dataesr/scientific-paragraphs-categorization huggingface dataset:
Most Peronia mitochondrial and nuclear sequences in our molecular data set are new (Table  2 ). New mitochondrial COI and 16S sequences are provided for 169 individuals, and COI and 16S sequences for ten specimens are from a previous study  (Dayrat et al. 2011 ; see below). In addition, all COI sequences in Gen-Bank and BOLD closely related to Peronia sequences in our dataset were examined, and COI sequences for eleven individuals were selected to be included in phylogenetic analyses (Table  2 ; see below). All nuclear 28S and ITS2 sequences are new except for two individuals which have been used as outgroups in several of our previous studies: [  from  Okinawa and [706]  from Hawaii (Table  2 ). COI sequences publicly available. Eleven COI sequences obtained from Gen-Bank (10) and BOLD (1) were added to our own data set (179 COI sequences) for a total of 190 sequences.
Four COI sequences are from China  (Sun et al. 2014) , two from Singapore  (Chang et al. 2018) , two from Japan  (Takagi et al. 2019) , one from the Persian Gulf (unpublished), one from Gujarat, western India (unpublished), and one from Iran  (Maniei et al. 2020a). All those sequences were merely referred to as Peronia sp. , except for the specimens from China (referred to as Peronia verruculata), the specimen from western India (referred to as Onchidium verruculatum), and the specimen from Iran (recently described as P. persiae, a name regarded here as a synonym of P. verruculata, unit #4). Correct identifications are provided here for all those sequences (Table  2 ). Note that in the case of duplicate sequences available in GenBank, only one representative was selected. So, for instance,  Chang et al.
(2018)  published many Peronia COI sequences that cluster in two mitochondrial units which they refer to as "Singapore clade" and "Peronia sp. 2 clade. " One sequence for their "Singapore clade" and one sequence for their "Peronia sp. 2 clade" are included here, which is enough to demonstrate that their two units correspond to our two mitochondrial units #1 and #3 of Peronia verruculata. Also, all COI sequences by  Maniei et al. (2020a)  for P. persiae cluster together within the unit #4 of P. verruculata, so only one of those individuals is included in our analyses: one individual is enough to demonstrate that P. persiae is a junior synonym of P. verruculata. A 16S sequence is available for the individual from Iran  (Maniei et al. 2020a) ; no 16S sequences are available for any of the other COI sequences from GenBank and BOLD, so gaps were inserted in the mitochondrial concatenated alignment.
2018b. All new DNA sequences were deposited in GenBank and vouchers deposited in museum collections (Table  2 ). The ends of each alignment were trimmed. Alignments of mitochondrial (COI and 16S) sequences and nuclear (ITS2 and 28S) sequences were concatenated separately in order to test whether these two data sets support the same relationships. The concatenated mitochondrial alignment included 1014 nucleotide positions: 614 (COI) and 400 (16S). The concatenated ITS2 and 28S alignment included 1544 nucleotide positions: 535 (ITS2) and 1009 (28S). The haplotype ITS2 alignment (in which identical sequences were grouped into a single haplotype sequence) included 740 nucleotide positions. Three independent sets of phylogenetic analyses were performed: 1) Maximum Likelihood and Bayesian analyses with concatenated mitochondrial COI and 16S sequences; 2) Maximum Parsimony analyses with concatenated nuclear ITS2 and 28S sequences; 3) Maximum Parsimony analyses with ITS2 haplotype sequences.
; ANSP 57967. • 1 specimen 28/25 mm; Viti Levu, Namuka; 18°08'S, 177°23  'E; 18 Apr 1917; S Bock's Pacific Expedition 1917 -1918     GenBank sequence. One COI sequence was obtained from GenBank (LC390402) for an individual identified as Peronia sp. and collected from Okinawa, Japan  (Takagi et al. 2019) , which is the northernmost confirmed locality for Peronia peronii. Distribution (Fig. 6 ). Given that our fresh molecular samples of P. peronii from the West Pacific (Guam, Papua New Guinea) are conspecific with those from Mauritius, it is assumed here that all individuals with a long spine of the accessory penial gland belong to the same species. Strictly speaking, however, the presence of P. peronii from places like Zanzibar, the Maldives, Nicobar Islands, West Papua, Timor, Palau, New Caledonia, and Tonga, would still need to be validated with fresh material.
The three labels of the other jar (MNHN-IM-2014-7993) say: "Peronia Mer Rouge Mr Jousseaume n°15, 1892," "Oncidium [written over "Oncidiella"] peronii Cuvier Mer Rouge M. Jousseaume n°15-1892," and, for unknown reasons, "60. " This jar contains six specimens of Peronia, from 60/45 to 25/15 mm, two of which were dissected, possibly by Labbé. The intestinal loops of the two dissected specimens are of type I and thus are not in agreement with  Labbé's (1934a: fig. 12 ) original illustration of the intestinal loops of type V in P. jousseaumei. Also, the sizes and the number of individuals do not match the original description of P. jousseaumei. Those specimens could possibly be some of the eight non-type specimens that  Labbé (1934a: 190)  mentioned in his re-description of Peronia peronii collected by Jousseaume from the Red Sea ("Mer Rouge") in "1852"  GenBank and BOLD sequences.
One COI sequence was obtained from BOLD (LGEN099-14) for an individual identified as Onchidium verruculatum and collected from Dwarka, Gujarat, on the western coast of India (ca. 22°N), which is the easternmost known locality for P. madagascariensis. A second COI sequence was obtained from GenBank (LC027608) for an individual identified as Peronia sp. and collected from the coast of Iran in the Persian Gulf. Both sequences were unpublished. Distribution (Fig. 6 ). From South Africa to the Red Sea and western India (ca. 22°N): South Africa, Mozambique, Madagascar (type locality of P. madagascariensis), Gulf of Oman, Iran (Strait of Hormuz), Yemen (Socotra), India  (Mumbai, Gujarat) , Red Sea (type locality of P. jousseaumei). All records are new except for the type locality in Madagascar. Peronia madagascariensis is, so far, not present in Mauritius.
g. ,  Dayrat et al. 2017 Dayrat et al. : 1861)). The specimen  [703]  from Oman was tentatively identified as Peronia sp. 2 by  Dayrat et al. (2011)  but it clearly belongs to P. madagascariensis (Fig. 2 ). Also, note that its COI sequence was resubmitted to GenBank because the old one (GenBank HQ660044) was inaccurate. The specimen [735] from Mozambique was tentatively identified as Peronia cf. peronii by  Dayrat et al. (2011). This identification should be disregarded because the specimen [735] belongs to P. madagascariensis (Fig. 2 ). A specimen from Durban (30°S), South Africa, preserved in Stockholm (SMNH 180711) identified as O. verruculatum by  Hoffmann (1928: 44, 73)  is identified here as P. madagascariensis because of its intestinal loops of type V (Table  4 ). Various records of Onchidium peronii, O.
DNA sequences (COI and 16S) are provided for 11 of those 14 individuals, including all four type specimens. However, it is unclear which GenBank sequences correspond exactly to the holotype because this information is missing in GenBank as well as in  Maniei et al. (2020a: table 2). It is assumed that the holotype, called "specimen LA7" in  Maniei et al. (2020a: table 1) , corresponds to the individual called "voucher LaFM7S" in GenBank. Ultimately, it does not matter at all because all mitochondrial sequences of P. persiae cluster together within the unit #4 of P. verruculata: only the COI (MK993404) and the 16S (MK993392) sequences of the "voucher LaFM7S" are included in our phylogenetic analyses to represent P. persiae (Fig. 2 ). Finally, note that the COI and 16S GenBank accession numbers are switched for P.
persiae in  Maniei et al. (2020a: table 2). Comments on the original description of P. persiae are provided in the species remarks (see below). (MH002570) for an individual identified as Peronia sp. and collected from Singapore  (Chang et al. 2018). This individual as well as others referred to as "Peronia sp. 2" by  Chang et al. (2018) , following  Dayrat et al. (2011) , clearly belong to the mitochondrial unit #1 of Peronia verruculata (Fig. 2 ). A third COI sequence was obtained from  GenBank (LC390389) for an individual identified as Peronia sp. and collected from Sakurajima, Kagoshima,  Japan (Tagaki et al. 2019) , which is south to the northernmost known locality near the Seto Marine Biological Laboratory (see material examined). This individual as well as others from "Group V" were referred to as "Peronia sp.
" by  Takagi et al. (2019)  and clearly belong to the mitochondrial unit #1 of Peronia verruculata (Fig. 2 ). Four COI sequences were obtained from GenBank (JN543152, JN543153, JN543154, JN543165) for individuals from the coast of China, from Hainan (18°N) to Fujian (26°N)  (Sun et al. 2014 ). These individuals were referred to as "Peronia verruculata" by  Sun et al. (2014)  and clearly belong to the mitochondrial unit #1 of Peronia verruculata (Fig. 2 ). Finally, the COI (MK993404) and 16S (MK993392) sequences of the "voucher LaFM7S" represent P. persiae (Fig. 2 ): all published mitochondrial sequences of P. persiae cluster together within the unit #4 of P. verruculata so only one individual is needed to represent P. persiae. Distribution (Fig. 6 ). Peronia verruculata is the most widespread of all onchidiid species.
Peronia persiae, originally described from the Persian Gulf, is regarded as a new junior subjective synonym of P. verruculata because its mitochondrial DNA sequences, represented by the GenBank "voucher LaFM7S" in our analyses, all cluster together within the unit #4 of P. verruculata (Fig. 2 ). An older name, P. gondwanae  (Labbé, 1934a) , already refers to the unit #4 of P. verruculata (Tables  1, 6 ). So, even in the hypothetical event that unit #4 would later need to be named as a distinct taxon (of subspecific or specific rank), P. persiae would still remain invalid because P. gondwanae would always take priority over it. The description of P. persiae by  Maniei et al. (2020a)  is an example of the common but regrettable practice that consists in creating new species names without a comprehensive revision, which almost inevitably leads to increasing the number of unnecessary synonyms  (Dayrat 2005).
Third,  Maniei et al. (2020a)  only examined specimens of P. persiae from the Persian Gulf, which means that, for comparison, they relied exclusively on the literature which, as the present work shows, is plagued with taxonomic and anatomical errors. For instance,  Maniei et al. (2020a: table S1)  assumed that the intestinal loops of P. verruculata were of types I and II, but it is positively demonstrated here that the intestinal loops of P. verruculata are all of type I and that there are no loops of type II in Peronia. Fourth, apart from P. persiae, only P. verruculata and P. peronii are represented in the phylogenetic trees by  Maniei et al. (2020a: figs 11, 12) , exclusively based on sequences obtained from GenBank (many of which were misidentified). Most specimens in their phylogenetic trees are not even identified at the species level.
Using DNA sequences to create a new species name while most species are not being included in phylogenetic analyses is highly problematic. Maniei et al. (2020b)  used the same mitochondrial COI sequences as in  Maniei et al. (2020a)  to compare metabolites between the Peronia slugs they called P. persiae and one Peronia individual from Bangka Island, near Sumatra, Indonesia. That specimen from Bangka Island, identified as Peronia sp. 7 by  Maniei et al. (2020a)  and as P. verruculata by  Maniei et al. (2020b) , belongs to the unit #1 of P. verruculata: its COI (MK993397) and 16S (MK993396) sequences cluster within unit #1. Note that the GenBank accession numbers for COI and 16S are switched in  Maniei et al. 's (2020a)  Table  2. Maniei et al. (2020b)  summarized their rationale for creating the name P.
Acknowledgements We would like to express our sincere gratitude to the many people who assisted us, by helping with logistics in the field, accompanying us in the field, hosting us at their institutions, sending us material on loan, or collecting material that we found in museums. We started collecting Peronia slugs in 2010 and this revision would not have been completed without the help of many people. First, we wish to thank associate editor  Nathalie Yonow  for spending many hours on our long manuscript. Three reviewers ( Adrienne Jochum ,  Eike Neubert ,  António M. de Frias Martins ) also provided helpful and constructive comments. Our field expeditions would not have been possible without help from many people:  Vivian Ang ,  Don Dumale , and  Marivene Manuel  in the Philippines,  Owen Griffiths  in Mauritius,  Richard Willan  in the  Northern Territory, Niel Bruce in Queensland ,  Rosemary Golding  and  Winston Ponder in Sydney , and  Vishal Bhave ,  Reshma Pitale ,  Sudhir Sapre , and  C.
The material from  Vanuatu (Santo)  and  Papua New Guinea (Madang, Kavieng)  was collected during the  MNHN-PNI-IRD Our Planet Reviewed expeditions (PI: Philippe Bouchet) , funded by the  Stavros Niarchos Foundation ,  Total Foundation ,  Prince Albert II of Monaco Foundation ,  Fondation EDF , Entrepose Contracting, and  Fonds Pacifique. The expeditions operated under permits delivered by, respectively, the  Environment Unit of the Government of Vanuatu , and the  Papua New Guinea Department of Environment and Conservation. This work was supported by the  Eberly College of Science  at the  Pennsylvania State University  and by a  REVSYS (Revisionary Syntheses in Systematics)  award from the  US National Science Foundation  ( DEB 1419394 ).
05m and for improving the signal/noise ratio, 8-times stacking was applied during the data acquisition. The typical velocity of electromagnetic wave travelling through a dry mixture of sand and gravel is circa 0. 1 m/ns. Taking into account the information from the previous section, concerning some degree of moisture of the examined dike, a reduced velocity of 0. 08 m/ns was assumed for time-depth conversion of the radargram. The recorded radargram (Fig. 2 ) was subjected to standard signal processing using ReflexW software (www. sandmeiergeo. de); a detailed description of the methodologies used in radargram processing may be found in geophysical literature  [2]. In Fig. 2  (radargram after processing), high-amplitude anomalies were recorded along the whole profile, to the depth of circa 1.
Modelling of electromagnetic wave field The aim of the modelling of electromagnetic (em) wave field was to answer the following question: "Why, when using the GPR method, was there no anomaly recorded in the area of leakage no. I?" To answer this question, four numerical models were constructed (Figs. 4 A, C, E, G ). The most popular technique of modelling the em wave field is the FDTD (Finite Difference Time Domain) technique, and this technique is commonly used for the GPR method. Detailed information about application of the FDTD technique for radargram interpretation may be found in publication  [6]  and, therefore, a description of theoretical background of the FDTD method has been omitted. Numerical modelling was carried using ReflexW software (www. sandmeiergeo. de). Based on the geological information obtained from boreholes #2 and #3 (Fig.
Impact of rust infection on metabolic pathways in apple leaves In order to determine the impact of the rust infection on metabolic pathways of apple leaves, we performed classification of DEGs into cellular categories using MapMan and KEGG and performed enrichment analysis. All DEGs were integrated into MapMan plant categories and 52 and 56% of them were classified into 28 functional categories at 10 and 30 dpi, respectively (Figure  5A ; Supplementary file: Table  S1 ). The direct comparison of proportions of up-and down-regulated transcripts assigned to Mapman categories helped to draw major inflexion in metabolic pathways. For instance, photosynthesis processes were remarkably represented among the down-regulated transcripts at the two time points. Conversely, cellular respiration was more represented among induced transcripts at both time points in infected apple leaves (Supplementary file: Table  S1 , Figure  5A ).
Interestingly, the solute transport category was proportionally more abundant in both up-and downregulated transcripts at 10dpi, indicating that this process might be particularly dynamic at the spermogonia infection stage. Similarly, the RNA trafficking category was also more represented in up-and down-regulated transcripts at 30 dpi, suggesting a highly dynamic regulation of this process at the aecial stage. The phytohormones and cell wall categories were also more represented among transcripts up-regulated at 10 dpi, and the vesicle trafficking category was more prominent at 30dpi among up-regulated transcripts (Figure  5A ). Almost all the genes falling in the MapMan photosynthesis-related apparatus category (Photosystem I, Photosystem II, ATP synthase, Redox chain, Photorespiration and Calvin cycle) were significantly down-regulated in infected leaves at the two time points (Figure  5B ).
All DEGs were also classified into Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and an enrichment analysis between inoculated and mock inoculated groups was performed for down-and up-regulated transcripts. In total, 3,090 and 715 downregulated transcripts were classified into 124 and 85 KEGG pathways, at 10 dpi and 30 dpi respectively; whereas 4,133 and 1,493 up-regulated transcripts were classified in 122 and 112 KEGG pathways at 10 and 30 dpi, respectively (Supplementary file: Table  S1 ). Consistent with the MapMan annotation results, photosynthesis related pathways were among the most significant down-regulated pathways at both time points, including biosynthesis of light-harvesting chlorophyll protein complex (LHC) in antenna proteins, impaired processes of Photosystem I, Photosystem II, and Cytochrome b6/f complex (Supplementary file: Table  S1 ).
G. yamadae spermogonia and aecia expressed genes The average length of the unigenes assigned to the rust fungus in spermogonia and aecia are respectively of 1,622-bp and 1,956-bp and the largest proportion of unigenes, with 19,589 (64. 67%) and 16,867 (74. 25%) at 10 and 30 dpi respectively, exhibits a size larger than 1kb, indicating the good quality of the reads assembly into fungal unigenes (Supplementary file: Figure  S3 ). Comparison of the fungal unigenes to the NCBI-nr, Swissprot and KOG databases provided putative annotation support for 17,951 (59. 3%) spermogonia unigenes and 17,515 (77. 1 %) aecia unigenes. Among them, 7,647 and 9,059 unigenes showed homology to genes of the wheat leaf rust fungus Puccinia graminis f. sp. tritici and 2,072 and 2,557 unigenes showed homology to genes of the poplar rust fungus Melampsora larici-populina.
Among the 26 and 23 most highly expressed unigenes (FPKM value > 1000) in spermogonia and aecia, respectively, more than half are hypothetical proteins or without any hit in the nr database (Table  3 ). Beyond that, we identified transcripts encoding secreted proteins, polyubiquitin-A and a pheromone precursor highly expressed in spermogonia, and transcripts encoding secreted proteins and a thiazole biosynthetic enzyme highly expressed in aecia (Table  3 ). Like in other rust fungi, many highly expressed rust transcripts are of unknown function. These molecular determinants are conserved across rust species and may play an important role in pathogenesis-related processes.
Functional distribution of G. yamadae unigenes during the interaction with the two host plants, apple and juniper G. yamadae unigenes from spermogonia and aecia were annotated in the Eukaryotic orthologous group (KOG) database. In total, 16,458 (54. 33%) and 11,299 (49. 74%) unigenes showed homology in the KOG database (Supplementary file: Table  S2 ) and the functional categories were compared to the distribution previously reported for the telial stage on juniper tree  (Tao et al. 2017). Excluding the category of "unknown function" and "General function prediction only", the most abundant KOG categories corresponded to "posttranslational modification, protein turnover, chaperones" at all three stages. The KOG categories showed similar distribution across the different fungal stages, although in each KOG category the unigenes are more abundant in spermogonia and aecia.
Transcriptome profiling of G. yamadae reveals expression of a conserved rust infection program and of specific in planta candidate effectors at two sporulating stages The large genome size of Gymnosporangium spp. (Tavares et al. 2014 ) hinders sequencing in this genus. With further efforts to obtain a reference genome for this genus (Aime et al. 2017; https://jgi. doe. gov/csp-2018-duplessis-reference-genomes-50-rustfungi/), the transcriptomes produced here and in a previous study  (Tao et al. 2017 ) will be helpful to support genome annotation. In the absence of any supporting G. yamadae genome resource, a predictive annotation strategy relying on comparison to pre-existing rust genes and transcripts in databases was built after an approach described for the coffee rust fungus H. vastatrix  (Fernandez et al.
2012) , and helped the identification of fungal unigenes from infected apple leaves. The prediction-based method most likely overestimates the unigenes numbers with some redundancy in the dataset when expected gene numbers in rust fungi are considered  (Aime et al. 2017 ). Nevertheless, the expression levels of G. yamadae transcripts were particularly high at apple infection stages spermogonia and aecia, compared to those recorded in telia in infected juniper host  (Tao et al. 2017) , although the total unigenes numbers were in a similar range at these different sporulation stages. Similar to all rust genome and transcriptome reports up-to-now, most of the transcripts expressed in spermogonia and aecia do not have functional annotation and correspond to hypothetical or unknown proteins (Aime et al.
In each library, 150-bp paired-end reads were generated from Illunima Hiseq platform. cDNA and RNAseq library were performed at Novogene (Beijing, China), following standard Illumina's procedures. Raw reads in fastq format were firstly processed through in-house perl scripts to remove adapters, poly-N and low-quality reads. The remaining high-quality clean reads were used in the subsequent analysis. All raw sequence data generated in this study has been deposited in the NCBI Sequence Read Archive (https://submit. ncbi. nlm. nih. gov/subs/sra/) under the accession number SRR9326001-SRR9326012.
Read mapping to the apple reference genome and gene expression analysis The reference genome and gene model annotation files of Malus domestica v1. 0 were downloaded from Phytozome v. 12 (https://phytozome. jgi. doe. gov/pz/portal. html). Bowtie v2. 2. 3  (Langmead et al. 2019 ) was used to build the index of the apple reference genome and paired-end clean reads were aligned to the reference genome using Tophat v2. 0. 12  (Trapnell et al. 2009). The mapped reads were counted using HTSeq v0. 6. 1  (Anders et al. 2015)  and expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced (FPKM) of each gene was calculated to estimate gene expression levels. Mapping and unigene expression estimates were performed by Novogene  (Beijing, China). The similarity between samples at the expression levels was visualized using R package pheatmap (https://CRAN.