Biology subjects

Mikryukov, V.

Publications and source records attributed to Mikryukov, V..

6 recordsLinked to original sources

bioRxiv2026

Polymerase and primer biases in eukaryote ultra-long-read metabarcoding

Ultra-long-read metabarcoding is a recently developed method for biodiversity monitoring that enables both high-accuracy species-level identification and reliable phylogenetic placement of taxa. Ultra-long-read analyses require high-processivity DNA polymerases for amplicons and primer pairs that fully cover the targeted taxonomic groups. So far, there is no published information on the relative suitability of commercial high-processivity polymerase kits and on the relative performance of primer pairs targeting a DNA fragment spanning much of the 18S, ITS and 28S rRNA gene regions in eukaryotes. Using PacBio sequencing, we assessed the performance of five commercial high-processivity DNA polymerases and three ultra-long marker primer pairs relative to a commonly used full-ITS primer pair on producing artefacts and recovering biodiversity in two mock communities and 10 soil samples. Our analyses revealed great differences in both polymerases and primer pairs in data quality and biodiversity. For testing evolutionary hypotheses, we recommend using the Solis or Fusion polymerases and the Euk575F-21Rngs primer pair in ultra-long-read metabarcoding analyses of soil eukaryotes. Compared with a previous study using the same DNA samples, the ultra-long amplicons revealed substantially lower biodiversity than medium-sized, full-ITS amplicons across taxonomic levels, suggesting that medium-sized amplicons may be better suited for routine soil eukaryote biodiversity monitoring than ultra-long amplicons.

ecology↗

bioRxiv2026

Benchmarking full-length ITS metabarcoding across Illumina 2x500, PacBio, and Oxford Nanopore sequencing using mock and soil communities

Metabarcoding is a powerful tool for biodiversity comparisons, where standard-size DNA barcodes (>500 bases) offer better taxonomic resolution than shorter ones. Still, the choice of sequencing platforms and bioinformatics pipelines may strongly affect inferred diversity due to various technical biases. We assessed the relative performance of Illumina MiSeq i100 (2x500 paired-end), PacBio Revio and Oxford Nanopore MinION sequencing and bioinformatics pipelines, using full-length ITS amplicon sequencing datasets from a 103-species mock community and 45 composite soil samples. Despite numerous low-quality reads, PacBio yielded the lowest overall error rate and highest number of taxa. Illumina revealed the highest proportion of chimeric and index-switched reads, along with a strong bias towards shorter amplicons. MinION data analysed using PRONAME and Minovar - a bioinformatics pipeline presented here - had the largest proportion of low-quality data, and rare taxa were lost during data filtering and read polishing steps. Although Minovar enabled amplicon sequence variant (ASV) level precision for common taxa, we recommend clustering ASVs into OTUs. For PacBio, standard filtering approaches outperformed the ASV approach because they retained rare taxa. For Illumina, a stringent ASV approach or removal of rare OTUs would limit artefacts. Across all platforms, excess PCR cycles promoted chimeric and low-quality reads and lost quantitativity in biodiversity assessments. With moderate differences in effect sizes, all analytical approaches supported the conclusion that sampling design determines how we see soil biodiversity responses to land use. For biodiversity surveys based on the full-length ITS metabarcoding, we recommend using PacBio sequencing with standard, non-ASV pipelines.

bioinformatics↗

bioRxiv2026

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↗

bioRxiv2023

What mycologists should talk about when they are talking about the International Code of Nomenclature for algae, fungi, and plants

Fungal metabarcoding of substrates such as soil, wood, and water are uncovering an unprecedented number of fungal species that do not seem to produce tangible morphological structures and that defy our best attempts at cultivation, thus falling outside of the ambit of the International Code of Nomenclature for algae, fungi, and plants. The present study uses the new, ninth release of the species hypotheses of the UNITE database to show that species discovery through environmental sequencing vastly outpaces traditional, Sanger sequencing-based efforts in a strongly increasing trend over the last five years. Our findings challenge the present stance of the mycological community - that "the code" works fine and that these complications will somehow sort themselves out given enough time and a following wind - and suggest that we should be discussing not whether to allow DNA-based descriptions (typifications) of species and by extension higher ranks of fungi, but what the precise requirements for such DNA-based typifications should be. We submit a tentative list of such criteria for further discussion. However, the present authors fear that no waves of change will be lapping the shores of mycology for the foreseeable future, leaving the overwhelming majority of extant fungi without formal names and thus scientific and environmental agency. It is not clear to us who benefits from that, but neither fungi nor mycology are likely to be on the winning side.

scientific communication and education↗

bioRxiv2022

Towards understanding diversity, endemicity and global change vulnerability of soil fungi

Fungi play pivotal roles in ecosystem functioning, but little is known about their global patterns of diversity, endemicity, vulnerability to global change drivers and conservation priority areas. We applied the high-resolution PacBio sequencing technique to identify fungi based on a long DNA marker that revealed a high proportion of hitherto unknown fungal taxa. We used a Global Soil Mycobiome consortium dataset to test relative performance of various sequencing depth standardization methods (calculation of residuals, exclusion of singletons, traditional and SRS rarefaction, use of Shannon index of diversity) to find optimal protocols for statistical analyses. Altogether, we used six global surveys to infer these patterns for soil-inhabiting fungi and their functional groups. We found that residuals of log-transformed richness (including singletons) against log-transformed sequencing depth yields significantly better model estimates compared with most other standardization methods. With respect to global patterns, fungal functional groups differed in the patterns of diversity, endemicity and vulnerability to main global change predictors. Unlike -diversity, endemicity and global-change vulnerability of fungi and most functional groups were greatest in the tropics. Fungi are vulnerable mostly to drought, heat, and land cover change. Fungal conservation areas of highest priority include wetlands and moist tropical ecosystems.

ecology↗

bioRxiv2022

DNA barcoding of fungal specimens using long-read high-throughput sequencing

Molecular methods are increasingly used to identify species that lack conspicuous macro- or micromorphological characters. Taxonomic and ecological research teams barcode large numbers of collected voucher specimens annually. In this study we assessed the efficiency of long-read high throughput sequencing (HTS) as opposed to the traditionally used Sanger method for taxonomic identification of multiple vouchered fungal specimens, and providing reference information about intra-individual allele polymorphism. We developed a workflow based on a test-set of 423 fungal specimens (representing 205 species), PacBio HTS method, and ribosomal rRNA operon internal transcribed spacer (ITS) and 28S rRNA gene (LSU) markers. PacBio HTS had a higher success rate than Sanger sequencing at a comparable cost. Species identification based on PacBio reads was usually straightforward, because the dominant operational taxonomic unit (OTU) typically represented the targeted organism. Unlike the Sanger method, PacBio HTS enabled detecting widespread allele polymorphism within the ITS marker in the studied specimens. We conclude that multiplex DNA barcoding of the fungal ITS and LSU markers using a PacBio HTS is a useful tool for taxonomic identification of large amounts of collected voucher specimens at competitive price. Furthermore, PacBio HTS accurately recovers various alleles, which can provide crucial information for species delimitation and population-level studies.

molecular biology↗