dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to detect a signature of selection in the sex region, Tajima's D  [43]  and Fu and Li's D*  [44]  statistics were calculated with the DnaSP v5 software  [45]  separately for the male, female and hermaphrodite haplogroups. To confirm traces of selection detected on the male haplogroups with the Tajima's D and the Fu and Li's D* tests, the E statistics and the DH test  [46]  were computed using the male haplotype of V. balanseana as an outgroup (Table  2 ). Finally, we evaluated the intraspecific genetic differentiation between male, female and hermaphrodite haplogroups, and the interspecific differentiation between V. v sylvestris and Vitis species haplotypes, using the Fst statistics  [47, 48]  with DnaSP v5 software as well. The Vitis species used for this statistics were V. balanseana, V.
Results Sequence polymorphisms linked to the sex trait Eleven amplicons representing 9. 523 bp in total and designed to partly amplify gene sequences were chosen to cover the sex locus and its boundaries  [18, 20]. Sequencing these 11 amplicons on a sample of 65 genetically and geographically diverse wild genotypes (31 males and 34 females, Additional file 1, [GenBank: KJ575622-KJ57662]), allowed the identification of 146 polymorphic sites (Additional file 3): 137 SNPs and 9 indels. Thirty-six SNPs were located in introns and twenty in exons, among which ten were non-synonymous. The allele frequencies of 51 and 64 polymorphisms in female and male genotypes respectively were found significantly deviating from the Hardy-Weinberg proportions (Figure  2b ). These significant polymorphisms were mainly found in VSVV006, VSVV007, VSVV009 and VSVV010 (87,04% of the significant polymorphisms in females and 90.
Linkage disequilibrium in the sex region The intra-and inter-amplicon linkage disequilibrium (LD) was estimated on a sub-sample of 18 male and 18 female wild grapevines (Additional file 1), by calculating the pairwise square correlation coefficient r 2 VS  [33] , correcting for the structure and kinship of the sample. Only sequence polymorphisms with less than 20% missing data and with a 0. 2 minor allele frequency were analysed. At these thresholds, no polymorphisms were retained in the VSVV001 fragment. The highest values of LD were found within and between the four sex-linked fragments (Figure  3 ). The mean LD for all pairwise comparisons for the four sex-linked fragment was r 2 VS = 0. 72 for a total physical length of 109. 76 kb. The maximum mean intra-amplicon LD was r 2 VS = 0. 84 over 374 bp for VSVV010 and the minimum was r 2 VS = 0.
The H haplogroups showed an intermediate diversity pattern between the M and F haplogroups, but closer to the M haplogroups (Table  2 ). For VSVV010, the H haplogroup presented diversity patterns quite equivalent to that of M haplogroups, except for a lower haplotype diversity. To illustrate these findings, the haplotypes identified for each sex-linked amplicon are presented in Figure  4  (for genotype and geographic details see Additional file 7). This dataset shows that the three grapevine flower sexes, male, female and hermaphrodite, could be correctly predicted in 97% of the genotypes of our geographically representative V. vinifera sample, using a few SNPs, i. e. n. 4 to 7 of VSVV007 and n. 8 of VSVV010 (identified by black circles respectively termed 1 and 2 in Figure  4a ). Male haplogroups revealed significantly negative Tajima's D, and Fu & Li's D* values for VSVV006 and VSVV009 (Table  2 ).
Acknowledgements The authors thank the staff of the  INRA Vassal grapevine collection , as well as  Catherine Roux ,  Catherine Bréton ,  Amandine Launay  for their laboratory work, and  Jean-Pierre Peros  and  Sandrine Maurice  for their useful suggestions on an earlier version of the manuscript. This work has been supported by the  CNRS   ATIP  project " ARCHEO-VITIS" , the  ANR program  " FRUCTIMEDHIS " and by the PhD fellowships from the  CNRS/Languedoc-Roussillon region (France)  to  S. Picq.
None of the examined contigs/singletons showed a significant interaction between time and treatment, indicating little difference in the transcriptomic response to 4 h and 8 h of Cu treatment. Only 11% of the contigs/singletons induced in response to Cu stress were automatically classified by the GOLEM and KOBAS annotation tools (data not shown); therefore manual classification was done for genes presenting a fold-change ratio > 2 compared to the control conditions. This dataset represents 560 genes (627 contigs/singletons), which were assigned to 13 categories (Figure  2 , Additional file 1). Cu stress transcriptomic data were further compared to previous results obtained with the same array and protocol for short-term (6 h) hyposaline (56 mM NaCl final concentration), hypersaline (1,470 mM NaCl final concentration) and oxidative (1 mM H 2 O 2 final concentration) stress  [25]  [ArrayExpress:E-TABM-578].
To reduce the number of false negatives no FDR correction was applied for this meta-analysis, and all transcripts previously found to be significantly regulated (p < 0. 05, fold-change compared to control > 2) after either 6 h  [25]  or 4 or 8 h (this study) were taken into account. Seventy-five contigs/ singletons were up-regulated in all considered stress conditions (Additional file 2A). Seventy-six percent of them (i. e. 57) code for proteins with unknown functions, and 48% (i. e. 36) are orphans (Additional file 3), that is as of March 2013, they had no match outside E. siliculosus in the NCBI nr database at an e-value cutoff of 1e-5. Regarding down-regulated transcripts, we identified 64 contigs/singletons (Additional file 2B) of which 55% (i. e. 35) correspond to unknown proteins and 27% (i.
In relation to downstream lipid metabolism and signaling cascades, a gene encoding a cytochrome P450 enzyme (Esi0060_0078) was among the most highly upregulated genes during copper treatment (41-fold after 4 h, 8-fold after 8 h) and also responded to oxidative stress (Additional file 3). The corresponding protein displays approximately 30% identity and 45% similarity with the cytochrome P450 domain of plant allene oxide synthases (AOSs) of the CYP74 family involved in the jasmonate biosynthetic pathway. A multiple alignment of this protein with members of the CYP74 family highlights the existence of several motifs common to AOSs, such as the IHCD motif and the conserved F and S catalytic amino acid residues (Additional file 5A). Finally, protein structure homology modelling using the Phyre2 software predicts high structural similarity between Esi0060_0078 and the AOS of Parthenium argentatum (Additional file 5, panel B; PDB: 3dan; 100% confidence, 91% coverage).
Conclusions This study provides an overview of copper stress acclimation in E. siliculosus, and highlights a number of processes that seem to be conserved with metazoans or land plants. Of interest for future brown algal research is the potential cross-talk between ROS, MI, and oxylipin signaling. Considering that two thirds of the regulated genes identified through this work encode proteins of unknown function, many additional components of the stress response remain to be discovered. The number of available medium to high throughput datasets related to stress response in brown algae is still limited  [56] , and the analysis of such results paves the way to decipher some of the molecular mechanisms leading to acclimation of these organisms to their frequently changing environment. They will be complemented by follow-up studies benefiting from the development of new techniques and protocols for brown algae, such as reverse genetics (transformation, RNAi, and tilling) or the assessment of nucleic acid-protein and protein-protein interactions.
7, A 260/230 ≥ 1. 5, median size ≥ 400 bp). Samples were Cy3-labeled and hybridized to the E. siliculosus EST-based Roche NimbleGen 4-plex expression array [ArrayExpress:A-MEXP-1445], described in  [25]. It is based on a set of 90,637 expressed sequence tags, corresponding to 8,165 contigs and 8,874 singletons, although in some cases, several contigs/singletons belonging to the same genomic locus had not been assembled. In total, the 17,039 contigs/singletons cover about 10,600 of the 16,256 predicted unique genes in the E. siliculosus genome  [59]. Each of the contigs/singletons is represented by four unique 60-mer probes on the array.
Statistical analysis of microarray experiments Normalization and probe averaging of raw microarray data were carried out by Roche Nimblegen using quantile normalization  [60] , and the robust multichip average algorithm  [61]. Normalized microarray signals were then log2-transformed and analysed in a two-way ANOVA with time (4 h, 8 h) and stress (0 or 250 μg L -1 Cu) as factors using TIGR MeV 4. 4  [62]. In this analysis, the false discovery rate (FDR) was limited to 5% according to Benjamini and Hochberg  [63]. In parallel, a metaanalysis was carried out to compare our data to a previous dataset available for other stressors  [25]. Transcripts previously found to be significantly regulated (p < 0. 05, fold-change compared to control > 2) after either 6 h  [25]  or 4 h or 8 h (this study) were taken into account, but to reduce the impact of false negatives on this analysis no FDR correction was applied here.
Metabolite profiling and data analysis After harvesting, samples were freeze-dried and ground in a mortar. For each sample, 250 ng of 12-OH-lauric acid was added as an internal standard. Extraction was carried out from 300 mg (fresh weight) of algal material during 1 h at 4°C with 1 ml MeOH:H 2 O (8:2) Samples were then centrifuged at 1,500 g for 15 min at 4°C. Aliquots of the supernatants were then used for metabolomic analysis by ultra-high pressure liquid chromatography coupled to mass spectrometry analysis (UPLC-MS), and for gas chromatography coupled to mass spectrometry (GC-MS) profiling. UPLC was performed using an RSLC Ultimate 3000 from Dionex equipped with a quaternary pump and autosampler. Separations were achieved using an Acclaim RSLC 120 C18 1. 9 μm (2. 1 × 100 mm) column (Dionex; Thermo Fisher Scientific, Courtaboeuf, France) maintained at 20°C using 5 μL injection volume and a flow-rate of 250 μL min -1.
1 software was used for instrument control and data acquisition. Raw files were converted to the mzXML format using MassMatrix File Conversion Tools (Version 3. 9, April 2011). Data were processed by XCMS  [74]  running under R or on the online version, using the parameters listed in Additional file 11, and further annotated by CAMERA  [75]. This approach allowed detecting 392 monoisotopic peaks, among which 31 free fatty acids and oxylipins were further identified by comparison with standards and mass spectral databases Metlin, HMDB and MassBank. GC-MS was used for profiling of amino acids. To this end, 100 μL aliquots of the MeOH:H 2 O (8:2) fraction were evaporated under a stream of nitrogen and resuspended in 60 μL of 20 g L -1 methoxyamine-hydrochloride (Sigma-Aldrich, Saint-Quentin Fallavier, France) in pyridine before incubation at 60°C for 1 h.
After addition of 50 μL of N,O-bis(trimethylsisyl)trifluoroacetamide, samples were incubated 1 h at 40°C and then at room temperature overnight before injection. Derivatized metabolites were analyzed by GC-MS using an Agilent GC 6890+ coupled to a 5975 MS Detector (Agilent, Les Ulis, France) and equipped with a DB-5MS column (30 m × 0. 25 mm I. D. × 0. 25 μm film thickness; J&W Scientific, Agilent) in the EI mode at 70 eV. The temperature gradient used was 60°C for 5 min, 60-120°C at 30°C min -1 , 120-290°C at 4°C min -1 , and 290°C for 10 min. Sixteen amino acids were identified by comparison with standards. By combining the data obtained in both positive and negative ion mode by UPLC-MS and by GC-MS, 47 metabolites corresponding to fatty acids, oxylipins, and amino acids could be reliably identified.
Acknowledgments We are especially grateful to  Laurence Dartevelle  for valuable help with Ectocarpus siliculosus cultivation. This work has been partially funded by  Marine Genomics Europe NoE  7 (EU contract n°GOCE-CT-2004-505403), and the  French Embassy  and the  CONICYT of Chile  through PhD fellowship to A. R. This work was also supported by the  Laboratoire International Associé 'Dispersal and Adaptation of Marine Species' (LIA DIAMS) PUC, Chile , and  CNRS-UPMC, France. S. G. benefited from the support of the  French Government via the National Research Agency  through the  investment expenditure program IDEALG  ( ANR-10-BTBR-04 ). Additional support came from  FONDAP   1501-0001 (Program 7 ) to J. A. C. and A. R.
© 2014 Piccolo et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4. 0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons. org/publicdomain/zero/1. 0/) applies to the data made available in this article, unless otherwise stated.
DATA The two multiwavelength survey fields analysed in this paper contain a wealth of observations from X-ray to radio wavelengths. In the following section we describe the specific datasets utilised here for the selection of z > 6. 5 galaxies, most importantly the near-infrared data from the Ul-traVISTA DR2 and UDS DR10. The coverage maps of the different wavelength data are shown in Figs. 1  and 2 , and a summary of the available broad-and narrow-band filters utilised to image each field can be found in Table  1. The final area of overlapping multiwavelength imaging over the two fields, excluding large stellar diffraction haloes that were masked, comprised 1. 65 deg 2 , with 0. 62 deg 2 from the Ultra-VISTA 'ultra-deep' survey, 0. 29 deg 2 from the UltraVISTA 'deep' component and 0. 74 deg 2 in the UDS field.
Auxiliary optical and mid-infrared imaging The auxiliary data used in this paper is described in full by  Bowler et al. (2012) , but here we briefly describe the key datasets that are shown in Fig. 1. The UltraVISTA survey lies within the multiwavelength imaging taken as part of the COSMOS survey  (Scoville et al. 2007b ), which covers a total of 2 deg 2 on the sky. Specifically we use optical imaging from the CFHTLS T0006 data release, which defines the maximal area of our search centred on RA 10 h 00 m 28 s. 00, Dec. +2 • 12 30 , with additional deep z -band data from Subaru Suprime-Cam. Mid-infrared imaging over the COSMOS field by Spitzer /IRAC exists from two programmes; the Spitzer Extended Deep Survey (SEDS;  Ashby et al. 2013)  and the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH, PI: Capak).
Imaging in the Y -band is key for the robust selection of z 7 galaxies in the UltraVISTA and UDS datasets, as the filter straddles the position of the spectral 2 http://surveys. roe. ac. uk/wsa/ Data from Subaru Suprime-Cam are shown as the green and blue outlines, where the blue outline defines a z -band mosaic of four pointings as in Fig. 1. The green cross-shaped outline shows the B, V, R, i and z -imaging from the original Subaru programme  (Furusawa et al. 2008) , where the mosaic is formed from five separate pointings. Finally, the footprint of Spitzer data from SpUDS is shown as the black diamond. The total area of overlapping Subaru optical and UKIRT near-infrared imaging is 0. 8 deg 2. break and hence can separate genuine high-redshift galaxies from dwarf stars and low-redshift galaxy contaminants that can have identical, red, z -J colours.
Data processing and consistency All images were mapped onto the astrometric solution and pixel grid of the binned UKIRT J-band imaging, with a pixel scale of 0. 2684 arcsec/pixel. Consistency within < 0. 05 mag was found between the zeropoints, with the exception being the VISTA VIDEO Y -band image which we found to be ∼ 0. 1 mag brighter than predicted from the sample of objects with flat z -J colours. We also observed an identical offset when comparing magnitudes with the Very Large Telescope/HAWK-I Y -band imaging in the field  (Fontana et al. in preparation). Hence we shifted the zeropoint of the VIDEO imaging to produce fainter magnitudes by 0. 1 mag, with the expectation that future reduction of the data will largely correct this offset with improved calibration, as was the case with the UltraVISTA Y -band data.
Image depths The careful determination of imaging depths across all bands is crucial to obtain accurate errors for use in the SED fitting analysis, and also in making appropriate preliminary magnitude cuts in the selection process. However, defining global limiting depths for data over degree-scale fields in the optical and near-infrared becomes problematic, as the combined pointings may have different integration times and seeing. Therefore, we obtained local depths over each image from the clipped median absolute deviation of the 200 closest apertures to each point. Apertures were placed randomly on the blank regions of the images that had been background subtracted using SExtractor, where blank regions were 3 http://www. cfa. harvard. edu/SEDS/data. html defined using the segmentation map of each image.
Determination of the enclosed flux We expect the high-redshift galaxies detected here to be close to unresolved in the available ground-based imaging, which typically has seeing of 0. 8 arcsec (see Section 6). However, the variations in seeing throughout the multiwavelength data, along with potential variations across each individual mosaic, result in a different fraction of the enclosed flux in a given fixed circular aperture, which must be corrected for to ensure accurate colours and magnitudes. To extract a point spread function (PSF) for each image, we selected stars using the BzK-diagram (uzK-diagram for the UltraVISTA dataset) as defined in  Daddi et al. (2004). For each star we extracted a postage-stamp from a backgroundsubtracted image, before centring using the centroid coordinates from SExtractor.
6 µm and 4. 5 µm values were calculated in a 2. 8-arcsec diameter aperture. We present the depths of the near-infrared data from UltraVISTA separately for the 'ultra-deep' and 'deep' parts of the survey. Note that the depths for the 'deep' part shown here are ∼ 0. 4 mags deeper than the results from the original data release presented in  Bowler et al. (2012)  and  McCracken et al. (2012). This is a result of improvements in the photometric calibration of the VISTA data, the smaller apertures used (1. 8-arcsec diameter as opposed to 2-arcsec results presented previously) and an improved global depth derived from the local depths. been background subtracted using a large filter size by SExtractor. The majority of our high-redshift candidates presented in the next section are isolated and hence the large aperture photometry is sufficiently accurate.
UltraVISTA DR2 selection The initial catalogue for the UltraVISTA dataset consisted of 278916 objects within the 0. 7 deg 2 'ultra-deep' part of UltraVISTA imaging that overlaps with the multiwavelength auxiliary data shown in Fig. 1. We then required that an object be detected at greater than 5σ significance in either the Y or J-bands, where the 5σ limit here was taken as the median local depth from the deepest of the three strips (Y = 25. 8, J = 25. 4 mag, 5σ, 1. 8-arcsec diameter circular aperture). Using our local depth estimates to compensate for the large diffraction halos around stars in the CFHT/Mega-Cam imaging, we then required the candidate to be undetected in the u * gri-bands at the 2σ-level. These optical non-detection requirements will inevitably result in a minority of real z 7 candidates being rejected at this stage (e.
UKIDSS/UDS selection The raw catalogue from the UDS dataset consisted of 248191 objects over the full area of J, H and K-band imaging shown in Fig. 2. We then applied the initial criteria that the candidates must be brighter than the 5σ-level in the J-band and undetected at 2σ-significance in the i-band, leaving 24797 sources. The available Y -band imaging in the UDS field is of insufficient depth to be competitive with the UltraVISTA Y -band imaging for the selection of galaxies, however it is essential to remove potential 'cross-talk' artefacts that occur only within the UKIRT imaging and hence can closely mimic a z-dropout LBG at z 7. Cross-talk appears at constant pixel separation from all objects in the UKIRT/WFCAM imaging, which is 128 pixels on the native 0. 4-arcsec/pixel scale (51.
Visual inspection In the final step before photometric redshift fitting, the candidates were visually inspected in the z , Y and J-images to remove obvious artefacts such as diffraction spikes, remaining cross-talk in the case of the UDS, and sources within the bright haloes around stars in the VISTA imaging. The i-band images were also inspected, and objects with any detection here (that may have escaped the 2σ-level cut applied above) were removed as indicative of galaxies at z < 6. 5. The final samples containing the remaining high-redshift candidates for SED fitting consisted of 400 galaxies in the UltraV-ISTA data and 36 in the UDS field (where the lower number of objects remaining in the UDS is due to the additional Yband detection requirement). All near-infrared photometry was corrected to a constant enclosed flux level of 84% (the enclosed flux in a 1.
2012). Using the redshift-χ 2 distributions from our photometric redshift fitting procedure, we required an acceptable fit above z = 6 (determined by χ 2 < 10 and 11. 3 for the UDS and UltraVISTA respectively, which corresponds to 2σ significance given the degrees of freedom in the fitting). In an effort to remove low-redshift contaminants from the sample we also excluded all objects that had a low-redshift solution (z < 4. 5) within ∆χ 2 = 4 of the high-redshift (z > 6) solution. In the final stage of selection we performed careful visual checks of a stack of the optical bands blueward of the z -band to ensure there was no residual optical flux that would imply a lower redshift solution. These further steps resulted in samples of 53 and 18 remaining candidates in the UltraVISTA and UDS datasets respectively.
2 for further discussion), although in practice the IRAC imaging is sufficiently shallow compared to the nearinfrared data that the unusual IRAC colours indicative of nebular emission, affect the χ 2 values derived from stellar only SED models very little (see Fig. A1 ). The results of careful consideration of the SED fits, along with final visual identification and removal of subtle near-infrared artefacts, Table  2. The photometry for the sources in our final UltraVISTA and UDS samples is presented in the upper and lower sections of the table respectively. The magnitudes presented here were based on 1. 8-arcsec diameter circular apertures except for the Spitzer /IRAC channels where 2. 8-arcsec diameter circular apertures were used. The photometry has been corrected to the 84% enclosed flux level using the appropriate point-source correction.
Where the flux is below 2σ significance, as defined by the local depth derived for each object, we replaced the magnitude with the limiting 2σ magnitude. The errors displayed were derived from the median absolute deviation of the fluxes from the closest 200 blank sky apertures. The presence of a dagger symbol in the right-hand column indicates that the [3. 6µm] and [4. 5µm] photometry is confused, and the number corresponds to the  Bowler et al. (2012)  galaxies with the order consistent with table 2 in  Bowler et al. (2012). The 'Himiko' galaxy from  Ouchi et al. (2013) -0. 3 25. 3 +0. 2 -0. 1 25. 3 +0. 3 -0. 2 25. 3 +0. 3 -0. 2 24. 9 +0. 5 -0. 3 24. 8 +0. 6 -0. 4 † resulted in the sample of 34 galaxies presented in the next section. The strength of our selection methodology is demonstrated by the confirmation, using the deeper near-infrared imaging analysed in this work, of 9 of the 10 candidates we originally selected from the first data release of the UltraV-ISTA dataset in  Bowler et al.