dataesr/scientific-paragraphs-categorization huggingface dataset:
As a result, P. tetraurelia germline MIC chromosomes--their sequence and precise number are not yet known--are fragmented into approximately 200 shorter MAC molecules healed by de novo telomere addition  (16). Key proteins required for programmed DNA elimination are: (i) the putative endonuclease PiggyMac (Pgm), necessary for the introduction of DNA double strand breaks at the extremities of IESs  (17, 18) ; (ii) the Polycomb-like putative histone methyltransferase Ezl1, necessary for histone H3 trimethylation of lysine 9 and lysine 27 during macronu-   (55). Duplicates from the last whole genome duplication are named a and b. Multiple alignments were performed with the MUSCLE software  (56). Phylogenetic analysis was carried out using PhyML 3. 0 (bootstrapping procedure, 100 bootstraps) with default parameters and trees were visualized using TreeDyn  (57).
For localization of CenH3a-GFP and CenH3b-GFP proteins, cells transformed with GFP transgenes were fixed as described in  (19). Quantification of GFP signal intensity was performed with the ImageJ software. The average fluorescence intensities of CenH3b-GFP in the two MICs (signal) and in corresponding volumes of the cytoplasm (background) were measured. The mean and standard deviation of the corrected average fluorescence intensities values (signal minus background) were calculated using at least 30 individual cells for each silencing condition.
ACKNOWLEDGEMENTS We thank  Jér ôme Poli  and  Haifa Touzi  for their contribution to the initial characterization of CenH3 proteins,  Olivier Arnaiz  and  Mireille Bétermier  for sharing unpublished RNAseq data and  Eric Meyer  for providing the plasmid pTI. Special thanks to all members of the  Duharcourt laboratory  for fruitful discussions and  Stéphane Brunet  and  Roger Karess  for critical reading of the manuscript. We acknowledge the  ImagoSeine facility , member of the  France BioImaging infrastructure supported  by the  ANR-10-INSB-04.
FUNDING Agence Nationale de la Recherche  [ ANR-12-BSV6-0017-02  ' INFERNO ' to S. D. ;  ANR-14-CE10-0005-04  ' PIG-GYPACK ' to S. D. ];  Centre National de la Recherche Scientifique [CNRS ATIP-Plus  to S. D. ];  Ministère de l'Enseignement Supérieur et de la Recherche  [to M. L. A. and A. F. ];  Fondation de la Recherche Médicale  [to M. L. A. and A. F. ]; LABEX ' Who Am I?'  [ ANR-11-LABX-0071   WHOAMI  and  ANR-11-IDEX-0005-02 ]. Funding for open access charge: CNRS.
In Argentina, the recent expansion of agriculture has turned into an extreme process almost completely dominated by soybean. The magnitude and speed of soybean expansion are 1 This study has received funding from l'Agence Nationale de la Recherche, from France, through the SYSTERRA program, under reference ANR-09-STRA-04. believed to be the main drivers behind social, organizational and economic changes, including the displacement of small-scale producers out of agriculture. Under these transformations, land leasing is a critical management practice and constitutes a link among agricultural actors. This study analyzes changes in land tenancy patterns considering the recent agriculturization process but also older drivers of change. Our results indicate that the expansion of agriculture affects small-and large-scale farms differently, as land renting practices and productive orientation show clear differences by size.
Data and Analysis Two main sources of data were used: farm level data and semi-directive interviews. These sources complement each other to describe the recent transformations experienced by local actors. The quantitative data from the selected farms selected provide information about the agronomic and management decisions made by the producers, while the semi-directive interviews allow the rationales and motivations behind these decisions to be explored. The farm level data include five variables describing the production and management practices and the relationships between owners and tenants of 247 farms of Balcarce. To ensure the representativeness of the sample, we collected general information of a relatively large number of farms, rather than more detailed information of a smaller number of farms.
The 247 farms constitute 45% of the total number of farms of Balcarce according to the 2002 National Agricultural Census (NAC) and cover 37. 8% of the land area of the district. Data from the 1988 and 2000 NACs were used to describe the evolution of local agrarian structure, including size and number of farms. The National Censuses define a farm unit as all agricultural land owned by a proprietor, wherever located, and thus figures for Balcarce include land owned by local farmers but located outside the district. In contrast, in our 2010 farm survey we defined a farm only as the land within Balcarce owned by the same proprietor. However, only 24 of the farms in the survey (less than 10% of the sample) have plots outside Balcarce and the main plot of most of them is located in Balcarce. Therefore, inconsistences in comparing data from the census and the survey should be small.
Farm level information was collected by interviewing agronomic consultants and using the cadastral map of the district. Data regarding farm size and ownership (name and residence of the owner) were taken directly from the cadastral map. Information regarding management decisions such as productive orientation, whether the farmer rents additional land, the percentage of the farm let out to tenants, and the type of tenant (i. e. , neighbor, an individual from the area but not a neighbor, a sowing pool, an individual from outside the area, or unknown) was taken from the interviews. The consultants were selected for having worked in specific parts of the district for several years and for participating actively in the local sociotechnical networks. As the consultants interviewed work and live in the district, they visit grain elevators, input retailers and cooperatives frequently and know land owners, tenants and the productive orientation of farms.
The principle of parsimony is applied when deciding on the optimal number of groups, which is kept to the minimum number possible that provides a comprehensive description of the farms. To implement the analysis, the packages FactoMineR  (Husson et al. , 2010)  and ADE4  (Chessel et al. , 2004)  of the statistics software R version 2. 11. 1  (Venables and Ripley, 2002)  were used. Readers interested in a more comprehensive and technical description of MCA are encouraged to consult  Greenacre (2007)  or  Abdi and Valentin (2007). The second stage of the analysis was based on eleven semi-directive interviews with seven farmers belonging to each of the seven groups identified in the typology, and four additional producers owning no land but renting the entire area that they farm. The interviews aimed to understand the rationales behind land leasing.
Proq631 was found within a putative gene encoding a cytochrome P450 conserved domain. For each genomic region, primers were designed using Primer3web version 4. 0. 0  [46, 47]  (http://primer3. ut. ee/). Information about the primers used is shown in Table  1. Thirty isolates were used to amplify by PCR the Proq845, Proq235 and Proq631 loci using the same PCR mixture as described above. These 30 isolates included: (i) isolates representative of the diversity according to five gene sequences (ß-tub, cmd, cct8, tsr1 and mcm7) and microsatellite markers, as well as (ii) isolates belonging to each of the six observed clusters in the previous study  [16]. The PCR program used is detailed in S3 Table. PCR products were sequenced using both their forward and reverse primers at the 'Plateforme Biogenouest' (Roscoff, France) using the dye-terminator technology.
Sequence assembly was carried out with Bionumerics version 6. 6 (Applied Maths, Belgium) and contigs were manually edited using Mesquite version 2. 75  [48]. Sequences corresponding to the eight loci chosen for multilocus analysis (ß-tub, cmd, cct8, tsr1, mcm7, Proq845, Proq235 and Proq631) were deposited in GenBank (see accession numbers in S4 Table. Sequence alignments were deposited in TreeBase (http://purl. org/phylo/treebase/phylows/study/TB2:S16359).
Posterior probabilities were determined from a consensus tree generated with the remaining 75,000 trees. MCMC convergence of our analyses was checked by using the Cumulative, Slide, and Compare analyses as implemented in AWTY  [55]. Incongruence Length Difference tests were performed (ILD,  [56]  as implemented in PAUP version 4. 0b10 (hompart option)). Phylogenetic trees were visualized and edited with FigTree version 1. 4. 1 (http://tree. bio. ed. ac. uk/software/figtree/). A cluster network consensus tree was obtained using Dendroscope version 3. 2. 10 [57,58] from the three Bayesian trees generated for Proq845, Proq235 and Proq631 loci in order to visualize incongruences among these trees.
roqueforti strains genome sequences and sequenced on the 30 isolates chosen for further phylogenetic reconstructions (S1 Fig; Table  3 ). Because the ILD tests indicated significant incongruence between the studied gene trees in both datasets (β-tub, cmd, cct8, tsr1, mcm7 on the one hand and Proq235, Proq631, Proq845 on the other hand) (P < 0. 05), no phylogenetic analyses were performed using concatenated datasets.
Penicillium roqueforti genetic diversity and population structure Preliminary tests were performed for the 24 identified microsatellite primer pairs on eight selected isolates. The number of alleles (n a ) detected varied from 1 to 4 and Polymorphism Information Content (PIC) values ranged from 0 to 0. 72. The four most polymorphic microsatellite markers (n a 3; PIC 0. 56) were used to genotype the whole collection of P. roqueforti isolates (n = 164) and allowed to detect 28 haplotypes. Interestingly, only 13 haplotypes were detected among the 140 blue-cheese isolates whereas 15 haplotypes were identified among the other isolates (n = 24). Significant linkage disequilibrium was detected between 5 locus pairs (out of 6) when the dataset was considered as a single population. This may result from a Wahlund effect if differentiated populations exist in the sample.
was used to determine the best-fit model of evolution for each dataset, namely: TIM2ef model for β-tub, TrN+G model for cct8, TIM1ef+G model for cmd the, K80 model for mcm7, TrN model for tsr1, TrN model for Proq235 locus, TPM3+I model for Proq631 locus and TIM1 model for Proq845 locus.
Acknowledgments We thank all the people worldwide who kindly provided cheese samples and therefore allowed us to create the working collection:  Tim Cogan ,  Raphaël Coton ,  Anne-Marie Coton ,  Andrew Dabrowski ,  Laurent Esclade ,  Maria Fernandez ,  Kévin Fontaine ,  Gareth Griffith ,  Alexis Guerin-Laguette ,  Frida Hassler ,  Jussi Heinonsalo ,  Ieva Jakobija ,  Annavera Laminolara ,  Vanesa Ludemann ,  Marie-Christine Montel ,  Marie-Pierre Murray ,  Jérôme Mounier ,  Patrice Nodet ,  Martina Peter  and  Hein Trip. We are grateful to  Jos Houbraken  for providing the P. psychrosexualis CBS 128137 HT isolate, to  J. I. Pitt  for helpful discussions on P. roqueforti macromorphology, to  Patrice Nodet  for his expertise on P. roqueforti micromorphology and to  Emese Meglecz  for help with QDD.
In each movie, we manually identified the start frame where the animal first triggered the attack and the end frame where the fish's jaw reach the initial position of the body of the water strider. The strike duration represented by the time elapsed between the start and the end frames was calculated using PCC software (Vision Research). Details about software and method of calculation can be found in this tutorial by Vision Research: http://www. visionresearch. com/Service--Support/Tutorials/ Measurement of water strider jump duration. This experiment was conducted in adult water striders to compare with the duration of flight below. To measure jump duration in a controlled manner, we simulated the attack using a dead backswimmer (Notonecta) attached at the end of a wire and manoeuvred by a manipulator.
This strategy reproducibly induced water striders to jump. We then filmed ten individuals at 2,000 frames per second. In each movie, we identified the start of the jump as the time elapsed between the frame where we see the first movement of the leg pushing downwards, and the frame where all legs lose contact with the water surface. Measurements of the time elapsed between start and end of the jump were performed using PCC software (Vision Research). Measurement of flight duration. To measure flight duration, we stimulated flight by increasing the density of water striders in the aquaria and by exposing them to an extra source of light. These conditions originate from our own observations while breeding water striders in the lab. We then took ten high-speed movies (2,000 frames per second) of 10 individuals during flight.
In each movie, we identified the start of the flight as the time elapsed between the frame where we first see wings moving and the frame where all legs lose contact with the water surface. Measurements of the time elapsed between start and end of the flight were performed using PCC software (Vision Research). Limnoporus dissortis reference transcriptome. A mixture of adult males and females, nymphal instars and various embryonic stages of L. dissortis were used to isolate total RNA using Trizol (Invitrogen). Transcriptome was sequenced using 454 Roche technology and assembled using Newbler program version 2. 6 (Roche). A total of 26,237 isotigs defining 16,368 isogroups were assembled. Assembled isotigs were annotated by sequence similarity against the NCBI 'non-redundant' protein database using BLAST2GO.
In addition to inferred annotations, for each annotated isogroup we predicted PFAM motifs using HMMER3 tools from Sanger institute. L. dissortis transcriptome can be retrieved in NCBI using the following accession number: PRJNA289202. Quantification of gene expression using comparative transcriptomics. RNA from dissected L. dissortis legs was used by ProfilExperts (Lyon-France) to conduct deep sequencing using TruSeq RNA kit and Illumina HiSeq2000 technology. A total of B50 million reads was generated per sample. These reads were trimmed and filtered to remove low-quality bases and aligned against the draft Limnoporus transcriptome and transcript levels were quantified by determining the number of Reads Per Kilobase per Million mapped reads (RPKM) in each sample  25. The raw reads of L. dissortis leg transcriptomes can be retrieved here: PRJNA289202.
gilt cloning. Total RNA from L. dissortis, A. paludum, M. hesperius, M. americana, H stagnorum, and M. mulsanti was extracted from different embryonic stages and nymphal instars. First strand cDNA synthesis was then performed for each species, using total RNA as a template, according to instructions outlined in the Invitrogen cDNA synthesis kit. Specific primers for gilt in L. dissortis were designed based on sequences obtained from the whole transcriptome of L. dissortis. Primers for each species used in PCR reaction to amplify a fragment of gilt, can be found in Supplementary Table  2. gilt sequence for each species can be retrieved in Genbank. gilt sequences from these various species can be retrieved in GenBank using the following accession numbers: KR704883, KR704884, KR704885, KR704886, KR704887, and KR704888.
Acknowledgements We thank  F. Payre ,  M. Averof ,  F. Bonneton  and  F. Leulier  for critical reading of the manuscript. We thank  F. Moreira  for help with species identification and  PSMN-ENS de Lyon  for providing access to servers and calculation power. This work was supported by an  ATIP-Avenir  from  CNRS  and an  ERC-CoG  #  616346  to A. K. and a PhD fellowship from UniversiteLyon1 to P. R.
Conclusion High-resolution multiscale imaging in plant sciences was until recently limited to the domain of remote sensing. It is now also possible to capture entire roots or shoots of plants, at various stages of development, with cellular or subcellular spatial resolution. These high-resolution imagings are producing huge amounts of data, specially when they are applied to large populations of plants in high-throughput phenotyping. In this framework, we have highlighted here some current approaches connected to the multiscale analysis of plants and pointed toward efficient computational implementation under the free and open software ImageJ in Table  2. Open problems emerge for image compression and image characterization. Multiscale approaches are specifically relevant for the new microscopies such as those presented in Table  1 ; these are more recent and have received so far, in a multiscale perspective, less attention than remote-sensing imaging or than proximal detection in the field.
Study site and experimental design The study was conducted using abundant plant species found in dry calcareous rangelands in southern France located on a limestone plateau (Larzac Causse) at the La Fage research station of INRA (French National Institute for Agricultural Research) (43 55 0 N, 3 05 0 E, 790 m above sea level). The climate of the plateau is sub-humid with a Mediterranean influence, with cool, wet winters and warm dry summers. Annual mean precipitation of 1070 mm occurs mainly during spring and autumn, and mean monthly temperatures vary from 1 C in January to  19 C in August (data 1973 19 C in August (data -2013 : from the on-site meteorological station; see  Chollet et al. (2014) ). The vegetation is dominated by perennial herbaceous species, the most abundant being Bromopsis erecta, along with loosely scattered shrubs and trees of which Buxus sempervirens and Juniperus oxycedrus are two of the most abundant shrub and tree species  (Bernard 1996; Bernard-Verdier et al.
Reflectance spectra were collected from duplicate samples Iris Bumb et al. -Dry matter content predicts forage quality presented in ring cells equipped with quartz glass using a FOSS Nirsystem 6500 spectrometer (FOSS Nirsystems, Silver Spring, MD, USA) operating at 400-2500 nm so as to produce an average spectrum with 870-1013 data points. Existing calibrations at CIRAD (French International Centre of Agricultural Research for Development) between the spectral properties and the measured digestibility were updated and adapted to our samples with reference to spectral analyses from 24 samples representative of our dataset. Calibration was performed using modified partial least square regression with WINISI software (version 4, Infrasoft International, Port Matilda, PA, USA). Statistical parameters of the calibration models for forage quality measurements are presented in File 1 [See Supporting Information].
Data analysis Statistical analyses were performed using R software (R Development Core Team 2010). Linear models were  used to test the influence of management regime, harvest date, growth form, and species (nested within a growth form) and their interactions with DMD, components of forage quality and DMC. These analyses were performed for each plant part (leaf, stem and reproductive part) of the studied species. The model selection, based on ANOVA, used manual backward elimination and stepwise regression with the 'lm' function. The normality of the distribution of residuals was verified for each model. The same procedure was applied to the four plant species in both treatments to test the influence of management regime, harvest date, and species and their interactions for each plant part.
Principal Component Analysis (PCA) was performed for each plant part at the time of peak biomass (harvest date 2) using the 'lme4' package to evaluate differences in DMD, the other components of forage quality and the DMC between species growth forms. The projection of the points on axis 1 was recovered to test differences in DMD, other forage quality components and DMC between growth forms using one-way ANOVA, followed by a Tukey test to determine differences between plant parts at the time of peak biomass. A variance decomposition analysis was performed for the four plant species present in both treatments in order to assess intraspecific variability of leaf DMD, components of forage quality and DMC (see Table  1 )  (Xu 2003). Pearson and Spearman correlations were calculated for each plant part of the 16 species, between forage quality and DMC.
1988) , and the 'species' effect was added as a random factor in the models tested. Several initial global conceptual models were developed following our hypothesis of causal relationships between the different variables (fertilization, grazing, DMD, NC, NDF and DMC), involving variations in direct and indirect effects between those variables. The overall fits of the path models were tested with a generalized d-sep test  (Shipley 2009 ) using the 'ggm' package in R. A Fisher's C test of the overall models was performed between each initial overall model proposed (expected covariance structure) and the data measured (observed covariance structure) in order to select the best model. A chi-squared distribution and a non-significant P value of fit indicated that the initial model structure and the data did not differ significantly and that the model suitably represented the data.
Acknowledgements We thank  B. Shipley  for his training and advice in path analysis. We thank  M. Del Rey Granado  for her invaluable help in the field and laboratory, and the technical staff of the experimental station ' INRA La Fage ' for access to facilities. We also thank  P. Hassoun  for helpful discussions and comments on the manuscript. We thank the associate editor,  Katharine Dickinson , and two anonymous reviewers for their fruitful comments, suggestions and advice which helped to greatly improve the manuscript.
Primers and Probes EHDV Target. Primers and TaqMan minor groove binder (MGB) probes were designed by multiple sequence alignment of segment 9 (available in Genbank) using MegAlign 8. 0. 2 (Lasergene DNASTAR) for the detection of all seven serotypes and the sequences of segment 2 for serotyping. The primers and probes were selected and evaluated using Primer Express software (Primer Express Software v3. 0. 1 by Lifetechnologies). Endogenous target. The concentration of primers and probe to detect an endogenous control (Beta actin) was optimised for use in the duplex real-time RT-PCR assays. The sequences of the two primers and probe are respectively: ACT_F_1005-1029 (5'-CAGCAC AATGAAGATCAAGATCATC-3'), ACT_R_1135-1114 (5'-CGGACTCATCGTACT CCTGCTT-3') and ACT_P_1081-1105 (VIC-TCGCTGTCCACCTTCCAGCAGATGT-TAMRA)  [23].
Primer and Probe Design A comparison of segment 9 nucleotide sequences (available in GenBank) from EHDV strains isolated around the world, and representing the seven EHDV serotypes, showed a conserved sequence in the 5' end region that allowed the design of two primers and one probe for the pan-EHDV real-time RT-PCR assay (Table  1 ). By aligning the segment 2 sequences of each EHDV serotype, it was possible to design two primers and one probe for EHDV-4, -5 and -8. There was greater sequence divergence among the different strains of serotypes EHDV-1, -2, -6 and -7, so more than two primers were designed for the specific real-time RT-PCR assays in order to ensure sensitivity.
Discussion In order to obtain good performance for the pan-EHDV assay, we decided to target VP6 encoding gene S9. In silico studies of S9 sequences available in GenBank showed that nucleotide variations ranged between 1. 2 and 33. 9%. However, a conserved region (in the 5' end region) appeared to be of interest for designing the primers and probe. Only one set of two primers and one probe was designed for this assay, whereas the previously reported pan-EHDV real-time RT-PCR assays use several primer pairs and/or probes targeting the NS3 or NS1 encoding genes (S10 and S5)  [18, 19]. The cost of the reaction can therefore be significantly reduced using this new assay. All the reference or field strains were detected and no amplification was generated with nucleic acid from the similar Bluetongue virus African Horse Sickness virus or various pathogens infecting cattle.