DOI: 10.5061/dryad.05qfttf3x
title: Fungus and plant sedimentary ancient DNA metabarcoding data from five lakes in Siberia

description: Here we provide data on lake sediment metabarcoding on sedimentary ancient
 DNA (sedaDNA) from five lake cores from Siberia. Our dataset includes 70
 sediment core samples spanning the last about 47.000 years. We applied a
 PCR-based approach called metabarcoding to amplify specific DNA target
 sequences: for fungus metabarcoding, we used the ITS marker alongside with
 the p6 loop trnL chloroplast marker for vegetation metabarcoding. The
 amplicons were analysed towards their composition with Next Generation
 Sequencing on 5 sequencing runs (APMG-17, APMG-20 and ATBH-2 for the
 fungus data; APMG-12 and APMG-29 for the vegetation). The data were used
 in the publication of von Hippel et al. (2022, Quaternary Science Reviews,
 accepted). All samples marked with asterisks in the *samples_ages files
 were not included in the publication.
description: The sedimentary ancient DNA
 (sedaDNA) was extracted from the samples using the DNeasy PowerMax Soil
 Kit. We amplified the plant DNA using the established chloroplast p6 trnL
 loop marker. For the fungus DNA, we used the ITS1 marker by Seeber et al.
 (2022, Environmental DNA; https://doi.org/10.1002/edn3.315). The plant metabarcoding was conducted in 3 replicates while the fungus metabarcoding was repeated 6 times. In total, we sequenced the data on five different Illumina sequencing runs. Each sequencing data consist of raw R1.fastq and R2.fastq files. We also provide the Obitools pipeline script for the analysis of the data as well as the databases and unique tag-files. The resulting final annotation files are attached as well.
description: # Fungus and plant sedimentary ancient DNA metabarcoding data from five
 lakes in Siberia Dataset DOI:
 [10.5061/dryad.05qfttf3x](10.5061/dryad.05qfttf3x) ## Description of the
 data and file structure This data submission includes ancient DNA
 metabarcoding results from five Siberian lake sediment cores. It is
 comprised of fungal and plant DNA datasets (raw data and scripts). The
 data has been included in the publication von Hippel et al. (2022).
 [https://doi.org/10.1016/j.quascirev.2022.107758](https://doi.org/10.1016/j.quascirev.2022.107758)  The dataset is prepared for the manuscript "Long-term fungus-plant covariation from multi-site sedimentary ancient DNA metabarcoding". It contains the processing of the raw sequencing data using bioinfomatics tools. We used OBItools (Boyer et al., 2016) and sumaclust (Mercier et al., 2013) for the processing of the sequencing data. In the data files, EB stands for "extraction blank" and NTC is "non-template control". The age of the samples is given in "cal. years BP" = "calibrated years before present", while BP refers to the year 1950. Below is the detailed data organisation:  ### Fungi metabarcoding: 1_raw_data: The raw sequencing files for APMG-17, APMG-20, and ATBH-2 * R1 = Forward: *_R1.fastq * R2 = Reverse: *_R2.fastq 2_scripts: The metabarcoding pipeline for analyzing the raw sequencing data using OBITools * README_Obitools_Pipeline_Fungi.txt 3_tagfile: de-multiplex tagged pooled samples * tagfile_APMG-17.txt * tagfile_APMG-20.txt * tagfile_ATBH-2.txt 4_database: the UNITE and embl142 release databases * database = UNITE_ITS_database.fasta * database = embl142_ITS_database.fasta 5_dataset: output of the metabarcoding pipeline and final dataset. We also provide the metadata for the samples. * final_table_embl142: all_fungi_sumaclust97_centers_embl142_anno.txt * final_table_UNITE: all_fungi_sumaclust97_centers_UNITE_anno.txt * APMG-17_samples_ages.xlsx * APMG-20_samples_ages.xlsx * ATBH-2_samples_ages.xlsx ### Plant metabarcoding: 1_raw_data: The raw sequencing files for APGM-12 and APMG-29 * R1 = Forward: *_R1.fastq * R2 = Reverse: *_R2.fastq 2_scripts: The metabarcoding pipeline for analyzing the raw sequencing data using OBITools\ * README_Obitools_Pipeline_Vegetation.txt 3_tagfile: de-multiplex tagged pooled samples * tagfile_APMG-12.txt * tagfile_APMG-29.txt 4_database: the Arctic and Boreal vascular plant and bryophyte database * database = arctborbryo_gh_database.fasta 5_dataset: output of the metabarcoding pipeline and final dataset. We also provide the metadata of the samples. * plant_APMG-12_unique_l10_c10_clean_arctborbryo_anno.txt * plant_APMG-29_unique_l10_c10_clean_arctborbryo_anno.txt * APMG-12_samples_ages.xlsx * APMG-29_samples_ages.xlsx