Performance of amplicon and shotgun sequencing for accurate biomass
ANGOR UNIVERSITY estimation in invertebrate community samples Bista, Iliana; Carvalho, Gary; Tang, Min; Walsh, Kerry; Zhou, Xin; Hajibabaei, Mehrdad; Shokralla, Shadi; Seymour, Mathew; Bradley, David ; Liu, Shanlin; Christmas, Martin; Creer, Simon Molecular Ecology Resources
DOI: 10.1111/1755-0998.12888
PRIFYSGOL BANGOR / B
Published: 01/09/2018
Peer reviewed version
Cyswllt i'r cyhoeddiad / Link to publication
Dyfyniad o'r fersiwn a gyhoeddwyd / Citation for published version (APA): Bista, I., Carvalho, G., Tang, M., Walsh, K., Zhou, X., Hajibabaei, M., Shokralla, S., Seymour, M., Bradley, D., Liu, S., Christmas, M., & Creer, S. (2018). Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples. Molecular Ecology Resources, 18(5), 1020-1034. https://doi.org/10.1111/1755-0998.12888
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04. Oct. 2021 This article isThis article by protected copyright. All rightsreserved. 10.1111/1755doi: differences to lead between the of thisversion citethisart and Version Record.Please copyediting, paginationbeen throughthe andproofreadingtypesetting, process,may which This article 8 7: 6 Guelph, Ontario, N1G Canada 2W1 5 4: ofChina Republic 3 Laboratory 2 1 Simon Creer Shadi Shokralla Iliana Bista Authors in invertebrate estimation P Article :Resource Article type : (Orcid ID 0000 BISTA ILIANA MISS : : : : : : erformance of amplicon of erformance
BGI De Bangor University, SchoolBangor University, of Wellcome Trust Sanger AcceptedNa Mersey, Stockport, APEM LTD,Heaton BiologyDepartment of Integrative & Biodiversity Instituteof Ontario,University of Agency, DeaneryEnvironment Horizon House, Road, BristolBS15AH, UK Article partment of Entomology, tural History Museum oftural HistoryMuseum Denmark, - Shenzhen, Shenzhen,Shenzhen, 518083, China
1 , LL57 2UW
, 2 , has been acceptedhas been forpublication andundergone fullpeer review buthasnot 2
* , Gary R. Carvalho , GaryR. 5 , Mathew Seymour
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Institute, Cambridgeshire, Hinxton, CB10 1SA, UK
and China AgriculturalChina University,100193, Beijing People’s Biological Sciences, Molecular Sciences, Biological 2 community samples community - , 0002
Min Tang Min 2
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4 icle as , 5 , This article isThis article by protected copyright. All rightsreserved. between correlations significant highly provided results sequencing Shotgun bias. primer was metabarcoding species, consistent abundance low very recover to failed occasionally (mitogenome sequencing Additionally, (3 metabarcoding COI macroinvertebrates of set ( genome different to metabarcoding of ability the bias, primer to Due efficiency. and discovery Abstract Simon Creer, * C Running title: biodiversity Keywords: Iliana Bista, o
Accepted Articlerrespon New applications of DNA and DNA of applications New taxa from taxa mito
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y aln t rcvr oe pce wt highe with species some recover to failing by eaacdn, eaeois biomass, metagenomics, metabarcoding, [email protected] [email protected] - e sd individual used we genome skimming) Shotgun vs. ecological monitoring, yet questions remain regarding precision and and precision regarding remain questions yet monitoring, ecological
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c ok omnte cmrsn 1 seis f freshwater of species 13 comprising communities mock ommunities amplicon invertebrate amplicon communities different respectively.
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unclear, and more reliable alternative. Here we used a a used we Here alternative. reliable more
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biodiversity biomass mapping genome genome less less
of of of s , This article isThis article by protected copyright. All rightsreserved. Acceptedrequire WFD the as such Initiatives directives ecosystem wider variation temporal and spatial both the biomonitoring, specimens immature Moreover, approaches and loss biodiversity rapid of face the in especially relationships, function ecosystem andbiodiversity understand to order ArticleIntroduction diversity metabarcoding studies, ecological communities macroinvertebrate bulk from Overall, read the improved approach) amplicon three all of results the Combining species. 658bp) FFFR, (amplicon relationships from obtained read the Conversely, species. one but all in biomass and number read
The accurate qualitative and quantitative assessment of biodiversity is essential in in essential is biodiversity of assessment quantitative and qualitative accurate The scale scale mito
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eaacdn varied metabarcoding Caso, 1990) (Cranston, 8
robust species identification species u o 1 (mlcn B1FR (amplicons 13 of out
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ae Faeok ietv (WFD) Directive Framework Water yielded more informative more yielded currently currently . ecological status classification classification status ecological s o xeie imntrn faeok, i frameworks, biomonitoring expedite To
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ako, Dpe, 2011) Dapkey, & Jackson,
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This article isThis article by protected copyright. All rightsreserved. Accepted2012) al., et Yu 2012; Konynenburg, taxonomic it steps, PCR and RbcL 2003) Waard, de & mitochondrial samples community as to genes marker more or one of sequencing amplicon 2014; al.,2018) et Seymour Altermatt, & Steinmann, Deiner, Mächler, 2008; Taberlet, & Pompanon, Miaud, Ficetola, (eDNA) DNA environmental aqueous from biodiversity of detection (Mala Articlesampling invertebrate litter leaf or soil from used, been have taxa al., et Pfrender 2011; Baird, & ecosystem studies recovered increasi by biomonitoring &Ohandja, Hoare, Voulvoulis, 2012) underpinned T Most
e det f ih hogpt eunig ehoois HS i revolutionising is (HTS) technologies sequencing throughput high of advent he eaacdn ad s omny ple fr h aayi of analysis the for applied commonly is and metabarcoding include various invertebrate taxa, various invertebrate include ITS2 studies using HTS for HTS using studies s (Baird & Hajibabaei, 2012) Hajibabaei, & (Baird represent
(e.g. by
for plants for Cytochrome s considered is
the taxonomic identification of organisms from routine monitoring routine from organisms of identification taxonomic the Gibson et al., 2014; al., et Gibson
and and
(Creer et al., 2016; Yu et al., 2012) al., et Yu 2016;al., et (Creer to of ation ribosomal RNA regions RNA ribosomal
(Fahner, Shokralla, Baird, & Hajibabaei, 2016) Hajibabaei, & Baird, Shokralla, (Fahner, g h truhu ad aooi ifrain ht a be can that information taxonomic and throughput the ng C .
ise traps) ise
Oxidase Subunit I (COI) (COI) I Subunit Oxidase
diversity diversity that 2010; Shokralla et al., 2015) al., et Shokralla 2010; bio diversity assessment of assessment diversity metabarcoding . . In fact, it has been has it fact, In . Gibson et al., 2015; Hajibabaei, Shokralla, Zhou, Singer, Singer, Zhou, Shokralla, Hajibabaei, 2015; al., et Gibson . The most commonly used taxonomic groups for for groups taxonomic used commonly most The .
(Ji et al., 2013) al., et (Ji in such as benthic macroinvertebrates for freshwater macroinvertebratesfor asbenthic such uk samples bulk such as such Yn e a. 2014) al., et (Yang
. rdcs bias produces barcod Amplicon sequencing Amplicon . More recent work recent More . .
16S C
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ommonly used markers include the include markers used ommonly reported . Similarly, terrestrial invertebrate terrestrial Similarly, .
e bulk (Epp et al., 2012) al., et (Epp
region
samples to date utilise date to samples
that PCR bias might alter alter might bias PCR that o fo aoe ground above from or , n eain to relation in
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Due t Due bulk/environmental (Bista et al., 2017; 2017; al., et (Bista encompasses
is
o intermediate o f often or animals or asingham,
accurate
referr (Collins, (Collins, such such PCR , or , the the ed
This article isThis article by protected copyright. All rightsreserved. Acceptedsamples. bulk in relationship reads to biomass bias 2013) approach simultaneously species multiple of reconstruction phylogenetic assessment ecological for samples bulk of characterisation (Crampton sequencing Illumina throughput to promoteaccessibility and eventualuptakeof technologies. such data independent of comparability improve to only not possible, Article2014) bioma and recovery richness estimations species improve to suggested been has region same the from amplicons multiple of combination and pairs, primer multiple of 2014) use pipelines, al., et Kelly 2014; al., et Hiiesalu 2017; Leese, reported been also have biomass and number 2015) Leese, & Elbrecht 2014; mis introduce species the
Seiial, t s ugse ta mtgnmc eunig results sequencing mitogenomic that suggested is it Specifically, . species The more recently introduced m introduced recently more The , .
advocat
Such Such (Piñol, Mir, Gomez Mir, (Piñol,
has been suggested been has - lt, u Zo, Vge, 2016) Vogler, & Zhou, Yu, Platt,
biomass ratio ratio biomass ( Gibson et al., 2014; Hajibabaei et al., 2012; Zhan, Bailey, Heath, & Macisaac, & Heath, Bailey, Zhan, 2012; al., et Hajibabaei 2014; al., et Gibson mrvmns to improvements - ing ersnain f atclr groups particular of representation The efficiency of this approach could be related to the assembly method method assembly the to related be could approach this of efficiency The
that the absence of absence the that - or Polo, & Agustí, 2015) Agustí, & Polo,
s produce inaccurate representation of of representation inaccurate produce
and as an alternative to PCR to alternative an as . methodological aspects aspects methodological On On
f hl mtcodil genome mitochondrial whole of possibly h ohr hand other the itochondrial metagenomics (mitogenomics) use (mitogenomics) metagenomics itochondrial initial more reliable representation reliable more
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template mismatches template
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This article isThis article by protected copyright. All rightsreserved. future compr a provide to aim method performance. their evaluate to considered, e shotgun and MiSeq, Illumina were extracts DNA community (e.g. work previous densities natural of P depending from biomass, of gradients comprise species. target per individuals taxo various including freshwater their for measured individually 13 comprising samples. extracted bulk in species macroinvertebrate investigate mappingCrampton for available are sequences reference whether and used, prmna workflow xperimental Acceptedotamopyrgus Article Here, utility was - Platt, Timmermans, Baselga, &Vogler,2015) we provid we
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biomonitoring sample collected for environmental assessment purposes, purposes, assessment environmental for collected sample biomonitoring for ecological applications in biodiversity and f and biodiversity applicationsin ecological for assessed while providing suggestions for future improvements. Ultimately, we Ultimately, improvements. future for suggestions providing while assessed
antipodarum co mmon macroinvertebrate species, species, macroinvertebrate mmon . DNA . e Crampton
nomic orders, while accounting for availability of large numbers of of numbers large of availability for accounting while orders, nomic a direct comparison between metabarcoding and mitogenomics and metabarcoding between comparison direct a ). ehensive evaluation of the two methods and troubleshoot their their troubleshoot and methods two the of evaluation ehensive
was (e.g each method to depict the richness and biomass presence of of presence biomass and richness the depict to method each Possible limitations and advantages of each method were were method each of advantages and limitations Possible , and 1 to 17 specimens for specimens 17 to 1 and , . eune on sequenced extracted from extracted
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amplicon sequenced for three fragments three for sequenced amplicon step increase of specimens per community from 1 to 33 for for 33 to 1 from community per specimens of increase step lt e al., et Platt diinly te elct communities replicate the Additionally, biomass. as low low
The samples were samples The
as a as ( Furthermore, the overall applicability of each each of applicability overall the Furthermore, 2015 Illumina pooled single specimen specimen single ) Gómez ;
Ten whole bodies whole Hi . R
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This article isThis article by protected copyright. All rightsreserved. preservatio during al.,1999)(Benke et mass dry of loss to due inaccurate be might specimens preserved speed and precision increased to due specimens, of weighing or biovolume of determination as such 2016)Dolman, produc could possible, wherever type ecosystem and region geographic account measurements the for accounting USA Rockville, species E marinus, m S ( Coleoptera and Ephemeroptera Amphipoda, Isopoda, Hemiptera, from: each of one extraction environment cool Ltd APEM ( Specimen and Materials September September 1, Figure Acceptedethodologies Article pcmn fr hs ok w work this for Specimens oy esrmns ee efre bsd n ulse work published on based performed were measurements Body
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October 2014 October which were selectedwhich were to biomonitoring represent atypical sample . ) : P )
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This article isThis article by protected copyright. All rightsreserved. extract community each extracted separately was which asses to community, communities controls positive ( individuals, only below) see species, communitiesDesign ofmock 2007) Corporation, (CodonCode v.3.7.1 Aligner Massachusetts) CodonCode using edited were sequences barcoding Ephemeroptera regarding successful not was sequencing barcode which for (Ephemeroptera), types protocol extraction with performed primers metazoan universal LibrarDNA barcode Reference AcceptedTable Article I Ten 6 ( 6 ndividual specimens were extracted and sequenced for the COI the for sequenced and extracted were specimens ndividual . .
High 1 N. glauca N. , omnte wr cetd otiig ihr 3 r 14 or 13 either containing created were communities Table
each ult broe wr otie fo al pce ( species all from obtained were barcodes quality . is, he seies of specimens three First,
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DN were used were t gain o boas pres biomass of gradient a at ) Te t The . , except , e ( s s Bod Tsu kit Tissue & Blood asy gastropods
extraction efficiency. Second, DNA Second, efficiency. extraction ( P. fontinalis P. tl u of sum otal at 1% concentration concentration 1% at
for (Folmer, Black, Hoeh, Lutz, & Vrijenhoek, 1994) Vrijenhoek, & Lutz, Hoeh, Black, (Folmer, to
y two species, where low numbers allowed representation in in representation allowed numbers low where species, two
assess the quality of sequencing performance across mock across performance sequencing of quality the assess , u t best to due ), (previously assembled by assembled (previously lsaW n MEGA in ClustalW )
of the communities. the of
specimens see D
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rm snl t mlil specimens multiple to single a from v5 melanogaster (
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arthropods Specimens ranged from ranged Specimens Shenz
of the of (Tamura, Dudley, Nei, & Kumar, Kumar, & Nei, Dudley, (Tamura, Tang communities communities . h
Table n China) en, bu et al. et 2017) species (including control control (including species t , and ), terfly
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This article isThis article by protected copyright. All rightsreserved. samples. between species of proportions biomass the skewing avoid to order in method enrichment yield 5min. for 2500g at centrifuged 4ml) volume (total (Sigma speed medium at shaker a in 65°C (MO then 37 bulk in sequencing. 2 of amount minimum A electrophoresis. gel agarose (Roche) Qiagen qu and mitogenomes DNA extractionforreference toselected due existing reference mitogenomeinformation. in variability o Accepted Articlefrom extracted was DNA genomic ality fr hours. 2 for C -
For the construction of individual shotgun reference genomes for each species, high high species, each for genomes reference shotgun individual of construction the For For the mock communities, DNA was extracted from extracted was DNA communities, mock the For
BIO) and vortexed at high speed for 5min. for speed high at vortexed and BIO) transferred into 50ml Power Bead tubes from the Power Max Soil DNA Isolation Kit Kit Isolation DNA Soil Max Power the from tubes Bead Power 50ml into transferred ( iue S2 Figure . -
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For the purposes of this work, we did not use any mtDNA mtDNA any use not did we work, this of purposes the For The elution The and was , with the addition of addition the with , ult ws sesd ih dsQubit with assessed was quality removed htu sequencing. shotgun leg or muscle tissue muscle or leg step was repeated a second time to time second a repeated was step manufacturer’s Lysis was per was Lysis
and mock
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in two
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control Fr f For .
used for shotgun shotgun for used DNA
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This article isThis article by protected copyright. All rightsreserved. Acceptedbleaching included Protocols DNA. community of l appropriate Appendix in available are protocols PCR Detailed protocol Illumina indexes Illumina with two round from amplicons target COI 2016) Port, & Lowell, community each of efficiency step, indexing extracts. community Articlebarcodes barcode aligned with comparison communities from (450bp) primer 1994) al., et (Folmer barcod Metabarcoding primer, Metabarcoding was performed performed was Metabarcoding
esir t al. et Meusnier
specific primers with added Illumina tails Illumina added with primers specific
e (130bp)
( region
ie uig ie V raet (0 cce) olwn the following cycles) (500 reagents V2 MiSeq using MiSeq I , (PE) -
n pies I primers and B1 B1 and performed PCRsetupswere inadedicated clean cabinet.
Round 2: Round ( ] aboratory at , primer primer
to minimise the effects of variant index sequences on the amplification amplification the on sequences index variant of effects the minimise to ; using the following the using Figure Figure -
and Primer selection selection Primer h Boiest Isiue f Ontario, of Institute Biodiversity the
. wa
(658bp);
3 Libraries were prepared using a a using prepared were Libraries purified purified R ( . precautions were taken to establish clean conditions clean establish to taken were precautions 2 2008) ) ound s
- 1 n I and B1 mlcn 1R using B1FR amplicon and modified from from modified
1:
both degenerate, modified for use with macroinvertebrate macroinvertebrate with use for modified degenerate, both
PCR 2. T Bry Mhod, anr & o, 01 O’donn 2011; Loy, & Wagner, Mahfoudh, (Berry,
able able amplification was performed using only the target specific specific target the only using performed was amplification ) and amplicon
amplicon FF130R using using FF130R amplicon -
primer pairs primer 130R product sequences hog s through 3 ) . )
Hajibabaei Hajibabaei ,
These primers were selected based on visual visual on based selected were primers These
and amplification performance tests on mock mock on tests performance amplification and steril from round 1 was 1 round from
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This article isThis article by protected copyright. All rightsreserved. (Canada). Guelph BIO at run was sequencing MiSeq and (UK), Bangor at performed was analysis data Neighbo MEGA6 in insertions systems. Wales (HPC) including NCBI downloaded BLAST+ ( community a as used sequences) abundant most the through selected are case USEARCH in table OTU an of generation and clustering with removed 2x250 Illumina of limitations current the to due forwar the between overlap sufficient allow not did (658bp) amplicon >25) score (phred ( whole (FFFR, 1 amplicon 450bp) de to Amplicon data analysis 2017) 230bp at truncation - Accepted ArticleBista elcto ad egn o sequences. of merging and replication Quality control and analysis of the Illumina MiSeq sequences was performed according performed was sequences MiSeq Illumina the of analysis and control Quality , ,
using Quantitative Insights In Microbial Ecology (QIIME) Ecology Microbial In Insights Quantitative using et al. et u the forward and reverse reads were merged with a 25bp minimum overlap. For For overlap. minimum 25bp a with merged were reads reverse and forward the (
n approximate n megablast
r USEARCH, QIIME and BLAST and QIIME USEARCH, - J oining samples.
(
2017) the . Th .
de novo de (NJ) method method (NJ) COI ) , using a a using ,
e truncation e Cmco t l, 2009) al., et (Camacho Similarly, taxonomic assignment was performed as in in as performed was assignment taxonomic Similarly, )
Tmr e a. 2007) al., et (Tamura bsd on based ,
h ietfe OU wr frhr hce for checked further were OTUs identified The acds ad u cso gnrtd O barcodes COI generated custom our and barcodes, average
option in USEARCH in option barcode USEARCH v7 USEARCH (Sait
value for characterisation of the diverse taxa present in the in present taxa diverse the of characterisation for value
strategy was selected because the length of the original the of length the because selected was strategy ou & Nei, 1987) Nei, & ou atC ( FastQC ein 658bp) region were (Edgar, 2010) (Edgar,
For amplicons 2 (FF130R, 130bp) and 3 (B1FR, (B1FR, 3 and 130bp) (FF130R, 2 amplicons For
performed using High Performance Computing Performance High using performed , www.bioinformatics.babraham.ac.uk , and a 97% similarity level was used for OTU OTU for used was level similarity 97% a and ,
n through and ih ≥ with .
bp Metabarcoding library preparation and and preparation library Metabarcoding ny h frad re forward the only
8 smlrt cut similarity 98%
custom pipeline fo pipeline custom (the dominant (the
MiSeq chemistry. Chimeras were were Chimeras chemistry. MiSeq . Th .
phylogenetic phylogenetic e OTU e
(Caporaso et al., 2010) al., et (Caporaso
level of similarity was was similarity of level
OTU centroids in this in centroids OTU d and reverse reads reads reverse and d r filtering, sorting, sorting, filtering, r stop codons and and codons stop - off nlss sn a using analysis d wr used were ads . , All against Bista Bista ) analys
results t al. et , and , the e s
This article isThis article by protected copyright. All rightsreserved. follo Accepted 0.6.2 BWA using on based scaffolds protein inside generated w frame translation and and gene mitogenomes reference by mitogenome for used were construction which sequences, mitogenome candidate 2012) Chin, scaffolds Articlel with reads removing described previously Shenzhen skimming mitogenome HiSeq2000 species instruction manufacturer’s following constructed F mitogenomes. reference Construction mitogenomes ofreference ag t al. et Tang Onco wing Siphlonurus immanis Siphlonurus eoi DA xrce fo individual from extracted DNA Genomic s
from 4 arthropod 4 from
libraries were pooled and and pooled were libraries using SOAPdenovo melania hupensis melania , China , Tang Tang .
. Assembled sequences were annotated following annotated were sequences Assembled . . irr construction Library
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a et al. nd each of them were aligned with corresponding reference protein reference corresponding with aligned were them of each nd .
( L & ubn 2009) Durbin, & (Li 2014) Fo PE
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2014, 2015) ow quality or adaptor contamination. Clean data Clean contamination. adaptor or quality ow reads. In addition, the original read original the addition, In reads. reference mitogenomes r mitogenomes reference in
. and analysis of analysis and
hce i MEGA6 in checked
species ) and 3 and ) hu t al. et Zhou Thirteen - ) using CLUSTALW 2.1 CLUSTALW using ) oig gene coding
- manual correction and checking were were checking and correction manual each or Trans ( Trans
( mollusc species mollusc .
Macrogyrus oblongus, Gammarus duebeni, Ligia oceanica Ligia duebeni, Gammarus oblongus, Macrogyrus
n asml o rfrne mito reference of assembly and - protein K 71)K 100
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This article isThis article by protected copyright. All rightsreserved. case this in although groups, the of separation vertical observe only again could we reads shotgun W (Figure data shotgun and amplicon of plotting Simultaneous amplicons. different the by obtained results 10 and (Figure 9 communities of exception the with axis vertical the along communities same Community analysis comparison to theothertwoamplicons in not but data, amplicon (Folmer) FFFR only using to comparison in improvement an was reads significant Nevertheless, 4) Figure thr all from obtained ( the using generated amplicon FFFR the for only but relationship, of exception the with relationships, for relationships across varied results reads data,FiguresS9amplicon of sum and (Shotgun community per trends overall visualise to biomass specimen against Figure Figure
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a large proportion of the species the of proportion large a uk netbae samples invertebrate bulk
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data did not provide accurate quantitative information on the the on information quantitative accurate provide not did data
biomass from biomass based etc.). etc.). .
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This article isThis article by protected copyright. All rightsreserved. Acceptedboth methods for r Sequence run. same therefor should included) molecules of taxa. size to of (according sequencing range during contents a library acrossNormalising used are pairs primer different when efficiency amplification binding reads shorter to attributed be could sequencing amplicons two amplicon shorter Article2016) to compared sufficient mapping, for baits as sequences (mito reads sequencing of proportion 8.5 size genome genome nuclear related tolarge Leese & Weigand, Zizka, duebeni length for coverage 6.4X at The majority majority The varied coverage sequencing work, metabarcoding the For . ,
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This article isThis article by protected copyright. All rightsreserved. Accepted Zhang,Hartl, (Bensasson, & Hewitt,2001 of removal and detection easier allows diversity. of recovery the outperforms genomes & Vogler,2017) beetles data genome reference a depth sequencing reduced of use allowed which genomes, mitochondrial Perspective & Bernatchez,2016;etal., Tang 2015; etal., Zhou 2013) Articlemitogenomic relationship biomass to reads of representation the for s and number read amplicon increased amplicon models linear to compared number logistic r be to likely are results the that species same The (Figure data metabarcoding . We
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maintain designed based on 379 mitochondrial genomes mitochondrial 379 on based designed 2 o te eunig data sequencing the of 42% .
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and be be in . . This article isThis article by protected copyright. All rightsreserved. the support partially results Our content. known of samples in detection species of levels Acceptedused were region amplicons samples community taxa of number large available already sequences repositoriesreference large of to the due markers to other 2012) metabarcoding through biodiversity 2014) al., detection specific group universal for designed sites priming has marker COI Article resembling more data shotgun the but amplicons), (individual assessed comparable, still reads amplico individual based composition community in similarities revealed from themetabarcoding data relationships reads/biomass the improved Multi Selection of the of Selection - , though the COI still retains its superior value superior its retains still COI the though , biomass . - In . against Additionally dimensional scaling analysis (nMDS, Bray (nMDS, analysis scaling dimensional
Gibson Dal e a. 2014) al., et (Deagle relationships for individual species, the community profiles obtained were were obtained profiles community the species, individual for relationships on occasion been occasion on
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This article isThis article by protected copyright. All rightsreserved. Accepted C.,Camacho, Coulouris,G.,Avagyan, V.,Papadopoulos, J.,Bealer, Ma,N., K., T. & Madden, TamaddoniBohan, D. C., A.,Vacher, Bista, I.,Walsh, K.,M., Carvalho, G.R.,Seymour, Hajibabaei,M., Lallias,D., …Creer, S. Berry, D.,Mahfoudh,Wagner, primersK. Ben, M.,used& Loy,A.(2011).in Barcoded Bensasson, Hartl,D. D.,G. L., &Hewitt, Zhang,D., M.(2001).pseudogenes: Mitochondrial A.C.,Benke, A.D., Huryn, Smock,L.a,& Wallace, J. B. (1999).Length Article D. Baird, J., & M. Hajibabaei, Biomonitoring2.0: (2012). newparadigminecosystem A Aird, D.,Ross, T., M. Chen,W.M.,Fennell, Russ,A. G., S., Danielsson, C.,…Gnirke, (2011). References through AgriculturalChina University. manuscript. We alsothankProf. and Leese for two reviewers commen Florian anonymous andtheValleys.WethankHPCWales Walesforallowing use for oftheirsystems analysis. https://doi.org/10.1186/1471 architectureL. (2009). BLAST+: and applications. https://doi.org/10.1016/j.tree.2017.03.001 Networks.Reconstruction of Ecological G. (2017).Next https:/ oflakeecosystemdynamics biodiversity. (2017). time Annual Microbiology amplicon pyrosequencingmultiplex biasamplification. https://doi.org/10.5061/dryad.d2f79 evolution ’smisplaced witnesses. 308 southeast inNorthfreshwater macroinvertebrates America withparticularreference to the 21 possible next assessment made by BiologyGenome andAnalyzing bias minimizingPCRamplification in Illum (8), 2039 – 343.https://doi.org/10.2307/1468447 /doi.org/10.1038/ncomms14087 X.Z. is also supported by the ChineseFund bythe UniversitiesX.Z. is Scientific (2017 alsosupported
ern United ern States. – 2044. https://doi.org/10.1111/j.1365 , 77 - Generation Global Large Biomonitoring: , (21 12 - (2), R18. https://doi.org/10.1186/gb ), 7846 series of analysis aqueouseDNAreveals ecologically relevant – 7849.https://doi.org/10.1128/AEM.05220 Journal NorthJournal of the AmericanBenthological Society - 21 - Nezhad, A., Raybould, Nezhad, A.,Raybould, Dumbrell, A. J., & Woodward, 05
TRENDS in TRENDS - generation DNAsequencing. - 10
- 421 Trends in Ecology and inEcology Evo Trends
Nature Nature Communications
Ecology &Ecology Evolution BMC BioinformaticsBMC - 294X.2012.05519.x
Applied andEnvironmental Applied - ina sequencing libraries. ina sequencing - scale, Automated 2011 - 12 - Molecular Ecolo Molecular mass relationshipsfor , - lution , 2 16 8 - , 14087. r18 , (6), 314 10
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This article isThis article by protected copyright. All rightsreserved. B.E., S. N.,Deagle, Jarman, Coissac AcceptedDarling, J.A., G.Galil, B. Carvalho, S., R., Viard,Rius, M., F.,& S., Creer, Deiner, K., Frey, S., D.,P.,Porazinska, Taberlet, Thomas, W. K., …Bik,H. M.(2016). Cranston, P. S.(1990).andinvertebrate taxonomy.Biomonitoring Crampton Crampton Collins, A., D.G.,Hoare,D.,& Ohandja, Voulvoulis, N. theWater (2012).Implementing ArticleClarke, J., L.J.,Soubrier, Weyrich, L.S., metabarcodes &A.(2014).Environmental Cooper, Clarke, J.M., L.J.,Beard, Swadling,K. M., &B.E.(2017). ofmarkerchoiceand Effect Deagle, Clarke, K.R., & Gorley,v6: N. R. UserManual/Tutorial. (2006). Plymouth: Primer PRIMER Choo, Crampton L. Q., Caporaso, G., J.,J. Kuczynski, Stombaugh,J., Bittinger,K.,Bushman,F.D.,Costello, E.K.,… Campos https://doi.org/10.1016/j.marpol.2017.08.014 biological ecosystems. invasions inmarine Recommendations fordeveloping andapplying genetictools andmanage to assess and Ecology The ecologist’s fieldguidetosequence and Assessmen https://doi.org/10.1186/s13742 outletting thegenes ofthebottle. Evolution mitochondrial metagenomicsrainforest ofabornean sample. V.,Khen, C. &Vogler,A. https://doi.org/10.1016/j.envsci.2011.11.003 and Wales. Framework Directive: A transition fromestabl Resources for insects:Insilico PCR Evolution th https://doi.org/10.1111/mec.14258 mitochondrial abundancespectrum. size classesin Phylogeny, alocal assemblageoftropicalDiptera: species diversityand data. Knight, R. (2010).allows of analysis high QIIME https:// (Hemiptera, Reduviidae). with two mitochondrial genesinMepraia spp. andTriatomaeratyrusiformis ermal cyclingermal protocol onDNA metabarcoding zooplankton studies. - Soto, Soto, R., Torres - - Nature Methods Platt, A., Yu,D.W., X., Zhou, & Platt, A., Timmermans, M.M. J.T. L., T. N.,Gimmel, Kutty,S. Cockerill, D., doi.org/10.1590/S1415 , , , pp. 1160 32 7 Environmental Science andPolicy (3), 873 Evolution (9), 2302 t , - 14 Platt, A., & Vogler,A.P. Shotgunmitogenomics (2017). acrossbody - – (2 Pérez, F.,&Pérez, Solari,A. incongruence inferred(2015). Phylogenetic – 883. https://doi.org/10.1002/ece3.2667 1170. https://doi.org/10.1111/1755 – – , , 3), 265 56 2316. https://doi.org/10.1093/molbev/msv111 7
reveals potentialreveals fortaxonomic bias. (5), 335 P. (2015). Soup to tree: The phylogeny of beetles P. toThephylogenyofbeetles inferred (2015).Soup tree: by , 68 Genetics andGenetics Molecular Biology – – , E., Pompanon, F., P.,, Taberlet, Taberlet, P., … 74. https://doi.org/10.1111/2041 - 273. https://doi.org/10.1007/BF00677921 475738320140301 - – 016 336. ht GigaScience
- Vogler, metagenomics: Mitochondrial A.P. (2016). Molecul 0120 - based identification of biodiversity. tps://doi.org/10.1038/nmeth0510 - Marine Policy y
, ar Ecology
ished monitoring networksinEngland 17
- ,
throughput community sequencing communitysequencing throughput 5 , 49 (1), 15.
– 61. ,
, Piraino, S. (2017). 17 , - 85 0998.12265 38 (8), 2045 (May), 54 (May), (3), 390
Molecular Molecular Ecology Environmental MonitoringEnvironmental Molecular Biology and Molecular - 210X.12574 – – 2054. – 395.
Ecology and Ecology
64.
- Methods Methods in 335
- E.
This article isThis article by protected copyright. All rightsreserved. Accepted C.,Baird,D.J.,Gibson, Shokralla,S., Curry, Monk, J.F., W. A.,King,I., & Hajibabaei, M O.,Folmer, Black,M., Hoeh, W.,R.,& forLutz, Vrijenhoek,R.(1994). primers DNA G.Ficetola, Pompanon, F., P.S Miaud, C., &Taberlet, (2008). N. Fahner, A., Shokralla,S.,Baird,D.J.,&M.(2016).Hajibabaei, Large Epp, L.S.,Bellemain, E.P.,J.,Esposito,A.,Riaz,T.,…Brochmann,C. Boessenkool, Haile, V.,Elbrecht, Vamos, Meissner, K., E. Aroviita,E., J.,& F.(2017). Leese, strengths Assessing Article V.,Elbrecht, & F.(2017). Leese, Validation andDevelopment ofPrimers COIMetabarcoding V.,Elbrecht, & F.(2015). Leese, DNA Can R.C. Edgar, (2010). andclusteringorder Search Dupuis, J.Roe,A.D.,& Spe R., Doi, H., R.,Akam Inui, throughput sequencing. throughput sequencing. (2015). Large https://doi.org/10.1371/journal.pone.0013102 invertebrates. amplification cytochrom of mitochondrial https://doi.org/10.1098/rsbl.2008.0118 environmental DNA fromwatersamples. https://doi.org/10.1371/journal.pone.0157505 annotation offourDNAmarkers. environmentalDNAplants through metabarcoding of Recovery, soil: resolution, and https://doi.org/10.1111/j.1365 past andpresentecosystems. (2012). environmentalmetabarcod New https://doi.org/10.1111/2041 routine stream monitoring. and weaknesses of DNAmetabarcoding 5 Macroinvertebrate Bioassfor Freshwater https://doi.org/10.1371/journal.pone.0130324 InnovativeMetabarcoding Protocol. Biasand TestingAbundance? Primer Biomass Bioinformatics 4436. https://doi.org/10.1111/j.1365 related animalsandfungi:isnot Onemarker enough. Freshwater Biology DNAanalysisforestimatingtheabundance ofEnvironmental and biomass streamfish. https://doi.org/10.1098/rsbl.2014.0562 not marker: a perfectmatch. Hajibabaei, M. (2014).cytochromeoxidase DNAmetabarcodingandthe c subunitI (April), 1 (April), – 11. https://doi.org/10.3389/fenvs.2017.00011 - scale biomonitoringscale of remoteand threatened ecosystems via high , Molecular Marine Biology Molecular Marine andBiotechnology 26 atsu, Y., Kanno, K., Yamanaka, H.,Takahara,T., T.& Minamoto, (2017). (19), 2460 , 62 (1), 30 PLoS ONE rling, F. Multi A. H. (2012). Methods in Ecology and inEcology Evolution Methods – – Biology Letters 2461. https://doi.org/10.1093/bioinformatics/btq461 - Molecular Ecology 39. https://doi.org/10.1111/fwb.12846 210X.12789 - 294X.2012.05537.x PLoS ONE PLoS , 10 - Based Ecosystem Assessments Species Ecosystem Based Quantify PLOS ONE - (10), 1 294X.2012.05642.x -
es foranalysingsoil DNA:Potential for studying based macroinvertebrat essment. essment. Biology Letters e c oxidasee c subunitI metazoan from diverse s than faster of BLAST. magnitude
, , 11 – — 10 15. , (6), e0157505.
Sequence ReSequence 10 (9), 1789 , 21 (7), e0130324. Frontiers inEnvironmentalScience
-
locus species delimitation in speciesdelimitation locus closely (8), 1821 Molecular EcologyMolecular , –
4 1793. pecies detectionusingpecies (4), 423 , lationships with an 3 – . (5), 294 1833. e identification for - scale monitoringscale – 425. –
299. , 21 (18), 4422 (18), . -
of
, – This article isThis article by protected copyright. All rightsreserved. AcceptedJackson, J.K., J. Battle, M., White, B.P.,Pilgrim, E.M., St Hu, S.(1987). Hiiesalu, Hebert, P. N., D. Ratna Hajibabaei, M., Spall,J.L.,Shokralla,S.,&van Konynenburg, Hajibabaei, M., Singer,G. Article Hajibabaei, M., Shokralla, S., Zhou, Gómez Gillett, C.P. D.T.,Crampton Gibson, S.,Porter, J., T.King,Shokralla, Konynenburg,S.,D. M., I.,van Janzen, H., … Science communities andDNAmorphological based on identifications. barcode biodiversitya B. W.Cryptic instreams: comparison ofmacroinvertebrate (2014). 4754(87)90094 Simulation https://doi.org/10.1111/nph andrichness biomass. Species mycorrhizalfungi: richness of Associations withplant arbuscular grassland https://doi.org/10.1098/rsbl.2003.0025 Proceedings RoyalSciences ofthe Society B: Biological among subunitspecies.cytochrome c oxidase 1 divergences closely related https://doi.org/10.1186/1472 environmental barcodingof DNAfrompreservativeethanol. of afreshwaterbenthic macroinvertebrate through community non https://doi.org/10.1186/1741 in of DNA andDNAbarcodes biodiversity monitoring. arrays https://doi.org/10.1371/journal.pone.0017497 using river benthos. barcoding: Anext 883 of assemblages.and phylogenetics complex P. the powermetagenomics (2015).Validating of ecology mitochondrial forcommunity and Evolution ofelucidates thephylogeny weevils(Coleoptera: Curculionoidea). & Vogler,A.P. (2014).denovofrom assembly Bulk mitogenome pool https://doi.org/10.1073/pnas.1406468111 AcademyNational ofSciences a bulksampleoftropicalmetasystematics. arthropods DNA through Hajibabaei, microbiome in M. (2014).assessmentof and Simultaneous themacrobiome https://doi.org/10.1371/journal.pone.0138432 - Rodríguez, C., CramptonRodríguez, C., – I., Pärtel,M., Davison, J.,P., M., Gerhold, Moora, Metsis, … Wilson, M.,D. S. (2014). 894.https://doi.org/10.1111/2041 , 33 Akaike informationcriterionAkaike statistics
(1), 312 (Vol. 29). KTKScientificPublishers,Tokyo. https://doi.org/10.1016/0378 , 31 - 2
(8), 2223 singham, S.,& Barcodinganimallife: J.R.singham, deWaard, (2003). - generation sequencing approach for biomonitoring applications for generation applications approach biomonitoringsequencing – 324. https://doi.org/10.1086/675225 PLoS ONE PLoS a C., Clare, E. L., E. &a C.,Clare, P. D. Hebert, andapplicability N.(2007).Design New Phytologist New - Platt, A., Timmermans, M. J. T. N., Jordal, B. H., Emerson, Emerson, Platt, A.,Timmermans,M.N.,Jordal,B.H., C., J.T. – - 2237. https://doi.org/10.1093/molbev/msu154 Platt, A., M. Timmermans, J.T.N.,Baselga,A.,& Vogler, .12765 , - - , X., Singer,G. A. C.,&Baird,D.J.Environmental (2011). 6785 7007 111 6 (4), e17497. (22), 8007 - -
12 5 - 24 , - 28 -
203 210X.12376
(1), 233 Methods in andEvolution Methods Ecology – 8012. .
Mathematics and Computers in andComputers Mathematics ein, E. D.,ein, E. Miller,P.& Sweeney, E., –
244. , 270
S. (2012). Assessing S. (2012). biodiversity Assessing
, S96 BMC BiologyBMC BMC EcologyBMC – S99. Molecular Biology - destructive destructive Proceedings of thProceedings of ed total DNA ed Freshwater , , 5
12 (1), 24. (1), 28. , 6 (8), -
A. e This article isThis article by protected copyright. All rightsreserved. J. Macher, Loreau, M.,& asynthesis C. andecosystemstability: deMazancourt, (2013).Biodiversity of Liu, S., Wang, X., L.,Tan,M.,Xie, Z., Su,X.,Zhou,X. capture Li, … (2016). Mitochondrial B.,Wysoker,Li, H.,Handsaker, The A.,Fennell,T.,Ruan,J.,Homer,N.,R.(2009). … Durbin, short Fastandaccurate readalignmentLi, H.,&R.(2009). withBurrows Durbin, M.,Yang, C.P.,Leray, N., J. Meyer, Mills,S.C.,Agudelo, Y., Ranwez,V., R.J.… Machida, M.,&Leray, Knowlton,ofstandardized N. andmetabarcoding (2015).DNAbarcoding Lacoursière L.,Krebes, & Kelly, R. Ji, Y., D. Ashton,L.,Pedley,Y., S.M.,A.,… P., Tang, Nakamura, Yu,D.Edwards, W.(2013). Je
Accepted Article ffery, N. W., & Gregory,T. usingGenome sizeestimatesR. (2014). Feulgen forcrustaceans protocol formetagenomic studies increases mitochondrial DNAyieldby twoorders of https://doi.org/10.1111/ele.12073 underlying mechanisms. 0998.12472 Molecular EcologyResources enriches mito https://doi.org/10.1093/bioinformatics/btp352 Alignment/MapSequence format andSAMtools. https://doi.org/10.1093/bioinformatics/btp324 transf 10 fish gut contents. region for metabar (2013). versatile settargeting primer ashortA new fragmentof themitochondrialCOI Academy ofSciences revealsamples patterns diversity. ofbenthic marine https://doi.org/10.1111/1755 environmental conditions. biomass eDNAconcentrations: amongvariability from methodsand capture Proteomics in thecontrolregion. Anewgene andnon Amphipoda): order Science L. DNAtoCrowder, environmentalmanagement.B. (2014). improve Harnessing Letters Reliable, verifiable andefficient monitoring of viametabarcoding.biodiversity 862 analysisimage of ethanol densitometry - 34 P., Port, J. a., Yamahara, K.P.,Port, J.a.,Yamahara, G., R. M.,Martone, Lowell, N., P.Thomsen, F.,… – 868.https://doi.org/10.1002/cyto.a.22516 -
orm. N., Zizka, - , , Roussel, A.,Rosabal, M.,& Bernatchez, L.(2016). Estimatingfish and abundance
16 Bastrop, R. (2012). The mitogenome of Gammarus duebeni (Crustacea (Crustacea mitogenome ofGammarus(2012). duebeni Bastrop, R. The 344 (10), 1245 , Bioinformatics
(6191), 1455 7 (2), 201 - DNA 100 fold, enablingPCRDNA 100 fold,
V.M. A., Weigand,A.M.,& Leese, F.(2017).centrifugation Asimple Frontiers inZoology Frontiers coding metazoan diversity: applicationcoding metazoandiversity: for characterizing coralreef , – – Comparative Biochemistry Comparative and Physiology 11 1257. https://doi.org/10.1111/ele.12162 211. https://doi.org/10.1016/j.cbd.2012.02.004 2 Ecology Letters Ecology – (7), 2076 , 1456. https://doi.org/10.1126/science.1251156 25 Molecular Molecular Ecology , (14), 1754 - 1 0998.12522 6 (2), 470 –
2081. https://doi.org/10.1073/pnas.1424997112 , 10 - – , preserved tissues. preserved - – 1760. neutral sequence repeats sequence evolutionneutral of tandem 16 (1), 34. https://doi.org/10.1186/1742(1), 34. 479. https://doi.org/10.1111/1755 -
free free mitogenomics biodiversity analysis. , 106
Resources
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Proceedings of the ofthe Proceedings National , 16 Cytometry PartCytometry A (6), 1401
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25 Part D: Genomics and Part D:Genomics (16), 2078(16), – 1414.
- Wheeler Wheeler , - 85 – Ecology Ecology 20 - (10), 9994 79. -
This article isThis article by protected copyright. All rightsreserved. Accepted M.,Seymour, Durance,I.,Cosby,Ransom B.J., Saitou, N., &Nei,M.(1987).Theneighbor Piñol, G., J.,Mir, Gomez M.,Pfrender, Hawkins,C.,Bagley, M., Courtney,G.,Creutzburg, B.,J.,… Epler, Whiting, M. Peng, Y., H.Yiu, M., Leung, C.M., &Chin,F. S. L.(2012).IDBA Y. O’donnell, L., R.P., Kelly, J. Lowell, C., N. Port,J. A.PCRinduce& primers (2016). Indexed Article J.,Morinière, L., Hendrich, Balke,M., Beermann, A. J., König,T., …Haszprunar,G. Hess, M., Miyamoto, M. M., M.Allard, R. W., L.L.,& M., Janecek, Adkins, Rodney, I.,Meusnier, Singer,G.A. C.,Landry,J.F. M.,Mährlein, Pätzig, Brauns,M., M., Mä chler, E., Deiner, K.,chler, E.,Deiner, Steinmann, P., Utility & F.(2014). ofenvironmental Altermatt, DNA 0005 mesocosms. S. (2018). promotes degradation Acidity of multi https://doi.org/citeulike phylogenetic trees. https://doi.org/10.1111/1755 metabarcoding of arthropods. mismatches limit theuse of high ReviewQuarterly ofBiology and Challenges inDNA (2010). Macroinvertebrate Assessing Biodiversity inFreshwaterEcosystems: Advances Bioinformatics single https://doi.org/10.137 template 1293 (Ephemeroptera, Plecoptera andTrichoptera). (2017). barcode forGermany′slibrary A DNA stoneflies andcaddisflies mayflies, Biology Congruence Test of Using Reliability Linked MitochondrialDNASequences. 214. https://doi.org/10.1186/1471 DNAmini (2008). A universal Hydrobiologia macroinvertebrateslake corrected forback 1174 andindicatorfor monitoringrare macroinvertebrate species. https://doi.org/10.1111/2041 magnitude. – – - 3 - 1307. https://doi.org/10.1111/17551307. https://doi.org/10.1086/678128.1183. cell andcell metagenomic sequencingdatawithhighlyunevendepth.
, 43 -
Specific biasin Large (2), 236 Methods in and Methods Ecology Evolution
Communications BiologyCommunications , , 768 28 (11), 1420 – - (1), 37 Polo, N. Universalandblockingprimer P.,&Agustí, (2015). Molecular Biology and E 249. https://doi.org/10.1093/sysbio/43.2.236 - 1/journal.pone.0148698 based ApproachesReview TheQuarterly of - article – 50. https://doi.org/10.1007/s10750 , – - 85 1428. https://doi.org/10.1093/bioinfo barcode for barcode biodiversity analysis. - - 210X.12937 0998.12355 Molecular Ecology Resources Molecular - - (3), 319
Scale DNA sequencing studies.Scale DNAsequencing id:93683 & Dolman,A.M.Length (2016). - throughput DNAsequencing forthequant throughput - 2164 , Hickey,D. P. A.,Hebert, M. D.N.,&Hajibabaei, - , joining method: a new method method:anewmethod forreconstructing joining 1 – (1), 4. https://doi.org/10.1038/s42003(1), 4. 340. https://doi.org/10.1086/655118 -
9 - Jones, E., Deiner, K., Ormerod, S. J., … Creer, Jones, E.,Deiner,K.,Ormerod,S. J.,…Creer, -
- 0998.12683 214 - volution transformation and preservationtransformation effects.
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- Biology. 2526 rmatics/bts174
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- , This article isThis article by protected copyright. All rightsreserved. AcceptedWeiss, S., S.,Amir,Xu, Z.Z.,Peddada, A., K.,Bittinger, A.,…Knight, Gonzalez, R.(2017). Weiss, H.,Li, Weigand, H., M.,Cai, C., Y., Yu,L., & Leese,F.(2017).Decipheringthe Zhang, Thomp Thomas, Deagle,B. A.C., E., J. P.,Eveson, Harsch,C.H C. Computing.Team, R. (2015). R:ALanguageandEnvironmentforStatistical Vienna, Tang, M., Tan,Meng,G.,sequencing Su,X.,S.,…X.(2014). Yang,Liu, Zhou, Multiplex S., Article C.J.,Tang, M., Hardman, Ji,Y., G., Tan, Meng, Yu,D. Liu,S., W.(2015). M., … High Tamura, K.,Dudley,J.,Nei,M., S. &(2007). MEGA4:MolecularEvolutionary Kumar, Genetics B.Sweeney, T.of W., J. J.K.,barcodes Battle, M., Jackson, &Dapkey, (2011).CanDNA F., Sinniger, Pawlowski, J., S.,Gooday,Harii, Chevaldonné,P., A. Yamamoto, H., …Creer, J., Shokralla, S.,Porter, W., T.M.,Gibson,J.F.,R.,Janzen,D.H.,Hallwachs, … Dobosz, characteristics. Normalization strategies upon anddifferential abundance depend data microbial 26 origin of mito 4 gap specific and choice. penalties weightmatrix alignmentof progressivemultiple sequence weighting, throughsequence position 714 correction derivedfromcontrol factors material. DNA metabarcoding: of Improvedestimates species proportional biomassusing Computing. RFoundation Austria: Statistical forStatistical Computing;2014.for RFoundation https://doi.org/ mito of pooledmitochondrialgenomes 210X.12416 in and Methods Ecology Evolution of wildthroughput monitoringdiversityand bee abunda 1599. https://doi.org/10.1093/molbev/msm092 (MEAnalysis https://doi.org/10.1899/10 quality? macroinvertebratesstream improve descr https://doi.org/10.3389/fmars.2016.00092 Knowledge of Deep of S. (2016).Analysis SedimentaryDNAReveals Worldwide Maj https://doi.org/10.1038/srep09687 identificat Hajibabaei, M. (2015). parallel Massively multiplex DNAsequencing for specimen 680. https://doi.org/10.1093/nar/22.22.4673 son, J.son, D., D. & Higgins, G., Gibson, W: improving T.J.CLUSTAL thesensitivity (1994). (20), 5705 – - 726.https://doi.org/10.1111/1755 metagenomics. metagenomics. Journal North ofthe American BenthologicalSociety ion using MiSeqplatform.an Illumina
– GA) softwareversion4.0. - 5715. https://d nuclear discordance in discordance two caddisflyspecies. nuclear sibling Microbiome 10.1093/nar/gku917 - Sea Benthos. Nucleic AcidsResearch - , 016.1 5 oi.org/10.1111/mec.14292 (1), 27. https://doi.org/10 , Frontiers inMarineFrontiers Science — 6
a crucial stepa crucial toward using biodiversityanalysis (9), 1034
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, – 42 1043. https://doi.org/10.1111/2041
(22), e166
Scientific Reports Nucleic Acids Research ., &Trites, A. W.(2016). Quantitative Molecular ResourcesMolecular Ecology
.1186/s40168
nce viamitogenomics.nce – e166. , , 30 3 , 92. or Gaps in Taxonomic or GapsinTaxonomic (1), 195 , 5 Molecular Ecology , 9687. - 017 , , – 24 22 216. - (8), 1596 (22), 4673 0237 - , 16 - y (3),
- - – – , This article isThis article by protected copyright. All rightsreserved. performed prep,metabarcoding library ranbioinformatics of metabarcoding data IB theexperimentsIB, SC,GRCdesigned Author contributions accession(Study The dataforthis work canbeaccessed Nucleotide attheEuropean Archive (ENA) database Data accessibility Zhou, X.,Y., Yang,Q.,Zhou,L.,Q. Li, Huang, Liu,S., Su,X., (2013). … Ultra H. A., Zhan, & MacIsaac, J. biosphereexploration Rare (2015). using high A.,S. Zhan, H.Bailey, Heath, D. Macisaac, D.,& J. Performance (2014). comparisonof Yu, D. W.,Ji,Y., Eme X.,Yang, Miller,J.A.,M.,Ji,Y.,C., Wang, De Blécourt, Yan Y.,Xie, Wu,G., Tang, Luo,R.,Patter J., G.,Woodward, & Gray,C., (2013). the21stnew Baird,D.J. Biomonitoringfor Century:
Accepted measurements, performed optimised andperformed morphometric DNA extractions and Article amplification. highenables 522. https://doi.org/10.1007/s10592 sequencing: progressresearch perspectives. and https://doi.org communities.complex markersgenetic for high https://doi.org/10.1111/j.2041 biomonitoring. and assessment arthropodsforrapidbiodiversity of soup: Metabarcoding https://doi.org/10.1016/j.ecolind.2014.06.028 biodiversitygeneral indicator. metabarcoding tocollected askifeasily soilleaf and 1660 De novo withassembly transcriptome short RNA 32 perspectives threats. globalisation andemerging inanageof environmental (2), 159 – 1666. https://doi.org/10.1093/bioinformatics/btu0771666. statistical analysis. SS,MHran – 174. PRJEB23036 - fidelity recoveryfidelity ofbiodiversity forbulkarthropod sampleswithoutPCR GigaScience /10.1111/1755 rson, B. C., Wang, X., B.C.,rson, Wang, Ye,C.,Yang,&Ding,Z. (2012).Biodiversity Methods in Ecology and inEcology Evolution Methods
Molecular EcologyResources ). - throughput sequencing throughput
, 2 (1), 4. https://doi.org/10.1186/2047 - Ecological Indicators 0998.12254 - 210X.2012.00198. . son, S.,J. J., Liu, … Wang, (2014).SOAPdenovo
KW, MH, XZ, MC contributed MCcontributed XZ, KW, MH, the - 014 metabarcoding sequencing. MT, SL, XZ - 0678
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(4), 613 - 46 , g, C., … Yu, D. W. (2014). Using g, C., … Yu,D.W.(2014).Using litter canbe samples usedasa 14 , 379 (5), 1049 – –
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, (3), 513 30 Limnetica (12), - design. Trans: ran – , This article isThis article by protected copyright. All rightsreserved. an invertebrate IB specimens. wrotefirstversionSC,GRCeditedmanuscript, ofmanuscript. sequen
Accepted Articled allauthorsprovidedcomments cing analysis ofand bioinformatics mitogenomics
.
.
DB taxonomically identifiedDB taxonomically This article isThis article by protected copyright. All rightsreserved. community. foreachmock positive control community. in (lightgrey) each abundance highest grey) (dark and abundance lowest with thespecies Highlighted Last col used. species Table 1 Accepted ArticleNumber 10 14 13 12 11 9 8 7 6 5 4 3 2 1 :
Design of mock communities. See columns for the detailed contents of each community (1 community each of thecontents for detailed columns See communities. mock of Design Total Number of species of Total Number Total specimens Drosophila melanogaster Gammarus pulex Bithynia leachi Notonecta glauca Physa fontinalis Radix balthica Potamopyrgus antipodarum Planorbis planorbis Gyrinus marinus Ephemera danica Bithynia tentaculata Bathyomphalus contortus Asellus aquaticus Anisus vortex umn: total number ofspecimens/ totalnumber umn: Species
157 14 12 10 10 24 16 24 14 35 3 2 1 3 2 1 1 species, bottom line: total number of specimens/ numberof total line: species, bottom 157 13 15 32 25 10 13 40 3 5 3 0 3 1 3 4 2
145 13 28 19 12 45 3 6 5 0 4 5 3 1 6 8 3 149 14 17 25 22 10 25 11 10 3 4 1 4 6 6 5 4 155 14 16 21 26 10 14 25 3 8 9 2 8 1 4 8 5 Community - 10), with numbers referring to specimens from each from specimens to referring numbers with 10), 146 14 11 10 10 33 12 17 20 3 8 1 4 8 1 8 6 community and number of species/ numberof and community 139 13 12 12 14 10 27 19 15 3 1 8 0 7 5 6 7 Drosophila melanogaster Drosophila 139 14 13 17 10 18 15 21 10 3 8 7 6 1 9 1 8 151 13 13 13 13 14 20 24 30 3 3 0 9 1 6 2 9 community. was used as used as was 141 10 13 14 16 20 26 24 3 7 8 0 6 5 7 4 1 per species Specimens Specimens 1479 186 141 108 180 142 226 30 52 83 31 70 94 55 81
This article isThis article by protected copyright. All rightsreserved. Total (mg) marinus Gyrinus pulex Gammarus Asellus aquaticus glauca Notonecta Radix balthica antipodarum Potamopyrgus Physa fontinalis tentaculata Bithynia leachi Bithynia planorbis Planorbis contortus Bathyomphalus Anisus Species Table 2
Accepted danica Ephemera Article
vortex
:
Estimated biomass Estimated
for each species included species for each inthemockcommunities 370.25 21.69 71.92 30.49 1.00 77.38 20.47 3.82 1.16 115.60 11.97 8.87 0.79 5.08 1 Community
255.46 9.36 14.24 54.70 4.92 0.00 89.72 13.37 4.14 46.33 3.19 9.04 0.70 5.75 2
211.02 30.00 4.18 75.11 9.00 0.00 31.37 11.66 4.78 26.58 4.52 6.75 0.65 6.44 3
479.23 104.94 28.62 51.18 13.02 33.88 106.12 9.89 7.91 113.80 0.94 7.66 0.56 0.70 4
464.82 40.35 35.93 90.38 19.50 16.09 101.69 8.10 10.81 128.77 8.95 0.37 0.47 3.41 5
. 377.48 85.77 54.17 104.72 22.01 7.47 57.27 13.87 13.10 4.01 10.30 1.56 0.40 2.84 6 Values are presented are inmilligramsValues (mg).
371.80 52.20 46.02 10.13 22.68 0.00 70.67 5.27 16.42 135.45 7.45 3.10 0.31 2.10 7
503.18 98.29 80.35 128.80 27.56 46.54 6.08 6.46 17.02 79.47 6.61 4.53 0.05 1.42 8
395.20 60.07 62.88 42.39 30.73 0.00 53.80 0.36 18.70 104.71 12.50 4.77 0.10 4.21 9
524.22 72.01 86.31 83.34 37.72 62.09 35.91 1.74 0.00 124.64 14.54 5.55 0.22 0.13 10
This article isThis article by protected copyright. All rightsreserved. Table I-130R I-B1 HC02198 LCO1490 Accepted ArticlePrimer Name 3 :
COI primers used primers COI for metabarcoding. GAAAATYATAAIGAAIGCRTGAGC CCHGATATAACITTYCCICG TAAACTTCAGGGTGACCAAAAAATCA GGTCAACAAATCATAAAGATATTGG Primer Sequence Primer Sequence
Direction
R R F F Meusnier Meusnier Hajibabaei Folmer Folmer et al. et al. et et al. et et al et 1994 1994 Citation 2008 (modified) . 2012. (modified)
Number 13 12 11 10 9 8 7 6 5 4 3 2 1
Accepted isThis article by protected copyright. All rightsreserved. Article( with indicated are (<0.05) relationships Significant t The normalised). ratio SumAmpl 658bp, FFFR: 130bp, Table
4 Gyrinidae Ephemeridae Gammaridae Asellidae Notonectidae Lymnaeidae Hydrobiidae Physidae Bithyniidae Bithyniidae Planorbidae Planorbidae Planorbidae Family Taxa :
Summary table of significance of of ofsignificance table Summary
ype of model used used ofmodel ype Radix balthica antipodarum Potamopyrgus Physa fontinalis tentaculata Bithynia leachi Bithynia planorbis Planorbis contortus Bathyomphalus Anisus vortex Species Gyrinus marinus Gyrinus danica Ephemera pulex Gammarus Asellus aquaticus glauca Notonecta icon
: sum of all amplicon data per species), and shotgun data (“Shotgun”, (“Shotgun”, data shotgun and dataperspecies), ofallamplicon sum :
reads to biomass to biomass reads
is
indicated by shading (light grey: shading by indicated
*). *).
correlations <0.01* 0.04 0.52 0.05* 0.02* 0.03* 0.04* 0.25 0.58 0.11 0.03* <0.01* 0.01* B1FR Amplicon
,
for each sequencing treatment. Amplicon data (“Amplicon”, B1FR:450bp, FF130R: FF130R: B1FR:450bp, (“Amplicon”, data Amplicon treatment. each for sequencing <0.01* 0.02* 0.06 0.07 0.01* 0.01* <0.01* <0.01* 0.27 0.01* 0.06 0.06 <0.01* FF130R
logistic
, white:
linear <0.01* 0.06 0.32 0.15 0.51 0.03* 0.02* 0.57 0.37 0.04* 0.09 0.07 0.06 FFFR
). Shotgun data not shown for species species for shown not data ). Shotgun
pShotgun: proportion of reads, Mit ofreads, proportion pShotgun: <0.01* 0.02* 0.46 0.06 0.09 0.01* 0.02* 0.04* 0.46 0.03* 0.07 0.02* 0.02* SumAmpl
icon
<0.01* <0.01* <0.01* 0.02* 0.01* <0.01* <0.01* <0.01* 0.08 <0.01* 0.01* <0.01* NA pShotgun Shotgun
A. vortex A.
oNorm: mito oNorm:
0.01* <0.01* <0.01* 0.03* 0.02* 0.01* <0.01* <0.01* 0.09 <0.01* 0.01* <0.01* NA MitoNorm (NA). (NA).
-
This article isThis article by protected copyright. All rightsreserved. Accepted Article
This article isThis article by protected copyright. All rightsreserved. Accepted Article
This article isThis article by protected copyright. All rightsreserved. Accepted Article