References
Acinas, S. G., Sarma-Rupavtarm,
R., Klepac-Ceraj, V., & Polz, M. F. (2005). PCR-induced sequence
artifacts and bias: Insights from comparison of two 16S rRNA clone
libraries constructed from the same sample. Applied and
Environmental Microbiology, 71 (12), 8966–8969. doi:
10.1128/aem.71.12.8966-8969.2005
Andruszkiewicz, E. A., Starks, H. A., Chavez, F. P., Sassoubre, L. M.,
Block, B. A., & Boehm, A. B. (2017). Biomonitoring of marine
vertebrates in Monterey Bay using eDNA metabarcoding. PLoS One,
12 (4), e0176343. doi: 10.1371/journal.pone.0176343
Apothéloz-Perret-Gentil, L., Cordonier, A., Straub, F., Iseli, J.,
Esling, P., & Pawlowski, J. (2017). Taxonomy-free molecular diatom
index for high-throughput eDNA biomonitoring. Molecular Ecology
Resources, 17 (6), 1231–1242. doi: 10.1111/1755-0998.12668
Aylagas, E., Borja, Á., Muxika, I., & Rodríguez-Ezpeleta, N. (2018).
Adapting metabarcoding-based benthic biomonitoring into routine marine
ecological status assessment networks. Ecological Indicators, 95 ,
194–202. doi: 10.1016/j.ecolind.2018.07.044
Blaxter, M. L., De Ley, P., Garey, J. R., Liu, L. X., Scheldeman, P.,
Vierstraete, A., . . . Thomas, W. K. (1998). A molecular evolutionary
framework for the phylum Nematoda. Nature, 392 (6671), 71–75.
doi: 10.1038/32160
Bohan, D. A., Vacher, C., Tamaddoni-Nezhad, A., Raybould, A., Dumbrell,
A. J., & Woodward, G. (2017). Next-generation global biomonitoring:
Large-scale, automated reconstruction of ecological networks.Trends in Ecology & Evolution, 32 (7), 477–487. doi:
10.1016/j.tree.2017.03.001
Bohmann, K., Evans, A., Gilbert, M. T., Carvalho, G. R., Creer, S.,
Knapp, M., . . . de Bruyn, M. (2014). Environmental DNA for wildlife
biology and biodiversity monitoring. Trends in Ecology &
Evolution, 29 (6), 358–367. doi: 10.1016/j.tree.2014.04.003
Bokulich, N. A., Kaehler, B. D., Rideout, J. R., Dillon, M., Bolyen, E.,
Knight, R., . . . Gregory Caporaso, J. (2018). Optimizing taxonomic
classification of marker-gene amplicon sequences with QIIME 2’s
q2-feature-classifier plugin. Microbiome, 6 (1), 90. doi:
10.1186/s40168-018-0470-z
Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible
trimmer for Illumina sequence data. Bioinformatics, 30 (15),
2114–2120. doi: 10.1093/bioinformatics/btu170
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 (8), 852–857. doi:
10.1038/s41587-019-0209-9
Bragalini, C., Ribière, C., Parisot, N., Vallon, L., Prudent, E.,
Peyretaillade, E., . . . Luis, P. (2014). Solution hybrid selection
capture for the recovery of functional full-length eukaryotic cDNAs from
complex environmental samples. DNA Research, 21 (6), 685–694.
doi: 10.1093/dnares/dsu030
Brandt, M. I., Trouche, B., Quintric, L., Wincker, P., Poulain, J., &
Arnaud-Haond, S. (2019). A flexible pipeline combining clustering and
correction tools for prokaryotic and eukaryotic metabarcoding.bioRxiv , 717355. doi: 10.1101/717355
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 (7), 581–583.
doi: 10.1038/nmeth.3869
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
Cordier, T., Forster, D., Dufresne, Y., Martins, C. I. M., Stoeck, T.,
& Pawlowski, J. (2018). Supervised machine learning outperforms
taxonomy-based environmental DNA metabarcoding applied to biomonitoring.Molecular Ecology Resources, 18 (6), 1381–1391. doi:
10.1111/1755-0998.12926
Costa, C., Fanelli, E., Marini, S., Danovaro, R., & Aguzzi, J. (2020).
Global deep-sea biodiversity research trends highlighted by science
mapping approach. Frontiers in Marine Science, 7 , 384. doi:
10.3389/fmars.2020.00384
Costello, M. J., & Chaudhary, C. (2017). Marine biodiversity,
biogeography, deep-sea gradients, and conservation. Current
Biology, 27 (11), R511–R527. doi: 10.1016/j.cub.2017.04.060
Costello, M. J., Cheung, A., & De Hauwere, N. (2010). Surface area and
the seabed area, volume, depth, slope, and topographic variation for the
world’s seas, oceans, and countries. Environmental Science &
Technology, 44 (23), 8821–8828. doi: 10.1021/es1012752
Creer, S., Fonseca, V. G., Porazinska, D. L., Giblin-Davis, R. M., Sung,
W., Power, D. M., . . . Thomas, W. K. (2010). Ultrasequencing of the
meiofaunal biosphere: Practice, pitfalls and promises. Molecular
Ecology, 19 Suppl 1 , 4–20. doi: 10.1111/j.1365-294X.2009.04473.x
Danovaro, R., Snelgrove, P. V., & Tyler, P. (2014). Challenging the
paradigms of deep-sea ecology. Trends in Ecology & Evolution,
29 (8), 465–475. doi: 10.1016/j.tree.2014.06.002
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 (1), 226. doi: 10.1186/s40168-018-0605-2
Deiner, K., Renshaw, M. A., Li, Y., Olds, B. P., Lodge, D. M., &
Pfrender, M. E. (2017). Long-range PCR allows sequencing of
mitochondrial genomes from environmental DNA. Methods in Ecology
and Evolution, 8 (12), 1888–1898. doi: 10.1111/2041-210X.12836
Dell’Anno, A., Carugati, L., Corinaldesi, C., Riccioni, G., & Danovaro,
R. (2015). Unveiling the biodiversity of deep-sea nematodes through
metabarcoding: Are we ready to bypass the classical taxonomy? PLoS
One, 10 (12), e0144928. doi: 10.1371/journal.pone.0144928
Denonfoux, J., Parisot, N., Dugat-Bony, E., Biderre-Petit, C., Boucher,
D., Morgavi, D. P., . . . Peyret, P. (2013). Gene capture coupled to
high-throughput sequencing as a strategy for targeted metagenome
exploration. DNA Research, 20 (2), 185–196. doi:
10.1093/dnares/dst001
Derocles, S. A. P., Bohan, D. A., Dumbrell, A. J., Kitson, J. J. N.,
Massol, F., Pauvert, C., . . . Evans, D. M. (2018). Biomonitoring for
the 21st century: Integrating next-generation sequencing into ecological
network analysis. In D. A. Bohan, A. J. Dumbrell, G. Woodward, & M.
Jackson (Eds.), Advances in ecological research (Vol. 58, pp.
1–62). San Diego, CA: Academic Press.
Förster, D. W., Bull, J. K., Lenz, D., Autenrieth, M., Paijmans, J. L.
A., Kraus, R. H. S., . . . Fickel, J. (2018). Targeted resequencing of
coding DNA sequences for SNP discovery in nonmodel species.Molecular Ecology Resources, 18 (6), 1356–1373. doi:
10.1111/1755-0998.12924
Gambi, C., & Danovaro, R. (2016). Biodiversity and life strategies of
deep-sea meiofauna and nematode assemblages in the Whittard Canyon
(Celtic margin, NE Atlantic Ocean). Deep Sea Research Part I:
Oceanographic Research Papers, 108 , 13–22. doi:
10.1016/j.dsr.2015.12.001
Gasc, C., & Peyret, P. (2017). Revealing large metagenomic regions
through long DNA fragment hybridization capture. Microbiome,
5 (1), 33. doi: 10.1186/s40168-017-0251-0
Gasc, C., & Peyret, P. (2018). Hybridization capture reveals microbial
diversity missed using current profiling methods. Microbiome,
6 (1), 61. doi: 10.1186/s40168-018-0442-3
Gasc, C., Peyretaillade, E., & Peyret, P. (2016). Sequence capture by
hybridization to explore modern and ancient genomic diversity in model
and nonmodel organisms. Nucleic Acids Research, 44 (10),
4504–4518. doi: 10.1093/nar/gkw309
Gauthier, M., Konecny-Dupré, L., Nguyen, A., Elbrecht, V., Datry, T.,
Douady, C., & Lefébure, T. (2020). Enhancing DNA metabarcoding
performance and applicability with bait capture enrichment and DNA from
conservative ethanol. Molecular Ecology Resources, 20 (1), 79–96.
doi: 10.1111/1755-0998.13088
Ghurye, J. S., Cepeda-Espinoza, V., & Pop, M. (2016). Metagenomic
assembly: Overview, challenges and applications. Yale Journal of
Biology and Medicine, 89 (3), 353–362.
Gnirke, A., Melnikov, A., Maguire, J., Rogov, P., LeProust, E. M.,
Brockman, W., . . . Nusbaum, C. (2009). Solution hybrid selection with
ultra-long oligonucleotides for massively parallel targeted sequencing.Nature Biotechnology, 27 (2), 182–189. doi: 10.1038/nbt.1523
Hajibabaei, M., Shokralla, S., Zhou, X., Singer, G. A., & Baird, D. J.
(2011). Environmental barcoding: A next-generation sequencing approach
for biomonitoring applications using river benthos. PLoS One,
6 (4), e17497. doi: 10.1371/journal.pone.0017497
Jaziri, F., Parisot, N., Abid, A., Denonfoux, J., Ribière, C., Gasc, C.,
. . . Peyret, P. (2014). PhylOPDb: A 16S rRNA oligonucleotide probe
database for prokaryotic identification. Database (Oxford),
2014 (0), bau036. doi: 10.1093/database/bau036
Kanagawa, T. (2003). Bias and artifacts in multitemplate polymerase
chain reactions (PCR). Journal of Bioscience and Bioengineering,
96 (4), 317–323. doi: 10.1016/s1389-1723(03)90130-7
Katoh, K., Misawa, K., Kuma, K., & Miyata, T. (2002). MAFFT: A novel
method for rapid multiple sequence alignment based on fast Fourier
transform. Nucleic Acids Research, 30 (14), 3059–3066. doi:
10.1093/nar/gkf436
Kawahara, A. Y., Breinholt, J. W., Espeland, M., Storer, C., Plotkin,
D., Dexter, K. M., . . . Lohman, D. J. (2018). Phylogenetics of
moth-like butterflies (Papilionoidea: Hedylidae) based on a new 13-locus
target capture probe set. Molecular Phylogenetics and Evolution,
127 , 600–605. doi: 10.1016/j.ympev.2018.06.002
Kopylova, E., Noé, L., & Touzet, H. (2012). SortMeRNA: Fast and
accurate filtering of ribosomal RNAs in metatranscriptomic data.Bioinformatics, 28 (24), 3211–3217. doi:
10.1093/bioinformatics/bts611
Liu, S., Wang, X., Xie, L., Tan, M., Li, Z., Su, X., . . . Zhou, X.
(2016). Mitochondrial capture enriches mito-DNA 100 fold, enabling
PCR-free mitogenomics biodiversity analysis. Molecular Ecology
Resources, 16 (2), 470–479. doi: 10.1111/1755-0998.12472
Machida, R. J., & Knowlton, N. (2012). PCR primers for metazoan nuclear
18S and 28S ribosomal DNA sequences. PLoS One, 7 (9), e46180. doi:
10.1371/journal.pone.0046180
Mahé, F., Rognes, T., Quince, C., de Vargas, C., & Dunthorn, M. (2015).
Swarm v2: Highly-scalable and high-resolution amplicon clustering.PeerJ, 3 , e1420. doi: 10.7717/peerj.1420
Mamanova, L., Coffey, A. J., Scott, C. E., Kozarewa, I., Turner, E. H.,
Kumar, A., . . . Turner, D. J. (2010). Target-enrichment strategies for
next-generation sequencing. Nature Methods, 7 (2), 111–118. doi:
10.1038/nmeth.1419
Martin, M. (2011). Cutadapt removes adapter sequences from
high-throughput sequencing reads. EMBnet Journal, 17 (1), 10. doi:
10.14806/ej.17.1.200
Mendoza, M. L. Z., Sicheritz-Pontén, T., & Gilbert, M. T. P. (2014).
Environmental genes and genomes: Understanding the differences and
challenges in the approaches and software for their analyses.Briefings in Bioinformatics, 16 (5), 745–758. doi:
10.1093/bib/bbv001
Mertes, F., Elsharawy, A., Sauer, S., van Helvoort, J. M. L. M., van der
Zaag, P. J., Franke, A., . . . Brookes, A. J. (2011). Targeted
enrichment of genomic DNA regions for next-generation sequencing.Briefings in Functional Genomics, 10 (6), 374–386. doi:
10.1093/bfgp/elr033
Meyer, M., & Kircher, M. (2010). Illumina sequencing library
preparation for highly multiplexed target capture and sequencing.Cold Spring Harbor Protocols, 2010 (6). doi: 10.1101/pdb.prot5448
Militon, C., Rimour, S., Missaoui, M., Biderre, C., Barra, V., Hill, D.,
. . . Peyret, P. (2007). PhylArray: Phylogenetic probe design algorithm
for microarray. Bioinformatics, 23 (19), 2550–2557. doi:
10.1093/bioinformatics/btm392
Miller, C. S., Baker, B. J., Thomas, B. C., Singer, S. W., & Banfield,
J. F. (2011). EMIRGE: Reconstruction of full-length ribosomal genes from
microbial community short read sequencing data. Genome Biology,
12 (5), R44–R44. doi: 10.1186/gb-2011-12-5-r44
Miya, M., Sato, Y., Fukunaga, T., Sado, T., Poulsen, J. Y., Sato, K., .
. . Iwasaki, W. (2015). MiFish, a set of universal PCR primers for
metabarcoding environmental DNA from fishes: Detection of more than 230
subtropical marine species. Royal Society Open Science, 2 (7),
150088. doi: 10.1098/rsos.150088
Oksanen, J., Kindt, R., Legendre, P., O’Hara, B., Simpson, G. L.,
Solymos, P. M., . . . Wagner, H. (2008). The vegan package.Community Ecology Package.
Parada, A. E., Needham, D. M., & Fuhrman, J. A. (2016). Every base
matters: Assessing small subunit rRNA primers for marine microbiomes
with mock communities, time series and global field samples.Environmental Microbiology, 18 (5), 1403–1414. doi:
10.1111/1462-2920.13023
Parisot, N., Denonfoux, J., Dugat-Bony, E., Peyret, P., &
Peyretaillade, E. (2012). KASpOD—A web service for highly specific and
explorative oligonucleotide design. Bioinformatics, 28 (23),
3161–3162. doi: 10.1093/bioinformatics/bts597
Porter, T. M., & Hajibabaei, M. (2018). Scaling up: A guide to
high-throughput genomic approaches for biodiversity analysis.Molecular Ecology, 27 (2), 313–338. doi: 10.1111/mec.14478
Pruesse, E., Quast, C., Knittel, K., Fuchs, B. M., Ludwig, W., Peplies,
J., & Glöckner, F. O. (2007). SILVA: A comprehensive online resource
for quality checked and aligned ribosomal RNA sequence data compatible
with ARB. Nucleic Acids Research, 35 (21), 7188–7196. doi:
10.1093/nar/gkm864
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 (Database issue), D590–D596. doi:
10.1093/nar/gks1219
Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J., & Segata, N.
(2017). Erratum: Corrigendum: Shotgun metagenomics, from sampling to
analysis. Nature Biotechnology, 35 (12), 1211. doi:
10.1038/nbt1217-1211b
Ranchou-Peyruse, M., Gasc, C., Guignard, M., Aüllo, T., Dequidt, D.,
Peyret, P., & Ranchou-Peyruse, A. (2017). The sequence capture by
hybridization: A new approach for revealing the potential of
mono-aromatic hydrocarbons bioattenuation in a deep oligotrophic
aquifer. Microbial Biotechnology, 10 (2), 469–479. doi:
10.1111/1751-7915.12426
Ribière, C., Beugnot, R., Parisot, N., Gasc, C., Defois, C., Denonfoux,
J., . . . Peyret, P. (2016). Targeted gene capture by hybridization to
illuminate ecosystem functioning. In F. Martin & S. Uroz (Eds.),Microbial environmental genomics (MEG) (pp. 167–182). New York,
NY: Springer.
Sayers, E. W., Cavanaugh, M., Clark, K., Ostell, J., Pruitt, K. D., &
Karsch-Mizrachi, I. (2020). GenBank. Nucleic Acids Research,
48 (D1), D84–D86. doi: 10.1093/nar/gkz956
Schmieder, R., & Edwards, R. (2011). Quality control and preprocessing
of metagenomic datasets. Bioinformatics , 27(6), 863-864.
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 (6),
1289–1303. doi: 10.1111/1755-0998.12402
Seeber, P. A., McEwen, G. K., Löber, U., Förster, D. W., East, M. L.,
Melzheimer, J., & Greenwood, A. D. (2019). Terrestrial mammal
surveillance using hybridization capture of environmental DNA from
African waterholes. Molecular Ecology Resources, 19 (6),
1486–1496. doi: 10.1111/1755-0998.13069
Sefc, K. M., Payne, R. B., & Sorenson, M. D. (2007). Single base errors
in PCR products from avian museum specimens and their effect on
estimates of historical genetic diversity. Conservation Genetics,
8 (4), 879–884. doi: 10.1007/s10592-006-9240-8
Shokralla, S., Gibson, J. F., King, I., Baird, D. J., Janzen, D. H.,
Hallwachs, W., & Hajibabaei, M. (2016). Environmental DNA barcode
sequence capture: Targeted, PCR-free sequence capture for biodiversity
analysis from bulk environmental samples. bioRxiv , 087437. doi:
10.1101/087437
Singer, G. A. C., Fahner, N. A., Barnes, J. G., McCarthy, A., &
Hajibabaei, M. (2019). Comprehensive biodiversity analysis via
ultra-deep patterned flow cell technology: A case study of eDNA
metabarcoding seawater. Scientific Reports, 9 (1), 5991. doi:
10.1038/s41598-019-42455-9
Sinniger, F., Pawlowski, J., Harii, S., Gooday, A. J., Yamamoto, H.,
Chevaldonné, P., . . . Creer, S. (2016). Worldwide analysis of
sedimentary DNA reveals major gaps in taxonomic knowledge of deep-sea
benthos. Frontiers in Marine Science, 3 , 92. doi:
10.3389/fmars.2016.00092
Smyth, R. P., Schlub, T. E., Grimm, A., Venturi, V., Chopra, A., Mallal,
S., . . . Mak, J. (2010). Reducing chimera formation during PCR
amplification to ensure accurate genotyping. Gene, 469 (1-2),
45–51. doi: 10.1016/j.gene.2010.08.009
Taberlet, P., Coissac, E., Hajibabaei, M., & Rieseberg, L. H. (2012).
Environmental DNA. Molecular Ecology, 21 (8), 1789–1793. doi:
10.1111/j.1365-294x.2012.05542.x
Thomsen, P. F., & Willerslev, E. (2015). Environmental DNA – An
emerging tool in conservation for monitoring past and present
biodiversity. Biological Conservation, 183 , 4–18. doi:
10.1016/j.biocon.2014.11.019
Torti, A., Lever, M. A., & Jørgensen, B. B. (2015). Origin, dynamics,
and implications of extracellular DNA pools in marine sediments.Marine Genomics, 24 , 185–196. doi: 10.1016/j.margen.2015.08.007
Valentini, A., Pompanon, F., & Taberlet, P. (2009). DNA barcoding for
ecologists. Trends in Ecology & Evolution, 24 (2), 110–117. doi:
10.1016/j.tree.2008.09.011
Wangensteen, O. S., Palacín, C., Guardiola, M., & Turon, X. (2018). DNA
metabarcoding of littoral hard-bottom communities: High diversity and
database gaps revealed by two molecular markers. PeerJ, 6 , e4705.
doi: 10.7717/peerj.4705
Wilcox, T. M., Zarn, K. E., Piggott, M. P., Young, M. K., McKelvey, K.
S., & Schwartz, M. K. (2018). Capture enrichment of aquatic
environmental DNA: A first proof of concept. Molecular Ecology
Resources, 18 (6), 1392–1401. doi: 10.1111/1755-0998.12928
Wilson, J. J., Brandon-Mong, G. J., Gan, H. M., & Sing, K. W. (2018).
High-throughput terrestrial biodiversity assessments: Mitochondrial
metabarcoding, metagenomics or metatranscriptomics? Mitochondrial
DNA Part A: DNA Mapping, Sequencing, and Analysis, 30 (1), 60–67. doi:
10.1080/24701394.2018.1455189
Wood, D. E., Lu, J., & Langmead, B. (2019). Improved metagenomic
analysis with Kraken 2. Genome Biology, 20 (1), 257. doi:
10.1186/s13059-019-1891-0
Wood, D. E., & Salzberg, S. L. (2014). Kraken: Ultrafast metagenomic
sequence classification using exact alignments. Genome Biology,
15 (3), R46. doi: 10.1186/gb-2014-15-3-r46
Xu, J. (2006). Microbial ecology in the age of genomics and
metagenomics: Concepts, tools, and recent advances. Molecular
Ecology, 15 (7), 1713–1731. doi: 10.1111/j.1365-294x.2006.02882.x
Yamamoto, S., Masuda, R., Sato, Y., Sado, T., Araki, H., Kondoh, M., . .
. Miya, M. (2017). Environmental DNA metabarcoding reveals local fish
communities in a species-rich coastal sea. Scientific Reports, 7 ,
40368. doi: 10.1038/srep40368
Zeppilli, D., Leduc, D., Fontanier, C., Fontaneto, D., Fuchs, S.,
Gooday, A. J., . . . Fernandes, D. (2018). Characteristics of meiofauna
in extreme marine ecosystems: A review. Marine Biodiversity,
48 (1), 35–71. doi: 10.1007/s12526-017-0815-z