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Metsoja, M.

Publications and source records attributed to Metsoja, M..

2 recordsLinked to original sources

Full-length COI barcodes improve eDNA metabarcoding data denoising relative to mini-barcodes

Animal COI (mitochondrial cytochrome oxidase I) metabarcoding of environmental DNA (eDNA) is increasingly used to assess biodiversity in complex substrates such as soil. However, due to read-length constraints of second-generation sequencing platforms, mini-barcodes have been used instead of the full barcode region. Long-read sequencing technologies now enable the recovery of full-length barcode sequences, and are more commonly applied for studying microbes, but their use for metabarcoding the full-length standard COI barcoding region in animals remains limited. In this study, we compared three COI amplicon sets - 313 bp, 660 bp, and 1,256 bp - amplified from soil eDNA samples and sequenced using Illumina and PacBio platforms to evaluate their overall concurrence, the effectiveness of identifying nuclear mitochondrial DNA segments (NUMTs) and chimeras, as well as their respective taxonomic resolution. The long-read datasets exhibited a higher identification rate of NUMTs and true chimeras, suggesting that longer sequences improve the detection of noise in COI metabarcoding data, thereby reducing the occurrence of spurious taxa. Taxonomy assignment confidence was similar between the 313 bp and 660 bp datasets, whereas extending the amplicon beyond the standard COI barcode region (1,256 bp) reduced confidence, likely because longer reads extend into regions poorly represented in barcode reference databases. Despite substantially lower sequencing depth in the 660 bp dataset, per-sample OTU richness did not differ significantly from that recovered with the Illumina 313 bp amplicon set. Similarly, the relationships between samples were strongly correlated across the detected OTU communities, indicating consistent ecological interpretations between short and long amplicons. We conclude that the standard [~]658 bp COI barcode is an optimal marker for soil animal metabarcoding from eDNA, balancing target recovery, artifact detection, taxonomic assignment and ecological interpretability. As COI eDNA metabarcoding becomes increasingly used in biodiversity assessment and is increasingly adopted in large-scale monitoring initiatives, this study provides methodological guidance for improving the robustness of soil animal community biomonitoring.

ecology↗

Sampling design and sample processing affect soil biodiversity assessments

Biodiversity surveys require an appropriate sampling design for optimal performance and comparability across space and time and across studies. Based on PacBio and Illumina amplicon sequencing of animals, bacteria and fungi, we assessed and compared various soil sampling designs from widely used continental and global metabarcoding-based biodiversity projects. Sampling designs revealed up to 27-fold, 6-fold and 15-fold differences in biodiversity estimates for animals, bacteria and fungi, respectively. Taxonomic coverage depended mostly on the number of subsamples but not sampling area within the 347-1790 m2, 428-1924 m2, 327-1790 m2 plot size range for animals, bacteria and fungi, respectively. Additional sampling of subsoil did not add significantly to diversity estimates of animals and fungi, although there was a slight positive effect on bacteria. Both soil pooling (compositing subsamples before DNA extraction) and DNA pooling (combining DNA extracts prior to PCR) reduced differences between sampling designs by decreasing diversity estimates in designs with many subsamples while increasing them in designs with fewer subsamples. However, pooling did not eliminate the influence of sampling factors (soil depth, sampling area and sample size). DNA pooling outperformed soil pooling in inventorying animals and fungi but not bacteria. Pooling had no effect on recovering rare biological species or sequencing artefacts. Soil pooling saved from 79.5% to 98.3% of labour and analytical costs compared with no pooling, depending on the number of pooled subsamples. The remarkable impact of sampling design on community diversity and composition should be considered during data collection and meta-analyses compiling data from different sampling designs.

microbiology↗