Data from: New environmental metabarcodes for analysing soil DNA: potential for studying past and present ecosystems

Metabarcoding approaches use total and typically degraded DNA from environmental samples to analyse biotic assemblages and can potentially be carried out for any kinds of organisms in an ecosystem. These analyses rely on specific markers, here called metabarcodes, which should be optimized for taxonomic resolution, minimal bias in amplification of the target organism group and short sequence length. Using bioinformatic tools, we developed metabarcodes for several groups of organisms: fungi, bryophytes, enchytraeids, beetles and birds. The ability of these metabarcodes to amplify the target groups was systematically evaluated by (1) in silico PCRs using all standard sequences in the EMBL public database as templates, (2) in vitro PCRs of DNA extracts from surface soil samples from a site in Varanger, northern Norway, and (3) in vitro PCRs of DNA extracts from permanently frozen sediment samples of late-Pleistocene age (~ 16 000–50 000 yr BP) from two Siberian sites, Duvanny Yar and Main River. Comparison of the results from the in silico PCR with those obtained in vitro showed that the in silico approach offered a reliable estimate of the suitability of a marker. All target groups were detected in the environmental DNA, but we found large variation in the level of detection among the groups and between modern and ancient samples. Success rates for the Pleistocene samples were highest for fungal DNA, whereas bryophyte, beetle and bird sequences could also be retrieved, but to a much lesser degree. The metabarcoding approach has considerable potential for biodiversity screening of modern samples and also as a paleoecological tool

Data from: New environmental metabarcodes for analysing soil DNA: potential for studying past and present ecosystems

Metabarcoding approaches use total and typically degraded DNA from environmental samples to analyse biotic assemblages and can potentially be carried out for any kinds of organisms in an ecosystem. These analyses rely on specific markers, here called metabarcodes, which should be optimized for taxonomic resolution, minimal bias in amplification of the target organism group and short sequence length. Using bioinformatic tools, we developed metabarcodes for several groups of organisms: fungi, bryophytes, enchytraeids, beetles and birds. The ability of these metabarcodes to amplify the target groups was systematically evaluated by (1) in silico PCRs using all standard sequences in the EMBL public database as templates, (2) in vitro PCRs of DNA extracts from surface soil samples from a site in Varanger, northern Norway, and (3) in vitro PCRs of DNA extracts from permanently frozen sediment samples of late-Pleistocene age (~ 16 000&ndash;50 000 yr BP) from two Siberian sites, Duvanny Yar and Main River. Comparison of the results from the in silico PCR with those obtained in vitro showed that the in silico approach offered a reliable estimate of the suitability of a marker. All target groups were detected in the environmental DNA, but we found large variation in the level of detection among the groups and between modern and ancient samples. Success rates for the Pleistocene samples were highest for fungal DNA, whereas bryophyte, beetle and bird sequences could also be retrieved, but to a much lesser degree. The metabarcoding approach has considerable potential for biodiversity screening of modern samples and also as a paleoecological tool.,Epp_etal_metabarcodes_dryadThis file contains all consensus sequences retrieved from clones of environmental samples and referred to in Table S6 of the Supplementary material.,</span

Epp_etal_metabarcodes_dryad

This file contains all consensus sequences retrieved from clones of environmental samples and referred to in Table S6 of the Supplementary material

Epp_etal_metabarcodes_dryad

This file contains all consensus sequences retrieved from clones of environmental samples and referred to in Table S6 of the Supplementary material

Genotyping errors: Causes, consequences and solutions

Times Cited: 66International audienceAlthough genotyping errors affect most data and can markedly influence the biological conclusions of a study, they are too often neglected. Errors have various causes, but their occurrence and effect can be limited by considering these causes in the production and analysis of the data. Procedures that have been developed for dealing with errors in linkage studies, forensic analyses and non-invasive genotyping should be applied more broadly to any genetic study. We propose a protocol for estimating error rates and recommend that these measures be systemically reported to attest the reliability of published genotyping studies

Megafauna diet data

Fasta file containing sequence data

Reference database Boreal (gh)

Fasta file of the Boreal reference database (P6 loop of the trnL

Data from: Fifty thousand years of arctic vegetation and megafaunal diet

Although it is generally agreed that the arctic flora is among the youngest and least diverse on Earth, the processes that shaped it are poorly understood. Here we present 50 thousand years (kyr) of arctic vegetation history, derived from the first large-scale ancient DNA metabarcoding study of circumpolar plant diversity. For this interval we additionally explore nematode diversity as a proxy for modelling vegetation cover and soil quality, and diets of herbivorous megafaunal mammals, many of which became extinct around 10 kyr BP (before present). For much of the period investigated, arctic vegetation consisted of dry steppe tundra dominated by forbs (non-graminoid herbaceous vascular plants). During the Last Glacial Maximum (25–15 kyr BP), diversity declined markedly, although forbs remained dominant. Much changed after 10 kyr BP, with the appearance of moist tundra dominated by woody plants and graminoids. Our analyses indicate that both graminoids and forbs would have featured in megafaunal diets. As such our findings question the predominance of a late Quaternary graminoid-dominated arctic “mammoth steppe”

Reference database Arctic (ITSAst)

Fasta file of the Arctic reference database (ITSAst