# R-Syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring

Frédéric Rimet, Philippe Chaumeil, François Keck, Lenaïg Kermarrec, Valentin Vasselon, Maria Kahlert, Alain Franc, Agnes Bouchez

► To cite this version:

Frédéric Rimet, Philippe Chaumeil, François Keck, Lenaïg Kermarrec, Valentin Vasselon, et al. R-Syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring. Database - The journal of Biological Databases and Curation, 2016, 2016, pp.baw016. 10.1093/database/baw016. hal-01426772

HAL Id: hal-01426772

https://inria.hal.science/hal-01426772

Submitted on 27 May 2020

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

Original article

# R-Syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring

Frédéric Rimet¹,²,* , Philippe Chaumeil³,⁴, François Keck¹,², Lenaïg Kermarrec⁵, Valentin Vasselon¹,², Maria Kahlert⁶, Alain Franc³,⁴ and Agnès Bouchez¹,²

¹INRA—UMR Carrtel, 75 Av. De Corzent—BP 511, Thonon Les Bains Cedex FR-74203, France, ²UMR CARRTEL, University of Savoie, Le Bourget Du Lac FR-73370, France, ³INRA, UMR BioGeCo, 69 Route D'arcachon, Cestas Cedex FR-33612, France, ⁴University of Bordeaux 1, UMR BioGeCo, Talence FR-33400, France, ⁵ASCONIT Consultants, Naturopôle—Bât. C, 3, Bd De Clairfont, Toulouges FR-66350, France, and ⁶Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, PO Box 7050, Uppsala SE-750 07, Sweden

*Corresponding author: Tel: +33-4-50-26-78-74, Fax: +33-4-50-26-07-60 Email: frederic.rimet@thonon.inra.fr

Citation details: Rimet,F., Chaumeil,P., Keck,F. et al. R-syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring. *Database* (2016) Vol. 2016: article ID baw016; doi:10.1093/database/baw016

Received 22 September 2015; Revised 12 January 2016; Accepted 3 February 2016

## Abstract

Diatoms are micro-algal indicators of freshwater pollution. Current standardized methodologies are based on microscopic determinations, which is time consuming and prone to identification uncertainties. The use of DNA-barcoding has been proposed as a way to avoid these flaws. Combining barcoding with next-generation sequencing enables collection of a large quantity of barcodes from natural samples. These barcodes are identified as certain diatom taxa by comparing the sequences to a reference barcoding library using algorithms. Proof of concept was recently demonstrated for synthetic and natural communities and underlined the importance of the quality of this reference library. We present an open-access and curated reference barcoding database for diatoms, called R-Syst::diatom, developed in the framework of R-Syst, the network of systematic supported by INRA (French National Institute for Agricultural Research), see http://www.rsyst.inra.fr/en. R-Syst::diatom links DNA-barcodes to their taxonomical identifications, and is dedicated to identify barcodes from natural samples. The data come from two sources, a culture collection of freshwater algae maintained in INRA in which new strains are regularly deposited and barcoded and from the NCBI (National Center for Biotechnology Information) nucleotide database. Two kinds of barcodes were chosen to support the database: 18S (18S ribosomal RNA) and *rbcL* (Ribulose-1,5-bisphosphate carboxylase/oxygenase), because of their efficiency. Data are curated using innovative (Declic) and classical bioinformatic tools (Blast, classical phylogenies) and up-to-date taxonomy (Catalogues
and peer reviewed papers). Every 6 months R-Syst::diatom is updated. The database is available through the R-Syst microalgae website (http://www.rsyst.inra.fr/) and a platform dedicated to next-generation sequencing data analysis, virtual_BiodiversityL@b (https:// galaxy-pgtp.pierroton.inra.fr/). We present here the content of the library regarding the number of barcodes and diatom taxa. In addition to these information, morphological features (e.g. biovolumes, chloroplasts...), life-forms (mobility, colony-type) or ecological features (taxa preferenda to pollution) are indicated in R-Syst::diatom.

Database URL: http://www.rsyst.inra.fr/

Introduction

Microalgae are the dominant primary producers of aquatic ecosystems. They display a huge taxonomic diversity—the numbers of diatoms alone have been estimated at 100 000 species (1) and each taxon occupies a particular ecological niche (2). These properties make them excellent ecological indicators. One of the most often used algal class for ecological assessment is diatoms (3). The first studies demonstrating the effect of pollution on freshwater diatom communities was over a century ago (4) and afterwards—50, 60 years ago (5–7)—several authors proposed methodologies based on the taxonomic composition of diatom communities. In recent years, hundreds of studies have shown the usefulness of diatoms to monitor aquatic ecosystems (8). Nowadays, directives and laws require using this ecological indicator to routinely assess the ecological quality of rivers and lakes (e.g. in Europe with the Water Framework Directive (9) and in the US with the National Water-Quality Assessment Program (10)).

The diatom cell has the characteristic of being encased in two siliceous shells (valves), which are connected by girdle bands; together, the valves and girdle bands of a single cell comprise its ‘frustule’ (11). The current identification of diatom taxa is based on the morphology of the frustule. Standard procedures for diatom biomonitoring (e.g. for Europe: (12) are based on counting and determining several hundred of valves under the light microscope. This is time-consuming and requires a high level of taxonomic expertise. Moreover, distinguishing morphologically very similar taxa is difficult and can lead to misidentifications that compromise the accuracy of diatom index results for water quality assessment (13).

A solution that avoids these identification uncertainties and reduces analysis time is to replace microscopic identifications by molecular identifications based on DNA sequences. This is the concept of DNA-barcoding, a taxonomic method that uses a short genetic marker in an organism’s DNA to identify it as belonging to a particular species (14). This approach, first developed for animals, has recently been applied to diatoms (15, 16) and several DNA-markers were

evaluated (18S, 28S, *cox*1, ITS, *rbcL*). Development of Next-Generation Sequencing (NGS) methods has opened a new area in the use of barcoding when applied to natural samples made of several taxa which is referred to as metabarcoding (17): NGS makes it possible to obtain a large quantity of data per sequencing run and by comparing each NGS sequence to the barcodes of a reference barcoding library, it enables the identification of the taxonomic composition of the natural community. The proof of this concept for diatoms has been shown first on mock communities—made of already barcoded strains—(18) and recently on natural communities from several temperate and tropical rivers (18, 19). These tests have shown that some barcodes yield better results than others. Cox1, displayed the most different molecular inventories from the expected inventories despite its high polymorphism distributed throughout the sequence: this is mostly due to the small number of reference barcodes built with Sanger sequencing. This small number is due to primer specificity that should be designed for each diatom genus. 18S (including v4 region) showed a good similarity between molecular and expected inventories mainly due to the highly variable v4 region and the high number of reference barcodes. The molecular inventories closest to expected inventories were obtained with *rbcL* because it showed a higher polymorphism than 18S with an equivalent number of reference barcodes. These tests highlighted also that an Achilles heel of metabarcoding was the reference barcoding library. It must be as complete as possible and requires a regular expert curation to maintain its quality (i.e. taxonomic homogeneity of assignations, sequence quality and traceability of data and metadata). Indeed the value of a curated database is to enable other workers to use it practically without having to sort out the same taxonomic name problems each time one is working with it. Several curated databases already exist, such as PR2 (20) or SILVA (21). They cover all microbes. But, a reference library dedicated to diatoms with a fine tuned taxonomy and curation at genus and species level was lacking.

In this article, we describe an open-access reference library, called R-Syst::diatom, and its curation procedures.
For most of the freshwater taxa, phenotypic information is
given (morphology, life-forms and ecological requirements).

This database was used in previous metabarcoding stud-
ies for river biomonitoring using diatoms (18, 22, 23).
R-Syst::diatom is included in the French barcoding net-
work R-Syst and gathers data for two barcodes (18S and
*rbcL*. It is freely accessible through a website (http://www.
rsyst.inra.fr/) and a supercomputing platform adapted for
NGS analyses (Y.C. Laizet et al. 2014, in preparation)
(https://galaxy-pgtp.pierroton.inra.fr/).

Data sources, metadata associated with the barcodes,
data curation procedures, data storage and accessibility are
presented in the methodology. Then results of a data cur-
ation exercise during an update of R-Syst::diatom and its
contents are given and discussed.

**Materials and Methods**

Data sources

Two data sources are used to fill R-Syst::diatom: the bar-
coded strains of the Thonon Culture Collection (TCC) and
the nucleotide database of NCBI.

Barcoded strains of the TCC

The UMR-CARRTEL is a research unit of the French
National Institute for Agricultural Research (INRA) working
on aquatic ecosystems. It has maintained the TCC since
1968, which is registered to the World Data Centre for
Microorganisms (1030) and to the Global Registry
Biorepository (http://grbio.org/institution/thonon-culture-col-
lection-umr-carrtel-inra). A total of 858 monoclonal strains
of freshwater microalgae are registered, among which 505
are diatoms. For each culture we keep in the laboratory of
the UMR-CARRTEL, DNA extracts (25 ng/µl at -80°C)
and raw material (living culture in growth chambers, frozen
raw material in glycerin 50% at -80°C). Moreover, for dia-
toms, at least one permanent slide (Naphrax) of clean frust-
ules as well as nitric acid treated material (in a vial) is kept.
This material is accessible for subsequent studies. Two hun-
dred eighteen diatom strains are maintained as live cultures
in December 2015, the oldest was isolated in 1985 and the
most recent in 2015. These strains are available on request
through a website dedicated to the collection (http://www6.
inra.fr/carrtel-collection_eng/). Each strain is sequenced for
at least two barcodes: 18S and *rbcL*. Several research pro-
grams financed the isolations and sequencings (see
Acknowledgements). All information about these strains, the
sampling site location (georeferenced on a google map), the
isolator, the barcode (including type of barcode, amplified re-
region, primer used, protocols), the phenotypic data, the photos
(all strains are photographed in light microscopy at ×40,

×100 in oil immersion and some of them in scanning electron microscopy), the associated research programs (for sampling and sequencing) and its taxonomic affiliation are available on the R-syst website (http://www.rsyst.inra.fr/). The strains are identified using updated literature such as the entire collection of Diatoms of Europe, Iconographia Diatomologica, Bibliotheca Diatomologica and peer reviewed papers.

The TCC is regularly enriched with new isolated strains,
which are sequenced for at least the two barcodes (18S, *rbcL*).
Their entry in R-Syst::diatom is submitted to the curation pro-
cess described in the section ‘Data curation’ here below.

Nucleotide database of NCBI

NCBI maintains a webserver that collects and provides
molecular data and software. In particular, NCBI allows
access to all public DNA sequence data via the GenBank
database (24) (http://www.ncbi.nlm.nih.gov/genbank). We
recovered all the nucleotide sequences of diatoms (fresh-
water and marine) available on GenBank main collection
(CoreNucleotide) for the 18s (including V4 region) and
*rbcL* whatever their length and their quality. We limited
ourselves to these markers because they generally discrim-
inate well between species and are therefore useful for spe-
cies identification (25–28), they provide access to the
largest taxonomic diversity and showed the best results for
metabarcoding (18, 22). Sequences for other genes sug-
gested as diatom barcodes – 28S and ITS rDNA and
cox1—are not added to the database.

These sequences are retrieved regularly (every 6 months)
using the following keywords on the Nucleotide Advanced
Search Builder selecting ‘All fields’ in the drop-down menu:
‘(18s OR rbcL) and (diatom OR Bacillariophyta)’. In add-
ition to these keywords, a publication interval in NCBI is
indicated in the Advanced Search Builder selecting
‘Publication date’ in the drop-down menu: the oldest is cor-
responding to the last R-Syst::diatom update and the most
recent to the current date. R-Syst::diatom is thus updated
every 6 months. As well as the barcodes coming from the
TCC, their entry in R-Syst::diatom is submitted to the cur-
ation process described in the next paragraphs.

In the particular case of a newly gathered sequences cor-
responding to uncultured and/or unidentified diatom in
NCBI, those are not accepted in the database.

Phenotypic data

For most species, three kinds of phenotypic data are given:
(i) morphological, (ii) life-form and (iii) ecological.

(i) Morphological data are gathering information about chloroplast and cell sizes. For the chloroplast, their shapes and number per cell are given for each taxon with the corresponding bibliographical references; most of the time, the
publication of Cox (29) was used. When possible, photos of the strains were look at to get such information. Cell-dimensions (length, width, thickness), biovolume and size-class are given. Most of this information is derived from Rimet and Bouchez (30) which is a database gathering morphological and ecological information about freshwater diatoms. Omnidia (31) database which is gathering information about cell-biovolumes and sizes was also used. Original references where such information can be found are given.

(ii) Even if diatoms are basically unicellular algae, they exhibit an important diversity of life-forms, and many of them can form colonies. Taxa can even present several successive life-forms during their life-cycle (e.g. *Cymbella* can be unicellular and move freely at one time and attached to a peduncle and then immobile at another time). Different kinds of life-form information are documented in R-Syst::diatom (30), such as motility, kind of colony, type of attachment (pad, stalk, adnate, pedunculate).

(iii) Several kinds of ecological information are given. Nutrients, organic matter and moisture preferences of the species according to Van Dam *et al.* (32) are given. Habitat preferences (benthic, planktonic, epipsammic, epipelic) are given mostly according to Round *et al.* (11). The ecological guilds to which species belong (high-profile, low-profile, mobile, euplanktonic) are given according to Rimet and Bouchez (30). Finally, the pollution sensitivity values and ecological weights of several diatom indices are given, such as the TDI (Trophic Diatom Index) (33), the TDI-Sweden, (34), the IPS (Pollution Sensitivity Index) (35) or the Phylogenetic-IPS (36).

## Data curation

The identifications and sequencing of diatoms included in R-Syst::diatom were carried out by different people and may not be equally reliable. There are three important drawbacks to take into account when gathering new sequences in R-Syst::diatom:

- First, in NCBI, data were deposited by different authors at different times: the first data were deposited in 1998. From this date to the present, taxonomy has evolved.

- Second, the identifications and taxonomic skills of the different authors who deposited their data in NCBI can be heterogeneous. The same problem is also visible for TCC.

- Third, the length or the quality of the sequences cannot be adapted for correct taxonomic affiliation.

These three drawbacks underline the necessity to curate the taxonomic names of the strains and their corresponding sequences in order to have homogeneous taxonomic names in R-Syst::diatom. As diatom taxonomy is under active development, the aim is to achieve for similar sequences a similarity in their taxonomic names, and to

ensure that these names are as taxonomically correct as possible according to the most recent taxonomy literature. However, as diatom taxonomy is under active development, there will be cases where only a consensus for practical use can be made and solutions regarding the correct name will have to await further scientific studies. In any case, if the original taxonomic name given by the authors of the sequence is changed during the curation procedure, the traceability of the original name is kept in the database and is visible on R-Syst web portal.

This data curation is carried out in three steps (the first two steps are mandatory):

- The first step is pre-curation. The objective of this first step is to check if each newly retrieved sequence from NCBI or the TCC has a comparable taxonomic name to similar sequences formerly deposited in NCBI, and to check if the quality and length of these sequences is correct. For this purpose, the newly retrieved sequences are compared to the entire NCBI database using Blast.

- The second step is detailed curation. The objective of this second step is to compare the new sequences meeting the criteria of the first step with the sequences already included in R-Syst::diatom, based on a local alignment methodology, called 'Declic algorithm' (for detail see 'Second curation step' section of this 'Data curation' part). If these sequences have taxonomic names similar to comparable sequences then their taxonomic names and the sequences are kept for the third curation step. If the taxonomic names from comparable sequences are different, then the taxonomic names are checked through a taxonomic curation procedure.

- The third step is an optional curation (for reasons see 'Third curation step' of the 'Data curation' part). The objective is to compare the new sequences meeting the criteria of the second step with those already included in R-Syst::diatom database, based on a global alignment and phylogenetic analyses. If the taxonomic names from comparable sequences are different, then the taxonomic names are checked through a taxonomic curation procedure. The second and third curation step are based on different algorithms which both have different advantages and so are complementary. The Declic analysis is based on local alignment and is run on all sequences whatever their length. The phylogenetic analysis is based on global alignment and is run on a sub-set of sequences which have a long common covering (1000 bp at least). Declic has the advantage to compare all sequences whereas the phylogenetic analysis has the advantage to compare with better precision a sub-set of sequences.

Figure 1 gives an overview of the general workflow of the curation procedures. Figure 2 gives details on the
<figure><img src="image_3.png" /><figcaption>**Figure 1.** General flowchart of the curation and integration of new sequences in the R-Syst::diatom. Taxonomic curation procedure is detailed in a flowchart (Figure 2). Diamonds are conditions, the arrow from the bottom point of the diamond corresponds to 'Yes', the arrow from the right point of the diamond corresponds to 'No'. Rectangles are processing steps.</figcaption></figure>
taxonomic curation procedure which is used several times
in the general workflow of Figure 1.

First curation step: pre-curation using NCBI and
Blastn of each sequence

For each sequence (whatever its quality or length), newly
gathered from NCBI or coming from new strains of the
TCC, a Blastn is run on the entire NCBI database. The 20
sequences showing the best pairwise identity matching to
this new sequence are consulted.

If the taxonomic affiliation of the new sequence is close
to those of the 20 other sequences then the taxonomic af-
filiation is kept and this new sequence is kept for the se-
cond curation step. Taxonomic affiliation designated here
is not necessarily the species level: it can be the genus or
family level in the case of newly isolated genera or families
never isolated before. For instance, if the newly retrieved
sequence is identified in an already well sequenced genus
(e.g. *Pseudo-nitzschia* or *Fistulifera*), the 20 closest se-
quences should belong to the same genus, and even to the
same species if the species has been already sequenced for-
merly (e.g. *Nitzschia palea*, *Cyclotella meneghiniana*). On
the other hand, if the new sequence is named with a genus
which has never been sequenced before, it is expected that
the 20 closest sequences belong to the same family or order
(e.g. sequences of *Didymosphaenia* had to be close to se-
quences belonging to Cymbellales).

If there is discordance between the taxonomic affiliation
of this new sequence and those of the 20 other sequences,
then the taxonomic curation procedure is applied (Figure 2):

i. First, we check if a peer-reviewed publication is associ-
ated with this new sequence. In this case this new se-
quence and its taxonomic name are kept for the second
curation step. If it is not the case, then point (ii) of the
taxonomic curation procedure is considered.

ii. If no peer-reviewed publication is available, taxonomic
synonymies are checked using Algaebase website
(http://www.algaebase.org/) (37), the catalogue of dia-
tom names of E. Fourtanier and P. Kociolek (http://
researcharchive.calacademy.org/research/diatoms/
names/index.asp) or Omnidia software (31). If this en-
ables the homogenization of its taxonomic name, then
the new sequence and its new taxonomic name are
kept for the second curation step. If it is not the case,
then point (iii) of the taxonomic curation procedure is
considered.

iii. If no peer-reviewed publication exists, and if the taxo-
nomic synonymies check was not successful, we check
if some photos or slides associated to the sequence are
available (e.g. in TCC or Algaterra databases (38) or
websites of culture collections such as http://www.

ccap.ac.uk/). If the re-examination of this material
(photos/slides) shows that the strain was wrongly iden-
tified then a correct taxonomic name is given. If this
new taxonomic name is similar to those of the 20 most
similar NCBI sequences, this sequence is kept for the
second curation step. If it is not the case, no photos/
slides are available or the new taxonomic name still
differs from those of the 20 most similar sequences,
then this new sequence is not accepted in the database.

After gathering all the new sequences from the first cur-
ation step, additional curation steps are done by compar-
ing them to the sequences already in the R-Syst::diatom
database. Two different and complementary tools are
used. The first tool is Declic analyses (second curation
step). This analysis is based on local alignments which are
useful when sequences of dissimilar sizes have to be com-
pared. If this is the case of the data usually gathered: de-
pending on the authors, only parts of 18s/rbcl are
sequenced. The second tool is phylogenetic trees (third op-
tional curation step) based on global alignments. Global
alignments are more useful when sequences of similar sizes
are compared and are carried out on a sub-set of sequences
of homogeneous size and similar regions.

Second curation step: use of Declic on the entire database

In the second curation step, the newly retrieved sequences and
the sequences of the R-Syst::diatom database are compared
two by two by mean of Declic (for Delimitation of species
with cliques) software written in python (19) which enable (i)
to define OTU (Operational Taxonomic Units) through an
unsupervised clustering algorithm and (ii) to represent these
OTU in a two dimensional space. This software can be run
with an R-package (39) or under a galaxy platform (https://
galaxy-pgtp.pierroton.inra.fr/) within the Virtual
BiodiversityL@b folder (Y.C. Laizet et al. 2014, in prepar-
ation). Briefly, Declic analysis is run after computing pairwise
local alignment scores (40) which are then transformed into
distances. We then have a full pairwise distance matrix.
Pairwise distances can be visualized by running Multi
Dimensional Scaling (MDS) on the distance matrix. Second, a
graph is attached to the matrix, where the nodes are the se-
quences, and there is an edge between two nodes if the dis-
tance between the two sequences is lower than a given
threshold (one graph per threshold). The threshold is selected
by the user and a graph can be built for any threshold value.
The graph is projected onto the plane using the Fruchterman–
Reingold layout (41). If edit distances were evolutionary dis-
tances, and if a threshold exists for separating taxa, then a
taxon would be a clique (i.e. in this case a subset of sequences
which are all connected with each other by an edge, see
Figure 3a). As we have edits distances from best local
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Flowchart of the taxonomic curation procedure. Diamonds are conditions, the arrow from the bottom point of the diamond corresponds to 'Yes', the arrow from the right point of the diamond corresponds to 'No'. Rectangles are processing steps.</figcaption></figure>

alignment, we built the connex components (i.e. in this case a
subset of sequences which are connected by at least one edge,
see Figure 4b) of such a graph, expecting they are close to cli-
ques, and related to taxa. Such a threshold may play the role
of a barcoding gap, although some sequences within a connex
component can be at a distance larger than the gap. Colors
are given to sequences belonging to the same taxon. The taxo-
nomic levels which are selected for data curation are genus
level or species level. A threshold of 1% is usually considered
to separate diatom species (15, 26), nevertheless generally a
threshold below 1% is selected during this curation procedure
because different species (e.g. *Fragilaria capucina*,
*perminuta*, *tenuistriata*) and even genera (e.g. *Surirella*,
*Campylodiscus*) often merge in the same group with 1%.

It is expected that a new sequence has a homogeneous
taxonomic name with the other sequences of the clique it
belongs to. If it is the case, the sequences of this clique and
their taxonomic names are kept for the third curation step.

If the new sequence and the other sequences have hetero-
erogeneous taxonomic names inside the same clique, then
the taxonomic curation procedure is applied (Figure 2) in a
similar way as in the first curation step:

i. We check if a peer-reviewed publication is associated with the new sequence. If it is the case, based on the results of the publication, the taxonomic names of the sequences are homogenized in the clique and the sequences are kept for the third curation step. If no peer-reviewed publication is available, then point (ii) is considered.
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Use of Declic analyses to curate the database: case of taxonomically heterogeneous clique (a) and connex component (b). (a) *Gomphonema bourbonense* clique (18s, gap 8) with one *G. angustum* sequence (TCC460)—white circle and (b) *Encyonema* spp. connex component (18s, gap 8) with one *Criticula cuspidata* sequence (KM084917)—white circle. TCC460 strain identification was changed into *G. bourbonense* after checking phos. KM084917 was rejected since there is an obvious mistake of identification.</figcaption></figure>

ii. In the case that there is no publication available for the new sequence, the synonymies of the taxonomic names of the sequences inside this clique are checked (using i.e. Algaebase, Catalogue of diatom names, Omnidia). If this enables us to homogenize the taxonomic names,

the sequences and their new taxonomic names are kept for the third curation step. If this is not the case, point (iii) is considered.

iii. If no publication is associated to this new sequence and if the synonymies check did not enable us to
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Use of Declic analyses to curate the database: case of taxonomically homogeneous clique (a) and connex component (b). (a) *Pseudo-nitzschia multistriata* (b) *Pseudo-nitzschia delicatissima*. No changes were made in these cases.</figcaption></figure>

homogenize taxonomic names, we check if photos/slides associated to it (collections as TCC, Algaterra, Bold) are available. If the re-examination of the photos/slides enable us to change the taxonomic names and make it similar to those of the other sequences in the clique, the sequence and its new taxonomic name is kept

for the third curation step. If the taxonomic name is still different after checking photos/slide, the sequence is rejected.

Connex components which were not cliques are also checked. Sequences belonging to the same connex
component should show homogeneous taxonomic names. If not, the same procedure (described here above) for clients was adopted (check of literature, synonymies, photos ...).

### Third curation step (optional): phylogenetic analyses

As with the Declic analyses, phylogenetic analyses are carried out for each marker (18S and *rbcL*) on all sequences (new sequences and R-Syst::diatom). A general alignment is carried out on all the sequences with Muscle in Seaview (42). The best compromise between removing the shortest sequences and trimming the alignment is found in order to keep an alignment long enough to get phylogenetic analyses robust enough. Usually, for 18S and *rbcL* the alignment is carried out on 1000 bp at least and so shorter sequences or sequences which have <1000 bp in common with the other sequences are not taken into account in this curation step. From this general alignment, all sequences are trimmed at the same length and a neighbor joining tree is run with Seaview (42) or Mega5 (43). The same verifications as those carried out in the second curation step are done: if taxonomic names in a given clade are heterogeneous, the taxonomic curation procedure is applied (Figure 2).

These phylogenetic analyses are done to confirm the curation completed with Declic analyses. Nevertheless, phylogenetic analyses are carried out on a sub-set of the database only, since short sequences are not integrated in this analysis. The shortest sequences, which were not integrated in the phylogenetic analyses, are only curated with the Declic analyses and if they meet all the criteria of taxonomic homogeneity in the second curation step they are directly integrated in R-Syst::diatom.

### Data storage and open access

All the curated data are stored in a PostgreSQL database built in the frame of the R-Syst network. R-Syst is a collaborative network supported by INRA for studies in systematics. It comprises several tens of research teams including technicians, researchers and engineers in the fields of molecular biology, genetics and bioinformatics who are involved in the molecular and morphological characterization of organisms. Among those, micro-algae are represented and a dedicated web interface is available from the R-Syst web portal (http://www.rsyst.inra.fr/en) to browse the stored data of the diatom barcoding database.

On this website, the algae section of the database gathers information about diatom strains (but also about Chlorophyta and Cyanophyta strains of the TCC) which were characterized for three kinds of criteria: taxonomic, phenotypic and genetic.

For each strain, the following information is given when available: (i) sampling site (name and location on Google map), (ii) type of habitat, (iii) strain code given by the laboratory, (iv) name of the project which funded the field sampling, sequencing, (v) laboratory responsible for field sampling, (vi) DNA extraction, (vii) PCR, sequencing and (viii) the dates of the different steps. A species name is given to each strain, except in a few cases where only genus level is given. Moreover the taxonomic affiliation is given until the regnum (11, 37, 44). For molecular criteria, the database gives the type of marker (18S or *rbcL*), the primers used for sequencing and PCR. Protocols for DNA extraction and PCR are also given. The laboratory responsible of the sequence is given. For phenotypic information, photos (living material and empty frustules) of the TCC strains are given.

## Results and Discussion

### Examples of curation

Results of the curation process of R-Syst::diatom in January 2015 are given in Table 1 and supplementary files give the list of sequences whose taxonomical name was changed after curation (Supplement data 1) and those which were not integrated in R-Syst::diatom (Supplement data 2). This curation was carried out on new sequences downloaded from NCBI and coming from the TCC between 29 July 2014 and 16 January 2015.

**First curation step:** In the curation process carried out in January 2015 (Figure 1), several sets of sequences deposited in NCBI were not kept because determinations were clearly erroneous or insufficient. This was especially the case for 18S where 162 sequences were rejected because of an insufficient taxonomic identification (class level identifications).

**Second curation step:** Taxonomic names of several sequences were modified after Declic both for 18S and *rbcL*. Modifications were for instance performed on a clique where all 18S sequences belonged to *Gomphonema bourbonense* except one *Gomphonema angustum* (Figure 3a). All these sequences came from the TCC, which meant that the identities of the strains could be checked from our photos. After checking the photos of *G. angustum* (strain number: TCC460), we realized that the determination was erroneous, and the name was changed to *G. bourbonense*. A second example is a connex component, which gathered five sequences of *Encyonema*, except one which belonged to *Craticula*. These two genera are very different morphologically and phylogenetically and cannot be in the same connex component. Even if though the sequence was recently published in a peer reviewed paper it was rejected. As an
<table><caption>**Table 1.** Results of the curation procedure of 16 January 2015</caption><thead><tr><th>Curation steps</th><th>18s</th><th>rbcL</th></tr></thead><tbody><tr><td>New sequences (TCC—NCBI)</td><td>428</td><td>194</td></tr><tr><td>R-Syst::diatom (former version)</td><td>1911</td><td>1624</td></tr><tr><td>First curation step</td><td></td><td></td></tr><tr><td>Sequences having a different identification from the 20 most similar NCBI sequences</td><td>207</td><td>4</td></tr><tr><td>Sequence published in peer review paper</td><td>45</td><td>1</td></tr><tr><td>Check of photos -&gt; modification of the determinations</td><td>0</td><td>0</td></tr><tr><td>homogenization of taxonomy/synonymies</td><td>0</td><td>0</td></tr><tr><td>Sequences rejected</td><td>162</td><td>3</td></tr><tr><td>Sequences kept</td><td>45</td><td>1</td></tr><tr><td>New sequences after first curation step</td><td>266</td><td>191</td></tr><tr><td>Second curation step</td><td></td><td></td></tr><tr><td>Sequences having a different identification from the sequences of the same clique</td><td>16</td><td>32</td></tr><tr><td>Changes according to peer review papers</td><td>3</td><td>3</td></tr><tr><td>Check of photos -&gt; modification of the determinations</td><td>6</td><td>6</td></tr><tr><td>Homogenization of taxonomy/synonymies</td><td>5</td><td>21</td></tr><tr><td>Sequences rejected</td><td>2</td><td>2</td></tr><tr><td>Sequences kept</td><td>14</td><td>30</td></tr><tr><td>New sequences after second curation step</td><td>264</td><td>189</td></tr><tr><td>Third curation step</td><td></td><td></td></tr><tr><td>Sequences having a different identification from the sequences of the same clade</td><td>9</td><td>10</td></tr><tr><td>Changes according to peer review papers</td><td>3</td><td>2</td></tr><tr><td>Check of photos -&gt; modification of the determinations</td><td>0</td><td>5</td></tr><tr><td>Homogenization of taxonomy/synonymies</td><td>1</td><td>3</td></tr><tr><td>Sequences rejected</td><td>5</td><td>0</td></tr><tr><td>Sequences kept</td><td>4</td><td>10</td></tr><tr><td>New sequences after third curation step</td><td>260</td><td>189</td></tr><tr><td>R-Syst::diatom (new version)</td><td>2171</td><td>1813</td></tr></tbody></table>

Sequences were imported from NCBI and the TCC between 29 July 2014 and 16 January 2015. Values in the table give the number of sequences.

example of a no-change, we show the connex component (Figure 4a) and the clique (Figure 4b) for two species of *Pseudo-nitzschia*, which names were taxonomically homogeneous.

## Content of the database

### Number and length of sequences

The number of sequences available for 18S and *rbcL* is given in Table 2. Sequences from the TCC represent 21% of the total number of sequences for 18S, and 19% for the *rbcL*. Only 16.7% of the 18S sequences of the TCC have been deposited on NCBI and have an accession number. Similarly, 21.7% of the *rbcL* sequences of the TCC were deposited on NCBI. These sequences were deposited in the framework of several peer-reviewed publications, as phylogenetic studies (45, 46), metabarcoding analyses using NGS (18, 22), diversity studies (47), ecotoxicological studies (48). The objective is to submit all accepted sequences from the TCC on NCBI.

The lengths of the barcodes in R-Syst::diatom is given in Figure 5. For 18S, a large majority of the sequences have lengths of 1600–1800 bp. Several of them are however much shorter (400–500 bp) and correspond to the 18-v4 region proposed as barcode by Zimmermann *et al.* (28) for

<table><caption>**Table 2.** Number of sequences in the R-Syst::diatom database coming from NCBI and the TCC (December 2015)</caption><thead><tr><th>Marker</th><th>18S</th><th>18S-V4<sup>a</sup></th><th>rbcL</th></tr></thead><tbody><tr><td>No. of sequences from the TCC</td><td>468</td><td>—</td><td>373</td></tr><tr><td>No. of sequences from NCBI</td><td>1759</td><td>85</td><td>1613</td></tr></tbody></table>

species identification. For *rbcL*, a large majority of the sequences have lengths of 1200–1600 bp. A few of them are much shorter and correspond to sequences deposited in the framework of barcoding studies studying the efficiency of shorter fragments inside the *rbcL* for species identification (e.g. *rbcL* 3P see Refs. 27 and 50), or were mostly submitted in the framework of the phylogenetic studies of Bruder and Medlin (50, 51).

### Taxonomic coverage of diatom taxa

To show the distribution of barcodes in the diatom taxonomy, we followed the classification given by Medlin (52) with the three classes Mediophyceae, Coscinodiscophyceae, Bacillariophyceae, and we kept the Fragilariophyceae as described in Round *et al.* (11), which were recently shown to

<footnote><sup>a</sup>le 18S-V4 is a region of 18S. It is counted as a separated column because these sequences are limited to this particular region.</footnote>
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Amount and length of the barcodes present in R-Syst::diatom (update of September 2015).</figcaption></figure>

be non-monophyletic (except Bacillariophyceae) but were grades which evolved from radials (Coscinodiscophyceae) to polar (Mediophyceae) to araphids (Fragilariophyceae) and then to raphids (Bacillariophyceae) (53). Figure 6 gives an overview of the number of barcodes and taxa for each class in the R-Syst::diatom database. The Bacillariophyceae is the

most barcoded class with the Bacillariales and the Naviculales orders. In all diatom classes the number of barcodes is higher for 18S than for *rbcL*: this can be explained by the longer legacy of 18S in diatom phylogeny (54 and 55), than *rbcL* which started to be used in diatom barcoding and phylogeny more recently (25).
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Number of barcodes (18S and rbcL) in the R-Syst::diatom for the different diatom classes and orders (update of September 2015). Large circles correspond to high number of barcodes. Tree created with itol.embl.de.</figcaption></figure>

In the Coscinodiscophyceae (Figure 7), the most sequenced genus is *Aulacoseira* (respectively, 31 and 23 for 18S and *rbcL* sequences). *Aulacoseira* strains are mostly sequenced by Shcherbakova (56), Edgar and Theriot (57) and Medlin and Kaczmarska (58).

In the Mediophyceae (Figure 8), the most sequenced genera are the *Thalassiosira* (respectively, 151 and 61 for 18S and *rbcL* sequences), *Skeletonema* (respectively, 107 and 16 for 18S and *rbcL* sequences) and the *Cyclotella* (respectively, 58 and 41 for 18S and *rbcL* sequences). *Thalassiosira* are intensively studied by Alverson et al. (59), Luddington et al. (60), Whittaker et al. (61) among others. The *Skeletonema* genus is also often sequenced (62–64).

In the Fragilariophyceae (Figure 9), the most sequenced genus is *Fragilaria* (respectively, 77 and 46 for 18S and

*rbcL* sequences), the other genera are much less represented in the database: *Asterionellopsis* (respectively, 17 and 22 for 18S and *rbcL* sequences) and *Diatoma* (respectively, 18 and 5 for 18S and *rbcL* sequences). The majority of the *Fragilaria* sequences are coming from the TCC collection and are not yet published (all photos and related data are available of R-Syst website).

In the Bacillariophyceae (Figure 10), the most sequenced genera are *Nitzschia*, *Navicula*, *Gomphonema*, *Pinnularia*, *Pseudo-nitzschia*, *Sellaphora*. In particular, *Nitzschia palea*, an indicator of polluted freshwaters, is the most sequenced species (respectively, 66 and 88 for 18S and *rbcL* sequences), because it is intensively studied (47, 65, 66). Similarly, *Gomphonema parvulum*, which is also an important freshwater quality indicator species, is intensively barcoded (respectively, 51 and 54 for 18S and *rbcL*
<figure><img src="image_9.png" /><figcaption>**Figure 7.** Number of barcodes (18S and rbcL) and taxa in R-Syst::diatom for Coscinodiscophyceae orders (update of September 2015). Red and purple horizontal bars give the number of barcodes, respectively, for 18S and rbcL. Blue and green horizontal bars give the number of taxa, respectively, for 18S and rbcL. Tree created with itol.embl.de based on diatom taxonomy.</figcaption></figure>

sequences) by Kermarrec et al. (27) and Abarca et al. (67). The *Sellaphora* genus is also a very well-studied genus, in particular the *Sellaphora pupula* species complex since it was studied as well for its reproduction mode than its phyl- ogeny (68–70) and has been a model for barcode tests (25). *Pseudo-nitzschia* genus, a potential harmful diatom genus which can bloom in marine waters is often investigated. Several studies, based on genetic data, show a cryptic di- versity inside several species (49, 71, 72). Several species belonging to the *Navicula* have been sequenced in several papers (50, 51, 73–75). *Pinnularia* genus is mostly studied by Souffreau et al. (76).

## Phenotypic data and their usefulness for ecological assessment

Greater than 93% of the barcodes present in R-Syst::diatom have associated a phenotypic information, only a few of them (7%) have none. These 7% correspond to marine taxa which were recently described. Since R-Syst::diatom objective is mostly devoted for freshwater ecological assessment we did not look actively for information about such kind of taxa; nevertheless marine diatom taxa are integrated in R-Syst::diatom since rivers and lakes can present marine taxa because of industrial wastes or natural situations (77).

Information about life-form (motility, kind of colony, kind of attachment), habitat preferences (planktonic, benthic, epipelic, epipsammic...), ecological guild (motile, low-profile, high-profile, euplanktonic) is given for the species identification of the barcodes. Similarly, in 93% of the cases, chloroplast shape, number and bibliographical references are

given. Cell-dimensions and biovolumes are given for 67% of the barcodes. The diatom indices values are given for 72% of the barcodes for the IPS and 49% for the TDI and 40% for the TDI-Sweden, because a large part of the barcodes are coming from marine habitats which are not covered by these diatom indices devoted to freshwater ecosystems. Similarly, only 38 to 40% of the barcodes have information for the eco- logical classes of nutrients, organic and moisture requirement of Van Dam et al. (32).

Several papers have shown the usefulness of diatom indices (8, 78, 79), ecological guilds and life-forms (80, 81) for lake and river assessment using classical microscopic data. Unpublished ongoing work (V Vasselon et al., personal communications) show that using similar metrics (diatom indices, life-forms) with metabarcoding data can also give a robust and accurate assessment of ecological quality of freshwater ecosystems. This is why it appears necessary to integrate this kind of phenotypic and ecological information to move forward to an environmental assessment using metabarcoding technology.

## Conclusion

In their article, Zimmermann et al. (82) highlight the importance of the quality of reference barcoding libraries. In particular, the traceability and availability of the metadata (sampling site, isolation protocols, pherograms, vouchers, slides, DNA, photos, etc...) and the physical deposit of vouchers (culture, raw material, slides, DNA, etc...) associated with the barcode are necessary for accurate biodiversity studies. Such requirements were recently integrated into a
<figure><img src="image_10.png" /><figcaption>**Figure 8.** Number of barcodes (18S and rbCL) and taxa in R-Syst::diatom for Mediophyceae orders (update of September 2015). Red and purple horizontal bars give the number of barcodes, respectively, for 18S and rbCL. Blue and green horizontal bars give the number of taxa, respectively, for 18S and rbCL. Tree created with itol.embl.de based on diatom taxonomy.</figcaption></figure>

pre-standard protocol by the European Committee for Standardization (83). Indeed, several European laboratories (in France, Germany, Hungary, United-Kingdom, Spain, Czech Republic, Belgium...) working on diatom barcoding for biomonitoring have agreed on a minimum set of metadata that must accompanied a normative barcode for a particular diatom taxon. Diatom barcodes stored in databases such as R-Syst, Algalerra of Bold fulfill these gold requirements.

Moreover, Zimmermann et al. (82) say that barcodes 'lacking voucher specimens ... are of no future use and valuable information is lost to science'. Our position is slightly different: historical data stored in NCBI may not meet the criteria now being established in the pre-standard protocol but are nevertheless precious and are not all 'lost to science'. Indeed, getting a clonal culture from a natural sample and then growing it until getting enough biomass to extract its DNA, to mount it for permanent slide, to
<figure><img src="image_11.png" /><figcaption>**Figure 9.** Number of barcodes (18S and rbcL) and taxa in R-Syst::diatom for Fragilariophyceae orders (update of September 2015). Red and purple horizontal bars give the number of barcodes, respectively, for 18S and rbcL. Blue and green horizontal bars give the number of taxa, respectively, for 18S and rbcL. Tree created with itol.embl.de based on diatom taxonomy.</figcaption></figure>

treat it for scanning electron microscopy is a long and risky process (many cultures are lost before getting DNA or permanent slides). Not considering barcodes that are not backed by voucher specimens will in some cases waste valuable data for barcode reference libraries: some such barcodes have been published in peer reviewed journals and are accompanied by photographs and other metadata. These, if carefully evaluated as described in this article, before sequences are integrated into the database, can be valuable, filling gaps in the taxon coverage.

Routine molecular identification of diatom taxa in natural communities to a genus level (instead to a species level)

with R-Syst::diatom is not a problem (18, 22, 84) because taxon coverage of the reference library at a genus level in freshwaters is almost complete. But, for molecular identification at a species level, even using all possible barcodes and after curating them (as shown in this article) before their integration in R-Syst::diatom, the library still suffers from an underrepresentation of some taxa living in particular habitats. In particular, pristine freshwater habitats and tropical rivers should be sampled more frequently to get cultures and to barcode them. This is a challenge of the next few decades.

Another difficulty met in the database is that several sister species—the definition and delimitation of which are
<figure><img src="image_12.png" /><figcaption>**Figure 10.** Number of barcodes (18S and rbcL) and taxa in R-Syst::diatom for Bacillariophyceae orders (update of September 2015). Red and purple horizontal bars give the number of barcodes, respectively, for 18S and rbcL. Blue and green horizontal bars give the number of taxa, respectively, for 18S and rbcL. Tree created with itol.embl.de based on diatom taxonomy.</figcaption></figure>
classically based on morphological criteria—display an overlap when considering their barcodes proximity. The result is that such species could be paraphyletic. This is currently the case for species in the *Fragilaria capucina* group (*capucina, perminuta, nanoides, gracilis ...*) when considering their 18S or rbcL barcodes. This type of problem also occurs, but less often, for generic levels (e.g. *Surirella, Campylodiscus*). Our curation procedure is not sufficient in these cases and an integrative study based on genetic data (using multiple markers), morphological data (scanning electron microscopy, light microscopy) and also ecological data must be undertaken to adjust taxonomy. A good example of such integrative studies is shown in the sister species *Nitzschia soratensis/inconspicua* (85, 86). More studies of this kind are required for the development of the database, in order to present well-defined and monophyletic taxa so that the molecular identifications of sequences from NGS can be done easily.

Finally, barcode databases have until now linked sequences only to a taxonomic identification, together with sufficient metadata to ensure data traceability and sequence origin (e.g. Barcoding of Life Data Systems (BOLD), http://www.boldsystems.org/). However, this information is not enough to move forward to a routine biomonitoring with metabarcoding. Ecological functions or requirements (e.g. diatom indices values in our case) of taxa are unfortunately not provided in the existing barcoding databases. Providing such information in R-Syst::diatom should enable a routine use of metabarcoding for next-generation biomonitoring (87).

## Supplementary data

Supplementary data are available at *Database* Online.

## Acknowledgements

R-Syst database system has been supported by annual grants of Divisions EFPA and SPE of INRA given to BioGeCo for collaborative work in the network. VirtualBiodiversityL@b and Declic software have been built with a grant of Labex CEBA (Centre d'Etude de la Biodiversité Amazonienne) given to A.F. The following research programs enabled us to isolate and sequence the diatom strains: @speedID, Bibliothèque du vivant (French Barcoding of Life projects), IperRetro (ANR project, France), Mayotte project (ONEMA France), Diamed, Modelecotox (FNR projects, Luxembourg), L. Kermarrec PhD grant (Asconit Consultants and ANRT, France). The authors thank Agnès Rimet, Sonia Lacroix, Isabelle Huguet for their input in the update of the database. The co-operation with Sweden was possible via funding of the Swedish Agency for Marine and Water Management (HaV) and the Lakes and Watercourses Monitoring Program (FOMA-SLU). Dr Valerie Laval and Philippe Robin (INRA, UMR Bioger) are thanked for their involvement in the improvement and implementation of the R-Syst website. The authors thank Prof Elliot Shubert for revising

the English and scientific content of the paper and the two anonymous reviewers for their constructive comments.

*Conflict of interest.* None declared.

## References

1. Mann,D.G. and Vanormelingen,P. (2013) An inordinate fondness? The number, distributions and origins of diatom species. *J. Eukaryot. Microbiol.*, 60, 414–420.

2. Stevenson,R.J. (2014) Ecological assessments with algae: a review and synthesis. *J. Phycol.*, 50, 437–461.

3. Smol,J.P. and Stoermer,E.F. (2010) *The Diatoms: Applications for the Environmental and Earth Sciences*. 2nd edn. Cambridge University Press, Cambridge, United Kingdom, 667 p.

4. Kolkwitz,R. and Marson,M. (1908) Ökologie der pflanzliche Saprobien. *Ber. Dtsch. Bot. Ges.*, 26, 505–519.

5. Butcher,R.W. (1947) Studies in the ecology of rivers. IV. The algae of organically enriched water. *J. Ecol.*, 35, 186–191.

6. Hustedt,F. (1957) Die Diatomeenflora des Flusssystems der Weser im Gebiet der Hansestadt Bremen. *Abh. Nat. Ver. Bremen*, 34, 181–440.

7. Zelinka,M. and Marvan,P. (1961) Zur Prazisierung der biologischen Klassifikation der Reinheit fliessender Gewasser. *Arch. Hydrobiol*, 57, 389–407.

8. Rimet,F. (2012) Recent views on river pollution and diatoms. *Hydrobiologia*, 683, 1–24.

9. European Commission (2000) Directive 2000/60/EC of the European Parliament and of the Council of 23rd October 2000 establishing a framework for Community action in the field of water policy. Official Journal of the European Communities, 327, 1–72.

10. Barbour,M.T., Gerritsen,J., Snyder,B.D. et al. (1999) *Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish*. 2nd edn. EPA 841-B-99-002, US Environmental Protection Agency, Office of Water, Washington, DC, USA.

11. Round,F., Crawford,C.G. and Mann,D.G. (1990) The diatoms. *Biology and Morphology of the Genera*. Cambridge University Press., Cambridge, United Kingdom, 747 p.

12. Afnor (2004) NF EN 14407. Qualité de l'eau—Guide pour l'identification et le dénombrement des échantillons de diatomées benethiques de rivières, et leur interprétation. Afnor, pp. 1–13.

13. Besse-Lotoskaya,A., Verdonschot,P. and Sinkeldam,J. (2006) Uncertainty in diatom assessment: sampling, identification and counting variation. *Hydrobiologia*, 566, 247–260.

14. Hebert,P., Cywinska,A., Ball,S.L. et al. (2003) Biological identifications through DNA barcodes. *Proc. Biol. Sci.*, 270, 313–321.

15. Evans,K.M. and Mann,D.G. (2009) A proposed protocol for nomenclaturally effective DNA barcoding of microalgae. *Phycologia*, 48, 70–74.

16. Moniz,M.B.J. and Kaczmarska,I. (2009) Barcoding diatoms: is there a good marker? *Mol. Ecol. Resour.*, 9, 65–74.

17. Pompanon,F., Coissac,E. and Taberlet,P. (2011) Metabarcoding a new way to analyze biodiversity. *Biofutur*, 30, 30–32.

18. Kermarrec,L., Franc,A., Rimet,F. et al. (2013) Next-generation sequencing to inventory taxonomic diversity in eukaryotic communities: a test for freshwater diatoms. *Mol. Ecol. Resour.*, 13, 607–619.
19. Zimmermann,J., Glöckner,G., Jahn,R. et al. (2014) Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies. *Mol. Ecol. Res.*, 15/3, 526–542. DOI: 10.1111/1755-0998.12336.

20. Guillou,L., Bachar,D., Audic,S. et al. (2013) The protist ribosomal reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy. *Nucleic Acids Res.*, 41, D597–D604.

21. Quast,C., Pruesse,E., Yilmaz,P. et al. (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. *Nucleic Acids Res.*, 41, D590–D596.

22. Kermarrec,L., Franc,A., Rimet,F. et al. (2014) A next-generation sequencing approach to river biomonitoring using benthic diatoms. *Freshw. Sci.*, 33, 349–363.

23. Bouchez,A., Kermarrec,L., Rimet,F. et al. (2014) A Next-Generation Sequencing approach for river biomonitoring using benthic diatoms. Joint Aquatic Sciences Meeting, Portland (Oregon, USA), 18–23 May 2014. Abstract ID:14368, session 029 Aquatic Species Investigation: Environmental DNA Applications For Aquatic Ecosystems.

24. Benson,D.A., Cavanaugh,M., Clark,K. et al. (2013) GenBank. *Nucleic Acids Res.*, 41, 36–42.

25. Evans,K.M., Wortley,A.H. and Mann,D.G. (2007) An assessment of potential diatom “barcode” genes (cox1, rbcL, 18S and ITS rDNA) and their effectiveness in determining relationships in *Sellaphora* (Bacillariophyta). *Protist*, 158, 349–364.

26. Hamsher,S.E., Evans,K.M., Mann,D.G. et al. (2011) Barcoding diatoms: exploring alternatives to COI-5P. *Protist*, 162, 405–422.

27. Kermarrec,L., Bouchez,A., Rimet,F. et al. (2013) First evidence of the existence of semi-cryptic species and of a phylogeographic structure in the *Gomphonema parvulum* (Kützing) Kützing complex (Bacillariophyta). *Protist*, 164, 686–705.

28. Zimmermann,J., Jahn,R. and Gemeinholzer,B. (2011) Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. *Org. Divers. Evol.*, 11, 173–192.

29. Cox,E.J. (1981) The use of chloroplast and other features of living cell in the taxonomy of naviculoid diatoms. *6th Diatom Symposium*. Budapest, Hungary, Koeltz Scientific Books, Königstein, Germany. pp. 115–133.

30. Rimet,F. and Bouchez,A. (2012) Life-forms, cell-sizes and ecological guilds of diatoms in European rivers. *Knowl. Manag. Aquat. Ecosyst.*, 406, 1–14.

31. Lecointe,C., Coste,M. and Prygiel,J. (1993) “Omnidia”: software for taxonomy, calculation of diatom indices and inventories manAGMENT. *Hydrobiologia*, 269/270, 509–513.

32. Van Dam,H., Mertens,A. and Sinkeldam,J. (1994) A coded checklist and ecological indicator values of freshwater diatoms from the Netherlands. *Neth. J. Aquat. Ecol.*, 28, 117–133.

33. Kelly,M.G. and Whitton,B.A. (1995) The trophic diatom index: a new index for monitoring eutrophication in rivers. *J. Appl. Phycol.*, 7, 433–444.

34. Kahler,M. and Jarlman,A. (2009). Påväxt i rinnande vatten—kiselalgsanalys. In: *Handledning för miljöövervakning*. Metoder. Programområde: Sötvatten. Version 3:1. In: Miljöövervakningens metoder och undersökningsterper inom

programområde Sötvatten. Hav- och vattenmyndighetens online document, 19 p.

35. Cemagref (1982) Etude des méthodes biologiques quantitative d'appréciation de la qualité des eaux. Rapport Q.E.Lyon-A.F. Bassin Rhône-Méditerranée-Corse, 218 p.

36. Keck,F., Bouchez,A., Franc,A. and Rimet,F. (2016) Linking phylogenetic similarity and pollution sensitivity to develop ecological assessment methods: a test with river diatoms (microalgae). *Journal of Applied Ecology*, accepted.

37. Guiry,M.D. and Guiry,G.M. (2014) *AlgaeBase*. World-wide electronic publication, National University of Ireland, Galway. http://www.algaebase.org (24 November 2014, date last accessed).

38. Kusber,W.H., Abarca,N., Skibbe,O. et al. (2012) Reference library of DNA-barcoded diatoms—A use case for publishing data via the GBIF database AlgaTerra. Book of abstracts of the 22nd International Diatom Symposium, Ghent, Belgium, 26-31 August 2012, p. 65.

39. Franc,A. (2014) A primer for MIAB INRA UMR. *Biogeoce Report*, INRA, Cstas, France, 31 p.

40. Smith,T.F. and Waterman,M.S. (1981) Identification of common molecular subsequences. *J. Mol. Biol.*, 147, 195–197.

41. Fruchterman,T.M.J. and Reingold,E.M. (1991) Graph drawing by force-directed placement. *Software-Pract. Exper.*, 21, 1129–1164.

42. Gouy,M., Guindon,S. and Gascuel,O. (2010) SeaView Version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. *Mol. Biol. Evol.*, 27, 221–224.

43. Tamura,K., Peterson,D., Peterson,N. et al. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. *Mol. Biol. Evol.*, 28, 2731–2739.

44. Monnier,O., Coste,M. and Rosebery,J. (2009) Une classification des taxons de l'Indice Biologique Diatomées (IBD, norme AFNOR NF T90-354, décembre 2007). *Diatomania*, 13, 17–47.

45. Kermarrec,L., Ector,L., Rimet,F. et al. (2011) A preliminary phylogenetic analysis of the Cymbellales based on 18S rDNA gene sequencing. *Diatom Res.* 26, 305–315.

46. Rimet,F., Kermarrec,L., Bouchez,A. et al. (2011) Molecular phylogeny of the family Bacillariaceae based on 18S rDNA sequences: focus on freshwater *Nitzschia* of the *Lanceolatae* section. *Diatom Res.* 26, 273–291.

47. Rimet,F., Trobajo,R., Mann,D.G. et al. (2014) When is sampling complete? The effects of geographical range and marker choice on perceived diversity in *Nitzschia* palea (Bacillariophyta). *Protist*, 165, 245–259.

48. Larras,F., Keck,F., Montuelle,B. et al. (2014) Linking diatom sensitivity to herbicides to phylogeny: a step forward for biomonitoring? *Environ. Sci. Technol.*, 48, 1921–1930.

49. MacGillivary,M.L. and Kaczmarska,I. (2011) Survey of the efficacy of a short fragment of the rbcL gene as a supplemental DNA barcode for diatoms. *J. Eukaryot. Microbiol.*, 58, 529–536.

50. Bruder,K. and Medlin,L.K. (2008) Morphological and molecular investigations of Naviculoid Diatoms. II. selected genera and families. *Diatom Res.*, 23, 283–329.
51. Bruder,K. and Medlin,L.K. (2008) Morphological and molecular investigations of Naviculoid Diatoms. III. *Hippodonta Navicula* S.S. *Diatom Res.*, 23, 331-347.

52. Medlin,L.K. (2011) A Review of the evolution of the diatoms from the origin of the lineage to their populations. In: Seckbach,J., Kociolek,J.P. (eds). *The Diatom World*. Springer Science+Business Media B.V., Germany. pp. 93-118.

53. Theriot,E.C., Ashworth,M.P., Nakov,T. et al. (2015) Dissecting signal and noise in diatom chloroplast protein encoding genes with phylogenetic information profiling. *Mol. Phylogenet. Evol.*, 89, 28-36.

54. Medlin,L., Elwood,H.J., Stickel,S. et al. (1988) The characterization of enzymatically amplified eukaryotic 16S rRNA-coding regions. *Gene*, 71, 491-499.

55. Theriot,E.C. and Serieyssol,K. (1994) Phylogenetic systematics as a guide to understanding features and potential morphological characters of the centric diatom family Thalassiosiraceae. *Diatom Res.*, 9, 429-450.

56. Shcherbakova,T.A., Kiril'chik,S.V., Likhoshvai,E.V. et al. (1998) Phylogenetic position of diatom algae of the genus *Aulacoseira* from Lake Baikal based on the results of the comparison of 18S rRNA gene nucleotide sequences. *Mol. Biol. Moscow*, 32, 735-740.

57. Edgar,S.M. and Theriot,E.C. (2004) Phylogeny of *Aulacoseira* (Bacillariophyta) based on molecules and morphology. *J. Phycol.*, 40, 772-788.

58. Medlin,L.K. and Kaczmarska,I. (2004) Evolution of diatoms: V. Morphological and cytological support for the major clade and a taxonomic reivsion. *Phycologia*, 43, 245-270.

59. Alverson,A.J., Jansen,R.K. and Theriot,E.C. (2007) Bridging the rubicon: phylogenetic analysis reveals repeated colonizations of marine and fresh waters by thalassiosiroid diatoms. *Mol. Phylogenet. Evol.*, 45, 193-210.

60. Luddington,I.A., Kaczmarska,I. and Lovejay,C. (2012) Distance and character-based evaluation of the V4 region of the 18S rRNA Gene for the identification of diatoms (Bacillariophyceae). *PLoS One*, 7, 1-11.

61. Whittaker,K., Rignanese,D., Olson,R. et al. (2013) Molecular subdivision of the marine diatom Thalassiosira rotula in relation to geographic distribution, genome size, and physiology. *BMC Evol. Biol.* 12, 1-14.

62. Kaeriyama,H., Katsuki,E., Otsubo,M. et al. (2011) Effects of temperature and irradiance on growth of strains belonging to seven Skeletonema species isolated from Dokai Bay, southern Japan. *Eur. J. Phycol.*, 46, 113-124.

63. Alverson,A.J. and Kolnick,L. (2005) Intragenomic nucleotide polymorphism among small subunit (18s) rDNA paralogs in the diatom genus Skeletonema (Bacillariophyta). *J. Phycol.*, 41, 1248-1257.

64. Kooistra,W., Sarno,D., Balzano,S. et al. (2008) Global diversity and biogeography of *Skeletonema* species (Bacillariophyta). *Protist*, 159, 177-193.

65. Trobajo,R., Clavero,E., Chepurnov,V. et al. (2009) Morphological, genetic and mating diversity within the widespread bioindicator *Nitzschia palea* (Bacillariophyceae). *Phycologia*, 48, 443-459.

66. Trobajo,R., Mann,D.G., Clavero,E. et al. (2010) The use of partial cox1, rbcL and LSU rDNA sequences for phylogenetics and species identification within the Nitzschia palea species complex (Bacillariophyceae). *Eur. J. Phycol.*, 45, 413-425.

67. Abarca,N., Jahn,R., Zimmermann,J. et al. (2014) Does the cosmopolitan diatom *Gomphonema parvulum* (Kutzing) Kutzing Have a Biogeography? *PLoS One*, 9, 1-18.

68. Evans,K.M., Chepurnov,V.A., Sluiman,H.J. et al. (2009) Highly differentiated populations of the freshwater diatom *Sellaphora capitata* suggest limited dispersal and opportunities for allopatric speciation. *Protist*, 160, 386-396.

69. Evans,K.M., Wortley,A.H., Simpson,G.E. et al. (2008) A molecular systematic approach to explore diversity within the *Sellaphora pupula* species complex (Bacillariophyta). *J. Phycol.*, 44, 215-231.

70. Mann,D.G., McDonald,S.M., Bayer,M.M. et al. (2004) The *Sellaphora pupula* species complex (Bacillariophyceae): morphometric analysis, ultrastructure and mating data provide evidence for five new species. *Phycologia*, 43, 459-482.

71. Lundholm,N., Bates,S.S., Baugh,K.A. et al. (2012) Cryptic and pseudo-cryptic diversity in diatoms with descriptions of *Pseudo-Nitzschia hasleana* Sp Nov and *P. fryxelliana* Sp Nov. *J. Phycol.*, 48, 436-454.

72. Lundholm,N., Moestrup,O., Kotaki,Y. et al. (2006) Inter- and intraspecific variation of the *Pseudo-nitzschia delicatissima* complex (Bacillariophyceae) illustrated by rRNA probes, morphological data and phylogenetic analyses. *J. Phycol.*, 42, 464-481.

73. Beszteri,B., Acs,E., Makk,J. et al. (2001) Phylogeny of six naviculoid diatoms based on 18S rDNA sequences. *Int. J. Syst. Evol. Microbiol.*, 51, 1581-1586.

74. Bruder,K., Sato,S. and Medlin,L.K. (2008) Morphological and molecular investigations of naviculoid diatoms IV. *Pinnularia* Vs. *Caloneis Diatom*, 24, 8-24.

75. Bruder,K. and Medlin,L.K. (2007) Molecular assessment of phylogenetic relationships in selected species/genera in the naviculoid diatoms (Bacillariophyta). I. The genus *Placoneis. Nova Hedwigia*, 85, 331-352.

76. Souffreau,C., Verbruggen,H., Wolfe,A. et al. (2011) A time-calibrated multi-gene phylogeny of the diatom genus *Pinnularia*. *Mol. Phylogenet. Evol.*, 61, 866-879.

77. Rimet,F. (2009) Benthic diatom assemblages and their correspondence with ecoregional classifications: case study of rivers in north-eastern France. *Hydrobiologia*, 636, 137-151.

78. Kelly,M.G., Juggins,S., Guthrie,R. et al. (2007) Assessment of ecological status in UK rivers using diatoms. *Freshw. Biol.*, 1111, 1365-2427.

79. King,L., Clarke,G., Bennion,H. et al. (2006) Recommendations for sampling littoral diatoms in lakes for ecological status assessments. *J. Appl. Phycol*, 18, 15-25.

80. Berthon,V., Bouchez,A. and Rimet,F. (2011) Use of diatom lifeforms and ecological guilds to assess pollution in rivers: case study of south-eastern french rivers. *Hydrobiologia*, 673, 259-271.

81. Passy,S.I. (2007) Diatom ecological guilds display distinct and predictable behavior along nutrient and disturbance gradients in running waters. *Aquat. Bot.*, 86, 171-178.
82. Zimmermann,J., Abarca,N., Enke,N. et al. (2014) Taxonomic reference libraries for environmental barcoding: a best practice example from diatom research. *PLoS One*, 9, 1-24.

83. CEN. (2014) *Water quality—Technical report for the management of diatom barcodes for ecological status assessment*, European Committee for Standardization (CEN), Brussels, Belgium, 7 p.

84. Kermarrec,L. (2012) Apport des outils de la biologie moléculaire pour l'utilisation des diatomées comme bioindicateurs de la qualité des écosystèmes aquatiques lotiques et pour l'étude de leur taxonomie. Ph.D. Thesis. Grenoble University, France, 297 p.

85. Trobajo,R., Rovira,L., Ector,L. et al. (2013) Morphology and identity of some ecologically important small *Nitzschia* species. *Diatom Res.*, 28, 37–59.

86. Kelly,M.G., Trobajo,R., Rovira,L. et al. (2015) Characterizing the niches of two very similar *Nitzschia* species and implications for ecological assessment. *Diatom Res.*, 30, 27–33.

87. Baird,D.J. and Hajibabaei,M. (2012) Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. *Mol. Ecol.*, 8, 2039–2044.