dataesr/scientific-paragraphs-categorization huggingface dataset:
To overcome the limit of use of a single dataset per infection time, we used the temporal clustering of samples to group infection times sharing similar expression pattern of genes. The limit of this approach is a higher dispersion than that expected of exact biological replicates which reduces the identification of differentially expressed genes. Nevertheless, it offers a first insight into modification of host expression. Indeed, using this approach on A. castellanii nuclear genes expressionwe identified a clear transcription downregulation of some ribosomal protein encoding genes similar to what is reported in amoeba undergoing encystment  (Schulze and Jantzen, 1982; Matthews et al. , 1995). Parallelly, the mitochondrial transcription showed a global decreased, while maintaining the general distribution of gene expression levels between functional groups of genes independently of the infection time.
FUNDING This work was supported by the  French Government  under the " Investissements d'avenir" program  managed by the  Agence Nationale de la Recherche (ANR) , [reference: Méditerranée-Infection  10-IAHU-03 ], by  Région Provence-Alpes-Côte d'Azur and European funding FEDER PRIMI. R. A. L. R. scholarship was provided by  CNPq  and  CAPES.
DATA AVAILABILITY STATEMENT The sequencing data from this study have been submitted to the NCBI Short Read Archive (http://www. ncbi. nlm. nih. gov/Traces/ sra/sra. cgi) under the accession number ERP117375. DATA SHEET S1 | Gene function and temporal class (complement to Figure  2 ). The order of genes presented here by each temporal class is related to the order they are shown in Figure  2B.
The Maroni is one of the most speciose basins of the Guianas and hosts a megadiverse freshwater fish community. Although taxonomical references exist for both the Surinamese and Guyanese parts of the basin, these lists were mainly based on morphological identification and there are still taxonomical uncertainties concerning the status of several fish species. Here we present a barcode dataset of 1,284 COI sequences from 199 freshwater fish species (68. 86% of the total number of strictly freshwater fishes from the basin) from 124 genera, 36 families, and 8 orders. DNA barcoding allowed for fast and efficient identification of all specimens studied as well as unveiling a consequent cryptic diversity, with the detection of 20 putative cryptic species and 5 species flagged for re-identification.
Introduction With over 32,000 known species, fishes represent more than half of the total number of vertebrates. Although 3,900 new species have been described during the last decade  (Nelson, Grande, & Wilson, 2016)  and 100 are described per year in the Neotropics only  (Birindelli & Sidlauskas, 2018) , the ultimate goal of cataloguing all fishes is still far from being achieved. DNA barcoding using the mitochondrial cytochrome c oxidase I gene, or COI  (Hebert, Cywinska, Ball, & DeWaard, 2003) , has proven to be a powerful tool to quicken and facilitate the global effort of species identification and discovery  (Barrett & Hebert, 2005; Goldstein & DeSalle, 2011; Gomes, Pessali, Sales, Pompeu, & Carvalho, 2015). This has led to the foundation of the BOLD platform, an ever-growing COI database of animal organisms  (Ratnasingham & Hebert, 2007).
In this context, several studies have already been carried out on the megadiverse Neotropical freshwater fish community with focuses on rivers and lakes of  Brazil (de Carvalho et al. , 2011; Nascimento et al. , 2016; Berbel-Filho et al. , 2018) , Argentina  (Rosso, Mabragaña, González Castro, & Díaz de Astarloa, 2012; Díaz et al. , 2016) ,  Mexico, and Guatemala (Valdez-Moreno, Ivanova, Elías-Gutiérrez, Contreras-Balderas, & Hebert, 2009). All of them have emphasised the efficacy of DNA barcoding for this model with successful species discrimination rates ranging from 90 to 100%. In this context, the Gui-BOL project by  Covain et al. (http://www. boldsystems. org/index. php/MAS_Management_DataConsole?codes=GBOL) is a work group affiliated to the FishBOL campaign  (Ward, Hanner, & Hebert, 2009 ) that aims at building a reference DNA barcode database for all fishes of the Guianas.
There is a growing number of methods and tools available to use genetic and spatial information in order to explore the biogeographical patterns of species and populations  (Chan, Brown, & Yoder, 2011). One of them is the mapping of spatial patterns through "genetic landscapes"  (Manel, Schwartz, Luikart, & Taberlet, 2003). This method can assist in identifying divergence hotspots  (Wood et al. , 2013)  and potential barriers to gene flow  (Vodȃ, Dapporto, Dincȃ, & Vila, 2015)  and has already been used on genetic distances between COI sequences to provide a visual framework of genetic variation between organisms across space  (Arbeláez-Cortés, Milá, & Navarro-Sigüenza, 2014; Mamos, Wattier, Burzyński, & Grabowski, 2016). The present study makes use of a large new dataset of DNA barcodes to (1) assess the validity of the current references on the Maroni's freshwater fish species richness, (2) reveal the presence of genetic heterogeneity in order to flag potential cryptic species, and (3) investigate spatial genetic distribution within species that may reveal obstacles to connectivity across the watershed, or the presence of recent colonisation from adjacent rivers.
Fish molecular identification and barcode analysis The barcode sequence data was used in conjunction with morphology and known geographical distribution (an integrative approach similar to  Gomes et al. (2015)  and  Pugedo, de Andrade Neto, Pessali, Birindelli, & Carvalho (2016)  to flag potential identifications errors, identify unknown specimens (e. g. juveniles), and detect putative cryptic species. Molecular identification was performed with BOLD Identification System (www. boldsystems. org), BLAST search  (Altschul, Gish, Miller, Myers, & Lipman, 1990)  on NC-BI (http://www. ncbi. nlm. nih. gov/BLAST) and by neighbour-joining tree based identification. Specimens showing a combination of unexpected intra-specific genetic divergence (both in our dataset and on the global BOLD database), overlooked morphological cues, and support from distribution patterns were flagged as putative cryptic species, given provisional new names, and treated as distinct species in all subsequent analyses.
All genetic distance analyses were performed under the Kimura two-parameter (K2P) substitution model  (Kimura, 1980) , as it is a standard metric in barcode studies  (Ward, 2009; Díaz et al. , 2016). Sequence divergences at the Species, Genus, and Family level were estimated using the BOLD Distance Summary Tool (BOLD Aligner, pairwise deletions). BOLD's Barcode Gap Analysis (same parameters) was used to investigate species who do not comply with barcode gap (i. e. for which distance to the Nearest Neighbour (NN) is lower than the standard barcode threshold of 2% or lower than the maximum intra-specific distance). The BIN Discordance Report tool was used to analyse the final dataset using the clustering method provided by BOLD: the Barcode Index Number  (BIN, Ratnasingham & Hebert, 2013)  which is the standard method in barcode studies to attribute each specimen to a new or pre-existing operational taxonomic unit.
If the p-values were greater or equal to 0. 05, IDW was performed directly on uncorrected K2P distances. For IDW, midpoints coordinates between pairs of samples locations connected by a Delaunay triangulation (i. e. the smallest network with non-overlapping edges) were extracted for each species with the phylin package 2. 0  (Tarroso, Carvalho, & Velo-Antón, 2019). Respective K2P distance values (or geographically corrected K2P distances) between pair of samples were assigned to each respective midpoint, and IWD (as implemented in phylin with default weighting method "Shepard") was used to interpolate the Z values of each coordinate in the grid within the whole species' sampling area. Real and interpolated K2P distance values or residuals were normalised to enable comparison of heterogeneous genetic divergence rates among species and then projected on basin maps using the raster package 2.
9-5  (Hijmans, 2019). IDW interpolations of species for which all pairwise distances were equal to zero were calculated and projected directly using these raw zero values. The global patterns of genetic divergence across the basin ("multispecies landscape") were visualised by projecting the arithmetic mean of all previously generated normalised overlapping surfaces. We then sought to ordinate genetic landscapes based on similar genetic divergence patterns in order to explore shared trends among species and ultimately assign each species to a broader cluster group. Ordination was performed through Principal Component Analysis (PCA). For this, a genetic landscape data table was compiled with Z values as estimates of genetic divergence for each species listed in rows and each grid cell in the basin in columns, resulting in a table of 129 rows and 60,675 columns.
Because genetic landscapes had different sizes depending of the species sampling area, many Z values were missing in the table. These missing values were replaced by the values for the corresponding coordinate pair from the multispecies landscape with MCRestimate package 2. 38-0  (Johannes et al. , 2018). The multispecies landscape was then treated as the "null genetic landscape" of the basin. The PCA was performed using the variance-covariance matrix of the data table using ade4 1. 7-13. Since the variables consisted of tens of thousands of coordinate points, their projection on the principal components were visualised as points with two separate colour gradient codes respectively representing latitudes (from red to orange to yellow) and longitude (purple to blue to green). In order to cluster genetic landscapes into general patterns, the canonical pairwise distance matrix of the row coordinates of informative axes of the PCA was submitted to an agglomerative hierarchical clustering analysis.
Barcode dataset The 1,284 COI sequences collected from the Maroni Basin generated a final barcode data library of 199 species (125 Genera, 36 Families, and 8 Orders) after integrative re-identification (Figure  2 ). Five out of these species were flagged for being putative re-identifications from the latest Maroni checklists, with the nominal species being presumably absent from the basin (Table  3 ), and 20 are putative cryptic species that were revealed by our integrative approach for identification, among which 13 are already BIN-concordant on the BOLD database (Table  3 ). All species in the data set belong to the class Actinopterygii with the exception of Potamotrygon marinae from the class Elasmobranchii. The number of individuals per species ranged from 1 to 59 (mean=6. 45) with 169 species represented by more than one specimen (84.
The neighbour-joining dendrogram showed no overlap between any species, except only for Corydoras aff. geoffroy , which was nested within the Corydoras geoffroy cluster (Figure  3 , Supplementary Material 3). Two hundred twenty nine BINs were assigned by BOLD to the total number of samples in the dataset, among which 171 were taxonomically concordant (represented by 1,195 specimens) and 55 were singletons (i. e. were assigned to only one specimen from this dataset). The remaining three BINs (32 specimens) showed some discordance and were represented by three pairs of species that shared the same BIN in our dataset: Guyanancistrus brevispinis / Guyanancistrus nassauensis , Corydoras geoffroy / Corydoras aff. geoffroy and Melanocharacidium sp. 1 /Melanocharacidium sp. 2 (Figure  3 ). Two specimens (oneSerrasalmus rhombeus and one Peckoltia otali ) were not assigned any BINs, probably due to a high proportion of ambiguous bases for the latter (14Ns/652bp).
However, both specimens clustered perfectly with their conspecifics, so they can be reasonably considered well identified. Among concordant BINs, species that were assigned more than one BIN in our dataset are: Aequidens tetramerus , Bryconamericus guyanensis , Characidium zebra , Cleithracara maronii ,Crenicichla multispinosa , Eigenmannia virescens ,Erythrinus erythrinus , Farlowella reticulata ,Gymnotus anguillaris , Hemiodus huraulti , Hoplias malabaricus , Hypopygus lepturus , Ituglanis amazonicus ,Moenkhausia moisae , Moenkhausia oligolepis ,Nannostomus bifasciatus , Pimelodella leptosoma ,Poptella brevispina with two BINs; Cetopsidium orientale ,Crenicichla albopunctata, Helogenes marmoratus ,Hyphessobrycon roseus , Phenacogaster wayana ,Pimelodella cf. cristata with three BINs, andGasteropelecus sternicla with four BINs (Figure  3 , Supplementary Material 3).
aff. cristata , see below). Tree based identification on the global database shows that this cluster of specimens is widely distributed (several rivers of Suriname and French Guiana) and actually branches far from P. cristata and P. cf. cristata , with its sister barcode species being Pimelodella macturki. However, although allP. aff. cristata on BOLD share the same BIN, it also includes two specimens identified as P. vittata and sevenPimelodella sp. , making it currently discordant.
Checklists updates: Putative new cryptic species The 13 putative new species that were BIN concordant on the BOLD database (Table  3 ) are as follows: (1) Ancistrus sp. is represented by one specimen from the remote Mitaraka Mountains that had a similar morphology to Ancistrus temminckii. However, Tree Based Identification analysis (Figure  3 , Supplementary Material 3) placed it as a distinct sister group to a clade composed of Ancistrus cf. leucostictus and A. temminckii. (2) Bryconops aff. melanurus : two specimens from Langa Sula and Saut Wayo (Marouini) showed a dNN greater than 12% with the four Bryconops melanurusthat were caught in the same two locations. They share the same BIN with four specimens from Sinnamary, Suriname and Mana rivers that were also re-identified as B. aff. melanurus on BOLD database.
(3) The eight specimens of Corydoras aff. guianensis , differing from the nominal species by a faint black margin along the dorsal-fin spine, constituted the sister group of the blunt snoutedCorydoras aff. breei (lineage 9 in  Alexandrou & Taylor (2011) ) and the nominal species C. guianensis in our dataset with a minimum K2P distance of respectively 5. 49% and 5. 13%. The fiveC. guianensis specimens available were caught in the Tapanahony and Paloemeu rivers in Suriname (type locality of C. guianensisbeing Nickerie River in Suriname) while the eight C. aff. guianensis came from the east tributaries in French Guiana. (4)Cyphocharax aff. spilurus 2 was first morphologically identified as C. spilurus but showed a dNN of 13. 84% with all other C. spilurus and 8. 59% with C. cf. spilurus(see below), while the shortest dNN was 7.
40% with C. biocellatus. This specimen was caught in the same location as sevenC. spilurus in the Tapanahony, while the two other C. spilurus were caught in the east tributaries. It displays a large dark spot on the caudal peduncle, and shares a BIN on the BOLD database with another Cyphocharax aff. spilurus 2 from Sipaliwini River (Suriname). Although not present in the two checklists, C. aff. spilurus 2 was already known to occur in the Maroni and suspected to live in sympatry with C. spilurus  (Planquette et al. , 1996). This putative species is different from C. aff. spilurus sensuLe  Bail et al. (2012)  described from Approuague and Iracoubo. (  5 ) The three juvenile specimens of Guianacara sp. Tapanahony showed a minimum dNN of 3. 26% with G. owroewefi from our dataset. They were all caught in the Paloemeu River in sympatry with G.
owroewefi. None of them display the diagnostic pattern of G. oelemariensis described from upper Marowijne River in Suriname and were thus treated as an unknown species. (6) Hemigrammus aff. guyanensis from Litany River likely corresponds to the form illustrated for H. guyanensis in  Planquette et al. (1996). However, the true H. guyanensis is illustrated in  Mol (2012)  asH. aff. ocellifer. Specimens from Tapanahony River correspond to this form and are here re-identified as H. guyanensis. They are characterised by a longitudinal black line, and a distinct iridescent spot on upper part of caudal peduncle. Specimens from Litany lack this last characteristic. (  7 ) Leptocharacidiumsp. : This non-identified specimen caught in Wayu Camp (Paloemeu) and firstly assigned to Melanocharacidium was peculiar in showing a very high genetic distance from all other closest species in our dataset (dNN=17.
71% with Parodon guyanensis instead of another Crenuchidae species) and on the BOLD database (dNN=14. 04% with aCharacidium sp. from Bolivia). It also has an unusual morphology, i. e. a small operculary spot and a longitudinal line, but lacks the diagnostic two unbranched rays in pelvic fins. It is tentatively placed in Leptocharacidium , awaiting further analyses. (  8 ) Six specimens first identified as Moenkhausia collettii from Litany and Sector Apsik were renamed Moenkhausia aff. collettii after showing a very high dNN of 15. 33% with previously recorded M. collettii from French Guiana in our dataset. (9) Nannacara sp. Litany was represented by a single specimen in his own BIN. It is the first occurrence of a Nannacara found in the Maroni basin and showed a minimum dNN of 10. 49% with other Nannacara from the BOLD database, including the two Nannacara species that occur in French Guiana: N.
aureocephalus and N. anomala. (10) The ten Pimelodella geryi specimens clustered into two clear groups in the neighbourjoining tree (Supplementary Material 3). The first group included specimens from the west (Tapanahony) and the east of the basin, while the second cluster included only specimens from the west. Although the dNN between these two groups is relatively low (1. 47), the second cluster exclusive to the west basin has its own concordant BIN and was flagged as a potential P. aff. geryi. (11)Pimelodella cf. cristata : Although Pimelodella cristata is present in the Maroni checklists, tree based identification of available close specimens from BOLD database coupled with observation of catch localities seem to indicate that the nominal species, described from Takutu River in Guyana, is present in the Corantijn River in Suriname but not in any basin of French Guiana.
Instead, two potentially undescribed species formerly identified as P. cristata occur in the Maroni: Pimelodella cf. cristata andPimelodella aff. cristata. According to Tree Based Identification, Pimelodella cf. cristata , which is present in several rivers of Suriname as well as the Maroni, is the closer of the two from the nominal P. cristata (although its NN is actually Pimelodella sp. ). It is represented by five specimens in our dataset that are split in three concordant BINs. (  12 ) One unidentified Pimelodella sp. from Paloemeu shows a high distance with its NN (P. geryi , 8. 59) and its sister group (P. megalops , 9. 58) in our dataset. Tree based identification on BOLD database showed that this specimen is most closely related to another group of unidentified Pimelodella from another basin in Sipaliwini.
(  13 ) Three unidentifiedRineloricaria specimens were caught in the Paloemeu River and were named Rineloricaria aff. stewarti 2. They constitute a sister species of an undescribed species from western Suriname. Their dNN in our dataset was 9. 95% with Rineloricaria aff. stewarti 3 (Rineloricaria aff. stewarti sensu Le Bail et al. (  2012 )), a species broadly distributed in French Guiana and eastern Suriname. Four putative cryptic species were BIN concordant in our dataset but not on the BOLD database (Table  3 ): (1) Cyphocharax cf. spilurus sister group was a group composed of C. biocellatus specimens in our dataset, as opposed to the C. spilurus cluster that branched further. However, this specimen showed morphological differences (e. g. absence of the lateral spot) withC. biocellatus and a high dNN of 7.
27. On the BOLD database, it shares a BIN with five other C. cf. spilurusfrom other rivers in Suriname and seven specimens from Guyana identified as C. spilurus by other authors. (2) While all Eigenmanniacf. limbata specimens shared a BIN with specimens identified asE. limbata and E. nigra , tree based identification strongly implies that E. limbata is a Surinamese species while E. cf. limbata is a French Guianese species. Moreover, all E. cf. limbata specimens display a black humeral spot that is not present in E. limbata. (3) Gymnotus aff. carapo: one specimen from Wawapsi Creek (Paloemeu) showed a dNN of 7. 30% with the G. carapo specimens in our dataset. It shares the same BIN with three specimens from Brazil identified as G. carapo on BOLD database. However, tree based identification shows that G.
aff. carapo and these three Brazilian specimens constitute a group situated very far from all othersG. carapo from several locations (Suriname, Brazil, Guyana and French Guiana) on BOLD database and that their sister group is composed of several G. pantana and unidentified Gymnotus. Gymnotus carapo is known to be a widespread species in South America and contains several sub-species  (Craig, Crampton, & Albert, 2017). (  4 ) Despite a similar colour pattern with the nominal species, one Sternopygus cf. macrurus from Tampok shows a high dNN of 13. 96% with other S. macrurus specimens from our dataset. Tree based identification shows that K2P distances among specimens identified as S. macrurus on BOLD database are particularly high and that this species seems to consist of a complex of several operational taxonomic units.
The two closest S. macrurus to ourS. cf. macrurus came from Suriname and Ecuador. Three putative cryptic species showed BIN discordance in our dataset after integrative identification (Table  3 ). (1) The two Corydorasaff. geoffroy specimens shared the same BIN as C. geoffroy. They are also nested in the C. geoffroy complex in the neighbour-joining dendrogram. However, there is still strong assumptions that it could be a cryptic species. The main hint is that some unidentified Corydoras that live in sympatry with C. geoffroy in the Litany River (Sector Apsik) display a dark lateral stripe that is not present on C. geoffroy. Although these striped specimens share the same mitochondrial DNA sequence as C. geoffroy , we decided to flag these specimens as C. aff. geoffroy waiting for further evidence on the status of these morphs.
(2) Melanocharacidium sp. 1 (two specimens from Wawapsi Creek, Paloemeu) and sp. 2 (one specimen from Wayu Camp, Paloemeu and two from Sector Apsik, Litany) share the same BIN and are a different group than other Melanocharacidium species on BOLD database with a dNN of 16. 30% with M. blennioides. They were kept split as sp. 1 and sp. 2 as the Wayu Camp specimen in the Surinamese Paloemeu River displays a much shorter genetic distance with the two Litany specimens in French Guiana than with the other two specimens from Paloemeu, which could indicate a potential genetic flow barrier between sp. 1 and sp. 2 although they can occur in the same river. Species from the Crenuchidae family are still under-studied, as undescribed Crenuchidae may be present in Suriname, especially in the Interior of the country  (Mol, 2012).
Barcode Gap Apart from the new putative species cited above, only three pairs of species from the final dataset were below the 2% barcode gap (Table  5 ). Among them, the only ones that shared the same BIN in our dataset and on BOLD were Guyanancistrus brevispinis and G. nassauensis(dNN=0. 62%). However, G. nassauensis is morphologically very distinct from G. brevispinis and has been formally described in detail  (Fisch-Muller et al. , 2018). Moreover, mitochondrial introgression between the two species has been reported, which explains this shared COI haplotype. The remaining two pairs, Ancistrus cf. leucostictus / Ancistrus temminckii (dNN=1. 84%) andHypostomus plecostomus / Hypostomus watwata (dNN=1. 94%) still bear little doubt on their species delimitation. Each of the four species have their own associated BIN, and their dNN is still relatively high and close to the classical 2%.