Systematic benchmark of ancient DNA read mapping
Abstract
The current standard practice for assembling individual genomes involves mapping millions of short DNA sequences (also known as DNA 'reads') against a pre-constructed reference genome. Mapping vast amounts of short reads in a timely manner is a computationally challenging task that inevitably produces artefacts, including biases against alleles not found in the reference genome. This reference bias and other mapping artefacts are expected to be exacerbated in ancient DNA (aDNA) studies, which rely on the analysis of low quantities of damaged and very short DNA fragments (~30-80 bp). Nevertheless, the current gold-standard mapping strategies for aDNA studies have effectively remained unchanged for nearly a decade, during which time new software has emerged. In this study, we used simulated aDNA reads from three different human populations to benchmark the performance of 30 distinct mapping strategies implemented across four different read mapping software-BWA-aln, BWA-mem, NovoAlign and Bowtie2-and quantified the impact of reference bias in downstream population genetic analyses. We show that specific NovoAlign, BWA-aln and BWA-mem parameterizations achieve high mapping precision with low levels of reference bias, particularly after filtering out reads with low mapping qualities. However, unbiased NovoAlign results required the use of an IUPAC reference genome. While relevant only to aDNA projects where reference population data are available, the benefit of using an IUPAC reference demonstrates the value of incorporating population genetic information into the aDNA mapping process, echoing recent results based on graph genome representations.
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The most common mapping tools for aDNA reads are BWA-aln, Bowtie2, and BWA-mem, each with applied aDNA parameters and post-filtering MQ scores of generally ≥25.
“Presently, the most common mapping tools for aDNA reads are BWA-aln (also known as BWA-backtrack), Bowtie2, and BWA-mem, each with applied aDNA parameters (Poullet and Orlando 2020, Oliva et al. 2021) and post-filtering map quality (MQ) scores of generally ≥25.”
From Unravelling reference bias in ancient DNA datasets (2024) · cites this paper as Oliva et al. 2021
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Unravelling reference bias in ancient DNA datasets
Dolenz, S., van der Valk, T., Jin, C., Oppenheimer, J., Sharif, M. B., Orlando, L., Shapiro, B., Dalén, L., & Heintzman, P. D. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae436 · Cited by 33 · see citing works
“Presently, the most common mapping tools for aDNA reads are BWA-aln (also known as BWA-backtrack), Bowtie2, and BWA-mem, each with applied aDNA parameters (Poullet and Orlando 2020, Oliva et al. 2021) and post-filtering map quality (MQ) scores of generally ≥ 25.”
BackgroundMethod
- Authors
- Oliva, A., Tobler, R., Cooper, A., Llamas, B., & Souilmi, Y.
- Affiliations
- The University of Adelaide (AU)
- South Australian Museum (AU)
- Corresponding author
- Souilmi, Yassine
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-04-08
- Volume
- 22
- Issue
- 5
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W3151257524
- Cited by
- 63
- References
- 44
- Citations by year
- 2026: 16 · 2025: 15 · 2024: 19 · 2023: 6 · 2022: 2 · 2021: 4 · 2014: 1
- FWCI
- 2.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Briefings in Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Funders
- Australian Research Council (DP190103705)
- ARC PhD Scholarship (IN180100017)
- ARC DECRA Fellowship (DE190101069)
- ARC Laureate Fellowship (FL140100260)
- ARC Future Fellowship (FT170100448)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- ancient DNA, read mapping, reference bias, BWA, Bowtie2, population genetic analysis
- MeSH terms
- DNA, Ancient, Algorithms, Humans, Software, Reproducibility of Results, Genome, Human, Sequence Alignment, Sequence Analysis, DNA, Computational Biology, Benchmarking, Polymorphism, Single Nucleotide, High-Throughput Nucleotide Sequencing
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