dataesr/scientific-paragraphs-categorization huggingface dataset:
963; Cohens' kappa test), and no significant difference was noted for any of the viral or putative families. In contrast, using raw data provided by Metavir would have led to a 24-fold overestimation of the proportion of these viruses in the metagenomes. These results suggested that MG-Digger may be slightly more sensitive and is more specific than Metavir in terms of identifying Megavirales or virophagerelated reads in metagenomic datasets. In addition, for 14, seven and three reads found using MG-Digger in the metagenomes described by  Williamson et al. (2012;  with an e-value threshold of 1e -3), sequences from the recently described Yellowstone Lake virophages, P. sibericum, and Faustovirus were the only significant hits. In terms of reads whose best match was P. sibericum, the mean ± standard deviation (SD) for amino acid identity and alignment length were 38 ± 5% and 105 ± 36 amino acids, respectively, and mean ± SD coverage of sequence reads by the amino acid alignments was 71 ± 22% (range, 37-98).
DISCUSSION MG-Digger, a user-friendly computational tool implemented in our laboratory for the detection of Megavirales-like or virophagelike sequences in metagenomes, automatically generated readyto-analyze metagenome files and annotated 100s of sequences as significantly matching those of giant viruses or virophages. These findings suggest the potential presence of megaviruses, virophages or close relatives in the original samples. MG-Digger functionality and efficiency to detect the best matches of a giant viral sequence set was validated by analyzing environmental or human metagenomes that were previously analyzed in four studies using other tools. Accurate comparisons of the results of MG-Digger with those previously obtained with other tools that analyze viral metagenomes are difficult because these tools used different strategies consisting of different similarity searches with different virus sequence databases.
However, a comparison with results obtained for an Ocean Water metagenome by Metavir 2  (Roux et al. , 2014) , a widely used tool for the study of viral metagenomes, suggested that MG-Digger had similar or slightly greater sensitivity. Moreover, MG-Digger presents several advantages in comparison with previously described tools. Thus, MG-Digger performs a fully automated process that starts with downloaded raw metagenomes and ends by providing annotations for metagenome sequences, and it operates as a standalone software either on a personal computer or on a laboratory bioserver, which enables large sequence sets to be handled within a limited time. In addition, MG-Digger requires limited user computer skills, as a graphical user interface is implemented that operates by clicking a computer mouse button, using either Linux or Microsoft Windows operating systems.
Moreover, it generates ready-to-analyze metagenomes for any subsequent searches, and can handle customized query and target sequence databases, using adjustable parameters for sequence similarity searches. Finally, output files contain selected reads with the identification of their best match. MG-Digger has been made available to any student or senior investigator in our clinical and research microbiology laboratory and is currently used for several studies of metagenomic datasets. Metagenome sequences identified in the present work were most often similar to phycodnavirus or mimivirus sequences. However, matches were also obtained with sequences from giant members belonging to putative new viral families in the proposed order Megavirales, namely pandoraviruses, Pithovirus sibericum and faustoviruses.
In addition, best matches with faustovirus sequences were found by our team in metagenomes generated from Mississippi ponds and from the serum samples of healthy Egyptian volunteers  (Reteno et al. , 2015). In contrast, to our best knowledge, P. sibericumrelated sequences were detected here for the first time from an environmental or a human metagenome. This suggests that relatives of P. sibericum, which has been described as having been retrieved from Late Pleistocene Siberian permafrost  (Legendre et al. , 2014) , currently exists and could be isolated in the near future from current samples. Hence, it is worth noting that the inclusion in our query dataset of sequences belonging to new putative viral families, such as pandoraviruses, P. sibericum or faustoviruses, detected matches with these viruses.
These data are an incentive to continue searching for sequences that match giant viruses in metagenomes generated from human samples in order to assess the link between megaviruses and humans. Finally, although MG-Digger was basically designed for the detection of giant virus sequences, query sequence sets can be selected according to the objectives. Thus, our tool could be used to search for matches with sequences related to bacteria, eukaryotes, archaea and other viruses in metagenomes.
Virome read mapping to chimeric viruses We compiled a database of full-length CP sequences (total of sixty-eight sequences) and attributed group affiliations according to the phylogenetic analysis. BLASTx analysis against the CP sequences was performed for the twelve Sphagnum-peat viromes and sixty-nine viromes from public databases that were equally obtained by whole genome amplification. To assure the reliability of matches a strict cut-off value of 10 À10 was applied. The number of matches was normalized to the total number of reads in the different viromes.
The circularity of the sequences was verified using MUMmer for sequence recruitment to reconstructed genomes  (Quaiser et al. 2015). In total, twenty-nine from thirty-seven contigs could be closed and were considered as circular (Fig. 1 ). All these assembled genomes contained genes that encode for two conserved proteins, tombusvirus-like CP and RC-Rep, as typical of chimeric viruses  (Roux et al. 2013). No other genes, beside CP and RC-Rep were conserved throughout the genomes. Additional ORFs were shared only by nearly identical contigs. The comparison of these ORFs to protein sequence databases revealed no significant matches. Although official classification of these viruses will require isolation of cultivable representatives, we propose referring to this viral assemblage as 'Cruciviridae' (crucis: cross in Latin) as these viruses originate from a "cross" (i.
restricted set of cranio-dental characters. Here we put this proposition to test by analyzing the mitochondrial genome of a specimen of the late surviving glyptodont Doedicurus. One of the largest members of its clade, with an estimated body mass of ˜1. 5 tons  [7] , Doedicurus exhibited numerous distinctive characters, famously including a club-shaped, armored tail adorned with spikes used, presumably, in intraspecific combat. Using ancient DNA (aDNA) extraction techniques, we recovered endogenous DNA from a carapace fragment (MACN Pv 6744) dated to 12,015 50 14 C yrpb (radiocarbon years before present; Supplemental Information). Utilizing a recently assembled dataset encompassing all modern xenarthran species [5], we reconstructed, in silico, a set of ancestral mitogenomic sequences, which permitted in turn the synthesis of a set of target capture RNA baits.
To further rule out the presence of NUMTs, we cut our final alignment into thirty-one 500bp fragments and performed a variety of tests. First, we verified that all 31 Doedicurus 500bp fragments have sequence similarity with other xenarthran mitogenomes using BLASTN searches against the NCBI non-redundant (nr) database. Each fragment had its best hit to available modern xenarthran mitogenomes but without any perfect match, which rules out contaminants represented in the database. Second, we reconstructed maximum likelihood (ML) trees using RAxML [S4] under the GTRGAMMA model for each of the 31 partitions. None of the inferred maximum likelihood trees showed a spurious relationship or a particularly long or short branch for Doedicurus, which was always recovered nested within armadillos. We feel these results argue in favor of a genuine, mitochondrial genome from this specimen of an extinct taxon.
Phylogenetic results Analyses of the mitogenomic dataset using Bayesian and ML methods implemented in both partitioned and mixture models, resulted in the same strongly supported topology (Fig. S2a, b ). The statistical support for the positioning of Doedicurus within Chlamyphoridae, as a sister-group to Chlamyphorinae + Tolypeutinae, was high with the Bayesian mixture model (PPCAT = 0. 97), maximal with the Bayesian mixed model based on the best fitting partitioned scheme (PPPART = 1), and more moderate with the partitioned ML model (BPPART = 69). The monophyly of Chlamyphorinae + Tolypeutinae showed similar support (PPCAT = 0. 93; PPPART = 1; BPPART = 73). With the exception of one particular node within the genus Dasypus, all nodes were strongly supported and congruent with the recently published complete xenarthran mitogenomic study of Gibb et al.
[S5]. This mitogenomic phylogeny of xenarthrans is fully congruent with previous studies conducted at the genus level, and using nuclear exons  [S6,S7]  as well as non-coding retroposon flanking sequences  [S8]. The inferred molecular timescale (Fig. 2c, d ) is also consistent with the ones previously obtained with nuclear data  [S9]. As discussed in Gibb et al. [S5] , the mitochondrial/nuclear congruence strongly argues for the adequacy of mitogenomic data for reconstructing xenarthran evolutionary history in terms of both phylogenetic relationships and divergence times. The analysis of morphological data onto the molecular topology, via character mapping using maximum parsimony, failed to identify any unambiguous synapomorphies for the grouping of Doedicurus with the Chlamyphorinae + Tolypeutinae clade.
Ancestral sequence reconstruction and bait design In order to maximize the capture of potentially divergent sequences from extinct xenarthran taxa, we designed a xenarthran bait set which was composed of 100bp baits tiled every 5 bases across a representative sample of living xenarthran mitochondrial genome sequences [S12] as well as 13 ancestrally inferred mitochondrial genomes including the ancestral xenarthran mitogenome. Ancestral sequences were inferred for each node of the modern xenarthran tree under a single GTR+G model using the program baseml of the PAML 4 package  [S14]. The variable tandem repeat section (VNTR) of the D-loop was masked with 10 Ns prior to bait design, as it is too long to resolve with short read sequencing. In light of evidence that bait coverage across targets can result in coverage biases in target read coverage  [S13,S15] , we chose not to collapse baits of identical sequence prior to manufacture.
The enriched library was pooled and sequencing was performed on the Illumina HiSeq system using the TruSeq Rapid (v1) chemistry with initial hybridization on the cBot. Each lane included a 1% spike-in of Illumina's PhiX v3 control library. Paired-end reads of either 111 or 85 bp were performed, along with dual 7 bp indexing on both runs. Raw data were processed with either HCS v2. 0. 10. 0 or v2. 0. 12. 0 and RTA v1. 17. 21. 3. File conversion and demultiplexing using each 7bp reverse index (requiring a 100% match) was performed with the Illumina CASAVA software version 1. 8. 2.
Mitogenome assembly and annotation Raw sequence reads were first trimmed to remove adapter and index tag sequences using CutAdapt [S16]. Duplicate paired reads were removed using FastUniq  [S17]  and the remaining reads were imported into Geneious R9  [S18]. Any potential human contamination was removed by mapping the reads to the human mitogenome using the ʻlow sensitivityʼ setting in Geneious, and any reads that mapped with a high similarity were discarded. The remaining trimmed reads were then mapped to the Euphractus sexcinctus reference mitogenome (Accession Number NC̲028571) using the ʻmedium sensitivityʼ setting in Geneious. Iterative mapping to successive "hybrid" consensus genomes was repeated until no more reads were included. Any remaining regions that lacked any coverage were filled in with question marks (?) in order to create a draft mitogenome.
Mitogenomic dataset construction We selected 31 representative living xenarthran species from the complete mitochondrial genome data set assembled by Gibb et al. [S5]  for modern species together with three afrotherian outgroup taxa. We then added Doedicurus sequences (excluding the control region) and aligned each gene data set individually using MAFFT G-INSI  [S20]  within Geneious for the 22 tRNA and the two rRNA genes, and using the amino acid translation for ! "'! the 13 protein-coding genes. Selection of unambiguously aligned sites was performed on each individual data set with Gblocks [S21] using default relaxed settings and the codon option for protein-coding genes. The final concatenation contained 15,214 unambiguously aligned nucleotide sites for 35 taxa.
This approach allows joint reconstruction of variations in molecular evolutionary rates, divergence times, and continuous variables by modeling these parameters as a multivariate Brownian diffusion process along the branches of the phylogenetic tree while taking their covariance into account. The Bayesian chronogram was used as a fixed topology to reconstruct ancestral body mass under the dsom procedure, which allows accounting for variation in non-synonymous to synonymous substitution ratio. Body mass values for extant xenarthrans were obtained from the PanTheria database  [S27]. We used an estimated body mass of 1,468 kg for Doedicurus  [S28]. CoEvol was run for 5,000 cycles sampling parameters at each step. The first 500 samples were discarded as the burnin and posterior averages were estimated on the remaining 4,500 points.
kindly provided access to the Doedicurus specimen. This work was supported by grants from the  Centre National de la Recherche Scientifique (CNRS) , the  Scientific Council of Université Montpellier 2  ( UM2 ), and Investissement dʼAvenir grants of the  Agence Nationale de la Recherche  ( CEBA :  ANR-10-LABX-25-01 ) to FD, the  Natural Sciences and Engineering Research Council of Canada (NSERC)  and the  Canada Research Chairs program  to HNP. HNP thanks the  McMaster Ancient DNA Centre members  and  D. Poinar  for constructive feedback. J. -M. R. has financial interest in MYcroarray ( Ann Arbor ,  MI, USA)  who provided insolution capture baits used in this work. All other authors declare that they have no conflicts of interest. This is contribution ISEM 2015-.
Results We successfully collected video and GPS data from 35 foraging Cape gannets, and at least one call was recorded for 34 of them. During 42 h 15 min of video recording of Cape gannet behaviour at sea (excluding records at the colony), calls were recorded from 16 birds on 72 occasions. Calls were emitted in sequences composed of short calls (about 0. 05 to 0. 3 s), repeated one to 18 times every ~0. 3 s, sometimes with longer gaps of ~1. 5 s in between (Fig. 1 ). Most of the energy was concentrated between 300 and 2400 Hz, but the detailed structure of harmonic series could not be observed due to the poor quality of the camera microphones and the waterproof casing. Figure  2  illustrates the context of call emissions along the foraging trips of Cape gannets. Calls were emitted only in the presence of conspecifics and mainly when the birds were foraging (81% of the total number of calling sequences).
Despite these challenges, sound recording of seabirds at sea will open new perspectives on several aspects of their foraging ecology. Their behaviour and time-activity-budgets can be monitored along foraging trips from the typical splash sounds emitted when taking off from the water, landing on the water and diving. Compared to data from Time-Depth Recorders (TDR), the dive profiles are not captured with microphones, but they can be an interesting complement as they provide additional information on the behaviour of the birds. Seabirds often gather in groups, on land to breed  9  and at sea to forage (e. g. 15, 17, 21 ). Social interactions necessarily shape the behaviour and foraging strategies of seabirds. Advances in technologies and the development of bio-logging provide us with new tools to observe and study seabirds at sea and enhance our understanding on the role of social interactions in their ecology and behaviour.
Methods Data collection. We deployed video cameras with built-in microphones and GPS units on 36 breeding Cape gannets at Bird Island (33°50′ 26. 6″S, 26°17′ 14. 5″E, Algoa Bay, South Africa) during the 2010-2011 breeding season. Fieldwork was conducted under a permit from South African National Parks (SANParks). All experimental protocols were approved by both SANParks and the Nelson Mandela Metropolitan University Ethics Committee (reference: A10-SCI-ZOO-008), and were carried out in accordance with the approved guidelines. The birds were captured near their nest, when departing to sea after a changeover with their partners. Only one adult per nest was equipped for one foraging trip, while the partner stayed at the nest guarding the chick. The video cameras (Camsports Nano; Camsports, Estrablin, France) recorded at a resolution of 736 × 480 pixels at 25 frames per second with a 74° lens angle, for a maximum of 90 min (due to limited battery capacity).
Microphones in the video camera loggers recorded the sound at a sampling frequency of 8 kHz. The GPS devices (i-GotU GT-600, Mobile Action Technology, Taipei, Taiwan) recorded a geographic position every 5 s when the birds moved at a speed higher than 10 km * h -1 and every 10 s or 30 s otherwise. A handheld GPS was placed in front of the camera lens so that the Greenwich Mean Time was recorded on the footage. The video and sound observations were hence accurately synchronized to movement data using the satellite derived time. The handling process lasted less than eight minutes and included weighing individuals using a spring balance [Pesola, Baar, Switzerland; precision 50 g]) and device attachment through the use of adhesive tape (Tesa, Hamburg, Germany). The loggers were attached to the lower back of the birds in such a way that potential drag due to modification of the birds' body shape was minimized.
The total mass attached to a bird was 70-75 g, corresponding to 2. 3-3. 0% of the bird's body mass (2,400-3,100 g, n = 36). The nests were then monitored regularly, and the study birds were recaptured soon after their return to the colony and the devices were retrieved. Data analysis. To analyse the images, video footage were observed frame by frame and the events of interest were visually flagged using a purpose-built video reader and event recorder coded in MATLAB software  32. Video data provided information on the behaviour of equipped birds, including taking off, sea landing, and diving, from which we defined flights, sitting on the water and foraging events (defined as in ref. 27). The surroundings of the study bird were also observed, as were interactions with conspecifics and other predators (other seabird species, dolphins, and boats).
To analyse the sound, videos with sound recordings were played using VLC media player (VideoLAN, France) while simultaneously running a software designed to record observed behaviours. All vocalization events were flagged and recorded together with the time since the start of the video. The spectrograms of identified calls (using a Hamming function on a 256 points window size, 31 Hz frequency resolution, with 75% overlap) were then displayed using Avisoft-SASLab Lite (Avisoft Bioacoustics, Germany). Spectrograms were only used to confirm the emission of a call from a gannet, and no detailed analyses of acoustic signals were conducted because of poor quality of a number of the recordings (the microphones were embedded in a waterproof casing resulting in sound degradation). Observations from deployed individuals were included if at least one call was recorded.
Sequence analysis Nucleotide sequence analysis and prediction of the open reading frame were performed with Genetyx software version 7. 3. 0 (GENETYX, Tokyo, Japan). The nucleotide homology search for the DNA sequence and protein homology search for the translated amino acids were performed by BLAST on the NCBI website (http://blast. ncbi. nlm. nih. gov/Blast. cgi). Sequence alignment analysis was performed with the ClustalW program  (Thompson et al. , 1994)   ) was used as a suitable template in the homology modeling analysis using CPH models 3. 0.
SDS-PAGE and Western blotting Comment Samples from the hemolymph of E. coli-immune challenged S. gregaria 5 th instar nymphs collected at different time intervals, purified lysozyme from S. gregaria plasma  (Mohamed et al. , 2013)  or rSgLys were subjected to 12% SDS-PAGE, according to  Laemmli (1970)   (Laemmli, 1970)   (Supplementary Table  S1 ) which gave a PCR product of 479 bp. The PCR conditions consisted of an initial denaturation at 94 o C for 2 min, followed by 30 cycles of denaturation at 94 o C for 1 min, annealing at 56 o C for 1 min and extension at 72 o C for 1 min, and a final extension at 72 o C for 5 min. The expression of the housekeeping gene β-actin (Genbank accession number: HQ851398) was used as an internal control with the forward primer 5'-GTGGGGCGCCCCAGGCACCA-3' and the reverse primer 5'-CTCCTTAATGTCACGCACGATTTC-3' and under the same PCR conditions as above.
Characterization of the predicted S. gregaria c-type lysozyme The encoded amino acid sequence of SgLys was also deduced with the Genetyx-Win version 7. 0. 3 software. The SgLys gene contains a 423 bp ORF with a possible initiation codon at position 27-29 of the nucleotide sequence which confirms our analysis above. The ORF encodes a 141 amino acid sequence composed of 22 residues at the N-terminal side predicted as a signal peptide (bold letters in Figure  1 ) and 119 residues as a mature peptide. The predicted 22 residues of the signal peptide are mostly hydrophobic amino acids, a feature common to the signal peptides of both eukaryotes and prokaryotes  (von Heijne, 1990). Based on these predictions, the molecular weight and isoelectric point of the full-length SgLys were estimated to be 15,702 Da and 9.
This is especially true in orthopterans when taking into account that no antimicrobial peptides, such as those inducible after the activation of the two signaling pathways Toll and Imd, have been reported yet in these insects with the exception of locustin (Accession number P83428,  Bulet et al. , 2002, unpublished). Comment   Neighbor-Joining criteria using MEGA6. Only bootstrap values higher than 50% are indicated for each root. Gallus gallus lysozyme was used as the out-group. Schistocerca gregaria lysozyme is written bold face letters. The sequences used in this analysis are listed in Supplementary Table  S2. Lysozymes with digestive function are underlined while full circles indicate acidic lysozymes.
Acknowledgments The authors would like to thank  Dr Venkatramana Krishna ,  Bhat Biotech's Vice President R&D (India)  (currently postdoctoral researcher at  University of Minnesota Twin Cities, USA ) for his technical support and enthusiastic work. We are also indebted to the late  Dr J. Nagaraju -Khorana Chair  at  Centre for DNA Fingerprinting and Diagnostics (CDFD), Hyderabad, India  for his help. His passing has inflicted a deep loss on both the personal and professional fronts.
cDNA Library Construction and Bioinformatics Male and female contigs previously obtained  (Bengtsson et al. 2012)  were analyzed through bioinformatics, in search of candidate TRPs. Tblastn searches were performed using available amino acid sequences of Lepidoptera and other insect TRPs. Contigs presenting similarity to TRP genes were further assembled using Cap3 (http://pbil. univ-lyon1. fr/cap3. php). Open reading frames (ORFs) were searched and translated to amino acid sequences using ExPASy (http://www. expasy. org/translate/), and Blastx on the Genbank non-redundant database (http://blast. ncbi. nlm. nih. gov/ Blast. cgi) was used to verify their annotation. For CpTRPA5 and its splice forms, transmembrane domains were predicted from translated sequences using TMHMM 2. 0 (http://www. cbs.