dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparison of secreted carbohydrate-active enzymes We screened the genomes of commensal, weakly pathogenic, and pathogenic Xanthomonas strains for the presence of various genes involved in breakdowns (CEs, PLs, GHs) and assembly (GTs) of carbohydrates, lignin degradation (AAs), and the carbohydrate-binding module (CBM)  (Kaoutari et al. , 2013; Lairson et al. , 2008). Carbohydrate active enzymes (CAZymes) were assigned to Prokka (v1. 14. 5)  (Seemann, 2014)  protein output files (. faa files) using run_dbcan command (https://github. com/linnabrown/run_dbcan) against the HMMER, DIAMOND, and eCAMI databases with default settings. Final CAZyme domain annotations were the best hits based on the outputs of at least two databases to investigate the genomic potential of various species for carbohydrate utilization.
Identification of lifestyle-associated genes We retrieved 1,834 Xanthomonas genomes from the NCBI GenBank RefSeq database to ensure a high-quality and minimally biased set of genomes. These genomes were then de-replicated using dRep (v3. 2. 2)  (Olm et al. , 2017)  to de-replicate the complete dataset using a 95% minimum genome completeness cut-off and 5% maximum contamination. The ANI threshold to form primary clusters (-pa) was set at 0. 95 (species level) and 0. 99 (strain level) for the secondary cluster. During secondary comparisons, a minimum level of overlap between genomes was set to 80% coverage. The de-replicated genomes were manually curated to include the 83 new genomes generated in this work in addition to representative genomes from diverse Xanthomonas species belonging to groups 1 and 2.
A total of 337 genomes were selected for downstream analysis (Table  S3 ). OrthoFinder was used as a clustering approach to compare the whole proteome of the 337 Xanthomonas strains with the default settings as previously described. To determine significantly enriched or depleted protein clusters in different Xanthomonas lifestyles, we used the hypergeometric test, PhyloGLM, and Scoary as described in  Levy et al. (2018). Among the three methods, the hypergeometric test looks for the overall enrichment of genes without considering the dataset's phylogenetic structure. PhyloGLM is a phylogenetic-aware method that eliminates enrichments related to shared ancestry  (Ives & Garland, 2010) , while Scoary combines the phylogeny-aware test, Fisher's exact test, and empirical label-switching permutation analysis  (Brynildsrud et al.
, 2016). All these approaches were used on gene presence/absence and gene copy-number data and used for PhyloGLM test. A gene was considered significant a) if it had a q-value < 0. 05 for Fisher's exact test and an empirical p-value < 0. 05 for Scoary; b) if it had a corrected p-value with FDR with q < 0. 01 for hypergeometric test; and c) a p-value < 0. 01 along with an estimate of < -1. 5 or > 1. 5 in copy number analysis for PhyloGLM. We used eggNOG-mapper (v2. 1. 7)  (Cantalapiedra et al. , 2021)  to address COG categories to each significantly enriched and depleted protein cluster from the combination of two or more methods (hypergeometric, PhyloGLM, and Scoary) in the different Xanthomonas lifestyles. In addition, each ortholog id was queried across the IMG database to obtain annotation based on COG, KO, TIGRFAM, and Pfam.
2022 ) transposable element methylation  (Laporte et al. 2019) , and transcriptional differences  (Derome et al. 2006; Jeukens et al. 2009; Rougeux, Gagnaire, Praebel, et al. 2019). Benthic-limnetic species pairs in different lakes thus present a naturally replicated system in which to study the molecular mechanisms associated with speciation. We assessed the role of genomic and epigenomic variation in whitefish speciation by performing low-coverage whole genome sequencing (WGS) and whole genome bisulfite sequencing (WGBS) for four benthic-limnetic species pairs (N=64 individuals sequenced in both datasets): lake whitefish from Cliff and Indian Lake, Maine, USA, and European whitefish from Langfjordvatn Lake, Norway and Zurich Lake, Switzerland (Figure  1 ). The objectives of this study were to (i) determine the extent of whole genome genetic divergence between benthiclimnetic whitefish species pairs, (ii) measure the rate of polymorphism at CpG sites relative to the rest of the genome, (iii) characterize whole genome differences in DNA methylation among limnetic-benthic whitefish species pairs, and (iv) determine whether there was an enrichment of outlier SNPs at differentially methylated loci (DMLs), which would support the hypothesis that epigenetically influenced mutagenesis may be driving genetic variation and be involved in speciation.
Whole genome sequencing analysis Reads were trimmed and filtered for quality with fastp  (Chen et al. 2018). The North American samples were aligned to the genome of Coregonus clupeaformis  (Mérot et al. (2022)  and the European samples were aligned to the genome of the European whitefish, Coregonus sp. Balchen, (De-Kayne et al. 2020) using BWA-MEM  (Li 2013). Aligned reads were filtered to keep mapping quality over 10 with Samtools v1. 8  (Li et al. 2009). Duplicate reads were removed with MarkDuplicates (PicardTools v1. 119. , http://broadinstitute. github. io/picard). We realigned around indels with GATK IndelRealigner  (McKenna et al. 2010 ) and soft clipped overlapping read ends using clipOverlap in bamUtil v1. 0. 14  (Breese and Liu 2013). The pipeline is available at https://github.
Frequency of SNPs in CpG sites We determined whether CpG sites were more polymorphic than the rest of the genome, which would be indicative of CpG methylation-induced mutagenesis  (Jones et al. 1992; Gorelick 2003). We started by using fastaRegexFinder. py (https://github. com/dariober/bioinformaticscafe/blob/master/fastaRegexFinder/) to find all CpG sites in each reference genome. Next, we restricted the CpG site lists to include only sites with sufficient coverage in the WGS data using bedtools intersect  (Quinlan and Hall 2010)  with the list of covered positions for each lake exported earlier (>75% of samples covered). We used regioneR  (Gel et al. 2016 ) to determine how many SNPs fell within CpG sites using the numOverlaps command. We assumed a uniform distribution of SNPs across the genome as a null hypothesis for both tests, thus a higher proportion of SNPs in CpGs relative to average polymorphism in the genome would indicate an enrichment of point mutations in CpGs.
Whole genome DNA methylation tabulation Raw methylation data were trimmed using fastp  (Chen et al. 2018 ) to remove sequences with phred quality less than 25, length less than 100 bp, and to remove the first and last nucleotides which have high sequencing error rate. After trimming, lake and European whitefish methylation data were analysed separately. Trimmed sequences were aligned to the same reference genomes for each continental lineage as described in the WGS methods using bwa-meth (https://github. com/brentp/bwa-meth). Alignments with mapping quality greater than 10 were outputted to a BAM file using samtools  (Li et al. 2009 ) and duplicate sequences were removed using Picard tools. Methyldackel's mbias function was used to inform trimming of biased methylation calls at the beginning and end of reads, then CpG-specific methylation calling was performed on bias-trimmed data using methyldackel's extract function (https://github.
com/dpryan79/MethylDackel). The pipeline is available at https://github. com/enormandeau/bwa-meth_pipeline. Individual-level whitelisting of methylation data using SNP data C/T SNPs cannot be discerned from true methylation reads because bisulfite conversion leaves methylated cytosine unchanged but converts unmethylated cytosine to uracil which is sequenced as a thymine. Therefore, CpG sites which overlap with C/T or G/A SNPs must be removed from the analysis. More specifically, we can use an individual-level approach where we filter CpG sites separately for each sample based on that sample's genotype. Relying on our WGS data, we thus created a whitelist of CpG sites for each sample, keeping the sites homozygous for C and G and masking individuals heterozygous or homozygous for the T or A allele at that site.
Subsets of CpG sites were randomly selected based on the total number of outlier SNP-DML overlaps for each lake then 100 000 permutations were performed to estimate the possible range of correlations using genome-wide CpG sites. We performed GO enrichment analysis for the outlier SNP-DML overlaps for each lake. The whitefish genomes were first annotated with the GAWN pipeline (https://github. com/enormandeau/gawn) using the Salvelinus namaycush (GCF_018398675. 1) transcriptome from GenBank. We then retrieved the genes that overlapped the SNP-DML overlap positions for each lake and proceeded to GO enrichment tests using the go_enrichment pipeline (https://github. com/enormandeau/go_enrichment). Results were filtered to remove broad terms (depths 0 and 1) and to require a Benjamini-Hochberg false discovery rate corrected pvalue of 0.
Acknowledgements We would like to thank  Anne-Laure Ferchaud  and  Kyle Wellband  for helpful discussions on the project. We thank  Kim Praebel ,  Shripathi Bhat  and the  Freshwater Ecology group at UiT (Tromso)  for providing samples from Norway, and  Ole Seehausen  for providing samples from Switzerland. This work was supported by a  Natural Sciences and Engineering Research Council of Canada   Discovery Grant  to L. B ( CG053918 ). WGS data for Coregonus clupeaformis and C. lavaretus are available online at SRA BioProject PRJNA820751 and [currently being uploaded], respectively. WGBS data are available online at BioProject PRJNA559821.
possible mutation: (i) all C/T and G/A SNPs (where G/A SNPs would indicate a C/T mutation at the G position in the reverse complement of the DNA), (ii) all C/A and T/G SNPs, and (iii) all C/G SNPs. We also generated a list of all C and G sites in the genome with sufficient WGS coverage. We compared the rate of finding each SNP type in a CpG site to the rate of finding that SNP type in C and G sites, then used Pearson's chi-squared test to determine if the proportions were significantly different. All scripts are available at https://github. com/cvenney/ga_permutation.
Our proposal is also uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles. 3. We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel-density hypervolumes using both simulated and empirical datasets. 4. Using NJ we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree-based representations. Moreover, the method is directly comparable with PD measures, and enables quantification of the richness, divergence and regularity of the functional space.
Hence, the quality of the functional space is 1 when using N axes. Therefore, we only used the simulated datasets with eight traits to assess the quality of the functional spaces built by PCoA. We used linear mixed models to estimate the effect of the different methods (fixed effects) in the quality of the functional space. The number of species per community, the number of traits per species and the evolutionary process used to generate the traits were introduced in the models as random effects. Because the quality of the functional space ranges between 0 and 1, with true 1s but no true 0s included in the response, we transformed all 1s by subtracting 0. 0001 and then ran the models following a beta distribution. Mixed models were performed using the glmmTMB (Mollie et al. , 2017) package, and model validation was performed by checking heterocedasticity, posterior predictive checking, and normality of random effects and residuals using the performance  (Lüdecke et al.
Comparing frameworks using empirical data The study of avian functional diversity has recently gained momentum due to the release of the AVONET database, which provides a complete set of data for eight continuous morphological traits for all the world's extant bird species  (Tobias et al. , 2022). Dozens of papers have been published using this data source in just a few months (e. g. ,  Weeks et al. , 2022) , including several focusing on islands (e. g. ,  Matthews et al. , 2022; Soares et al. , 2022 ). An often mentioned issue when studying the functional diversity of birds is the so-called "kiwi problem". In short, kiwis (Apterygidae: Apteryx spp. ) differ substantially from other birds regarding their morphology (e. g. , for wing length, in AVONET, the kiwis have values roughly 267 times smaller than the species with the next smallest wing length) and thus all five species are always (extreme) outliers in functional diversity analyses.
In addition, some of the methods for building NJ trees allow for missing distances between pairs of species  (Criscuolo & Gascuel, 2008). The flexibility provided in both these steps, calculating distances and building trees, will help circumvent the many gaps that most trait databases have, particularly for taxa less well studied than birds (e. g. ,  Pekar et al. 2022; Shirey et al. 2022). The construction of NJ trees is extremely fast, orders of magnitude faster than hypervolumes, which can be an advantage for large datasets or simulations or null models requiring many repeated calculations. In addition, it is possible to at least visually estimate to a close approximation many of the metrics derived from tree-like representations (e. g. , richness), a task that is much harder for multidimensional representations.
Case studies We considered, as an illustration, simulated theoretical datasets based on a pool of 100 species characterized by a single quantitative, discrete trait. To obtain distances between species bounded in 0 and 1, we first standardized the trait by dividing it by the range of variation (maximum-minimum) and defined the dissimilarity between two species has the absolute difference in their standardized trait value. Note that only  D requires the use of bounded distances but for homogeneity we apply also the standardization when using  Q. Let y i be the raw trait value for species i; and x i = y i / (max j (x j )-min j (x j )) be its standardized trait value. We simulated functional diversity in 5 areas. We considered a reference species pool with 100 species with raw trait values (the y i 's) equal to 1 to 100 with a step of 1.
Opting for the use of this component C, the detection of an overall trend of overdispersion or clustering does thus not require the involvement of null models. This is reassuring given the difficulty there is to identify best performing null models  (Hardy, 2008; Miller et al. , 2017) , the additional methodological step they represent, and given the amount of calculation these null models require, particularly on large datasets. Although index C could also be used with null models to test the significance of an observed clustering or overdispersion, it has thus the great advantage of evaluating levels of clustering versus overdispersion without the need for these null models. This can be useful in situations where the aim is to compare the level of clustering versus overdispersion of distinct sets of communities be they for example, different ecoregions (to reveal, e.
High Resolution Mass Spectrometry analysis of the iturinic lipopeptides in B. velezensis 32a The corresponding iturinic lipopeptide (iturin A or mycosubtilin) in 32a was determined by RP-HPLC-tandem MS (RP-HPLC-MS/MS) to characterize the amino acid residues of the iturinic sequence. Briefly, 10 µL of filtered 32a supernatants (as previously described above) and iturin A and mycosubtilin standard solutions concentrated at 1000 mg/L were chromatographed using the same RP-HPLC conditions as described above (as previously described above). The chromatographed peptides were then ionized into the electrospray ionization source of the Q-TOF Synapt G2-Si™ (Waters Corporation, Manchester, UK). MS analysis was performed in sensitivity, positive ion and data-dependent analysis (DDA) modes using the proprietary Mass Lynx software (Waters).
The source temperature was set at 150 • C and the capillary and cone voltages were set at 3000 and 60 V, respectively. The MS data were collected for m/z values in the range of 200 and 1500 Da with a scan time of 0. 2 s. A maximum of 5 precursor ions were chosen for MS fragmentation, with an intensity threshold of 1000. The MS/MS data were collected for m/z values in the range of 10-3000 Da using the collision-induced dissociation (CID) mode and a scan time of 0. 1 s at an energy collision of 10-15 V for low m/z (200 Da) and a range of 20-100 V for high m/z (1500 Da).
Statistical analysis The two-way analysis of variance (ANOVA) and Tukey's multiple comparison tests were used to determine significant differences (p < 0. 05) between purified lipopeptides and their mixtures. Statistical analyses for evaluating the antagonistic activity of 32a and GA1 mutants against the bacterial pathogen were determined by twoway ANOVA with post hoc Tukey's and Dunnett's tests respectively. The statistical analysis was performed using Graph Pad Prism 9. 0. 1 Software.
MS identification of the lipopeptides, polyketides and bacilysin compounds produced by B. velezensis 32a Antimicrobial compounds produced by B. velezensis 32a in Landy medium from 72 h culture were analyzed using RP-HPLC-MS with an m/ z ranging from 200 to 1250. Using prior data about MS analysis of molecules from B. subtilis and according to the analysis of purified lipopeptides, three well-known families of cyclic lipopeptides (surfactins, fengycins, and iturins), three different kinds of polyketides (macrolactins, oxydifficidin and bacillaenes), bacilysin and chlorotetaine; a chlorinated derivative of bacilysin; were observed. The main results are summarized in Table  2. The strain efficiently secretes different variants or isoforms of surfactin, iturin, and fengycin (Fig. S1 ). Ion signals at m/z 1016.
Acknowledgments Authors would like to thank the  Partenariat Hubert Curien (PHC) UTIQUE  n •  46421UF/21G0906  which helped finance part of the work. This work was also supported by a grant from the  Tunisian Ministry of Higher Education and Scientific Research  and by the  University of Lille  through the  CPER Bi Hauts Eco de France program  funding administered by the  Hauts-de-France Region. The authors would like to thank  Dr Christophe Flahaut  for his availability and advice on mass spectrometry analysis.
To assess the frequency of vHGT during nucleocytoviruses evoluIon, we used the amalgamated likelihood esImaIon 27 (ALE) method, which is a tree reconciliaIon method that compares a gene tree to a species tree to idenIfy different evoluIonary events. ALE is a probabilisIc approach that supports the detecIon of three classes of gene gain (gene duplicaIon, HGT, and originaIon) and gene loss. We applied the ALE method on the gene families and viral species tree for nucleocytoviruses. In this framework, the HGT events inferred by ALE are likely to be vHGT, while the originaIon events represent either HGT from outside the tree, such as cellular organisms or other viruses not included in our dataset, or de novo gene creaIon. In this study, we generated a robust viral tree ("species tree") for 195 reference nucleocytoviruses (mostly cultured ones) and performed the reconciliaIon of over 4,700 gene families to infer the evoluIonary events.
95) for gene gain, loss, duplicaIon, and vHGT (Mann-Whitney U test, P < 0. 001; Fig. 4b  and Fig. S4b ). The evoluIonary inference of moumouvirus genomes, for example, depicts the high rates of recent evoluIon. Three moumouviruses had diverged in recent past (RED = 0. 98), and their mean ANI (Average NucleoIde IdenIty) was 84. 7%. In the period from RED = 0. 98 to 1, they gained and lost a lot of genes: the average gene gain was 63 and the average gene loss was 162. These results suggest conservaIve esImates of evoluIonary events for deeper branches compared with more recent ones, as expected due to the absence of exInct viruses in the analyzed dataset.
e. , gene duplicaIon, vHGT, originaIons, and losses) along the evoluIon of nucleocytoviruses. We verified vHGT is as frequent as other gene gain events. We suggest that through vHGT, nucleocytoviruses can get access to other nucleocytoviruses' gene repertoires and have chance to get beneficial genes that has experienced selecIon in the evoluIon of other viruses. We decided not to include Metagenome-Assembled Genomes (MAGs) due to possible contaminaIon and incompleteness. The restricted diversity of genomes in our dataset hence resulted in robust yet conservaIve esImate of evoluIonary events. Should the MAGs of nucleocytoviruses reach higher quality and compleIon, their inclusion would help reconstruct more concrete evoluIonary scenarios. The frequent vHGT observed from this study coupled with its potenIal implicaIons in facilitaIng transiIons and adaptaIons to new hosts, lead us to posit an open quesIon for future research: "To what extent does vHGT influence transiIons to and adaptaIons in new hosts during the evoluIonary path of nucleocytoviruses?" The challenge remains due to the high proporIon of unknown funcIon gene families and the lack of markers for host transiIon.
Collec2on of reference and complete Nucleocytoviricota genomes The reference genomes of viruses in the phylum Nucleocytoviricota were collected from the NaIonal Center for Biotechnology InformaIon (NCBI) RefSeq databases by searching for the taxonomy Nucleocytoviricota or collected from published nucleocytoviruses isolaIon paper (Genomic data is available in www. genome. jp/qp/db/community/vHGT/vHGT_data/). Our curated dataset includes 195 viruses that cover six proposed viral orders: Algavirales, Asfuvirales, Chitovirales, Imitervirales, Pandoravirales, and Pimascovirales.
Reconstruc2on of the robust viral tree Each virus in the dataset was subject to de novo protein sequence predicIon to unify the gene predicIon quality using Prodigal/2. 6. 3  33  with the -a parameter to predict all potenIal genes. From these predicted proteins, we idenIfied and aligned seven suggested marker genes using the tool ncldv_markersearch 31 with the -c parameter to produce a mulIple sequence alignment file by Clustal Omega. To limit the influence of non-informaIve sites, alignment columns containing more than 90% gaps were trimmed using trimAI/1. 4. 1  34  with the -gt 0. 1 parameter. To minimize the influence of long branch anracIon effects, we employed the posterior mean site frequency model, which necessitates a guide tree as input. We constructed this guide tree using IQ-TREE/2.
Among them, the tree reconciliaIon was successful for 4,786 OGs (see details below). We idenIfied viral-specific OGs among these 4,786 OGs through a sensiIve homology search using Diamond/2. 0. 15  41  (--very-sensiIve). An OG was classified as viral-specific if none of its members matched any entry in the database, which comprised both KEGG (Kyoto Encyclopedia of Genes and Genomes) cellular organisms  42  and metagenome-assembled genomes from marine planktonic eukaryotes, derived from the Tara Oceans project  43  , with an E-value threshold of 10 -3. Consequently, we idenIfied 3,535 of the 4,786 OGs as being viralspecific.