dataesr/scientific-paragraphs-categorization huggingface dataset:
4. 1. ConceptThe IAGOS central database is the main access point for observations measured by the IAGOS fleet. More than 44 000 flights have been carried out since August 1994. The database includes data from the former MOZAIC project (38 494 flights from August 1994 to December 2014), data from the CARIBIC project (390 flights since May 2005) and data, named IAGOS-CORE, from more than 6800 IAGOS flights since July 2011; see Fig. 6 for an overview.
manage metadata (for administrator), validate data and manage instruments (for PIs), choose the type of data set and the output format, display flight tracks on a map, retrieve data within a location bounding box and a time period, retrieve data related to an airport location and a time period, generate quick interactive visualisations: vertical profiles, time series and maps, direct link to download matching data from the Deutsches Zentrum fu¨r Luft-und Raumfahrt (DLR) HALO database and direct link to the JOIN interface in FZJ for intercomparison with MACC data. Data are provided to the users in standard formats. The output files contain metadata information and are either plain text files respecting the CSV format NASA AMES 1001 or NetCDF binary files compliant with the CF convention.
Acknowledgements IAGOS gratefully acknowledges financial support during its preparation, implementation and operation phase from the  European Commission  in  FP6  and  FP7  programmes, national research programmes in Germany (BMBF),  France  ( INSU-CNRS, MESR, CNES ) and  UK (NERC) , in addition to institutional resources in Germany ( Helmholtz Association, Max-Planck-Society, Leibniz Association), France (Universite´de Toulouse, Me´te´o-France ) and the  UK (University of Manchester, University of Cambridge) , and the continuing support by participating airlines ( Deutsche Lufthansa ,  Air-France ,  Iberia in Europe, China Airlines and Cathay Pacific in Asia). IGAS has received funding from the  European Community 's  Seventh Framework Programme  ( FP7/2007Á2013 ) under grant agreement no.
Background: The oil palm (Elaeis guineensis Jacq. ) is a major cultivated crop and the world's largest source of edible vegetable oil. The genus Elaeis comprises two species E. guineensis, the commercial African oil palm and E. oleifera, which is used in oil palm genetic breeding. The recent publication of both the African oil palm genome assembly and the first draft sequence of its Latin American relative now allows us to tackle the challenge of understanding the genome composition, structure and evolution of these palm genomes through the annotation of their repeated sequences. Methods: In this study, we identified, annotated and compared Transposable Elements (TE) from the African and Latin American oil palms. In a first step, Transposable Element databases were built through de novo detection in both genome sequences then the TE content of both genomes was estimated.
oleifera) for comparison purposes. To further facilitate data mining, software tools allowing the identification of the structural features of TEs from highthroughput sequencing data have been developed  [40] [41] [42]. In the present study, we have conducted a genome-wide annotation of Transposable Elements from the publicly available African and American oil palm genome sequences, with a focus on LTR retrotransposons. As a preliminary step, we have built a Transposable Element database and analyzed the TE content for each of the two oil palm genome sequences in order to compare their respective TE populations. We have further identified putative full-length LTR retrotransposons in the E. guineensis genome and characterized their structural diversity, chromosomal distribution and estimated their evolution through time.
De novo construction and analysis of consensus TE databases A total of 991 E. oleifera (Eo) and 846 E. guineensis (Eg) scaffolds were used for self-comparison in order to detect repeated sequences within each dataset. After clustering, 4025 and 10,193 consensus repeated sequences were selected and classified as transposable elements according to Repbase  [43]  for E. oleifera and E. guineensis, respectively. The complete databases are provided in Additional file 1 and a summary of their contents is presented in Additional file 2. The consensus sequences that were classified as either chimeric or potential host genes (272 and 278 sequences, respectively) were subsequently removed from TEdenovo's output. Among the remaining 3475 Eo consensus sequences, 72 % are assigned to Class I and 19 % to Class II, whereas for Eg (9915 consensus sequences) the respective proportions are 39 and 8 %, respectively (Fig.
6 , suggest that the oil palm genome underwent several waves of LTR retrotransposon amplification events, with different temporal patterns of transpositional activity for the main superfamilies Copia and Gypsy. Massive insertion events of Copia retrotransposons into the oil palm genome were displayed in two distinct peaks. By contrast, we observe a single peak for the insertion of Gypsy elements and Non-Autonomous LTR retrotransposons. Finally, we detect very few recent insertion events in our dataset, with the notable exception of the Pi519857_RT4_B11_L9_394 element (Copia superfamily, Oryco lineage).
In rice, the comparison of the transpositional history of LTR retrotransposons between the Japonica and Indica sub-species has provided evidence for two independent domestication processes in Asian rice  [50]. As a first step in our study, we have annotated the transposable elements from both Elaeis genomes through a de novo approach  [42]. While we found that the overall repeat content is nearly identical between both genomes, the comparison between the two TE databases revealed the occurrence of 6 times more Unclassified Repeats in Fig. 4  Chromosomal distribution full-length LTR retrotransposons in the Elaeis guineensis genome. Green track: Copia elements; orange track: Gypsy elements; blue track: predicted genes. The intensity of the coloring is directly proportional to the respective sequence densities the E guineensis genome compared to E.
According to some authors, this divergence took place 51 Mya ago  [39]  but other studies using different datasets and methods suggested that the speciation event might be much more recent: between 7 Mya ago  [52]  and 15 Mya ago according to Baker and Couvreur  [53]. Clearly, more phylogenetic analyses of the oil palm genomes are needed to ascertain both the time frame of this event and the dating of TE insertions since the genomic organization of TE populations results from a dynamic balance between amplification bursts and recombination events leading to DNA loss  [1, 6, 54, 55]. It must be kept in mind that the approach that were used here, and which are based on the de novo reconstruction of TE consensus sequences from available genome contig sequences, may have led to an underestimation of the repeat content.
Taken together with estimates of LTR sequence divergence and the high degree of structural diversification observed between retrotransposon lineages, this result suggests that no significant insertion event occurred recently in the African oil palm genome. However, in the absence of data on base substitution rates in oil palm genes and TEs, it is not possible to improve on the dating of these insertion events through the use of a "molecular clock" such as was used in the rice genome  [57]. Despite this limitation, our analysis shows that the full-length Copia and Gypsy elements studied were inserted into the oil palm genome around the same period of time but exhibited distinct dynamics. Interestingly, no recent insertion event was inferred, further strengthening the hypothesis that the LTR retrotransposons of the oil palm genome are most likely transpositionally inactive.
Conclusions The present study presents the most comprehensive description of oil palm LTR retrotransposons to date. Our results, which reveal a congruence in the tranpositional history of LTR retrotransposons between E. oleifera and E. guineensis, will provide crucial information for dating their divergence and further, to elucidate the history of genome evolution in the Arecaceae palm family. Moreover, our TE database will be a helpful resource in future studies aiming at assessing the possible contribution of LTR retrotransposons to genome and transcriptome variations resulting from the in vitro somatic embryogenesis process, especially in the context of the oil palm mantled phenotype.
Annotation of transposable elements A combination of manual approaches and automated programs (REPET package V. 2. 2-RC;  [42] ) were used to identify, classify and annotate repeated sequences from the largest scaffolds (size > 300 kbp) assembled for each of the studied genomes. The sequences that were investigated include 991 scaffolds amounting to a total of 730,618,412 bp of genome sequence from the O8-build and 846 scaffolds representing 1,068,102,326 bp from the P5-build, respectively. TE consensus nucleotide sequences were classified according to the Repbase database  [43]  and named according to the classification proposed by Wicker et al. [1] : DHX (Helitron), DMX (Maverick), DTX (TIR Transposon), DXX (MITE) for Class II elements, and RIX (LINE), RLX (LTR Retrotransposon), RSX (SINE), RXX (unclassified or nonautonomous retrotransposons), RYX (DIRS) for Class I element.
Consensus sequences assigned as LTR retrotransposons were further classified through the phylogenetic analysis of their reverse transcriptase (RT) amino-acid domains: putative RT coding domains were first identified in consensus nucleotide sequences using BLASTX  [71]  and translated using Genewise  [72] , then the resulting RT amino acid sequences (with a minimum length of 150 residues) and reference RTs from Gypsy Database 2. 0  [44]  were aligned with ClustalW to construct a NJ tree that was finally edited with FigTree (http://tree. bio. ed. ac. uk/software/figtree/). Repeatmasker  [45]  was used with default parameters so that sequences with less than 80 % identity to the reference sequence were masked. The LTR_STRUC 1. 1 algorithm  [46]  was used with default parameters in order to detect full-length LTR retrotransposons among the complete dataset of Elaeis guineensis (1,535,150,282 bp).
Copy number estimation, distribution and insertion time All identified full-length LTR retrotransposons were clustered into families or group using the CD-HIT software  [73]  with a minimum of 70 % of nucleotide identity and a minimum sequence coverage of 70 % between related elements. Within each family, the longest sequence displaying a high percentage of nucleotide sequence identity between both LTR regions was selected as the reference sequence. The copy number of each superfamily was determined using Censor  [74]. A copy is considered as complete if it covers a minimum of 70 % of the reference sequence with a minimum of 70 % of nucleotide identity. The density of retrotransposon distribution along pseudo-chromosomes was calculated using a home-made shell script, with a 1 Mbp sliding window (step size of 500 kbp) and plotted using CIRCOS  [75].
Transcriptional analysis of LTR retrotransposons The transcriptional analysis was carried out using data deposited into NCBI's databases (Bioproject number PRJNA201497). Eight sets of oil palm (Elaeis guineensis) transcriptome data from different tissues were reanalyzed: root (SRX278062), leaf (SRX278048), shoot apex (SRX278055), young female flower (SRX278052), mature female flower (SRX278053), pollen (SRX278051), kernel (SRX278018) and mesocarp (SRX278017). Data quality was evaluated with FastQC  [76]  and low quality reads were excluded with Cutadapt  [77]. Reads were mapped against our full-length LTR retrotransposons reference library using the BWA-MEM package with default parameters  [78]. Samtools  [79]  was used to calculate the number of mapped reads (counts) for each reference sequence and normalization was performed using the EdgeR package  [80].
Acknowledgments: We thank the staff from beamlines  BM30A ,  ID23eh1 , and ID23eh2 of the  European Synchrotron Radiation Facility  ( ESRF, Grenoble, France ). We are grateful to  E. Barbier  for the initial work with the FNR from A. fischeri. Funding: We thank the  CEA  and the  CNRS  for institutional funding. This work used the platforms of the Grenoble Instruct center (ISBG;  UMS 3518 CNRS-CEA-UJF-EMBL ) with support from  FRISBI  ( ANR-10-INSB-05-02 ) within the  Grenoble Partnership for Structural Biology  (PSB). Author contributions: A. V. did the crystallography work, analyzed the structure, and wrote the paper; C. D. and O. R. performed the purification, characterization, and crystallization of FNR; Y. N. supervised the work by C. D. and O. R. ; J. C. F. -C. supervised the work by C.
D. and O. R. , analyzed the structure and previous bibliography, and wrote the paper. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. Atomic coordinates and structure factors have been deposited with the Protein Data Bank codes 5E44 (holo-AfFNR) and  5CVR  (for partially degraded AfFNR). Submitted 12 August 2015 Accepted 4 October 2015 Published 4 December 2015 10. 1126/sciadv. 1501086Citation:  A. Volbeda ,  C. Darnault ,  O. Renoux ,  Y. Nicolet ,  J. C. Fontecilla-Camps , The crystal structure of the global anaerobic transcriptional regulator FNR explains its extremely finetuned monomer-dimer equilibrium.
They showed that a deletion of 4 bp is sufficient for loss-of-susceptibility to AvrXa7 and PthXo3. As discussed below Round 4), this genome editing strategy could be extensively used to develop resistant varieties to Xanthomonas in various systems. It is expected that more naturally occurring loss-ofsusceptibility alleles can be found by promoter screening of S genes in different host germplasm collections (see Round 4). An example of a resource for this type of screening is the recently released SNP data from rice obtained from the sequencing of the genomes of 3000 rice varieties, available in the SNPseek database  (Alexandrov et al. , 2015). Surprisingly when using this data to look for SNPs in a set of known EBEs in rice (not all from S genes) very few SNPs are found within the EBEs (Table  2 ).
It is worth noting, that no indels are included in the SNPseek data and that all the SNPs were obtained from mapping NGS reads onto only one reference genome  (Alexandrov et al. , 2015). So it is possible that more SNPs in these regions will be found using different tools and datasets. Nonetheless, this raises the question: how common are lossof-susceptibility alleles of S genes? Gaining resistance through loss-of-susceptibility alleles requires the plant to mutate a region of the promoter to avoid binding of the TAL effector without altering physiologically important regulatory elements in the promoter. This might be particularly hard to achieve given that many TAL effectors seem to bind to crucial elements of the promoter. As a matter of fact, most of the known functional binding sites for TAL effectors are located in a region overlapping with that of core promoter elements of the gene (between 300 bp upstream and 200 bp downstream of the transcription start site).
, 2012). Also, RVDs in  SNP data were obtained from the Rice SNPseek database  (Alexandrov et al. , 2015). the C-terminal region of TAL effectors seem to be particularly tolerant of mismatches  (Meckler et al. , 2013; Perez-Quintero et al. , 2013). So a theoretical scenario for point mutations in an EBE to be effectively selected would be if they occur in a position normally bound by a strong-effect RVD in the N-terminal region. This seems to be the case of the xa13 alleles found in the rice varieties Tepa1, BJ1, Chinsurah 11484, Chinsurah 11760, and Chinsurah 50930  (Romer et al. , 2010)  where a single nucleotide substitution in the position matching the first RVD of PthXo1 is enough to prevent binding of the TAL effector. It would be interesting to test whether the SNPs found in the EBEs in Table  2  can prevent the binding of the corresponding TAL effector.
Any such genes with a predicted EBE for the TAL effector are strong candidates. For these, functional characterization using designer TAL effectors is the next step  (Boch et al. , 2014). Then, bioinformatics and functional analyses can be used to identify S hubs. The identification of natural variants in the EBEs from germplasm databases or Ecotilling or the generation of EBE mutations by genome editing in specific EBEs will lead to loss-of-function alleles as new plant disease resistance sources. it is possible to accurately assemble complete TAL effector sequences from whole genome data (A. Bogdanove, personal communication). A more difficult and time-consuming strategy is to clone and sequence TAL effectors individually. A nontested way could be to generate TAL effector-specific libraries and sequence them.
The Prediction and Validation of Susceptibility Hubs in the Host Any host gene representing a benefit to bacteria is a potential plant susceptibility gene and can be considered as a candidate for transformation strategies. However, considering that the aim is to provide broad and durable resistance, those S genes that constitute convergence hubs for various TAL effectors (like the SWEET family) are ideal. These could be identified by combining EBE prediction using the RVD sequences for the major virulence TAL effectors identified and expression data (RNA-seq or microarray). Functional characterization of the S gene would also be ideal. Once a key S gene targeted by one or more major TAL effectors is identified, a logical step is: The Screening for Natural Loss-of-Susceptibility Alleles in the Germplasm For this, researchers can take advantage of the new sequencing technologies and the public genome sequence databases.
In addition to the Rice SNPSeek data  (Alexandrov et al. , 2015) , and other genomic databases for rice  (Yonemaru et al. , 2014; Zhao et al. , 2015) , similarly large datasets exist for other hosts worth exploring. In Arabidopsis, the 1001 project as of September 2014 includes the sequencing of over 1000 lines, representing a valuable resource to find resistance sources for X. campestris  (Weigel and Mott, 2009). In cassava, an important resource consisting of the partial genome for 600 accessions is available and can be exploited to identify polymorphism in EBEs for targets of TAL effectors from X. axonopodis pv. manihotis 2. In tomato the sequence of 84 accessions has been recently reported  (Tomato Genome Sequencing Consortium et al. , 2014). For important crops with no such databases, alternatives like ecotilling or amplicon sequencing can be considered for identifying natural loss-S alleles  (Wang et al.
Acknowledgments We are grateful to  J. Lang  for edits and comments and to  L. Lamy  for his help in retrieving SNP data. MH and AP-Q are supported by doctoral fellowships awarded by the  MESR  and the  Erasmus Mundus Action 2 PRECIOSA program  of the European Community, respectively. This project was supported by a grant from  Agence Nationale de la Recherche  ( ANR-14-CE19-0002 ) and from  Fondation Agropolis  (# 1403-073 ).
The measurements and the uncorrelated experimental uncertainties are given by σ exp i and ∆ i , respectively, and the theory predictions are σ th i. The χ 2 function of Eq. 2 can be generalised to account for asymmetric PDF uncertainties: Γ th ik → Γ th ik + Ω th ik β k,th , (3) where Γ th ik = 0. 5(Γ th+ ik -Γ th- ik ) and Ω th ik = 0. 5(Γ th+ ik + Γ th- ik ) are determined from the shifts of predictions corresponding to up (Γ th+ ik ) and down (Γ th- ik ) PDF uncertainty eigenvectors. The minimisation of Eq. 2 in its original form leads to a system of linear equations. The generalised function, with asymmetric PDF uncertainties, is minimised iteratively: the values of Γ th+ ik are updated using β k,th from the previous iteration and following the substitution of Eq. 3. Several iterations are required to converge, and the procedure is verified using the MINUIT program which yields identical results.
The central value and the uncertainties of the PDFs are evaluated with MC replicas  [45] : the data points are smeared using Gaussian distributions, according to their experimental uncertainties, and the PDF fit is repeated 1000 times, using different random seeds for the smearing. The central PDFs are calculated as the average of the replicas and the PDF uncertainties are calculated from their standard deviation. Figure  3  shows the comparison of the PDFs extracted with the MC-replica method by fitting the HERA I data, and by fitting the HERA I and Tevatron W -and Z-boson data. Figure  4  shows the comparison of the relative uncertainty of the two PDFs. A significant reduction of the PDF uncertainties is observed in the fit which includes the Tevatron W -and Z-boson measurements, in particular for the valence quarks and d quarks.
A fit of the HERA I and Tevatron W -and Z-boson data with the same settings, but with a correlation model in which trigger and identification uncertainties are treated as correlated bin-to-bin, yields very similar central PDFs and PDF uncertainties [not shown]. The χ 2 of all the data sets are also very similar, except for the χ 2 of the CDF W -boson asymmetry measurements, which is about twice as large. The W -boson charge asymmetries rely on the reconstruction of the W -boson rapidity, which is measured assuming a fixed W -boson mass, and inferring the unmeasured longitudinal momentum of the neutrino on a statistical basis  [5, 6]. The reconstruction of the Wboson rapidity introduces a model dependence in the measurement. To study the possible bias due to the W -boson rapidity reconstruction, an alternative fit is performed in which the W -boson charge asymmetries measured by CDF and D0 are excluded, and the latest D0 measurement of the electron asymmetry is included.
The χ 2 min / dof and the partial χ 2 of the fit are shown in Tab. 5. Also for this fit the partial χ 2 of each of the Tevatron and HERA I data set is close to unity. The d v PDF determined from the fit is shown in Fig. 5 , and compared to the nominal fit. The fit to the lepton asymmetry data yields very compatible results, but the uncertainties on the d v PDF are up to twice as large. The impact of posterior inclusion of the Tevatron W -and Z-boson measurements on the PDF uncertainties as estimated by CT10nlo, MMHT2014, and NNPDF3. 0 is assessed by profiling and reweighting. For consistency with the other PDFs, the uncertainties of the CT10nlo PDFs are scaled to 68% confidence interval by applying a factor of 1. 645. The three PDF sets already include the CDF and D0 Z-boson differential cross sections as a function of rapidity, and the MMHT2014 fit also includes the D0 muon charge asymmetry in W → µν decays and the CDF W charge asymmetry in the W → eν decay channel.
Only the measurements that are not included in each of the PDF sets are considered for the corresponding profiling or reweighting. The compatibility of the Tevatron data with the CT10nlo, MMHT2014 and NNPDF3. 0 sets is tested by evaluating the χ 2 function of Eq. (  2 ), accounting for asymmetric PDF uncertainties according to Eq. (3). To perform this calculation for the NNPDF3. 0 set, the covariance matrix for the predictions is decomposed using the eigenvector representation. Table  4  shows the compatibility between the Tevatron measurements and the above PDF sets, together with the partial χ 2 of each data set. The partial χ 2 per number of points of each of the Tevatron data set, and the total χ 2 / dof, are close to unity for all the PDFs, when the χ 2 evaluation includes the PDF uncertainties.