DOI: 10.5061/dryad.vdncjsxth
title: Plant DNA metabarcoding record from a sediment core from Lake Naleng, southeastern Tibetan Plateau

description: Here, we provide the raw plant DNA metabarcoding data archived in Lake
 Naleng sediment core spanning the late-glacial to the present (17,700 to 0
 cal yr BP). Lake Naleng (31.10° N, 99.7°5 E, 4200 above sea level) is
 situated in a glacially-formed basin on the southeastern Tibetan Plateau.
 It is an alpine freshwater lake with a maximum water depth of 36.7 m, an
 open surface area of 1.7 km2,  a specific conductivity of 0.045
 mS/cm, a Secchi depth of 2.9 m, a pH of 8.1, a dissolved oxygen content of
 6.9 mg/L (measured 19.09.2003), and a catchment area of 128 km2. The
 catchment is used for seasonal grazing by yaks and sheep. The
 lake is located at the upper treeline with main vegetation of alpine
 meadow. The detailed geographic, biogeochemical and vegetation
 information are described in Kramer et al., 2010a, b, c (doi:
 10.1007/s00334-009-0219-5, 10.1016/j.yqres.2009.12.003, and
 10.1016/j.palaeo.2009.12.001) and Opitz et al., 2015 (doi:
 http://dx.doi.org/10.1016/j.quascirev.2015.03.011). The lake sediment
 cores (17.81 m) was recovered from water depth of 32 m using an UWITEC
 (Niederreiter 60) piston corer system on the frozen lake surface in
 February 2004 (Kramer et al., 2010a).  Due to lack of
 macrofossil remains, ten bulk organic carbon samples were
 selected for AMS (accelerator mass spectrometry) radiocarbon
 dating at the Leibniz Laboratory, Kiel. The age-depth model
 was built after subtracting the lake reservoir effect
 of 1500 cal yr BP. The original 14C dating and
 chronology is given by Kramer et al., 2010a, b, c. In this
 project, we inferred the plant richness based on DNA data
 and simulated glacial dynamics and habitat area within lake
 catchment. We synthesized these data with published palaeoenvironmental
 data  (temperature, soil development, and treeline location) to
 find the direct factor of plant richness variations over the past
 ~18,000 years. According to the inferred relationship, we predicted the
 plant richness change in the next 250 years (until 2300 C.E.).
description: <strong>1. Sedimentary ancient DNA isolation, polymerase
 chain reactions (PCR), and purification and
 pooling</strong> Sedimentary ancient DNA
 (sedaDNA) was extracted from about 3–10 g of sediment using the
 PowerMax<sup>®</sup> Soil DNA Isolation Kit (MoBio
 Laboratories, Inc., USA) with a modifed instructions in a dedicated
 ancient DNA laboratory.  The plant sedaDNA was amplified using general
 plant gh primer targeting the P6 loop (10-143 bp) of chloroplast
 <em>trn</em>L (Taberlet et al., 2007).  Each PCR reaction (25
 µL) were prepared in ancient DNA laboratory and amplified in PCR
 thermocycler in post-PCR laboratory. Then, each PCR batch was run in
 agarose gel electrophoresis (2%) to check if it can be purified. Each PCR
 batch was replicated until obtaining two positive PCR products for each
 sediment sample with associated negative controls.  Positive means: the
 brightest staning is in a range of 100-200 bp and the gene band is
 evidently longer than one of control. The gene band with length &lt;
 50 bp is considered as primer dimer.  All qualified PCR replicates were
 purified with the MinElute PCR Purification Kit (Qiagen, Germany) in
 post-PCR lab.  Afterwards, 1 μL of PCR product was measured with the
 ds-DNA BR Assay and the Qubit<sup>®</sup> 2.0 fluorometer
 (Invitrogen, USA). Finally, all purified PCR products were equimolarly
 pooled.  It should be note that the ancient DNA lab and the post-PCR lab
 are located in different buildings.  The genetic lab work was done in
 Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research,
 Potsdam.  <strong>2. High throughput
 sequencing</strong> The pooled PCR products were
 sequenced on the Illumina HiSeq 2500 platform (2 x 125 bp, paired-end
 reads) at <i>Fasteris</i> SA sequencing service, Switzerland.
 The mode is HiSeq High Output Version 4 with the HiSeq SBS Kit v4. Our
 project resulted in 9.5 Gb with 37,922,797 generated clusters &gt;=
 Q30. <strong>3.
 Bioinformatics</strong> We used OBITools (Boyer
 et al., 2016) to do the upstream analysis of  the sequencing data. The raw
 sequecning data (two fastq files), scripts for creating the taxonomic
 database and analyzing the raw sequencing data are enclosed as well as the
 tag-sample-matirx.
description: 1. There are no missing values. 2.
 Metabarcoding data: the raw NGS data    
 Forward: 170421_SND393_B_L004_HUA-7_R1.fastq.gz    
 Reverse: 170421_SND393_B_L004_HUA-7_R2.fastq.gz
 3. NGSfilter file: tag-sample-matrix for demultiplexing the NGS
 data in ObiTools.     Filename:
 1-tagfile_04NC.txt 4. ObiTools script for building a
 reference database (v. embl127) for taxonomic assignment.
     Filename: 2-embl127creation_OBITools.txt
 5. ObiTools script for analyzing the metabarcoding data
     Filename: 3-MetabarcodingData_analysis_OBITools.txt
 6. Two reference databases for taxonomic assignment in
 ObiTools     Filename:
 4-arctborbryo_gh.fasta; 5-g_h_embl127_new_taxon_good.fasta
 7. Taxonomy dump files of Arctic and Boreal vascular plant and
 bryophyte reference libraries  
   Filename: 6-ecochange.zip.gz 8. Scientists who are
 working on palaeoecology, especially in using environmental DNA from lake
 sediment core, may be interested in this data.