Biology subjects

Bergfeldt, N.

Publications and source records attributed to Bergfeldt, N..

2 recordsLinked to original sources

bioRxiv2025

Ancestry, admixture, and pathogens in contemporaneous Neolithic farmers and foragers on the Island of Gotland

Two archaeological cultural complexes coexisted on Gotland for over 500 years, between [~]3300 and 2800 calBCE, i.e. the Neolithic Funnelbeaker culture (FBC), and the Pitted ware culture (PWC). The ancestry of the FBC farmers and PWC marine foragers largely aligns with European Neolithic Farmers and European Mesolithic foragers, respectively, but the direct interactions between the groups on Gotland is not understood. We present a Middle Neolithic (MN) high-coverage genome and a Late Neolithic (LN) low-coverage genome from the Ansarve FBC dolmen. We investigate ancestry, admixture, and pathogens among these MN farmers (n =6), foragers (n=19), and a LN individual. We find that recent gene-flow between farmers and foragers could have taken place, although most gene-flow happened prior to their coexistence on the island. We also find evidence of different Yersinia pestis strains in the three cultural groups, showing that the pestis was widespread among groups with different subsistence strategies.

genomics↗

bioRxiv2022

aMeta: an accurate and memory-efficient ancient Metagenomic profiling workflow

Analysis of microbial data from archaeological samples is a rapidly growing field with a great potential for understanding ancient environments, lifestyles and disease spread in the past. However, high error rates have been a long-standing challenge in ancient metagenomics analysis. This is also complicated by a limited choice of ancient microbiome specific computational frameworks that meet the growing computational demands of the field. Here, we propose aMeta, an accurate ancient Metagenomic profiling workflow designed primarily to minimize the amount of false discoveries and computer memory requirements. Using simulated ancient metagenomic samples, we benchmark aMeta against a current state-of-the-art workflow, and demonstrate its superior sensitivity and specificity in both microbial detection and authentication, as well as substantially lower usage of computer memory. aMeta is implemented as a Snakemake workflow to facilitate use and reproducibility.

bioinformatics↗