dataesr/scientific-paragraphs-categorization huggingface dataset:
RESULTS We performed nano-to millisecond transient absorption spectroscopy with visible light for PAS-GAF, PAS-GAF-PHY, and full-length samples. The data (figs. S1 and S2) establish that the D. radiodurans phytochrome has a photocycle similar to that of the A. tumefaciens homolog (Fig. 1B )  (24, 25). The derived time constants (53 ms and 3. 5 ms for PAS-GAF; 55 ms, 1. 0 ms, and 200 ms for PAS-GAF-PHY; and 80 ms, 2. 6 ms, and 27 ms for full-length samples) are indicated in Fig. 2. Figure  3  shows the time-resolved x-ray scattering signal from all three samples. Unlike the transient absorption spectra (fig. S1 ), the x-ray data show very little response on microsecond time scales. This is remarkable considering that time-resolved x-ray scattering can resolve conformational changes of less than 1 Å (root mean square deviation), provided that secondary structural elements move  (37) (38) (39) (40) (41).
In the reconstruction, the difference data are weighted by the photocoversion yield [a = [Pfr]∕([Pr] + [Pfr])]. We experimentally estimated a to be 0. 38 ± 0. 06 by titrating the laser power in the difference x-ray scattering experiment (see Fig. 5  and Materials and Methods). Considering the expected approximate size and shape of the dimeric protein, the SAXS analysis yielded reasonable values for R g and V c in the Pr state (Table  1  and table S1 ). By transition to the Pfr state, R g did not change significantly, and V c changed by <1% compared to the Pr state (see a = 0. 38 in table  S1 ). We verified that R g and V c are invariable in the range 0. 26 < a < 0. 45, covering the margin of error for a (see table  S1 ). We also measured the difference x-ray scattering for a concentration series and found that DR g and DI 0 converged to stable values for low concentrations (fig.
radiodurans  (14)  and a homology model based on the cytoplasmic part of a histidine kinase from Thermotoga maritima [Protein Data Bank (PDB) code 2C2A] shows good agreement. Black curves are from a separate experiment with 10-ms time resolution. The scattering vector modulus is defined as q = 4psin(q)/l. The models indicate that the quaternary structure of the protein does not change when going from Pr (gray) to Pfr (orange). We found that none of the generated ab inito models of the Pfr state shows an opening of the dimer at the DHp interface. This agrees with the observed small changes of the invariants R g and V c. Instead, the dimerization interface of the kinase domain is kept intact, and a rotation of the output domain with respect to the PAS/GAF domains is observed. The rotational motion is robust across the confindence range of a and was observed, to different extents, for all values with the exception of a = 0.
For the transient absorption data, the absorbance at 754 nm is shown (red lines). For the x-ray data, the similarity of the time-resolved data to the "steady-state" component (the response between 500 ms and 1 s) is shown (circles). This is extracted as described in the Materials and Methods. Error bars represent 95% confidence intervals based on individual detector images. Blue, green, and black circles represent independent measurements performed at ID09b, BioCARS, and cSAXS, respectively. The half-times for the structural transitions are approximately 1, 2, and 6 ms for the PAS-GAF, PAS-GAF-PHY, and full-length constructs, respectively. Table  1. SAXS parameters. Parameters pertaining to the Pr state were derived from absolute scattering data. The Pfr parameters were derived from reconstructed scattering curves, obtained by adding the difference curves (Fig.
If so, the millisecond process in the PAS-GAF moiety controls the larger-scale transformation of the rest of the molecule. The process is only slightly retarded by the attached PHY or PHY-histidine kinase modules, from 1 to 2 and 6 ms, respectively. Because the main structural change coincides with the formation of the meta-Rc state and the same transition has been associated with the transfer of a proton to the surrounding solution  (23, 24) , we suggest that the deprotonation step ultimately controls the biochemical activity of phytochromes. For the full-length protein, a final process is detected spectroscopically, which overlaps with the tail of the evolution of the time-resolved x-ray data. The present data do not provide direct information on the nature of this process. However, given the general direction of signal propagation, it is plausible that this process represents final rearrangements of the output domains, which weakly feed back onto the chromophore.
) was used to revert the sample to the Pr state by constant illumination through the Teflon tubing. Kinetic analysis. Each time-resolved data set was analyzed using the program PygSpec  (56). The time-dependent difference between the sample absorbance at time t and in the ground state was analyzed by approximating the data by a sum of exponentials convoluted with the Gaussian pulse. The expression DAðt; lÞ ¼ A 0 ðlÞ þ ∑ N i¼1 A i ðlÞe Àðt=t i Þb was used, where A 0 (l) is the final difference spectrum, and A i (l) (with i = 1, …, N) is the transient component spectrum, each associated with a decay time t i. The parameter b is an empirical quantity that represents the nonexponential behavior often found in biological samples. The fitting expression is merely a convenient analytical expression, and there is no meaningful relation between b and the actual distribution.
However, it serves as a reasonable mathematical tool for estimating the decay time constants, t i , from nonexponential decays. The minimum number of exponential components was determined by evaluation of fit residuals, and N was increased until the SD of weighted residuals did not improve further. X-ray scattering data collection SAXS measurements. Conventional SAXS data of the protein in Pr state were collected at BM29 at the European Synchrotron Radiation Facility (ESRF) at room temperature as described elsewhere  (14, 35). The collected patterns were subjected to standard Guinier analysis to retrieve R g and I 0. Data recorded at low and high concentrations (1. 3 and 22 mg/ml, respectively) were merged at q ≈ 1. 5/nm. Pump-probe time-resolved x-ray scattering. Time-resolved laser pump and x-ray-probe experiments were carried out at the BioCARS beamline 14-ID-B of the Advanced Photon Source and at beamline ID09B of the ESRF.
Finally, difference scattering curves from heating induced by a 1470-nm laser were used to subtract out effects of laser-induced heating. Time-resolved experiments using a rapid readout detector. The measurements were performed at the cSAXS beamline X12SA at the Swiss Light Source. The millisecond resolution data in Figs. 3  and 4  were collected as described by Takala et al. (14). The difference x-ray scattering data used for the structural analysis (fig. S3B ) were collected as follows: an x-ray energy of 11. 2 keV was used, and the detector was read out at 25 Hz over the course of a 5. 5-s x-ray exposure. Excitation of the sample was achieved using a 671-nm laser pulse 1 s after the first x-rays hit the sample. The dependence of the difference scattering signal on excitation pulse energy was measured by varying the length of the laser pulses (Fig.
5 ). Most of the data were collected at an energy density of ca. 5 mJ/mm 2 , corresponding to a 10-ms laser pulse. To ensure that the protein was in Pr at the beginning of each experiment (0. 5 s after the first x-rays), the sample was exposed to a 50-ms laser pulse at 789 nm, corresponding to an energy density of ca. 7 mJ/mm 2. To obtain difference scattering patterns, subsequent x-ray exposures with the 671-nm laser were subtracted from exposures without the laser. For each "laser on" cycle, the neighboring "laser off " cycles were then averaged and subtracted from the laser on cycle. The sample solution was stationary in the x-ray beam during each x-ray exposure, and a new sample was supplied by pumping the solution in between cycles. A reservoir solution of several hundred microliters of sample was kept at 20°C, and the capillary was kept at room temperature.
For the pump-probe data, each repeat (each individual detector image) was considered as its own observation, so that the spread in T for each delay time t could be used to estimate the uncertainty. This was done by letting each repeat contribute an element to T, and by binning identical delay times only after solving Eq. 1. Thus, Fig. 4  also displays the 95% confidence intervals as error bars. SAXS analysis software. The pair distance distribution functions of scattering curves was calculated using GNOM  (57). Difference scattering data were processed using our own code, and conventional SAXS parameters for all values of a were computed using programs from the ATSAS package  (58) , with the exception of the SAXS invariant V c and molecular mass that were calculated as described by Rambo and Tainer  (43).
Determining DR g and DI 0 from difference x-ray scattering data. Changes in R g and I 0 were evaluated with an adapted Guinier analysis where the difference scattering at low scattering angles was approximated as DI ¼ I 0 ðPf rÞe Àq 2 RgðPf rÞ 2 =3 À I 0 ðPrÞe Àq 2 RgðPrÞ 2 =3 similar to that of Levantino et al. (59). I 0 (Pr) and R g (Pr) were extracted from the Pr SAXS data, and the corresponding values for the Pfr state were recovered through minimizing the Euclidean distance between the data and the fit. Reconstruction of Pfr SAXS curves. Low q difference x-ray scattering (q < 1/nm) measured at low concentration (7. 2 mg/ml) was merged with high-concentration data (30 mg/ml) for higher q values. The absolute SAXS curve recorded at BM29 in the Pr state  (35)  was scaled and added to the difference data.
Ab initio modeling of difference x-ray scattering To assess the overall structure of the Pr and Pfr states, ab initio models were generated using DAMMIN  (44). Models were calculated in rounds. Twenty DAMMIN models were calculated for each scattering curve. Because phytochromes are expected to be elongated homodimeric proteins, the symmetry was fixed as P2, and the shape was assumed to be prolate along the protein. The assumption on twofold symmetry rests on the solved crystal structures of the D. radiodurans phytochrome photosensory domain [for example, PDB code 4Q0J  (33) ] as well as the near-symmetric arrangement seen in histidine kinases  (36). The starting shape was a sphere. For each curve, the 20 generated models were aligned using DAMAVER  (45). This gave a model that was used as input for a second DAMMIN round to generate 10 additional structures.
Construction of homology models A homology model for the full-length D. radiodurans phytochrome was constructed by combining known structures and homology information. The output domain was modeled using the SWISS-MODEL web interface  (60) , with the cytoplasmic portion of a histidine kinase from T. maritima (PDB code 2C2A) as a monomeric template. The model dimer was then derived using symmetry operations of the template structure, and the histidine kinase model extended in the N-terminal direction with an ideal helix containing the D. radiodurans phytochrome residues 492 to 501. The model of the output domain was combined with our previously proposed solution structure of the Pr state of PAS-GAF-PHY  (14)  in a number of steps. First, to reconcile the registry mismatch between the two parts of the connecting helices from the PAS-GAF-PHY fragment and the model output domain, a series of molecular dynamics simulations were run, where the backbone of residues 492 to 501 on the output domain was restrained by progressively higher force constants to overlap with the corresponding residues on the PAS-GAF-PHY fragments.
Acknowledgments: We thank  A. Liukkonen  for preparing parts of the protein samples used in this study. Funding: The authors acknowledge funding from  The Swedish Foundation for International Cooperation in Research and Higher Education. S. W. acknowledges funding from the  European Research Council  and the  Foundation of Strategic Research, Sweden. J. A. I. , H. T. , and H. L. acknowledge funding from the  Academy of Finland  and  Finnish Cultural Foundation. M. H. was funded by  Marie Curie  grant  IEF-GA-2013-CHE-624864  ANISOPROTEINXRAY. Beamline access at  ID09b  and  BM29  of the  ESRF  is acknowledged. Use of the Advanced Photon Source was supported by the  U. S. Department of Energy, Basic Energy Sciences, Office of Science , under contract no. DE-AC02-06CH11357. The use of BioCARS was also supported by  NIH National Institute of General Medical Sciences  grant  1R24GM111072.
Overall, 77. 7 % (363/467) of DEGs were shared between the xenobiotic transcriptome datasets. Despite differences in gene regulation observed among the types of xenobiotics studied, underlining  specific molecular mechanisms, we identified a core set of 363 genes, containing all 39 genes putatively involved in PHN detoxification. We propose that this core set of genes is representative of the gene network regulated in response to xenobiotics in higher plants (Additional file 2: Table  S4 ). Finally, we confronted our top list of DEGs (Table  1 ) to transcriptome dataset corresponding to the plant response to abiotic (stress selection), biotic and chemical perturbations, using the Genevestigator data base (Additional file 3: Figure  S9 ). A hierarchical clustering analysis was performed, revealing relatively identical a b Fig.
*: gene members of each family were retrieved from the TAIR website (http://www. arabidopsis. org/browse/genefamily/). Genes indicated in bold in each family correspond to differentially expressed genes selected after ANOVA analysis stress response, from 30 min up to 4 h of treatment. We identified 39 DEG genes classified in the PHN xenome, all regulated at 24 h. The 13 genes upregulated as early as 4 h following PHN exposure suggest that detoxification processes are engaged just a few hours after treatment. They mostly correspond to CYP involved in putative transformation of PHN (phase 1), UGT and GST of the tau family known to catalyze the conjugation and detoxification of numerous xenobiotics (phase 2). Gene ontology enrichment analysis and comparisons with other publicly available data provide clear evidence that detoxification processes occur, but also that ROS are rapidly produced.
Measurement of seedling growth and development Seeds were sown on MS/2 solid medium supplemented with 0, 50, 100, 200 and 400 μM of PHN or with DMSO alone as a control. For primary root length measurements, plants were cultivated vertically on square Petri dishes (15 × 15 cm). Primary roots were measured after 10 days of growth using digital photographs analyzed using Image J v 1. 45 s software  [71]. For each condition, primary root length of at least 18 independent plants was measured. Rosette fresh weight and chlorophyll content measurements were carried out as described in  [51]. Results are given as the mean of six measurements for the four independent biological replicates. Statistical analyses were carried on using the t-test in R  [72].
Clustering Hierarchical clustering analyses were performed via the Genevestigator toolbox for plant biology (https://www. ge nevestigator. com/gv/), with our top list (Table  1 ) measured as Euclidian distance, and based on stress, biotic and chemical data. Data were selected by sample, filtering on wild type genetic background. The stress, biotic and chemical selections correspond respectively to 788 samples from 310 perturbations, 450 samples from 111 perturbations and 500 samples from 117 perturbations.
Acknowledgments Authors would like to thanks  Marie-Noelle Soler  for help with microscopy analyses,  Marie-Laure Martin Magniette  for statistical analysis performed on microarray data,  Nathalie Marnet ,  Emilie Jardé  and  Alain Bouchereau  for carrying out the target analysis of metabolites, for PHN quantification in plants and  Rémi Peyraud  for helpful discussions and analyses related to plant metabolism model.
Thus, we inspected sequence alignments from O. sativa and O. glaberrima that covered genes plus 3 kb of their flanking regions, and selected 50 segments that contained regions with local SNP accumulations ('high-SNP' set, examples in Supplementary Fig. 6 ). As a control, 50 segments with an overall low SNP density, similar to that of the genome-wide average were used (examples in Supplementary Fig. 6 ). The 100 alignments were manually searched in detail for the presence of polymorphic transposons and other insertions and deletions (InDels). In the high-SNP data set, we identified 16 TE excisions, while in the control data set we only identified two excisions, a highly significant enrichment (Table  3 ). Interestingly, the high-SNP data set was also significantly depleted in transposons insertions, with 16 insertions identified in the high-SNP and 27 in the control data set (Table  3 ).
Methods Survey of DNA transposon distribution relative to rice genes. A total of 101 sequences of DTT_Mariner and DTH_Harbinger transposons from rice were obtained from the TREP database (wheat. pw. usda. gov/ITMI/Repeats/). They represent 19 DTT_Mariner and 25 DTH_Harbinger families. The 101 sequences were mapped with blastn to the O. sativa genome (version 6) using an in-house Perl script. The cutoff for blast hits was 50 bp and 80% sequence identity. If multiple TE families mapped to the same location, the one with the strongest blastn hit was chosen. To analyse their position relative to genes, the TE annotation was then cross-matched with the gff format gene annotation of the rice genome. We used the annotated transcription start and end points as anchor points and generated a data set of the positions of all annotated TEs within 5 kb upstream of the transcription start point and 5 kb downstream of the transcription end point for each gene.
Furthermore, positions of TEs inside the gene were recorded. We selected genes larger than 4 kb and recorded TE positions within 2 kb from each end of a gene. For simplicity, only genes in forward orientation were used. The final dataset included data for 4,994 genes. Sequences covered by TEs were added up for all genes, resulting in a final coverage plot that reflects the overall distribution of TEs relative to genes (Supplementary Fig. 1 ). Identification of transposon polymorphisms. We used an alignment of B60% of the genomes of O. sativa and O. glaberrima described in our previous study  9  to identify insertions larger than 50 bp. Insertions were screened for homology with TE sequences by blastn against the TREP database (wheat. pw. usda. gov/ITMI/ Repeats/). Using an in-house Perl script, TEs with the highest homology were mapped onto the O.
CDS for O. glaberrima were deduced from aliment with O. sativa CDS and are available upon request. Closest homologues from different species or, in the case of maize, homeologs that originated from a whole-genome duplication were identified by bi-directional blastn searches. Only homologues which had each other as the top blastn hit were used for comparison. Bi-directional closest homologues were aligned at the protein level using the programme WATER from the EMBOSS package (emboss. sourceforge. net). The aligned protein sequences were back-translated to ensure that corresponding codons were aligned. We considered only alignment positions corresponding to the third codon base for Ala, Gly, Leu, Pro, Arg, Ser, Thr and Val. For those amino acids which all have six possible codons (Leu, Arg and Ser), we used only the codons starting with CT, TC and CG, respectively (that is, the codons in which the third base can be exchanged without causing an amino acid change).
The 1,000 windows were aligned with the programme WATER from the EMBOSS package against themselves in reverse orientation. Outputs were parsed and visually inspected for the presence of inverted repeats longer than B15 bp and over B70% identity. The candidate sequences (inverted repeat and the sequences between them) were excised from the 1,000 bp. The candidate TEs were then used in blastn searches against the respective genome. Sequences with multiple hits were considered true DNA transposons. The de novo detection was done on one entire Arabidopsis chromosome, 2 Mbp of poplar linkage group 1 and 500 kb of rice chromosome 10 (Supplementary Fig. 8 ). Comparative analysis of DNA methylation. Data on methylation sites in O. sativa and O. glaberrima were kindly provided by Detlef Weigel and Claude Becker (Max Planck Institute for Developmental Biology, Tu ¨bingen, Germany).
These data sets will be published elsewhere (personal communication, Detlef Weigel and Claude Becker). Sequence segments of 4 kb spanning the polymorphic transposon in O. sativa and O. glaberrima were extracted from the chromosomes. Methylated sites were flagged and the sequence segments were aligned with the programme Water (emboss package, emboss. sourceforge. net/). Since we found that practically no methylation sites were conserved between the two species, methylation states were compared by simply counting the numbers of methylated sites in the sequences segments from the two species. The ratio of the number of methylation sites in O. sativa and O. glaberrima was then calculated for each transposon locus. For comparison, a second segment 2,000-4,000 bp downstream of the transposon was extracted.
A w 2 -test was used to test for differences between substitution rates in TSDs and LTRs. Data availability. Repositories where CDS of different species were obtained are listed in Supplementary Table  5. The genome sequence of O. glaberrima can be obtained from Gramene (ensembl. gramene. org). The authors declare that all other data supporting the findings of this study are available within the manuscript and its Supplementary Information Files or are available from the corresponding author upon request (such as original software and sequence aliments of genomic and CDS sequences).
Acknowledgements We thank  Detlef Weigel  and  Claude Becker  for providing methylome data for O. sativa and O. glaberrima. This material is based on work supported by the  Swiss National Foundation  grant # 31003A_138505/1  to T. W. , by the  US National Science Foundation  under grants # 0321678 , # 0638541 , # 0822284  and # 1026200  to Y. Y. , and R. A. W. and the  Bud Antle.
| Fields, plots, and subplots We conducted our study in an experimental banana field (Lamentin, Petit Morne, West French Indies, 14°37′25. 1″N, 60°58′07. 3″W, 3 m a. s. l) during the dry season (from 23 of April to 19 of June) of 2012. The sampling area or plot was 44 m long and 20 m wide. The banana crop (Cavendish Grande Naine) was in its first cycle when the data were collected to ensure homogeneity across the plot. The age of the banana plantation was 8 months. The climate at the study site is humid tropical with a mean (± SE) monthly temperature of 26. 5 ± 0. 3°C and a mean monthly rainfall of 174. 6 ± 21. 2 mm. Within the main plot, we defined 60 regularly spaced subplots (14. 7 m 2 each; Figure  1 ). F I G U R E 1 Schema of the experimental design. Gray squares: ceramic tile with baits; black circles: pitfall traps.
| Data mining and probability matrices of transition We first performed a principal component analysis and a hierarchical cluster analysis, based on Ward's method  (Ward, 1963) , to classify the observations at baits according to their similarities in species distribution and abundance. We thus obtained a hierarchical classification of observations for each replicate tile at one sampling time. Once the partition of observations into groups on the basis of the Ward's minimum variance agglomerative clustering was obtained, we used that partition as the initial value for K-means partitioning  (Murtagh & Legendre, 2014). This procedure was used to identify the type of "momentary" communities that we observed at baits and to established transition matrices. Moreover, the type of "momentary" community (which we called hereafter a group) observed at sampling time 1 are likely to be indicative of the colonies that was spatially close to the subplot (see below in Subplot scale dynamics and correlations between ant species abundances).