dataesr/scientific-paragraphs-categorization huggingface dataset:
The optimal number of clusters found by STRU CTU RE HAR-VESTER (used to visualize the results of STRU CTU RE analysis) was two with ΔK = 16. 03 (the second biggest ΔK was 2. 55). Surprisingly, the clusters found by STRU CTU RE did not match the DAPC or BAPS results. These two clusters grouped individuals from several stations with no obvious relation with any ecological or geographical parameter, and with a very small average assignment probability of individuals to their cluster (P Ass = 0. 53683). The partition found by STRU CTU RE and STRU CTU RE harvester with K = 2 is probably meaningless. Cytb fragment sequencing of seven individuals from cluster 21 (# 12, 17, 18, 19, 856, 872, and 874) and one of the two outliers (# 23, cluster 2) showed 99-100% similarity with Ph. ariasi (GenBank accession number: KP685539.
To check the result stability, additional DAPC analyses were performed by successively removing the following loci Aria1, Aria10, Aria11, Aria12, and Aria15. As long as Aria1 was kept, the obtained pattern was the same as in Fig. 2  (data not shown). With the remaining six loci (Aria2, Aria3, Aria4, Aria5, Aria13, and Aria14), DAPC and BAPS provided no clear structure. This suggested that the distinction between group A (the 22 outliers) and group B (the 1,177 remaining individuals) only relied on the Aria1 locus (Supplementary Table  S1 ). Aria4, Aria5, Aria13,  and Aria14 ). Outlier individuals (Group A) are indicated in red. The same tree was obtained also using 10 loci (excluding Aria1). Linkage disequilibrium and F-statistics with the six remaining loci. With the remaining six loci (Aria2, Aria3, Aria4, Aria5, Aria13, and Aria14), the proportion of significant LD tests was 13.
002). The Micro-Checker analysis suggested the presence of null alleles at four loci (Aria2, Aria3, Aria4, and Aria14). According to the criteria described in De Meeûs  30  (see "Methods" section), null alleles only explained partly (if any) the observed heterozygote deficit. To check the result stability again, the F IS computed for the dataset that included also Group A (complete dataset) was compared with the one obtained without it (Group B) (Supplementary Table  S1 ). The F IS was bigger in the complete dataset than in Group B alone (F IS = 0. 079 and F IS = 0. 057, respectively), and the difference was significant (p value = 0. 0486 unilateral Wilcoxon signed rank test). This translated into a Wahlund effect when Group A individuals were included in the data. These individuals were thus kept excluded.
Direct sequencing in both directions was performed by Eurofins Genomics. Data analysis. Microsatellite raw data were formatted for CREATE  62  that allowed their transformation into the formats needed for the different analyses. Samples with more than 50% of missing data were removed from the analyses. Bayesian clustering. Several Bayesian clustering analyses were carried out. To validate the sand fly species identification, the first analysis was based on the 11 selected loci and included all sand fly samples. Then, to study the organization of Ph. ariasi populations, data were analyzed at different scales: hillside, altitude, and station. This analysis was performed with the loci selected after Linkage Disequilibrium (LD) and F-statistics analyses (see "Results" section). As the clustering method accuracy can vary depending on the statistical properties of specific software programs and datasets  29, 42, 63  , three different Bayesian clustering methods were used.
First, a discriminant analysis of principal components (DAPC)  64  was performed using the adegenet  65  package for R 66. This was followed by a Bayesian Analysis of Population Structure (BAPS; admixture model  67, 68  , maximum number of clusters: 35, repetition: 50; that is freely available at https ://www. helsi nki. fi/bsg/softw are/BAPS/), and a STRU CTU RE (version 2. 3. 4) analysis  69  (burning period: 10,000, number of clusters from 1 to 35, with the admixture model). STRU CTU RE HARVESTER vA. 2  70  was used to visualize the STRU CTU RE analysis results, examine the ad hoc ΔK statistic, and determine the optimal number of clusters. Finally, a dendrogram (NJTree) was built with MEGA 7  71  from a Cavalli-Sforza and Edward's chord distance (D CSE )  72  matrix as recommended  73  , between subsamples defined as combinations of the group obtained by Bayesian clustering and sampling stations.
All glm's were done using R version 3. 5. 1  66  , with the package rcmdr (R-commander)  83, 84. Model selection was performed using a forward stepwise model selection procedure and the Akaike Information Criterion  85. The influence of different factors (including interactions) was tested by examining the differences between models (complete, additive, and with one variable) with analyses of variances. As the entry order of explanatory variables matters in R analyses, the mean partial R 2 of each variable was calculated across all possible models. Isolation by distance. Geographic distances were computed with Genepop version 4. 7. 0 86 using the Euclidian distance computed with the Universal Transverse Mercator (UTM) coordinates (Table  2 ). Genetic distances were estimated with the Cavalli-Sforza and Edwards chord distance 72 D CSE , the most powerful method to detect isolation by distance with microsatellite markers in most situations  87.
Due to the presence of missing data, data were converted into the FreeNA format to compute D CSE between each station pair with the ENA correction  36  that provides a very good correction for the isolation by distance regression slope in the case of null alleles  87. As these station pair ended into a non-squared matrix that could not be handled by Genepop, the relationships between genetic and geographic distances were tested with a Mantel test (10 4 permutations)  88  in F STAT 2. 9. 4. As the Mantel test in F STAT is bilateral by default, the p value was halved in the case of positive slope, or computed as: "1-(1-bilateral p values)/2" in the case of negative slope, to obtain unilateral p values for a positive slope. The relationships between genetic and altitudinal distances were also tested in the conditions described above.
Acknowledgements This work was supported by  EU  Grant  FP7-261504  EDENext (https ://www. edenext. eu). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the  European Commission. The authors wish to thanks the  ISEM GenSeq technical facilities, Institut des Sciences de l'Evolution de Montpellier , and the  Centre Méditerranéen de l'Environnement et de la Biodiversité  where some of the samples were prepared. We are also particularly grateful to  Pr Rioux  for sharing knowledge of the study area,  Mr Lacoste  and the  "Fondation France", IRD (Institut de Recherche pour le Développement) ,  CNRS  ( Centre National de la Recherche Scientifique ) and  INFRAVEC2  project (https ://infra vec2. eu/) for financial support. We also thank  Elisabetta Andermacher  for assistance in preparing and editing the manuscript and  Jérôme Goudet  for useful tips regarding PCAGen.
5mm, microparticles GmbH) with the aid of epoxy glue to obtain a well-defined indenter geometry and decrease local strain during indentation. Cantilevers were calibrated prior to experiments using built-in procedures of the SPM software (JPK Instruments). The bead was lowered at a defined speed (10mm/sec) onto the cell surface. After reaching the setpoint of 2nN, the cantilever was retracted. During the force-distance cycle, the force was recorded for each piezo position. The resulting force-distance curves were transformed into force-versus-tip sample separation curves  (Radmacher, 2002)  and fitted with the Hertz/Sneddon model for a spherical indenter  (Sneddon, 1965)  using the JPK data processing software (JPK DP, JPK Instruments). A Poisson ratio of 0. 5 was used for the calculation of the apparent elastic modulus.
Real-time Deformability Cytometry Mitotic cells were collected after 5 hours of STLC treatment (5mM) using the mitotic shake-off method. Interphase cells were detached by treatment with Accutase (PAA laboratories) for 15 minutes. The cells were washed with PBS and resuspended in 0. 5% methylcellulose buffer before loading in the RT-DC setup as described previously  (Otto et al. , 2015). Cells were deformed by flowing them through 30mm 3 30mm channels with a speed of 0. 16ml/sec or 0. 32ml/sec and the deformation was recorded using ShapeIn software (Zell Mechanik Dresden). Data for over 2000 cells was recorded for each of 10 biological replicates of the experiment. Apparent elastic modulus was calculated using ShapeOut Software (Zell Mechanik Dresden, available Developmental Cell 52, 563-573.
e1-e3, March 9, 2020 e2 at https://github. com/ZELLMECHANIK-DRESDEN/ShapeOut) based on a numerical simulation model described previously  (Mokbel et al. , 2017). The results from 10 independent experiments were analysed using a Linear Mixed Model method integrated in ShapeOut Software (Zell Mechanik Dresden)  (Herbig et al. , 2018).
Statistical Analysis Images were processed and cell shapes measured using FIJI  (Schindelin et al. , 2012) , https://fiji. sc/). Graphs were produced using Prism 7 (GraphPad). Bar charts show mean with error bars showing standard deviation and Box-and-whisker plots use the Tukey method to identify outliers. For live cell imaging, cell shape measurements and gel confinement experiments, graphs show data pooled from at least 3 independent experiments, unless otherwise stated. The number of cells (n) analysed in each condition is indicated in parentheses on plots. For western blotting, at least three independent experiments were carried out and one representative dataset is shown. For AFM, two independent experiments were carried out and one representative dataset is shown. Statistical testing was carried out using Prism 7 (GraphPad).
Unless otherwise stated, p values were calculated using the Mann-Whitney two-tailed test. *p<0. 05 **p<0. 01 ***p<0. 001. To perform statistical analysis on multiple sets of RT-DC experiments, linear mixed effects models were implemented using the lme4-package in R (R Core Team, 2017; www. R-project. org/. ). As fixed effects, we had cell type (control, ras) and cell cycle stage (interphase/mitotis), as random effects, we had random intercepts/slopes for different experimental days. p-values were obtained by likelihood ratio tests of the full model with the effect in question against the model without the effect in question. Further details of the statistical tests used, exact value of n, definition of error bars on graphs can be found in figures and figure legends.
ACKNOWLEDGMENTS The authors thank  Ewa Zlotek-Zlotkiewicz  and  Ma€ el Le Berre  for help with the gel confinement experiments,  Gautam Dey  for help with cell volume measurements, and  Oliver Otto  for carrying out pilot RT-DC experiments. We also thank  Andrew Vaughan ,  Ki Hng , and  John Gallagher  for microscopy support and  Anne-Laure Cattin ,  Alison Lloyd ,  Susana Godinho ,  Julian Downward , and  Erik Sahai  for reagents. We also thank  Susana Godinho ,  Guillaume Charras , and  Nitya Ramkumar  for comments on the manuscript. This project was funded by  Cancer Research UK : H. K. M. , K. P. , and B. B. were supported by a  CRUK Programme Grant  ( C1529/A17343 ); H. K. M. was also funded by a  CRUK/EPSRC   Multi-Disciplinary Project Award  ( C1529/A23335 ); and S. G. was supported by a  CRUK Clinical studentship  ( 5369923 ).
1% formic acid. Then, the peptides were eluted towards the nano-column (C18 PepMap, 75 μm i. d. x 15 cm, 3 μm, 100 Å) at a flow rate of 300 nL/min, maintained at 35°C and using a 65-min linear gradient (from 4 to 35% acetonitrile containing 0. 1% formic acid). The mass spectrometer source settings were as follows: capillary voltage, 1. 5 kV; dry gas, 4. 0 L/min; dry temperature, 150°C. The MS analysis was carried out in the positive ion mode with a resolution of ~50,000 at m/z ~1200, while MS/MS acquisitions were performed in a data-dependent acquisition mode using the seven most intense precursor ions. Precursor ions from the 400-2000 m/z window were fragmented under CID conditions for peptide identification. All data sets were re-calibrated using a lock mass (m/z 1221. 9906) before data analysis.
Resulting MS and MS/MS data were manually extracted and interpreted. Tandem affinity purification of Flag-HA-H2A. J and Flag-HA-H2A were performed as previously described  (17). Co-immunoprecipitation assays. Trypsinized cells were washed with PBS and quickly with Hypotonic Lysis Buffer (10 mM Tris-HCl (pH 7. 5), 1. 5 mM MgCl2, 10 mM KCl, 0. 5 mM DTT, protease inhibitors). Cells were then incubated on ice for 10 minutes in Hypotonic Lysis Buffer and flash frozen in liquid nitrogen. Cell membranes were disrupted using a Dounce homogenizer with a type B pestle (25 strokes). Nuclei were pelleted by centrifugation at 1,500 g for 10 minutes at 4°C. Nuclear pellet was washed once with Hypotonic Lysis Buffer, then resuspended in Nuclear Extraction Buffer  (25 mM  Tris-HCl (pH 7. 5), 500 mM NaCl, 1% Triton-X-100, 1% sodium deoxycholate, 1 mM DTT, protease inhibitors) and incubated on ice for 30 minutes.
RT-qPCR. RNA was extracted as indicated in RNA-seq and Illumina Bead ChIP Array protocols. cDNA was prepared from 500ng of RNA using random hexamer primers. Quantitative PCR was performed with a Luminaris Color HiGreen Fluorescein qPCR Master Mix (Thermo Scientific #K0384) and a CFX96 Touch Real-Time PCR Detection System (Bio-Rad) following the manufacturer's protocols. Values were normalized to GAPDH RNA levels. DNA primers for the qPCR are shown in Supplementary Table  2. Illumina Bead ChIP Array transcriptome analyses. The effect of expressing H2A. J, H2A. J mutants, and H2A-type1 on the transcriptome of proliferating WI-38hTERT fibroblasts was assessed by microarray analyses using Illumina HumanHT-12v4 Bead Chip Arrays as previously described  (11). Bioinformatic analyses. R and bash scripts are posted on Zenodo.
DNA Gene set enrichment analysis was performed with camera  (33)  and with the Broad Institute server  (34). RepEnrich2 (https://github. com/nerettilab/RepEnrich2) was used to assign bam files generated by bowtie2 to repeated DNA elements, and differential expression analysis was then performed as above for unique sequences. The bash and R codes used for the ChIP-seq, Ribo-Zero RNA-seq, and small-RNA-seq analyses are availabe at Zenodo (10. 5281/zenodo. 4147010). Code and salmon quant files for the MEF transcriptome analysis are available at Zenodo (10. 5281/zenodo. 4140080). Illumina Bead Chip microarrray analysis code and idat files are available at Zenodo (doi:10. 5281/zenodo. 4139402).
Sequence availability. RNA-seq, ChIP-seq, and microarray data were deposited in the EBI Array Express database under the following accession numbers: MEF polyA+ RNA-seq (E-MTAB-9704), Illumina Bead Chip microarrays (E-MTAB-9706), RNA-seq of small RNAs (E-MTAB-9710), RNA-seq of rRNA-depleted total RNAs (E-MTAB-9714), ChIP-seq of RNA polymerase II (E-MTAB-9717), ChIP-seq of H3-K4me3 (E-MTAB-9718).
ACKNOWLEDGEMENT This work has benefited from the facilities and the expertise of the High-throughput Sequencing Platform and the  SICaPS Proteomic  platform of the  I2BC (Institute for Integrative Biology of the Cell ),  CEA ,  CNRS ,  Univ. Paris-Sud ,  Université Paris-Saclay ,  91198 ,  Gif-sur-Yvette  cedex, France.
AVAILABILITY The bash and R codes used for the ChIP-seq, Ribo-Zero RNA-seq, and small-RNA-seq analyses are availabe at Zenodo (10. 5281/zenodo. 4147010). Code and salmon quant files for the MEF transcriptome analysis are available at Zenodo (10. 5281/zenodo. 4140080). Illumina Bead Chip microarrray analysis code and idat files are available at Zenodo (doi:10. 5281/zenodo. 4139402).
Vesicular gene expression in various Gallus gallus tissues We evaluated the literature on bone and cartilage extracellular vesicles  (32) (33) (34) (35) , EVs  (36) (37) (38) (39) , and the Vesiclepedia database (www. microvesicles. org/), which lists the top 100 proteins that are identified in EVs  (40). A total of 33 genes coding for proteins involved in vesicular transport were selected, corresponding to proteins involved as calcium channels to supply calcium, bicarbonate supplier/transporter, chaperone molecules, addressing molecules, intracellular trafficking proteins, extracellular biogenesis and release, and signaling proteins (Table  S2 ). Expression levels for these 33 genes were quantified in different tissues and organs, namely oviduct segments, bone, duodenum, kidney and liver (Table  1 , Fig.
The CA4-catalysed accumulation of high levels of bicarbonate in proximity to the vesicular stores of Ca would promote the formation of intravesicular ACC. SLC4A7 is a sodium bicarbonate cotransporter containing transmembrane domains (https://www. uniprot. org/), which was identified in matrix vesicles released from mineralizing human osteoblast-like cells  (35). Its gene was reported in chicken uterine RNA-Seq (https://anr. fr/Projet-ANR-13-BSV6-0007). We also investigated its expression in the oviduct segments but was not significantly overexpressed in RI and Ut. In this study, we quantified the expression of numerous additional vesicle markers within uterine epithelial cells. Among the 20 vesicular genes highly expressed in RI and Ut, seven encode for proteins ranked in the Top 100 of EV protein markers by Vesiclepedia (Table  S2 ).
Our uterine RNA-Seq analysis reveals elevated expression of several genes of this paracellular pathway (Tjp1, Cldn1, Cldn10, Ocln, Jam2) (https://anr. fr/Projet-ANR-13-BSV6-0007). Moreover, expression of Cldn10 has also been detected in chicken uterus  (108, 109). Although the involvement of the paracellular pathway in eggshell calcification is controversial, it has been incorporated in our comprehensive model of ionic pathways during shell biomineralization (Fig. 8 ). The ionic calcium concentration in uterine fluid ranges from 6 to 10 mmol/l depending of the stage of calcification  (46) , which is higher than blood ionic calcium levels (1-2 mmol/l); consequently the concentration gradient is not in favor of calcium movement towards the uterine fluid  (26). However,  Bar (2009)  suggested that the electrical potential difference could invert this gradient, allowing paracellular transfer of calcium into the uterine fluid  (110).
Gene expression Total RNA was extracted from tissues harvested at 10 h p. o. (except bone, which was extracted at 18 h p. o. ), and treated as previously described  (29). Briefly, the concentration of each RNA sample was measured at 260 nm with NanoDrop™ and their integrity was assessed on 1. 5 % agarose gels. Total RNA samples (1 µg) were reverse-transcribed using RNase H-MMLV reverse transcriptase (Superscript II, Invitrogen, Carlsbad, California) and Oligo (dT)™ primers (Invitrogen, Carlsbad, California). Primers for the Edil3, Mfge8, Ca4, the 31 vesicular genes and the eight housekeeping genes (B2m, Eif3i, Gapdh, Gusb, Stag2, Tbp, Sdha, and Ppia) were designed from Gallus gallus gene sequences (Table  S4 ), using Primer-BLAST on National Center for Biotechnology Information (NCBI), and were synthesized (Eurogentec, Lièges, Belgium).
Primer efficiencies were evaluated by RT-qPCR using LightCycler ® 480 SYBR Green I Master and LightCycler ® 480 instrument II (Roche, Bâle, Switzerland). Gene expression was quantified using the Biomark microfluidic system, in which every sample-gene combination is quantified using a 96. 96 Dynamic Array™ IFCs (BMK-M-96. 96, Fluidigm ® , San Francisco, California) at the GeT-GenoToul platform (Toulouse, France). Samples were pre-amplified according to the manufacturer's specifications. PCR was then performed using the following thermal protocols: Thermal Mix  (  Six biological replicates and two technical replicates were carried out for each tissue. GenNorm software (https://genorm. cmgg. be/) was used for validation of housekeeping gene stability. The normalized quantities were calculated using the following formula: (gene efficiency (ctcalibrator-ctsample) )/geometric average quantity of the eight housekeeping genes.
Normalized quantities were compared between various measured tissues and oviduct segments using one-way ANOVA followed by Tukey pairwise test analysis on Minitab® 18 software (http://www. minitab. com/fr-fr/). A p-value < 0. 05 was selected as the threshold for significance between different groups. The heatmap of the gene expression levels (Row-Z score) in different tissues for Edil3, Mfge8 and the 31 vesicular genes was computed using the heatmap. 2 function from gplots packages of Rstudio software 1. 1. 456 (https://www. rstudio. com/). Row and column clustering were performed using pearsonward. D2 methods and spearman-Ward. D2 methods, respectively. The Ca4 mRNA was amplified by endpoint PCR in each oviduct segment and tissues using DreamTaq PCR Master Mix 2X (ThermoFisher Scientific, Waltham, USA) and Mastercycler gradient (Eppendorf, Hambourg, Germany).
1 software (ThermoFisher Scientific, Bremen, Germany) against the NCBIprot_chordata database (July 2018). The search parameters included trypsin as a protease with two allowed missed cleavages, carbamidomethylcysteine, methionine oxidation and acetylation of protein N-termini as variable modifications. The tolerance of the ions was set to 5 ppm for parent and 0. 8 Da for fragment ion matches. Mascot results obtained from the target and decoy databases searches were subjected to Scaffold software (v 4. 8. 8, Proteome Software, Portland, USA) using the protein cluster analysis option (assemblage of proteins into clusters based on shared peptide evidence). Peptide and protein identifications were accepted if they could be established at greater than 95. 0 % probability as specified by the Peptide Prophet algorithm and by the Protein Prophet algorithm, respectively.
779±0. 251 bc 0. 784±0. 324bc0. 780±0. 422bc1. 701±0. 881a1. 337±0. 500abc1. 294±0. 300abc1. 649±0. 596ab<0. 001 List of the 29 proteins identified by nanoLC-MS/MS analysis in uterine fluid EVs. The EV fraction was purified from uterine fluid (UF) collected at 9 h p. o. Supplementary information on proteomic results are provided in TableS3. Indicated accessions correspond to the GenBank accession number.
(32)(33)(34)(35)(62)(63)(64)(65)67,(69)(70)(71)(72)(73)(74)(75)(76)(77)(78)C-MS/MS analysis (Scaffold software) in uterine fluid EVs. The EV fraction was purified from uterine fluid (UF) collected at 9 h p. o. The entire set of detected proteins is listed in TableS3. Indicated accessions correspond to the GenBank accession number. ACC, amorphous calcium carbonate; EV: extracellular vesicle; HCO3 -, bicarbonate ion. Vesiclepedia database (www. microvesicles. org)classifiesthe proteins that are frequently identified in EVs. EV localization was predicted using molecular function of proteins on Uniprot (https://www. uniprot. org/). References:(32)(33)(34)(35)(62)(63)(64)(65)67,(69)(70)(71)(72)(73)(74)(75)(76)(77)(78).
(24,27,(32)(33)(34)(35)(41)(42)(43)(58)(59)(60)(61)(62)(63)(64)(65)67,(69)(70)(71)(72)(73)(74)(75)(76)(77)(78)(79)(114)(115)(116)(117)(118)(119)(120)ially involved in vesicular transport for eggshell biomineralization. EV: extracellular vesicle, UF: uterine fluid. Vesiclepedia database (www. microvesicles. org/)classifiestheproteins that are frequently identified in EVs. Protein localization in EVs was predicted using molecular function of proteins on Uniprot (https://www. uniprot. org/). References:(24,27,(32)(33)(34)(35)(41)(42)(43)(58)(59)(60)(61)(62)(63)(64)(65)67,(69)(70)(71)(72)(73)(74)(75)(76)(77)(78)(79)(114)(115)(116)(117)(118)(119)(120), *.