dataesr/scientific-paragraphs-categorization huggingface dataset:
ncbi. nlm. NCBI Sequence Read D Bickel, Benjamin Acyrthosiphon wingless males nih. gov/sra/SRR10030337 Archive, SRR10030 J Parker, Omid 337 Saleh Ziabari, Fangzhou Liu, Neetha Nanoth Vel- lichirammal, Jean- Christophe Simon, David L Stern, Jen- nifer A Brisson Binshuang Li, Ryan 2020 Paired end sequencing of pooled https://www. ncbi. nlm. NCBI Sequence Read D Bickel, Benjamin Acyrthosiphon winged males nih. gov/sra/SRR10030338 Archive, SRR10030 J Parker, Omid 338 Saleh Ziabari, Fangzhou Liu, Neetha Nanoth Vel- lichirammal, Jean- Christophe Simon, David L Stern, Jen- nifer A Brisson Binshuang Li, Ryan 2020 Rose aphid genome https://www. ncbi. nlm. NCBI BioProject, D Bickel, Benjamin nih. gov/bioproject/? PRJNA576965 J Parker, Omid term=PRJNA576965 Saleh Ziabari, Fangzhou Liu, Neetha Nanoth Vel- lichirammal, Jean- Christophe Simon, David L Stern, Jen- nifer A Brisson The following previously published dataset was used: Database and Author(s) Year Dataset title Dataset URL Identifier Gouin A, Legeai F, 2015 Whole-genome re-sequencing of https://www.
Control ants were subjected to the same conditions but no pheromone was presented within the larger pot. After the 15-min pre-exposure, each pot with the three ants was removed from the larger one. Ants were then offered a 3-µl drop of 5% w/w sucrose solution at the center of their container. They were video recorded over 3 min using a SONY Handycam HDR-XR260 camera, and videos were analyzed using BORIS software  (Friard and Gamba, 2016). Ants' feeding responses were coded as a binary response (feeding, 1; not feeding, 0). Ants that did not touch the drop of sucrose solution were excluded from analyses (∼14% of the total ants).
The orientation of the arena was also randomly changed between trials to prevent the use of visual or spatial cues. Ants were subjected to three consecutive conditioning trials. Trials were video recorded using a SONY Handycam HDR-XR260 camera, and videos were analyzed with BORIS software  (Friard and Gamba, 2016). From the videos, the latency to find sucrose was measured as the time (s) from the moment at which the ring was removed until the ant found the sucrose solution.
To this end, we used the same arena as during training, but empty plastic discs were placed in front of the two tubes containing either linalool or mineral oil. As for training, a semi-circular zone was drawn around each tube, which allowed recording of the time spent by the ant near the odor or the solvent over 2 min (duration), as well as the number of times the ant entered each zone (occurrence). The orientation of the arena was also randomly changed between the last training trial and the evaluation test to limit the use of visual or spatial cues. Each ant underwent only one evaluation test. Evaluation tests were video recorded using a SONY Handycam HDR-XR260 camera, and videos were analyzed with BORIS software  (Friard and Gamba, 2016). From the videos, we quantified the occurrence as the number of times the ant entered each zone (linalool or mineral oil) and the duration as the time (s) the ant spent in each zone.
Data analysis Ants' feeding responses to the sucrose drop after pre-exposure to the different doses of pheromone (Experiment 1) were examined using a binomial generalized linear mixed model (GLMM; binomial error structure with logit-link function, glmer function, lme4 package;  Bates et al. , 2015). The response variable was 'feeding' (i. e. 1/0) and 'dose' (i. e. 0, 0. 2, 0. 4, 0. 8, 1. 6 and 3. 2 μl) was the predictor. The container of the three-ant group was added as random factor to account for the fact that the experiment was performed in groups, although ants' responses were assessed individually. Post hoc comparisons between treatments and control were performed with the emmeans package (https://github. com/rvlenth/emmeans), and the false discovery rate correction was applied. The ants' sucrose solution acceptance after pre-exposure to the pheromone or not (Experiment 1) was examined using a binomial (logit-link function) additive GLMM (glmer function, lme4 package;  Bates et al.
The response variable was log transformed to meet the criteria of the LMM. For the memory tests (Experiment 2), two response variables were analyzed separately: the time spent close to each tube (duration) over 2 min and the visit frequency (occurrence) of these zones. The GLMM retained to analyze the visit frequency contained 'zone' (i. e. linalool or solvent) as predictor and individuals nested in colonies as random factors, given the dependence of the data. A Poisson family and a log link were chosen, given the data distribution (glmer function, lme4 package;  Bates et al. , 2015). The LMM retained to analyze the time spent in each zone contained 'zone' (i. e. linalool or solvent) as predictor and individuals nested in colonies as random factors (lme function, nlme package). The response variable was log transformed to meet the criteria of the LMM.
Acknowledgements References Acknowledgements We would like to thank the editorial board and the anonymous reviewers for their valuable suggestions. We thank  D. Jubault  for the drawings. We thank  Annie Buchwalter  for editing this manuscript. We thank  D Wipf  and  PE Courty  for their input in the PhD proposal writing. Emma Mortier's PhD thesis was funded by The  French Ministry of Agriculture  and benefited from a collaboration with L Jouve's company.
When using the Carbowax one, it was as follows: the initial oven temperature was held at 70 • C for 2 min, after which it increased to 220 • C at a rate of 5 • C/min and maintained at 220 • C for 8 min. The GC-MS parameters were 250 • C for the injector temperature, 280 • C for the ion source temperature, 70 eV for the electron ionization, 30-300 amu and 2. 77 scan/s for the mass spectra range, 1/100 for the split ratio, and 1 µL pentane solution for the injection volume. The individual components in both essential oils and volatile extracts were identified by comparing their retention indices (RI) (determined thanks to an n-alkanes series) with those existing in the literature  [15] [16] [17] [18]. The comparison of their mass spectra with those present in the mass spectra library of data process softwares (NBS75 K database, Wiley 7th NIST 98 EPA/NIH Mass Spectral Library, Mass finder 3/Hochmuth, and FFNSC2/Mondello, 2nd Edition, November 2011) completed the identification, just as their comparison with those also existing in published data.
Yield and Chemical Composition of Essential Oils of Cumin Seeds Data on lipids and essential oils from Lebanon, France, Algeria and Syria have not yet been undertaken. Thus, in the present study, the analysis of these varieties was conducted in order to enhance their valuation as new sources of vegetable and essential oils. Differences in essential oil yield were observed between the seeds of the four origins (Table  1 ). The examination of cumin seeds from different geographical areas has been the subject of several previous studies. Comparative yields were obtained for Indian (1. 2-1. 9%) [29, 30]  and Egyptian (2. 5%) cumin seeds  [31]. Lower yields were found for Iranian (1. 5%) and Tunisian (1. 2%) cumin  [32]. In contrast, cumin seeds from China gave a higher yield (3. 8%)  [33]. Cumin growing in agro-ecological sub regions (India) exhibited essential oil yield ranging from 2.
palmivora root See also Figures  S1  and S2. infection as measured by pathogen biomass, respectively (Figures S2A-S2I). To obtain independent evidence for the role of API in P. palmivora infection, we used a hairpin RNAi construct targeting the 3 0 UTR of MtrunA17_Chr4g0004861 (hpAPI) to attenuate API transcript levels in wild-type roots. Roots expressing the hpAPI construct displayed the shorter root hair phenotype (Figures  S2J  and S2K ), in contrast to control roots expressing a construct targeting the non-existent uidA gene (hpuidA). We further confirmed that hpAPI-expressing transgenic roots infected with P. palmivora showed a significant reduction in API transcripts concomitantly with a reduction of P. palmivora biomass markers (Figure  S2L ). Taken together, the data demonstrate that the SCAR2 protein API is required for efficient colonization of M.
ACKNOWLEDGMENTS We are indebted to Paul Knox (Leeds) for provision of cell wall antibodies and to Jean-Marie Prosp eri (INRA, Montpellier) and Fang Xie (SIBS, Shanghai) for providing seeds and plasmids, Magdalena Bezanilla (Dartmouth College) for the script for analysis of actin dynamics, and Rene Geurts (Wageningen University) for providing a fluorescently labeled strain of S. meliloti. We would like to thank Philip Carella for critical reading; Diego H. Sanchez for helpful discussions; and Annika Luebbe, Heena Yadav, and Bettina Hause for their technical support and scientific discussions. This work was funded by the Gatsby Charitable Foundation (GAT3395/GLD), by the European Research Council (ERC-2014-STG, H2020, and 637537), and by the Royal Society (UF110073 and UF160413).
To identify the api mutation we sequenced the api mutant (accession SRR8468999, Bioproject: PRJNA516327) and in parallel employed a comparative genome sequencing strategy. API and api plant genomic DNA was extracted using DNeasy Plant Mini Kit (QIAGEN). The libraries for whole genome sequencing were prepared with TruSeq DNA LT Sample Prep Kit (Illumina) and subjected to 100 bp paired-end sequencing by Illumina Hi-seq2500. Raw data can be found on http://www. ddbj. nig. ac. jp/ using accession DRA003037. The sequence reads in which more than 10% of sequenced nucleotides had a phred quality score of less than 30 were excluded from the subsequent analysis. For detecting SNPs of api, we first constructed a ''reference sequence'' of API by replacing the nucleotides of the publicly available A17 M.
truncatula reference genome (ftp://ftp. jcvi. org/pub/data/m_truncatula/Mt4. 0/Assembly/JCVI. Medtr. v4. 20130313. fasta) with those of API as described previously  [58]. A total of 122,523 SNP positions were substituted. The sequence reads from api were aligned to the developed API reference sequence using BWA software  [59]. Alignment files were subjected to filtering using Coval software  [60]  and calculating the SNP-index for all SNP positions using the MutMap pipeline  [61]. Finally the SNP positions having a sequence depth > 5 and showing an SNP-index > 0. 9 were extracted as homozygous SNPs of api. Presence of the api causal mutation was confirmed via Sanger sequencing service at Source Bioscience (http://www. sourcebioscience. com/).
The same settings were used to screen for transgenic hairy roots of M. truncatula expressing monomeric DsRED. Light microscopy imaging and infection scoring were performed using Zeiss Axioimager M2 microscope with a 64 MP color camera. Pictures were processed with ImageJ software v1. 46 including Fiji plugins and AxioVision Microscopy Software (Zeiss). Promoter GUS assay Medicago transgenic roots were collected and washed twice in 0. 1 M sodium phosphate buffer, pH 7. 2, incubated in GUS buffer (100 mM sodium phosphate pH 7. 0, 5 mM K 3 Fe(CN) 6 , 5 mM K 4 Fe(CN) 6 and 2 mM 5-bromo-4-chloro-3-indoxyl-b-d-glucuronic acid, X-gluc) under vacuum at room temperature for 30 min to allow the buffer to replace air in the tissue, incubated at 37 C for 2-6 h to enable the enzymatic reaction, and analyzed using the Microscope Leica M165 FC and Zeiss Axioimager M2 microscope.
Correlation coefficient was calculated using the built-in MATLAB function corr2  [55]  and differences per pixel were calculated using Actin_difference_maps (https://github. com/SchornacklabSLCU/Actin_difference_maps). For quantification of actin filament bundling and occupancy, cells were imaged using 1024 3 1024 pixel resolution. A maximum intensity projection of 15-20 image stacks was subjected for image processing and analysis performed as described by Higaki et al. [64]. The serial optical sections of the root cell images were skeletonized using the 'Analyze Skeleton (2D/3D)' plugin in Fiji  [56, 65]  and projected. Actin bundling was estimated as the skewness of the intensity distribution of the actin filament pixels. Filament occupancy was defined as ratio of the total pixel numbers of actin filaments and cell area using Actin_skewness-and-occupancy (https:// github.
Endomembrane dynamics analysis Medicago hairy roots expressing SPPR1-GFP reporter  [43]  were treated with 50 mM brefeldin A (BFA). The GFP fluorescence signal intensity and distribution were analyzed after 1-2h of treatment. For image processing and analysis, the software ImageJ was used. To obtain intensity information for each BFA compartment per cell, a picture of the GFP channel was duplicated and thresholded to highlight all structures of interest. Once the areas are highlighted a binary version of the image was created. Subsequent steps involved setting the ''Redirect to'' line to the name of the image of GFP channel and selecting the checkboxes ''Mean grey value'' and ''Area. '' The ''Analyze Particles'' tool then obtained mean pixel intensities and area for the BFA compartments on the original image, based on outlines applied from the binary image.
Microarray Affymetrix Medicago Gene Chip hybridizations were carried out in biological triplicates at IMGM (Germany). M. truncatula total RNAs were extracted as described previously and quality assessed using NanoDrop ND-1000 spectral photometer and a 2100 Bioanalyzer (Agilent Technologies). Total RNA was processed according to manufacturer recommendations using the 3 0 IVT Expression Kit (Affymetrix Inc. ). After hybridization, microarrays signal intensities were detected with the Affymetrix GeneChipÒ 3000 Scanner and AGCC Scan Control Software v3. 2. 3. 1515 (Affymetrix). Automatic grid was arranged and raw data (*. DAT files) were processed to generate image and intensity files (*:CEL, *. JPG) by the AGCC Scan Control Software. The software tool GeneSpring GX 12. 6. 1 (Agilent Technologies) was used for visualization and normalization (using the RMA algorithm).
After normalization, data is returned as log2 transformed values. Significant differential expression level between API and api plants was assessed for each individual probe using a Student's t test and a Bonferroni correction in R (3. 0. 2, ww. r-project. org). The Affymetrix probeset was annotated according to Czaja et al. [70]  while MAPMAN BINs were used to classify probes in biological processes (http://mapman. gabipd. org/ web/guest) and the probes were mapped to version V4. 0 of the Medicago gene models (http://jcvi. org/medicago/) Raw data (. CEL files) can be found on the Gene Expression Omnibus (http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE65903).
DATA AND CODE AVAILABILITY Microarray data can be found on the Gene Expression Omnibus: GSE65903. Sequencing data can be found on the Bioinformation and DDBJ Center: DRA003037, The Sequence Read Archive: SRR8468999, and Bioproject: PRJNA516327. The Actin_difference_maps script is available on https://github. com/SchornacklabSLCU/Actin_difference_maps. The Actin_skewness-and-occupancy script is available on https://github. com/SchornacklabSLCU/Actin_skewness-and-occupancy.
T. R. was funded by the European Research Council (FP7-PEOPLE-2013-IEF, FP7, and 624398). S. B. was funded by the University of California, Los Angeles (403976-SB-69313), Gatsby Charitable Foundation (GAT3396/PR4), and Biotechnology and Biological Sciences Research Council (BB. L002884. 1). J. L. K. was funded by the George and Lillian Schiff Foundation. D. R. , E. -P. J. , F. D. , and F. d. C. -N. were funded by TULIP (no. ANR-10-LABX-41). V. C. is a recipient of a Thailand Research Fund grant.
ncbi. nlm. nih. gov/geo/ GSE65903 query/acc. cgi?acc=GSE65903 Sequencing data http://www. ddbj. nig. ac. jp DRA003037 Sequencing data https://www. ncbi. nlm. nih. gov/sra SRR8468999 Sequencing data Bioproject PRJNA516327 Experimental Models: Organisms/Strains Medicago truncatula Jemalong A17 Lab stocks N/A M. truncatula Jemalong A17 api EMS mutant line [37] N/A Lotus japonicus Gifu B-129 [16] N/A L. japonicus scarn-1 EMS mutant line [16] N/A Phytophthora palmivora AJ-td Lab stocks N/A Phytophthora palmivora LILI-td Lab stocks N/A Phytophthora palmivora LILI-YKDel Lab stocks N/A Oligonucleotides Primers for plasmid construction see Table S1 Eurofins N/A Recombinant DNA pUB-GW-GFP-pUb:SCARN [16] N/A pUB-GW-GFP-pEp:SCARN [16] N/A pUC57-API GENEWIZ N/A pENTR:pAPI This paper N/A (Continued on next page).
The cylinder was placed on a representative spot of the plot with a plant at the centre. Each cylinder was then emptied, and roots were manually separated from the soil. The roots were washed gently with running water to remove the soil from the cylinders. All roots found in each soil cylinder were weighted and scanned in a film of water (Epson Perfection V850 Pro) with a resolution of 600 dpi. The software WinRhizo 2016 (Regent Instrument Inc. , Instruments, Québec city, QC, Canada) was used to measure the total root length. Roots were then dried at 105 °C for 24 h and weighed to obtain the DMC and the SRL. The dry weight and length were then divided by the total volume of the soil cylinder to obtain the RLD and RMD.
The cylinder was placed on a representative spot of the plot with a plant at the centre. Each cylinder was then emptied, and roots were manually separated from the soil. The roots were washed gently with running water to remove the soil from the cylinders. All roots found in each soil cylinder were weighted and scanned in a film of water (Epson Perfection V850 Pro) with a resolution of 600 dpi. The software WinRhizo 2016 (Regent Instrument Inc. , Instruments, Québec city, QC, Canada) was used to measure the total root length. Roots were then dried at 105 • C for 24 h and weighed to obtain the DMC and the SRL. The dry weight and length were then divided by the total volume of the soil cylinder to obtain the RLD and RMD. For each species, determination of C/N was carried out on subsamples of roots that were representative of the whole root system and reserved for chemical analyses (Table  S1 ).
Acknowledgments: We gratefully thank the technical support during the experiment of  Vincent Hervé ,  Nicolas Honvault ,  Benoit Detot ,  Léo Simon ,  Julia Denier  and  Cécile Nobile. This work has been supported by the  Chair in Agricultural Machinery and New Technologies , backed by the  Institut Polytechnique UniLaSalle  with financial support from the  Michelin Corporate Foundation, AGCO Massey-Ferguson, Kuhn , the  Hauts-de-France Regional Council  and the  European Regional Development Fund (ERDF).
It has even been suggested that one class of transcription factors, the MYBs, may be preferred targets of pollination syndrome evolution, analogous to the predominance of MADS box transcription factors in specifying floral whorl identity  (Yuan et al. , 2013). Figure  1. Workflow for the identification of candidate speciation genes in Petunia species with differences in reproductive organ morphology. (a) P. axillaris, P. parodii, and P. exserta with corolla partly removed to show the reproductive organs. (b) The initial dataset is filtered stepwise based on expression in styles and correlation with the growth traits of interest. The reduced dataset is then analyzed for differential and allele-specific expression (ASE) as well as coding sequence differences between the studied species. The numbers in the brackets represent the number of genes remaining after each step.
Petunia floral organs of different species have different growth-associated trait profiles To understand how Petunia floral reproductive organs attain different final lengths, measurements of the growing buds were taken from less than 1 cm long until 1-2 days after flower opening. As flower opening is a reliable and easily measurable time point, all data were expressed as hours until opening. The length of the buds at the time of opening is significantly different between the three species (Figure  2a ). The growth curves of the buds of all species show a characteristic sigmoidal type growth: with initial slow growth followed by fast elongation and then slowing again around the time of opening (Figure  2b ). As the pistil develops inside the bud, we dissected buds at different stages of growth and determined the relationship between bud length and pistil length (Figure  2c ).
The clusters of the MS2 and LS samples are not homogenous and cluster together. We also observed that the transcriptome of the S stage stands apart from the other stages consistent with what was observed for growth rate, cell number, and cell division rate. The genes were filtered to remove pollen genes that contaminated the late-stage style samples (see Experimental procedures for details). Genes showing no or very low expression were removed using the R package HTSfilter  (Rau et al. , 2013). From 2284 putative Petunia transcription factors initially identified, 1411 were expressed in styles according to these criteria. 2) Correlation of transcript levels with growth-associated traits. Our analysis showed that Petunia styles grow by a mixture of cell division in early stages and cell elongation in the later stages.
However, whole genome sequences were available only for P. axillaris and P. exserta. Therefore, we assembled a de novo draft genome for P. parodii using high-coverage short-read sequencing (Table  2 ). In total, we found six genes with amino acid variation of potential functional significance using homologous sequences between Petunia species (Table  3 ). This brings the total dataset of candidate speciation genes to 43 (Tables  1, S2 , and  S3 ).
Interestingly, MYB transcription factors were overrepresented with 14 genes out of 43 belonging to this family, which is highly unlikely by chance (Table  S4 ). An additional point of interest is that three of these MYBs are known regulators of the phenylpropanoid pathway in Petunia: scent-related factors ODO1, EOBI, and PhMYB4  (Colquhoun et al. , 2011a) ;  (Van Moerkercke et al. , 2011) ;  (Spitzer-Rimon et al. , 2012). Moreover, all three genes show a strong positive correlation with style length and a negative correlation with cell wall elasticity. Such a correlation is seen in nine out of the 14 MYB genes. We also noticed Petunia genes similar to Arabidopsis genes known to affect plant organ morphology, such as ARF2, SHR, and BPE in the final dataset (Tables  1  and S2 ).
These data support a view where final style length is a product of early cell division and later cell wall stiffening to trigger growth arrest. The genes that regulate these processes are potential causative agents for the interspecific differences in style morphology. Prominently absent from our dataset is the homolog of LO2 (PRE1 in Arabidopsis), an HLH-encoding gene previously shown to be responsible for the style length reduction that occurred during tomato domestication  (Chen et al. , 2007). However, we identified a candidate HLH protein, BIGPETAL (BPE), known to regulate Arabidopsis petal size through its effect on cell expansion  (Sz ecsi et al. , 2006). For functional validation, we performed VIGS on six candidate genes. Four of them, including BPE, showed no differences. In contrast, inactivation of EOBI and EOBII had a significant effect on style length, which makes these genes prime candidates for further functional analyses, such as stable overexpression and CRISPR/CAS9.