draft - university of toronto t-space · draft 6 level and were left as bacidina arnoldiana...

Draft

Barcoding lichen-forming fungi using 454 pyrosequencing is

challenged by artifactual and biological sequence variation

Journal: Genome

Manuscript ID gen-2015-0189.R2

Manuscript Type: Article

Date Submitted by the Author: 29-Apr-2016

Complete List of Authors: Mark, Kristiina; Swiss Federal Research Institute WSL; University of Tartu, Institute of Ecology and Earth Sciences Cornejo, Carolina; Swiss Federal Research Institute WSL Keller, Christine; Swiss Federal Research Institute WSL Flück, Daniela; Swiss Federal Research Institute WSL Scheidegger, Christoph; Swiss Federal Research Institute WSL

Keyword: 454 pyrosequencing, Internal Transcribed Spacer, Lichenized fungi, Intragenomic variation, DNA barcoding

https://mc06.manuscriptcentral.com/genome-pubs

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Barcoding lichen-forming fungi using 454 pyrosequencing is challenged by

artifactual and biological sequence variation

Kristiina Mark1, 2*, Carolina Cornejo1, Christine Keller1, Daniela Flück1, Christoph

Scheidegger1

1Biodiversity and Conservation Biology, Swiss Federal Research Institute WSL,

Switzerland

2Institute of Botany and Ecology, University of Tartu, Estonia

* Corresponding author: Kristiina Mark; e-mail: [email protected]

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Abstract

Although lichens (lichen-forming fungi) play an important role in the ecological integrity

of many vulnerable landscapes, only a minority of lichen-forming fungi have been

barcoded out of the currently accepted ~18,000 species. Regular Sanger sequencing can

be problematic when analyzing lichens since saprophytic, endophytic, and parasitic fungi

live intimately admixed, resulting in low-quality sequencing reads. Here, high-throughput,

long-read 454 pyrosequencing in a GS FLX+ System was tested to barcode the fungal

partner of 100 epiphytic lichen species from Switzerland using fungal-specific primers

when amplifying the full Internal Transcribed Spacer region (ITS). The present study

shows the potential of DNA barcoding using pyrosequencing, in that the expected lichen

fungus was successfully sequenced for all samples except one. Alignment solutions such

as BLAST were found to be largely adequate for the generated long reads. In addition,

the NCBI nucleotide database—currently the most complete database for lichen-forming

fungi—can be used as a reference database when identifying common species, since the

majority of analyzed lichens were identified correctly to the species or at least to the

genus level. However, several issues were encountered, including a high sequencing error

rate, multiple ITS versions in a genome (incomplete concerted evolution), and in some

samples the presence of mixed lichen-forming fungi (possible lichen chimeras).

Keywords: 454 pyrosequencing, DNA barcoding, Intragenomic variation, Internal

transcribed spacer, Lichenized fungi

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Introduction

Lichens are intimate and long-term symbiotic associations consisting of a heterotrophic

fungal partner—also called the mycobiont—and photosynthetic algae or cyanobacteria—

also called the photobiont (Nash III 2008). In a systematic context, lichens are named

after the fungal partner, and according to most recent estimates, about 18% of all fungal

species are lichen-forming (Feuerer & Hawksworth 2007). While lichens include many

bio-indicators for monitoring environmental quality—including air pollution and

ecological integrity of forest landscapes (Nimis et al. 2002)—accurate identification of

lichenized fungal species remains challenging (Lumbsch and Leavitt 2011). DNA-based

specimen identification to a species level is useful in a system of well-circumscribed taxa

and a high-quality reference database (Seifert 2009, Begerow et al. 2010). Recently, the

internal transcribed spacer region (ITS) of the nuclear ribosomal RNA cistron was

proposed as the primary fungal barcode marker (Schoch et al. 2012). However, only a

minority of lichen-forming fungi have been barcoded from the estimated 17,500 species

(Feuerer & Hawksworth 2007). For example, the largest and most typical order of lichen-

forming fungi (Lecanorales) consists of about 5,700 species, but only about 29% of them

have publicly available ITS sequences in sequence databases such as the National

Institute of Health’s (NIH) genetic sequence database, GenBank

(http://www.ncbi.nlm.nih.gov/genbank/; accessed 28 September 2015), the Barcode of

Life Data System (BOLD; www.boldsystems.org; Ratnasingham and Hebert 2007), and

UNITE (https://unite.ut.ee/; accessed 24 November 2015; Abarenkov et al. 2010).

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Barcoding lichens using Sanger sequencing has been successful in some groups of

lichens (Kelly et al. 2011, Divakar et al. 2015), especially with foliose and fruticose

lichens; however, in crustose lichens—that constitute by far the vast majority of

lichenized species (Bergamini et al. 2005)—it often proves quite challenging (Flück

2012). Sampling difficulties occur where other very similar lichen species live mixed or

close by, and many saprophytic, endophytic, and parasitic fungi also live intimately

admixed with the lichen mycobiont, making the application of Sanger sequencing

insufficient in many cases (Flück 2012, Orock et al. 2012). A limited number of studies

are known to have successfully applied pyrosequencing to recover the identity of a lichen,

when Sanger sequencing failed to produce usable results (Hodkinson and Lendemer 2013,

Lücking et al. 2014a).

Recent advancements in pyrosequencing methods now allow the amplification of

fragments up to 1,000 basepairs (bp) in the GS FLX+ system of Roche/454

pyrosequencing. However, 454 pyrosequencing is notorious for its high indel (short

insertions and deletions) error rate in homopolymeric regions (three or more identical

nucleotites) and carry-forward-incomplete-extension (CAFIE) errors (Margulies et al.

2005, Huse et al. 2007, Gilles et al. 2011, Lücking et al. 2014b). In addition to artifactual

sequence variation, biological sequence variation—such as intragenomic and/or intra-

mycelial (i.e. allelic heterozygosity) variation of this multicopy gene—may be possible

(Wörheide et al. 2004, Simon and Weiß 2008, Linder et al. 2013).

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The aim of our study was to test whether lichen mycobiont can be successfully identified

to a single species using DNA barcoding through pyrosequencing the ITS marker of 100

species of both foliose-fruticose and crustose lichens, using fungal-specific markers in the

high-throughput 454 sequencing in the GS FLX+ system, while elucidating and

quantifying artifactual and biological sequence variation.

Materials and Methods

Taxon sampling and morphology-based identification

One hundred lichen specimens, including 52 crustose species and 48 macrolichens

(foliose and fruticose thalli), were collected from different locations in Switzerland in

2011 and 2014. The full list of specimens with voucher information is given in Table 1.

Additional specimen data—such as the collection GPS coordinates, substrate, specimen

photographs, the primary ITS barcodes—are available though a public BOLD dataset

DOI: dx.doi.org/10.5883/DS-LICODE. All project data can also be accessed though the

PlutoF cloud database under a project “Barcoding Swiss lichens using 454

pyrosequencing” (https://plutof.ut.ee/#/study/view/31890). Specimen identifications of

the collected material were based on morphological and chemical characters, following

the nomenclature of Clerc and Truong (2012). Lichen chemistry was examined with

standardized thin layer chromatography (TLC) using solvent systems A, B, and C

(Culberson and Ammann 1979, White and James 1985). Sorediate Bacidia and Lecanora

species without apothecia, samples #6, #7, and #42, could not be identified to the species

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level and were left as Bacidina arnoldiana aggregate (aggr.) and Lecanora strobilina

aggr., respectively. Specimen LC-088, determined as Lecidella sp., includes an

undescribed chemotype for Lecidella (arthothelin, 2,4-dichloronorlichexanthone), and

BC-47-1 Lecanora sp. morphologically resembles Haematomma ochroleucum or Biatora

flavopunctata, with atranorin, usnic acid, and zeorin identified as secondary substances.

Specimens with poorly expressed diagnostic characters were re-checked in light of

barcoding data, and the determination of five specimens was corrected (LC-023 Lecanora

cf. umbrina ⇒ Lecania cf. cyrtella, BC-027-1 Haematomma aff. ochroleucum or Biatora

flavopunctata ⇒ Lecanora sp., BC-155-5 Lecidea nylanderi ⇒ Loxospora elatina, BC-

161-5 Lecanora farinaria/expersa ⇒ Loxospora elatina, KM-03-02 Usnea florida ⇒

Usnea intermedia). All specimens are stored at the WSL Swiss Federal Research Institute

at –20°C.

Molecular methods

About 3–5 mg of visually uncontaminated lichen thallus of each specimen was sampled

for molecular analyses. In sampling, vegetative thallus was preferred, but in some

apotheciate crustose species with no visible vegetative thallus, 1–2 apothecia were used

for DNA extraction. Frozen lichen samples were lyophilized and disrupted with a

stainless steel bead in a Retsch MM2000 mill (Düsseldorf, Germany) for two min at 30

Hz. The full genomic DNA was extracted using the Qiagen DNEasy Plant Mini Kit

(QIAGEN, Hilden, Germany) following the manufacturer’s Plant Tissue Mini Protocol

and diluted in 50µL elution buffer. A two-step Polymerase Chain Reaction (PCR)

approach was used for unidirectional amplicon sequencing. First, the full ITS was

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amplified via PCR by using short fungal-specific primers, ITS1F (Gardes and Bruns

1993) and ITS4 (White et al. 1990). Each PCR reaction (25µl) consisted of 2× KAPA

HiFi HotStart ReadyMix PCR mix (KAPA Biosystems), 5 µM of each of the forward and

reverse primer, and 1 µL of template DNA. Thermal cycle conditions included the initial

denaturation at 95°C for 2 min; 35 cycles of denaturation for 20 sec at 98°C, primer

annealing for 15 sec at 57°C, and extension for 20 sec at 72°C; and final extension for 3

min at 72°C. The PCR products were visualized on 1.5% agarose gel and purified via

Exo-SAP (Fermentas) treatment. In the second PCR step, the products were re-amplified

with full-length fusion primers designed by Microsynth AG (Balgach, Switzerland). The

fusion primers contained the GS FLX Titanium A- and B-adapters of the kit Lib-L

(Roche Diagnostics), the Multiplex Identifier (MID) sequence, four base library key

sequence (TCAG), and the same sample-specific primers used in the first step. The MID

tags were used only on the forward, A-adapter for unidirectional sequencing.

Amplifications were conducted in 50 µL reaction volumes containing 39 µL of

mastermix with reagents 5× KAPA HiFi Buffer, 10 mM KAPA dNTP Mix, 2U/100µL

KAPA HiFi HotStart DNA Polymerase (KAPA HiFi HotStart PCR Kit, KAPA

Biosystems), 4 µM of each of the forward and reverse primer, and 1 µL of template DNA.

The cycle conditions were: initial denaturation at 95°C for 3 min; 12 cycles of

denaturation at 98°C for 20 sec, primer annealing at 56°C for 30 sec, and elongation at

72°C for 30 sec; and a final elongation step at 72°C for 5 min. The aliquots were then

purified via AMPure Beads XP (Beckman Coulter, Brea, CA, USA). Concentrations of

purified PCR products were quantified by fluorometry using the Quant-iT™ PicoGreen®

dsDNA Assay Kit (Molecular Probes, Eugene, OR, USA). Probes were pooled in four

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equimolar pools (25 each), purified in 1.5% preparative gel, and run on 4/16 of a

sequencing plate using Titanium FLX+ reagents on a GS Roche Sequencer (454

technology, Roche Diagnostics). Pre-sequencing steps (starting from the second PCR),

sequencing, raw data processing using #3 pipeline preconfigured by Roche for long

amplicons, and sorting the resulting reads into samples based on their MID’s

(demultiplexing) were all carried out by Mircosynth AG.

Data processing and analyses

We followed a traditional and rather conservative approach when sorting and clustering

sequences. Reads with a non-matching forward primer, that were shorter than 500 bp,

included more than two ambiguous sites, and/or with a mean quality score lower than 25

were disregarded using the programs Cutadapt v1.7 (Martin 2011) and PRINSEQ-lite

v0.20.4 (Schmieder and Edwards 2011). The quality-sorted reads were screened for

chimeras using the ‘uchime_ref’ command in the sequence analysis tool USEARCH

v8.0.1623 (Edgar et al. 2011), searching against the UNITE/INSDC reference database of

fungal ITS sequences (Nilsson et al. 2015) available at http://unite.ut.ee/repository.php

(accessed 26 July 2015). The sequence data were not denoised, and singleton sequences

were included to better understand the artifactual and biological sequence variation. The

remaining reads for each sample were sorted by length, then clustered with USEARCH at

a 95% similarity threshold using the ‘centroids’ function in the UCLUST algorithm

(Edgar 2010). This approach assumes that the longest read of a cluster is the most

appropriate and assures that the longest fragment of the full ITS marker will be used for

downstream analyses. The less stringent clustering was opted for our data to compensate

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for a high sequence error rate in the 454 system and to better reflect biological units,

based on preliminary analyses where the suggested 97% threshold (see Blaalid et al.

2013) was applied. The resulting centroid sequences were compared against the NCBI

nucleotide database (Coordinators 2013) using the ‘blastn’ algorithm to obtain their

initial taxonomic affiliations.

Even though the Roche GS FLX+ system is capable of sequencing fragments up to 1000

bp long, the average read length remains between 500-600 bp (Erguner et al. 2015). The

quality of the barcodes becomes an issue towards the end of the read as the base-call

quality drops, and the further away from the start, the more ambiguous the base calling

becomes (Fig. 1). The full ITS region in fungi has an average length of 500 bp in

ascomycetes (Porter and Golding 2011). Based on the available sequences of the studied

fungi, the barcoded ITS region is usually more than 550 bp long, and depending on the

presence and length of the group I intron, it can be more than 1,000 bp long.

Consequently, ITS barcodes of more than 500-600 bp get fewer full-length target reads

with low-quality sequence ends. Furthermore, various sequencing and PCR errors, such

as homopolymer indel errors, CAFIE errors, and chimeras, are frequent and not always

detected using the quality scores (reviewed in, for example, Margulies et al. 2005, Huse

et al. 2007, Gilles et al. 2011, Lücking et al. 2014b).

To obtain a more reliable species reference sequence, the reads of the target taxon that

were concordant with the quality parameters specified above were aligned using the

MAFFT v7.017 automatic algorithm (Katoh and Standley 2013) in the Geneious v7.1.6

platform (Kearse et al. 2012). To gather the relevant sequences from a pool, we used the

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cluster identifications from a previous step. Sequences within the target species (the

expected mycobiont of the observed and determined lichen species) cluster(s)—identified

as the taxon and/or closely related taxon (for closely related species groups) using the

GenBank BLAST function—were gathered and aligned together with reference

sequences from GenBank. Clear outliers in the alignment were removed, the primer

binding sites were trimmed, and the remaining region—including the end of ribosomal

RNA gene 18S, ITS1, 5.8S rRNA gene, ITS2, the beginning of the 28S rRNA gene, and

in some species, also the group I intron at the end of the 18S gene—was designated as the

barcode region for the species. Nucleotide diversity was estimated for alignments with

removed reference sequences using DnaSP v5.10.1 (Librado and Rozas 2009). The

consensus sequence of this region was assigned as the barcode for this species. The

barcode and the representative centroid sequence—the longest read of the biggest cluster

of the taxon—were aligned using the same alignment function in MAFFT, to estimate

sequence similarity and the quantity of indels and nucleotide differences. Using the

consensus sequence approach allowed us to ignore much of the random noise within

sequences, but it is dependent on the accuracy of a given alignment. Alternatively to

MAFFT, we applied the PaPaRa alignment (Berger and Stamatakis 2011) to better

account for erroneous insertions. Finally, however, PaPaRa alignments were not used due

to multiple reasons, discussed and exemplified in the online supplementary Data S1.

We tested the identification of the generated barcodes using the NCBI nucleotide

database, currently the most complete database for lichen-forming fungi. The barcodes

were compared against the database using the ‘megaBLAST’ function in GenBank

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(http://www.ncbi.nlm.nih.gov/genbank/; Accessed 11 January 2015; Madden 2002). To

evaluate the success of specimen identification using DNA barcoding we only counted

the identity of the best match in GenBank BLAST, ignoring the sequence similarity since

no singe meaningful threshold can be applied over the species set, and for many of the

taxa, too little or no information is known for accurate threshold estimation. We

compared the morphological species determination with the best match (= with the

highest bit score) from the barcode sequence megaBLAST search and recorded for each

specimen if the identification via DNA barcoding resulted in concordant results at the

species or the genus level (= correct species / = correct genus but different species or

species not present in the database), divergent (= different genus and species), or neutral

results (= unidentified or uncultured fungus). In cases where the hypothesized identity

differed from the GenBank match, or the similarity between the GenBank sequences and

our sequence was less than 97% (following Blaalid et al. 2013), a phylogeny-based

identification was used. To achieve this, available closely-related representative ITS

sequences of the same genus or species group (depending on the known information of

the species phylogeny) were aligned with the barcode using the program MAFFT v7

(Katoh and Standley 2013), where the G-INS-i alignment algorithm (Katoh and Toh

2008) with ‘1PAM / K=2’ scoring matrix was set. The alignments of ITS sequences were

analyzed using a maximum likelihood (ML) criterion in the program RAxML v7.3.1

(Stamatakis 2006) where the evolutionary model was set to GTRGAMMA, and node

support was assessed using 1,000 "fastbootstrap" replicates (Stamatakis et al. 2008).

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Where distinct nucleotide variation—possibly representing intragenomic variation of ITS

sequences or a mixture of individuals of the same or closely related species—was noted,

the target species alignments were studied carefully, and different ITS version

frequencies were counted. In cases where (a) less-dominant version(s) of ITS was/were

higher in frequency than 10% of the target reads, consensus barcode(s) for the less-

dominant versions were also generated. The most frequent barcode version was assigned

as the primary barcode for the specimen. The different barcode versions were aligned

using the MAFFT v7.017 automatic algorithm (Katoh and Standley 2013), and sequence

variation, nucleotide diversity, and distances (p-distances, with indels treated as missing

data with pairwise deletion) were estimated using DnaSP v5.10.1 (Librado and Rozas

2009) and MEGA5 (Tamura et al. 2011). More distant barcodes of a sample—possibly

resulting from a mixture of closely related species—were aligned with closely related

representative ITS sequences (for the species list and references see Table S1 in online

supplementary material), and phylogenetic trees were constructed using the ML approach

executed with RAxML v7.3.1 as described above. In some samples, unalignable, up to

ten-bp-long regions were detected. Since these regions were usually within or after GC-

rich areas, we suspected a problematic PCR accompanied by CAFIE errors, rather than

genuine mutations (Dutton et al. 1993). A known issue for GC-rich islands is knot

formations in the RNA fold. The RNA secondary structure for such problematic regions

was estimated using RNAstructure web servers (available at:

http://rna.urmc.rochester.edu/RNAstructureWeb; accessed 18 November 2015) utilizing

the default parameters (Bellaousov et al. 2013).

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Results

The sequencing of 100 lichens resulted in 128,449 reads. The number of reads per sample

varied between 207 and 5,473, with an average of 1,285. A general overview of

sequencing reads is given in Fig. 1. Through quality sorting and chimera checking, on

average 21% of the reads were removed, varying from 9% to 57% among samples.

Clustering of reads at 95% resulted in an average of 88 clusters per sample (minimum –

mean±standard deviation – maximum; 5 – 88±57 – 231). Despite conservative quality

sorting, high nucleotide variation per sample was present in the data. While a high

proportion of variation resulted from contaminant fungi within samples, significant

nucleotide variation within the target taxon is also present (Table 2). The mean number of

clusters per target species was 8 (0 – 8±7 – 32), and the average nucleotide diversity

within a target was 0.01128±0.01862. The pairwise identity between the consensus

sequence (barcode) and centroid sequence of the biggest cluster was on average 98.5%,

with 9.65 as the mean number of differences per sequence pair. Comparing centroid

sequences with consensus barcodes revealed a mean difference of 1.46%. About 90% of

the differences were insertions (69%) and deletions (21%) that were especially prominent

towards the end of the sequences, while the rest were nucleotide substitutions or CAFIE

errors.

From one hundred samples, we were able to recover the fungal ITS sequence of the

lichen mycobiont for all sequenced species except one. Fuscidea arboricola sequences

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were not recovered in its sequence pool. Full barcodes, including the end of 18S rRNA,

ITS1, 5.8S rRNA, ITS2, and the beginning 28S rRNA, were generated for all species,

except for the barcode of Anaptychia crinalis, which remained incomplete, with a partly

missing ITS1 sequence due to two long group I introns towards the end of 18S rDNA

(altogether 512 bp). To recover the end of the barcode, chimeric sequences without the

introns were used. Introns at the end of 18S rDNA were identified in 37 target taxa

(Table 1). The length of the intron varied from 60 to 594 bp. The primary barcode

sequences have been deposited in the NCBI and BOLD databases under the accession

codes as indicated in the Table 1. All project data—specimen voucher info, photographs,

the complete list of the barcode sequences (including the alternative versions), alignment

matrices, phylogenetic trees—can be accessed though the PlutoF cloud database under a

project “Barcoding Swiss lichens using 454 pyrosequencing”

(https://plutof.ut.ee/#/study/view/31890).

The barcodes from the targeted lichenized fungi were, in most cases, morphologically

and molecularly identified to the same species (n=69) or at least to the same genus (n=18)

using the NCBI nucleotide database as reference (Fig. 2; for details see online

supplementary material Table S2). Nine of the species correctly identified using

GenBank BLAST showed less than 97% similarity, which could indicate wider ITS

genetic variation of the species or even the presence of cryptic species. ITS sequences of

14 of the studied species were previously not available in GenBank, this being one of the

reasons for imprecise identifications. For eight species, the best match in GenBank was

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an “uncultured fungus”, originating from environmental metabarcoding studies where

morphology-based identifications and taxonomic assignments are often not performed.

Nine samples were identified to the same genus but to a different species than that based

on morphology, and one sample to a different genus based on a high identity score

(≥97%). These species were: Anaptychia crinalis (identified as Anaptychia ciliaris,

98.0%), Bryoria capillaris (identified as Bryoria fuscescens, 98.8%), Lecanora impudens

(identified as Lecanora allophana, 99.2%), Loxospora elatina (identified as Loxospora

ochrophaea, 99.7%), Parmelia sulcata (identified as Myelochroa auruleanta, 99.7%),

Parmotrema perlatum (identified as Parmotrema crinitum, 98.7%), and Usnea barbata

and U. substerilis (identified as Usnea intermedia/rigida, >98.0%). We found that these

misidentifications had three main causes – (a) labelling or identification mistakes in the

NCBI nucleotide database, as in the case of Parmelia sulcata; (b) the incomplete

reference database with missing species or partial sequences, as in the case of Anaptychia

crinalis; (c) biological reasons, such as low genetic variation in the ITS region (e.g.,

Bryoria capillaris, Parmotrema perlatum, Usnea barbata, and U. substerilis).

Besides the expected mycobiont, many other fungi were recovered within our samples.

For 22 samples, the most-sequenced fungus was not the expected mycobiont but another

fungus instead. Many of these fungi were identified as lichen-associated (facultative

parasites/lichenicolous) or plant-associated (epi-or endophytes). However, the lichen-

associated fungal diversity within our sequenced lichens is not in the scope of the present

study and will not be discussed further.

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We studied the nucleotide variation of samples where (a) less frequent version(s) of ITS

constituted more than 10% of the expected mycobiont reads. Multiple barcodes per

species were generated for 22 samples (Table 3; for the full list of barcodes of such

samples refer to the online supplementary Table S3). The number of generated barcodes,

and distances between them, varied considerably from species to species. Barcode

versions with only indels as differences showed zero distance (Buellia arborea, Cladonia

digitata, Hypotrachyna laevigata). However, since the indels in these species were

present in the non-coding regions (group I intron, ITS1, or ITS2), they cannot be

completely ruled out as genuine mutations. In Lecanora subcarpinea, Lepraria lobificans,

and Menegazzia terebrata, a poorly alignable, up to 10-bp-long region was detected in

ITS1. These regions were positioned within or at the end of sequence regions with high G

+ C content (GC%), where formations of strong knots in RNA folds are likely. In

Lecanora subcaripinea, a region of six ambiguous bases occurs at the end of a 38-bp

region of 79.5% GC content. In Lepraria lobificans, five ambiguous bases occur at the

end of a 44-bp region with a GC% of 82.6%. In Menegazzia terebrata, in a 60-bp region,

with a GC% of 86.0%, an ambiguous region of nine bases occurs within the sequencing

reads. RNA secondary structure analyses revealed that the sequences in these areas form

a secondary structure knot with probabilities of >95% for Lecanora, >99% for Lepraria,

and >99% for Menegazzia. Online supplementary Figure S1 shows, by way of example,

the ITS1 RNA secondary structure of the primary barcode version and ambiguous bases

of this region in Menegazzia terebrata barcodes.

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The dominant ITS version of Physica adscendens is highly similar to sequences of this

species (99%; online supplementary material Table S2), while the second, less-frequent

version includes a high number of mostly unidirectional transitional mutations and is of

low similarity to Physcia adscendens sequences (87%). However, no better alignment

with any other sequence in GenBank was found. Altogether, 92 transitional mutations are

present among the two ITS versions (4 in 18S, 32 in the group I intron, 22 in ITS1, 9 in

5.8S, 18 in ITS2, and 7 in 28S). These mutations are almost exclusively unidirectional,

being mainly G⇒A and C⇒T.

Besides artificial nucleotide variation caused by PCR/sequencing errors, nucleotide

variation can occur for biological reasons, such as: (1) incomplete concerted evolution

within the ITS and (2) intraspecific variation. For 13 species, distinct nucleotide variation

could not be explained by PCR or CAFIE errors only (Table 3). By comparing the

variation within the reads of the mycobiont with available Sanger sequences from

GenBank of the same species (where available), we also found the same variable bases in

Sanger sequences in eight species. Therefore, it seems probable that intragenomic and/or

intra-mycelial (i.e. allelic heterozygosity) variation is present at least in the following

samples: #8 Bryoria capillaris, #55 Lepraria rigidula, #64 Melanohalea exasperata, #70

Parmelia sulcata, #79 Physcia adscendens, #95 Usnea intermedia, and #96 Usnea

lapponica. For eight species, such comparisons could not be made due to a lack of Sanger

sequences. Sequence variation possibly resulting from intragenomic or intra-mycelial

variation were additionally detected in #6 Bacidina arnoldiana, #12 Chaenotheca cf.

stemonea, #19 Fellhanera bouteillei, #30 Lecania cf. cyrtella, #50 Lecidella scabra, and

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#51 Lecidella sp., of which the first three are seemingly also accompanied with

intraspecific variation (Fig. 3.-5.). The number of barcodes, however, might not

necessarily represent the true intragenomic variation of a species. For example, seven

variable nucleotide positions were found in Usnea intermedia with no clear segregation

into distinct ITS types. In ITS1, three mutation positions (G⇔C, T⇔C, T⇔C) generated

three types, while in ITS2, four mutation positions (T⇔C, G<⇔A, A⇔C, T⇔A)

generated four types, of which three are dominant. These types were combined with each,

generating seven different barcode versions. Incomplete concerted evolution within ITS

is therefore possible. However, inflation of ITS types should also be considered due to

recombination or chimera formation between different ITS1 and ITS2 versions. The more

similar the parents, the harder it is to detect and identify chimeras. Therefore, it could just

as well be possible that fewer than seven different ITS versions are natural, while others

are artificial formations. The number of barcodes can also be inflated by systematic

CAFIE errors, which we have tried to account for when interpreting the reasons of base

variation of some species (e.g. #69 Parmelia saxatilis). For the full list of the alternative

barcodes and their hypothetical origin refer to the online supplementary Table S3.

The highest number of variable sites, as well as the greatest genetic distance between

barcodes, occurred in samples where multiple distinct lineages, probably representing

different species, were identified in the pool. These samples were crustose species

Bacidina arnoldiana aggr., Chaenotheca cf. stemonea, and Fellhanera bouteillei.

In Bacidina arnoldiana aggr. (sample #6), five different ITS versions from two

closely related Bacidina arnoldiana clades were identified (Fig. 4). The morphologically

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homogenous, yet variable species B. arnoldiana is therefore polyphyletic, comprising in

itself multiple lineages and possibly other taxa with unresolved taxonomy. The five ITS

versions from Bacidina arnoldiana belong in two major clusters, ‘B. arnoldiana 1’ and

‘B. arnoldiana 3’, and group together with other B. arnoldiana sequences. ‘B. arnoldiana

2’ includes only GenBank data and is more closely related to ‘B. arnoldiana 3’. Four ITS

versions cluster within ‘B. arnoldiana 1’, of which two are dominant, A1 and B1. These

are also almost equally present in the sequence pool (A1 in 65 reads, 42.6%; B1 in 45

reads, 41.7%). The subversions A1 and B1 have a pairwise identity of only 93.8%, and

based on genetic distances, clade ‘B. arnoldiana 1’ could therefore include cryptic

species. However, no final conclusions can be made of our limited sample size and data

based on ITS markers only.

In Chaenotheca cf. stemonea (sample #12), sequences from two Chaenotheca

“species” were present (Fig. 5) – C. cf. stemonea and C. trichialis-xyloxena group. The

first includes four highly similar (>98%) barcodes differing in multiple mutations and in

intron presence/absence towards the end of the 18S rDNA. The Chaenotheca trichialis-

xylogena group includes six barcodes that cluster further into three groups: versions B

together with a subgroup of C. trichialis, version A1 clusters within C. xyloxena, and

version A2 with a second subgroup of C. trichialis at the base of the clade. The distances

within subversions B are low (pairwise identity >98%), while between subversions B, A1,

and A2, distances are larger (pairwise identities between 96–97%).

Fellhanera bouteillei (sample #19) includes three ITS versions, of which two

highly similar types (identity 99%), A1 and A2, are dominant, while the third, less-

frequent version B is only present in three sequences. The less-dominant version is,

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however, significant as it represents the clade of Fellhanera beouteillei s.str. together

with sequences available in GenBank (Fig. 6). The dominant types A1 and A2 cluster

distantly outside of Fellhanera bouteillei and could represent a different species (pairwise

identity between barcode versions A1 and B is 89%).

Discussion

Barcoding lichens

In the scope of this study, we ‘barcoded’ 99 out of 100 lichen mycobiont species using

454 pyrosequencing. Good success in generating barcodes shows the high potential of

this method, especially concerning crustose lichens, which can be difficult to sequence

with the Sanger technique. To our knowledge, this is the first attempt to apply

pyrosequencing to lichen barcoding to such an extent.

The success of DNA-based identification depends greatly on the reference database, both

in the quality and quantity of the barcodes included. Purely DNA-based identification of

lichens—without considering morphological and chemical characters—is far from reach,

especially regarding crustose lichens and samples from poorly-investigated regions due to

missing references and unknown diversity (Orock et al. 2012). Within the present study,

we generated ITS barcodes for 12 described species whose sequences were previously

not available in GenBank and for two morphologically newly characterized specimens

(#41 Lecanora sp., #51 Lecidella sp.). Multiple species showed low intraspecific ITS

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sequence similarity to other available sequences in GenBank (e.g. #10 Bunodophoron

melanocarpum, #12 Chaenotheca cf. stemonea, #19 Fellhanera bouteillei, #30 Lecania cf.

cyrtella, #66 Micarea cinerea) or a high similarity to a different taxon (e.g. #8 Bryoria

capillaris, #13−16 Cladonia species, #36 Lecanora impudens, #47 Lecidella cf.

elaeochroma, #47 Lecidella cf. leprothalla, #58/59 Loxospora elatina, #74 Parmotrema

perlatum, #91/92 Usnea barbata; refer to the Table S2 and to the project in PlutoF for

further information). Before specimen identification via DNA barcoding can be

confidently applied, taxonomic studies in these groups are needed to confirm the species

monophyly or, in cases of non-monophyly, propose segregation of a taxon into multiple

species. However, our results also suggest that the NCBI nucleotide database, currently

the most complete database for lichen-forming fungi, could be used as a reference

database to identify common species, as the majority of the analyzed lichens were

identified correctly to the species or, at least, to the genus level.

When generating barcodes, we applied a rather conservative approach by generating

consensus sequences from target taxon alignments, rather than using centroid sequences.

In most cases, centroid reads were sufficiently accurate for correct specimen

identification to a species level. However, when producing a barcode database, even a

few errors can cause systemic mistakes in future identifications. Even though it is more

time consuming, this approach helps to better identify and avoid mistakes, such as those

caused by sequencing, undetected chimeras, and multiple ITS copies. However, the

propagation of errors cannot be avoided completely; they can originate directly from PCR

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amplification or be hindered by systematic sequencing errors, independent from data

processing methods.

Reasons for nucleotide variation

The source of nucleotide variation within a species can be the PCR, the sequencing, or be

of biological origin. While the first two sources generate artifactual variation, biological

origins represent genuine mutations.

We identified three main sources of artifactual variation in our samples.

(1) Chimeras are hybrid products of PCR formed by different template sequences.

Undetected chimeras lead to overestimated richness, artificial entities, and incorrect

taxonomic identifications. It has been shown that chimera formation is especially strong

in regions with alternating patterns between conserved and less-conserved regions, such

as 16S rRNA genes (Shin et al. 2014). In the ITS barcodes—including conserved 18S,

5.8S, and 28S rRNA exons, alternating with variable ITS1 and ITS2 regions—frequent

chimeras with switched ITS1 or ITS2 regions were observed (data not shown). Reads

with group I intron towards the end of 18S rRNA gene often included chimeras where the

intron had been excluded. Longer templates require longer extension times, which can

contribute to chimera formation (Haas et al. 2011, Shin et al. 2014). Chimera detection is

reasonably applicable in a closed system, where recombining gene variants are known.

While the vast majority of fungal diversity is still unknown, chimeras should be

considered as a real issue in diversity analyses where multiple templates are present in the

pool (Sharifian 2010).

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(2) High content of the nucleotides guanine and cytosine can impede

amplification and result in low-quality sequencing with ambiguous bases. This difficulty

is associated with poor denaturation of regions with high GC concentration, while

template secondary structure hinders the access of PCR primers and enzyme work at

elongation (Dutton et al. 1993). Even though high-temperature denaturation (98°C) and

high-fidelity heat-stable polymerase were used, the formation of strong knots in RNA

structure that impede correct amplification cannot be ruled out and might have affected

the ambiguous regions in the species Lecanora subcarpinea, Lepraria lobificans, and

Menegazzia terebrata.

(3) 454 pyrosequencing is notorious for its high indel error rate in homopolymeric

regions and carry-forward-incomplete-extension (CAFIE) errors (Margulies et al. 2005,

Huse et al. 2007, Gilles et al. 2011). Incomplete extension creates shorter homopolymers

due to insufficient dNTPs. Carry-forward errors are the result of incomplete dNTP

flushing, which then causes a nucleotide from the end of the homoploymer to be read

some bases later (e.g. a true sequence AAAATCG, can be read as AAATCGA). A

comparison between the consensus barcodes and a representative read (the centroid

sequence of the biggest cluster) showed a mean difference of 1.46%. About 90% of the

errors were indels. These were most prominent in homopolymeric regions and were

especially frequent towards the end of the sequence, while the rest were nucleotide

substitutions. Considering that in closely related species complexes, less than 2%

variation could already result in a different identification, the necessity to reliably

separate artificial from genuine variation becomes clear.

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Nucleotide variation in the ITS can represent genuine mutations when a species is

characterized by incomplete concerted evolution (Feliner and Rosselló 2007). We have

highlighted 12 species in Table 3 where detected nucleotide variation could represent

intragenomic variation within ITS, or alternatively, allelic heterozygosity caused by

differing nuclei within a single mycelium (Huang et al. 2010, Hyde et al. 2013). The

latter is more likely when only two primary allele variants in approximatly equal ratios

are observed (Linder et al. 2013). Two more or less equally represented ITS paralogs

were found in #1 Alectoria sarmentosa, #6 Bacidina arnoldiana, #8 Bryoria capillaris,

#43 Lecanora subcarpinea, and #70 Parmelia sulcata, while one dominant ITS version

together with relatively rare haplotypes was found in #5 Bacidia vermifera, #12

Chaenotheca cf. stemonea, #19 Fellhanera bouteillei, #30 Lecania cf. cyrtella, #50

Lecidella scabra, #51 Lecidella sp., #55 Lepraria rigidula, #64 Melanohalea exasperata,

#95 Usnea intermedia, and #96 Usnea lapponica. The latter list includes representatives

from a closely related species group in the genus Usnea (sect. Usnea; Mark et al. 2016),

where low genetic variation and possible rapid radiation of species have been

characterized (Truong et al. 2013, Kraichak et al. 2015,). However, four other Usnea

specimens from this closely related group were also included in our study, where such

nucleotide variation was not detected (#91/92 U. barbata, #94 U. intermedia, and #97 U.

substerilis). Whether or not intragenomic variation can be detected via pyrosequencing

likely also depends on the random effects of PCR and the proportions of different ITS

copies in a genome.

Xu et al. (2009) demonstrated a high level of intra-individual polymorphism in rDNA,

including multiple functional genes, putative pseudo genes, and recombinants. They also

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found a systematic bias in the efficiency with which different sequences were amplified.

In Physcia adscendens, a second ITS version with unidirectional transitions from

cytocine to thymine and adenine to guanine was detected. The second ITS version of this

species could represent a rare divergent ITS allele or a pseudogene, propagated to a

higher frequency due to a PCR bias. Ribosomal DNA pseudogenes are characterized by

low stability in the predicted secondary structure, a higher substitution rate, and

deamination-driven stubstitutions (Buckler et al. 1997). A large multigene family of 5S

rRNA, including pseudogenes, has also been identified in other filamentous fungi

(Margolin et al. 1998, Rooney and Ward 2005). A duplication event of the ribosomal

DNA cistron could be a plausible explanation for the detected nucleotide variation in

Physcia adscendens and is in concordance with the findings of Lücking et al. (2012).

Intraspecific variation, resulting from possible lichen chimeras or microcosms—where

diverse communities live mixed and alongside—is illustrated by the phylogenies for three

crustose species. For example, in a single sample of Bacidina, constituting a minute

quantity of lichen soredia, four distinct lineages of Bacidina were identified in a visually

inseparable community. In these species, the problem of distinguishing between intra-

and interspecific variation arises. This variation within a specimen cannot be detected in

Sanger sequencing environmental samples, and this could be one of the reasons for the

taxonomic mess in the Bacidina arnoldiana aggregate, as also illustrated in Figure 4.

Further studies with more data are needed to investigate such phenomena.

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Whatever the reason, nucleotide variation detected through 454 pyrosequencing must be

interpreted with caution, both with respect to the acquired barcode database as well as

answering biological questions. Using other, less error-prone squencing platforms and/or

combining a large number of reads per taxon could help to avoid random sequencing

errors. Sanger references can aid in distinguishing between CAFIE errors and biological

sequence variation. However, Sanger sequencing may remain insufficient in some cases,

as it is unable to detect intragenomic sequence variation (e.g. to investigate species and

genome evolution) and fails to give useable results in a mixture of templates.

Acknowledgements

We thank Jean-Claude Walser from ETH Zurich Genetic Diversity Centre (GDC) for

help with pyrosequencing data analyses and Microsynth AG for their collaboration. We

also wish to thank the editor and the reviewers for their useful comments, and Curtis

Gautschi for linguistic corrections. This study was funded by the Rectors’ Conference of

the Swiss Universities (CRUS) through the SCIEX-NMSch Scientific Exchange

Programme (project SCIEX-LiCode), FOEN – the Federal Office for the Environment

(grant to Silvia Stofer and CS), and SwissBOL (grant to CS).

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Wörheide, G., Nichols, S.A., and Goldberg, J. 2004. Intragenomic variation of the rDNA

internal transcribed spacers in sponges (Phylum Porifera): implications for

phylogenetic studies. Mol. Phylogen. Evol., 33: 816–830.

Xu, J., Zhang, Q., Xu, X., Wang, Z., and Qi, J. 2009. Intragenomic variability and

pseudogenes of ribosomal DNA in stone flounder Kareius bicoloratus. Mol.

Phylogen. Evol., 52: 157–166.

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Table 1 Studied species with specimen voucher info, the primary barcode length for the sequenced ITS region, the position and length of an intron in

the barcode (if present), and the primary barcode accession numbers in the NCBI and BOLD databases.

# Target taxon Collection data (site, date, ID)

Barcode

length (bp)

Group I intron

length (bp) and

position GenBank # BOLD #

1 Alectoria sarmentosa (Ach.) Ach. CH-Bern; 06.02.2014; LC-064 579 KX132948 LIFU039-16

2 Anaptychia crinalis (Schleich. ex Schaer.)

Vězda

CH-Graubünden; 18.02.2014; LC-071 1067 512 (18-322;

332-538)

KX132954 LIFU045-16

3 Arthrosporum populorum A. Massal. CH-Valais; 06.02.2014; LC-046 586 KX132986 LIFU078-16

4 Bacidia rubella (Hoffm.) A. Massal. CH-Valais; 06.02.2014; LC-041 774 216 (26-241) KX132984 LIFU076-16

5 Bacidia vermifera (Nyl.) Th. Fr. CH-Bern; 04.07.2012; RE-515-19 578 KX132992 LIFU084-16

6 Bacidina arnoldiana aggr.* CH-Lucerne; 30.03.2011; BC-038-1 583 KX132958 LIFU049-16

7 Bacidina arnoldiana aggr.* CH-Zurich; 15.07.2011; BC-132-1 795 213 (26-238) KX132972 LIFU063-16

8 Bryoria capillaris (Ach.) Brodo & D. Hawksw. CH-Bern; 06.02.2014; LC-058 803 223 (26-248) KX132945 LIFU036-16

9 Buellia arborea Coppins & Tønsberg CH-Obwalden; 13.08.2011; BC-154-2 584 KX132975 LIFU066-16

10 Bunodophoron melanocarpum (Sw.) Wedin CH-Bern; 06.02.2014; LC-065 584 KX132949 LIFU040-16

11 Cetrelia monachorum (Zahlbr.) W. L. Culb. &

C. F. Culb.

CH-Lucerne; 22.02.2014; KM-03-07 577 KX132924 LIFU015-16

12 Chaenotheca cf. stemonea (Ach.) Müll. Arg. CH-Neuchâtel; 13.05.2011; BC-087-3 571 KX133006 LIFU098-16

13 Cladonia chlorophaea (Flörke ex Sommerf.)

Spreng.

CH-Zurich; 01.02.2014; KM-01-8 872 227 (26-252) KX132914 LIFU005-16

14 Cladonia coniocraea (Flörke) Spreng. CH-Bern; 06.02.2014; LC-068 868 226 (26-251) KX132951 LIFU042-16

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15 Cladonia digitata (L.) Hoffm. CH-Bern; 06.02.2014; LC-067 650 KX132950 LIFU041-16

16 Cladonia squamosa (Scop.) Hoffm. CH-Bern; 06.02.2014; LC-069 873 227 (26-252) KX132952 LIFU043-16

17 Evernia divaricata (L.) Ach. CH-Bern; 06.02.2014; LC-057 585 KX132944 LIFU035-16

18 Evernia prunastri (L.) Ach. CH-Graubünden; 18.02.2014; LC-070 578 KX132953 LIFU044-16

19 Fellhanera bouteillei (Desm.) Vězda CH-Lucerne; 03.2014; LC-118 609 KX132990 LIFU082-16

20 Flavoparmelia caperata (L.) Hale CH-Zurich; 15.02.2014; KM-02-02 1176 594 (26-619) KX132916 LIFU007-16

21 Frutidella pullata (Norman) Schmull CH-Bern; 17.05.2011; BC-115-2 828 232 (26-257) KX132970 LIFU061-16

22 Fuscidea arboricola Coppins & Tønsberg CH-Vaud; 10.03.2007; BC-185-5 n.a. KX132962 LIFU053-16

23 Fuscidea pusilla Tønsberg CH-St. Gallen; 20.04.2011; BC-063-2 542 1LIFU072-16

24 Hyperphyscia adglutinata (Flörke) H.

Mayrhofer & Poelt

CH-St. Gallen; 11.04.2011; BC-055-3 795 228 (26-253) KX132959 LIFU050-16

25 Hypocenomyce scalaris (Ach. ex Lilj.) M.

Choisy

CH-Valais; 06.02.2014; LC-016 564 KX132982 LIFU074-16

26 Hypogymnia farinacea Zopf CH-Bern; 06.02.2014; LC-062 580 KX132947 LIFU038-16

27 Hypogymnia physodes (L.) Nyl. CH-Valais; 06.02.2014; LC-039 810 228 (26-253) KX132937 LIFU028-16

28 Hypogymnia tubulosa (Schaer.) Hav. CH-Jura; 01.03.2014; LC-107 797 220 (26-245) KX132956 LIFU047-16

29 Hypotrachyna laevigata (Sm.) Hale CH-Lucerne; 22.02.2014; KM-03-05 582 KX132922 LIFU013-16

30 Lecania cf. cyrtella (Ach.) Th. Fr. CH-Valais; 06.02.2014; LC-023 801 223 (26-248) KX132983 LIFU075-16

31 Lecanora albella (Pers.) Ach. CH-Bern; 17.05.2011; BC-118-1 590 KX133002 LIFU094-16

32 Lecanora allophana f. sorediata Nyl. CH-Valais; 07.05.2011; BC-72-3 813 223 (26-248) KX133001 LIFU093-16

33 Lecanora argentata/subrugosa CH-Bern; 17.05.2011; BC-118-2 598 KX133003 LIFU095-16

34 Lecanora carpinea (L.) Vain. CH-Valais; 16.04.2011; BC-58-3 840 248 (26-273) KX132999 LIFU091-16

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35 Lecanora horiza (Ach.) Röhl. CH-St. Gallen; 11.04.2011; BC-54-3 591 KX132998 LIFU090-16

36 Lecanora impudens Degel. CH-St. Gallen; 11.04.2011; BC-49-1 813 223 (26-248) KX132996 LIFU088-16

37 Lecanora muralis (Schreb.) Rabenh. CH-Valais; 06.02.2014; LC-045 590 KX132985 LIFU077-16

38 Lecanora praesistens Nyl. CH-Bern; 20.05.2013; MG-076-49 833 231 (26-256) KX132991 LIFU083-16

39 Lecanora pulicaris (Pers.) Ach. CH-Jura; 01.03.2014; LC-101 831 226 (26-251) KX132989 LIFU081-16

40 Lecanora saligna (Schrad.) Zahlbr. CH-Glarus; 11.04.2011; BC-47-1 597 KX132995 LIFU087-16

41 Lecanora sp.* CH-Bern; 22.05.2011; BC-027-1 796 206 (26-231) KX133005 LIFU097-16

42 Lecanora strobilina aggr.* CH-Glarus; 11.04.2011; BC-52-1 590 KX132997 LIFU089-16

43 Lecanora subcarpinea Szatala CH-Bern; 01.03.2014; LC-090 595 KX132988 LIFU080-16

44 Lecanora varia (Hoffm.) Ach. CH-Zurich; 16.04.2011; BC-60-5 808 218 (26-243) KX133000 LIFU092-16

45 Lecidella albida Hafellner CH-St. Gallen; 20.04.2011; BC-067-3 590 KX132987 LIFU079-16

46 Lecidella cf. elaeochroma (Ach.) M. Choisy CH-Graubünden; 18.02.2014; LC-072 592 KX132966 LIFU057-16

47 Lecidella cf. leprothalla (Zahlbr.) Knoph &

Leuckert

CH-Neuchâtel; 13.05.2011; BC-077-2 599 KX132965 LIFU056-16

48 Lecidella flavosorediata (Vězda) Hertel &

Leuckert

CH-Valais; 08.05.2011; BC-074-14 599 KX132994 LIFU086-16

49 Lecidella flavosorediata (Vězda) Hertel &

Leuckert

CH-Bern; 01.03.2014; LC-091 597 KX132960 LIFU051-16

50 Lecidella scabra (Taylor) Hertel & Leuckert CH-St. Gallen; 11.04.2011; BC-055-4 595 KX132993 LIFU085-16

51 Lecidella sp.* CH-Bern; 01.03.2014; LC-088 596 KX132978 LIFU069-16

52 Lepraria elobata Tønsberg CH-Obwalden; 13.08.2011; BC-158-2 604 KX132979 LIFU070-16

53 Lepraria jackii Tønsberg CH-Obwalden; 13.08.2011; BC-156-3 601 KX132974 LIFU065-16

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54 Lepraria lobificans Nyl. CH-Zurich; 18.07.2011; BC-133-3 564 KX132961 LIFU052-16

55 Lepraria rigidula (B. de Lesd.) Tønsberg CH-Valais; 16.04.2011; BC-056-2 598 KX132973 LIFU064-16

56 Lepraria vouauxii (Hue) R. C. Harris CH-Zurich; 18.07.2011; BC-133-2 601 KX132927 LIFU018-16

57 Letharia vulpina (L.) Hue CH-Valais; 06.02.2014; LC-006 581 KX132976 LIFU067-16

58 Loxospora elatina (Ach.) A. Massal. CH-Obwalden; 13.08.2011; BC-155-5 564 KX133004 LIFU096-16

59 Loxospora elatina (Ach.) A. Massal. CH-Obwalden; 19.08.2011; BC-161-5 564 KX132969 LIFU060-16

60 Megalaria pulverea (Borrer) Hafellner & E.

Schreiner

CH-Bern; 17.05.2011; BC-113-3 569 KX132913 LIFU004-16

61 Melanelixia fuliginosa subsp. glabratula

(Lamy) J. R. Laundon

CH-Zurich; 01.02.2014; KM-01-6 807 229 (26-254) KX132939 LIFU030-16

62 Melanelixia glabra (Schaer.) O. Blanco, A.

Crespo, Divakar, Essl., D. Hawksw. & Lumbsch


63 Melanelixia subargentifera (Nyl.) O. Blanco, A.

Crespo, Divakar, Essl., D. Hawksw. & Lumbsch


64 Melanohalea exasperata (De Not) O. Blanco,

A. Crespo, Divakar, Essl., D. Hawksw. &

Lumbsch

CH-Valais; 06.02.2014; LC-028 801 220 (26-245) KX132943 LIFU034-16

65 Menegazzia terebrata (Hoffm.) A. Massal. CH-Bern; 06.02.2014; LC-054 583 KX132981 LIFU073-16

66 Micarea cinerea (Schaer.) Hedl. CH-Lucerne; 22.02.2014; KM-03-03 571 KX132957 LIFU048-16

67 Micarea xanthonica Coppins & Tønsberg CH-St. Gallen; 15.03.2011; BC-015-6 755 192 (18-209) KX132971 LIFU062-16

68 Mycoblastus sanguinarius (L.) Norman CH-Bern; 17.05.2011; BC-119-4 596 KX132946 LIFU037-16

69 Parmelia saxatilis (L.) Ach. CH-Bern; 06.02.2014; LC-060 583 KX132926 LIFU017-16

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70 Parmelia sulcata Taylor CH-Valais; 06.02.2014; LC-004 593 KX132912 LIFU003-16

71 Parmelina tiliacea (Hoffm.) Hale CH-Zurich; 01.02.2014; KM-01-4A 578 KX132918 LIFU009-16

72 Parmeliopsis ambigua (Wulfen) Nyl. CH-Valais; 06.02.2014; LC-002 581 KX132923 LIFU014-16

73 Parmotrema crinitum (Ach.) M. Choisy CH-Lucerne; 22.02.2014; KM-03-06 609 KX132915 LIFU006-16

74 Parmotrema perlatum (Huds.) M. Choisy CH-Zurich; 14.02.2014; KM-02-01 610 KX132941 LIFU032-16

75 Phaeophyscia ciliata (Hoffm.) Moberg CH-Valais; 06.02.2014; LC-050 998 418 (18-224;

233-443)

KX132942 LIFU033-16

76 Phaeophyscia orbicularis (Neck.) Moberg CH-Valais; 06.02.2014; LC-051 992 418 (18-224;

233-443)

KX132940 LIFU031-16

77 Phaeophyscia poeltii (Frey) Clauzade & Cl.

Roux


78 Phlyctis argena (Spreng.) Flot. CH-St. Gallen; 20.04.2011; BC-065-1 924 351 (18-368) KX132910 LIFU001-16

79 Physcia adscendens (Fr.) H. Olivier CH-Zurich; 01.02.2014; KM-01-2B 784 222 (26-247) KX132934 LIFU025-16

80 Physcia aipolia (Ehrh. ex Humb.) Fürnr. CH-Valais; 06.02.2014; LC-026 783 216 (26-241) KX132933 LIFU024-16

81 Physconia distorta (With.) J. R. Laundon CH-Valais; 06.02.2014; LC-021 972 402 (18-217;

226-427)

KX132967 LIFU058-16

82 Placynthiella dasaea (Stirt.) Tønsberg CH-Neuchâtel; 13.05.2011; BC-084-1 900 335 (26-360) KX132911 LIFU002-16

83 Pleurosticta acetabulum (Neck.) Elix &

Lumbsch

CH-Zurich; 01.02.2014; KM-01-3A 577 KX132925 LIFU016-16

84 Pseudevernia furfuracea (L.) Zopf CH-Valais; 06.02.2014; LC-001 574 KX132917 LIFU008-16

85 Punctelia jeckeri (Roum.) Kalb CH-Zurich; 15.02.2014; KM-02-03 901 336 (26-361) KX132977 LIFU068-16

86 Pycnora sorophora (Vain.) Hafellner CH-Obwalden; 13.08.2011; BC-156-1 565 KX132955 LIFU046-16

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Note: The morphology and chemistry of the undescribed taxa marked with * are discussed in text. 1No sequence, specimen data only.

87 Ramalina pollinaria (Westr.) Ach. CH-Jura; 01.03.2014; LC-093 770 215 (26-240) KX133007 LIFU099-16

88 Scoliciosporum umbrinum (Ach.) Arnold CH-Valais; 06.02.2014; LC-024 598 KX133008 LIFU100-16

89 Scoliciosporum umbrinum (Ach.) Arnold CH-Bern; 16.05.2013; MG-114-3C 598 KX132936 LIFU027-16

90 Tuckermannopsis chlorophylla (Willd.) Hale CH-Valais; 06.02.2014; LC-032 560 KX132929 LIFU020-16

91 Usnea barbata (L.) Weber ex F. H. Wigg. CH-Valais; 06.02.2014; LC-011 578 KX132932 LIFU023-16

92 Usnea barbata (L.) Weber ex F. H. Wigg. CH-Valais; 06.02.2014; LC-019 578 KX132921 LIFU012-16

93 Usnea ceratina Ach. CH-Lucerne; 22.02.2014; KM-03-04 578 KX132919 LIFU010-16

94 Usnea intermedia (A. Massal.) Jatta CH-Lucerne; 22.02.2014; KM-03-01 578 KX132920 LIFU011-16

95 Usnea intermedia (A. Massal.) Jatta CH-Lucerne; 22.02.2014; KM-03-02 578 KX132930 LIFU021-16

96 Usnea lapponica Vain. CH-Valais; 06.02.2014; LC-013 579 KX132928 LIFU019-16

97 Usnea substerilis Motyka CH-Valais; 06.02.2014; LC-009 577 KX132968 LIFU059-16

98 Violella fucata (Stirt.) T. Sprib. CH-Bern; 17.05.2011; BC-109-4 834 235 (26-260) KX132980 LIFU071-16

99 Violella fucata (Stirt.) T. Sprib. CH-Obwalden; 13.08.2011; BC-159-4 592 KX132931 LIFU022-16

100 Vulpicida pinastri (Scop.) J.-E. Mattsson & M.

J. Lai


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Table 2 Pyrosequencing results with nucleotide variation in the studied samples and comparison of consensus barcodes with representative sequencing

reads for each sample.

Comparison between consensus barcode and

representative centroid

# Species Reads Clusters1

Reads of target

taxon (%)

Target

clusters1

Nucleotide

diversity ππππ

Pairwise

identity (%)

No of base

differences (%) TS / TV / Ind2

1 Alectoria sarmentosa 582 28 463 (79.6) 1 0.00385 97.2 14 (2.4) 1 / 3 / 10

2 Anaptychia crinalis 342 70 52 (15.2) 3 0 98.6 9 (1.4) 0 / 0 / 9

3 Arthrosporum populorum 2937 78 2499 (85.1) 24 0.00433 98.0 12 (2.0) 0 / 0 / 12

4 Bacidia rubella 2194 38 2167 (98.8) 24 0.00643 98.6 11 (1.4) 0 / 0 / 11

5 Bacidia vermifera 4052 195 1813 (44.7) 24 0.00865 97.6 14 (2.4) 0 / 0 / 14

6 Bacidina arnoldiana aggr. 1715 231 116 (6.8) 8 0.03161 98.6 8 (1.4) 0 / 1 / 7

7 Bacidina arnoldiana aggr. 1406 185 100 (7.1) 4 0.01275 99.0 8 (1.0) 0 / 0 / 8

8 Bryoria capillaris 636 45 424 (66.7) 4 0.00811 98.5 12 (0.5) 2 / 2 / 8

9 Buellia arborea 891 98 281 (31.5) 8 0.00902 97.6 14 (2.4) 0 / 0 / 14

10 Bunodophoron melanocarpum 128 19 82 (64.1) 3 0.02226 98.0 12 (2.0) 0 / 0 / 12

11 Cetrelia monachorum 1903 93 1644 (86.4) 32 0.00487 97.6 14 (2.4) 0 / 1 / 13

12 Chaenotheca cf. stemonea 542 94 156 (28.8) 8 0.08548 99.3 4 (0.7) 2 / 0 / 2

13 Cladonia chlorophaea 1159 131 485 (41.8) 1 0.00099 98.9 10 (1.1) 0 / 0 / 10

14 Cladonia coniocraea 425 52 241 (56.7) 1 0.00274 98.9 10 (1.2) 0 / 0 / 10

15 Cladonia digitata 718 69 582 (81.1) 6 0.00195 97.5 16 (2.5) 0 / 2 / 14

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16 Cladonia squamosa 291 82 159 (54.6) 1 0.0022 98.9 10 (1.1) 1 / 0 / 9

17 Evernia divaricata 472 48 366 (77.5) 5 0.0014 99.2 5 (0.8) 0 / 0 / 5

18 Evernia prunastri 382 55 112 (29.3) 8 0.00118 99.0 6 (1.0) 0 / 0 / 6

19 Fellhanera bouteillei 422 78 159 (37.7) 12 0.02398 99.7 2 (0.3) 0 / 0 / 2

20 Flavoparmelia caperata 553 109 42 (7.6) 9 0.00442 97.9 19 (2.1) 0 / 1 / 18

21 Frutidella pullata 841 161 31 (3.7) 3 0.00283 98.9 9 (1.1) 1 / 0 / 8

22 Fuscidea arboricola 1369 180 0 0 - - - - / - / -

23 Fuscidea pusilla 1568 165 411 (26.2) 3 0.00409 99.6 2 (0.4) 1 / 0 / 1

24 Hyperphyscia adglutinata 1433 218 198 (13.8) 5 0.00389 99.5 4 (0.5) 0 / 0 / 4

25 Hypocenomyce scalaris 1446 34 1349 (93.3) 8 0.00467 98.8 7 (1.2) 1 / 2 / 4

26 Hypogymnia farinacea 752 33 621 (82.6) 4 0.00097 97.0 18 (3.0) 0 / 1 / 17

27 Hypogymnia physodes 806 57 615 (76.3) 2 0.00352 97.7 19 (2.3) 2 / 1 / 16

28 Hypogymnia tubulosa 716 43 532 (74.4) 2 0.00219 98.0 16 (2.0) 0 / 0 / 16

29 Hypotrachyna laevigata 1137 92 867 (76.3) 16 0.00145 99.1 5 (0.9) 0 / 0 / 5

30 Lecania cf. cyrtella 728 78 413 (56.7) 7 0.02063 98.0 16 (2.0) 0 / 0 / 16

31 Lecanora albella 267 11 12 (4.5) 3 0.11882 77.7 118 (19.9)* 26 / 47 / 45

32 Lecanora allophana f. sorediata 1717 19 1397 (81.4) 3 0.00643 99.5 4 (0.5) 0 / 0 / 4

33 Lecanora argentata/subrugosa 625 24 553 (88.5) 13 0.01542 98.8 7 (1.2) 0 / 0 / 7

34 Lecanora carpinea 224 6 187 (83.5) 2 0.02157 99.5 4 (0.5) 0 / 0 / 4

35 Lecanora horiza 963 9 963 (100) 9 0.0019 98.5 9 (1.5) 1 / 0 / 8

36 Lecanora impudens 221 14 186 (84.2) 7 0.00799 99.4 5 (0.6) 1 / 1 / 3

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37 Lecanora muralis 1231 97 737 (59.9) 22 0.00641 99.3 4 (0.7) 0 / 0 / 4

38 Lecanora praesistens 773 19 127 (16.4) 1 0.00532 99.1 7 (0.9) 0 / 0 / 7

39 Lecanora pulicaris 379 10 347 (91.6) 2 0.01427 99.0 8 (1.0) 0 / 0 / 8

40 Lecanora saligna 298 29 209 (70.1) 12 0.00692 99.0 6 (1.0) 0 / 0 / 6

41 Lecanora sp. 868 124 104 (12) 4 0.03276 99.0 7 (1.0) 3 / 0 / 4

42 Lecanora strobilina aggr. 269 11 247 (91.9) 3 0.01246 98.5 9 (1.5) 0 / 0 / 9

43 Lecanora subcarpinea 1551 14 1390 (89.6) 7 0.00754 98.0 12 (2.0) 2 / 5 / 5

44 Lecanora varia 430 5 404 (94) 2 0.00386 98.9 9 (1.1) 2 / 0 / 7

45 Lecidella albida 1096 163 247 (22.5) 4 0.01403 97.7 14 (2.3) 0 / 1 / 13

46 Lecidella cf. elaeochroma 1215 58 1152 (72.7) 8 0.00403 99.2 5 (0.8) 1 / 0 / 4

47 Lecidella cf. leprothalla 1585 133 254 (20.9) 5 0.00127 99.3 4 (0.7) 3 / 1 / 0

48 Lecidella flavosorediata 634 59 644 (69.1) 4 0.0462 98.7 8 (1.3) 0 / 0 / 8

49 Lecidella flavosorediata 932 76 214 (33.8) 2 0.00199 99.3 4 (0.7) 0 / 0 / 4

50 Lecidella scabra 2186 185 337 (15.4) 13 0.00193 97.7 14 (2.3) 2 / 0 / 12

51 Lecidella sp. 331 39 160 (48.3) 14 0.01223 99.7 2 (0.3) 0 / 0 / 2

52 Lepraria elobata 1134 194 197 (17.4) 22 0.0049 98.2 11 (1.8) 1 / 0 / 10

53 Lepraria jackii 960 166 161 (16.8) 18 0.00537 99.2 5 (0.8) 0 / 0 / 5

54 Lepraria lobificans 1021 212 349 (34.2) 16 0.00497 99.3 4 (0.7) 1 / 0 / 3

55 Lepraria rigidula 704 184 144 (20.5) 13 0.01333 99.2 5 (0.8) 0 / 0 / 5

56 Lepraria vouauxii 744 90 312 (41.9) 7 0.00822 98.8 7 (1.2) 0 / 0 / 7

57 Letharia vulpina 621 19 574 (92.4) 7 0.0011 98.1 11 (1.9) 0 / 0 / 11

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58 Loxospora elatina 722 90 291 (40.3) 13 0.01002 98.9 6 (1.1) 0 / 0 / 6

59 Loxospora elatina 3077 60 2713 (88.2) 23 0.00785 99.1 5 (0.9) 0 / 0 / 5

60 Megalaria pulverea 1516 198 290 (19.1) 9 0.01208 99.6 2 (0.4) 0 / 0 / 2

61 Melanelixia fuliginosa subsp.

glabratula

975 163 294 (30.2) 4 0.00344 97.7 19 (2.3) 0 / 0 / 19

62 Melanelixia glabra 890 96 476 (53.5) 10 0.00457 98.3 10 (1.7) 0 / 0 / 10

63 Melanelixia subargentifera 698 58 478 (68.5) 3 0.00111 99.3 4 (0.7) 0 / 0 / 4

64 Melanohalea exasperata 891 85 330 (37) 3 0.00361 99.0 8 (1.0) 1 / 0 / 7

65 Menegazzia terebrata 926 94 672 (72.6) 20 0.00207 97.1 17 (2.9) 1 / 6 / 10

66 Micarea cinerea 422 32 341 (80.8) 4 0.00999 99.1 5 (0.9) 0 / 0 / 5

67 Micarea xanthonica 711 87 373 (52.5) 7 0.00728 99.3 5 (0.7) 0 / 0 / 5

68 Mycoblastus sanguinarius 824 102 222 (26.9) 3 0.00246 98.8 6 (1.0) 0 / 0 / 6

69 Parmelia saxatilis 362 58 241 (66.6) 1 0.00159 96.9 18 (3.1) 0 / 3 / 15

70 Parmelia sulcata 753 143 400 (53.1) 21 0.00604 98.0 11 (1.8) 0 / 0 / 11

71 Parmelina tiliacea 1391 133 1031 (74.1) 18 0.00203 99.0 6 (1.0) 1 / 0 / 5

72 Parmeliopsis ambigua 1401 89 878 (62.7) 7 0.00294 98.1 11 (2.1) 1 / 0 / 10

73 Parmotrema crinitum 1284 83 1146 (89.3) 15 0.0023 98.4 10 (1.6) 0 / 1 / 9

74 Parmotrema perlatum 1981 112 1234 (62.3) 17 0.00143 98.2 11 (1.8) 0 / 0 / 11

75 Phaeophyscia ciliata 365 86 90 (24.7) 3 0.00115 98.2 17 (1.8) 0 / 0 / 17

76 Phaeophyscia orbicularis 407 92 83 (20.4) 2 0.01161 99.4 5 (0.6) 0 / 0 / 5

77 Phaeophyscia poeltii 756 71 423 (56) 3 0.00104 97.9 17 (2.1) 0 / 0 / 17

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78 Phlyctis argena 1078 127 246 (22.8) 3 0 99.1 8 (0.9) 0 / 0 / 8

79 Physcia adscendens 962 111 474 (49.3) 29 0.04417 98.5 12 (1.5) 0 / 0 / 12

80 Physcia aipolia 612 73 377 (61.6) 4 0.002 98.6 11 (1.4) 0 / 0 / 11

81 Physconia distorta 1081 182 183 (16.9) 3 0.04149 98.2 17 (1.8) 0 / 0 / 17

82 Placynthiella dasaea 1089 133 179 (16.4) 5 0.00495 99.1 8 (0.9) 1 / 0 / 7

83 Pleurosticta acetabulum 585 134 20 (3.4) 14 0.05287 99.1 5 (0.9) 1 / 2 / 2

84 Pseudevernia furfuracea 1017 27 879 (86.4) 9 0.0017 95.7 25 (4.3)* 9 / 7 / 9

85 Punctelia jeckeri 499 79 107 (21.4) 2 0.07591 99.4 5 (0.6) 0 / 0 / 5

86 Pycnora sorophora 984 112 351 (35.7) 8 0.01008 98.9 6 (1.1) 0 / 0 / 6

87 Ramalina pollinaria 705 22 654 (92.8) 9 0.00525 98.5 12 (1.5) 1 / 0 / 11

88 Scoliciosporum umbrinum 1244 101 8 (1.4) 5 0.05371 99.5 4 (0.7) 0 / 1 / 3

89 Scoliciosporum umbrinum 592 201 148 (11.9) 3 0.01479 99.0 6 (1.0) 0 / 0 / 6

90 Tuckermannopsis chlorophylla 347 72 146 (42.1) 5 0.0035 97.6 14 (2.4) 0 / 0 / 14

91 Usnea barbata 1498 39 1269 (84.7) 10 0.00258 97.8 13 (2.2) 0 / 1 / 12

92 Usnea barbata 2202 51 2101 (95.4) 11 0.00209 96.8 19 (3.2) 0 / 4 / 15

93 Usnea ceratina 2627 69 2518 (95.9) 14 0.00213 97.0 18 (3.0) 0 / 1 / 17

94 Usnea intermedia 2152 59 2009 (93.4) 2 0.00355 97.6 14 (2.4) 0 / 4 / 10

95 Usnea intermedia 1536 70 1287 (83.8) 5 0.00466 97.8 13 (2.2) 0 / 0 / 13

96 Usnea lapponica 1585 50 1463 (92.3) 14 0.00311 96.3 22 (3.7) 0 / 1 / 21

97 Usnea substerilis 868 38 700 (80.6) 7 0.00205 97.8 11 (1.9) 0 / 1 / 10

98 Violella fucata 830 93 134 (16.1) 4 0.02164 98.6 12 (1.4) 0 / 0 / 12

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99 Violella fucata 1780 122 646 (36.3) 7 0.00704 99.7 2 (0.3) 0 / 0 / 2

100 Vulpicida pinastri 874 93 387 (44.3) 9 0.00159 98.9 9 (1.1) 1 / 0 / 8

Note: 1Clustering conducted at 95% using ‘centroids’ function in USEARCH; 2quantity of transitions (TS), transversions (TV), and indels (Ind) between the generated consensus

sequence (barcode) and representative centroid. * denotes chimeric representative centroid.

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Table 3 List of samples where minor barcode version(s) constituted more than 10% of the target reads, with characteristics of nucleotide variation

between the barcodes and comparison with available Sanger sequences of the species (where possible, otherwise marked with “—“).

Quantity of base differences TS/TV/Ind2

#

Species

No of

Barcodes

Alignment

(bp)

Variable

sites

Nucleotide

diversity ππππ

Max

distance 18S Intron ITS1 5.8S ITS2 28S

Same

mutations

in Sanger

1 Alectoria sarmentosa 8 579 8 0.00795 0.016 0/0/0 n.a. 0/4/1 0/0/0 1/4/2 0/0/0 0

6 Bacidina arnoldiana aggr. 1 5 799 66 0.05519 0.087 0/0/0 n.a. 7/1/1 0/0/0 7/0/1 0/0/0 —

8 Bryoria capillaris 4 803 6 0.00498 0.008 0/0/0 0/1/0 2/1/0 0/0/0 2/0/0 0/0/0 3

9 Buellia arborea 2 586 0 0 0 0/0/0 n.a. 0/0/1 0/0/0 0/0/0 0/0/0 —

12 Chaenotheca cf. stemonea 1 10 647 121 0.11473 0.253 0/0/0 0/0/03 2/0/0 1/0/1 3/1/3 0/0/0 —

15 Cladonia digitata 4 650 0 0 0 0/0/0 n.a. 0/0/0 0/0/0 0/0/3 0/0/0 0

19 Fellhanera bouteillei 1 3 610 57 0.06421 0.102 0/0/0 n.a. 3/1/0 0/0/0 1/1/0 0/0/0 —

29 Hypotrahyna laevigata 2 583 0 0 0 0/0/0 n.a. 0/0/0 0/0/0 0/0/1 0/0/0 —

30 Lecania cf. cyrtella 2 802 25 0.03145 0.032 0/0/0 6/5/1 7/3/0 1/0/1 3/0/2 0/0/3 —

43 Lecanora subcarpinea 18 597 7 0.00445 0.01 0/0/0 n.a. 1/3/7 0/0/0 3/0/0 0/0/0 0

50 Lecidella scabra 20 837 10 0.00987 0.024 0/0/0 0/0/03 7/3/1 0/0/0 3/1/1 0/0/0 —

51 Lecidella sp. 9 597 13 0.01063 0.017 0/0/0 n.a. 8/1/1 0/0/0 3/1/0 0/0/0 —

54 Lepraria lobificans 6 565 4 0.00239 0.011 0/0/0 n.a. 0/6/3 0/0/0 0/0/1 0/0/0 1

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55 Lepraria rigidula 6 601 13 0.00836 0.022 0/0/0 n.a. 5/2/1 0/0/0 3/3/2 0/0/0 12

64 Melanohalea exasperata 2 806 6 0.00752 0.008 0/0/0 0/0/1 3/1/1 0/0/0 2/0/3 0/0/1 5

65 Menegazzia terebrata 16 592 16 0.00836 0.035 0/0/0 n.a. 1/18/0 3/6/6 0/0/3 0/0/0 0

69 Parmelia saxatilis 2 586 3 0.00515 0.005 0/0/0 n.a. 0/0/0 0/0/1 0/3/3 0/0/0 0

70 Parmelia sulcata 2 593 3 0.00506 0.005 0/0/0 n.a. 2/0/0 0/0/0 1/0/0 0/0/0 2

79 Physcia adscendens 2 790 92 0.11735 0.137 4/0/0 32/0/0 22/0/0 9/0/0 18/0/4 7/0/2 3

86 Pycnora sorophora 2 565 4 0.00708 0.007 0/0/0 n.a. 0/0/0 0/0/0 0/4/0 0/0/0 0

95 Usnea intermedia 9 578 7 0.00596 0.01 0/0/0 n.a. 1/2/0 0/0/0 2/2/0 0/0/0 4

96 Usnea lapponica 6 579 8 0.00783 0.014 0/0/0 n.a. 2/2/0 0/0/0 3/1/0 0/0/0 4

Note: 1In presence of intraspecific variation, nucleotide variation within one of the “species” was compared: Bacidina arnoldiana subversions A1 & A2, Chaenotheca cf. stemonea

subversions A1, A2, B & C, Fellhanera bouteillei subversions A1 & A2 (for reference see Figures 3.–5.); 2quantity of transitions (TS), transversions (TV), and indels (Ind), divided

into exons and introns; 3variation in intron presence. Nucleotide variation of specimens in bold more likely represents genuine mutations, while in others is probably due to

PCR/sequencing errors.

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Figure 1 General overview of pyrosequencing reads, with (A) number of reads per

sample, (B) average read length, and (C) read quality distribution over read length.

Figure 2 Comparison of morphological species determination and the results from

sequence megaBLAST search in the NCBI nucleotide database for the studied 100

species. Only the best match accession identy was considered, and the sequence

similarity results were ignored. Diagram proportions are indicated for concordant

results at the species or the genus level (= correct species / = correct genus but

different species or species not present), divergent (= different genus and species), or

neutral results (= unidentified or uncultured fungus). For one species, no sequences

were recovered within the quality-sorted reads; this is noted as “no target”.

Figure 3 Maximum likelihood ITS gene tree of available Bacidina arnoldiana aggr.

sequences, with extended outgroup of closely related Bacidia species. Barcodes from

Bacidina arnoldiana aggr. (sample #6) are indicated with a shaded background. The

number of reads per barcode is given in brackets at the end of the name. Branches

leading to strongly supported nodes (≥70%) are marked in bold. The scale bar shows

the number of substitutions per site.

Figure 4 Maximum likelihood ITS gene tree of available Chaenotheca sequences,

including the barcodes from Chaenotheca cf. stemonea (sample #12, all with shaded

background). The number of reads per barcode is given in brackets at the end of the

name. Branches leading to strongly supported nodes (≥70%) are marked in bold. The

scale bar shows the number of substitutions per site.

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Figure 5 Maximum likelihood ITS gene tree of available Fellhanera sequences with

extended outgroup of closely related species, including the barcodes from Fellhanera

boutellei (sample #19; all with shaded background). The number of reads per barcode

is given in brackets at the end of the name. Branches leading to strongly supported

nodes (≥70%) are marked in bold. The scale bar shows the number of substitutions

per site.

Figure captions for supplementarty data:

Figure S1 ITS1 rDNA secondary structure of the dominant ITS type of Menegazzia

terebrata (sample #65) together with probabilities of fold formation. The red circle on

the RNA structure indicates the region of ambiguous bases. An alignment of the

alternate barcodes in this region is given below.

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146x118mm (300 x 300 DPI)

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64x48mm (300 x 300 DPI)

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224x202mm (300 x 300 DPI)

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314x328mm (300 x 300 DPI)

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275x276mm (300 x 300 DPI)

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Mark et al. “Barcoding lichen-forming fungi using 454 pyrosequencing is challenged by

artifactual and biological sequence variation”

PaPaRa alignments

Our priority in this paper was to present (hopefully) accurate barcodes for the sequenced

samples. Using the consensus sequence approach allowed us to ignore much of the

random noise within sequences, but it depends on the accuracy of a given alignment.

Carry-forward-incomplete-extension (CAFIE) errors are the result of incomplete dNTP

flushing, which then causes a nucleotide from the end of a homoploymer to be read some

bases later (e.g. a true sequence AAAATCG can be read as AAATCGA). Sequences with

this error cannot be removed through the quality filters, as it appears as a true base call;

when occurring repeatedly, this can be interpreted in an alignment as genuine

intragenomic variation. Alternatively to MAFFT, we applied the PaPaRa alignment1 that

should better account for erroneous insertions.

PaPaRa alignments with default parameters were conducted for 85 datasets, where

enough closely related reference sequences could be acquired from a public database

(GenBank). Reference trees for each reference alignment were produced with RAxML.

For 14 samples, there were fewer than four (minimum for RAxML tree construction)

reference sequences (i.e. sequences of approx. >90% similarity) available, and PaPaRa

alignments could not be performed.

We compared the consensus sequences from the PaPaRa alignments with the barcodes

generated from MAFFT alignments. In this comparison we found that for the majority of

analysed samples the consensus sequences from the two alignments were identical

(n=42). In 38 samples, one or more differences between the consensus sequences were

found. These differences resulted from the interpretation of homopolymer and/or

alignment errors.

In general, PaPaRa alignments were comparable to MAFFT alignments, but in regions

with high noise rate (i.e. read ends), PaPaRa produced more consistent alignments.

However, consistent alignments were produced in PaPaRa only when reference

sequences were as long as the alignment. In other words, for a good PaPaRa alignment,

reference sequences have to cover the full length of the matrix. PaPaRa fails to align

regions that are not covered by references; therefore, for five alignments a reasonable

consensus could not be produced by PaPaRa, and comparisons with the barcode could not

be made.

Additionally, PaPaRa follows rather strictly the reference alignment and the reference

tree. Its algorithm more accurately inserted gaps in noisy regions, but with true CAFIE

1 Berger, S.A., and Stamatakis, A. 2011. Aligning short reads to reference alignments and

trees. Bioinformatics 27.15: 2068−2075.

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errors, it produced a misleading alignment that we have illustrated in the figure below. In

the illustration, three clear CAFIE errors can be seen, and instead of making gap-rich

columns, an evolutionarily less likely alignment is produced by PaPaRa.

Fig. An alignment example of sequences with CAFIE errors (data from #69 Parmelia

saxatilis). PaPaRa follows strictly the gaps produced by the reference sequences, while

the MAFFT alignment minimizes the number of mutations.

It seems that using PaPaRa does not provide a benefit for our data sufficient to choose it

over the MAFFT alignment. The main reasons are: (1) when using PaPaRa, we lost

already almost 30% of the barcodes from missing or inappropriate reference sequences,

and the alignments of many others were far from perfect due to this reason. (2) The

original idea for choosing pyrosequencing over Sanger sequencing for barcoding lichen

fungi was to be able to produce barcodes for species that are more difficult to sequence

using the traditional way. If we need Sanger sequences of these samples as references for

alignment, then the original benefit of this approach is lost. (3) And finally, PaPaRa does

not seem to detect CAFIE errors in our data more efficiently. By contrast, it rather strictly

follows the gaps of references and suggests evolutionarily less likely mutations.

However, in other cases, where many good-quality reference sequences are available, it

could prove to be a better option than MAFFT.

REFERENCES

PAPARA

alignment

MAFFT

alignment

* * * * * *

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A

C

CGAGGG

10

A

GG

GG

C

TTT

G

20

CGCTCC

C

GGG

30

GGCTC

CG G C C

40

C C C

A

A

C

T

C

T

T

50

C

AA

CC

C G T T G

60

CG

TA

C

C

T

AC C

70

T T C G

T

TG C

TT

80

TGGCGGGC

C

C

90

C

GGGG

CT C

G

CCCC

CGCCGGC

110

T

TT

T

GG

GC

CG

120

GC

GA

GC

GCCC

130

GCCGGAG

G

A C

140

T CT A

C

C A T T

C

150

T A TT

C

TGT

C

A

160

GT

GATGTC

C

G

170

AGT

ENERGY = 16.5

Probability >= 99%99% > Probability >= 95%95% > Probability >= 90%90% > Probability >= 80%80% > Probability >= 70%70% > Probability >= 60%60% > Probability >= 50%50% > Probability

Conse

nsus

Identi

ty

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The species and references of additional ITS sequences used for Bacidina (Fig. 5), Chaenotheca (Fig.

6), and Fellhanera (Fig. 7) phylogeny reconstructions.

# Species Voucher info GenBank # Reference

1 Bacidia auerswaldii Johansson 20 (UPS) AF282122 Ekman 2001

2 Bacidia bagliettoana Ekman 3137 (BG) AF282123 Ekman 2001

3 Bacidia caligans Johansson 21 (UPS) AF282096 Ekman 2001

4 Bacidia circumspecta Ekman L1330 (LD) AF282124 Ekman 2001

5 Bacidia medialis Ekman L1193 (LD) AF282102 Ekman 2001

6 Bacidia sp. DF223 (WSL) KX098339 Flück 2012



9 Bacidia subincompta Ekman 3413 (BG) AF282125 Ekman 2001

10 Bacidia subincompta DF231 (WSL) KX098342 Flück 2012

11 Bacidia vermifera Johansson 1619 (BG) AF282109 Ekman 2001

12 Bacidia vermifera E:DNA:EDNA09-01506 FR799130 Kelly et al. 2011

13 Bacidia vermifera E:DNA:EDNA09-02101 FR799131 Kelly et al. 2011

14 Bacidina adastra GPN 4961 JN972442 Czarnota and Guzow-

Krzemińska 2012

15 Bacidina arnoldiana Ekman 3157 (BG) AF282093 Ekman 2001

16 Bacidina arnoldiana AFTOL-ID 1845 HQ650650 Schmull et al. 2011

17 Bacidina arnoldiana GPN 5301 JN972439 Czarnota and Guzow-

Krzemińska 2012


Krzemińska 2012


Krzemińska 2012

20 Bacidina arnoldiana DF207 (WSL) KX098343 Flück 2012


22 Bacidina arnoldiana DF211a (WSL) KX098345 Flück 2012




26 Bacidina chloroticula Toensberg 18642 (BG) AF282098 Ekman 2001

27 Bacidina delicata 1996 Fritz (BG) AF282097 Ekman 2001

28 Bacidina delicata LG DNA 369 JQ796854 Sérusiaux et al. 2012

29 Bacidina egenula Ekman 3003 (BG) AF282095 Ekman 2001

30 Bacidina flavoleprosa GPN 5329 JN972443 Czarnota and Guzow-

Krzemińska 2012

31 Bacidina inundata Ekman 3187 (BG) AF282094 Ekman 2001

32 Bacidina neosquamulosa GPN 4888 JN972444 Czarnota and Guzow-

Krzemińska 2012

33 Bacidina neosquamulosa LG DNA 490 JQ796855 Sérusiaux et al. 2012

34 Bacidina phacodes Ekman 3414 (BG) AF282100 Ekman 2001

35 Bacidina sulphurella GPN 5967 JN972446 Czarnota and Guzow-

Krzemińska 2012

36 Bacidina sulphurella GPN 7246 JN972447 Czarnota and Guzow-

Krzemińska 2012

37 Bapalmuia palmularis Lucking 16003 (BG) AY756457 Andersen, unpubl.

38 Byssolecania variabilis Lucking 16033b (BG) AY756458 Andersen, unpubl.

39 Byssoloma leucoblepharum Ekman 3502 (BG) AY756459 Andersen, unpubl.

40 Byssoloma marginatum Tonsberg 27125 (BG) AY756460 Andersen, unpubl.

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41 Byssoloma subdiscordans Tonsberg 25968 (BG) AY756461 Andersen, unpubl.

42 Calopadia foliicola Lucking 16011 (BG) AY756462 Andersen, unpubl.

43 Chaenotheca brachypoda Tibell 17062 (UPS) AF297962 Tibell 2001b

44 Chaenotheca brachypoda Tibell 22193 (UPS) AF297963 Tibell 2001b

45 Chaenotheca brunneola Tibell 22202 (UPS) AF297964 Tibell 2001b

46 Chaenotheca cf. stemonea

Tibell 22113

Tibell 22113 (UPS) AF298135 Tibell 2001b

47 Chaenotheca chlorella Tibell 22187 (UPS) AF297966 Tibell 2001b

48 Chaenotheca chlorella Tibell 22372 (UPS) AF445356 Tibell and Beck 2001

49 Chaenotheca chrysocephala Tibell 22162 (UPS) AF298120 Tibell 2001b

50 Chaenotheca chrysocephala Tibell 21799 (UPS) AF298121 Tibell 2001b

51 Chaenotheca cinerea Jonsson & Nordin (UPS) AF298122 Tibell 2001b

52 Chaenotheca cinerea Tibell 22374 (UPS) AF421201 Tibell 2002

53 Chaenotheca deludens Tibell 16575 AF408678 Tibell 2001a

54 Chaenotheca ferruginea Tibell 22276 (UPS) AF298123 Tibell 2001b

55 Chaenotheca ferruginea DF82 (WSL) KX098349 Flück 2012

56 Chaenotheca furfuracea Thor 15698 AF298124 Tibell 2001b

57 Chaenotheca furfuracea Tibell 22364 AF445357 Tibell and Beck 2001

58 Chaenotheca furfuracea Wedin 6366 (UPS) JX000101 Prieto et al. 2013

59 Chaenotheca furfuracea DF251 (WSL) KX098350 Flück 2012

60 Chaenotheca furfuracea DF252 (WSL) KX098351 Flück 2012

61 Chaenotheca gracilenta Wedin 7022 (S) JX000100 Prieto et al. 2013

62 Chaenotheca gracillima Tibell 17943 (UPS) AF298126 Tibell 2001b

63 Chaenotheca gracillima Tibell 17052 (UPS) AF298127 Tibell 2001b

64 Chaenotheca gracillima Tibell 17614 (UPS) AF408679 Tibell 2001a




68 Chaenotheca hispidula Tibell 21900 (UPS) AF298128 Tibell 2001b

69 Chaenotheca hygrophila Thor 15612 AF298129 Tibell 2001b

70 Chaenotheca laevigata Tibell 22176 (UPS) AF298130 Tibell 2001b

71 Chaenotheca laevigata Tibell 21998b (UPS) AF298131 Tibell 2001b

72 Chaenotheca nitidula Koffman 222 (UPS) AF492386 Tibell and Koffman 2002

73 Chaenotheca nitidula Koffman 170 (UPS) AF492387 Tibell and Koffman 2002

74 Chaenotheca nitidula Tibell 21490 (UPS) AF492388 Tibell and Koffman 2002

75 Chaenotheca phaeocephala Tibell 16885 (UPS) AF298132 Tibell 2001b

76 Chaenotheca phaeocephala Tibell 22201 (UPS) AF298133 Tibell 2001b

77 Chaenotheca phaeocephala Hermansson 8290 (UPS) AF445358 Tibell and Beck 2001

78 Chaenotheca phaeocephala Hermansson 8428 (UPS) AF445359 Tibell and Beck 2001

79 Chaenotheca phaeocephala Tibell 21819 (UPS) AF445360 Tibell and Beck 2001

80 Chaenotheca phaeocephala Tibell 22291 (UPS) AF446045 Tibell and Beck 2001

81 Chaenotheca sphaerocephala Tibell 21939 (UPS) AF298134 Tibell 2001b

82 Chaenotheca stemonea Tibell 22191 (UPS) AF408683 Tibell 2001a

83 Chaenotheca subroscida Tibell 22150 (UPS) AF298136 Tibell 2001b

84 Chaenotheca subroscida Tibell 22161 (UPS) AF298137 Tibell 2001b

85 Chaenotheca subroscida Tibell 22167 (UPS) AF446047 Tibell and Beck 2001

86 Chaenotheca subroscida Tibell 22365 (UPS) AF446048 Tibell and Beck 2001

87 Chaenotheca trichialis Tibell 16878 (UPS) AF298139 Tibell 2001b

88 Chaenotheca trichialis Tibell 22355 AF410674 Tibell 2001a

89 Chaenotheca trichialis Tibell 22300 (UPS) AF421203 Tibell 2002

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Andersen, H.L. Phylogeny and classification of Micarea. Unpubl.

Czarnota, P. and Guzow-Krzemińska, B. 2012. ITS rDNA data confirm a delimitation of Bacidina arnoldiana and B.

sulphurella and support a description of a new species within the genus Bacidina. The Lichenologist, 44: 743–755.

Ekman, S. 2001. Molecular phylogeny of the Bacidiaceae (Lecanorales, lichenized Ascomycota). Mycol Res, 105: 783–

797.

Flück, D. 2012. DNA barcoding of Swiss epiphytic crustose lichens – a feasibility study. M.Sc. thesis. Academic

Deparment, University of Bern, Bern, Switzerland.

Grube, M. 2001. A simple method to prepare foliicolous lichens for anatomical and molecular studies. The Lichenologist,

33: 547–550.

Kelly, L.J., Hollingsworth, P.M., Coppins, B.J., Ellis, C.J., Harrold, P., Tosh, J., and Yahr, R. 2011. DNA barcoding of

lichenized fungi demonstrates high identification success in a floristic context. New Phytol., 191: 288–300.

Prieto, M., Baloch, E., Tehler, A., and Wedin, M. 2013. Mazaedium evolution in the Ascomycota (Fungi) and the

classification of mazaediate groups of formerly unclear relationship. Cladistics, 29: 296–308.

Schmull, M., Miadlikowska, J., Pelzer, M., Stocker-Wörgötter, E., Hofstetter, V., Fraker, E., Hodkinson, B.P., Reeb, V.,

Kukwa, M., and Lumbsch, H.T. 2011. Phylogenetic affiliations of members of the heterogeneous lichen-forming

fungi of the genus Lecidea sensu Zahlbruckner (Lecanoromycetes, Ascomycota). Mycologia, 103: 983–1003.

Sérusiaux, E., van den Boom, P.P., Brand, M.A., Coppins, B.J., and Magain, N. 2012. Lecania falcata, a new species from

Spain, the Canary Islands and the Azores, close to Lecania chlorotiza. The Lichenologist, 44: 577–590.

Tibell, L. 2001a. Cybebe gracilenta in an ITS/5.8 S rDNA based phylogeny belongs to Chaenotheca (Coniocybaceae,

lichenized Ascomycetes). The Lichenologist, 33: 519–525.

Tibell, L. 2001b. Photobiont association and molecular phylogeny of the lichen genus Chaenotheca. The Bryologist, 104:

191–198.

Tibell, L. 2002. Morphological variation and ITS phylogeny of Chaenotheca trichialis and C. xyloxena (Coniocybaceae,

lichenized ascomycetes). Ann. Bot. Fenn., 39: 73–80.

Tibell, L. and Beck, A. 2001. Morphological variation, photobiont association and ITS phylogeny of Chaenotheca

phaeocephala and C. subroscida (Coniocybaceae, lichenized ascomycetes). Nord. J. Bot., 21: 651–660.

Tibell, L. and Koffman, A. 2002. Chaenotheca nitidula, a new species of calicioid lichen from northeastern North America.

The Bryologist, 105: 353-357.

90 Chaenotheca trichialis Tibell 22090 (UPS) AF421205 Tibell 2002

91 Chaenotheca trichialis Selva 8274a (UMFK) AF421206 Tibell 2002

92 Chaenotheca trichialis Prieto 3028 (S) JX000102 Prieto et al. 2013

93 Chaenotheca xyloxena Tibell 18431 (UPS) AF298138 Tibell 2001b

94 Chaenotheca xyloxena Tibell 22188 (UPS) AF298140 Tibell 2001b

95 Chaenotheca xyloxena Tibell 16673 (UPS) AF421208 Tibell 2002




99 Chaenotheca xyloxena Selva 7753 (UMFK) AF421213 Tibell 2002

100 Fellhanera bouteillei AF414858 Grube 2001

101 Fellhanera bouteillei Ekman 3417 (BG) AY756463 Andersen, unpubl.

102 Fellhanera subtilis Tonsberg 28199 (BG) AY756464 Andersen, unpubl.

103 Fellhanera viridisorediata Tonsberg 27375 (BG) AY756465 Andersen, unpubl.

104 Fellhaneropsis myrtillicola Tonsberg 25311 (BG) AY756466 Andersen, unpubl.

105 Lasioloma arachnoideum Lucking 16005 (BG) AY756467 Andersen, unpubl.

106 Micarea clavopycnidiata Tonsberg 27215 (BG) AY756473 Andersen, unpubl.

107 Micarea prasinella McCune 25337 (BG) AY756491 Andersen, unpubl.

108 Sporopodium antoninianum Lucking 16002d (BG) AY756498 Andersen, unpubl.

109 Szczawinskia tsugae Tonsberg 30044 (BG) AY756499 Andersen, unpubl.

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GenBank megablastBLAST best hit results for sequenced species’ primary barcodes (queries on 11

January 2015).

GenBank BLAST result

# Barcode Organism

Accession

No

Max

score

Query

coverage (%)

Identity

(%)

1 Alectoria sarmentosa versA Uncultured Alectoria JN397372 990 96 99

2 Anaptychia crinalis Anaptychia ciliaris KJ027714 571 56 96

3 Arthrosporum populorum Arthrosporum populorum AF282106 911 85 99

4 Bacidia rubella Bacidia rubella EU266078 1110 82 98

5 Bacidia vermifera Bacidia vermifera FR799128 856 89 96

6 Bacidina arnoldiana aggr. versA1 Bacidina neosquamulosa JN972444 817 100 92

7 Bacidina arnoldiana aggr. Bacidina neosquamulosa JN972444 965 70 98

8 Bryoria capillaris versA Bryoria fuscescens DQ534452 1456 100 99

9 Buellia arborea versA Buellia penichra AF540503 785 85 95

10 Bunodophoron melanocarpum Sphaerophorus globosus DQ534485 684 100 88

11 Cetrelia monachorum Cetrelia olivetorum HQ671305 989 98 98

12 Chaenotheca cf. stemonea versC Chaenotheca cf.

stemonea 'Tibell 22113'

AF298135 737 84 92

13 Cladonia chlorophaea Cladonia sp. KC-2014 KM245923 1434 99 97

14 Cladonia coniocraea Cladonia gracilis JN863236 1550 100 99

15 Cladonia digitata versA Cladonia borealis JN863286 1081 96 98

16 Cladonia squamosa Cladonia cenotea FN868596 1447 98 97

17 Evernia divaricata Evernia divaricata AF297741 979 93 99

18 Evernia prunastri Evernia prunastri HQ650611 1037 97 99

19 Fellhanera bouteillei versA1 Fellhanera bouteillei AF414858 773 100 90

20 Flavoparmelia caperata Flavoparmelia sp. Hur

CH080070

HQ671302 2002 93 99

21 Frutidella pullata Lecidea pullata HQ650669 1367 90 99

22 Fuscidea arboricola No barcode

23 Fuscidea pusilla Lasallia papulosa HQ650603 388 72 85

24 Hyperphyscia adglutinata Hyperphyscia adglutinata AF224361 880 63 98

25 Hypocenomyce scalaris Hypocenomyce scalaris HQ650632 974 97 99

26 Hypogymnia farinacea Hypogymnia tubulosa HQ725075 915 94 97

27 Hypogymnia physodes Uncultured ascomycete AM901734 1474 100 99

28 Hypogymnia tubulosa Uncultured ascomycete AM901734 1048 100 90

29 Hypotrachyna laevigata versA Hypotrachyna laevigata AY611074 928 86 99

30 Lecania cf. cyrtella versA Uncultured fungus clone KC965610 808 69 93

31 Lecanora albella Lecanora albella AY541241 907 92 97

32 Lecanora allophana f. sorediata Lecanora allophana AF070031 909 62 99

33 Lecanora argentata/subrugosa Lecanora subrugosa AY398711 1003 92 99

34 Lecanora carpinea Lecanora carpinea FR799199 961 63 99

35 Lecanora horiza Lecanora horiza AY541252 959 92 98

36 Lecanora impudens Lecanora allophana AF070031 922 62 99

37 Lecanora muralis Lecanora muralis FJ497040 939 100 95

38 Lecanora praesistens Uncultured Rhizoplaca

clone 19A

EF095283 660 95 82

39 Lecanora pulicaris Uncultured fungus clone JN904337 861 58 99

40 Lecanora saligna Lecanora saligna AF189716 942 85 99

41 Lecanora sp. Uncultured fungus clone JN905599 841 62 97

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42 Lecanora strobilina aggr. Lecanora symmicta AF070024 848 85 97

43 Lecanora subcarpinea versA1 Lecanora subcarpinea AY541269 974 92 99

44 Lecanora varia Lecanora varia AF070027 918 62 99

45 Lecidella scabra versO Uncultured fungus clone KC965645 1029 97 99

46 Lecidella albida Rhizoplaca macleanii JX036146 462 69 90

47 Lecidella cf. elaeochroma Uncultured fungus clone KC965645 953 97 96

48 Lecidella cf. leprothalla Uncultured fungus clone KC966001 944 100 95

49 Lecidella flavosorediata Uncultured fungus clone KC966001 931 100 95

50 Lecidella flavosorediata Uncultured fungus clone KC966001 944 100 95

51 Lecidella sp. versA Uncultured fungus clone KC966001 959 100 96

52 Lepraria elobata Lepraria elobata EF619545 1098 100 99

53 Lepraria jackii Lepraria jackii EF619567 1110 100 100

54 Lepraria lobificans versA Lepraria lobificans HQ650623 891 97 96

55 Lepraria rigidula versA Lepraria rigidula EF619561 1072 100 99

56 Lepraria vouauxii Lepraria membranacea KF682452 880 100 93

57 Letharia vulpina Letharia vulpina AF228470 1050 100 99

58 Loxospora elatina Loxospora ochrophaea HQ650641 1031 100 99

59 Loxospora elatina Loxospora ochrophaea HQ650641 1031 100 99

60 Megalaria pulverea Megalaria pulverea FR799227 933 89 99

61 Melanelixia fuliginosa subsp.

glabratula

Melanelixia fuliginosa EU034667 1391 93 100

62 Melanelixia glabra Melanelixia glabra EU761216 924 86 99

63 Melanelixia subargentifera Melanelixia albertana GU994560 922 95 97

64 Melanohalea exasperata versA Melanohalea exasperata AY611083 867 62 98

65 Menegazzia terebrata versC4 Menegazzia terebrata GU994567 990 93 99

66 Micarea cinerea Micarea alabastrites AY756469 632 88 89

67 Micarea xanthonica Ascomycota sp. CH-

Nl2LBM

FJ008690 523 71 85

68 Mycoblastus sanguinarius Mycoblastus

sanguinarius

JF744920 994 90 99

69 Parmelia saxatilis versA Parmelia saxatilis EU034668 922 96 97

70 Parmelia sulcata versA Myelochroa aurulenta HQ671303 1075 99 99

71 Parmelina tiliacea Parmelina tiliacea JX466454 1057 99 99

72 Parmeliopsis ambigua Uncultured Ascomycota FR682210 996 93 99

73 Parmotrema crinitum Parmotrema crinitum AY586565 977 87 99

74 Parmotrema perlatum Parmotrema crinitum AY586565 944 87 99

75 Phaeophyscia ciliata Phaeophyscia ciliata AF224447 1696 95 99

76 Phaeophyscia orbicularis Phaeophyscia orbicularis JQ301694 1683 94 99

77 Phaeophyscia poeltii Phaeophyscia denigrata EU670226 1053 98 91

78 Phlyctis argena Phlyctis argena FR799264 902 55 99

79 Physcia adscendens versA Physcia adscendens FJ497044 1437 100 99

80 Physcia aipolia Physcia caesia DQ534476 1266 100 96

81 Physconia distorta Physconia distorta EU266086 1365 77 99

82 Placynthiella dasaea Placynthiella uliginosa HQ650633 1127 98 90

83 Pleurosticta acetabulum Pleurosticta acetabulum AF058034 1011 96 99

84 Pseudevernia furfuracea Pseudevernia furfuracea GU300779 959 98 98

85 Punctelia jeckeri Punctelia jeckeri AF494385 1531 93 99

86 Pycnora sorophora versA Pycnora sorophora KF360404 821 79 99

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Genome

DraftNote: ITS sequences of species previously not represented in GenBank are marked in bold.

87 Ramalina pollinaria Ramalina pollinaria JF923612 1339 100 98

88 Scoliciosporum umbrinum Uncultured fungus clone

S335

FJ820822 1105 100 100

89 Scoliciosporum umbrinum Uncultured fungus clone

S335

FJ820822 905 100 94

90 Tuckermannopsis chlorophylla Tuckermannopsis

chlorophylla

AF192413 994 97 99

91 Usnea barbata Usnea intermedia JN086313 987 93 99

92 Usnea barbata Usnea intermedia JN086313 970 93 99

93 Usnea ceratina Usnea ceratina AJ457142 977 92 99

94 Usnea intermedia Usnea intermedia JN086313 987 93 99

95 Usnea intermedia versA Usnea intermedia JN086313 970 93 99

96 Usnea lapponica versA Usnea lapponica JN086316 992 93 99

97 Usnea substerilis Usnea wasmuthii JN086334 952 93 99

98 Violella fucata Violella fucata JN009733 1458 95 99

99 Violella fucata Mycoblastus fucatus JF744968 922 85 99

100 Vulpicida pinastri Vulpicida pinastri AF072239 1347 96 98

Page 65 of 70


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List of specimens with multiple barcodes generated in this study. Primary barcodes representing the specimens in BOLD and available in

GenBank are marked in bold (refer to the Table 1 for GB and BOLD codes). The hypothetical source for the alternative barcodes is marked

in the Notes column (data accessible in PlutoF database: https://plutof.ut.ee/#/study/view/31890).

Specimen

Code 454 Barcodes

No of

reads Notes Taxon

LC-064 Alectoria_sarmentosa_versA 43 primary barcode Alectoria sarmentosa

Alectoria_sarmentosa_versB 42 alternate barcode version: intragenomic variation Alectoria sarmentosa

Alectoria_sarmentosa_versC 5 alternate barcode version: intragenomic variation Alectoria sarmentosa

Alectoria_sarmentosa_versD 10 alternate barcode version: intragenomic variation Alectoria sarmentosa

Alectoria_sarmentosa_versE 41 alternate barcode version: CAFIE errors Alectoria sarmentosa

Alectoria_sarmentosa_versF 51 alternate barcode version: CAFIE errors Alectoria sarmentosa

Alectoria_sarmentosa_versG 6 alternate barcode version: CAFIE errors Alectoria sarmentosa

Alectoria_sarmentosa_versH 12 alternate barcode version: CAFIE errors Alectoria sarmentosa

RE-515-19 Bacidia_sp1_versA 20 alternate barcode version: intraspecific and intragenomic variation Bacidia rubella

Bacidia_sp1_versB 7 alternate barcode version: intraspecific and intragenomic variation Bacidia rubella

Bacidia_sp2 14 alternate barcode version: intraspecific and intragenomic variation Biatora beckhausii

Bacidia_vermifera_versA 1763 primary barcode 1Bacidia vermifera

Bacidia_vermifera_versB 50 alternate barcode version: intragenomic variation Bacidia vermifera

BC-038-1 Bacidina_arnoldiana_versA1 46 primary barcode 1Bacidina arnoldiana sp1

Bacidina_arnoldiana_versA2 6 alternate barcode version: intraspecific and intragenomic variation Bacidina arnoldiana sp1

Bacidina_arnoldiana_versB1 45 alternate barcode version: intraspecific and intragenomic variation Bacidina arnoldiana sp1

Bacidina_arnoldiana_versB2 3 alternate barcode version: intraspecific and intragenomic variation Bacidina arnoldiana sp1

Bacidina_arnoldiana_versC 8 alternate barcode version: intraspecific and intragenomic variation 1Bacidina arnoldiana sp3

LC-058 Bryoria_capillaris_versA 123 primary barcode Bryoria capillaris

Bryoria_capillaris_versB 26 alternate barcode version: intragenomic variation Bryoria capillaris

Bryoria_capillaris_versC 39 alternate barcode version: intragenomic variation Bryoria capillaris

Bryoria_capillaris_versD 139 alternate barcode version: intragenomic variation Bryoria capillaris

BC-154-2 Buellia_arborea_versA 225 primary barcode Buellia arborea

Buellia_arborea_versB 48 alternate barcode version: CAFIE errors (?) Buellia arborea

BC-087-3 Chaenotheca_cf_stemonea_versA1 15 alternate barcode version: intragenomic variation 2Chaenotheca cf. stemonea

Chaenotheca_cf_stemonea_versA2 9 alternate barcode version: intragenomic variation Chaenotheca cf. stemonea

Chaenotheca_cf_stemonea_versB 7 alternate barcode version: intragenomic variation Chaenotheca cf. stemonea

Chaenotheca_cf_stemonea_versC 75 primary barcode Chaenotheca cf. stemonea

Chaenotheca_sp_versA1 8 alternate barcode version: intraspecific and intragenomic variation 2Chaenotheca xyloxena/trichialis

Chaenotheca_sp_versA2 9 alternate barcode version: intraspecific and intragenomic variation Chaenotheca xyloxena/trichialis

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Chaenotheca_sp_versB1 3 alternate barcode version: CAFIE errors (?) Chaenotheca xyloxena/trichialis

Chaenotheca_sp_versB2 9 alternate barcode version: CAFIE errors (?) Chaenotheca xyloxena/trichialis

Chaenotheca_sp_versB3 10 alternate barcode version: intraspecific and intragenomic variation Chaenotheca xyloxena/trichialis

Chaenotheca_sp_versB4 10 alternate barcode version: intraspecific and intragenomic variation Chaenotheca xyloxena/trichialis

LC-067 Cladonia_digitata_versA 167 primary barcode Cladonia digitata

Cladonia_digitata_versB 60 alternate barcode version: intragenomic variation/sequencing errors Cladonia digitata

Cladonia_digitata_versC 56 alternate barcode version: intragenomic variation/sequencing errors Cladonia digitata

Cladonia_digitata_versD 46 alternate barcode version: intragenomic variation/sequencing errors Cladonia digitata

LC-118 Fellhanera_bouteillei_versA1 106 primary barcode 3Fellhanera bouteillei s.lat

Fellhanera_bouteillei_versA2 20 alternate barcode version: intragenomic variation Fellhanera bouteillei s.lat

Fellhanera_bouteillei_versB 3 alternate barcode version: intraspecific variation 3Fellhanera bouteillei s.str.

KM-03-05 Hypotrachyna_laevigata_versA 496 primary barcode Hypotrachyna laevigata

Hypotrachyna_laevigata_versB 120 alternate barcode version: CAFIE/homopolymer errors Hypotrachyna laevigata

Hypotrachyna_laevigata_versC 241 alternate barcode version: CAFIE/homopolymer errors Hypotrachyna laevigata

LC-023 Lecania_cf_cyrtella_versA 292 primary barcode Lecania cf. cyrtella

Lecania_cf_cyrtella_versB 89 alternate barcode version: intragenomic variation Lecania cf. cyrtella

LC-090 Lecanora_subcarpinea_versA1 474 primary barcode Lecanora subcarpinea

Lecanora_subcarpinea_versA2 424 alternate barcode version: CAFIE errors+intragenomic variation (?) Lecanora subcarpinea



Lecanora_subcarpinea_versB1 6 alternate barcode version: CAFIE errors+intragenomic variation (?) Lecanora subcarpinea



Lecanora_subcarpinea_versC1 2 alternate barcode version: CAFIE errors+intragenomic variation (?) Lecanora subcarpinea



Lecanora_subcarpinea_versD1 2 alternate barcode version: CAFIE errors+intragenomic variation (?) Lecanora subcarpinea




Lecanora_subcarpinea_versE1 1 alternate barcode version: CAFIE errors+intragenomic variation (?) Lecanora subcarpinea




BC-055-4 Lecidella_scabra_versA 5 alternate barcode version: intragenomic variation Lecidella scabra

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Lecidella_scabra_versB 3 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versC 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versD 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versE 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versF 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versG 4 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versH 3 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versI 16 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versJ 2 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versK 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versL 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versM 12 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versN 22 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versO 202 primary barcode Lecidella scabra

Lecidella_scabra_versP 2 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versQ 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versR 1 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versS 6 alternate barcode version: intragenomic variation Lecidella scabra

Lecidella_scabra_versT 37 alternate barcode version: intragenomic variation Lecidella scabra

LC-088 Lecidella_sp_versA 138 primary barcode Lecidella sp.

Lecidella_sp_versB 9 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versC 5 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versD 2 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versE 2 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versF 2 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versG 1 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versH 1 alternate barcode version: intragenomic variation Lecidella sp.

Lecidella_sp_versI 1 alternate barcode version: intragenomic variation Lecidella sp.

BC-133-3 Lepraria_lobificans_versA 135 primary barcode Lepraria lobificans

Lepraria_lobificans_versB 107 alternate barcode version: CAFIE errors Lepraria lobificans

Lepraria_lobificans_versC 20 alternate barcode version: CAFIE errors Lepraria lobificans

Lepraria_lobificans_versD 20 alternate barcode version: CAFIE errors Lepraria lobificans

Lepraria_lobificans_versE 42 alternate barcode version: CAFIE errors Lepraria lobificans

Lepraria_lobificans_versF 25 alternate barcode version: CAFIE errors Lepraria lobificans

BC-056-2 Lepraria_rigidula_versA 100 primary barcode Lepraria rigidula

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Lepraria_rigidula_versB 21 alternate barcode version: intragenomic variation Lepraria rigidula

Lepraria_rigidula_versC 5 alternate barcode version: intragenomic variation Lepraria rigidula

Lepraria_rigidula_versD 5 alternate barcode version: intragenomic variation Lepraria rigidula

Lepraria_rigidula_versE 8 alternate barcode version: intragenomic variation Lepraria rigidula

Lepraria_rigidula_versF 5 alternate barcode version: intragenomic variation Lepraria rigidula

LC-028 Melanohalea_exasperata_versA 270 primary barcode Melanohalea exasperata

Melanohalea_exasperata_versB 60 alternate barcode version: intragenomic variation Melanohalea exasperata

LC-054 Menegazzia_terebrata_versA1 56 alternate barcode version: PCR/sequencing errors Menegazzia terebrata

Menegazzia_terebrata_versA2 90 alternate barcode version: PCR/sequencing errors Menegazzia terebrata






Menegazzia_terebrata_versB1 49 alternate barcode version: PCR/sequencing errors Menegazzia terebrata



Menegazzia_terebrata_versC1 39 alternate barcode version: PCR/sequencing errors Menegazzia terebrata



Menegazzia_terebrata_versC4 93 primary barcode Menegazzia terebrata

Menegazzia_terebrata_versD 70 alternate barcode version: PCR/sequencing errors Menegazzia terebrata

Menegazzia_terebrata_versE 48 alternate barcode version: PCR/sequencing errors Menegazzia terebrata

LC-060 Parmelia_saxatilis_versA 125 primary barcode Parmelia saxatilis

Parmelia_saxatilis_versB 116 alternate barcode version: CAFIE errors Parmelia saxatilis

LC-004 Parmelia_sulcata_versA 212 primary barcode Parmelia sulcata

Parmelia_sulcata_versB 188 alternate barcode version: intragenomic variation Parmelia sulcata

KM-01-2B Physcia_adscendens_versA 337 primary barcode Physcia adscendens

Physcia_adscendens_versB 118 alternate barcode version: pseudogene (?) Physcia adscendens

BC-156-1 Pycnora_sorophora_versA 296 primary barcode Pycnora sorophora

Pycnora_sorophora_versB 41 alternate barcode version: CAFIE errors (?) Pycnora sorophora

KM-03-02 Usnea_intermedia_versA 1101 primary barcode Usnea intermedia

Usnea_intermedia_versB1 9 alternate barcode version: intragenomic variation Usnea intermedia



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LC-013 Usnea_lapponica_versA 1264 primary barcode Usnea lapponica

Usnea_lapponica_versB1 92 alternate barcode version: intragenomic variation Usnea lapponica




Usnea_lapponica_versB5 24 alternate barcode version: intragenomic variation Usnea lapponica 1For reference see Fig. 3;

2 see Fig. 4;

3 see Fig. 5.

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Genome

draft - university of toronto t-space · draft 6 level and were left as bacidina arnoldiana...

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