dataesr/scientific-paragraphs-categorization huggingface dataset:
Whole Genome Sequencing of Insectomime Insectomime genome sequencing generated 272,503 reads. Assembly of the reads resulted in 9 large contigs with a mean size of 42,306 bp. The contigs assembled themselves in scaffolds of 382,776 and 3,855 bp. The Insectomime draft genome (GenBank submission ID 1632859) is a double-stranded DNA molecule composed of approximately 386,000 bp, with a guanine-cytosine content of 42. 7%. Phylogeny based on a concatenated alignment of the D6-D11 helicase, the major capsid protein and the DNA polymerase B family sequences showed the position of this virus among previously isolated Marseillevirus, Lausannevirus and Tunisvirus, which is its closest neighbor ( fig. 4  ). A tree constructed based on the family B DNA polymerase exhibited the same topology. Comparative analyses using BLASTp searches of the Insectomime genome and ge- nomes of other marseilleviruses showed substantial levels of similarity and collinearity, particularly at the ends of the genome ( fig.
In the aphid case, the Insectomime protein, orf298, is an ankyrin repeat-containing protein that is also found in Lausannevirus (YP_004347163. 1) and Tunisvirus (Tunisvirus_orf78). The Insectomime genome encodes 6 ankyrin repeat-containing proteins, which is equivalent to what is found in the Tunisvirus genome but greater than what is found in the genomes of the other marseilleviruses. Eight of the twenty best hits found by a BLASTp search for Insectomime orf298 against the NCBI GenBank non-redundant protein sequence database matched to putative ankyrin repeatcontaining proteins from Acyrtosiphon pisum. For the top hit (XP_001949966. 2), the e value was 7e-9, the amino acid identity was 26% and the query (Insectomime orf298) and target coverage were 80 and 66%, respectively. The twelve other best target sequences were proteins from Lausannevirus, A.
Discussion We found one giant virus from the recently described family Marseilleviridae  [7]  in the 86 larvae studied. The virus is phylogenetically distinct from other previously described marseilleviruses, including Marseillevirus  [8]  , Lausannevirus  [32]  , Cannes 8 [unpubl. data] (GenBank submission ID 1632635). Tunisvirus [unpubl. data] (Gen-Bank submission grp 4154826)  [6]  is the most closely related virus to the new virus. This new virus was found only in the internal organs of the insect, including the digestive tract, and no virus could be found in the surface or in the suspension used to wash the larvae before the experiment. The species E. tenax (Diptera, Brachycera, Muscomorpha, Syrphidae, E. tenax ) is an insect with a complex metamorphosis process. The eggs are typically laid on the surface of water and the larvae proceed through three stages of development.
Acknowledgements The authors are grateful to  Dott Giuseppe Panzera  for its essential assistance during this research activity and to the director and officials of the environmental protection sector of the province of  Reggio Calabria  for authorisation to use their atomic absorption spectrophotometer. SEM observations were performed at  laboratory LMT Cachan ,  ENS de Cachan / CNRS / Université Pierre et Marie Curie  (Paris 6),  France. The manuscript was improved by the insightful comments of anonymous reviewers from Journal of Environmental Management.
The carbonation simulations were performed using the Thermoddem lv12 (2008) database, developed by BRGM (Orléans, France)  [9]. For the waste disposal package (Fig. 1. B) simulations, only a 1D half section of the concrete container (section = 0. 11 m) is represented, assuming that atmospheric carbonation occurs on both faces of the wall. Initial liquid water saturation of the material is assumed to be 0. 8. The ventilation air temperature is 25°C and the relative humidity is 40%.
The labeled terminal restriction fragments (TRFs) were then separated on an ABI 3130 Genetic Analyzer (Applied Biosystems) with default fragment analysis parameters. Each sample was run twice as replicates to account for migration discrepancies. All T-RFLP electropherograms were visually inspected for possible artifacts and incorrect peak determination and were tabulated in GeneMapperH version 4. 0 software (Applied Biosystems) using the Local Southern method as the size-calling algorithm  [38]. Only fragments longer than 80 bp and smaller than 600 bp were considered.
Data were binned using the interactive and automatic binning algorithms  [40]  implemented in the free R programming language  [41] , applying custom R binning scripts (WS 1; Sh 0. 1) to account for size calling imprecision. Based on the ''best binned frame'' identified by the algorithm, the data were transformed for further graphical and statistical representations. The relative abundances in the different analyzed samples were calculated for each TRF. The data were transformed to a binary matrix (presence/absence), and the distance matrix between samples was computed from the Dice similarity index using R (R package ade4;  [42] ). Patterns of bacterial community similarities were represented on a 2-D scatter plot using multidimensional scaling (MDS) ordination. The K-means clustering method was then performed to determine the center coordinates of the clusters (R package fpc;  [43] ).
Phylogenetic analysis All bacterial 16S rDNA clone sequences were trimmed to 750 bp starting at the 59 end of the 63F primer, and the production of chimeras during PCR was evaluated with the Pintail program  [45]. The resulting libraries were dereplicated using FastGroupII (  [46] ; http://biome. sdsu. edu/fastgroup/index. htm) with a similarity cutoff value of 97% for sequence group definition. The unique sequence groups were classified taxonomically at the family level by the SeqMatch tool of the Ribosomal Database Project (RDP; http://rdp. cme. msu. edu). Within the dominant family-level groups, the sequence affiliations and closest relatives were identified by comparison with the GenBank database using the BLAST algorithm (  [47] ; http://blast. ncbi. nlm. nih. gov/Blast. cgi). To describe the compositional differences between the 3 summer 2007 libraries, the Shannon-Weaver index for diversity  [48]  and the Chao1 richness index  [49]  were calculated using the RDP Pipeline tools, with sequence groups defined with 97% similarity.
Nucleotide sequences accession numbers The nucleotide sequence data for the partial 16S rRNA genes reported in this paper were deposited in GenBank under the accession numbers JX874190-JX874360 (Medes; summer 2007 library), JX874361-JX874536 (Riou; summer 2007 library), JX874537-JX874629 (Riou; winter 2007 library), JX874630-JX874713 (Riou; winter 2008 library) and JX874714-JX874889 (Scandola; summer 2007 library).
clavata tissue samples. The dominant 16S rDNA band in the fingerprint of P. clavata was excised from the gel and sequenced for identification of the corresponding ribotype. This band was related to 16S rDNA sequences from marine bacteria belonging to the order Oceanospirillales. The closest cultivated relative was Spongiobacter nickelotolerans (GenBank accession number AB205011), with 94% similarity along the 479 bp sequence length. The dominant DGGE bands obtained with 3 other universal bacterial primer pairs were also sequenced. The band obtained with the EUB f933/EUB r1387 primer pair (Figure  2 , lane 11) was related to Spongiobacter nickelotolerans 16S rDNA (94% similarity among 417 bp). The sequences recovered from the 341F-GC/ 907RA and 341F-GC/907R amplifications (Figure  2 , lanes 12-13) shared 91 to 92% similarity with the 16S rDNA of Endozoicomonas elysicola (AB196667), a close relative of Spongiobacter spp.
The T-RFLP profiles obtained for replicate colonies of each sampling were consistent, although variations in peak intensity were observed, likely due to the nonquantitative PCR amplification step. However, the dominant TRFs between replicates from the same seasonal sampling were broadly conserved between the CfoI and MspI data sets. Two dominant TRFs were consistently recovered throughout most of the survey, indicating the presence of conserved ribotypes. The CfoI profiles were dominated by TRF-171. 4, with the exception of 9 samples from summer 2007 (Figure  3 ). When present, this TRF accounted for 37. 3 to 91. 1% of the total area of the TRF peaks in the fluorescence profiles. Profiles from P. clavata colonies sampled in summer 2007 did not contain TRF-171. 4 but were dominated by TRF-193.
By contrast, the MspI TRF-100. 1 was detected in 10 other profiles from the 2009 and 2010 samples, among which 7 also contained TRF-110. 1. Overall, peak diversity was significantly higher in the summer 2007 profiles, with an average of 8. 9 6 2. 5 CfoI TRFs versus 5. 9 6 1. 6 for other profiles and 9. 3 6 2. 2 MspI TRFs versus 3. 8 6 2. 8 for other profiles (p,0. 001). The T-RFLP profiles of the bacterial communities in the surrounding seawater were compared with the profiles of colonies sampled on 3 occasions in Riou (winter 2007 and 2008 and summer 2007). None of the detected TRF peaks were common to the seawater and gorgonian tissue profiles (data not shown). The ordination of P. clavata-associated community profiles by MDS did not demonstrate visible clustering by sampling site (Figure  5 ) but revealed that most of the CfoI (Figure  5A ) and MspI (Figure  5B ) profiles grouped regardless of geographic origin.
In contrast to the unique Hahellaceae ribotype revealed by our study in P. clavata, several distinct Endozoicomonas-Spongiobacter sequences coexist in hexacoral species. This difference suggests that distinct hexa-and octocoral hosts may exert different selective controls on their microbial partners, resulting in various diversity patterns of Hahellaceae associates. Consistent with this hypothesis of host-driven control on associated Hahellaceae bacteria, the ribotype identified in P. clavata did not closely match the Spongiobacter-Endozoicomonas sequences found in hexacorals (,93% similar) but was more closely related (. 96% similar) to bacterial sequences retrieved from the tropical gorgonian Gorgonia ventalina (GenBank accession number GU118518;  [13] ), suggesting that the species associated with P.
For instance, changes in microbial associates were observed in the stony coral A. millepora during a mass bleaching event, and occurred prior to visual signs of bleaching on the sampled colonies  [28]. Major shifts in bacterial communities were Regarding the potential causes of stress within the gorgonian populations in summer 2007, the available temperature time series data recorded at the study areas during the survey period (T-MedNet network; http://t-mednet. org) did not reveal any temperature anomaly. In addition, surveys of P. clavata populations conducted during and after summer 2007 in the 3 study areas did not reveal any symptoms of disease (J. Garrabou et al. , unpublished data). Notably, we did not detect the presence of Vibrio coralliilyticus 16S rDNA in the Paenibacillus-dominated summer 2007 clone libraries, although this Vibrio has been implicated in recent disease outbreaks in P.
Acknowledgments We gratefully acknowledge  J. M. Dominici  ( Reserve Naturelle de Scandola ); the staff of  Parc Natural del Montgrı ´, Illes Medes i Baix Ter ;  B. de Ligondes ,  C. Marschal  and  F. Zuberer  (Diving staff,  Observatoire des Sciences de l'Univers -Institut Pytheas) ;  E. Cebrian  ( Centre d'Estudis Avancats de Blanes-CSIC );  C. Linares  and  N. Teixido  ( Ecology Department, University of Barcelona ); and  O. Bianchimani  ( Septentrion Environnement ) for assistance with sample collection. We also thank  C. Rocher  ( Institut Mediterraneen de Biodiversiteet d'Ecologie Marine et Continentale -UMR 7263 ) for technical assistance with the molecular work. Finally, we thank  Y. Eynaud ,  K. J. Soda  and  G. Meisterhans  for assistance with statistical analyses.
Location and animals This study was carried out in Al -Jouf 'Camel & Range Research Center' located in north-west Saudi Arabia, 950 km from Riyadh. Average annual temperature was 20°C, ranging from 12°C to 27°C, and average annual rainfall were 55 mm. The herd was composed by camels of four ecotype breeds (Malhah, Wadhah, Hamrah and Safrah) and their crosses  (Abdallah and Faye, 2012). Camels were kept indoor throughout the year and housed in pens. Their diet was composed of alfalfa, barley, and salt and wheat bran. For each animal, the following parameters were reported: parity (primiparous or multiparous), gestation length, calf weight at birth and adult weight at calving date. The quantitative data were shared into 2 modalities for statistical analysis (Table  1 ).
Statistical analysis Physiological and seasonal changes (mean and SD) were studied at weekly and /or monthly basis. The correlations between the different components of the camel milk were calculated using Pearson correlation. The effects of some parameters were investigated as parity, gestation length, breed and body weight by ANOVA procedure. The differences between modalities reported in table 1 were investigated by Fisher test  (LSD). The data of present study was analyzed by using XLSTAT software (2010, 2. 02 version, Addinsoft ©).
Acknowledgements This study has been achieved within  FAO  project  UTF/SAU/021/SAU  with the support of  Camel and range research Center (CRRC). The authors thank  Dr. Mohamed Bengoumi , Animal production and health officer (FAO) for his encouragements and support. We are grateful also for the farm labors ( Hassan Mohamed ,  Suresh Kumar  and  Mohamed Hussein ) for their contribution in the camel management.
Background: Giant viruses in the genus Chlorovirus (family Phycodnaviridae) infect eukaryotic green microalgae. The prototype member of the genus, Paramecium bursaria chlorella virus 1, was sequenced more than 15 years ago, and to date there are only 6 fully sequenced chloroviruses in public databases. Presented here are the draft genome sequences of 35 additional chloroviruses (287 -348 Kb/319 -381 predicted protein encoding genes) collected across the globe; they infect one of three different green algal species. These new data allowed us to analyze the genomic landscape of 41 chloroviruses, which revealed some remarkable features about these viruses. Results: Genome colinearity, nucleotide conservation and phylogenetic affinity were limited to chloroviruses infecting the same host, confirming the validity of the three previously known subgenera.
Clues for the existence of a fourth new subgenus indicate that the boundaries of chlorovirus diversity are not completely determined. Comparison of the chlorovirus phylogeny with that of the algal hosts indicates that chloroviruses have changed hosts in their evolutionary history. Reconstruction of the ancestral genome suggests that the last common chlorovirus ancestor had a slightly more diverse protein repertoire than modern chloroviruses. However, more than half of the defined chlorovirus gene families have a potential recent origin (after Chlorovirus divergence), among which a portion shows compositional evidence for horizontal gene transfer. Only a few of the putative acquired proteins had close homologs in databases raising the question of the true donor organism(s). Phylogenomic analysis identified only seven proteins whose genes were potentially exchanged between the algal host and the chloroviruses.
Conclusion: The present evaluation of the genomic evolution pattern suggests that chloroviruses differ from that described in the related Poxviridae and Mimiviridae. Our study shows that the fixation of algal host genes has been anecdotal in the evolutionary history of chloroviruses. We finally discuss the incongruence between compositional evidence of horizontal gene transfer and lack of close relative sequences in the databases, which suggests that the recently acquired genes originate from a still largely un-sequenced reservoir of genomes, possibly other unknown viruses that infect the same hosts.
Currently, the phycodnaviruses are grouped into 6 genera, initially based on host range and subsequently supported by sequence comparison of their DNA polymerases  [10]. Members of the genus Chlorovirus infect chlorellalike green algae from terrestrial waters, whereas members of the other five genera (Coccolithovirus, Phaeovirus, Prasinovirus, Prymnesiovirus and Raphidovirus) infect marine green and brown algae. Currently, 24 genomes of members in four phycodnavirus genera are present in Genbank. Comparative analysis of some of these genomes has revealed more than 1000 unique genes with only 14 genes in common among the four genera  [4]. Thus gene diversity in the phycodnaviruses is enormous. Here we focus on phycodnaviruses belonging to the genus Chlorovirus, referred to as chloroviruses (CV).
Novel protein genes One hundred and sixty-six clusters totaling 403 proteins did not have an orthologous member in any of the reference viruses. The corresponding genes are thus seen for the first time in CV and encode potential new functionalities. Only 22 new clusters had a match in a public database, the rest of the proteins were annotated as "hypothetical protein. " Furthermore, only 6 clusters were homologous to proteins annotated with functional attributes (Additional file 2: Table  S2 ). They include a fumarate reductase possibly involved in anaerobic mitochondrial respiration  [29] , and five proteins with generic functional annotation: acetyltransferase, SAM-dependent methyltransferases, nitroreductase, glycosyl hydrolase and helicase.
Phylogeny Phylogenetic relationships between the sequenced CVs and Ostreococcus viruses were determined from an analysis of the concatenated alignment of 32 protein families encoded by a single gene in each genome. Ostreococcus viruses were treated as an outgroup to root the phylogenetic trees. These genes represent a subset of the "core" CV genes and are mostly involved in basic replication processes. The resulting maximum likelihood (ML) phylogenetic tree is shown in Figure  1A. All branches are associated with high bootstrap values (>90%) except for those containing very similar viruses, for which the exact timing/order of separation events could not be resolved unambiguously. Phylogenetic trees were also inferred by Neighbor Joining (NJ) and Maximum Parsimony (MP) methods using the same sequence dataset (Additional file 3: Figure  S1  and Additional file 4: Figure  S2 ).
A fraction of them were presumably encoded in the ancestral genome and subsequently lost in all of the NC64A, Pbi and SAG viruses, so that their occurrence in the common ancestor could not be established using the parsimony criterion. Furthermore, we cannot rule out that some of the ORFan genes (ORF without match in sequence databases and the other chlorovirus subgenera) are erroneous predictions. Sequence randomization between non-ORFan genes indicates that on average less than 1 ORF >300 bp in size can be obtained by chance in a chlorovirus genome; 185 non-ancestral protein families were encoded by ORFs that have a median length >300 bp. Alternatively, the corresponding genes could have been gained after the divergence of the main CV clades. There are three known mechanisms that can lead to gene gain: duplication of existing genes, capture of genes from other genomes through horizontal gene transfer (HGT) and creation of new genes from noncoding sequences de novo.
0001 and Steel-Dwass-Critchlow-Fligner W* test p < 0. 0001 between each pairwise combination of ancestral and non-ancestral CDI subsets). On average, non-ancestral ORFs had lower CDI values meaning that their nucleotide composition tends to exhibit a poorer fit to the nucleotide frequency model. This trend was true irrespective of the identification of homologs in databases or not. Furthermore, the distributions of CDI values for long (>300 bp) and short (<300 bp) ORFan families were not significantly different (Mann-Whitney test p ~0. 99). This suggests that at least a fraction of the non-ancestral genes, including the genes with no recognizable homologs in the database, have been captured by HGT from genomes with distinct nucleotide compositional biases and that this event was sufficiently recent so that the difference in nucleotide composition is still visible.
To test this hypothesis, phylogenetic trees were reconstructed from 35 of the 54 non-ancestral protein families that had significant matches in Genbank. For the remaining 19 protein families, no reliable phylogenetic tree could be generated due to the scarcity of homologous sequences or too high sequence divergences between homologs. Most of the 35 phylogenetic trees were not conclusive as to the exact evolutionary history of the viral genes (Phylogenetic trees are shown in Additional file 6: Figure  S3  and a summary of the interpretations is shown in Additional file 7: Table  S4 ): In many cases, CV proteins had relatively deep branches in the tree implying that if the hypothesis of a recent HGT is supportable, sequences of the donor genome or its close relatives are not available in databases.
Thus, although the non-ancestral genes exhibit specific compositional features suggesting this subset is enriched in sequences with a potential extraneous origin, a majority of them (281 families) have no identifiable homolog in the databases, and for those that do (54 families), only a few produced a phylogenetic tree where the clade of the donor organism could be identified with a reasonable degree of confidence. Thus, if the hypothesis of acquisition by HGT is supported for the non-ancestral CV genes, they must originate from a DNA fraction that is under-represented in public databases. Finally, we investigated the location of the non-ancestral genes within the CV genomes. The non-ancestral genes are evenly distributed across the CV genomes (Figure  3C ). This contrasts with the cases of Mimiviridae and Poxviridae, which have genus-and species-specific genes clustered toward the extremities of their genomes, whereas the conserved genes are clustered in the middle  [30, 34].
Our study shows that the capture (and fixation) of algal host DNA has been rare in the evolutionary history of CVs and cannot explain the vast majority of nonancestral CV genes. Furthermore, we believe that bacterial DNA is not a major source of extrinsic genes in CVs: if non-ancestral genes were mainly of bacterial origin we would expect that the proportion of ORFans in the non-ancestral gene data set to be comparable to the proportion of ORFans in bacterial genomes. Estimated frequencies for ORFans in bacterial genomes vary between 7% for the most recent estimates  [41]  to 20-30% for estimates made early in the history of genome analysis  [42] , when only the first organisms had been sequenced. These frequencies are significantly below the frequency of ORFans in the non-ancestral CV protein family dataset (from 141/195 = 72% if we only consider "long" ORFans to 281/335 = 84% if we consider all predicted genes).
Thus if the conjecture of acquisition by HGT is true for the non-ancestral CV genes, they must originate from a still largely un-sequenced reservoir of genomes. The biological entities that match best with this characteristic are the viruses themselves. Viruses are by far the most abundant entities in aquatic environments and we are only now realizing the extraordinary range of global viral biodiversity  [8]. Thus, we suspect that the apparent incongruence between compositional evidence of HGT and lack of donor (or close relative) sequences in the databases reflect the fact that non-ancestral CV genes arose from recombination with other unknown viruses that infect the same hosts. However, this does not rule out alternate hosts that could be underrepresented in the existing databases as possible donors.