dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  Dr David Baulcombe  ( Cambridge University, UK ),  Dr Tsuyoshi Nakagawa  ( Shimane University, Japan ),  Dr Hiroshi Kouchi  ( International Christian University, Japan ),  Dr Hirobumi Yamamoto  ( Toyo University, Japan ), and  Dr Nathalie Giglioli-Guivarc 'h ( Universit e Franc ßois-Rabelais de Tours, France ) for providing the pBIN61-P19 plasmid, the pHKN29 plasmid, the pGWB vectors, DMAPP, and GGPP, respectively. Liquid chromatography-ion trap-time-of-flight/mass spectrometry (LC-IT-TOF/MS) analyses for preliminary biochemical analysis of FcPT1 were performed in collaboration with the  Development and Assessment of Sustainable Humanosphere (DASH)  system of the  Research Institute for Sustainable Humanosphere (RISH) ,  Kyoto University (Japan). This work was financially supported by  JSPS Overseas Research Fellowships  (to RM), by  Grants-in-Aid for Scientific Research  (no.
Spectral analysis of the host star The spectral analysis of the host star was performed to derive its fundamental parameters and the chemical composition of the photosphere. We used the HARPS spectra corrected from systemic velocity and planetary reflex-motion. We removed the spectra with a S/N lower than ten in order 47 (550 nm) and the ones contaminated by the Moon (S/N above 1. 0 in fibre B). We then co-added the spectra in a single 1D spectrum. Then, the spectral analysis was performed using two sets of tools. Firstly, we proceeded as described in  Deleuil et al. (2012 Deleuil et al. ( , 2014)). The single 1D spectrum was carefully normalised. The spectral analysis was performed using the Versatile Wavelength Analysis (VWA) package  (Bruntt et al. 2010). The spectral parameters were determined by fitting the Iron lines until the derived Fe i and Fe ii abundances minimised the correlation with both the equivalent width and the excitation potentials.
They are all fully consistent with those obtained within the joint analysis with PASTIS, as described in Sect 3. 3. They are also consistent with the results in  Christiansen et al. (2018). As an independent check of the stellar parameters, we employed the same tools as used for stars in the SWEET-Cat catalogue  (Santos et al. 2013 ). The method is in essence the same as in the first part (equivalent widths of Fe i and Fe ii lines, and  iron excitation and ionisation equilibrium). Local thermodynamical equilibrium is assumed in the framework of the 2014 version of the code MOOG  (Sneden 1974) , together with the grid of Kurucz ATLAS9 plane-parallel model atmospheres  (Kurucz 1993)  and the equivalent width measurements of the iron lines from the code ARES  (Sousa et al. 2015). The derived values are log g = 4.
PASTIS analysis Similarly to previous studies  (Osborn et al. 2017; Barros et al. 2017; Santerne et al. 2018; Lam et al. 2018) , we used the bayesian software PASTIS  (Díaz et al. 2014; Santerne et al. 2015)  to jointly analyse the HARPS radial velocities, the K2 light curve and the spectral energy distribution (SED). For the SED, we used the magnitudes in optical from the APASS survey and in near-infrared from the 2MASS and AllWISE surveys  (Henden et al. 2015; Munari et al. 2014; Cutri & et al. 2014). The list of magnitudes is given in Table  1. The RVs were modelled with keplerian orbits and the stellar activity with a GP. We did not filtered the activity using de-correlation of the spectroscopic proxies as we did not find any significant correlations between them and the RVs (the highest correlation with RVs is 0.
14 for  the FWHM). We used a quasi-periodic kernel with the following covariance matrix: K QP = A 2 2 exp        - 1 2 ∆t RV λ 1 2 - 2 λ 2 2 sin 2 π |∆t RV | P rot        + I σ 2 + σ 2 j. (1) The first term is the quasi-periodic kernel with the hyperparameters: A 2 (amplitude), P rot (stellar rotation period), λ 1 (coherent timescale) and λ 2 (relative weight between the periodic and decay terms). The matrix ∆t RV have elements ∆t i j = t it j from the RV time series. The second term is the identity matrix I multiplied by the data uncertainty vector σ plus an extra source of uncorrelated noise σ j (jitter). The transits were modelled with the jktebop package (Southworth 2008) using an oversampling factor of 30 to account for the long integration time of the data  (Kipping 2010).
The upper masses derived are M f < 8. 7 M ⊕ and M g < 25. 5 M ⊕ at 99% confidence interval, though the one for planet f should be taken with caution as its signal may have been partly absorbed by the activity filtering. The timing precision obtained with K2 does not allow to use TTVs to bring further constraints on the masses of planets f and g. Additional observations of transits in this system, with a higher cadence than K2, would allow both to constrain the mass of planet f and to use K2-138 as a benchmark system to compare RV and TTV masses. Finally, thanks to its dynamical peculiarities, K2-138 is also a good candidate to search for co-orbital bodies. Analysis Center for Exoplanets (DACE), which is a facility based at the University of Geneva (CH) dedicated to extrasolar planets data visualisation, exchange and analysis.
DACE is a platform of the Swiss National Centre of Competence in Research (NCCR) PlanetS, federating the Swiss expertise in Exoplanet research. The DACE platform is available at https://dace. unige. ch. This research was made possible through the use of the AAVSO Photometric All-Sky Survey (APASS), funded by the Robert Martin Ayers Sciences Fund. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration.
This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This paper includes data collected by the K2 mission. Funding for the K2 mission is provided by the NASA Science Mission directorate. This research has made use of the Exoplanet Follow-up Observation Program website, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This research has made use of NASA's Astrophysics Data System Bibliographic Services. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.
Acknowledgements. We thank  Jessie L. Christiansen  and  Kevin Hardegree-Ullman  for the useful discussions on TTVs and on the Spitzer transit detection of planet g. We are grateful to the pool of HARPS observers who conducted part of the visitor-mode observations at  La Silla Observatory :  Julia Seidel ,  Amaury Triaud ,  David Martin ,  Nicola Astudillo ,  Jorge Martins ,  Vedad Hodzic. Based on observations made with  ESO Telescopes at the La Silla Paranal Observatory  under programme  ID 198. C-0. 168. This publication makes use of The Data &.
vestigador  FCT  contract  IF/01312/2014/CP1215/CT0004. O. D. S. D. is supported in the form of work contract ( DL 57/2016/CP1364/CT0004 ) funded by national funds through FCT. This work was supported by  FCT -Fundação para a Ciência e a Tecnologia  through national funds and by  FEDER -Fundo Europeu de Desenvolvimento Regional  through  COMPETE2020 -Programa Operacional  Competitividade e Internacionalização by these grants:  UID/FIS/04434/2019; PTDC/FIS-AST/28953/2017 & POCI-01-0145-FEDER-028953  and  PTDC/FIS-AST/32113/2017 & POCI-01-0145-FEDER-032113.
Schönrich et al. (2019)elease 2(Gaia Collaboration et al. 2018)parallax, taking into account the correction fromSchönrich et al. (2019), to derive the stellar distance. K2-138 has a corrected parallax of 4. 962 ± 0. 065 mas, leading to a distance of 201. 66 ± 6. 38 pc. Table 2. 3. Gaia astrometry & contamination Table A. 3. We also measured indices sensitive to stellar activity: H α , Na i D and Ca ii from which we de-4 https://rodluger. github. io/everest/using_everest. html rived S MW. The periodograms associated to the RVs and different indices are given in Fig. A. 1.
52 ± 0. 15 g Iron abundance [Fe/H] [dex] 0. 14 ± 0. 10 g Metallicity [M/H] [dex] 0. 15 ± 0. 04 g Rotational velocity υ sin i [km s -1 ] 2. 5 ± 1. 0 g Macroturbulence υ macro [km s -1 ] 1. 9 ± 0. 1 g Microturbulence υ micro [km s -1 ] 0. 90 ± 0. 10 g Stellar age (gyrochronology) [Gyr] 2. 3 +0. 44 -0. 36 g Spectral type G8 a. EXOFOP-K2: https://exofop. ipac. caltech. edu/k2/ b. Two Micron All Sky Survey (2MASS) c. Gaia DR2 d. Schoenrich, McMillan & Eyer (2019). Distances for the Gaia RV set with corrected parallaxes (Version 1. 0): http://doi. org/10. 5281/ zenodo. 2557803 e. AAVSO Photometric All-Sky Survey (APASS) f. AllWISE g. Spectral analysis (Sect. 3. 1) FWHM periodogram (Fig. A. 1) show a significant peak at 25 days of period, below 0. 1% FAP. In contrast, there is no clear signal in the S MW time series.
Statistical Analysis The relative percentage of UnIC conversion by bisulfite was calculated for each sample according to the delta-delta cycle threshold (ΔΔCT) method as described previously  (Livak and Schmittgen, 2001). ΔΔCT Sample = ΔCT UnIC -ΔCt Calibrator ; ΔCT UnIC = CT UnIC/MP- SHOX2 -CT UnIC/CF ; ΔCT Calibrator = CT ConIC/MP-SHOX2 -CT ConIC/CF. Efficiency of bisulfite conversion was calculated using the following formula: Percentage conversion UnIC = Percentage conversion ConIC x 2 -ΔΔCTSample = 100% x 2 -ΔΔCTSample. For all statistical analyses, a p-value ≤ 0. 05 was considered as significant. All analyses were performed with the STATA program version 12 (https://www. stata. com/) and Graphpad Prism program version 7 (https:// www. graphpad. com/scientific-software/prism/).
Quantitative SYBR Green real time PCR assay Bisulfite specific primers that are complementary to the sense strand of the converted DNA were designed using the Methyl Primer Express Software v1. 0. The primers used for methylated SHOX2 templates contained CpGs to ensure their specific annealing to methylated sequences. Real time PCR reactions with primer sets specifically designed to ConIC and UnIC were performed on bisulfite treated or nontreated DNAs extracted from healthy volunteers' lymphocytes in order to verify their specificity. The methylation status of the UnIC was evaluated by real time PCR that was carried out in 20 µl per reaction using 10 ng of bisulfite converted DNA as template and qPCRBIOSyGreen Mix Hi-ROX (PCR Biosystem). Real time PCR assays were duplexed in 2 reactions: (1) a reaction to quantify the total input UnIC; (2) a methylation specific reaction to quantify the bisulfite converted UnIC.
005 ng of linearized pUnIC or pConIC where separately mixed with 500ng of genomic DNA, then the mix was subsequently treated with bisulfite. Subsequently, real time PCR was performed on both samples using the CF-F/R and MP-SHOX2-F/R specific primer sets. We found that the CT values are not significantly different (p>0. 05) (data not shown), indicating that pConIC can be used as representative of the 100% bisulfite converted pUnIC. This result was consistent with previous report describing that DNA polymerases recognise uracil as efficiently as thymine during extension  (Heyn et al. , 2010). In order to confirm the performance of pUnIC as an indicator of bisulfite conversion efficiency, aliquots of 0. 005 ng of linearized pUnIC were mixed with 500 ng genomic DNA extracted from 3 FFPE samples of patients with non-cancerous pulmonary diseases and then treated with bisulfite following (1) manufacturer's instruction using the EpiTect Bisulfite Kit (Qiagen) or (2) with a 50% reduced time for bisulfite treatment compared to recommended time.
Bisulfite conversion efficiency in those 159 DNA samples was evaluated via the pUnIC indicator. Direct sequencing of PCR products amplified by the primer set specific to methylated SHOX2 showed that all cytosines in the CpG sites remained to be cytosines and the cytosines alone were converted to thymines (data not shown). Taking into account that 2 samples from the control group showed conversion rate (82% and 84%) below the 85% cut-off value (Figure  5 ), these 2 samples were excluded from further specificitysensitivity analysis of SHOX2 methylation. The mean conversion efficiency was estimated to 98. 7% (Figure  5 ). In addition, the pUnIC recovery rate was around 18% compared to 0. 005ng input pUnIC (data not shown), which is in agreement with the results previously presented in Figure  3C.
Acknowledgements The authors would like to thank  Nguyen T Trang ,  Pham AT Duong ,  Nguyen T Nga ,  Tran TC Van  at the  Biomedical Lab, Faculty of Biology, VNU University of Science, Hanoi, Vietnam , and the  Company BCE Vietnam Co, Ltd  for supporting 7500 Real-time PCR instrument. This study was financially supported by Grant  106-YS. 06-2015. 07from the  Ministry of Science and Technology, Viet Nam.
Results Identification of putative Hydra head inhibitors. To identify inhibitors of apical patterning that regulate the activity of the head organizer in both homeostatic and regenerative conditions, we established five criteria to be fulfilled by head inhibitor (HI) gene(s): (1) be controlled by Wnt/β-catenin signaling, (2) display an apical-to-basal graded activity, (3) be upregulated within the first day of head regeneration, (4) inhibit Wnt/β-catenin signaling, (5) prevent head formation (Fig. 1b ). To select β-catenin target genes, we used a dataset of 440 genes downregulated in planarians silenced for β-catenin  25  to retrieve 124 Hydra cognate genes (Supplementary Data 1). We analyzed their spatial and temporal RNA-seq expression profiles and found 5/124 genes predominantly expressed in the head and 3/5 upregulated in head-regenerating tips at least 1.
In Hydra, a two days exposure to ALP suffices to upregulate Sp5 expression along the body column (Fig. 5a , Supplementary Fig. 14 ), suggesting that Sp5 regulation by the Wnt/β-catenin pathway predates the divergence of cnidarians. To test this hypothesis, we cloned 2'992 bp of the Fig. 1  Screening strategy to identify candidate head inhibitor genes in Hydra. a Anatomy of an intact Hydra. The apical extremity (head) is composed of a dome-shaped structure called hypostome, surrounded by a ring of tentacles. At the other extremity (foot), the basal disk allows the animals to attach. b The five criteria used to identify HI candidate genes. c, d Screening procedure applied to identify HI candidate genes: An RNA-seq dataset of 440 downregulated genes in β-catenin (RNAi) planarians was used to retrieve through blastx on NCBI (E value < 1e -10 ) 124 non-redundant Hydra sequences that correspond to 106 unique proteins (Supplementary Data 1).
These candidates were next tested on RNA-seq data sets obtained in intact Hydra measured at five positions along the body axis (apical -Ap-, regions R1, R3, R4, basal -Ba-) to identify five apical-to-basal graded genes, which were tested on RNA-seq data sets obtained from regenerating tips taken at nine time points after a 50% or 80% bisection. Data available on HydrAtlas. unige. ch e Three genes downregulated after β-catenin(RNAi) in planarians, show an apical-to-basal graded expression in Hydra, and a minimal 1. 5-fold upregulation in head-regenerating tips at 24 hpa. The 3rd column indicates the mean value of the number of reads measured in three biological replicates in the indicated regions. Fold Change (FC) measured in head-regenerating (HR) tips at 24 h post-amputation (hpa) over the values measured at time 0.
2. 6. 2  56  , implemented in galaxy  57. Significantly enriched regions were identified using MACS2 58 (version 2. 1. 0. 20151222. 0). Coverage files were normalized by the millions of mapped reads in each sample using a manually created R script. Normalized bedgraph files were converted to bigwig using the Wig/BedGraph-to-bigWig converter tool (version 1. 1. 1) implemented in the pubblic Galaxy server (https://usegalaxy. org/) and visualized with UCSC genome browser. The fastq files from the two biological replicates of each condition were merged and remapped in order to obtain the average coverage profile. Only autosomal chromosomes were analysed in this study. MACpeaks regions were either extended or cropped from their respective center to match a final size of 500 bp using a personalized R script based on the GenomicRanges package (version 1.
32. 6). Fasta files containing the DNA sequences corresponding to the coordinates of the MACpeaks regions were obtained using the UCSC table browser tool. These files were used to identify enriched motifs for transcription factor binding sites using the MEME-ChIP Suite 59 (http://meme-suite. org/tools/meme-chip) in classic mode. Significantly enriched motifs were identified and compared to previously described TF weight matrixes from the JASPAR CORE 2014 database  59  using the TOMTOM tool of the MEME-ChIP suite. Significantly enriched motifs were used to scan the HySp5, HyWnt3 and ZfWnt3 promoters, using the FIMO tool (http:// meme-suite. org/tools/fimo)  60 to identify putative Sp5 binding sites. Gene assignment of the identified MACpeak region was performed using the ChipEnrich Package in R (version 2.
4. 0; locus definition: nearest TSS; gene set: gene ontology biological process; method: polyenrich). Calculations of the total HySp5 and ZfSp5a coverages (in Mb) and of the frequency distribution of the number of Sp5enriched regions per gene were performed in R using personalized scripts. ChIPseq data sets for the Sp5 and β-catenin occupancies in mouse ES cells  31, 61  were, respectively, downloaded from the GEO subseries GSE72989 and GSM1065517 and re-mapped on the mouse mm10 genome assembly using the same workflow describe above. RNA-seq data analysis. Demultiplexed RNA-seq reads from our sequenced samples were mapped onto the Human GRCh37 (hg19) genome assembly using the STAR RNA-seq aligner  62  workflow implemented in Galaxy. The fastq files from the three biological replicates of each condition were merged and remapped in order to obtain the average coverage profile.
We ran the Wald test and the P values were corrected for multiple testing with the Benjamini-Hochberg approach. We computed reads per kilobase of exon per million mapped reads gene expression levels using Cufflinks  66. FPKM levels were Log2-transformed, after adding an offset of 1 to each value. The Log2-transformed values were centered across samples before Principal Component Analysis (PCA); no variance scaling was performed. Heatmap plots were produced using the gplot package (version 3. 0. 1 in R). For this we computed the Z score ((X -μ)/σ, where for each gene μ and σ are respectively the average and standard deviation of all the replicates of the two conditions being compared and X is the FPKM value of each sample) based on the FPKM value of each gene differentially expressed between HySp5 vs HySp5-ΔDBD or between ZfSp5a vs ZfSp5a-ΔDBD.
Acknowledgements This work was supported by the  Swiss National Foundation  ( SNF 31003A_149630 ;  31003_169930 ), the  Canton of Geneva , the  Human Frontier Science Program  (grant no. RGP0016/2010 ), the  NCCR 'Frontiers in Genetics' , the  Claraz donation and the de Staël foundation. The authors warmly thank  Denis Duboule  and  Claude Desplan  for valuable inputs on the manuscript,  Ariel Ruiz I Altaba  and  Charisios Tsiairis  for discussions and reagents,  Carol Gauron  for excellent technical assistance,  Nenad Suknovic  and  Szymon Tomczyk  for help with image acquisition and the  IGe3 Genomic Platform  for ChIP-seq and RNA-seq library preparation and sequencing.
Data availability The Hydra Sp5 sequence has been deposited in GenBank under: MG437301. The genome assemblies and reads have been deposited in the BioProject under: PRJNA419866. RNA-seq and ChIP-seq data have been deposited in the GEO database under accession code GSE121321 [https://www. ncbi. nlm. nih. gov/geo/ query/acc. cgi?acc = GSE121321]. The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files or from the corresponding author upon reasonable request. The Source Data underlying Figs. 4f, 5d and Supplementary Figs. 6b, 12d are provided as a Source Data file.
We identified that common symbiotic genes such as LaSYMRK and LaCCamK remained present in WL genome and expressed in AMIGA roots (Supplementary Note 6). This suggests that WL adapted to environments where fungi partners may not thrive and instead favored a new type of root adaptive mechanism towards phosphate acquisition while maintaining the ability to symbiotically fix atmospheric nitrogen; conferring tremendous adaptation abilities to this plant  19. Despite the importance of cluster roots in nutrient acquisition, no gene controlling cluster root development has been described to date. We therefore generated a detailed transcriptomic dataset of WL cluster root developmental zones. Our RNA-seq survey (mRNA and miRNA) covered 8 sections of mature clusters that mimic the temporal stages of their development (Fig.
The impact of domestication on these candidate genes and WL soil exploration capacity was determined using a 2D-phenotyping platform. We identified that the root system architecture of AMIGA develops earlier than the wild-relative GRAECUS as a result of a strong increase in lateral and cluster root number (Fig. 3d ). This difference was correlated with an increased level of expression of the regulatory gene LaPUCHI-1 (Fig. 3c  and 3e ), an ortholog of a gene that is required for morphogenesis of the lateral root primordium in Arabidopsis  23. A list of candidate genes selected on their high induction level at the S1 stage (LaCLE1, LaMYB1, LaPEP1, LaPME41 and LaSTART), also showed a higher expression level in AMIGA compared to its wild relative GRAECUS (Extended Data Fig. 6 ). This suggests that activation of key regulatory genes can trigger the early establishment of the root system, a trait that has been characterized in other crops to be key for more efficient phosphate acquisition (e.
METHODS Genome assembly and annotation of Lupinus albus L. cv. AMIGA. A meta-assembly strategy similar to the one developed to assemble the Rosa genome  6  was applied. The Supplementary Table  1  provides details of the different steps of the process including data, software and the evolution of the metrics of the assembly. Firstly, three assemblies were performed with CANU 1 using different level of stringency (errorRate=default, 0. 015 and 0. 025 respectively). Corrected reads generated by CANU were also used to run FALCON  7. The graph of overlaps of FALCON was filtered using three different sets of parameters of the program til-r  6  , in order again to generate alternative assemblies with different level of stringency. The N50 metrics of the primary assemblies ranged from 1. 6 to 7. 1Mb.
The sequences of these six primary assemblies were first transformed in pseudo long reads of 100kb with an overlap of 50kb. Then, the pseudo long reads were assembled with CANU 1. 6 in the mode -trim-assemble to enable the trimming of sequence ends specific to a single primary assembly. The meta-assembly result displays a N50 of 8. 9Mb in only 129 contigs. The Bionano hybridScaffold. pl software was run in order to scaffold the contigs of the meta-assembly using the Bionano Optical map (N50 2. 3Mb). 15 putative breakpoints were identified and corrected by the scaffolder. The scaffolds were polished twice, firstly using arrow and the pacbio raw data mapped with blasr, then with Pilon 8 using 100x of illumina data mapped with glint software (http://lipmbioinfo. toulouse. inra. fr/download/glint/).