References
Aas, A. B., Davey, M. L., & Kauserud, H. (2017). ITS all right mama: Investigating the formation of chimeric sequences in the ITS2 region by DNA metabarcoding analyses of fungal mock communities of different complexities. Molecular Ecology Resources, 17, 730–741. doi: 10.1111/1755-0998.12622 Abdala Asbun, A., Besseling, M. A., Balzano, S., van Bleijswijk, J. D., Witte, H. J., Villanueva, L., & Engelmann, J. C. (2020). Cascabel: A scalable and versatile amplicon sequence data analysis pipeline delivering reproducible and documented results. Frontiers in Genetics, 11, 1329. Albanese, D., Fontana, P., De Filippo, C., Cavalieri, D., & Donati, C. (2015). MICCA: A complete and accurate software for taxonomic profiling of metagenomic data. Scientific Reports, 5, 9743. doi: 10.1038/srep09743 Alberdi, A., Aizpurua, O., Gilbert, M. T., & Bohmann, K. (2018). Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods in Ecology and Evolution, 9, 134-147. doi: 10.1111/2041-210X.12849 Alberdi, A., & Gilbert, M.T. (2019). A guide to the application of Hill numbers to DNA‐based diversity analyses. Molecular Ecology Resources, 19, 804-817.doi: 10.1111/1755-0998.13014 Amend, A., Burgaud, G., Cunliffe, M., Edgcomb, V. P., Ettinger, C. L., Gutiérrez, M. H., … Gladfelter, A. S. (2019). Fungi in the marine environment: open questions and unsolved problems. mBio, 10, e01189-18. doi: 10.1128/mBio.01189-18 Amir, A., McDonald, D., Navas-Molina, J.A., Kopylova, E., Morton, J. T., Zech Xu, Z., … Knight, R. (2017). Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems, 2, e00191-16. doi: 10.1128/mSystems.00191-16 Anderson, M. J., Gorley, R. N., & Clarke, R. K. (2008).Permanova+ for Primer: Guide to Software and Statistical Methods. Plymouth: Primer-E. Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26, 32-46. doi: 10.1111/j.1442-9993.2001.01070.pp.x Anslan, S., Bahram, M., Hiiesalu, I., & Tedersoo, L. (2017). PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data. Molecular Ecology Resources, 17, e234–e240. doi: 10.1111/1755-0998.12692 Anslan, S., Li, H., Künzel, S., & Vences, M. (2021). Microbiomes from feces vs. gut in tadpoles: distinct community compositions between substrates and preservation methods. Salamandra, 57, 96-104. doi: 10.1101/651612 Anslan, S., Nilsson, R. H., Wurzbacher, C., Baldrian, P., Tedersoo, L., & Bahram, M. (2018). Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding. MycoKeys, 39, 29-40. doi: 10.3897/mycokeys.39.28109 Antoninka, A., Wolf, J. E., Bowker. M., Classen, A. T., & Johnson, N. C. (2009). Linking above- and belowground responses to global change at community and ecosystem scales. Global Change Biology, 15, 914-929. doi: 10.1111/j.1365-2486.2008.01760.x Bahram, M., Harend, H., & Tedersoo, L. (2014). Network perspectives of ectomycorrhizal associations. Fungal Ecology, 7, 70-77. doi: 10.1016/j.funeco.2013.10.003 Bahram, M., Hildebrand, F., Forslund, S. K., Anderson, J. L., Soudzilovskaia, N. A., Bodegom, P. M., … Bork P. (2018). Structure and function of the global topsoil microbiome. Nature, 560, 233-237. doi: 10.1038/s41586-018-0386-6 Bahram, M., Peay, K. G., & Tedersoo, L. (2015). Local-scale biogeography and spatiotemporal variability in communities of mycorrhizal fungi. New Phytologist, 205, 1454–1463. doi: 10.1111/nph.13206 Bakker, M. G. (2018). A fungal mock community control for amplicon sequencing experiments. Molecular Ecology Resources, 18, 541-556. doi: 10.1111/1755-0998.12760 Baldrian, P., Vetrovsky, T., Cajthaml, T., Dobiasova, P., Petrankova, M., Snajdr, J., & Eichlerova, I. (2013). Estimation of fungal biomass in forest litter and soil. Fungal Ecology, 6, 1-11. doi: 10.1016/j.funeco.2012.10.002 Balint, M., Bahram, M., Eren, A. M., Faust, K., Fuhrman, J. A., Lindahl, B., … Tedersoo, L. (2016). Millions of reads, thousands of taxa: microbial community structure and associations analyzed via marker genes. FEMS Microbiology Reviews, 40, 686-700. doi: 10.1093/femsre/fuw017 Balint, M., Pfenninger, M., Grossart, H. P., Taberlet, P., Vellend, M., Leibold, M. A., … Bowler, D. (2018). Environmental DNA time series in ecology. Trends in Ecology & Evolution, 33, 945-957. doi: 10.1016/j.tree.2018.09.003 Banos, S., Lentendu, G., Kopf, A., Wubet, T., Glöckner, F. O., & Reich, M. A. (2018). Comprehensive fungi-specific 18S rRNA gene sequence primer toolkit suited for diverse research issues and sequencing platforms.BMC Microbiology, 18, 190. doi: 10.1186/s12866-018-1331-4 Barbera, P., Kozlov, A. M., Czech, L., Morel, B., Darriba, D., Flouri, T., & Stamatakis, A. (2019). EPA-ng: Massively parallel evolutionary placement of genetic sequences. Systematic Biology, 68, 365–369. doi: 10.1093/sysbio/syy054 Bengtsson-Palme, J., Ryberg, M., Hartmann, M., Branco, S., Wang, Z., Godhe, A., … Nilsson, R. H. (2013). Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data.Methods in Ecology and Evolution, 4, 914-919. doi: 10.1111/2041-210X.12073 Berry, D., & Loy, A. (2018). Stable-isotope probing of human and animal microbiome function. Trends in Microbiology, 26, 999-1007. doi: 10.1016/j.tim.2018.06.004 Beule, L., & Karlovsky, P. (2020). Improved normalization of species count data in ecology by scaling with ranked subsampling (SRS): Application to microbial communities. PeerJ, 8, e9593. doi: 10.7717/peerj.9593 Bissett, A., Fitzgerald, A., Meintjes, T., Mele, P. M., Reith, F., Dennis, P. G., … Byrne, M. (2016). Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database.GigaScience, 5, 21. doi: 10.1186/s13742-016-0126-5 Blanchet, F. G., Cazelles, K., & Gravel, D. (2020). Co‐occurrence is not evidence of ecological interactions. Ecology Letters 23, 1050-1063. doi: 10.1111/ele.13525 Blazewicz, S. J., Barnard, R. L., Daly, R. A., & Firestone, M. K. (2013). Evaluating rRNA as an indicator of microbial activity in environmental communities: Limitations and uses. The ISME Journal, 7, 2061-2068. doi: 10.1038/ismej.2013.102 Bohmann, K., Elbrecht, V., Carøe, C., Bista, I., Leese, F., Bunce, M., … & Creer, S. (in press). Strategies for sample labelling and library preparation in DNA metabarcoding studies. Molecular Ecology Resources. Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., … Caporaso, J. G. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology, 37, 852–857. doi: 10.1038/s41587-019-0209-9 Bork, P., Bowler, C., De Vargas, C., Gorsky, G., Karsenti, E., & Wincker, P. (2015). Tara Oceans studies plankton at planetary scale.Science, 348, 873. doi: 10.1126/science.aac5605 Boyer, F., Mercier, C., Bonin, A., Le Bras, Y., Taberlet, P., & Coissac, E. (2016). Obitools: A unix‐inspired software package for DNA metabarcoding. Molecular Ecology Resources, 16, 176-182. doi: 10.1111/1755-0998.12428 Brabcova, V., Novakova, M., Davidova, A., & Baldrian, P. (2016). Dead fungal mycelium in forest soil represents a decomposition hotspot and a habitat for a specific microbial community. New Phytologist, 210, 1369-1381. doi: 10.1111/nph.13849 Brandt, M. I., Trouche, B., Quintric, L., Günther, B., Wincker, P., Poulain, J., & Arnaud‐Haond S. (2021). Bioinformatic pipelines combining denoising and clustering tools allow for more comprehensive prokaryotic and eukaryotic metabarcoding. Molecular Ecology Resources, 21, 1904-1921. doi: 10.1111/1755-0998.13398 Bruns, T. D., & Taylor, J. W. (2016). Comment on “Global assessment of arbuscular mycorrhizal fungus diversity reveals very low endemism”.Science, 351,826-826. doi: 10.1126/science.aad2346 Bunge, J., Willis, A., & Walsh, F. (2014). Estimating the number of species in microbial diversity studies. Annual Review of Statistics and Its Application, 1, 427-445. doi: 10.1146/annurev-statistics-022513-115654 Buschmann, T., & Bystrykh, L. V. (2013). Levenshtein error-correcting barcodes for multiplexed DNA sequencing. BMC Bioinformatics, 14,272. doi: 10.1186/1471-2105-14-272 Buttigieg, P. L., & Ramette, A. (2014). A guide to statistical analysis in microbial ecology: a community-focused living review of multivariate data analyses. FEMS Microbiology Ecology, 90, 543-550. doi: 10.1111/1574-6941.12437 Byrne, A. Q., Rothstein, A. P., Poorten, T. J., Erens, J., Settles, M. L., & Rosenblum, E. B. (2017). Unlocking the story in the swab: A new genotyping assay for the amphibian chytrid fungus Batrachochytrium dendrobatidis. Molecular Ecology Resources, 17, 1283-1292. doi: 10.1111/1755-0998.12675 Caceres, M. D., & Legendre, P. (2009). Associations between species and groups of sites: Indices and statistical inference. Ecology, 90, 3566-3574. doi: 10.1890/08-1823.1 Cai, F., & Druzhinina, I. S. (2021). In honor of John Bissett: Authoritative guidelines on molecular identification of Trichoderma.Fungal Diversity, 107, 1-69. doi: 10.1007/s13225-020-00464-4 Calderón‐Sanou, I., Münkemüller, T., Boyer, F., Zinger, L., & Thuiller, W. (2020). From environmental DNA sequences to ecological conclusions: How strong is the influence of methodological choices? Journal of Biogeography, 47, 193-206. doi: 10.1111/jbi.13681 Callahan, B. J., Grinevich, D., Thakur, S., Balamotis, M. A., & Yehezkel, T. B. (2021). Ultra-accurate microbial amplicon sequencing with synthetic long reads. Microbiome, 9, 130. doi: 10.1186/s40168-021-01072-3 Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J., & Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13, 581-584. doi: 10.1038/nmeth.3869 Callahan, B. J., Wong, J., Heiner, C., Oh, S., Theriot, C. M., Gulati, A. S., … Dougherty, M. K. (2019). High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic acids research, 47, e103. doi: 10.1093/nar/gkz569 Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009). BLAST+: Architecture and applications. BMC Bioinformatics, 10, 421. doi: 10.1186/1471-2105-10-421 Carlsen, T., Aas, A. B., Lindner, D., Vrålstad, T., Schumacher, T., & Kauserud, H. (2012). Don’t make a mista(g)ke: Is tag switching an overlooked source of error in amplicon pyrosequencing studies?Fungal Ecology, 5, 747-749. doi: 10.1016/j.funeco.2012.06.003 Carøe, C., & Bohmann, K. (2020). Tagsteady: A metabarcoding library preparation protocol to avoid false assignment of sequences to samples.Molecular Ecology Resources, 20, 1620-1631. doi: 10.1111/1755-0998.13227 Castano, C., Parladé, J., Pera, J., De Aragón, J. M., Alday, J. G., & Bonet, J. A. (2016). Soil drying procedure affects the DNA quantification of Lactarius vinosus but does not change the fungal community composition. Mycorrhiza, 26, 799-808. doi: 10.1007/s00572-016-0714-3 Castle, S. C., Song, Z., Gohl, D. M., Gutknecht, J. L., Rosen, C. J., Sadowsky, M. J., … Kinkel, L. L. (2018). DNA template dilution impacts amplicon sequencing-based estimates of soil fungal diversity.Phytobiomes, 2, 100-107. doi: 10.1094/PBIOMES-09-17-0037-R Chalmandrier, L., Pansu, J., Zinger, L., Boyer, F., Coissac, E., Génin, A., … Taberlet, P. (2019). Environmental and biotic drivers of soil microbial β‐diversity across spatial and phylogenetic scales.Ecography, 42, 2144-2156. doi: 10.1111/ecog.04492 Chambouvet, A., Monier, A., Maguire, F., Itoïz, S., del Campo, J., Elies, P., … Richards, T. A. (2019). Intracellular Infection of Diverse Diatoms by an Evolutionary Distinct Relative of the Fungi.Current Biology, 29, 4093-4101. doi: 10.1016/j.cub.2019.09.074 Chao, A., Gotelli, N. J., Hsieh, T. C., Sander, E. L., Ma, K. H., Colwell, R. K., & Ellison, A. M. (2014). Rarefaction and extrapolation with Hill numbers: A framework for sampling and estimation in species diversity studies. Ecological Monographs, 84, 45-67. doi: 10.1890/13-0133.1 Chazdon, R. L., Chao, A., Colwell, R. K., Lin, S. Y., Norden, N., Letcher, S. G., … Arroyo, J. P. (2011). A novel statistical method for classifying habitat generalists and specialists.Ecology, 92, 1332-1343. doi: 10.1890/10-1345.1 Clasen, L. A., Detheridge, A. P., Scullion, J., & Griffith, G. W. (2020). Soil stabilisation for DNA metabarcoding of plants and fungi. Implications for sampling at remote locations or via third-parties.Metabarcoding and Metagenomics, 4, e58365. doi: 10.3897/mbmg.4.58365 Cline, L. C., Song, Z., Al‐Ghalith, G. A., Knights, D., & Kennedy, P. G. (2017). Moving beyond de novo clustering in fungal community ecology.New Phytologist, 216, 629-634. doi: 10.1111/nph.14752 Collier, J. E. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. New York: Routledge Publishing. Colwell, R. K., Mao, C. X., & Chang, J. (2004). Interpolating, extrapolating, and comparing incidence-based species accumulation curves. Ecology, 85, 2717–2727. doi: 10.1890/03-0557 Connor, N., Barberán, A., & Clauset, A. (2017). Using null models to infer microbial co-occurrence networks. PLoS ONE, 12, e0176751. doi: 10.1371/journal.pone.0176751 Cristescu, M. E., & Hebert, P. D. (2018). Uses and misuses of environmental DNA in biodiversity science and conservation. Annual Review of Ecology, Evolution, and Systematics, 49, 209-230. doi: 10.1146/annurev-ecolsys-110617-062306 Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A., & Callahan, B. J. (2018). Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data.Microbiome, 6, 226. doi: 10.1186/s40168-018-0605-2 de Carcer, D. A., Denman, S. E., McSweeney, C., & Morrison, M. (2011). Evaluation of subsampling-based normalization strategies for tagged high-throughput sequencing datasets from gut microbiomes. Applied and Environmental Microbiology, 77, 8795-8798. doi: 10.1128/aem.05491-11 Delavaux, C. S., Bever, J. D., Karppinen, E. M., & Bainard, L. D. (2020). Keeping it cool: Soil sample cold pack storage and DNA shipment up to 1 month does not impact metabarcoding results. Ecology and Evolution, 10, 4652-4664. doi: 10.1002/ece3.6219 Delavaux, C. S., Sturmer, S. L., Wagner, M. R., Schütte, U., Morton, J. B., & Bever, J. D. (2021). Utility of LSU for environmental sequencing of arbuscular mycorrhizal fungi: A new reference database and pipeline.New Phytologist, 229, 3048-3052. doi: 10.1111/nph.17080 Deng, Y., Jiang, Y-H., Yang, Y., He, Z., Luo, F., & Zhou, J. (2012). Molecular ecological network analyses. BMC Bioinformatics, 13, 113. doi: 10.1186/1471-2105-13-113 Deshpande, V., Wang, Q., Greenfield, P., Charleston, M., Porras-Alfaro, A., Kuske, C. R., … Tran-Dinh, N. (2016). Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer sequences. Mycologia, 108, 1-5. doi: 10.3852/14-293 Dickie, I. A., Boyer, S., Buckley, H. L., Duncan, R. P., Gardner, P. P., Hogg, I. D., … Weaver, L. (2018). Towards robust and repeatable sampling methods in eDNA-based studies. Molecular Ecology Resources, 18, 940–952. doi: 10.1111/1755-0998.12907 Dormann, C. F., Fründ, J., Blüthgen, N., & Gruber, B. (2009). Indices, graphs and null models: analyzing bipartite ecological networks.Open Ecology Journal, 2, 7-24. doi: 10.2174/1874213000902010007 Douhan, G. W., Vincenot, L., Gryta, H., & Selosse, M-A. (2011). Population genetics of ectomycorrhizal fungi: From current knowledge to emerging directions. Fungal Biology, 115, 569–597. doi: 10.1016/j.funbio.2011.03.005 Dray, S., Blanchet, G., Borcard, D., Guenard, G., Jombart, T., Larocque, G., … Wagner, H. H. (2018). Package ‘adespatial’.Available:https://cran.microsoft.com/web/packages/adespatial/adespatial.pdf Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., & Knight, R. (2011). UCHIME improves sensitivity and speed of chimera detection.Bioinformatics, 27, 2194-2200. doi: 10.1093/bioinformatics/btr381 Edgar, R. C. (2010). Search and clustering orders of magnitude faster than BLAST. Bioinformatics, 26, 2460-2461. doi: 10.1093/bioinformatics/btq461 Edgar, R. C. (2016). UNOISE2: Improved error-correction for Illumina 16S and ITS amplicon sequencing. BioRxiv, 2016, 081257. doi: 10.1101/081257 Edgar, R. C. (2017). Accuracy of microbial community diversity estimated by closed- and open-reference OTUs. PeerJ, 5, e3889. doi: 10.7717/peerj.3889 Egan, C. P., Rummel, A., Kokkoris, V., Klironomos, J., Lekberg, Y., & Hart, M. (2018). Using mock communities of arbuscular mycorrhizal fungi to evaluate fidelity associated with Illumina sequencing. Fungal Ecology, 33, 52-64. doi: 10.1016/j.funeco.2018.01.004 Eisenhofer, R., Minich, J. J., Marotz, C., Cooper, A., Knight, R., & Weyrich, L. S. (2019). Contamination in low microbial biomass microbiome studies: Issues and recommendations. Trends in Microbiology, 27, 105-117. doi: 10.1016/j.tim.2018.11.003 Escalas, A., Hale, L., Voordeckers, J. W., Yang, Y., Firestone, M. K., Alvarez‐Cohen, L., & Zhou, J. (2019). Microbial functional diversity: From concepts to applications. Ecology and Evolution, 9, 12000-12016. doi: 10.1002/ece3.5670 Escudie, F., Auer, L., Bernard, M., Mariadassou, M., Cauquil, L., Vidal, K., … Pascal, G. (2018). FROGS: Find, rapidly, OTUs with galaxy solution. Bioinformatics, 34, 1287-1294. doi: 10.1093/bioinformatics/btx791 Estensmo, E. L., Maurice, S., Morgado, L., Martin‐Sanchez, P. M., Skrede, I., & Kauserud, H. (2011). The influence of intraspecific sequence variation during DNA metabarcoding: A case study of eleven fungal species. Molecular Ecology Resources, 21, 1141-1148. doi: 10.1111/1755-0998.13329 Fadrosh, D. W., Ma, B., Gajer, P., Sengamalay, N., Ott, S., Brotman, R. M., & Ravel, J. (2014). An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform.Microbiome, 2, 6. doi: 10.1186/2049-2618-2-6 Fan, Y., Chen, J., Shirkey, G., John, R., Wu, S. R., Park, H., & Shao, C. (2016). Applications of structural equation modeling (SEM) in ecological studies: An updated review. Ecological Processes, 5, 19. doi: 10.1186/s13717-016-0063-3 Faust, K., & Raes, J. (2016). CoNet app: Inference of biological association networks using Cytoscape. F1000Research, 5, 1519. doi: 10.12688/f1000research.9050.2 Faust, K., & Raes, J. (2012). Microbial interactions: From networks to models. Nature Reviews Microbiology, 10, 538-549. doi: 10.1038/nrmicro2832 Fernandez, C. W., Nguyen, N. H., Stefanski, A., Han, Y., Hobbie, S. E., Montgomery, R. A., … Kennedy, P. G. (2017). Ectomycorrhizal fungal response to warming is linked to poor host performance at the boreal‐temperate ecotone. Global Change Biology, 23, 1598-1609. doi: 10.1111/gcb.13510 Ficetola, G. F., Coissac, E., Zundel, S., Riaz, T., Shehzad, W., Bessière, J., … Pompanon, F. (2010). An in silico approach for the evaluation of DNA barcodes. BMC Genomics, 11, 434. doi: 10.1186/1471-2164-11-434 Fischer, M., Renevey, N., Thür, B., Hoffmann, D., Beer, M., & Hoffmann, B. (2016). Efficacy assessment of nucleic acid decontamination reagents used in molecular diagnostic laboratories. PLoS ONE, 11, e0159274. doi: 10.1371/journal.pone.0159274 Foster, Z. S. L., Sharpton, T. J., & Grünwald, N. J. (2017). Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Computational Biology, 13, e1005404. doi: 10.1371/journal.pcbi.1005404 Fouquier, J., Rideout, J. R., Bolyen, E., Chase, J., Shiffer, A., McDonald, D., … Kelley, S. T. (2016). Ghost-tree: Creating hybrid-gene phylogenetic trees for diversity analyses. Microbiome, 4, 11. doi: 10.1186/s40168-016-0153-6 Friedman, J., & Alm, E. J. (2011). Inferring correlation networks from genomic survey data. PLoS Computational Biology, 8, e1002687. doi: 10.1371/journal.pcbi.1002687 Furneaux, B., Bahram, M., Rosling, A., Yorou, N. S., & Ryberg, M. (2021). Long‐and short‐read metabarcoding technologies reveal similar spatiotemporal structures in fungal communities. Molecular Ecology Resources, 21, 1833-1849. doi: 10.1111/1755-0998.13387 Geisen, S., Tveit, A. T., Clark, I. M., Richter, A., Svenning, M. M., Bonkowski, M., & Urich, T. (2015). Metatranscriptomic census of active protists in soils. The ISME Journal, 9, 2178-2190. doi: 10.1038/ismej.2015.30 Georgieva, D., Liu, Q., Wang, K., & Egli, D. (2020). Detection of base analogs incorporated during DNA replication by nanopore sequencing.Nucleic Acids Research, 48, e88. doi: 10.1093/nar/gkaa517 Gherbawy, Y., & Voigt, K. (eds). (2010). Molecular identification of fungi. Berlin: Springer. Glassman, S. I., & Martiny, J. B. (2018). Broadscale ecological patterns are robust to use of exact sequence variants versus operational taxonomic units. mSphere, 3, e00148-18. doi: 10.1128/mSphere.00148-18 Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., & Egozcue, J. J. (2017). Microbiome datasets are compositional: And this is not optional.Frontiers in Microbiology, 8, 2224. doi: 10.3389/fmicb.2017.02224 Gohl, D. M., Auch, B., Certano, A., LeFrançois, B., Bouevitch, A., Doukhanine, E., … Beckman, K. B. (2021). Dissecting and tuning primer editing by proofreading polymerases. Nucleic Acids Research, 49, e87. doi: 10.1093/nar/gkab471 Gohl, D. M., Vangay, P., Garbe, J., MacLean, A., Hauge, A., Becker, A., … Knights, D. (2016). Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies. Nature Biotechnology, 34, 942-949. doi: 10.1038/nbt.3601 Gotelli, N. J., & Ellison, A. M. (2004). A primer of ecological statistics. Sunderland: Sinauer Associates. Grossart, H. P., Van den Wyngaert, S., Kagami, M., Wurzbacher, C., Cunliffe, M., & Rojas-Jimenez, K. (2019). Fungi in aquatic ecosystems.Nature Reviews Microbiology, 17, 339–354. doi: 10.1038/s41579-019-0175-8 Guerrieri, A., Bonin, A., Münkemüller, T., Gielly, L., Thuiller, W., & Ficetola, G. F. (2021). Effects of soil preservation for biodiversity monitoring using environmental DNA. Molecular Ecology, 30,3313-3325. doi: 10.1111/mec.15674 Gweon, H. S., Oliver, A., Taylor, J., Booth, T., Gibbs, M., Read, D. S., … Schonrogge, K. (2015). PIPITS: An automated pipeline for analyses of fungal internal transcribed spacer sequences from the I llumina sequencing platform. Methods in Ecology and Evolution, 6,973-980. doi: 10.1111/2041-210x.12399 Ha, M. J., Kim, J., Galloway-Peña, J., Do, K. A., & Peterson, C. B. (2020). Compositional zero-inflated network estimation for microbiome data. BMC Bioinformatics, 21, 581. doi: 10.1186/s12859-020-03911-w Halwachs, B., Madhusudhan, N., Krause, R., Nilsson, R. H., Moissl-Eichinger, C., Högenauer, C., & Gorkiewicz, G. (2017). Critical issues in mycobiota analysis. Frontiers in microbiology, 8, 180. doi: 10.3389/fmicb.2017.00180 Hamady, M., Lozupone, C., & Knight, R. (2010). Fast Unifrac: Facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data.The ISME Journal, 4, 17-27. doi: 10.1038/ismej.2009.97 Hannula, S. E., Morriën, E., de Hollander, M., van der Putten, W. H., van Veen, J. A., & de Boer, W. (2017). Shifts in rhizosphere fungal community during secondary succession following abandonment from agriculture. The ISME Journal, 11, 2294–2304. doi: 10.1038/ismej.2017.90 Hanson, C. A., Allison, S. D., Bradford, M. A., Wallenstein, M. D., & Treseder, K. K. (2008). Fungal taxa target different carbon sources in forest soil. Ecosystems, 11, 1157-1167. doi: 10.1007/s10021-008-9186-4 He, Y., Caporaso, J. G., Jiang, X-T., Sheng, H-F., Huse, S. M., Rideout, J. R., … Zhou, H-W. (2015). Stability of operational taxonomic units: An important but neglected property for analyzing microbial diversity. Microbiome, 3, 20. doi: 10.1186/s40168-015-0081-x Heeger, F., Bourne, E. C., Baschien, C., Yurkov, A., Bunk, B., Spröer, C., … Monaghan, M. T. (2018). Long-read DNA metabarcoding of ribosomal rRNA in the analysis of fungi from aquatic environments.Molecular Ecology Resources, 18, 1500-1514. doi: 10.1111/1755-0998.12937 Hildebrand, F., Tadeo, R., Wright, A. Y., Bork, P., & Raes, J. (2014). LotuS: An efficient and user-friendly OTU processing pipeline.Microbiome, 2, 30.doi: 10.1186/2049-2618-2-30 Holm, J. B., Humphrys, M. S., Robinson, C. K., Settles, M. L., Ott, S., Fu, L., & Ravel, J. (2020). Ultrahigh-throughput multiplexing and sequencing of >500-base-pair amplicon regions on the Illumina HiSeq 2500 platform. mSystems, 4, e00029-19. doi: 10.1128/mSystems.00029-19 Horn, S., Caruso, T., Verbruggen, E., Rillig, M. C., & Hempel, S. (2014). Arbuscular mycorrhizal fungal communities are phylogenetically clustered at small scales. The ISME Journal, 8, 2231-2242. doi: 10.1038/ismej.2014.72 Hugerth, L. W., & Andersson, A. F. (2017). Analysing microbial community composition through amplicon sequencing: From sampling to hypothesis testing. Frontiers in Microbiology, 8, 1561. doi: 10.3389/fmicb.2017.01561 Ihrmark, K., Bödeker, I. T. M., Cruz-Martinez, K., Friberg, H., Kubartova, A., Schenk, J., … Lindahl, B. D. (2012). New primers to amplify the fungal ITS2 region - evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiology Ecology, 83, 666-677. doi: 10.1111/j.1574-6941.2012.01437.x Ikenaga, M., Tabuchi, M., Kawauchi, T., & Sakai, M. (2016). Application of Locked Nucleic Acid (LNA) primer and PCR clamping by LNA oligonucleotide to enhance the amplification of Internal Transcribed Spacer (ITS) regions in investigating the community structures of plant–associated fungi. Microbes and Environments, 31, 339-348. doi: 10.1264/jsme2.me16085 Jalili, V., Afgan, E., Gu, Q., Clements, D., Blankenberg, D., Goecks, J., … Nekrutenko, A. (2020). The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2020 update.Nucleic Acids Research, 48, W395-W402. doi: 10.1093/nar/gkaa434 Jarman, S. N., Berry, O., & Bunce, M. (2018). The value of environmental DNA biobanking for long-term biomonitoring. Nature Ecology & Evolution, 2, 1192-1193. doi: 10.1038/s41559-018-0614-3 Joos, L., Beirinckx, S., Haegeman, A., Debode, J., Vandecasteele, B., Baeyen, S., & De Tender, C. (2020). Daring to be differential: Metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units.BMC Genomics, 21, 733. doi: 10.1186/s12864-020-07126-4 Jumpponen, A., & Jones, K. L. (2009). Massively parallel 454 sequencing indicates hyperdiverse fungal communities in temperate Quercus macrocarpa phyllosphere. New Phytologist, 184, 438-448. doi: 10.1111/j.1469-8137.2009.02990.x Karst, S. M., Ziels, R. M., Kirkegaard, R. H., Sørensen, E. A., McDonald, D., Zhu, Q., … Albertsen, M. (2021). High-accuracy long-read amplicon sequences using unique molecular identifiers with nanopore or PacBio sequencing. Nature Methods, 18, 165-169. doi: 10.1038/s41592-020-01041-y Kembel, S. W., Cowan, P. D., Helmus, M. R., Cornwell, W. K., Morlon, H., Ackerly, D. D., … Webb, C. O. (2010). Picante: R tools for integrating phylogenies and ecology. Bioinformatics, 26, 1463-1464. doi: 10.1093/bioinformatics/btq166 Kennedy, P. G., Cline, L. C., & Song, Z. (2018). Probing promise versus performance in longer read fungal metabarcoding. New Phytologist, 217, 973–976. doi: 10.1111/nph.14883 Kolaríkova, Z., Slavíková, R., Krüger, C., Krüger, M., & Kohout, P. (2021). PacBio sequencing of Glomeromycota rDNA: A novel amplicon covering all widely used ribosomal barcoding regions and its applicability in taxonomy and ecology of arbuscular mycorrhizal fungi.New Phytologist, 231, 490–499. doi: 10.1111/nph.17372 Kõljalg, U., Nilsson, H. R., Schigel, D., Tedersoo, L., Larsson, K. H., May, T. W., … Abarenkov, K. (2020). The Taxon Hypothesis paradigm—on the unambiguous detection and communication of taxa.Microorganisms, 8, 1910. doi: 10.3390/microorganisms8121910 Kõljalg, U., Tedersoo, L., Nilsson, R. H., & Abarenkov, K. (2016). Digital identifiers for fungal species. Science, 352, 1182-1183. doi: 10.1126/science.aaf7115 Kuczynski, J., Liu, Z., Lozupone, C., McDonald, D., Fierer, N., & Knight, R. (2010). Microbial community resemblance methods differ in their ability to detect biologically relevant patterns. Nature Methods, 7, 769-775. doi: 10.1038/nmeth.1499 Kumar, G., Eble, J. E., & Gaither, M. R. (2020). A practical guide to sample preservation and pre‐PCR processing of aquatic environmental DNA.Molecular Ecology Resources, 20, 29-39. doi: 10.1111/1755-0998.13107 Kurtz, Z. D., Müller, C. L., Miraldi, E. R., Littman, D. R., Blaser, M. J., & Bonneau, R. A. (2015). Sparse and compositionally robust inference of microbial ecological networks. PLoS Computational Biology, 11, e1004226. doi: 10.1371/journal.pcbi.1004226 Kyaschenko, Y., Clemmensen, K., Hagenbo, A., Karltun, E., & Lindahl, B. (2017). Shift in fungal communities and associated enzyme activities along an age gradient of managed Pinus sylvestris stands.The ISME Journal, 11, 863–874. doi: 10.1038/ismej.2016.184 Lagerborg, K. A., Normandin, E., Bauer, M. R., Adams, G., Figueroa, K., Loreth, C., … Hooper, D. (2021). DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing. bioRxiv, 2021, 435654. doi: 10.1101/2021.03.16.435654 Laliberté, E., & Legendre, P. (2010). A distance‐based framework for measuring functional diversity from multiple traits. Ecology, 91, 299-305. doi: 10.1890/08-2244.1 Larsson, A. J., Stanley, G., Sinha, R., Weissman, I. L., & Sandberg, R. (2018). Computational correction of index switching in multiplexed sequencing libraries. Nature Methods, 15, 305-307. doi: 10.1038/nmeth.4666 Legendre, P., & Gallagher, E. D. (2001). Ecologically meaningful transformations for ordination of species data. Oecologia, 129, 271-280. doi: 10.1007/s004420100716 Legendre, P., & Legendre, L. (2012). Numerical Ecology. New York: Elsevier. Lennon, J. T., Muscarella, M. E., Placella, S. A., & Lehmkuhl, B. K. (2018). How, when, and where relic DNA affects microbial diversity.mBio, 9, e00637-18. doi: 10.1128/mBio.00637-18 Letunic, I., & Bork, P. (2021). Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Research, 49, W293-W296. doi: 10.1093/nar/gkab301 Li, S., Du, X., Feng, K., Wu, Y., He, Q., Wang, Z., … Escalas, A. (2021). Assessment of microbial α-diversity in one meter squared topsoil. Soil Ecology Letters, 2021, 1-3. doi: 10.1007/s42832-021-0111-5 Lin, H., & Peddada, S. D. (2020a). Analysis of compositions of microbiomes with bias correction. Nature Communications, 11, 3514. doi: 10.1038/s41467-020-17041-7 Lin, H., & Peddada, S. D. (2020b). Analysis of microbial compositions: A review of normalization and differential abundance analysis. NPJ biofilms and microbiomes, 6, 60. doi: 10.1038/s41522-020-00160-w Lindahl, B. D., Nilsson, R. H., Tedersoo, L., Abarenkov, K., Carlsen, T., Kjøller, R., … Kauserud, H. (2013). Fungal community analysis by high-throughput sequencing of amplified markers – a user’s guide.New Phytologist, 199, 288–299. doi: 10.1111/nph.12243 Lindner, D. L., Carlsen, T., Nilsson, R. H., Davey, M., Schumacher, T., & Kauserud, H. (2013). Employing 454 amplicon pyrosequencing to reveal intragenomic divergence in the internal transcribed spacer rDNA region in fungi. Ecology and Evolution, 3, 1751–1764. doi: 10.1002/ece3.586 Liu, C., Cui, Y., Li, X., & Yao, M. (2021). Microeco: An R package for data mining in microbial community ecology. FEMS Microbiology Ecology, 97, fiaa255. doi: 10.1093/femsec/fiaa255 Lofgren, L. A., Uehling, J. K., Branco, S., Bruns, T. D., Martin, F., & Kennedy, P. G. (2019). Genome‐based estimates of fungal rDNA copy number variation across phylogenetic scales and ecological lifestyles.Molecular Ecology, 28, 721-730. doi: 10.1111/mec.14995 Loit, K., Adamson, K., Bahram, M., Puusepp, R., Anslan, S., Kiiker, R., … Tedersoo, L. (2019). Relative Performance of MinION (Oxford Nanopore Technologies) versus Sequel (Pacific Biosciences) third-generation sequencing instruments in identification of agricultural and forest fungal pathogens. Applied and Environmental Microbiology, 85, e01368-19. doi: 10.1128/AEM.01368-19 Loos, D., Zhang, L., Beemelmanns, C., Kurzai, O., & Panagiotou, G. (2021). DAnIEL: A user-friendly web server for fungal ITS amplicon sequencing data. Frontiers in Microbiology, 12, 720513. doi: 10.3389/fmicb.2021.720513 Lopez-Mondejar, R., Tláskal, V., Větrovský, T., Štursová, M., Toscan, R., da Rocha, U. N., & Baldrian, P. (2020). Metagenomics and stable isotope probing reveal the complementary contribution of fungal and bacterial communities in the recycling of dead biomass in forest soil.Soil Biology and Biochemistry, 148, 107875. doi: 10.1016/j.soilbio.2020.107875 Lovell, D. R., Chua, X. Y., & McGrath, A. (2020). Counts: an outstanding challenge for log-ratio analysis of compositional data in the molecular biosciences. NAR Genomics and Bioinformatics, 2, lqaa040. Lücking, R., Aime, M. C., Robbertse, B., Miller, A. N., Aoki, T., Ariyawansa, H. A., … & Schoch, C. L. (2021). Fungal taxonomy and sequence-based nomenclature. Nature Microbiology, 6, 540-548. Lundberg, D. S., Yourstone, S., Mieczkowski, P., Jones, C. D., & Dangl, J. L. (2013). Practical innovations for high-throughput amplicon sequencing. Nature Methods, 10, 999–1002. doi: 10.1038/nmeth.2634 Mahe, F., Czech, L., Stamatakis, A., Quince, C., de Vargas, C., Dunthorn, M., & Rognes, T. (in press). Swarm v3: Towards tera-scale amplicon clustering. Bioinformatics. doi: 10.1093/bioinformatics/btab493 Manion, G., Lisk, M., Ferrier, S., Nieto-Lugilde, D., Mokany, K., & Fitzpatrick, M. C. (2018). Gdm: Generalized Dissimilarity Modeling. Available: https://CRAN.R-project.org/package=gdm Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet, 17, 10-12. doi: 10.14806/ej.17.1.200 Matchado, M. S., Lauber, M., Reitmeier, S., Kacprowski, T., Baumbach, J., Haller, D., & List, M. (2021). Network analysis methods for studying microbial communities: A mini review. Computational and Structural Biotechnology Journal, 19, 2687-2698. doi: 10.1016/j.csbj.2021.05.001 Matsuoka, S., Sugiyama, Y., Sato, H., Katano, I., Harada, K., & Doi, H. (2019). Spatial structure of fungal DNA assemblages revealed with eDNA metabarcoding in a forest river network in western Japan.Metabarcoding and Metagenomics, 3, e36335. doi: 10.3897/mbmg.3.36335 McKnight, D. T., Huerlimann, R., Bower, D. S., Schwarzkopf, L., Alford, R. A., & Zenger, K. R. (2019). MicroDecon: A highly accurate read‐subtraction tool for the post‐sequencing removal of contamination in metabarcoding studies. Environmental DNA, 1, 14-25. doi: 10.1002/edn3.11 McMurdie, P. J., & Holmes, S. (2013). Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PloS ONE, 8, e61217. doi: 10.1371/journal.pone.0061217 McMurdie, P. J., & Holmes, S. (2014). Waste not, want not: Why rarefying microbiome data is inadmissible. PLoS Computational Biology, 10, e1003531. doi: 10.1371/journal.pcbi.1003531 Metsalu, T., & Vilo, J. (2015). ClustVis: A web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap. Nucleic acids research, 43, W566-W570. doi: 10.1093/nar/gkv468 Mikryukov, V. S., Dulya, O. V., Likhodeevskii, G. A., & Vorobeichik, E. L. (2021). Analysis of ecological networks in multicomponent communities of microorganisms: Possibilities, limitations, and potential errors.Russian Journal of Ecology, 52, 188-200. doi: 10.1134/S1067413621030085 Miyauchi, S., Kiss, E., Kuo, A., Drula, E., Kohler, A., Sánchez-García, M., … Buée, M. (2020). Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits. Nature Communications, 11, 5125. doi: 10.1038/s41467-020-18795-w Moreira-Grez, B., Vuong, P., Waite, I., Morald, T., Wise, M., & Whiteley, A. S. (2019). RNA Stable Isotope Probing (RNA-SIP).Methods in Molecular Biology, 2046, 31-44. doi: 10.1007/978-1-4939-9721-3_3 Nguyen, N. H., Smith, D., Peay, K., & Kennedy, P. (2015). Parsing ecological signal from noise in next generation amplicon sequencing.New Phytologist, 205, 1389–1393. doi: 10.1111/nph.12923 Nguyen, N. H., Song, Z., Bates, S. T., Branco, S., Tedersoo, L., Menke, J., … Kennedy, P. G. (2016). FUNGuild: An open annotation tool for parsing fungal community data sets by ecological guild. Fungal Ecology, 20, 241–248. doi: 10.1016/j.funeco.2015.06.006 Nilsson, R. H., Anslan, S., Bahram, M., Wurzbacher, C., Baldrian, P., & Tedersoo, L. (2018). Mycobiome diversity: High-throughput sequencing and identification of fungi. Nature Reviews in Microbiology. 17,95–109. doi: 10.1038/s41579-018-0116-y Nilsson, R. H., Larsson, K. H., Taylor, A. F., Bengtsson-Palme, J., Jeppesen, T. S., Schigel, D., … Abarenkov, K. (2019). The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research, 47,D259-D264. doi: 10.1093/nar/gky1022 Nilsson, R. H., Taylor, A. F., Adams, R. I., Baschien, C., Bengtsson-Palme, J., Cangren, P., … & Abarenkov, K. (2017). Taxonomic annotation of public fungal ITS sequences from the built environment–a report from an April 10–11, 2017 workshop (Aberdeen, UK).MycoKeys, 28, 65. Nilsson, R. H., Tedersoo, L., Abarenkov, K., Ryberg, M., Kristiansson, E., Hartmann, M., … Kõljalg, U. (2012). Five simple guidelines for establishing basic authenticity and reliability of newly generated fungal ITS sequences. MycoKeys, 4, 37–63. doi: 10.3897/mycokeys.4.3606 Noble, W. S. (2009). How does multiple testing correction work?Nature biotechnology, 27, 1135-1137. doi: 10.1038/nbt1209-1135 O’Donnell, K., Ward, T. J., Robert, V. A., Crous, P. W., Geiser, D. M., & Kang, S. (2015). DNA sequence-based identification of Fusarium: Current status and future directions. Phytoparasitica, 43, 583-595. doi: 10.1007/s12600-015-0484-z Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., … Wagner, H. (2019). Vegan: Community Ecology Package. Available: https://CRAN.R-project.org/package=vegan Oliver, A. K., Brown, S. P., Callaham, M. A., & Jumpponen, A. (2015). Polymerase matters: Non-proofreading enzymes inflate fungal community richness estimates by up to 15%. Fungal Ecology, 15, 86-89. doi: 10.1016/j.funeco.2015.03.003 Oliveros, J. (2007). An Interactive Tool for Comparing Lists with Venn Diagrams. Available: http://bioinfogp.cnb.csic.es/tools/venny/index.html Ondov, B. D., Bergman, N. H., & Philippy, A. M. (2011). Interactive metagenomic visualization in a Web browser. BMC Bioinformatics, 12, 385. doi: 10.1186/1471-2105-12-385 Öpik, M., Vanatoa, A., Vanatoa, E., Moora, M., Davison, J., Kalwij, J. M., … Zobel, M. (2010). The online database MaarjAM reveals global and ecosystemic distribution patterns in arbuscular mycorrhizal fungi (Glomeromycota). New Phytologist, 188, 223-241. doi: 10.1111/j.1469-8137.2010.03334.x Paliy, O., & Shankar, V. (2016). Application of multivariate statistical techniques in microbial ecology. Molecular Ecology, 25, 1032–1057. doi: 10.1111/mec.13536 Palmer, J. M., Jusino, M. A., Banik, M. T., & Lindner, D. L. (2018). Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data. PeerJ, 6, e4925. doi: 10.7717/peerj.4925 Pedersen, E. J., Miller, D. L., Simpson, G. L., & Ross, N. (2019). Hierarchical generalized additive models in ecology: An introduction with mgcv. PeerJ, 7, e6876. doi: 10.7717/peerj.6876 Pinheiro, J., Bates, D., & DebRoy, S. (2011). Nlme: Linear and nonlinear mixed effects models Available: http://cran.rproject.org/web/packages/nlme/ Pinol, J., Senar, M. A., & Symondson, W. O. (2019). The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Molecular Ecology, 28, 407-419. doi: 10.1111/mec.14776 Piombo, E., Abdelfattah, A., Droby, S., Wisniewski, M., Spadaro, D., & Schena, L. (2021). Metagenomics approaches for the detection and surveillance of emerging and recurrent plant pathogens.Microorganisms, 9, 188. doi: 10.3390/microorganisms9010188 Porras-Alfaro, A., Liu, K. L., Kuske, C. R., & Xie, G. (2014). From genus to phylum: Large-subunit and internal transcribed spacer rRNA operon regions show similar classification accuracies influenced by database composition. Applied and Environmental Microbiology, 80,829-840. doi: 10.1128/aem.02894-13 Põlme, S., Abarenkov, K., Nilsson, R. H., Lindahl, B. D., Clemmensen, K. E., Kauserud, H., … Tedersoo, L. (2020). FungalTraits: A user-friendly traits database of fungi and fungus-like stramenopiles.Fungal Diversity, 105, 1–16. doi: 10.1007/s13225-020-00466-2 Qian, H., & Jin, Y. (2016). An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure. Journal of Plant Ecology, 9, 233-239. doi: 10.1093/jpe/rtv047 Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., … Glöckner, F. O. (2013). The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research, 41, D590–D596. doi: 10.1093/nar/gks1219 Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J., & Segata, N. (2017). Shotgun metagenomics, from sampling to analysis. Nature Biotechnology, 35, 833-844. doi: 10.1038/nbt.3935 Quinn, T. P., Erb, I., Gloor, G., Notredame, C., Richardson, M. F., & Crowley, T. M. (2019). A field guide for the compositional analysis of any-omics data. GigaScience, 8, giz107. doi: 10.1093/gigascience/giz107 Radajewski, S., McDonald, I. R., & Murrell, J. C. (2003). Stable-isotope probing of nucleic acids: A window to the function of uncultured microorganisms. Current Opinion in Biotechnology, 14, 296-302. doi: 10.1016/S0958-1669(03)00064-8 Rajala, T., Peltoniemi, M., Hantula, J., Mäkipää, R., & Pennanen, T. (2011). RNA reveals a succession of active fungi during the decay of Norway spruce logs. Fungal Ecology, 4, 437–448. doi: 10.1016/j.funeco.2011.05.005 Rammitsu, K., Kajita, T., Imai, R., & Ogura-Tsujita, Y. (2021). Strong primer bias for Tulasnellaceae fungi in metabarcoding: Specific primers improve the characterization of the mycorrhizal communities of epiphytic orchids. Mycoscience, 62, MYC551. doi: 10.47371/mycosci.2021.06.005 Rao, C., Coyte, K. Z., Bainter, W., Geha, R. S., Martin, C. R., & Rakoff-Nahoum, S. (2021). Multi-kingdom ecological drivers of microbiota assembly in preterm infants. Nature, 591, 633-638. doi: 10.1038/s41586-021-03241-8 Ricotta, C., Pavoine, S., Cerabolini, B. E., & Pillar, V. D. (2021). A new method for indicator species analysis in the framework of multivariate analysis of variance. Journal of Vegetation Science, 32, e13013. doi: 10.1111/jvs.13013 Rillig, M. C., Ryo, M., Lehmann, A., Aguilar-Trigueros, C. A., Buchert, S., Wulf, A., …Yang, G. (2019). The role of multiple global change factors in driving soil functions and microbial biodiversity.Science, 366, 886-890. doi: 10.1126/science.aay2832 Rivers, A. R., Weber, K. C., Gardner, T. G., Liu, S., & Armstrong, S. D. (2018). ITSxpress: Software to rapidly trim internally transcribed spacer sequences with quality scores for marker gene analysis.F1000Research, 7, 1418. doi: 10.12688/f1000research.15704.1 Rognes, T., Flouri, T., Nichols, B., Quince, C., & Mahé, F. (2016). VSEARCH: A versatile open source tool for metagenomics. PeerJ, 4,e2584. doi: 10.7717/peerj.2584 Roy, J., Mazel, F., Sosa‐Hernández, M. A., Dueñas, J. F., Hempel, S., Zinger, L., & Rillig, M. C. (2019). The relative importance of ecological drivers of arbuscular mycorrhizal fungal distribution varies with taxon phylogenetic resolution. New Phytologist, 224,936-948. doi: 10.1111/nph.16080 Röttjers, L., & Faust, K. (2018). From hairballs to hypotheses – biological insights from microbial networks. FEMS Microbiology Reviews, 42, 761-780. doi: 10.1093/femsre/fuy030 Sato, H., Sogo, Y., Doi, H., & Yamanaka, H. (2017). Usefulness and limitations of sample pooling for environmental DNA metabarcoding of freshwater fish communities. Scientific Reports, 7, 14860. doi: 10.1038/s41598-017-14978-6 Sato, M. P., Ogura, Y., Nakamura, K., Nishida, R., Gotoh, Y., Hayashi, M., … Hayashi, T. (2019). Comparison of the sequencing bias of currently available library preparation kits for Illumina sequencing of bacterial genomes and metagenomes. DNA Research, 26, 391-398. doi: 10.1093/dnares/dsz017 Schloss, P. D. (2020). Reintroducing mothur: 10 years later.Applied and Environmental Microbiology, 86, e02343-19. doi: 10.1128/AEM.02343-19 Schnell, I. B., Bohmann, K., & Gilbert, M. T.P. (2015). Tag jumps illuminated – reducing sequence-to-sample misidentifications in metabarcoding studies. Molecular Ecology Resources, 15, 1289–1303. doi: 10.1111/1755-0998.12402 Schwarzenbach, K., Enkerli, J., & Widmer, F. (2007). Objective criteria to assess representativity of soil fungal community profiles.Journal of Microbiological Methods, 68, 358-366. doi: 10.1016/j.mimet.2006.09.015 Singer, E., Wagner, M., & Woyke, T. (2017). Capturing the genetic makeup of the active microbiome in situ. The ISME Journal, 11, 1949-1963. doi: 10.1038/ismej.2017.59 Song, Z., Schlatter, D., Kennedy, P., Kinkel, L. L., Kistler, H. C., Nguyen, N., & Bates, S. T. (2015). Effort versus reward: Preparing samples for fungal community characterization in high-throughput sequencing surveys of soils. PLoS ONE, 10, e0127234. doi: 10.1371/journal.pone.0127234 Sze, M. A., & Schloss, P. D. (2019). The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data.mSphere, 26, e00163-19. doi: 10.1128/mSphere.00163-19 Strobl, C., Hothorn, T., & Zeileis, A. (2009). Party on! A new, conditional variable-importance measure for random forests available in the party package. R Journal, 1, 14–17. doi: 10.32614/RJ-2009-013 Sun, X., Hu, Y. H., Wang, J., Fang, C., Li, J., Han, M., … Gong, M. (2021). Efficient and stable metabarcoding sequencing data using a DNBSEQ-G400 sequencer validated by comprehensive community analyses.Gigabyte, 2021, 1-15. doi: 10.1101/2020.07.02.185710 Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018).Environmental DNA: For biodiversity research and monitoring. London: Oxford University Press. Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C., & Willerslev, E. (2012). Towards next‐generation biodiversity assessment using DNA metabarcoding. Molecular Ecology, 21, 2045-2050. doi: 10.1111/j.1365-294x.2012.05470.x Talas, L., Stivrins, N., Veski, S., Tedersoo, L., & Kisand, V. (2021). Sedimentary ancient DNA (sedaDNA) reveals fungal diversity and environmental drivers of community changes throughout the holocene in the present boreal Lake Lielais Svētiņu (Eastern Latvia).Microorganisms, 9, 719. doi: 10.3390/microorganisms9040719 Tanabe, A. S., & Toju, H. (2013). Two new computational methods for universal DNA Barcoding: A benchmark using barcode sequences of bacteria, archaea, animals, fungi, and land plants. PLoS ONE, 8, e76910. doi: 10.1371/journal.pone.0076910 Taylor, D. L., Hollingsworth, T. N., McFarland, J. W., Lennon, N. J., Nussbaum, C., & Ruess, R. W. (2014). A first comprehensive census of fungi in soil reveals both hyperdiversity and fine-scale niche partitioning. Ecological Monographs, 84, 3-20. doi: 10.1890/12-1693.1 Tedersoo, L., Albertsen, M., Anslan, S., & Callahan, B. (2021a). Perspectives and benefits of high-throughput long-read sequencing in microbial ecology. Applied and Environmental Microbiology, 87, e00626-21. doi: 10.1128/aem.00626-21 Tedersoo, L., Anslan, S., Bahram, M., Drenkhan, R., Pritsch, K., Buegger, F., … Abarenkov, K. (2020). Regional-scale in-depth analysis of soil fungal diversity reveals strong pH and plant species effects in Northern Europe. Frontiers in Microbiology, 11, 1953. doi: 10.3389/fmicb.2020.01953 Tedersoo, L., Anslan, S., Bahram, M., Kõljalg, U., & Abarenkov, K. (2020). Identifying the ‘unidentified’fungi: A global-scale long-read third-generation sequencing approach. Fungal Diversity, 103,273-293. doi: 10.1007/s13225-020-00456-4 Tedersoo, L., Anslan, S., Bahram, M., Põlme, S., Riit, T., Liiv, I., … Abarenkov, K. (2015). Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. MycoKeys, 10, 1-43. doi: 10.3897/mycokeys.10.4852 Tedersoo, L. et al. 2021b. GSMc. Fungal Diversity, pending revision. Tedersoo, L., Bahram, M., Põlme, S., Kõljalg, U., Yorou, N. S., Wijesundera, R., … Abarenkov, K. (2014). Global diversity and geography of soil fungi. Science, 346, 1078. doi: 10.1126/science.1256688 Tedersoo, L., & Lindahl, B. (2016). Fungal identification biases in microbiome projects. Environmental Microbiology Reports, 8, 774-779. doi: 10.1111/1758-2229.12438 Tipton, L., Müller, C. L., Kurtz, Z. D., Huang, L., Kleerup, E., Morris, A., … Ghedin, E. (2018). Fungi stabilize connectivity in the lung and skin microbial ecosystems. Microbiome, 6, 12. doi: 10.1186/s40168-017-0393-0 Tucker, C. M., Cadotte, M. W., Carvalho, S. B., Davies, T. J., Ferrier, S., Fritz, S. A., … Pavoine, S. (2017). A guide to phylogenetic metrics for conservation, community ecology and macroecology.Biological Reviews, 92, 698-715. doi: 10.1111/brv.12252 Turon, X., Antich, A., Palacín, C., Præbel, K., & Wangensteen, O. S. (2020). From metabarcoding to metaphylogeography: Separating the wheat from the chaff. Ecological Applications, 30, e02036. doi: 10.1002/eap.2036 U’Ren, J. M., Lutzoni, F., Miadlikowska, J., Zimmerman, N. B., Carbone, I., May, G., & Arnold, A. E. (2019). Host availability drives distributions of fungal endophytes in the imperilled boreal realm.Nature Ecology & Evolution, 3, 1430-1437. doi: 10.1038/s41559-019-0975-2 U’Ren, J. M., Riddle, J. M., Monacell, J. T., Carbone, I., Miadlikowska, J., & Arnold, A. E. (2014). Tissue storage and primer selection influence pyrosequencing‐based inferences of diversity and community composition of endolichenic and endophytic fungi. Molecular Ecology Resources, 14, 1032-1048. doi: 10.1111/1755-0998.12252 van Dijk, E. L., Jaszczyszyn, Y., Naquin, D., & Thermes, C. (2019). The third revolution in sequencing technology. Trends in Genetics, 34, 666-681. doi: 10.1016/j.tig.2018.05.008 Vasar, M., Davison, J., Neuenkamp, L., Sepp, S. K., Young, J. P. W., Moora, M., & Öpik, M. (2021). User‐friendly bioinformatics pipeline gDAT (graphical downstream analysis tool) for analysing rDNA sequences.Molecular Ecology Resources, 21, 1380-1392. Vestheim, H., Deagle, B. E., & Jarman, S. N. (2011). Application of blocking oligonucleotides to improve signal-to-noise ratio in a PCR.Methods in Molecular Biology, 687, 265-274. doi: 10.1007/978-1-60761-944-4_19 Vetrovsky, T., Baldrian, P., Morais, D., & Berger, B. (2018). SEED 2: A user-friendly platform for amplicon high-throughput sequencing data analyses. Bioinformatics, 34, 2292–2294. doi: 10.1093/bioinformatics/bty071 Vetrovsky, T., Morais, D., Kohout, P., Lepinay, C., Algora, C., Awokunle Hollá, S., … Baldrian, P. (2020). GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies. Scientific Data, 7, 228. doi: 10.1038/s41597-020-0567-7 Wagner, A. O., Malin, C., Knapp, B. A., & Illmer, P. (2008). Removal of free extracellular DNA from environmental samples by ethidium monoazide and propidium monoazide. Applied and Environmental Microbiology, 74, 2537-2539. doi: 10.1128/AEM.02288-07 Wang, F., Che, R., Deng, Y., Wu, Y., Tang, L., Xu, Z., … Cui, X. (2021). Air-drying and long time preservation of soil do not significantly impact microbial community composition and structure.Soil Biology and Biochemistry, 157, 108238. 10.1016/j.soilbio.2021.108238 Wang, H., Qi, J., Xiao, D., Wang, Z., & Tian, K. (2017). A re-evaluation of dilution for eliminating PCR inhibition in soil DNA samples. Soil Biology and Biochemistry, 106, 109-118. doi: 10.1016/j.soilbio.2016.12.011 Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73, 5261-5267. doi: 10.1128/aem.00062-07 Washburne, A. D., Morton, J. T., Sanders, J., McDonald, D., Zhu, Q., Oliverio, A. M., & Knight, R. (2018). Methods for phylogenetic analysis of microbiome data. Nature Microbiology, 3, 652-661. doi: 10.1038/s41564-018-0156-0 Webb, C. O., Ackerly, D. D., & Kembel, S. W. (2008). Phylocom: Software for the Analysis of Community Phylogenetic Structure and Trait Evolution, Version 4.0.1 [software]. Retrieved from http://www.phylodiversity.net/phylocom/ Weete, J. D., Abril, M., & Blackwell, M. (2010). Phylogenetic distribution of fungal sterols. PloS ONE, 5, e10899. doi: 10.1371/journal.pone.0010899 Weiss, S., Van Treuren, W., Lozupone, C., Faust, K., Friedman, J., Deng, Y., … Birmingham, A. (2016). Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. The ISME Journal, 10, 1669-1681. doi: 10.1038/ismej.2015.235 White, J. R., Maddox, C., White, O., Angiuoli, S. V., & Fricke, W. F. (2013). CloVR-ITS: automated internal transcribed spacer amplicon sequence analysis pipeline for the characterization of fungal microbiota. Microbiome, 1, 6. doi: 10.1186/2049-2618-1-6 Witek, K., Jupe, F., Witek, A. I., Baker, D., Clark, M. D., & Jones, J. D. (2016). Accelerated cloning of a potato late blight–resistance gene using RenSeq and SMRT sequencing. Nature Biotechnology, 34,656-660. doi: 10.1038/nbt.3540 Yang, T., Adams, J. M., Shi, Y., He, J-S., Jing, X., Chen, L., Tedersoo, L., & Chu, H. (2017). Plant diversity and productivity drive soil fungal richness in natural grasslands of the Tibetan Plateau. New Phytologist, 215, 756–765. doi: 10.1111/nph.14606 Yoon, G., Gaynanova, I., & Müller, C. L. (2019). Microbial networks in SPRING - semi-parametric rank-based correlation and partial correlation estimation for quantitative microbiome data. Frontiers in Genetics, 10, 516. doi: 10.3389/fgene.2019.00516 Zafeiropoulos, H., Viet, H. Q., Vasileiadou, K., Potirakis, A., Arvanitidis, C., Topalis, P., … Pafilis, E. (2020). PEMA: a flexible Pipeline for Environmental DNA Metabarcoding Analysis of the 16S/18S ribosomal RNA, ITS, and COI marker genes. GigaScience, 9, giaa022. doi: 10.1093/gigascience/giaa022 Zaiko, A., Greenfield, P., Abbott, C., von Ammon, U., Bilewitch, J., Bunce, M., Cristescu, M. E., Chariton, A., Dowle, E., Geller, J., & Ardura Gutierrez, A. (in press). Towards reproducible metabarcoding data‐lessons from an international cross‐laboratory experiment.Molecular Ecology Resources. doi: 10.1111/1755-0998.13485 Zanne, A. E., Abarenkov, K., Afkhami, M. E., Aguilar-Trigueros, C. A., Bates, S., Bhatnagar, J. M., … Moreno, H. F. (2020). Fungal functional ecology: Bringing a trait-based approach to plant-associated fungi. Biological Reviews, 95, 409-433. doi: 10.1111/brv.12570 Zhang, Z. F., Pan, Y. P., Liu. Y., & Li, M. (2021). High diversity of basal fungal lineages and stochastic processes controlled fungal community assembly in mangrove sediments. Applied and Environmental Microbiology, 87, e00928-21. doi: 10.1128/AEM.00928-21 Zhou, J., Deng, Y., Shen, L., Wen, C., Yan, Q., Ning, D., … Brown, J. H. (2016). Temperature mediates continental-scale diversity of microbes in forest soils. Nature Communications, 7, 12083. doi: 10.1038/ncomms12083 Zifcakova, L., Vetrovsky, T., Howe, A., & Baldrian, P. (2016). Microbial activity in forest soil reflects the changes in ecosystem properties between summer and winter. Environmental Microbiology, 18, 288-301. doi: 10.1111/1462-2920.13026 Zimmerman, N. B., & Vitousek, P. M. (2012). Fungal endophyte communities reflect environmental structuring across a Hawaiian landscape. Proceedings of the National Academy of Sciences, 109, 13022-13027. doi: 10.1073/pnas.1209872109 Zinger, L., Bonin, A., Alsos, I. G., Bálint, M., Bik, H., Boyer, F., … De Barba, M. (2019a). DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions.Molecular Ecology, 28, 1857-1862. doi: 10.1111/mec.15060 Zinger, L., Lionnet, C., Benoiston, A. S., Donald, J., Mercier, C., & Boyer, F. (2021). metabaR: an R package for the evaluation and improvement of DNA metabarcoding data quality. Methods in Ecology and Evolution, 12, 586-592. doi: 10.1111/2041-210X.13552 Zinger, L., Taberlet, P., Schimann, H., Bonin, A., Boyer, F., De Barba, M., … Chave, J. (2019b). Body size determines soil community assembly in a tropical forest. Molecular Ecology, 28, 528-543. doi: 10.1111/mec.14919
Table 1. Properties of bioinformatics pipelines used for fungal metabarcoding. Interface: command line (CL).