dataesr/scientific-paragraphs-categorization huggingface dataset:
) in male and female extraendoderm stem (XEN) cells (GHP7/7 and GHP7/9 cell lines). Expression data were extracted from the Gene Expression Omnibus database [GSE:15519]  [29]. n = 1,054 intergenic regions and n = 642 X-linked genes. *P < 0. 05 by Kolmogorov-Smirnov test. (B) Representative examples of H3K27me3 distribution along expressed genes enriched in H3K27me3 in female compared to male XEN cells ([K27-high]) and along expressed genes showing low levels of H3K27me3 in female and in male XEN cells ([K27-low]) (GHP7/7 and GHP7/9 cell lines). mm9 University of California Santa Clara (UCSC) Genome Browser screenshots are shown. IP, immunoprecipitated DNA; IN, input DNA. (C) Scatterplot of H3K27me3 percentages along the body of expressed X-linked genes in female (y-axis) relative to male (x-axis) XEN cells (GHP7/7 and GHP7/9 cell lines (see Additional file 4A for results in the GHP7/3 cell line and Additional file 2C for the complete data set).
ChIP-chip procedure and data analysis ChIP assays were performed as previously described  [54]  using an H3K27me3 antibody (07-449) and an H3K4me2 antibody (07-030; both from EMD Millipore, Billerica, MA, USA) and analysed as described previously  [18]  (see also Additional file 9 for the detailed protocol). ChIP-chip data have been deposited under Gene Expression Omnibus accession number [GSE:50587]. Raw data were analysed using the Tobias Straub protocol (http://www. epigenesys. eu/images/stories/protocols/ pdf/20111025114444_p43. pdf ) with the Bioconductor R interface. This protocol includes quality assessment, data normalization and transformation. Raw H3K27me3 data in male and female livers were taken from the Gene Expression Omnibus database.
RNA-FISH and Immuno-RNA-FISH RNA-FISH and immuno-RNA-FISH procedures were carried out as described at http://www. springerprotocols. com/Abstract/doi/10. 1007/978-1-59745-406-3_18?verPrint =print  [56]  (H3K27me3 antibody, 07-449; EMD Millipore). For details of our experimental procedures, see Additional file 9. For probe localisation, see Additional file 2D. Z-stacks were captured (step = 0. 2 μm) on a Zeiss Axioplan 2 microscope (Carl Zeiss Microscopy, Thornwood, NY, USA) equipped with a Hamamatsu ORCA ER chargecoupled device camera (Hamamatsu City, Japan) and controlled using Volocity Acquisition software (PerkinElmer, Waltham, MA, USA). Z-stacks deconvolution consisted in 50 iterations per each channel using Huygens Professional software (Scientific Volume Imaging, Hilversum, the Netherlands).
Underneath the scatterplots, the pie charts show the percentage of expressed genes of each H3K27me3 class in each cell type. The number of expressed genes in each cell type is indicated (n). Liver ChIP-chip data were extracted from Gene Expression Omnibus ID [GSE:20617] [31] and subjected to the same statistical analysis as the ChIP-chip data obtained for TS and XEN cells. Note that only 376 X-linked genes have been analysed in the liver  [31]  compared to 642 X-linked genes in TS and XEN cell lines. We found a significantly higher percentage of expressed X-linked genes showing low levels of H3K27me3 in extraembryonic stem cells (either XEN or TS cells) compared to liver cells (P < 0. 05 by Fisher's exact test). In contrast, we observed no significant difference between the two XEN cell lines or between either XEN cell line and TS cells (P < 0.
Acknowledgements We thank  Michel Cohen-Tannoudji ,  Jérôme Artus  and  Edith Heard  for critical reading of the manuscript and  Jérôme Artus  for advice on XEN cell culture and differentiation. This work was supported by a  Marie Curie ERG  grant to CM ( 224945 ), by recurrent funding from the  Institut Pasteur and the French National Centre for Scientific Research (CNRS)  and by grants from the  French National for Research (ANR) , the  Epigenome Network of Excellence, REVIVE Labex  and the  Louis D Foundation of the Institut de France  ( Louis D Prize  awarded to PA). JLD was supported by a postdoctoral fellowship from the  Association for Research against Cancer (ARC). SM was supported by a doctoral fellowship from the  French Ministry for Scientific Research , and by grants from the  ARC  and from the  REVIVE Labex.
All the above-mentioned formulations were evaluated by comparing them to field measurements. Two instruments which retrieve snow specific surface areas from infrared reflectance measurements at 1310 nm, DUFISSS  (Gallet et al. , 2009)  and ASSSAP (a light version of POSSSUM,  Arnaud et al. , 2011) , were used at Summit Camp (Greenland) in May and June 2011 and during the 2009/2010 and 2011/2012 winter seasons at Col de Porte (French Alps). During these field campaigns, SSA data were acquired with high vertical resolution (about 1 cm), allowing for testing of the accuracy of the different representations of dry metamorphism. 2 Metamorphism in SURFEX/ISBA-Crocus 2. 1 Model overview SURFEX (Surface Externalisée,  Masson et al. , 2013)  is the surface modelling platform developed by Météo-France.
Formulation T07 Taillandier et al. (  2007 ) performed several experiments during which the SSA was measured under isothermal and temperature gradient conditions. Based on this data set, they proposed a parameterisation of the rate of decay of SSA (formulation T07), whose implementation in Crocus is described in this section. The SSA decrease over time under isothermal (ET) and temperature gradient (TG) conditions can be written as SSA ET (t) = A ET (SSA 0 , T ) -B ET (SSA 0 , T ) • ln t + e C ET (SSA 0 ,T ) B ET (SSA 0 ,T ) (6a) SSA TG (t) = A TG (SSA 0 , T ) -B TG (SSA 0 , T ) • ln t + e C TG (SSA 0 ,T ) B TG (SSA 0 ,T ) (6b) www. the-cryosphere. net/8/417/2014/ The Cryosphere, 8, 417-437, 2014 Table  1. Metamorphism formulations implemented in Crocus. B92  (Brun et al. , 1992)  describes snow grains in terms of dendricity (δ), sphericity (s) and size (g s ).
For the period of our field campaign, ERA-Interim data were replaced by in situ measurements acquired on an hourly basis by the Summit Automatic Weather Station (AWS,  Steffen et al. , 1996). Air temperature and relative humidity were measured using a Type-E thermocouple (estimated accuracy of 0. 1 • C) and a Campbell Sci. CS-500 (accuracy of 10 %), respectively. Wind speed was recorded with a RM Young propeller-type vane (estimated accuracy of 0. 1 m s -1 ) and short-wave incoming radiation was measured using a Li Cor photodiode (nominal accuracy of 15 %). No measurement of precipitation rates and incoming long-wave radiation were performed by AWS. Figure  S1  shows a comparison between AWS measurements and ERA-Interim reanalysis for four different variables during the period April-July 2011.
For simulations at Col de Porte, we used in situ meteorological observations with a time step of 1 h, spanning the period from 1 August 1993 to 31 July 2012. A detailed description of the procedure followed to generate such an interrupted driving data set is presented in  Morin et al. (2012). Briefly, in situ observations were used in the period of the year concerned with snow on the ground (i. e. from mid-September to mid-June, approximately). A manual procedure for data inspection and correction was followed, including filling of episodic data gaps using redundant sensors. The summer period may be used for site maintenance and not all sensors operate continuously during this time. Hence, during such periods, to which the snowpack conditions in the following winter season are marginally sensitive, meteorological data were provided by the SAFRAN meteorological analysis  (Durand et al.
The snow height was monitored by the AWS, using a Campbell SR-50 with 1 mm precision. A more in-depth description of the snow data set acquired at Summit can be found in  Carmagnola et al. (2013). At Col de Porte, 14 and 16 vertical profiles of density and SSA were acquired during the winter of 2009/2010 and 2011/2012, respectively. Density was recorded for each snow layer with cylindrical steel cutters and SSA was measured in 2009/2010 using DUFISSS, whereas in 2011/2012 highresolution measurements of SSA were obtained using ASS-SAP (Alpine Snowpack Specific Surface Area Profiler). This instrument is the handy and lightweight version of POSS-SUM  (Arnaud et al. , 2011). Its working principle is similar to that of DUFISSS (retrieval of SSA from infrared reflectance measurements), the main difference being that it allows the continuous acquisition of SSA profiles down to about 90 cm, with a vertical resolution of 1 cm.
In addition to density and SSA measurements, manual weekly observations of snow height and SWE were carried out. The daily integrated surface albedo was computed from the ratio between incoming and reflected short-wave fluxes, measured using radiation sensors  (Morin et al. , 2012). Rather than computing an average of the hourly albedo estimates, which would be impacted by noise induced by low radiation conditions early and late in the day, the ratio of the sums of total reflected and incoming radiations, respectively, was taken for each day, featuring enough incoming radiation. This approach mitigates the impact of low radiation conditions and puts more weight on the time of the day when maximum radiation occurs. These data can be safely compared to albedo simulations at noon since diurnal variations of snow albedo, induced by variations of the solar zenith angle, are currently not represented in Crocus.
Acknowledgements. CNRM-GAME/CEN and LGGE are part of  Labex OSUG@2020  ( ANR10 LABX56 ). This work was funded by  INSU/LEFE  project  QUASPPER. The Summit field campaign was funded by grant no. 1088  from  French Polar Institute (IPEV)  to  F. Domine  and by grant no. 1023227  from  National Science Foundation (NSF)  to  M. Bergin. We thank  K. Steffen  and  N. Bayou  for providing the AWS data for Summit,  M. Flanner  for providing his algorithm describing the evolution of effective radius and  J. -M. Willemet  for help in programming. We also wish to thank  A. Royer ,  H. Loewe ,  E. Brun  and  M. Dumont  for useful discussions and  M. Lehning  and an anonymous referee for helpful and constructive reviews Edited by: E. Larour The publication of this article is financed by  CNRS-INSU.
g. cloud-radiation or land-atmosphere interactions). This analysis contributes towards a better understanding of WRF as a dynamical downscaling tool for RCM modeling studies and its optimization for this specific region. (Haylock et al. , 2008). The E-OBS dataset is based on the ECA&D (European Climate Assessment and Data) station dataset and other stations from different archives. Short-and longwave downwelling radiation fluxes at the surface and cloud fraction were evaluated with the International Satellite Cloud Climatology Project (ISCCP) Flux Dataset. The ISCCP radiation fluxes comprise a satellite derived product including shortwave (0. 2-5 µm) and longwave (5. 0-200 µm) radiation at the Earth's surface. Radiation is a satellite derived product including shortwave (0. 2-5 µm) and longwave (5.
0-200 µm) downwelling and upwelling radiation at the Earth's surface. The radiation estimates come from the synergistic use of ISCCP cloud dataset, satellite data (TOMS, TOVS and SAGE-II), models (NCEP reanalysis, GISS climate model) and climatologies of various tropospheric and stratospheric parameters  (aerosols, water vapour, etc). The dataset spans from July 1983 to December 2009 having a temporal resolution of 3 h and a spatial resolution 280 km × 280 km (∼ 2. 5 • × 2. 5 atmosphere and cloud physical properties as input, the radiation and cloud datasets are considered fully compatible. For the current analysis, seasonal averages of the IS-CCP variables were calculated for the time period 1990-2008 and were compared to the WRF surface downward short-and longwave radiation, after bilinear interpolation to the 2.
Back Close Full an equal area grid with a resolution of 280 km × 280 km, being available 8 times per day. The ISCCP cloud product is in good agreement to the MODIS cloud mask product  (Pincus et al. , 2012 ). An additional, higher resolution, satellite dataset was also used for model validation, in order to confirm the robustness of the validation findings with ISCCP. Shortwave downward radiation at the surface was additionally obtained from Satellite Application Facilities for Climate Monitoring (CMSAF), which is part of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The spatial resolution of the data is 0. 03   (Posselt et al. , 2012). In this study, seasonal mean solar surface radiation data from CMSAF were re-gridded to the EOBS 0. 44 domain in order to be compared with the WRF simulations for the time period 1990-2005.
Since this dataset does not exactly overlap with the hindcast timeslice  (1990) (1991) (1992) (1993) (1994) (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) , we used the higher resolution dataset only as auxiliary material to support the major findings of the model comparison with the coarser ISCCP satellite retrievals.
Models In this work we present EURO-CORDEX hindcast climate simulations performed with the WRF/ARW (version 3. 3. 1) model. The simulations cover the EURO-CORDEX domain with a resolution of 0. 44 •. Some options are common to all the simulations. The Noah Land Surface Model (NOAH) was the commonly selected land surface model  (Chen et al. , 1996) , the Yonsei University scheme (YSU) was the chosen Planetary Boundary Layer (PBL) scheme  (Hong et al. , 2006)  and MM5 similarity the surface layer option. All simulations were forced by the ERA-interim reanalysis dataset  (Dee et al. , 2011)  at 6 hourly intervals with a spatial resolution of 0. 75. The way the forcing fields were pre-processed and implemented in the simulations (relaxation zone, method etc), Figures.
Back Close Full the setting of vertical layering, land use databases, or sea surface temperatures were decided by each group separately. In the current ensemble, five different WRF configurations are applied (Table  1 ). Three different convection schemes were used, namely the Kain-Fritsch (KF,  Kain, 2004) , the  Grell-Devenyi (GD, Grell and Devenyi, 2002)  and the Betts-Miller-Janjic ensemble (BMJ,  Janjic, 2000). The radiation physics options tested were: the newer version of the Rapid Radiative Transfer Model (RRTMG,  Iacono et al. , 2008)  and the CAM scheme  (Collins et al. , 2004). The selected microphysics options were the WRF Single-Moment 3 and 5-class schemes (WSM3/WSM5,  Hong et al. , 2004)  and the WRF Single-Moment 6-class schemes 6 (WSM6,  Hong and Lim, 2006). WRF_ A configuration is simulated twice with different SSTs (WRF_A and WRF_A_SST).
In WRF_A_SST, the SST field was interpolated as provided in the standard 3. 3. 1 release (METGRID. TBL). This option results in a coarse resolution of the SSTs resulting in a strong temperature perturbation across the European coastline. In other configurations, either a finer interpolation method is used or the SST fields are replaced by skin temperature. Five meteorological variables are evaluated, namely surface temperature, precipitation, total cloud cover, the short-and longwave downward radiation at the surface. Temperature and precipitation fields were interpolated to the 0. 44 E-OBS grid and an elevation correction (standard lapse rate of 6 • C km -1 ) was applied to the simulated temperature to account for the difference between EOBS9 and model orography. Radiation and cloud data were bilinearly interpolated to a common ISCCP 2.
Radiation The primary driver of latitudinal and seasonal variations in temperature is the seasonally varying pattern of incident sunlight, and a fundamental driver of the circulation of the atmosphere are the local-to-planetary scale imbalances between the shortwave (SW) and longwave (LW) radiation. The impact of the distribution of insolation on temperature can be strongly modified by the distribution of clouds and surface characteristics. In the current section we evaluate two radiation components of the WRF model simulations, namely the surface downwelling SW and LW, which are compared to available ISCCP satellite measurements. The comparison was also performed with the CMSAF satellite dataset, available in a higher spatial resolution, but only between 1997-2003. in some configurations (WRF-A/WRF-C with KF or WRF-D with BMJ convection) the SW radiation gradient is less steep towards the north compared to the satellite data, leading to a general positive SW bias over Europe except Scandinavia with a maximum over central Europe, within the range of 40-60 % (Fig.
Back Close Full biases (60-70 %) over this area correspond to small absolute changes, which lie within the uncertainty of the satellite data  (Zhang et al. , 2004). The wintertime positive bias of cloud cover over north Europe is accompanied by negative bias in the LW downward radiation at the surface, in all model configurations. There is not a straightforward explanation for this feature, since increased cloudiness should be associated with increased LW radiation. Both model and observational datasets are internally consistent (the cloud and radiation components), since the IS-CCP radiation data are derived by the cloud data (see Sect. 2. 1), while WRF has its own internally consistent physics. The results are robust, since they are reproduced by  Garcia-Diez et al. (2014b)  in their 5 year simulations of the same ensemble, validated with a different satellite dataset.
, 2014). Our current findings are in the same line, with the KF convective scheme being related to the highest bias over the Mediterranean in summer. All ensemble members better capture winter than summer precipitation, the latter being locally rather than large-scale controlled. There is no specific configuration that totally alleviates the wet bias of WRF both here and according to literature. This issue points, among other things, towards Figures weaknesses of convective schemes. The precipitation spread of the EURO-CORDEX WRF-ensemble analyzed by Garcia-Diez (2014a), could only be partially attributed to the selected physical parameterizations. Different model domain configurations and datasets seemingly contribute to the precipitation spread. Our study identifies the implementation of SSTs as one important contributing factor.
in a North-Atlantic SST sensitivity experiment of the fall and winter 2006/2007 with a climatic (colder) SST dataset. A similar response in land surface temperature above Europe was showcased, in which anomalous SSTs affected land temperature through the upper-air advection of heat and water vapor, interacting with radiative fluxes over the continent. This mechanism was also found to be more pronounced in autumn and winter, when SSTs anomalies and upper air advection is more efficient. Figures Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |.
Acknowledgements. We acknowledge the E-OBS dataset from the  EU - FP6  project  ENSEM-BLES  (http://ensembles-eu. metoffice. com) and the data providers in the  ECA&D  project (http: //www. ecad. eu). Aristotle University of Thessaloniki simulations have been produced using the EGI and Hel-lasGrid infrastructures and supported by the  Scientific Computing Center at the Aristotle University of Thessaloniki. Katragkou E. acknowledges financial support from the  AUTH-Special Account for Research Funds. The contribution from  Centre de Recherche Public  - Gabriel Lippmann  was funded by the  Luxemburg National Research Fund  through the Grant  FNR C09/SR/16  (CLIMPACT). Alexandri G. and Zanis P. acknowledge financial support from the  QUADIEEMS  project which is co-financed by the  European Social Fund (ESF)  and national resources under the operational.
Molecular dynamics (MD) simulations The starting models of pVHL were constructed from the crystal structure solved by Min and co-workers (2002) (PDB ID code 1lm8)  (21). Mutant models were generated from the wild-type model by in silico substitutions of the arginine (R) in positions 161 and 200, with a glutamine (Q) and a tryptophan (W) respectively. All the details are given in Supplementary Data.
Transcriptomic study RNA was extracted using Trizol reagent (Sigma) and purified on Qiagen columns. 500 ng of total RNA from each RNA sample was amplified and labelled with two fluorescent dyes (Cy5 and Cy3). Labelled cRNA were hybridized to the Agilent Human Whole Genome Oligo Microarray format 4x44K (Agilent Technologies), prior to washing and scanning. All hybridizations were performed in duplicate with dye swap to eliminate possible dye bias. Data were extracted from scanned images using Feature Extraction software (Agilent) with default settings. Data from all hybridizations were analysed with Rosetta Resolver software. The microarray data related to this paper have been submitted to the Array Express data repository at the European Bioinformatics Institute (http://www. ebi. ac. uk/arrayexpress/) under the accession number E-MTAB-1269.
HIF-2 α target gene identification Chromatin Immunoprecipitations (ChIPs) were performed on 786. O cells as previously described (  23 ) using rabbit polyclonal anti-sera to HIF-2α (PM9). Preimmune serum or IgG were used as negative controls. High-throughput sequencing was performed on libraries prepared from immunoprecipitated chromatin using the Illumina ChIP-Seq kit; 36-bp single end sequence analysis was performed on the Illumina GAII platform. The microarray analysis of 786. O cells in the presence of either control or HIF-2α siRNA was performed as previously described  (24). Correlation of ChIP-seq data with microarray analysis of gene expression was performed using GSEA software Version 2 (www. broadinstitute. org/gsea/).
Expression profiles of the 30 identified genes in clear cell renal cell carcinoma The GSM14994 dataset  (25) , was used to analyse the expression of the 30 genes identified as direct target of the pVHL/HIF-2α pathway. The Affymetrix HT Human Genome U133A Arrays [[HT_HG-U133A] was normalized with the justRMA procedure in BrB Array Tools v. 4. 4. 0. The signature corresponding to the comparaison of 52 clear cell renal cell carcinoma (VHL mutated) versus 11 normal kidney tissues was performed with the Class Comparison procedure on a restrictive list of 26 genes (probes for KCNIP3, TMEM141, ARRDC3, ERRFI1 were absent of the dataset (  25 )). All the details are given in Supplementary Data.
The target genes of the pVHL/HIF-2α pathway are deregulated in renal cell carcinoma In order to validate our identified genes on naturally occurring tumors, our set of 30 candidate genes was analyzed via the webtool SEEK (Search-Based Exploration of Expression Compendium, http://seek. princeton. edu/) that prioritizes public human mRNA microarray datasets from many tumor types according to the genes of interest. When we analyzed our 30 genes with SEEK, they turned out to be significantly deregulated in microarrays from many series of renal cell carcinoma (data not shown). We selected one dataset of ccRCC with detailed VHL status (GSM14994 dataset  (25) ). The expression profiles of our 30 candidate genes were studied in VHL mutated ccRCC compared to normal kidney tissues. Among 26 genes with validated probes, 17 were differentially expressed with a threshold of 0.