Multiplexing PCR allows the identification of within-species genetic diversity in ancient eDNA

Sedimentary ancient DNA (sedaDNA) has rarely been used to obtain population-level data due to either a lack of taxonomic resolution for the molecular method used, limitations in the reference material or inefficient methods. Here, we present the potential of multiplexing different PCR primers to retrieve population-level genetic data from sedaDNA samples. Vaccinium uliginosum (Ericaceae) is a widespread species with a circumpolar distribution and three lineages for present-day populations. We searched 18 plastid genomes for intraspecific variable regions and developed 61 primers to target these. Initial multiplex PCR testing resulted in a final set of 38 primers. These primers were used to analyse 20 lake sedaDNA samples (11,200 cal. yr BP to present) from five different localities in northern Norway, the Alps and the Polar Urals. All known V. uliginosum lineages in these regions and all primers could be recovered from the sedaDNA data, where for each sample 28.1 primers containing 34.1..., DNA was extracted from 20 sediment samples and 4 extraction/sampling negative controls using a modified DNeasy PowerSoil kit (Qiagen, Germany) protocol in the ancient DNA laboratory at TMU. DNA extracts and negative extraction/sampling controls were amplified with a dual-tagged multiplex primer sets that amplified 38 intraspecific regions on the Vaccinium uliginosum chloroplast.
The OBITools software package was used for the bioinformatics pipeline. Paired-end reads were aligned using SeqPrep (https://github.com/jstjohn/SeqPrep/releases, v1.2). Merged reads were demultiplexed according to the 4 bp primer tags and identical sequences were collapsed. Singleton sequences and those shorter than 10 bp were removed and putative artifactual sequences were identified and removed from the dataset. The multiplex marker data was identified with a reference dataset., The data files are \"Tab-Separated Values\" (TSV) files and can be opened with any text editor, imported into spreadsheet software, analysed with stastical programs such as R, parsed with command line tools or scripting languages.
The Python script can be ran from the command line.
The fasta files are plain text and can be opened in any text editor.