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