dataesr/scientific-paragraphs-categorization huggingface dataset:
The BV2-5 gene was found in S. exigua DNA from different geographic sources (America, Europe, Japan). However, European populations contained a frame shift mutation generating a truncated form of the protein (S2 Fig). Interestingly, data mining indicated that BV2-5 homologues are also expressed in S. littoralis (H. Vogel personal communication) and S. litura (Genbank). Bracovirus sequences encoding lectins in Spodoptera spp. and evidence of bracovirusmediated gene flux between Hymenoptera and Lepidoptera. A second group of S. exigua ESTs is composed of 6 sequences (500 bp long) with significant similarity to the C-type lectin gene of bracoviruses (close to 70% nucleotide identities). Accordingly we named these genes S. exigua bracovirus-like lectin genes (Se-BLLs). All 6 Se-BLLs code for hypothetical proteins of about 20 kDa with a predicted signal peptide at their N-terminus.
The Se-BLL2 gene fragment contains a C-type-lectin gene including the intron (Fig 1F ) and a short bracovirus upstream sequence. The Sf 5. 1 gene (BLL) organization is similar (Fig  1G ). Strikingly the analysis of the BV2-5 insertion also revealed the presence of a 40 bp regulatory sequence (Direct Repeat Junction, DRJ) involved in bracovirus circle production. This sequence is highly similar to the DRJ of CcBV C25 and is at the same position in the BV2-5 containing sequence as in C25, which is an unambiguous signature of the bracoviral origin of this sequence (Fig  5 ). This DRJ was used as a query for blastn analysis (NR data bank) and the retrieved sequences sharing similarity corresponded only to bracoviral DRJs of Cotesia congregata. Moreover no sequence was retrieved from WGS data base (NCBI) restricted to Lepidoptera genomes, indicating this DRJ is not generally present within lepidopteran genomes and confirming that this sequence could not be found by chance in Spodoptera exigua DNA.
Identification of bracovirus insertions Sequences sharing high similarity with Bracovirus sequences in lepidopteran genomes were identified using the 35 CcBV circles  [18]  as queries in megablast analysis (NCBI) against whole genome shotgun contig data banks (wgs at NCBI) restricted to lepidopteran genome sequences. Unlike the bioinformatic study which recently reported numerous short insertions of bracovirus sequences in lepidopteran genomes  [31]  we focused here on bracovirus-like sequences more than 1 kb long and encoding at least one gene. A blast analysis between proviral integrated circle sequences and the different contigs identified was used to determine the precise location of high scoring pairs (HSP) reported in Fig 1. HSP and annotated sequences were visualised using DNAPlotter  [77].
Homologous transcribed sequences were then searched for in the Transcriptome Shotgun Assembly (TSA) database at NCBI, for Spodoptera and Bombyx sequences (no data was found in TSA for Danaus plexippus). It should be noted that although all the identified insertions are very closely related to CcBV since the donor circle can be identified in many cases, this does not necessarily indicate that C. congregata was the donor species since only a handful of bracovirus packaged genomes have been sequenced to date among those associated with the estimated 1200 species of the Cotesia genus  [78].
Measure of the selection pressures operating on Danaus plexippus Ben4 and Ben9 genes Selection pressures operating on D. plexippus Ben4 and Ben9 genes were measured using Illumina data available at NCBI (SRA data bank) and corresponding to 80 individuals from different wild populations and 8 individuals from other Danaus species (D. erippus, D. chrysippus, D. eresimus, D. gilippus)  [30]  in order to identify molecular signatures that might be associated with particular selection pressures. The reads from D. plexippus samples were mapped onto the reference genome of D. plexippus  [30]  with Bowtie2 (2. 2. 4)  [83]  using default parameters. The Ben regions were then extracted with Samtools  [84]. A consensus sequence was obtained for each sample (minimum coverage of 5 reads and minimum frequency of a variant for the individual to be considered as heterozygote = 0.
form of the Sf 5. 1 C-lectin gene from the draft genome of S. frugiperda (Fig 1(G)). We thus confirmed these genes were present in Lepidoptera genomes and are flanked by sequences containing lepidopteran specific repetitive sequences (Fig 1). The other BLLs genes are known only by their cDNA sequences. Fragments of 3687 and 2529 bp were obtained for BV2-5 and Se-BLL2, respectively (Fig 1E and 1F)). The flanking sequence upstream of BV2-5 contains a retrotranscriptase from a mobile element (jockey-like) found in several lepidopteran species which is expressed in Spodoptera exigua (from TSA database Fig 1E), indicating that this part of the fragment corresponds to the lepidopteran genome. The two extremities of the Se-BLL2 containing fragment also show high nucleotide similarity (70-80%) with sequences from several Spodoptera species available in Genbank.
Acknowledgments We thank  H. Vogel  for giving access to S. littoralis EST database,  C. Béliveau  and  M. Cusson  for providing D. plexippus samples and  D. Smith  for the Danaina specimens. We are grateful to  B. A. Federici ,  T. Williams ,  J. Whitfield ,  E. Herniou ,  C. Gilbert  and  R. Cordaux  for stimulating discussions.
ROI selection and colour analysis For each site, a squared region of interest (ROI) was selected from a visual inspection of the images. The ROI had to be as large as possible and common to all images of the same growing season, while including as many plants as possible but no soil or sky areas. Image ROIs were then analysed using the open-source image analysis software, Image-J (Image-J v1. 36b; NIH, MS, USA). A customised macro was used to extract red-green-blue (RGB) digital number (DN) values between 0 and 255 (n colour ) for each pixel of the ROI, and a mean value for all pixel values in a given ROI of each image was calculated. Various colour indices can be obtained from digital image properties  (Mizunuma et al. , 2011) , but here we used only the chromatic coordinates, hereafter called colour fraction  (Richardson et al.
Data filtering procedure Image quality is often adversely affected by rain, snow, low clouds, aerosols, fog and uneven patterns of illumination caused by the presence of scattered clouds. These influences often create noise in the trajectories of colour indices, and are an important source of uncertainty that can hamper the description of canopy seasonal variations and the derivation of robust phenological metrics from colour index time series. To remove problematic images that were affected by raindrops, snow or fog from the digital photograph analysis, we used a filtering algorithm based on the statistical properties of the time series; we used two steps to filter the raw data. The first filter, based on the deviation from a smoothed spline fit as described in  Migliavacca et al. (2011) , was used to remove outliers.
Radiative transfer modelling To interpret the colour fraction time series produced by cameras in the network mechanistically, we combined the bidirectional radiative transfer model PROSAIL  (Jacquemoud and Baret, 1990; Jacquemoud et al. , 2009)  with some basic spectral properties of the photodetectors and the transmittances of the optical elements and filters used in the cameras, all combined into the so-called spectral efficiency of the RGB colour channels (G RGB , in DN W 1 , defined as the digital number per watt). This version of PROSAIL has been made available to the research community on the following repository (https://bitbucket. org/jerome_ogee/webcam_ network_paper). This version of PROSAIL is required to make the necessary link between the DN values measured by the camera sensors to the reflectances simulated by PRO-SAIL.
Acknowledgements. Lisa Wingate  was supported through a  CarboEurope-IP grant  awarded to  Professor John Grace  ( University of Edinburgh ), a  Marie Curie Intra-European Fellowship (LATIS)  awarded to  L. Wingate  and a  NERC Advanced Research Fellowship  awarded to L. Wingate. The salary for  Toshie Mizinuma  and the equipping of several sites within the European network with cameras was kindly supported through a  Jim Gray Seed Trust Award  from  Microsoft Research  awarded to  L. Wingate. Edoardo Cremonese  acknowledges financial support from the  PhenoALP  project, an  Interreg  project co-funded by the  European Regional Development Fund , under the operational program for territorial cooperation Italy-France (ALCOTRA) 2007-2013. The Alice Holt site is funded by the  UK Forestry Commission , and the StarDot camera installation was funded through the  Life+ FutMon project  ( LIFE07 ENV/D/000218 ) of the  European Commission.
Manuela Balzarola  acknowledges financial support from the  EU -project  Geoland2. Andreas Ibrom received funding by the  Danish strategic research project ECOCLIM  and the  EU  project  CARBO-extreme , whilst installation of the webcam was initiated and funded by the  EU  infrastructure project IMECC. We also kindly acknowledge fieldwork funding from the  British Embassy Tokyo  and the  British Council   UK-Japan 2008 collaborative Project Grant Award ,  GHG Europe  and STSM support for  T. Mizunuma  from the  EUROSPEC Cost Action   ES0903. We also thank the  Phenological Eyes Network  and the  US PhenoCam Network  and especially  Andrew Richardson  and  Shin Nagai  for their assistance and encouragement developing the European network. We are also grateful to  Daniel Lawton  for his fast response time to questions regarding the technical details of the Stardot camera.
Genetic identification Unless otherwise specified, all statistical analyses were carried out with R version 3. 0. 2 [37]. Total genomic DNA was extracted from the caudal fin sample, and a 500-bp fragment of the mitochondrial cytochrome b gene (which can be used to determine the maternal inheritance of individuals) was sequenced by standard polymerase reaction (PCR) procedures, as previously described  [38]. SEQSCAPE 2. 5 software (Applied Biosystem1) was used to align and correct sequences. We amplified 41 microsatellite loci with five multiplex PCR kits, as described in  [34]  and  [39]. The INTROGRESS R package  [40] [41]  was used to estimate the hybrid index (h). A second hybrid index was estimated using the Bayesian model-based clustering algorithm.
Ecological traits Age, size and coefficient of condition. We compared the mean sizes of the groups (C. nasus, P. toxostoma, hybrids) between three environment conditions (Durance basin, Ardèche basin and "reference populations," variable env), performing ANCOVA (type III tests). Age, determined by scalimetry, was used as variable of adjustment for mean size comparisons. Coefficient of condition K (= weight (in mg)/size (in cm) 3 ) was considered as an estimate of the "well-being" of the fish  [43]. We studied the effect of three factors on K: size, species status (Pt or Cn), designated sp, and environment condition (env). We first consider a dataset (n = 1,809) corresponding to non-hybrid specimens after the exclusion of 12 specimens because they present extreme K values (K<5 or K>20), most likely due to errors in the determination of weight.
This dataset included individuals from all sets of conditions (the Durance basin, the Ardèche basin and the "reference populations," defining the env variable). We considered the model K = env x bs(size, m) x sp + ε where bs (size, m) is the polynomial basis of degree m<6 for size, and the value of m is selected on the basis of the Akaike information criterion (AIC). In the selected model, a type III sum of squares was considered in order to test the effects. The interpretation of simple effects was simplified by centering the size variable (centered) on the overall median (13. 25 cm). For example, species comparisons were carried out for a fixed size of 13. 25 cm. We then considered hybrid specimens (n = 145). As hybrid specimens are genetically defined by h, they may be theoretically viewed as a mixture of a P.
toxostoma as vulnerable A2ce ver 3. 1  [35]  in their origin area and the C. nasus as least concern ver 3,1 locally threatened  [36]. Dietary analyses therefore had to be carried out by non-invasive methods. We therefore used the PCR-based method for feces developed in a previous study  [31]  to obtain qualitative (presence/absence) information about the prey ingested by the fish (S1 Table ). We then construct a feeding index defined by the first axis of the PCA on prey proportion  [44] [45]. This index, after discretization, was subjected to a multinomial logistic modelling in which season, environment and species defined the explanatory variables. Morphological analysis. We used the landmark-based morphometric approach as described in  [25] : 21 homologous landmarks were digitized with TPSDIG software  [46] , and a generalized procrustes analysis (GPA) was performed on their coordinates.
We thus considered 21 x 2 = 42 morphological variables. Each coordinate was then modeled in the same way as the coefficient of condition K. First we analyzed non-hybrid specimens (n = 1,684), and second we compared hybrid specimens (n = 132) to predictions obtained via the first model (S1 Text). Explanatory variables are species status sp (Pt or Cn), environment conditions (env) and size. Size is considered here as a surrogate for the development. Hence morphological modifications related to the size will be interpreted as ontogenetic deformations  [47]. All the data produced for this work are available on S2 Table.
In order to assess the sustainability of this situation, we analyzed the abundance of the ten most present species (including both chondrostoms) in our seven syntopic stations across time (S2 Text, S8 Fig) based on the electrofishing database (48 freshwater fish taxa and 590 sites) of the French National Agency for Water and Aquatic Environments (ONEMA,  [70] ). It appears that abundances of C. nasus and P. toxostoma are quite stable in the Durance, underlining the persistence of a minimum viable population density in this river. This strongly suggests that the observed traits displacement (i. e. pedomorphosis) for chondrostoms in the Durance River do not constitute the premise of a demographic decline, but rather a phenotype displacement (accommodation and/or adaptation) allowing them to persist in this ecosystem.
Acknowledgments We thank the  Directions Départementales de l'ONEMA  ( Office National de l'Eau et des Milieux Aquatiques) from Aude, Ain, Alpes de Haute-Provence, Haute-Alpes, Ardèche, Meuse and Allier  for their assistance in the collection of faeces and baseline samples. We particularly thank  Jean-Pierre Chevalier  from  ONEMA Ardèche ,  Alain Devaux  for Chondrostoma nasus populations in the Rhône River, and  Henri Persat  for the Parachondrostoma toxostoma population in the Suran River. We thank the  AAPPMA (Association Agréée de Pêche et de Protection du Milieu Aquatique) in Ardèche, particularly Serge Perbost (Ruoms)  and  Jean-Claude Beranger (Saint-Just d'Ardèche). We also thank  Jean-Pierre Cornec  for his valuable help in the analysis of fish scales. This work was conducted through the molecular facilities of the  LabEx CEMeB (Montpellier, France ).
Data Analysis All data analysis were conducted with R software (R Development Core Team, 2010). Student t-test was used to verify the differences between the two source-sink ratios at each developmental stage. Carbon allocation analysis was conducted as it follows. First, the carbon accumulated in berries throughout development was calculated as a function of hexose concentration and berry fresh weight with a carbon transformation coefficient of 0. 4 g carbon g -1 hexose. Second, the total carbon accumulated (C) in berries per vine was fitted to the following sigmoid curve  (Sadras et al. , 2008) : C = C max 1 + e t 0 -t b where t is the number of days after flowering, C max is the maximal quantity of carbon (g), t 0 is the number days after flowering when carbon quantity is half the maximum, and b represents the carbon accumulation duration from 0.
Our results and those from  Parker et al. (2015)  both confirm that the organic acids are less responsive to carbon limitation than sugars. In addition to the relative sensitivity of sugars and organic acids, we also studied the response of important secondary metabolites such as anthocyanins. Source limitation caused 75 and 93. 5% reductions in anthocyanin concentrations in Cabernet Sauvignon and Sangiovese berries at harvest, paralleled by only 17. 5 and 36. 7% reductions in sugars, as compared to the nonsource limited berries. After recalculation from the dataset of recent reports, we found that source limitation caused a 99. 2% reduction in anthocyanins with a 38. 5% reduction in sugars in cv. Jingyan (Vitis vinifera;  Wu et al. , 2013) , and a 17. 5 or 19. 1% reduction in anthocyanins with a 8.
A similar reserve remobilization could explain the high carbon proportion that was observed when it was cloudy and the vine photosynthesis rate was extremely low. Although we did not quantify the reserve remobilization,  Weaver (1963)  reported that reserves (both soluble sugars and starch) in shoots were significantly reduced by source limitation in cv. Carignane and Zinfandel vines. Kliewer and Antcliff (1970)  estimated that as much as 40% of the total sugars in berries may come from storage tissues of the vine. Using 14 C-labeling,  (Candolfi-Vasconcelos et al. , 1994a)  showed that carbon reserves from the woody storage tissues can be actively reallocated into berries under source limitations. Future use of 14 C-labeling, whole-canopy net carbon exchange rate (NCER) measurement, and carbon content assessment in various tissues (leaf, shoot, wood, fruit, and root) would provide a valuable dataset for the quantification of the carbon balance and allocation analysis.
Acknowledgments This research was supported partly by a grant from the  Environment and Agronomy Department of the Institute National de la Recherche Agronomique (INRA). It also received funding from the  European Community 's  Seventh Framework Program  ( FP7/2007-2013 ) under the grant agreement no. FP7-311775 , Project  INNOVINE. This study has been carried out in the framework of the Cluster of Excellence COTE. We thank  Dr. Philippe Vivin  for his valuable suggestion on the discussion.
1 software. The instrument was calibrated by multipoint calibration using fragment ions that resulted from the collision-induced decomposition of a peptide from β-casein, β-CN (193-209). To identify peptides, all data (MS and MS/MS) were submitted to X! Tandem using the X! Tandem pipeline developed by PAPPSO (Plateforme d'Analyse Protéomique de Paris Sud-Ouest (PAPPSO), INRA, Jouy-en-Josas, France, http://pappso. inra. fr). The search was performed against a database composed of (i) a homemade database containing all the predicted proteins of the P. freudenreichii strain CIRM-BIA 1 used in this study and (ii) a portion of the UniProtKB database corresponding to P. freudenreichii. Database search parameters were specified as follow: trypsin cleavage was used and the peptide mass tolerance was set to 0.
(Continued)Fold changes correspond to the protein overexpressed with a minimum fold change of 1. 2 in the CdM or EJ determined by image analysis **: e-value is the number of times a given peptide score will be achieved by incorrect matches from a database search. Protein identifications were automatically validated when they showed at least two unique peptides with an e-value below 0. 05 corresponding to log(e-value) < -1. 30 doi:10. 1371/journal. pone. 0135780. t002 higher amount than in CdM, as well as other components such as citrate, peptides (22-30 g kg -.
Acknowledgements Publication of this work is funded by the  Agence Nationale pour la Recherche ,  Ancestrome  project  ANR-10-BINF-01-01. PB was visiting INRIA thanks to  FAPESP grant   2013/25084-2  when this work was elaborated. This article has been published as part of  BMC Bioinformatics Volume 16 Supplement 14 , 2015: Proceedings of the 13th Annual Research in  Computational Molecular Biology (RECOMB) Satellite Workshop on Comparative Genomics: Bioinformatics. The full contents of the supplement are available online at http://www. biomedcentral. com/bmcbioinformatics/supplements/ 16/S14.
, 2013; Pautasso et al. , 2013; Coulibaly et al. , 2014; Deu et al. , 2014). This paper is the product of a series of interdisciplinary workshops conducted biannually over three years that examined the nature, role and significance of farmer seed networks in Africa, Europe, Latin America and Oceania. The workshops brought together the NetSeed network, a French initiative funded by CESAB-FRB (Centre de Synthèse et d'Analyse sur la Biodiversité-Fondation pour la Recherche sur la Biodiversité), to share datasets and field experience of researchers working on farmer seed provisioning in different societies, cultures and economies  (Pautasso et al. , 2013). Participants contributed considerable depth of field-based understanding of farmer seed networks to workshop discussions from a diversity of disciplinary perspectives, including ecology, plant genetics, anthropology, ethnobotany, sociology, political science, geography and development studies.
Data acquisition and handling were carried out by connecting the GC to a computer equipped with the TotalChrom workstation (Perkin-Elmer, Villebon-sur-Yvette, France). Individual FAMEs were identified by comparing the retention times of authentic standard mixtures. The results of individual FA composition were expressed as a percent of total identified FAME. Chemical analyses of feed were performed in duplicate for each sample according to AOAC (Association of Official Analytical Chemists 1984) methods: ash (7 h at 550°C), crude fat  [31] , and crude protein (Dumas method with an Elementary NA 2000 1 , N × 6. 25). FAME were extracted and analyzed on total lipid fraction using the previously described method.
Temperature was kept constant by a recirculating water system from the external bath (Teco TR20, Conselice, Italy). A flush pump allowed water exchange between the respirometer and the external bath, in which water temperature and oxygenation were controlled. Oxygen consumption measurements. Oxygen concentration in the respirometer was continuously measured during the experiments with an oxygen probe (PreSens, GmbH, Regensburg, Germany) connected to an oxymeter (Oxy-4, PreSens, GmbH, Regensburg, Germany) transferring oxygen data every 10 s to a storage computer. The oxygen concentration was automatically adjusted according to the real-time temperature recorded in the respirometer. Oxygen consumption (MO 2 ) was measured by intermittent-flow respirometry, based on an alternation between (i) a flushing phase (5 min) and (ii) a measuring phase (20 min), during which the flush pump was turned off, preventing the inflow of water from the external bath into the respirometer.
Data analyses For each fish and at each temperature tested during the challenge, the aerobic scope AS and the net cost of transport at maximum exercise NCOT were calculated. AS (mgO 2 kg -1 h -1 ) was determined for each fish as MO 2max -MO 2min measured at the same temperature. NCOT (mgO 2 kg -1 m -1 ) was calculated according to Clark et al. [38] : NCOT ¼ ðMO 2max À MO 2min Þ U max ð5Þ.