Biology subjects

Borry, M.

Publications and source records attributed to Borry, M..

6 recordsLinked to original sources

bioRxiv2026

AncientMetagenomeDir dating metadataset highlights need for standardised radiocarbon reporting in ancient DNA

Ancient DNA is a valuable data source for the understanding of our past. However, to effectively interpret this data, it is essential to know the age of the samples from which the DNA is obtained. Although the field of palaeogenomics has been recognised for its robust open data sharing practices, dating information associated with analysed samples is not reported consistently across palaeogenomic studies, nor is it included as metadata in most genetic data repositories. Here, we describe the addition of standardised precise dating information for ancient microbial genomes into the AncientMetagenomeDir metadata repository of published ancient metagenomic samples. This extension currently includes dating information for over 700 ancient microbial genomic datasets, of which 333 are dated using historical, contextual, or stratigraphic methods, and 405 are radiocarbon dated. We quantitatively assess the quality of radiocarbon date reporting and find that, despite established reporting conventions, radiocarbon dating information is often reported inconsistently across ancient metagenomic studies. This new resource provides ancient microbial researchers with standardised dating information that facilitates more accurate and consistent analysis of metagenomic sequencing data. The dataset also highlights the need for greater standardisation of radiocarbon date reporting in original publications in order to allow effective reuse of this and future ancient microbial data.

bioinformatics↗

bioRxiv2023

nf-core/taxprofiler: highly parallelised and flexible pipeline for metagenomic taxonomic classification and profiling

1 AbstractMetagenomic classification tackles the problem of characterising the taxonomic source of all DNA sequencing reads in a sample. A common approach to address the differences and biases between the many different taxonomic classification tools is to run metagenomic data through multiple classification tools and databases. This, however, is a very time-consuming task when performed manually - particularly when combined with the appropriate preprocessing of sequencing reads before the classification. Here we present nf-core/taxprofiler, a highly parallelised read-processing and taxonomic classification pipeline. It is designed for the automated and simultaneous classification and/or profiling of both short- and long-read metagenomic sequencing libraries against a 11 taxonomic classifiers and profilers as well as databases within a single pipeline run. Implemented in Nextflow and as part of the nf-core initiative, the pipeline benefits from high levels of scalability and portability, accommodating from small to extremely large projects on a wide range of computing infrastructure. It has been developed following best-practise software development practises and community support to ensure longevity and adaptability of the pipeline, to help keep it up to date with the field of metagenomics.

genomics↗

bioRxiv2021

PyDamage: automated ancient damage identification and estimation for contigs in ancient DNA de novo assembly

DNA de novo assembly can be used to reconstruct longer stretches of DNA (contigs), including genes and even genomes, from short DNA sequencing reads. Applying this technique to metagenomic data derived from archaeological remains, such as paleofeces and dental calculus, we can investigate past microbiome functional diversity that may be absent or underrepresented in the modern microbiome gene catalogue. However, compared to modern samples, ancient samples are often burdened with environmental contamination, resulting in metagenomic datasets that represent mixtures of ancient and modern DNA. The ability to rapidly and reliably establish the authenticity and integrity of ancient samples is essential for ancient DNA studies, and the ability to distinguish between ancient and modern sequences is particularly important for ancient microbiome studies. Characteristic patterns of ancient DNA damage, namely DNA fragmentation and cytosine deamination (observed as C-to-T transitions) are typically used to authenticate ancient samples and sequences. However, existing tools for inspecting and filtering aDNA damage either compute it at the read level, which leads to high data loss and lower quality when used in combination with de novo assembly, or require manual inspection, which is impractical for ancient assemblies that typically contain tens to hundreds of thousands of contigs. To address these challenges, we designed PyDamage, a robust, automated approach for aDNA damage estimation and authentication of de novo assembled aDNA. PyDamage uses a likelihood ratio based approach to discriminate between truly ancient contigs and contigs originating from modern contamination. We test PyDamage on both simulated, and empirical aDNA data from archaeological paleofeces, and we demonstrate its ability to reliably and automatically identify contigs bearing DNA damage characteristic of aDNA. Coupled with aDNA de novo assembly, PyDamage opens up new doors to explore functional diversity in ancient metagenomic datasets.

bioinformatics↗

bioRxiv2020

Community-curated and standardised metadata of published ancient metagenomic samples with AncientMetagenomeDir

Ancient DNA and RNA are valuable data sources for a wide range of disciplines. Within the field of ancient metagenomics, the number of published genetic datasets has risen dramatically in recent years, and tracking this data for reuse is particularly important for large-scale ecological and evolutionary studies of individual microbial taxa, microbial communities, and metagenomic assemblages. AncientMetagenomeDir (archived at https://doi.org/10.5281/zenodo.3980833) is a collection of indices of published genetic data deriving from ancient microbial samples that provides basic, standardised metadata and accession numbers to allow rapid data retrieval from online repositories. These collections are community-curated and span multiple sub-disciplines in order to ensure adequate breadth and consensus in metadata definitions, as well as longevity of the database. Internal guidelines and automated checks to facilitate compatibility with established sequence-read archives and term-ontologies ensure consistency and interoperability for future meta-analyses. This collection will also assist in standardising metadata reporting for future ancient metagenomic studies.

bioinformatics↗

bioRxiv2020

Reproducible, portable, and effcient ancient genome reconstruction with nf-core/eager

The broadening utilisation of ancient DNA to address archaeological, palaeontological, and biological questions is resulting in a rising diversity in the size of laboratories and scale of analyses being performed. In the context of this heterogeneous landscape, we present nf-core/eager, an advanced and entirely redesigned and extended version of the EAGER pipeline for the analysis of ancient genomic data. This Nextflow pipeline aims to address three main themes: accessibility and adaptability to different computing configurations, reproducibility to ensure robust analytical standards, and updating the pipeline to the latest routine ancient genomic practises. This new version of EAGER has been developed within the nf-core initiative to ensure high-quality software development and maintenance support; contributing to a long-term lifecycle for the pipeline. nf-core/eager will assist in ensuring that ancient DNA sequencing data can be used by a diverse range of research groups and fields.

bioinformatics↗

bioRxiv2019

CoproID predicts the source of coprolites and paleofeces using microbiome composition and host DNA content

Shotgun metagenomics applied to archaeological feces (paleofeces) can bring new insights into the composition and functions of human and animal gut microbiota from the past. However, paleofeces often undergo physical distortions in archaeological sediments, making their source species difficult to identify on the basis of fecal morphology or microscopic features alone. Here we present a reproducible and scalable pipeline using both host and microbial DNA to infer the host source of fecal material. We apply this pipeline to newly sequenced archaeological specimens and show that we are able to distinguish morphologically similar human and canine paleofeces, as well as non-fecal sediments, from a range of archaeological contexts.

microbiology↗