A 2-million-year-old microbial and viral communities from the Kap København Formation in North Greenland

Fernàndez-Guerra, Antonio; Borrel, Guillaume; Delmont, Tom O.; Elberling, Bo; Eren, A. Murat; Gribaldo, Simonetta; Jochheim, Annika; Henriksen, Rasmus Amund; Hinrichs, Kai‐Uwe; Korneliussen, Thorfinn Sand; Krupovìč, Mart; Larsen, Nicolaj K.; Laso-Pérez, Rafael; Pedersen, Mikkel Winther; Pedersen, Vivi Kathrine; Sand, Karina K.; Sikora, Martin; Steinegger, Martin; Veseli, Iva; Wörmer, Lars; Zhao, Lei; Žure, Marina; Kjær, Kurt H.; Willerslev, Eske

doi:10.1101/2023.06.10.544454

Cited by 7 publications

(2 citation statements)

References 100 publications

(114 reference statements)

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“…The availability of ancient DNA (aDNA) sequence data has revolutionized our understanding of evolutionary processes and natural history ( Green et al 2010 , van der Valk et al 2021 ) but also poses analytical challenges due to the degraded nature of aDNA and the presence of environmental contaminants ( Orlando et al 2021 ). Further, as new boundaries for aDNA recovery beyond the million year time range are tested ( van der Valk et al 2021 , Kjær et al 2022 , Fernandez-Guerra et al 2023 ), the ability to robustly study increasingly damaged samples from diverged populations requires an assessment of current alignment tools, as target data become more diverged from reference genomes. 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.…”

Section: Introductionmentioning

confidence: 99%

Unravelling reference bias in ancient DNA datasets

Dolenz,

van der Valk,

Jin

et al. 2024

Bioinformatics

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Motivation The alignment of sequencing reads is a critical step in the characterization of ancient genomes. However, reference bias and spurious mappings pose a significant challenge, particularly as cutting-edge wet lab methods generate datasets that push the boundaries of alignment tools. Reference bias occurs when reference alleles are favoured over alternative alleles during mapping, whereas spurious mappings stem from either contamination or when endogenous reads fail to align to their correct position. Previous work has shown that these phenomena are correlated with read length but a more thorough investigation of reference bias and spurious mappings for ancient DNA has been lacking. Here, we use a range of empirical and simulated palaeogenomic datasets to investigate the impacts of mapping tools, quality thresholds, and reference genome, on mismatch rates across read lengths. Results For these analyses, we introduce AMBER, a new bioinformatics tool for assessing the quality of ancient DNA mapping directly from BAM-files and informing on reference bias, read-length cut-offs and reference selection. AMBER rapidly and simultaneously computes the sequence read mapping bias in the form of the mismatch rates per read length, cytosine deamination profiles at both CpG and non-CpG sites, fragment length distributions, and genomic breadth and depth of coverage. Using AMBER, we find that mapping algorithms and quality threshold choices dictate reference bias and rates of spurious alignment at different read lengths in a predictable manner, suggesting that optimised mapping parameters for each read length will be a key step in alleviating reference bias and spurious mappings. Availability AMBER is available for non-commercial use on GitHub (https://github.com/tvandervalk/AMBER.git). Scripts used to generate and analyze simulated data sets are available on Github (https://github.com/sdolenz/refbias_scripts). Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Introductionmentioning

confidence: 99%

Unravelling reference bias in ancient DNA datasets

Dolenz,

van der Valk,

Jin

et al. 2024

Bioinformatics

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“…Analyzing aDNA has proven to be an essential tool for researchers to study the past. It has, for example, aided a deeper understanding of ancestral population history [1, 2] and the dynamics of ancient ecosystems [7, 12].…”

Section: Introductionmentioning

confidence: 99%

Revisiting the Briggs ancient DNA damage model: a fast regression method to estimate postmortem damage

Zhao,

Heriksen,

Ramsøe

et al. 2023

Preprint

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MotivationOne essential initial step in the analysis of ancient DNA is to authenticate its ancientness to ensure reliable conclusions. That is, meticulously assessing whether next-generation sequencing reads exhibit ancient characteristics, with a particular focus on the postmortem damage (PMD) signal induced by cytosine deamination in the fragments termini. We present a novel statistical method implementation in a fast multithreaded program ngsBriggs that enables the rapid quantification of PMD by calculation of the Briggs ancient damage model parameters (Briggs parameters).ResultsUsing a fast multinomial regression approach, ngsBriggs accurately models the Briggs parameters, quantifying the PMD signal from single and double-stranded DNA regions. We revisit and extend the original Briggs model, with ngsBriggs modeling PMD signals for contemporary sequencing platforms. Furthermore, ngsBriggs asserts itself as a reliable and consistent tool, by accurately estimating the Briggs parameters across a variety of contamination levels. The classification accuracy of ngsBriggs significantly exceeds the current tool available when discerning ancient-from modern sequencing reads to decontaminate samples. Our novel method and implementation ngsBriggs outperforms existing tools regarding computational speed and accuracy, establishing its practicality and usability. Our tool, ngsBriggs offers a practical and accurate toolset for researchers seeking to authenticate ancient DNA and improve the quality of their data.Availabilityhttps://github.com/lz398/metadamage_briggs

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Enriching barcoding markers in environmental samples utilizing a phylogenetic probe design: Insights from mock communities

Nota,

Orlando,

Marchesini

et al. 2024

Environmental DNA

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Hybridization capture is an emerging method making use of short oligonucleotide baits to enrich DNA libraries for genomic fragments of specific organisms thus enabling detection of their presence in environmental samples. Although it offers a primer‐independent alternative to metabarcoding, little empirical work has been dedicated to characterizing the underlying biases and coupled implications for biological interpretation. Moreover, few published bioinformatic pipelines are available for designing polynucleotide capture baits from a reference sequence collection. We designed RNA‐baits specifically targeting two chloroplast barcoding genes matK and rbcL to reveal the plant taxonomic diversity present in a given environmental sample. Our approach leverages the sensitivity of hybridization capture and the capacity of high‐throughput DNA sequencing instruments. It builds on a new and universal method based on ancestral sequence reconstruction, ultimately limiting the number of bait‐probes required and reducing experimental costs, while accessing high levels of taxonomic diversity. Our bait‐set selectively targets four main plant orders (Fagales, Pinales, Asterales, and Poales), representing ~18% of all described vascular plants. This is achieved through the use of only 4084 baits, each 80 nucleotides in length (80‐mer), capturing ~1.0–1.6 k nucleotide sequences from each taxon. Tests on mock communities revealed important factors influencing capture efficiency and relative abundance estimates, including GC‐content, the overall target length per taxa, and the bait density and mean number of mismatches to the bait sequence. Our results show that hybridization capture, like metabarcoding, requires caution when interpreting results quantitatively within (paleo)‐ecological studies. Biases detected in this work have the potential to be mitigated with bait designs that avoid extreme base compositional biases and balancing bait targets across taxa. However, we strongly recommend the use of mock communities and read simulations to quantify the accuracy of taxonomic representation when using new bait designs.

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A 2-million-year-old microbial and viral communities from the Kap København Formation in North Greenland

Cited by 7 publications

References 100 publications

Unravelling reference bias in ancient DNA datasets

Unravelling reference bias in ancient DNA datasets

Revisiting the Briggs ancient DNA damage model: a fast regression method to estimate postmortem damage

Enriching barcoding markers in environmental samples utilizing a phylogenetic probe design: Insights from mock communities

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