dataesr/scientific-paragraphs-categorization huggingface dataset:
The schematic representation of the mean clusters profiles is plotted at the right of the heatmap. (D) Enrichment in insulin-sensitive genes as determined byBatista et al. (2019b). The size of the circles is relative to the percentage of all identified insulin-sensitive genes within a cluster and the color to the p value of the hypergeometric test. (E) Enrichment of transcription factors based on the TRRUST database (Han et al. , 2018)  and over Gene Ontology (GO) Biological Process (Pages et al. , 2021)  are presented for clusters showing a significant enrichment in insulin-sensitive genes in (D). TRRUST enrichment over the whole transcriptome, and GO enrichment is performed over insulin-sensitive genes highlighted in (D) only. The gradient color of the characters strings is relative to the p value of the enrichment.
ACKNOWLEDGMENTS We thank all members of the  EZOP  staff for their help. We thank the staff from  Genotoul  ( Anexplo, GeT-TRiX, Metatoul ) and from  WeMet  ( INSERM I2MC ) facilities for their help. We thank  Dr. M. Hancock  and  Prof. J. Flanagan  ( Harvard Medical School, Boston, MA, USA ) for providing us with the list of genes with IR-bound promoters. We thank  Dr. T. Batista  and  Prof. C. R. Kahn  ( Harvard Medical School, Boston, MA, USA ) for providing us with the list of insulin-sensitive hepatic genes. We thank  Dr. B. Weger  ( EPFL Lausane, Switzerland ) for his help with the use of the dryR package. T. F. was supported by a PhD grant from  Toulouse University  and by  INRAE and Institut National du Cancer (INCA). A. F. was supported by an Agreenskills post-doctoral fellowship.
B. T. was supported by  FRM  ( FDM201906008682 ). A. B. was supported by  ISITE-BFC  (contract  ANR-15-IDEX-0003 ). T. F. , B. T. , P. G. , C. P. , A. M. , and H. G. were supported by grants from '' SocieteFrancophone du Diabete. ''P. G. , N. L. , A. M. , and H. G. were supported by grants from  Region Occitanie. P. G. , H. D. , N. L. , C. P. , A. M. , and H. G. were supported by a  Hepatomorphic grant  from  ANR.
(C) Heatmap based on expression level of 11,159 differentially expressed genes (n = 6 mice per group, individual values are represented). The schematic representation of the mean clusters profiles is plotted at the right of the heatmap. (D) Enrichment in insulin-sensitive genes as determined byBatista et al. (2019b). The size of the circles is relative to the percentage of all identified insulin-sensitive genes within a cluster and the color to the p value of the hypergeometric test. (E) Enrichment of transcription factors based on the TRRUST database (Han et al. , 2018)  and over Gene Ontology (GO) Biological Process (Pages et al. , 2021)  are presented for clusters showing a significant enrichment in insulin-sensitive genes in (D). TRRUST enrichment over the whole transcriptome, and GO enrichment is performed over insulin-sensitive genes highlighted in (D) only.
Specifically, the conformational propeller-like chirality of cpb could perhaps be transmitted, and even changed, through intraframework π-π interactions and via the coordination sphere. The cpb linker is one of few flat hexagon-shaped building blocks used in MOF chemistry and probably the only commonly used MOF linker displaying conformational chirality, and potential linker-linker chiral recognition. The one-benzene-ring extended version of cpb, hexakis(4-(4carboxyl-phenyl)phenyl)benzene, was found in five structures in the Cambridge Crystallographic Database, CSD. 15  (CEF-NIN,  16  FAKKEK,  17  FAKKIO,  17  IXETEM,  18  and UFO-QOY  19  ). For the hexakis(phenyl)benzene core, 10% of structures in the Cambridge Structural Database (CSD) appear to crystallize with one enantiomer only,  20  corroborating the chiral recognition idea.
43. 1. 4. Single-Crystal X-ray Diffraction. Data were collected using Cu Kα radiation (λ = 1. 54184 Å) on a Rigaku XtaLAB Synergy-DW diffractometer equipped with a HyPix-Arc 150°detector and on a Synergy-R, diffractometer equipped with a HyPix-Arc 150°detector. Diffraction data were acquired and processed with CrysAlisPro software package. 44, 45  Direct or structure expansion methods were used for all structures, and the refinements were established by fullmatrix least squares with SHELX-2018/3 46 using X-seed  47  and Olex2 48 software as a graphical interface. Details of structure refinements are found in the Supporting Information. 4. 1. 5. Powder X-ray Diffraction. Powde  X-ray diffraction patterns were recorded using a Bruker D8 Twin diffractometer (Billerica, Massachusetts) with Cu Kα radiation λ = 1.
54 Å at room temperature scanning between 2θ = 0 and 50°. Variable-temperature powder X-ray diffraction data were collected using a Panalytical X'Pert Pro diffractometer (Cu Kα 1,2 , λ 1 = 1. 540598 Å, λ 2 = 1. 544426 Å) using a Bragg-Brentano geometry, equipped with an Anton Paar XRK 900 high-temperature chamber. 4. 1. 6. Other Tools. Elemental analysis was performed by Mikroanalytisches Labor Kolbe, c/o Fraunhofer Institut, Oberhausen, Germany. For TGA measurements, we used a Mettler Toledo TGDS/ DSC 3+ Star system. CrystalMaker was used for all structure drawings and porosity and cavity calculations. For the two latter calculations, van der Waals radii were used. CrystalMaker calculates empty volumes as the residual volume after atomic volumes have been subtracted from the total volume.
For the size of cavities, CrystalMaker scans through the structure, aiming to find the largest sphere that can fit into any cavity using multiple iterations. 49 Systre was used for topology analysis. 50 We also used Mercury to calculate voids using Contact Surface giving the volume that can be occupied by a probe of a given radius, in this case 1. 6 Å corresponding to the kinetic diameter of CO 2. The Cambridge Crystallographic Database 5. 42 was used for the data in Table  S2  and Figure  S3. 15  2 and CO 2 adsorption isotherms were recorded on a Micromeritics ASAP2020 surface area analyzer at liquid N 2 temperature (-196 °C). The samples were pretreated up to 275 °C under dynamic vacuum (1 × 10 -4 Pa) for 6 h before the analysis. The relative pressure range of 0. 05-0. 15 was used to estimate the Langmuir and Brunauer-Emmett-Teller (BET) surface area of the samples.
Additionally, CO 2 and N 2 adsorption isotherms were recorded at 0, 10, and 20 °C (with a temperature-controlled water bath) using the same instrument. Density functional theory (DFT) calculations were performed with the CRYSTAL17 code. 51 The basis sets used were taken from the online CRYSTAL basis sets library (https://www. crystal. unito. it/ basis-sets. php): all-electron Gaussian basis sets of double-ζ valence with polarization for O, C, and H;  52  an effective core potential was used for La. 53 The exchange-correlation functional chosen was the PBE functional  54  and a Grimme "D3" dispersion correction. 55 epresentative input files for the calculations are available online at https://github. com/fxcoudert/citable-data ■ ASSOCIATED CONTENT * sı Supporting Information The Supporting Information is available free of charge at https://pubs.
acs. org/doi/10. 1021/jacs. 2c02351. General procedure, SCXRD crystallographic information of the MOFs, crystallographic information for the 3D ED data, thermal analysis, PXRD Chemical stability studies, and network topology (PDF) Accession Codes CCDC 2155881-2155884 and 2155886 contain the supplementary crystallographic data for this paper. These data can be obtained free of charge via www. ccdc. cam. ac. uk/data_request/ cif, or by emailing data_request@ccdc. cam. ac. uk, or by contacting The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK; fax: +44 1223 336033.
BUSCO analysis  [21]  was used to assess the assembly in "genome" mode showing 98. 3% complete single and duplicated Embryophyta core gene sets from the embryophyta_odb10 database (Table  2 , Supplementary Table  S3a ): of the 1,614 genes tested for, 1,526 are complete and singlecopy BUSCOs (S), 61 are complete and duplicated BUSCOs (D), 12 are fragmented BUSCOs (F), 15 are missing BUSCOs (M). Few genes were fragmented or missing. E. glaucum chromosome designations were chosen to follow major regions of synteny with M. acuminata chromosomes  [16, 17].
Genome size, heterozygosity, and organization The contig-level assembly size is 495,175,598 bp, and 97. 2% of these contigs are anchored to 9 pseudo-chromosomes after Hi-C scaffolding, resulting in a 481,507,213-bp final chromosomelevel genome assembly. Some arrays of tandem repeats, including the ribosomal DNA (rDNA) (see below) and telomeres, were collapsed and chromosome termini were not fully assembled. Approximately 55% of the assembled genome was estimated to be repeat sequences (RepeatMasker; Table  2 ). The genome size was estimated as 563,295,571 bp (highest 17-mer peak frequency). Presumably because of sensitivity of parameters to the evolutionary whole-genome duplications (WGDs) (Fig. 1 , centre) and more recent duplications, slightly higher estimates were made by findGSE software (k = 21: 588,939,614 bp; range from k = 17 to 25, 582-591 Mb), and lower estimates by GenomeScope (468,990,370 bp for k = 21; or 407,601,233 bp for k = 17, Supplementary Fig.
Tandem (satellite) repeats and centromeric sequences The repeat analysis revealed the presence of an abundant tandemly repeated sequence with a monomer length of ∼134 bp (Fig. 5A ). The sequence, named Egcen (Ensete glaucum centromere), represents ∼1. 3% of the E. glaucum genome (45,000 copies) (Table 2, Supplementary Table  S12 ; GenBank: OL310717) and forms arrays that are at places interspersed by the long interspersed nucleotide element (LINE) Nanica (described in M. acuminata  [14] ) and other sequences (Fig. 5B , see below). There were 1 or 2 major arrays of Egcen repeats found in the assemblies of all 9 chromosomes (Fig. 5C ). In situ hybridization of Egcen showed that it was located around the primary, centromeric, constrictions as seen by DAPI (4´,6-diamidino-2-phenylindole) staining (Fig.
5S and 45S rDNA and rRNA genes Tandem repeats of the rDNA were predominantly located within extended, complex loci on chromosomes eg05 (5S rDNA) and eg06 (45S rDNA) (Figs 2, 5C, 7, and 8). The 45S rDNA monomer containing the 18S rRNA gene -ITS1 -5. 8S rRNA gene -ITS2 -26S rRNA gene -NTS (GenBank: OL310719) was 9,984 bp long, typical but slightly longer than other plant species  [50] [51] [52]. The NTS region includes in most cases 16 copies of a degenerate 180-bp tandem repeat. On the basis of occurrence in the unassembled Illumina reads, there were 587 copies of the 45S rDNA monomer (1. 21% of the genome, Table  2  and Supplementary Table  S12 ). Although in the whole genome assembly the rDNA array was collapsed, the strength of the in situ hybridization signal using the rDNA sequence from wheat (Fig.
7A  and B ) is consistent with representing 1% of the genome. The long chromosome arm carrying the 45S NOR locus was depleted in protein-coding genes by 10-fold (mean of 12. 6 genes/Mb compared with 127. 6/Mb on the short arm; Fig. 7D ). The single site of 45S rDNA at the NOR per chromosome set is similar to M. acuminata and other Musa species [53], although not Ensete gilletii (2n = 18), where there are 4 pairs of sites  [23]. The 5S rDNA (GenBank: OL310718) comprised the 5S rRNA gene (119 bp long, typical for all plants; e. g. ,  [51] ) and intergenic spacer (937 bp), representing 0. 078% of the genome or ∼366 copies, with a complete motif length of 1,056 bp (Supplementary Table  S12 ). The 5S rDNA locus lies in the middle of the short arm of chromosome eg05, in 3 parts ∼34. 5M, ∼37. 5M, and ∼45.
The 5S rDNA monomer length of 1,056 bp was exceptionally long in comparison to any other plant species (typically 400-500 bp long). The first 400 bp of the intergenic spacer had no significant BLAST hits in GenBank, while the second part showed only short regions with weak homology largely to chromosome assemblies of Musa species in GenBank. There were no motifs characteristic of retroelements in the 937-bp intergenic spacer. It is unclear why the monomer length for the 5S rDNA in E. glaucum should be twice that typical in other species, including Musa, and was to be relatively homogeneous over all copies (Fig. 7E ). Furthermore, in contrast to the single locus on eg04 of E. glaucum, all species of Musa examined so far have multiple 5S rDNA sites (2, 3, or 4 per genome), and E. gilletii had 3 pairs of sites  [23, 53].
Sample collection and distribution The individual Ensete glaucum plant used for genome sequencing and analysis was collected from Puer city, Yunnan province, China and maintained in the South China Botanical Garden, Guangdong province, China (accession No. 19990288; Fig. 1A-E ). The distributions of Ensete and Musa species were identified in databases of Flora of China, South China Botanical Garden, iNaturalist, GBIF  [61]  (excluding cultivation sites), and regional distribution maps. Figure  1F  was then made from POWO  [62]  (overlaid and colouradjusted in Adobe Photoshop CC2018).
Valid interaction paired-end reads were identified by HiC-Pro v2. 8. 1 (HiC-Pro, RRID:SCR_017643)  [75]  and retained for further analysis while invalid read pairs, including dangling-end, self-cycle, re-ligation, and dumped products were discarded. The scaffolds were further clustered, ordered, and oriented onto pseudo-chromosomes by LACHESIS (LACH-ESIS, RRID:SCR_017644)  [76] , with parameters as follows: "CLUS-TER_MIN_RE_SITES = 100, CLUSTER_MAX_LINK_DENSITY = 2. 5, CLUSTER NONINFORMATIVE RATIO = 1. 4, ORDER MIN N RES IN TRUNK = 60, ORDER MIN N RES IN SHREDS = 60". Finally, regions with obvious discrete chromatin interaction were detected and their placements and orientations were manually adjusted (Supplementary Fig. S12 ). Validation of the assembly was performed using BUSCO v5 (BUSCO, RRID:SCR_015008)  [21]  to assess the completeness and presence of 1,614 genes in the embryophyta_odb10 database in "genome" mode (Supplementary Table  S3a ).
31. 10 (MAKER, RRID:SCR_005309)  [86]  as model, and the RNA alignment of E. glaucum and proteins from M. acuminata v2 were used as Expressed Sequence Tag (EST) and protein evidence, respectively. We also used GeMoMa v2. 3 (GeMoMa, RRID:SCR_017646)  [87]  to perform homology-based gene prediction using M. acuminata v2  [16]  as reference annotated genome. Evidence-Modeler (EvidenceModeler, RRID:SCR_014659)  [88]  was used to combine de novo and homology-based predictions and our transcriptome evidence to produce the final structural gene annotation. To annotate the function of predicted genes, we performed BLASTP (e-value = 1e-10) (BLASTP, RRID:SCR_001010) from the BLAST+ package  [89]  for each predicted coding sequence against the databases: UniProtKB/Swiss-Prot, UniProtKB/TrEMBL  [90] , and NR (non-redundant protein database at NCBI).
These sequences are then processed to produce a non-identical (often referred to as pseudo non-redundant) prediction. To assign a putative function to a polypeptide we kept only the best hit on the basis of 3 parameters: (i) Qcov (Query coverage = length high-scoring segment pair [HSP]/length query), (ii) Scov (Subject coverage = length HSP/length subject), and (iii) identity. Additional functional information was added by scanning sequences with In-terProScan v5. 46 (InterProScan, RRID:SCR_005829)  [91]. Blast2GO v6. 0. 1 (Blast2GO, RRID:SCR_005828)  [92]  was used to integrate the results of BLAST and InterProScan, and to link the GO (Gene Ontology) terms to genes accordingly (Supplementary Table  S4 ). The functional annotation procedure is given in greater detail at  [93]. BUSCO was run in mode "transcriptome" using the em-bryophyta_odb10 database to assess the gene annotation results and found 1,529 (94.
Gene family expansion and contraction To identify gene family expansion and contraction, we expanded previous analyses with OrthoFinder by adding a representative of Musaceae sister clades in Palms (P. dactylifera, date palm  [98] ) and Poales (O. sativa v7, rice  [99] ; data downloaded from Phytozome  [100] ) but omitting E. ventricosum owing to gene redundancy. The longest transcripts were kept if alternative splicing occurred. Divergence time estimation with approximate likelihood calculation used MCMCTREE in PAML v4. 9j (PAML, RRID:SCR_014932). CAFE (CAFE v4. 2. 1, RRID:SCR_018924)  [101]  was used to model the evolution of gene family sizes and stochastic birth and death processes and summarized in the phylogenetic tree (Fig. 3C ).
Transcription factors Protein-coding gene sequences for E. glaucum and M. acuminata v2 were searched in PlantTFDB v5. 0 (PLANTTFDB, RRID:SCR_003362) and iTAK online v1. 6  [102]. Predicted TFs were verified through a hidden Markov model (HMM) with PFAM searching tools using the cut-off E-value of 0. 01 (Fig. 3D  and Supplementary Table  S9 ). Genes were verified by PFAM (Pfam, RRID:SCR_004726), CDD (Conserved Domain Database, RRID:SCR_002077), and SMART (SMART, RRID:SCR_005026) databases.
Repetitive DNA identification and annotation For repetitive DNA analysis, publicly available programs (see below and  [38] ) as well as manual searches and sequence comparisons were applied. Geneious v. 10. 2. 6 (Geneious, RRID:SCR_010519) (Biomatters Ltd. , Auckland, New Zealand) was used to produce the dotp lots of Figs  5A, B, 7E,  and 8B , and Supplementary Fig. S9 ). In the assembly, repeated sequences were first searched with REPET v2. 5 pipeline  [107]. The top 100 repeated sequences were plotted on the 4 reference Musa genome assemblies (i. e. , M. acuminata, M. balbisiana, M. schizocarpa, and E. glaucum) using Blas-tAndDrawDensity. py script described in  [17]  and available on the GitHub repository  [108].
Transposable elements TEs were annotated by EDTA pipeline  [109] , which integrates various software to discover TEs including LTR retrotransposons  [110] [111] [112] , terminal inverted repeat (TIR) transposons  [113] , short TIR transposons or miniature inverted transposable elements (MITEs)  [114] , and Helitrons  [115]. According to suggestions in  [109] , we also adopt RepeatModeler2 (RepeatModeler, RRID:SCR_015027) v2. 0. 1  [116]  to find remaining TEs. We also discovered repetitive elements through the REPET v2. 2  [117]  package including TEdenovo and TEannot. The TEdenovo procedure was used on masked assembly to produce a batch of 4,229 TE consensus sequences. From these 2,800 consensus sequences, only those with full-length fragments present in the assembly were kept for further analysis, quantification, and annotation with the TEannot procedure.
A first annotation was performed using public Repbase (Repbase, RRID:SCR_021169) release 20. 05, followed by Gypsy/Copia retroelement family identification using HMMs (hmmsearch version 3) to search consensus for corresponding retro-transposase PFAM domains PF04195 and PF14244, respectively. The above results were then combined and CD-HIT v4. 1. 8 (CD-HIT, RRID:SCR_007105)  [118]  was used to reduce redundancy. The LTR retrotransposons were sent to TEsorter  [119]  to classify into lineage level and RT domain amino acid sequences were extracted. Phylogenetic trees of Copia and Gypsy were inferred by RT domain alignment results (Supplementary Fig. S4 ). The proportions of TEs in the assembly are given in Table  2  (Supplementary Tables  S11  and S12 ) and chromosomal distributions in Fig. 2.
To estimate ages of LTR retrotransposons and the time of insertion (Fig. 4B  and C  and Supplementary Fig. S5 ), complete elements were found by LTRharvest v1. 6. 1 (LTRharvest, RRID:SCR_018970)  [110]  and LTR_retriever (LTR_retriever, RRID:SCR_017623)  [111]  and then classified by TEsorter v1. 3. The estimation of time was based on the divergence of the 5 -and 3 -end LTRs, and these 2 LTRs of every LTR retrotransposon were extracted into separate files with a custom script. The 5 and 3 LTRs were aligned by MUSCLE v3. 8. 1551  [120]. The divergence distances under K2P evolutionary model were calculated by R package ape v5. 4-1 (ape, RRID:SCR_017343). The average base substitution rate was selected to be 11. 3E-8  [121]. The insertion time T was calculated as T = K/(2r), with r as the rate of nucleotide substitution and K as the divergence distance between LTR pairs.
Graph-based clustering of reads using RepeatExplorer A sample of 2 Gb of the Illumina HiSeq raw reads were used for assembly-free analysis by RepeatExplorer2  [39]. Graph-based clusters of similar sequence fragments were generated under default parameters. Clusters were assigned to repeat classes and retroelement lineages using the automated Repeat Masker and Domain hits provided by the program (Supplementary Table  S11 ). Comparative analysis with sample Illumina sequence reads from 5 other Musaceae species, namely, M. acuminata v2  [16] , M. balbisiana v1. 1  [15] , and M. schizocarpa v1  [13] , E. ventricosum  [20] , and Downloaded from https://academic. oup. com/gigascience/article/doi/10. 1093/gigascience/giac027/6576245 by guest on 09 May 2022 M. lasiocarpa (Wang, Cui, Rouard, Schwarzacher, Heslop-Harrison, Liu in preparation)) were also analysed (Supplementary Fig.
Acknowledgments This work was technically supported by the high-performance cluster of the  UMR AGAP -CIRAD  of the  South Green Bioinformatics Platform  (http://www. southgreen. fr). Assistance and discussion with  Celia Hansen  and  Paulina Tomaszewska ,  University of Leicester , are acknowledged. We thank  Ye Yushi  for the assistance with growing and maintaining the plants. We thank the  International Musa Germplasm Transit Centre  (https://www. bioversityinternational. org/banana-genebank/)for samples of M. balbisiana.
Data Availability All supporting data can be found in the GigaScience database  [127]. Raw sequence reads (RNA-seq, Illumina HiSeq, ONT, and Hi-C) were deposited in NCBI under accession No. PRJNA736572. Specifically, ONT raw reads: SRX11350424 and SRX11350425; RNA-seq raw reads, as follows: leaf: SRX11350426; root: SRX11350427; genomic Illumina short-read data: SRX11350423; raw reads of the Hi-C library: SRX11350428 and SRX11350429. The raw read data were also deposited in the Genome Sequence Archive (GSA) of the China National Center for Bioinformation (accession code: CRA004283). The assembled genome was also deposited to GenBank in NCBI and can be accessed via accession No. JAHSUZ000000000. Genome assembly, gene and TE annotation data, and transcriptomic data are also available on the Banana Genome Hub (http://banana-gen ome-hub.
Serum Samples The two phases of this study comprised proteomic analysis of a discovery cohort and then a validation cohort (Table  1 ). The discovery phase aimed to identify potential EV associated protein biomarkers for DFTD using a cohort of 12 DFTD infected devils and 10 healthy controls. DFTD infected devils were considered to be in advanced stages (mid-late) of the disease based on large tumor volumes (15 ml to 161 ml). Tumor volumes were calculated by the ellipsoid formula described by Ruiz-Aravena et al. (26) , utilizing measures of length, width, and depth of each DFTD tumor. DFTD infected devils often present more than one tumor on multiple locations of the body. Therefore, total tumor volume was calculated by summing the volume of each tumor present at the time of sampling. The second phase was designed to validate the first phase data in an independent cohort and further investigate the potential biomarkers in preclinical, presumed DFTD latent devils.
Nano Particle Tracking Analysis (Zetaview) EV size distribution and concentration were determined using a ZetaView PMX-120 nanoparticle analyzer (Particle Metrix, Inning am Ammersee, Germany) equipped with Zetaview Analyze Software version 8. 05. 12. Prior to measurement, the system was calibrated as per manufacturer's instructions with 100nm Nanospheres 3100A (Thermo Fisher Scientific). Measurements were performed in scatter mode, and for all measurements, the cell temperature was maintained at 25°C. Each sample was diluted in PBS to a final volume of 1 ml. Capture settings were sensitivity 80, shutter 100, and frame rate 30. Post-acquisition settings were minimum trace length 10, min brightness 30, min area 5, and max area 1000.