dataesr/scientific-paragraphs-categorization huggingface dataset:
Genotyping by Sequencing and genetic mapping. Two 96-plex GBS libraries (Keygene N. V. owns patents and patent applications protecting its Sequence Based Genotyping technologies) were constructed for the two parents (two replicates for each) and the 114 F1 plants of the cross CS × RGM. Raw reads were checked with FastQC 32 , demultiplexed with a custom script and cleaned with CutAdapt  33. Cleaned reads were then mapped to the V. riparia RGM scaffolds previously obtained, the V. vinifera Cabernet Sauvignon contigs  12  and V. vinifera PN40024 genome assemblies  4  for SNP calling. Aligned on these genomes were performed using BWA  34  , SAMtools  35  and Picard tools  36  and SNP genotypes were detected with GATK 37 using the hardfilter parameters  38. In the variant call format (VCF) output file only sites with less than 20% missing data and a minimum allele frequency (MAF) ≥ 0.
2 were retained. The SNP set was parsed into two data sets based on a pseudo-test cross mapping strategy  39  using major_minor and get_pseudo_test_cross scripts from Hetmapps  40. The segregation ratios of markers in the population were examined by Chi-square analysis. Markers with segregation ratios that differed from expected 1:1 at P < 0. 05 were classified as segregation distortion markers and discarded. The RGM and CS sets contain 1591 and 2359 SNPs respectively. Linkage groups (LGs) were determined using software JoinMap ® 4. 1 41,42 and Rqtl 43. LG were formed with a logarithm of odds (LOD) threshold of 6 and a maximum recombination frequency of 0. 45. The 19 LGs that corresponded to the 19 chromosomes of grapevine were reconstructed and leaded to a total genetic map length of 2,268 cM and 2,514 cM for RGM and CS respectively.
Data Records The V. riparia genome project was deposited at NCBI under BioProject number PRJNA512170 and BioSample SAMN10662253. The DNA sequencing data from Illumina, PacBio and 10x Genomics have been deposited in the Sequence Read Archive (SRA) database under accession SRP174866  54  from SRX5189632 to SRX5189680. This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession SJAQ00000000  55. The versions described in this paper are version SJAQ01000000 and genome ID 13150 (https:// www. ncbi. nlm. nih. gov/genome/13150). Genetic mapping data and structural and functional annotation file of the Vitis riparia assembly are available on figshare  56.
The assembled genome was also subjected to Benchmarking Universal Single-Copy Orthologs  58  , which quantitatively assesses genome completeness using evolutionarily informed expectations of gene content from near-universal single-copy orthologs, using the genes in the embryophyta release 9 dataset (embryophyta. odb9). The BUSCO results showed that 96. 5% of conserved BUSCO proteins were detected in the V. riparia assembly, including 1. 1% of fragment BUSCO proteins (Table  2 ). Overall, these metrics compare well with other recently published grape genomes, providing a high quality genome sequences for the following functional investigations. 17. Interproscan functional annotation and putative gene function assignation Download protein DB from http://www. uniprot. org makeblastdb -in protein_db.
acknowledgements We thank  Dr. Gregory Gambetta  for critical review of the manuscript. We thank the  INRA Genotoul bioinformatics platform  (http://genotoul. toulouse. inra. fr)for providing computational resources and support and  INRA-CNRGV  (http://cnrgv. toulouse. inra. fr/)for V. riparia HMW DNA extraction. Sequencing was performed at the  GeT core facility, Toulouse, France , supported in part by  France Génomique National infrastructure  (contract  ANR-10-INBS-09 ). We thank  Dr. Timothée Flutre  and  Amandine Launay  for their help in coordinating the  FruitSelGen  project and in acquiring GBS data. This work was supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  ANR-09-GENM-024  " Vitsec" program  and by the  University of Bordeaux.
Plant food bioacƟves Variability in response Fig. 1  Factors influencing inter-individual variability in cardiometabolic response to plant food bioactive consumption ethnicity) to identify the main factors responsible for between-subject variation beyond bioavailability. The network also performed a systematic analysis of nutrigenomic data available, to identify the cellular and molecular targets involved in the effects of plant food bioactives on cardiometabolic outcomes. The present review summarizes the main findings resulting from this extensive body of work together with the needs and recommendations for future research. Existing clinical data collected for cardiometabolic risk biomarkers such as blood lipids, blood pressure and BMI show large variations among randomized controlled trials (RCTs) carried out in different countries, from individuals with different lifestyles, ethnicity, age, sex, and physiological/health status, etc.
This summary will focus on published meta-analyses, examining the effect of flavonols  [28] , flavanols  [29] , anthocyanin and ellagitannin-containing products  [30]  on selected biomarkers of cardiometabolic risk, including blood lipids, blood pressure, endothelial function, glucose homeostasis and anthropometric parameters. The first meta-analysis examined the effects of various factors on the variability in the responses to their consumption of flavanol-containing tea, cocoa and apple products, where data from 120 RCTs involving 5931 individuals was examined  [29]. Selected biomarkers of cardiometabolic risk including body mass index (BMI), waist circumference (WC), total cholesterol (TC), LDL-cholesterol (LDL-c), HDL-cholesterol (HDL-c), and triacylglycerides (TAGs) were considered. Overall, the effects on BMI, WC, total cholesterol and LDL-c appear to be statistically significant in subgroups of people with overweight/obesity (BMI > 25 kg/m 2 ).
Taking TNF-alpha as an example, a search of SNP databases [Variation Viewer (https ://www. ncbi. nlm. nih. gov/varia tion/view/overv iew) or Ensembl genome database (https ://www. ensem bl. org/ index. html)] showed several hundreds of SNPs in this gene, some of which were insertion or deletion of bases in the DNA, missense mutations, mutations in 5′ UTR region which encompass the promoter region of the gene, frameshift or nonsense/stop gained, with 23 SNPs with a minor allele frequency of > 0. 1 or nearly 60 with minor allele frequency > 0. 05. Some of these SNPs were previously identified as associated with high or low blood pressure using genome-wide association studies, as identified from genome-wide association studies (GWAS) Catalog database (https ://www. ebi. ac. uk/gwas/). Furthermore, several SNPs were observed to be associated with known variability in the effects of certain drugs [as observed using Pharmacogenomics Knowledgebase (https ://www.
| ME THODOLOGY Empirical data for this study were collected during two Citizen Summits organized as part of the CARISMAND 9 project and held in F I G U R E 1 Questionnaire | 297 Rome (Italy) and Frankfurt (Germany) in June 2017. These two research sites were chosen because both Italy and Germany are positioned in the middle ranks of disaster risk indices amongst European countries, 10 but with very specific local experiences. On the one hand, citizens in the Rome area are living in a comparatively safe location but, at the time of the summit, had very recent experience of a series of earthquakes ("natural hazards"). On the other hand, citizens living in the Frankfurt/Rhine-Main area may not have had recent experiences but are exposed to an elevated level of local "man-made hazards" (large airport, chemical industry).
More recently, it has also been used for scientific research, for example, related to citizens' perceptions and attitudes towards surveillance technologies  (Degli Esposti & Santiago Gomez, 2015). Following the same concept, CARISMAND Citizen Summits combined public information and public feedback-gathering with quantitative and qualitative data collection. The Italy Citizen Summit was held in Rome, with participants recruited from the greater Rome and Lazio region. 11 The Germany Citizen Summit was held in a conference centre at the Frankfurt International Airport with participants from all over the Rhine-Main area. 12 Participants were recruited via local research agencies using an industry-standard "FreeFind" approach, 13 and they were incentivized in line with regular local practices. A recruitment questionnaire ensured the selection of balanced samples with an even gender and age distribution, and 105 participants in each of the two locations.
Furthermore, the recruitment criteria included key aspects of disaster experience and disaster risk perception (Q1 in Figure  1  below), to ensure that all levels of experience with disasters were present in each sample. Quantitative data were collected via a plenary session in the morning, capturing participants' immediate responses to all questions via an audience response system. 14 After each Summit, these responses were exported to a database and fully anonymized. All analyses were conducted with SPSS version 24. 0, and significance tests were run for all results. For the qualitative part of the study held in the afternoon session of each event, participants were allocated to ten simultaneously held discussion groups of nine to eleven participants with an even gender split, and a division into age groups that aimed to allow participants to discuss amongst peers with similar life experience.
| LI M ITATI O N S The main limitation of this study lies in that the data in both research locations were collected from non-probability samples, which are not representative of either the German or the Italian population. Furthermore, data were collected in two geographical locations only. However, the samples had a spread of participants of all ages, an even gender split, and different levels of disaster experience and disaster risk perception. In addition, these locations were chosen due to their difference in local disaster histories and types of local hazards, and the similarity of participants' responses in both Citizen Summits suggests that citizens' contrasting attitudes and perceptions towards disaster apps and social media use in disasters may not be significantly affected by local differences in disaster experiences and disaster risk perceptions.
All Citizen summits addressed the same overarching research theme, that is, risk perception and culture in disaster management, and each of the three individual "rounds" of summits explored a specific set of additional topics. Findings presented in this article represent only one of several research topics targeted in these summits. 10 https ://relie fweb. int/repor t/world/ world-risk-report-2017; accessed 08/2018. 11 One of Italy's 20 administrative regions with Rome being its regional capital. 12 Metropolitan region in Germany stretching over several large cities. 13 Process of recruiting participants outside existing databases or panels, using any, or a variety of, suitable methods (e. g. , posters, newsletters, social media). 14 Clik-a-pad system with ppvote software; http://www. clika pad.
In Fig. 1  we show results from preliminary simulations on case "Hab1" conducted with four different GCMs; UM, LMDG, ROCKE3D and ExoCAM. We show surface contours for surface temperature, thermal emitted radiation (TOA) and reflected stellar radiation (TOA). We can see significant differences in the maximum, minimum and mean values of these parameters between the models. For such a complex atmosphere it is difficult to disentangle the effects leading to these differences. However, it seems clear that the patterns of thermal emitted and reflected stellar TOA fluxes are strongly influenced by the cloud patterns produced by each respective model. Here we have shown preliminary outputs to demonstrate the feasibility of the described experiments. In depth analysis of these simulations will be discussed in a following manuscript in preparation.
Acknowledgements. Goddard affiliates are thankful for support from  GSFC Sellers Exoplanet Environments Collaboration (SEEC) , which is funded by the  NASA Planetary Science Divisions Internal Scientist Funding Model. M. T. acknowledges the use of the computing resources on OCCIGEN (CINES,  French National HPC ). This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie Grant  Agreement No. 832738/ESCAPE. M. W. and A. D. acknowledge funding from the  NASA   Astrobiology Program  through participation in the Nexus for  Exoplanet System Science (NExSS). The  THAI GCM  intercomparison team is grateful to the  Anong 's  THAI Cuisine restaurant in Laramie  for hosting its first meeting on November 15, 2017.
Code availability. ExoCAM  (Wolf and Toon, 2015)  is available on Github, https://github. com/storyofthewolf/ExoCAM. The Met Office Unified Model is available for use under licence, see http://www. metoffice. gov. uk/research/modelling-systems/unified-model. ROCKE-3D is public domain software and available for download for free from https://simplex. giss. nasa. gov/gcm/ROCKE-3D/. Annual tutorials for new users take place annually, whose recordings are freely available on line at https://www. youtube. com/user/NASAGISStv/playlists?view=50& sort=dd&shelf_id=15. LMD-G is available upon request. Data availability. No data have been used in this study Competing interests. No competing interests are present.
, 2018). However, this study did not investigate the selective consequences (positive or negatives) of the introgressed domestic ancestry within wild populations which thus remains poorly understood. The recent availability of a high density linkage map developed for S. fontinalis  (Sutherland et al. , 2016)  and a reference genome for the sister species the Arctic Charr (Salvelinus alpinus)  (Christensen et al. , 2018)  open new opportunities to investigate for the first in any salmonid how selection in interaction with recombination modulates introgression at a genome-wide scale, as well as within and between chromosomes following human-mediated hybridization events. More specifically, we used a RADseq data set collected from 24 Brook Charr populations that have been stocked with the afore mentioned domestic strain to assess genome-wide patterns of variation in local domestic ancestry for both early and late-generation hybrids.
Sampling, sequencing and genotyping The Brook Charr populations analyzed in this study were sampled in 2014 and 2015  (Létourneau et al. , 2018)  and consist in 611 individuals from 24 lakes located in two wildlife reserves (Mastigouche and St-Maurice) in Québec, Canada. Additionally, 37 domestic fish originating from the Truite de la Mauricie Aquaculture Center broodstock, were used as reference for domestic samples. Stocking intensity was variable among lakes,as can be seen from the data on the history of stocking including the number of years since the mean year of stocking (mean_year), the total number of stocking events (nb_stock_ev), the mean number of fish stock per stocking event (mean_stock_fish) and the total number of fish stocked per stocking event (total_ha) reported in Table  1.
GBS library preparation was performed in  Létourneau et al. (2018) , after the extraction of genomic DNA from fin clips and quality evaluation. Libraries were amplified by PCR and sequenced on the Ion Torrent Proton P1v2 chip. Raw reads were checked for quality and the presence of adapters with FastQC (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/), reads were then demultiplexed with STACKS v1. 40  (Catchen, Hohenlohe, Bassham, Amores, & Cresko, 2013)  with the option process_radtags as described in  Létourneau et al. (2018). Demultiplexed reads were aligned to the Arctic Charr (Salvelinus alpinus) reference genome  (Christensen et al. , 2018)  with BWA_mem program v. 0. 7. 9  (Li & Durbin, 2010)  before the individual SNPs calling with pstacks module (using m=3 and the bounded error model with α=0.
05). To build the catalogue in cstacks, we randomly used 10 individuals per population with a coverage depth of at least 10X and a minimum of 500,000 reads. Each individual was then matched against the catalogue with sstacks. The population module was then run separately for each of the 24 lakes and the domestic strain, in order to generate one VCF file per population with loci passing the following filters: (i) a minimum depth of 4 reads per locus, (ii) a genotype call rate of at least 60% per population, (iii) a minimum allele frequency of 2% and (iv) a maximum observed heterozygosity of 80%. Individuals with a high percentage of missing data (>20%) were removed resulting in a final data set of 33 domestic individuals and 603 wild caught individuals (Table  1 ). Finally, to avoid merging paralogs, we removed for each individual loci with more than two alleles with the R package stackr  (Gosselin & Bernatchez, 2016).
Finally, the number of admixture generations (-mg) was estimated using the mean year of stocking and the approximate mean age at maturity of 3 years and ranged from 3 to 16 generations (Table  1 ). We then generated individual domestic ancestry profiles by plotting the estimated number of domestic allele copies for each replicate run and its median along each LG with R  (Team, 2015). The pipeline we used is available on GitHub (https://github. com/mleitwein/local_ancestry_inference_with_ELAI). We then compared the percentage of domestic ancestry computed here with ELAI to the previous study from  Létourneau et al. (2018)  using a spearman's correlation.
Normality of the residuals was examined graphically using a quantile-quantile plot. We used a likelihood ratio test to assess the significance of the tested relationship by comparing the models with and without the explanatory term. We calculated marginal R² to quantify the proportion of variance explained by the explanatory variable only. All analyses were performed in R using the package "lme4"  (Bates, Mächler, Bolker, & Walker, 2015).
Domestic ancestry profiles as a function of hybrid classes The fraction of domestic ancestry rate was estimated separately for both hybrid classes, with the early-generation hybrids comprising 47 individuals from 17 populations and the late-generation hybrids comprising 394 individuals from the 24 populations. Local ancestry rate from the domestic strain was estimated at 11,803 SNPs positions distributed along the 42 LGs and common between all the individuals originating from different lakes and found in the two hybrids categories. Estimates of genome-wide domestic ancestry rate for each hybrid category were plotted with R (Team, 2015) (https://github. com/mleitwein/local_ancestry_inference_with_ELAI). The mean domestic ancestry rate and its 95% CI were reported along the 42 LGs. Then, genomic regions exceeding the 95% CI were considered as displaying excess or deficit of domestic ancestry.
Linear mixed models were used to investigate how domestic ancestry profiles (i. e. mean number and length of domestic tracts) differ between early and late hybrid classes. The domestic tracts characteristics were log-transformed and treated as dependent variables whereas the hybrid class (discrete variable with two modalities) was introduced in the model as an explanatory term. The population (24 populations) and region (two regions, Mastigouche and St Maurice) terms were introduced as random effects in the model. All analyses were performed in R using the package "lme4"  (Bates et al. , 2015).
A linear mixed model was built for each of the 42 linkage groups and the 2Mb sliding window was introduced as a random effect in all models. The slope coefficient (and the 95% CI) of the relationship between domestic ancestry rate and recombination rate was reported for the 42 linkage groups. At the 2Mb window level, generalized linear models were built for each window containing at least 5 positions with an estimated recombination and introgression rate (resulting in 689 models) because a regression analysis could not be performed with fewer values. The slope coefficient and its 95% CI were reported for each sliding window. In all models, the significance of the effect of the explanatory terms was assessed with a likelihood ratio test. All analyses were performed in R using the package "lme4"  (Team, 2015).
As in previous studies (e. g. Renaut & Rieseberg, 2015; Ferchaud, Laporte, Perrier, & Bernatchez, 2018)  a threshold of -2. 5 in Provean score was applied to distinguish between nonsynonymous mutations potentially deleterious (-2. 5) and neutral (>-2. 5). In PROVEAN, the deleteriousness of a variant can be predicted based on its effect on gene functioning (such as protein changing, stop-gain, stop-lost), for example by assessing the degree of conservation of an amino acid residue across species. The pipeline used for the entire process is available on github (gbs_synonymy_genome: https://github. com/QuentinRougemont/gbs_synonymy_with_genome). To evaluate the relationship between the presence of potentially deleterious mutations and the domestic ancestry rate as a function of recombination rate, a mean domestic ancestry and recombination rate was estimated in a window size of 400Kb surrounding the position of the potentially deleterious mutation (i.
Acknowledgments We thank biologists and technicians of the  Société d'Etablissement de Plain Air du Québec (SEPAQ)  and the  Ministère des Forêts, de la Faune et des Parcs du Québec (MFFP) , in particular  Amélie Gilbert  and  Isabel Thibault  for their implication in the project and/or their field assistance and sampling. This research was funded by the  MFFP , the  Canadian Research Chair in Genomics and Conservation of Aquatic Resources, Ressources Aquatiques Québec  (RAQ) as well as by a  Strategic Project Grant  from the  Natural Science and Engineering Research Council of Canada (NSERC)  to  L. Bernatchez ,  D. Garant  and  P. Sirois.
Chemometric Analyses Principal Component Analysis (PCA) was performed on the data set as exploratory unsupervised analysis. Individuals outside of the 95% confidence interval of the Hotelling's T-square were considered to be outliers and excluded from the subsequent analyses. Partial least squares discriminant analysis (PLS-DA), a method of supervised classification, was performed to predict the chicken group (i. e. , D+ or D-) by explanatory quantitative variables (defined here by the peaks), using the SIMCA 13 Software  (Barker and Rayens, 2003). The selection of metabolomics variables was carried out by iteratively excluding the variables with low regression coefficients and wide confidence intervals derived from jackknifing combined with low variable importance in the projection (VIP) until maximal improvement of the quality of the models.
The putative molecules included in the model were lipids [ceramide (Cer), diglyceride (DG), phosphocholine (PC), phosphoethanolamide (PE), 3-O-(2-O-(2E-decenoyl)-alpha-L-rhamnopyranosyl-(1-2)-alpha-L-rhamnopyranosyl)-3-hydroxydecanoic acid, kamlolenic acid] as well as a terpenoid (24-noroleana-3,12-diene), a steroid (22:5 cholesteryl ester), and xanthophylls (lutein/zeaxanthin), the latter being the most differential between lines with a fold change of 4. 63. The contribution plots generated by SIMCA software (Figure  2b ) were used to identify the metabolites allowing chicken-line discrimination. The M395T10 feature (24-Noroleana-3,12-diene) was the only one to highly and positively contribute (outside of 3 standard deviations in the raw data distribution) to the D-line, while M551T5 (lutein/zeaxanthin) was the highest contributor to the D+ line.
ACKNOWLEDGMENTS We thank the staff of the  Poultry Breeding Facilities (INRA, Unité Expérimentale Pôle Expérimental Avicole de Tours, INRA, Nouzilly, France)  and of the Rearing Facilities ( INRA, Unité Expérimentale Elevage Alternatif et Santé des Monogastriques, INRA, Le Magneraud, France ). This study was supported by Feed-a-Gene, a project that has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 633531.