools for reconstructing ancient DNA sequences.

Main Methods:

• Simulation of ancient DNA sequencing data.
• Analysis of seven commonly used adapter trimming and read merging tools.
• Evaluation of tools' accuracy in error correction and read overlap identification.
• Assessment of quality score calculation for merged bases.

Main Results:

• Significant differences were observed in tools' ability to correct errors and identify read overlaps.
• The most substantial differences were in calculating quality scores for merged bases.
• The tool 'leeHom' generally outperformed other tools, while 'fastp' had shortcomings.
• Tool choice did not significantly impact population genetics analyses (PCA).

Conclusions:

• The selection of an appropriate tool is critical and depends on project-specific factors.
• Downstream analyses sensitive to merged read accuracy or quality scores can be significantly affected by tool choice.
• Accurate adapter trimming and read merging are essential for reliable ancient DNA sequence reconstruction.