DNAharvester: A Nextflow Pipeline for Analysing Highly Degraded DNA from Ancient and Historical Specimens

Abstract Motivation Ancient DNA (aDNA) research has advanced rapidly with the development of high-throughput sequencing, enabling genome-wide analyses of large collections of prehistoric specimens. However, analysing palaeontological and archaeological material with highly degraded DNA constitutes a major bioinformatic challenge. DNA from such samples is characterized by short fragment lengths, low endogenous content, post-mortem damage, and cross-species contamination, which can increase spurious mapping and reference bias, affecting downstream population genetic inferences. Results We present DNAharvester, a modular and reproducible pipeline designed specifically for processing highly degraded DNA from ancient and historical specimens. DNAharvester integrates metagenomic filtering, competitive mapping, adaptive aligner selection (incorporating BWA-aln, BWA-mem, and Bowtie2), and systematic evaluation of reference bias and spurious mapping. By incorporating flexible mapping and filtering strategies, the pipeline can be adapted to varying sample preservation, focusing on maximizing authentic data recovery. DNAharvester features subworkflows for iterative assembly of mitogenomes, identification of genomic repeats and CpG sites, taxonomic classification, microbial/pathogen screening, genetic sex determination, and variant calling. To accommodate varying sequencing depths, the pipeline supports diploid variant calling, genotype likelihood estimation, and pseudo-haploid random allele calling. We validated the pipeline using simulated and empirical datasets, demonstrating its ability to systematically mitigate complex background contamination while preserving authentic genomic signals. By streamlining complex bioinformatic tasks through simple configuration files, DNAharvester establishes a standardized approach for analysing aDNA datasets and makes genomic analyses of ancient remains accessible to the broader research community. Availability and Implementation Implemented in Nextflow, DNAharvester provides a highly scalable, containerized framework that enhances reproducibility, portability, and robustness in aDNA analyses. DNAharvester is open source under the GNU General Public License v3.0 and freely available at https://github.com/NBISweden/DNAharvester. Supplementary Information Supplementary data are available at Bioinformatics online and Zenodo repository: https://doi.org/10.5281/zenodo.22725211

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Publication Details

Journal
Bioinformatics
Published
2026-10-15
DOI
https://doi.org/10.1093/bioinformatics/btag782
Primary Topic
Forensic and Genetic Research
Type
article
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article

DNAharvester: A Nextflow Pipeline for Analysing Highly Degraded DNA from Ancient and Historical Specimens

Verena Esther Kutschera, Tom van der Valk, Love Dalén, Edana Lord et al.
Bioinformatics
Forensic and Genetic Research
article

DNAharvester: A Nextflow Pipeline for Analysing Highly Degraded DNA from Ancient and Historical Specimens

Verena Esther Kutschera, Tom van der Valk, Love Dalén, Edana Lord, Juan Camilo Chacón-Duque, David Díez‐del‐Molino, Peter D. Heintzman, Jonas Oppenheimer, Nikolay Oskolkov, Benjamin Guinet, Bilal Sharif
article en

Abstract

Abstract Motivation Ancient DNA (aDNA) research has advanced rapidly with the development of high-throughput sequencing, enabling genome-wide analyses of large collections of prehistoric specimens. However, analysing palaeontological and archaeological material with highly degraded DNA constitutes a major bioinformatic challenge. DNA from such samples is characterized by short fragment lengths, low endogenous content, post-mortem damage, and cross-species contamination, which can increase spurious mapping and reference bias, affecting downstream population genetic inferences. Results We present DNAharvester, a modular and reproducible pipeline designed specifically for processing highly degraded DNA from ancient and historical specimens. DNAharvester integrates metagenomic filtering, competitive mapping, adaptive aligner selection (incorporating BWA-aln, BWA-mem, and Bowtie2), and systematic evaluation of reference bias and spurious mapping. By incorporating flexible mapping and filtering strategies, the pipeline can be adapted to varying sample preservation, focusing on maximizing authentic data recovery. DNAharvester features subworkflows for iterative assembly of mitogenomes, identification of genomic repeats and CpG sites, taxonomic classification, microbial/pathogen screening, genetic sex determination, and variant calling. To accommodate varying sequencing depths, the pipeline supports diploid variant calling, genotype likelihood estimation, and pseudo-haploid random allele calling. We validated the pipeline using simulated and empirical datasets, demonstrating its ability to systematically mitigate complex background contamination while preserving authentic genomic signals. By streamlining complex bioinformatic tasks through simple configuration files, DNAharvester establishes a standardized approach for analysing aDNA datasets and makes genomic analyses of ancient remains accessible to the broader research community. Availability and Implementation Implemented in Nextflow, DNAharvester provides a highly scalable, containerized framework that enhances reproducibility, portability, and robustness in aDNA analyses. DNAharvester is open source under the GNU General Public License v3.0 and freely available at https://github.com/NBISweden/DNAharvester. Supplementary Information Supplementary data are available at Bioinformatics online and Zenodo repository: https://doi.org/10.5281/zenodo.22725211

Bioinformatics
Uppsala University (SE), Stockholm University (SE), Lund University (SE), Science for Life Laboratory (SE), Swedish Museum of Natural History (SE), Geological Survey of Sweden (SE), Latvijas Organiskās Sintēzes Institūts (LV), Royal Botanic Garden Sydney (AU), Centre for Palaeogenetics (SE)
Openalex Percentile: Top 15%
Forensic and Genetic Research
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