dataesr/scientific-paragraphs-categorization huggingface dataset:
This suggests a divergent transcriptional control of this gene and potential additional functions in hemichordates. To study the role of Nodal signaling in P. flava, we performed pharmacological drug treatments using SB431542 that inhibits the function of Alk4/5/7, the TGF-β receptor activated by Nodal, Activin or TGF-β itself. Hence, one could argue that SB431542 treatments could affect signaling other than the one mediated by Nodal. While this may be true, we have not been able to identify Activin by degenerate PCR or in our RNAseq datasets, and TGF-β appears to be expressed well after the end of gastrulation prior to hatching (data not shown). Therefore, we currently believe that the phenotypes observed with SB431542 treatments in P. flava are caused by inhibition of Nodal signaling during embryonic development.
However, it is noticeable that Pf-cripto, an essential co-receptor for Nodal signaling  (Gritsman et al. , 1999)  in vertebrates, is expressed in the apical domain from blastula to late gastrula stages. This expression pattern suggests a role for Nodal signaling in patterning the A/P axis or, perhaps the larval nervous system in P. flava. The Pf-cripto expression pattern also suggests that the mesodermal and D/V patterning phenotypes we observed in SB431542-treated embryos may be linked to Cripto-independent Nodal signaling as has been described during early vertebrate embryogenesis  (Liguori et al. , 2008). Alternatively, there could also be additional Nodal coreceptors that we have not been able to identify in our RNAseq datasets. Recent studies in the cnidarian Hydra, the gastropod mollusc Lottia gigantea and echinoderms have suggested an ancestral function of Nodal signaling in establishing axial asymmetries  (Watanabe et al.
Cloning P. flava genes With the exception of Pf-nodal, all sequences described in this study were isolated in the course of a transcriptome analysis described in  (Röttinger and Martindale, 2011). Sequences were used to sub-clone full-length open reading frames (ORF, or the longest possible ORF) of the genes of interest into pGemT® (Promega Corp. ) from mixed stage cDNA. If needed we performed 5′ and 3′ RACE PCR on mixed stage RACE cDNA using the SMART TM RACE cDNA Amplification Kit (Clonetch Inc. ). Degenerate, RACE-PCR as well as full-length primers used to clone Pf-nodal are indicated in supplementary material Table  S1. Nucleotide sequences have been submitted to GenBank and the accession numbers are indicated in Table  1.
Phylogenetic analysis Sequences from the following animals were gathered from NCBI protein database (http://www. ncbi. nlm. nih. gov/protein) and are abbreviated as follows: Am -Alligator mississippiensis; Amil -Acropora millepora; Sequences were aligned using MUSCLE (http://www. ebi. ac. uk/Tools/ msa/muscle/) and then trimmed according the conserved protein domains. Protein domain boundaries were identified using the SMART protein prediction database (http://smart. embl-heidelberg. de/). Phylogenetic trees were constructed using MrBayes  (Huelsenbeck and Ronquist, 2001; Ronquist and Huelsenbeck, 2003)  and are based upon five million generations using a "mixed" evolutionary model. Trees were imported and edited using FigTree (version 1. 4. 0, http://tree. bio. ed. ac. uk/software/ figtree) and finalized using Adobe Illustrator (CS6).
PBS was used for washes between antibodies. Specimens were mounted in 80% glycerol and imaged using a Zeiss LSM 710 confocal microscope running the LSM ZEN software (Carl Zeiss). Antibodies tested and used (all Cell Signaling Technologies, Inc): Phospho-Smad1 (Ser463/465) / Smad5 (Ser463/465) / Smad8 (Ser426/428), #9511S; Phospho-Smad2 (Ser463/465) / Smad3 (Ser423/425), #9510S; Phospho-Smad2 (Ser465/467), #3101S; Phospho-Smad2 (Ser245/250/255), #3104S; Phospho-Smad2 (Ser465/467), #3108S; Phospho-Smad2 (Ser465/467), #3108P; Phospho-Smad3 (Ser423/425), #9520S; Smad3, #9513; Smad3, #9523S. All expression and activation pattern can be consulted at: http://www. kahikai. org/index. php?content=genes.
, 2004; Teng et al. , 2010; Pogge von Strandmann et al. , 2012)  and atmospheric mineral dusts  (Kisakurek et al. , 2004; Liu et al. , 2013; Huh et al. , 2004) , both can shift the isotopic signature of the bulk soil. Despite the fact that atmospheric inputs can significantly contribute to soil solutes (e. g. ,  Widory et al. , 2005; Millot et al. , 2007) , very little atmospheric data exists for non-traditional stable isotope systems as pointed out by  Millot et al. (2010b). In order to better characterize Li atmospheric inputs and to investigate their influence on Li isotopes as a weathering proxy, we analyzed here the Li isotopic fractionation in the Quiock Creek catchment, a tributary of the already well-constrained Bras-David River basin (monitored within the framework of the French Critical Zone Observatory) on the Caribbean island of Guadeloupe.
Water budget The mean annual rainfall is 3500 mm yr - 1  (ObsErA database). The yearly average throughfall flux varies significantly between the two years studied: 3530 mm yr -1 for the first year (June 2011 to June 2012) and 2990 mm yr -1 for the second year (June 2012 to June 2013). We used a sliding average to estimate a mean throughfall flux of 3079 ± 660 mm yr -1. Unlike throughfall, stemflow flux cannot be accurately estimated because of the difficulty in determining the water interception surface of the trees. The discharge of the catchment was measured ten times in the Quiock Creek and was found to vary between 150 and 400 L. min - without significant loss. As we know the throughfall flux, the median throughfall Cl concentration (100 µmol L -1 ) and the mean Cl concentration in RQ (272 µmol L -1 ), we can infer the discharge.
Acknowledgements: This work has been financially supported by  INSU-CNRS  and by the  Région Guadeloupe. H. L. Buss  acknowledges support of the  NSF-CZEN International Scholars Program. This work could not be done without logistical support from two  INSU-CNRS  observatories run by IPGP: the  Observatoire Volcanologique et Sismologique de Guadeloupe (OVSG)  and the  Observatoire de l'Eau et de l'Erosion aux Antilles (ObsErA). We thank in particular  O. Crispi  from  OVSG  for his assistance in field work and the ObsErA advisor E. Lajeunesse. This study also received funding from  Région Guadeloupe  which supported the project " Vulnerability of tropical ecosystems of Guadeloupe ", in partnership with the  Antilles-Guyane University  and the  Parc National de Guadeloupe. We especially.
23 re, we report a first-principles study of the electronic absorption spectrum of the full LHC-II Chl chromophore network in which all atoms were treated at the same theoretical level using real-space time-dependent density functional theory (TDDFT)  24  as implemented in the Octopus code. 25 Some of the TDDFT calculations performed in this work are at the edge of what is feasible with today's computer resources and required extensive optimisations of Octopus. These involved not only the parallel execution  26  , but also issues related to memory management  27  , the Poisson solver  28  , the initialisation  29  , input/output efficiency  30  and post-processing. To the best of our knowledge the geometry optimisation of the full 17,000 atom LHC-II complex performed in this work using the Mopac electronic structure package is the largest performed to date using semi-empirical electronic structure methods.
Preparation of LHC-II Geometry The initial geometry of LHC-II was extracted from the crystal structure of the spinach major light-harvesting complex (PDB accession code 1RWT). 31 Several lipid molecules originating in the experimental crystallisation mixture that remained in the crystal structure, β-nonylglucoside and digalactosyl diacyl glycerol, were removed as these were not part of the biological unit. Furthermore, these were expected to have little or no impact on the excited state electron dynamics of the LHC-II chromophores. Hydrogens were added using the Chimera molecular modeling package. 32 At this stage it was necessary to select the protonation state of acidic residues located at the stromal and lumenal membrane/aqueous interfaces of LHC-II. It was decided to protonate all acidic side chains at these interfaces since it was considered that in the cellular environment the charges associated with these side chains would be effectively shielded by counter-ions in solution or by association with other charged bio-molecular species.
A solution to this problem lies in quantum mechanical electronic structure methods where no bonds are enforced and atomic nuclei are free to move in the potential created by the electronic structure of the system being studied. Due to the size of the LHC-II system the only feasible choice in this case was to use a semiempirical electronic structure method. The recently developed PM7 Hamiltonian as implemented in the Mopac semi-empirical electronic structure package was selected as this has been shown to closely reproduce molecular geometries calculated with high level quantum chemical methods and also provides a good model of weaker interactions such as hydrogen-bonding and dispersion forces. 33 e initial step in the refinement of the crystal structure at the PM7 level involved optimisation of the positions of only the hydrogen nuclei with all other atoms fixed in space.
Real-space time-propagation TDDFT calculations All absorption spectrum calculations of the LHC-II complex were performed with the realspace/time-propagation TDDFT code Octopus. 25, 34, 35 In Octopus, all the relevant functions are discretised in a real-space regular rectangular grid. To make the calculations computationally affordable, the core electrons were treated using norm-conserving Troullier-Martins pseudopotentials. These pseudopotentials were filtered using the scheme proposed by Tafipolsky and Schmid to remove the high frequency components that cannot be described accurately in the grid. 36 The grid parameters that control the numerical convergence are the spacing between the grid points and the size of the simulation box. We found that a grid spacing of 0. 2 Å and simulation boxes constructed from a union of spheres of radius 4 Å centered at the nuclei were necessary to converge the position of the main spectral peaks within 0.
Acknowledgments The authors acknowledge financial support from the  European Research Council Advanced Grant DYNamo  ( ERC-2010-AdG-267374 ),  European Commission Project CRONOS  (grant number  280879-2 ,  CRONOS CP-7P7 ),  Spanish Grant  ( FIS2013-46159-C3-1-P ),  Grupos Consolidados UPV/EHU del Gobierno Vasco  ( IT578-13  and  IT395-10 ),  UPV/EHU  (grant  UFI11/45 ),  COST Actions   CM1204  (XLIC) and MP1306 (EUSpec). We also thank  PRACE  and  RES  for awarding access to MareNostrum III at  BSC-CNS, Barcelona , Spain (2013081486). We acknowledge RZG for the computing time in Hydra. JJS gratefully acknowledges the Comissionat per a  Universitats i Recerca del Departament dInnovació, Universitats i Empresa, de la Generalitat de Catalunya  for financial support, and the  Marie Curie Cofund Action  ( FP7)  of the  European Union for the Beatriu de Pins  ( 2010 BP-A2-00024 ) postdoctoral fellowship.
JAR acknowledges the fellowship of the  UPV/EHU. JJPS acknowledges financial support from the  National Institute Of General Medical Sciences of the National Institutes of Health  (Award Number  1R44GM108085-01A1 ). BFM acknowledges financial support from the  Portuguese Foundation for Science and Technology  ( CONT DOUT/11/UC/405/10150/18/2008 ), the  Donostia International Physics centre  and the  Centro de Fisica de Materiales, UPV/EHU , for financial support. BFM also thanks  the Laboratory for Advanced Computing of the University of Coimbra , Portugal the provision of computer resources, technical support and assistance.
All the data of the Met Office undergo a quality control before being publicly available; this control is performed according to the recommendations of the World Meteorological Organization  (WMO, 1981 (WMO, , 1982 (WMO, , 1989 (WMO, , 1993 (WMO, , 1996;; Zahumensky, 2004). We used the rainfall and temperature datasets of the meteorological stations of Rabat-Sale on the coastline of the Bouregreg basin, Kasba-Tadla from the inland, Safi on the coastline of the Tensift basin and Marrakech from the inland. From outside the basins, we used Tanger in the extreme north coastline of Morocco, Fes in the North-East of the Bouregreg basin, Agadir from the south coastline of Morocco, South of Marrakech, and Ouarzazate in the East of the Tensift basin on the Saharian side of the Atlas Mountains (Fig.
Back Close Full 3. A station dataset is considered as complete when no more than three consecutive seasons are missing. The common period to all the datasets is between 1983 and 2005, this work was performed on the overall periods of data availability and also on the common period of 23 years, the most significant results were obtained from the long periods. Here after we show the most significant results, those relative to the common period are not presented. For this work, the homogenization of the data used was not performed due to the poor horizontal resolution of data and the differences in the periods of availability; this implies an additional uncertainty to the results. Nonetheless, the problem was addressed by examining the metadata of available stations and considering the documented changes in the stations' location and environment, the instruments or also the observers.
Back Close Full ber. For this paper needs, the cold season is named winter, while the hot season is named summer. In order to rank the extreme events of rainfall and temperature we used, the 1st, 5th, 90th and 95th percentiles as thresholds, as they are widely employed and recommended by the STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes for European regions) (http://www. cru. uea. ac. uk/projects/stardex/) and the ETCCDI (Expert Team on Climate Change Detection and Indices) (http://www. wmo. int/pages/prog/wcp/ccl/opace/opace2/ETCCDI. php) projects. In addition, exceptional events were selected using the 99th percentile as threshold. This approach was applied to the winter and summer data separately and the following definitions have been used: -A heavy rainfall event is a day that recorded precipitations greater than or equal to the 90th percentile; -An intense rainfall event is a day that recorded precipitations greater than or equal to the 95th percentile; -An exceptional rainfall event is a day that recorded precipitations greater than or equal to the 99th percentile; -A one day hot (cold) event is a day that recorded a maximum (minimum) temperature greater (lower) than or equal to the 95th (5th) percentile; -A one day very hot (cold) event is a day that recorded a maximum (minimum) temperature greater (lower) or equal to 99th (1st) percentile; -A hot (cold) spell is a succession of 3 or more hot (cold) events; -A very hot (cold) spell is a succession of 3 or more very hot (cold) events.
, 2011). For all these regions, the rise in minimum temperature is large when compared to the detected trends in maximum temperature. Although evaluated with different definitions and indicators, most of the studies in the literature found that extreme temperatures tend to increase. Inverse trends of mean maximum temperatures at the stations of Marrakech, Agadir and Ouarzazate (in summer) and mean minimum temperatures at the stations of Rabat-sale, Tanger and Fes (in winter) may be explained by natural factors such as microclimates and local physical geographic and vegetations conditions or also by inhomogeneities in the analyzed datasets. According to  Khomsi et al. (2013 Khomsi et al. ( , 2014)) , the temperature regime has changed in all the studied stations  (Marrakech in 1982 , 1993 and 1999 , Agadir in 1986 and 1993 , Ouarzazate in 1976 and 1993 , Rabat-sale in 1979 and 1986 , Tanger in 1994 and Fes in 1993).
Contents lists available at ScienceDirect Genomics Data j o u r n a l h o m e p a g e : h t t p : / / w w w. j o u r n a l s. e l s e v i e r. c o m / g e n o m i c s -d a t a / Sample collection and RNA preparation Sample collection and RNA preparation were performed using plants 16 days after seed plating (16-day-old seedlings). For each sample set, about 30 to 40 plants were collected from three replicating Petri Dishes. For each plant genotype/strain, three independent sets were pooled. Thus, a total of 33 samples were analyzed in this work. Total RNA was isolated from plant samples using the Nucleospin RNA Plant kit (Macherey-Nagel, http://www. mn-net. com) followed by RNeasy mini kit (Qiagen, https://www. qiagen. com/) clean-up according to manufacturer's instructions. The quality of the RNA obtained from each sample was assessed based on the RNA profile generated by the Agilent Bioanalyzer 2100 (Agilent technologies, Santa Clara, CA).
Microarray data Microarray analyses were performed using Agilent's Whole Arabidopsis Gene Expression Microarray (G2519F, V4, 4 × 44K) via custom service of the Shanghai Huaguan Biochip Co. (http://www. bioequip. cn/). Total RNA was amplified and Cy3-labeled using Low Input Quick Amp Labeling Kit, one-color by following the manufacturer's instructions (Agilent technologies, http://www. genomics. agilent. com/). Labeled cRNA was purified using RNeasy mini kit (Qiagen), slide hybridization at 65 °C for 17 h and image scanning (Scan resolution = 5μm, PMT 100%, 10%, 16 bits) were performed by following standard Agilent's protocols. Data extraction was performed using Agilent Feature Extraction software. Feature Extraction was used for background subtraction and normalization between the set of arrays was done by Quantile algorithm, a method that gives the same distribution of probe intensities to each array in the set  [8].
Basic and focused analysis From previous studies we know that full-length transcripts of mutated genes are missing in the corresponding mutant strains used in this work. Therefore, it is predicted that our microarray data should confirm this information. Indeed, mutated genes are among the downregulated genes in the respective mutants (GSE55167;  [7] ), e. g. SDG26 is downregulated in sdg26, sdg26 sdg25, sdg26 atx1, sdg26 clf and sdg26 ldl1 ldl2 but not in the other mutants, SDG25 is downregulated in sdg25 and sdg26 sdg25 but not in the other mutants, etc. This confirmatory information on multiple mutated genes in various single, double and triple gene mutants in a same microarray analysis provides a good validation of our data. Our focused analysis on flowering time regulatory genes revealed that FLOWERING LOCUS C (FLC) is upregulated or downregulated (-)  to more than 2 folds in several of the mutant strains analyzed in microarray (GSE55167; Table  3 ).
The threshold cycle value (CT) was set so that the fluorescent signal was above the baseline noise but as low as possible in the exponential amplification phase. The relative expression level of FLC was calculated using the Lightcycler 480 software and normalized using ACT2 and GAPDH as internal reference genes. Each sample was analyzed in triplicate, and mean ± SD was shown as result (Table  3 ). Our qRT-PCR data show an overall agreement with microarray results obtained on FLC expression changes in different mutants.
Discussion We described here a unique dataset of microarray analyses on multiple different mutants deprived of one, two or three histonemethyltransferase(s)/histone-demethylase(s). This dataset has been recently used in a study focused on plant flowering time regulation  [7]. We anticipate that the dataset may also be useful for comparative study of other mutants as well as for investigation of roles of histone methylations in processes beyond plant flowering time control.
(d) Summary of the DE analysis of gametocytes compared with merozoites (G vs M) or sporozoites (G vs S) showing the percentage of genes upregulated (blue) or downregulated (red) in gametocytes, of all predicted E. tenella genes. (e) Venn diagram revealing the overlap of genes whose transcript levels were upregulated in gametocytes compared with either merozoites (left, G > M) or sporozoites (right, G > S). A total of 863 upregulated gametocyte transcripts genes were identified in this overlapping region. merozoite stages co-purified in gametocyte samples, an unavoidable bi-product of the asynchronicity of E. tenella infections at this later time point (144 h post-infection). Next, normalised read counts were generated for each of the three different biological stages using the DESeq algorithm  [19] , thereby allowing a comparison of gene transcript levels between different samples.
For the purposes of defining stage-specific expression, genes were defined as DE if the log2 fold-change calculated from normalised counts between two stages was equal to or greater than three (or a fold-change ≥ eight). The population of upregulated gametocyte transcripts identified using this threshold has been highlighted in the pairwise comparisons with merozoites and sporozoites (dotted red and green lines, respectively -Figure  1b, c ). The log2 fold-changes calculated for all genes in DESeq pairwise comparisons between (i) gametocytes and merozoites or (ii) gametocytes and sporozoites are provided (Additional file 3) along with an adjusted p-value representing false discovery rates. Excluding genes with DE false discovery rates of >0. 05, 1,669 gene transcripts (19. 0% of all predicted E.
5 kDa) (Figure  3b ). It is unclear whether these bands represent different conformations of the one EtOWP6 protein or represent different cross-reactive targets. Immunolocalisation studies of E. tenella-infected chicken intestine using this antibody revealed reactivity against wall-forming bodies type I of macrogametes, with GAM56 antibody used as a counterstain for wall-forming bodies type II (WFBII) (Figure  3c ). Surprisingly, EtOWP6 could not be detected in oocyst samples by either Western blot (Figure  3b ) or immunolocalisation on both broken and unbroken oocysts (data not shown), despite being detected in proteomic analyses of E. tenella oocyst walls  [29]. One explanation may be that cross-linking of the cysteine-rich protein during oocyst wall assembly drastically reduced the affinity of this particular antibody; although the reduction and alkylation performed prior to Western blot analyses should have been sufficient for breaking disulphide bonds.
AAT-1 (AMY-1-associated protein expressed in testes-1) protein (ETH_00005660) is predicted to have versatile functions in spermatogenesis, including the modulation of energy required for fertilisation  [45] , while enkurin (ETH_00003635) is expressed in mammalian sperm and is thought to be involved in signal transduction pathways of fertilisation during gamete fusion  [46]. Finally, two upregulated gametocyte transcripts, ETH_00017050 and ETH_00017055, are tandemly located in the E. tenella genome and code for proteins with homology to a family of transmembrane proteins, known as HAP2-GCS1 (HAPLESS2/Generative Cell Specific) whose expression is restricted to male gametes in a range of different organisms  [47]. Each of these genes aligns to different regions of an E. tenella 'GCS1' mRNA sequence (GenBank: AB723702.
1, direct submission, unpublished) implying a misprediction of both ETH_00017050 and ETH_00017055 exon models (data not shown). Mapping of gametocyte RNA Seq reads to the E. tenella genome supported that the two HAP2-like genes are actually part of one contiguous gene transcript (Figure  6a ); in fact, the canonical HAP2 domain is located in what is currently predicted as an intergenic region of the E. tenella genome, highlighting the current pitfalls in gene prediction models not informed by transcriptome data. Subsequent RT-PCR and sequencing of the ethap2 transcript confirmed this observation and revealed 100% of identity to the GenBank mRNA sequence, herein used as the EtHAP2 CDS. The expression of HAP2 in Plasmodium is restricted to microgametes and is required for gamete fusion and subsequent fertilisation  [48] [49] [50].