Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. idvriyi elnn napaeaysaea naamn aedet nhooei atr.Classical factors. anthropogenic the to address due to rate scalable alarming not an and resource-intensive, at time-consuming, scale are planetary approaches a monitoring biodiversity on declining is Biodiversity Abstract G.U – 0000-0003-4086-7445 ORCiD: S.M 0000-0002-9114-8793- ORCiD: Biology, Molecular and (G.U. Cellular [email protected] for Correspondence: CSIR-Centre Species, Endangered of India Hyderabad, Conservation the for Laboratory Umapathy PCR-free Govindhaswamy and using Manu Shivakumara Life of Tree title: the Running across eDNA Extracellular Biomonitoring of for Sequencing Workflow Ultra-deep Metagenomic for Novel adapted A and ecosystems different in ARTICLE tested RESOURCE be availability life increasing can of tree the approach the and our across sequencing project, biodiversity of biogenome of one costs assessment earth about decreasing rapid with the microorgan- large-scale With detected from from effectively brackish workflow. resources life, be hyper-diverse reproducible can of genomic Fishes, large tree our of and the a using Arthropods across reads Chilika, as biodiversity paired-end such in that macroorganisms billion show setup low-abundant we relatively experimental demonstrate statistics, the We spatially-replicated incidence-based to pilot-scale Using isms algorithm. a ancestor India. in common in next-generation lowest ecosystem approach ultra-deep dual lagoon pro- a an our enrichment the in step, of DNA using preparation life utility extracellular strategy library of assignment customised the PCR-free tree pseudo-taxonomic a completely the a of a across and comprising samples, data workflow sequencing, water biodiversity metagenomic filtered unbiased novel large-volume biomonitoring, deliver a from next-generation can describe tocol of using we that potential organisms Here, technologies of full genomic assay. groups the PCR-free single targeted utilise To develop monitoring to to biases. limited intended environ- PCR-induced currently we various The is from evaluating scope for suffers crisis. its solution which However, biodiversity holistic metabarcoding, current entities. and ecological scalable, the various efficient, monitoring address an in biodiversity provides to changes Classical framework scalable factors. biomonitoring anthropogenic not next-generation to DNA-based and due mental rate resource-intensive, alarming time-consuming, an at are scale approaches planetary a on declining is Biodiversity Abstract 2021 22, February 1 Manu Shivakumara of Sequencing eDNA Ultra-deep Extracellular PCR-free using the Life across of Biomonitoring Tree for Workflow Metagenomic Novel A etefrClua n oeua ilg CSIR Biology Molecular and Cellular for Centre imntrn costete flife of tree the across Biomonitoring 1 n oidawm Umapathy Govindhaswamy and # ,saucm.e.n(S.M.) [email protected] ), # 1 1 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. N na niomna ape(iue1,eN-ae imntrn a mre sapwru new powerful Numerous 2017). a al., of as define et sources (Deiner emerged clearly various communities has to ecological exploiting biomonitoring survey and By we eDNA-based way 2019), 2020). 1), the al., Stewart, revolutionised (Figure et 2016; has sample considerable that Turner, Rodriguez-ezpeleta environmental technique been & 2020; an also al., (Barnes in has biomo- et eDNA DNA (Pawlowski there eDNA-based of eDNA advances, 2012a). of ecology term technical al., development the the the et methodological the understand with (Taberlet the utilising to Along air) in ecosystem effort 2019). soil, strides water, (Seymour, the tremendous techniques (e.g., in witnessed nitoring samples taxa decade environmental various last whole of mole- 2015). from The (eDNA)-based Willerslev, presence directly DNA & the Environmental extracted (Thomsen detect scale. methods DNA large biomonitoring techniques a classical biomonitoring over on advantages eDNA-based deploy several to of offer scalable identification methods easily manual to cular not require before, are resource-intensive, ever and time-consuming, life. than specimens, of are large-scale techniques a encyclopedia at biomonitoring the strategies. biodiversity Classical in management monitor few catalogued guide and next being and assess the before policies to in even conservation imperative extinct extinct chart that Under become go go estimated 2019). has might may U.N. it Services, and species Therefore, the Ecosystem extinction many by and with scenario, Biodiversity threatened report current on be assessment the long-lasting Platform may global have the Science-Policy species may A (Intergovernmental to eukaryotic and dropped services. decades million irreversible compared have and is a times species functioning species to of of many ecosystem up thousands Extinction of the 2017). to sizes on 2015, hundreds al., population effects increased et The have (Ceballos 2020). loss, rates rate habitat background al., extinction change, threat et land-use species impending pollution, (Ceballos an and as cata- currently change significantly, such to is factors climate of years there anthropogenic However, years various of and 2013). to hundreds 250 Given majority poaching, al., due take despite earth. the extinction et would science mass (Costello on 2014), it discovery, sixth alone to exist al., of species species unknown 2016) et novel eukaryotic remain the of Lennon, (Parr diversity all rate database & microbial logue current life (Locey the the of At microbes of exploration. encyclopedia of most scientific the species and of environ- diversity trillion various eukaryotic completeness a inhabit of the to to lineages and up ( adapted evolutionary million contested estimates and and 8.7 the fourth these 2011) evolved about a All have that al., and estimate life Eukaryota, et evolution. studies Bacteria, of (Mora accepted of Archaea, tree Widely years the domains: earth. three across of on to ments Organisms billions belong of Viruses. life of result of category tree the the is up earth make that on biodiversity vast The INTRODUCTION Life of of Tree tree Metagenomics, the ing, across be biodiversity can sequencing of approach Keywords: assessment of our rapid costs project, large-scale decreasing biogenome for the earth adapted With with to the and life. detected from workflow. ecosystems microorganisms different resources effectively reproducible from in genomic be our of tested life, availability can using increasing of Using Fishes, reads the tree and paired-end and India. billion the Arthropods spatially- in one as across pilot-scale ecosystem about such biodiversity a lagoon macroorganisms in brackish that low-abundant approach hyper-diverse show relatively our large we of a statistics, utility Chilika, dual the incidence-based in the preparation demonstrate setup using We library experimental strategy assignment PCR-free replicated algorithm. pseudo-taxonomic completely ancestor a a and common sequencing, samples, lowest DNA next-generation extracellular water customised ultra-deep in filtered a an life of large-volume step, of comprising workflow tree from metagenomic the novel suffers across protocol a data which intended describe enrichment biodiversity we we metabarcoding, unbiased Here, biomonitoring, deliver assay. using next-generation can single of that organisms a potential technologies its of full genomic However, PCR-free the groups entities. develop utilise targeted To to ecological various monitoring biases. in PCR-induced to various changes limited from evaluating currently for solution is holistic scope and provides framework scalable, biomonitoring efficient, next-generation an DNA-based environmental The crisis. biodiversity current niomna N,EtaellrDA etGnrto imntrn,SognSequenc- Shotgun Biomonitoring, Next-Generation DNA, Extracellular DNA, Environmental 2 ± . ilo)seiso Eukaryotes of species million) 1.3 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. htiflec ahohr(acmt,20) etgnrto imntrn ssahlsi prahb in- machine-learning by using approach life derived holistic of networks a web ecological interacting uses multi-layered eDNA-based continually large-scale biomonitoring a the from next-generation is properties in 2009), network ecosystem meta-ecosystems, (Bascompte, ferring the other to incorporating Since each genes by 2020). influence from biomonitoring al., that levels, classical et organisational (Makiola of framework ecological limits biomonitoring of the current 2017). spectrum all the al., the et broader for push to (Bohan applicability a to barcodes biomonitoring several their next-generation aims DNA Nevertheless, restrict the biomonitoring library as that decades. known Next-generation approaches the coming bar- biomonitoring targeted eDNA-based complete the DNA the of to frontier to in of next inherent plan mission millions are and biodiversity amassing limitations planetary species is and available eukaryotic disadvantages a consortium were of with Life taxa range organisms of related wide multicellular Barcode closely taxonomic a between International low from resolution The at species, conserved taxonomic codes 2019). invasive are high al., single that a et a a ITS) provide reference (Meiklejohn rbcL-matK, or of and large COI, Kingdom) single-species monitoring Second, (e.g., (e.g., 2019). a classical barcodes (Seymour, ranks of eDNA-based existing DNA macro-invertebrates monitoring standardised and of the species fishes of targeted approaches with multiple of databases of targeted communities synonymous or idea or was the 2020) the species, taxa adopted keystone al., First, related readily reasons. et of community main (Jensen two group scientific hybridisation species of as The single because such 2019). a group approaches biomonitoring a al., targeting PCR-free used detect Recently, et for is to marker. assay employed utilised (Seeber barcoding PCR is were quantitative common metabarcoding sequencing a PCR-based a Routinely, approaches universal capture sharing detected. a targeted are taxa and taxa sensitively, related to related species of limited of single group currently a a detect are or to biomonitoring species specific eDNA-based a the in where in employed environments of fast-changing methodologies the needs The on the check for paleo-communities a suitable keep and techniques to past Anthropocene. eDNA-based high required reconstruct current make extremely stra- programs, to scalability an biomonitoring sampling used and with large-scale annual be flexibility sediments very can or Such deep centuries a seasonal in 2018). to of with preserved al., years (B´alint resolution DNA biomonitoring et from such extracellular temporal ranging long-term Finally, Further, resolution application high benefit 2018). 2020). temporal time-sensitive a might al., al., with a months et et particles few (Nagler for (Thomas tegies soil a suitable difficult surface-reactive to is is weeks suspended organisms days extra-organismal few to of Whereas, few sampling bound 2018). a direct DNA al., of ecology where extracellular et that resolution functional species Lennon DNA invasive the temporal 2016; relic detecting studying al., moderate as as et for considered a (Carini suited are with signal 1) DNA best DNA functional (Figure extracellular is desired applications and DNA the various extra-organismal organismal obscures for while biodiversity example, communities, scalability For of microbial ecological resolutions 2014). offer of (Dysthe sample spatio-temporal sampling al., a repeated of are et in sample for range present samples same (Bohmann need DNA wide the the environmental eDNA and a of eliminating Thus, taxa providing types organisms, diverse different taxa. by of target the set of to Fourth, different used 2018). range a For al., be detect wide can et 2015). to sample a al., single repurposed other et a across be and Torti that can organisms DNA, sense 2016; the from from extracellular Turner, in invertebrates, DNA sizes & scalable, of microorganisms, various biologically (Barnes sources contain 1) of multiple can (Figure particles sample contain sample life biological per typically sediment of samples incurred bulk tree eDNA a cost the Third, instance, economic across increases. West the biomonitoring organisms project (e.g., eDNA-based reduces different the effort in many sequencing of used minimal next-generation scale methods with the and molecular ecosystems as PCR of sampling entire nature quantitative in covering scalability high-throughput as samples physical the such Such of Second, electrofishing. number 2021). or large al., bio- nets et a significantly classical gill of requires the using communities surveying collection of fish than most enables detect resources than to and effort samples time water less less filtering very ecological example, rela 3 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. ssml olcin niomna N xrcin irr rprto,sqecn,adbioinformatics. and sequencing, by such preparation, introduced pipeline library biomonitoring artefacts to the extraction, approach and of DNA top-down step reads every environmental a duplicate at followed collection, solutions We uninformative deduced sample samples 2015). of logically of environmental as Zador, adapting number in & by proportion high issues (Kebschull microbes overwhelming these libraries of a the alleviate sequencing abundance and 2020), of high 2017) al., amplification the al., et to PCR et due Singer assignment taxa (e.g., Stat taxonomic overall macrobial between databases (e.g., of to efficiencies proportion reference relative lysis low incomplete a in taxa 2017), Tara differences to microbial al., (e.g., to et due area (Djurhuus due vast reads taxa bias a of of monitoring a extraction from range of DNA wide biodiversity while collection a the 2020)), namely, encountered from of al., approach, cell-types representation are et metagenomic unbiased (Sunagawa a that an project using obtain challenges ecosystems oceans to main large samples in of five life number identified large of data we tree to sequences. the survey, sampling genome across literature transitioning from biodiversity whole the era, of for biogenome number on factor earth growing limiting Based Therefore, the the the life. for from of be pipeline benefit tree biomonitoring could will futuristic in- the that lab a across analysis, sequencing approaches. dry develop biomonitoring metagenomic genome followed and to next-generation various adopting aimed lab, project, untargeted for of we wet to barrier the completion field, biomonitoring a and of targeted the species be progress phase from known at not the first every challenges will with sequencing sequences the technical future, finally reference Instead, in near and of lineage the availability phase, eukaryotic the In second itiatives, phase. the the in third in genus the families will every in genome the for reference genomes of representative representative a each by where for approach The massive of phylogenomic generated (https://www.earthbiogenome.org/affiliated-project-networks). this time a joined taxa adopted be record have has a of initiatives databases project in variety sequencing genome biogenome million) genome wide earth incomplete 1.5 large-scale a of Several (about 2018). scenario targeting species al., eukaryotic the effort et known change (Lewin the to decade all in a set for initiative over is presently resources moonshot is international Project genomic an metabarcoding generating BioGenome Nevertheless, which by Earth 2017). to the rela- al., due have called et databases (Stat genome biology databases metagenomics whole barcode than of the DNA preferable completeness than the coverage more the Currently, species upon sequences. of high depend very proportion genome directly tively The whole will sequences. containing annotated approaches DNA taxonomically metagenomic databases environmental be capture, reference of can hybridisation library to that Due and input across 2012b). sequences the PCR biodiversity al., metagenomic of as monitor et representation (Taberlet such to approaches unbiased steps used targeted an enrichment of be provide limitations of targeted can and of benefits that biases absence the full sample overcome the sequencing the per and throughput life sequences reap of high DNA to tree extremely of fundamental the on billions metage- is sequencing yield a life that shotgun could envision environmental of platforms to performing tree first biodiversity the of the were of approach al. across nomic structure et biomass Taberlet underlying programs. of the biomonitoring abundance next-generation preserves eDNA-based relative which detection of der (van of terms targeted approach in are unbiased taxa and of untargeted range An wide bias are a primer when there and 2020). deter- abundances bias, Finally, Nijland, in relative marker diversity. & bias, and usage genomic Loos diversity amplification its original bias, their extraction the limits monitoring by DNA obscures genes as and that separated such non-barcoding communities biases species from technical of between known data potential various interactions life of ecosystem-level functional of of lack building the tree types targeted the for the mining other necessary Further, a across is and distances. organisms data animals, evolutionary trophic holistic the and a large all incorporate Such plants, of assay. that abundances single fungi, networks differ relative a ecological protists, in that the sample prokaryotes, determine barcodes environmental obtained to DNA as an principle, used standard from such in be on organisms never be, dependency can can of the approach that to groups information due next-generation major ecological instance, to in For approaches div 4 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. rsrigfitrhle smd po eictn lsi aeilwihcmltl eoe n rcsof 2019). traces al., any self- et removes (Thomas The completely temperature extraction. which enrichment room DNA material in DNA for We plastic weeks Extracellular dark sampling. several desiccating the the for of in during eDNA the up temperature preserves controls avoids made and filtration room replaced also water is negative at are system any holder laboratory which sampling of use filter the holders The not volume preserving to filter minute. during did and samples self-preserving per lysis we the rate single-use cell litre Thus, transported any sterile the location. one minimise utilising sampling than maximise to every by less to 10psi for contamination of of used sample rate pressure was of flow vacuum module risk maximum a a of maintain sampling 47mm set free-form and in triplicate We the water a filtration A location. of to used litres per 2018). bind 10 sampled we to al., about water shown Further, filtered et We been 2018). 28 (Thomas 2013). has Keeley, on al., such Inc. it & selected station DNA (Liang as et sampling The affinity extracellular (MCE), geolocated chemical (Nagler locations. ester by each its (50um-2mm) cellulose to sampling bound due mixed sand water potentially the DNA of of be and in extracellular up volume could observed (2-50um), DNA made more that turbidity membrane of for silt DNA particles filter high allow yield any (<2um), soil to the of sufficient clay suspended 0.22um to absence obtain retains of as due the to instead also to clogging 0.45um filtered size water owing before of pore be the DNA size filtered from to of pore be extracted amounts need a be to more water selected can relatively We of that step. require eDNA volumes amplification that total large approaches the 2015), PCR-free of al., fraction for a et only (Torti experiences up sample makes and study. 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Pilot-scale biogenome earth for the METHODS tool in powerful AND programs a MATERIALS biomonitoring experimental provides approach pilot-scale next-generation to unbiased a implement 2) in and to (Figure ecosystems untargeted ecologists workflow aquatic an molecular large such metagenomic in of novel life implementation our of this Large-scale tree of In setup. are the taxa. reproducibility across macrobial organisms and biodiversity on than monitor feasibility target taxa effectively rather the microbial the pseudo- analysis of demonstrate community when a effect we overshadowing incidence-based richness adapted paper, the used billions we taxa minimise we Fourth, to obtained the Fifth, statistics taxa. database. approximate and abundance-based macrobial reference to libraries low-abundant the assignment PCR-free the the in read underrepresented pushed the detect we of to of Third, approach of sample sequencing reads. taxonomic method per ultra-deep the PCR-free reads in performing completely paired-end duplicates by a of filtration and used sequencing water artefacts we of large-volume PCR-induced Second, using limits obliterate protocol. samples to extraction environmental preparation DNA the library customised in a DNA and extracellular techniques the targeted we First, th eebr21 sn h nertdeN ape ySmithroot by sampler eDNA integrated the using 2019 December 5 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. h hsht ue a rsl rprdbfr xrcinb iig017 fNaH of 0.197g mixing by extraction contamination. before aerosol any prepared avoid 70% to freshly and extraction clean water was Na the distilled a during buffer by a liquids in followed the phosphate membranes bleach, Within all commercial filter The pipette Germany). diluted the to 50% (Macherey-Nagel, filter-tips from with used kit extraction We wiped ethanol. 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All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. 4gnr,Apii ihfu eea hnrctyswt he eea n etlswt n observed one with Reptiles and genera, with Aves three genera, the with 30 among Chondrichthyes with representation genera, Mammalia highest four were the Phylum with groups had invertebrates. Amphibia represented genera of low genera, 61 60.39% the with 14 and Among Actinopteri sequenced chordates chordates. class the of and and in 39.61% invertebrates we Metazoa genera of detect, of 97 comprised groups to with targeted genera difficult Arthropoda Bacteria, commonly most Metazoan the of the 308 were among are The genera observed genera macro-organisms samples. genera 675 and eukaryotic abundant Specifically, of (18.85%), Further, Archaea, low number Viridiplantae 3.67%. the 4). the of (18.85%), Since just inspected Fungi (Figure genera 1A). 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Giga DNA 851.43 environmental of total a generated life We of tree the across samples. the Jaccard Biomonitoring the among estimates depth the estimate SpadeR sequencing 2015). measured to in shared Jost, differences we depth RESULTS & and the Finally, (Chao unique sequencing considering bootstraps taxa. of by of hundred number indices various with function the Sorenson package across R using and a diversity SpadeR samples as the spatially-replicated maximum extrapolation in completeness three detect taxa and (Hsieh the sample interpolation to bootstraps among the hundred The similarity required with community 2014). assessed package depth al., R then optimal et iNEXT We the (Chao the level 2016). using units species al., performed sampling the were (hill et the at curves sample of each accumulation higher in each genus prohibitively Genbank taxa of in and various the genera of 2019) richness in different al., genus level of asymptotic et of genus the (Leray genus 0 counts estimated the 1% the of then the We to number than at obtained 2020). analysis less sequences al., our we be et misidentified restricted unit, We (Locatelli to taxonomically level. sampling estimated genus of each is the proportion In to database up each. the least reads reads because at of million classified level billions abundance-based taxonomically 100 containing is are standard sample of that database metagenomic the units reads each reference of divided sampling taxa. 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Data may be preliminary. ovr o aooi ak eo aiylvlb h C loih,wihde o ffc u analysis our merging and affect independently not reads does paired-end which the algorithm, analysing of LCA choice the our contrary, by classified the been level have On may family homologs level. sensitivity distant below less genus very to the ranks evolutionarily due at reads only taxonomic unclassified miss low the to of very algorithms likely computationally most sensitive are to Thus, is study less species. 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All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. ilo ardedrasmyb pia o imntrn costete flf,wihcuddtc about coverage the one detect increased could about only billion which that two per life, to indicate reads billion of one results tree billion from the depth Our 3 the across costs. of Doubling biomonitoring 6). sequencing depth (Figure for diversity current sequencing optimal the of under maximum be 90% may a limit by reads caused to practical paired-end issues up the billion technical concentrations. values is the library predict mitigate which in to differences and sample, us the depths allowed to the curves sequencing due but accumulation including unequal reads samples further genus paired-end taxa, across be billion of examined 5.6 data cannot extrapolation of as sequencing that the total Statistical depth level) of a all generated optimal genus depths we which study, the the unequal this at (at define obtained In threshold effort. we million) sequencing coverage widely, minimal 100 sample vary with maximum of increased life a multiples of cross tree (in sequencing ones, the depth low-abundant minimal across with sequencing also organisms biodiversity we discrete maximum of Hence, the a detect abundance sequencing. to with the ultra-deep required projects Since perform depth biomonitoring to effort. sequencing funding decade, optimal considerable last the require the may determine over samples reduced of drastically (Supporting number have large animals costs biomonitoring farmed sequencing for the domestically optimal Although and be ecosystem. 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Data may be preliminary. ist h oretxnwt h viaiiyo elppltddtbssi h future. the in databases well-populated of availability the during the closer to redundancy evolutionarily with clustered the more taxon provide reducing been source will while other have approach the similarity pseudo-taxonomic might to were sequence The hits genomes construction. high there suspect database Delphinidae We to though of closer. due other process even phylogenetically sequences the the the more gene database, from from be dolphin the sequences may sequences river that of Chinese gene in available Delphinidae thousands annotated genome not family Interestingly, the the is dolphin samples. from that genome reference our river database whole in the the Chinese whose in present in the genomes Chilika, be available hit of to not dolphin species expected example is Irrawaddy an flagship but species provide database endangered 7) also target the an we (Figure the in illustrate, similarity dolphin, To community from Irrawaddy approach. high the pseudo-taxonomic locus very the of have the of samples available when reproducibility spatially-replicated nearest high hit the indicating the we from best approach, Hence, results the pseudo-taxonomic feasible. Our with the as not database. genome In chosen is databases. the approach is reference by taxonomy-free across species approaches on fraction taxonomy-free a loci dependent and a utilising taxonomy-based from partially have of scenario, advantages only being arise a with may approach sequences such sizes pseudo-taxonomic the In a genome adapted sampled. studies, large genome with (Callahan metagenomic organisms their samples of higher across of case Further, diversity resolutions. compare in taxonomic to of But, varying approach abundance 2017). relative taxonomy-free The al., a 2015). amplicon provides al., et or clustered ASVs et 2015) (Tikhonov be or Schloss, sequences can OTUs & denoised and (Westcott different the locus identity reads on sequence single based being on al., sequenced a (ASVs) (M¨achler variants based from et are of databases sequence (OTUs) arise approaches reference units number derived Taxonomy-free taxonomic the sequences large due originated. operational the on into studies, a Also, they dependency targeted environment, the which genetics. marker-based eliminate the from In population to sequence 2020). taxa and in studies reference source barcoding taxa metabarcoding the the in in novel employed match used assembled, uncatalogued directly routinely yet of not are not proportion may that high are loci a genomes few to a whose only organisms contain non-model databases most more for become Currently, might future. reproducible and shotgun the is 72 complications ultra-deep in approach fewer to higher-end, costs pseudo-taxonomic relatively the up sequencing The reads. with of on add million choice reduction case 720 can simpler further requiring extreme much the taxa) which an 6 a with is CytB) x attractive is markers example Protists (COI, eDNA 2 metabarcoding 23S), x Animals of life (16S, sets sequencing and Bacteria of primer 2 23S), tree rbcL), x (16S, the & (matK, replicates sets Archaea Although technical different Loos namely, Plants (3 two groups, der location ITS), pair, six van per primer (18S, libraries the 2017; per of Fungi of replicates al., tree each technical 28S), the et for three (18S, across (Stat marker least program at per metabarcoding biomonitoring need primers life unbiased may of of completely one markers a tree different metabarcoding, implement achieve with using to life libraries to example, and taxa For primer-bias, of 2020). reduce increases stochasticity,Nijland, groups to also PCR-induced different approaches taxon alleviate targeted a target to of targeting to required cost primers replicates the different However, technical with metabarcoding metagenomics. of libraries library, than number per choice the requirement achieve better low-depth considering to relatively a significantly library the In be of per to sequencing. to Gb reads Due of seem million 2019). 300 may Gb 10 al., requires only et 150 coverage require (Singer requires 100x may sensitivity typical biomonitoring at metabarcoding good now for as genome 100 such reads also sized approaches requires paired-end are mammalian targeted coverage 150bp contrast, depths 30x a billion sequencing at assembling one high novo genome Such whereas extremely human de sample. sequencing, at a and per re-sequencing length sequencing, incurred instance, in of For cost 150bp Gb biology. the to in reducing applications up various run reads Illumina in single paired-end the a deliver as such can in to sequencers small platform depths for next-generation Novaseq feasible utilise The be they advantage may 6000. them when sample take Novaseq differentiating programs per can for reads biomonitoring One samples paired-end sized low. re 11 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. hf oad mlmniglresaenx-eeainbooioigporm costete flf nthe in life of ACKNOWLEDGEMENTS paradigm tree a the advances for across study necessary programs era. this is biomonitoring biogenome that that next-generation earth and metagenomics believe large-scale test eDNA-based implementing We of further towards conditions. capabilities shift to different the opportunity costs under regarding excellent sequencing understanding workflow an taxa, Plummeting our metagenomic provide spatio-temporal effort. specific novel projects sampling high our to sequencing the the optimise enables genome traits reducing 1) large-scale Third, significantly (Figure functional increasing DNA by services. of extracellular and ecosystems employing and large mapping through functioning approach whole of level, our the monitoring ecosystem by gene from provided to biodiversity data the of changes generated tracking resolution at by the community diversity kingdoms of linking across nature monitoring interactions multi-faceted and species for the inferring Second, allows enables biodiversity that abundances. detecting genome has assay relative effectively single approach and the a simultaneously our in in the of limitations, changes life in possibility of the programs the tree biomonitoring First, Despite the databases next-generation features. 2020). across key large-scale barcode into three al., resolving to curated incorporated et due as and using (Singer future adapted such approaches be metagenomics applications to targeted than For potential level, suitable the databases. pseudo-taxonomic species more sequence using the reference be ecosystem at may uncurated adopted the structure using in widely community level our changes be Finally, genus fine-scale broad-scale affordable. not the more monitoring may become at to approach biomonitoring costs labels limited metagenomic Next, large-scale sequencing deep currently very a 2019). the is for Hence, al., until approach prohibitive sequencing. managers et ecosystem economically of (Seeber and be costs researchers animals by may current by strategies sample the visited sampling at per routinely innovative programs reads need waterholes may billion from cases one samples sub- Such obtaining and water plants, animals. collecting microbes, terrestrial detect as large to pooled such useful not soil, be the but only from may organisms, isolated ecosystems, applicability obtaining DNA terranean terrestrial Further, extracellular where in ecosystem). the plots ecosystems Tundra since sampling different tested in multiple (e.g., rigorously for from samples difficult be necessary of should be is ecosystems number may testing terrestrial limited DNA to more a extracellular ecosystem, of with model warrant quantities objectives a next- microgram that our in for achieved limitations way study we unbiased some pilot-scale Although an has a in optimisation. also data and approach required in testing metagenomic the further advancements deliver our is can Nevertheless, Hence, bioinformatics that and biomonitoring. technologies 2017). sequencing, generation level futuristic preparation, every al., develop library at to extraction, adaptations et DNA attempt with collection, 2) an (Bohan sample (Figure workflow from life metagenomic pipeline a novel the of Our at of genome 2020). biomonitoring al., tree entire next-generation et deploying the (Makiola the for from scale requirement global data across indispensable requires an species which a are ecosystems technologies monitoring various entire metagenomic of from to approach genes inherent individuals holistic from the more to entities of due ecological a standardised life different of employs have of range that biomonitoring tree wide organisms entire next-generation of the Moreover, groups of not major loci. but limitations across interest barcoding may abundances the of relative approaches taxon revealed the targeted provide particular have Such to a its 2017). inability decade monitoring of al., for past et understanding suitable the (Elbrecht be thorough technique only in a metabarcoding studies requires PCR-based Numerous widely-used problems the weaknesses. practical and solve strengths to technical technologies of application Successful 1) (Figure conclusion DNA environmental and biomonitoring of Limitations large-scale type designing consideration. targeted ecosystems. before under the large ecosystem of studies spatially large resolutions the pilot-scale represent monitoring spatio-temporal in of for to the importance evaluate suitable required to the be samples programs may emphasises extra- of DNA also of number sampled extracellular distribution study the the that homogenous Our in reducing implies the km and effectively to column 10 the by due water than be ecosystems that the could higher indicates in biodiversity much of DNA is also resolut 12 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. eals . hlc,P . ae,P .(00.Vrertso h rn sidctr fbiological of indicators as brink the on Vertebrates (2020). H. America extinction. P. of mass Raven, States sixth & the R., and P. annihilation Ehrlich, G., extinction Ceballos, mass America sixth declines. ongoing of the and States via United losses annihilation the Biological population (2017). vertebrate R. Accele- by Dirzo, (2015). & signaled R., M. P. extinction. Ehrlich, T. G., Palmer, mass Ceballos, & sixth M., the R. Entering DNA Pringle, losses: Garc´ıa, Relic A., https://doi.org/10.1126/sciadv.1400253 species D., (2016). human-induced A. diversity. N. Barnosky, modern Fierer, microbial R., rated & P. soil S., Ehrlich, of G., M. 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(8), ihadSels iest n t Sustainable Its and Diversity Shellfish and Fish oeua Ecology Molecular niomna DNA Environmental Vl 8,p.41) leirLtd. Elsevier 4–18). pp. 183, (Vol. , 21 , , 9 2 aueCommu- Nature 8,2045–2050. (8), 6,1379–1385. (6), 3,261–270. (3), Molecular Molecular Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. rmwoeognss iht o oeua egtetaognsa N rmdsoitdprso the of parts dissociated from DNA extra-organismal weight DNA molecular organismal weight low molecular to High high types: main organisms, three whole to attributed from be can samples water environmental 1: Figure the approved and draft the data, to the edits generated provided samples, FIGURES G.U. the AND TABLES collected manuscript. S.M. link: the study. drafted the reviewer immedi- designed and manuscript. and analysis, following idea the released the peer-review. un- performed conceived after the provided G.U publicly SRA be and will using S.M. NCBI link be DOI verified R permanent to and https://github.com/manu-script/exDNA-pilot-study. a will CONTRIBUTIONS scripts and be review: AUTHOR submitted archived, Python for be data pipeline, available will may Snakemake been are repository the analysis GitHub The data), submission has The the (Supporting for file study used The count scripts lineage this taxonomic filtered PRJNA691704. fi- in nal The acceptance. accession generated https://dataview.ncbi.nlm.nih.gov/object/PRJNA691704?reviewer=3ocgpcesbu8qu5gl19m8749stc. upon data BioProject sequencing ately the raw der the All Virosphere RNA the Expanding STATEMENT (2019). ACCESSIBILITY DATA C. E. Holmes, & 2. C., Kraken X. virology-092818-015851 with Qin, W., analysis Metagenomics. Wang, Unbiased metagenomic M., Y. by Improved Chen, Z., (2019). Y. B. Zhang, Langmead, & meth- J., units. reference-based Lu, taxonomic Biology outperform E., operational methods D. to clustering Wood, novo sequences De gene J., rRNA S. (2015). 16S D. Newman, https://doi.org/10.7717/peerj.1487 assigning P. D., for Schloss, J. & ods Australia. DiBattista, survey L., north-western metabarcoding T., S. eDNA tropical Westcott, Z. Large-scale over Richards, (2021). transitions M. S., and Bunce, E. break & Distributions Harvey, biogeographic M., Heydenrych, M., marine extra- and L., reveals Stat, communities C. of marine Skepper, J., of A., implications M. metabarcoding Harry, DNA Travers, and bulk: K., in dynamics, West, Biases Origin, (2020). R. involved. Nijland, & methodology (2015). In M., the L. B. Loos, der B. sediments. van Jorgensen, marine & in A., https://doi.org/10.1016/j.margen.2015.08.007 pools M. DNA Lever, cellular A., Torti, , 20 h ope clg fevrnetlDA(DA natpclautceoytm N in DNA ecosystem. aquatic typical a in (eDNA) DNA environmental of ecology complex The 1,27 https://doi.org/10.1186/s13059-019-1891-0 257. (1), d.32.https://doi.org/10.1111/ddi.13228 ddi.13228. , oeua Ecology Molecular nulRve fVirology of Review Annual https://doi.org/10.1111/mec.15592 . aieGenomics Marine 18 , 6 1,1919 https://doi.org/10.1146/annurev- 119–139. (1), Vl 4 p 8–9) Elsevier. 185–196). pp. 24, (Vol. PeerJ , 2015 iest and Diversity 1) e1487. (12), Genome Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. 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Data may be preliminary. ersn ttsial xrpltdvle,adterbo rudtelnsrpeet h 5 confidence 95% the represents lines the around ribbon the and intervals. values, extrapolated statistically represent 5: Figure eu cuuaincre safnto fsqecn et cosvrostx.Tedte lines dotted The taxa. various across depth sequencing of function a as curves accumulation Genus 21 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. ne ih9%cndneitrasars aiu taxa. various across intervals confidence 95% with index 7: Figure intervals. and confidence regression, 95% polynomial local the from indicates derived lines samples the the around among values ribbon coverage the of trend the represent lines 6: Figure apecvrg ttegnslvla ucino eunigdphars aiu aa The taxa. various across depth sequencing of function a as level genus the at coverage Sample omnt iiaiyaogtesmlsmaue ihteSrno ne n h Jaccard the and index Sorenson the with measured samples the among similarity Community 22 Posted on Authorea 22 Feb 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161401815.51766652/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. vs1 33 (SD 13.30 reads. (SD paired-end 91.75 billion similarity index. Community one Jaccard (E) of the index. depth with Sorenson sequencing measured the sample a with samples Average 1.97) measured for the (C) samples (SD among deviation the 30.6 deviation. standard among standard similarity with Community with level (D) sample genus per the richness at genus coverage (SD asymptotic 61.21 14 estimated Average (B) 1: Table (SD 93.72 (SD 292.34 30 Aves (SD 191.37 61 (SD 189.73 Mammalia 97 (SD 313.19 308 Actinopteri Arthropoda (SD 194 985.81 (SD 194 673.46 Metazoa (SD 64.28 333 Viridiplantae (SD 45.97 Fungi 1029 675 Protists 64 Eukaryota 47 Bacteria Archaea Viruses Taxon ttsia umr cosvrostaxa. various across summary Statistical samples across genera Observed (A) 0.59) 0.63) 5.19) 5.32) 2.09) 5.49) 26.66) 35.83) 2.72) 0.55) 1.03) sample per richness genus asymptotic Estimated (B) 23 ( )Ttlnme fosre eeaars samples. across genera observed of number Total A) 7.23) (SD 95.16 6.50) (SD 94.75 4.36) (SD 95.95 3.52) (SD 95.87 5.87) (SD 95.36 1.90) (SD 97.77 3.00) (SD 93.04 3.34) (SD 95.31 0.30) (SD 99.22 2.15) (SD 97.72 1.91) (SD 98.49 reads billion one at coverage Sample (C) 13.71) .80.93 1.00 0.98 0.95 0.93 1.00 0.97 0.98 0.98 0.97 0.91 0.99 0.94 0.99 1.00 0.97 1.00 0.98 0.97 1.00 1.00 0.99 index Sorenson (D) .01.00 1.00 index Jaccard (E)