dataesr/scientific-paragraphs-categorization huggingface dataset:
Geographical distribution of Leptospira species and L. interrogans sublineages Species of the saprophytes and intermediates subclades were represented by few strains. In contrast, some species of pathogens subclade P1 were represented by multiple isolates (e. g. , 160 for L. interrogans, 76 for L. borgpetersenii, 52 for L. kirschneri, 27 for L. santarosai, 27 for L. noguchi and 23 for L. mayottensis). Based on the present sample of Leptospira genomes, the geographic distribution of these species showed clear differences (Fig  2 ). L. interrogans, L. borgpetersenii and L. kirschneri were found in all world regions, even though L. kirschneri appeared more rarely in Asian and American samples than in Europe and Mayotte. In contrast, in our dataset, L. santarosai was only sampled from the American continent and the Caribbean islands and L.
noguchi was found predominantly in the Americas and rarely in Asia. So far, L. mayottensis has been only isolated from the Indian Ocean islands (Fig  2 ). We analyzed in more details the geographic distribution of the diversity of L. interrogans, the most common Leptospira species from human infections around the world, and which was the most represented in our dataset. S5 Fig presents a phylogenetic tree of the 152 L. interrogans isolates for which the geographic source was known; these were from 32 countries in all world regions. The data reveal extensive geographical spread of L. interrogans sublineages. Although some sublineages were sampled in a single world region (e. g. , the sublineage containing serovars Szwajizak, Wewak, and Hawain originated in Oceania), it is clear that most sublineages are geographically widespread (S5 Fig).
The derived strain (cgST20) was clearly distinct from the virulent parental strain (cgST23, differing by 15 loci). Nevertheless, these subcultures were grouped together in the phylogenetic tree (S2 Fig). Similarly, a virulence-attenuated isolate of L. interrogans serovar Manilae passaged 67 times was sequenced  [68]  and compared with the corresponding parental virulent culture. The cgMLST analysis classified the 2 cultures as cgST31 and cgST32, differing by only 2 alleles out of 545 genes. These results illustrate the high resolutive power of cgMLST, which can distinguish genomes of isolates that evolved in-vitro over several generations. To evaluate the genetic diversity among isolates classified into the same cgST (or groups of cgSTs differing only by missing data in some isolates), we analyzed the three most numerous ones (highlighted with colors in S1 Table, column cgST) using a whole-genome single nucleotide polymorphisms (SNP) approach.
Only 4, 1 and 2 cgMLST clusters matched more than one MLST ST for scheme 1, 2 and 3, respectively (S9 Fig). Reciprocally, 26, 9 and 13 STs for MLST1, MLST2 and MLST3, respectively, were subdivided into more than one CG. In other words, despite accepting 40 mismatches within members of the groups, CG classification is still more discriminatory than each of the classical MLST systems. Note that although the lowand high-passage strains (see above) of L. interrogans serovar Lai and L. interrogans serovar Manilae were distinguishable at the level of cgST subtypes, they were classified into the same CG (CG16 and CG23, respectively), consistent with their recent evolutionary link. To provide access to the cgMLST allele and profiles nomenclature, allowing for comparison and sharing of typing results among laboratories worldwide, a database was set-up and was made publicly accessible online (https://bigsdb.
The wide geographic distribution of CGs indicates that geographic spread of Leptospira strains is faster than their genetic evolution into distinct CGs. We next analyzed the geographic distribution of the high-resolution cgMLST types (cgST). One of the most represented cgSTs (cgST482) in our dataset is constituted by L. interrogans serovar Pomona strains (n = 6) isolated from cattle in Uruguay  [76]  (S1 Table ). Although five out of six of these strains have been isolated from the same farm and were undistinguishable by SNP analysis, one isolate from another region of the country differed from the group of five isolates by 3 SNPs. This shows that cgST classification could possibly inform on the epidemiological links among Leptospira isolates.
Thus, L. interrogans strains belonging to serovars Copenhageni and Icterohaemorrhagiae share the same CG regardless of their geographic origin. This limited genetic diversity and broad geographic distribution (S5 Fig) is consistent with recent evolution/expansion following extensive migration of rodents, the main reservoir of serovars Copenhageni and Icterohaemorrhagiae, and multiple introductions due to modern global transport, in particular long-range, ship-based travel and trade. Due to this rapid geographic diffusion, little phylogeographic signal was present in the dataset, rendering challenging the reconstruction of the geographic origins of L. interrogans and its sublineages with confidence. By contrast, species such as L. noguchi, L. kirschneri, and L. mayottensis are not associated with rats and are largely confined in specific geographical areas.
The pathogen L. mayottensis may have been introduced into Mayotte from Madagascar via the tenrec, a small terrestrial mammal  [83]. This work provides a framework for the definition of Leptospira clades, subclades, subgroups, species, as well as strains at two levels of resolution (S3 Table ). The possibility for laboratories around the world to identify the same strains using a unified nomenclature and a centralised genotyping database will facilitate the sharing and dissemination of knowledge on circulating Leptospira genotypes, worldwide. The cgMLST scheme will also enable early detection of new genotypes being introduced into locations where they are not usually found. The links between genotypes and their pathogenic potential and virulence will be an important subject for future studies.
For yet unknown reasons, a limited number of Leptospira serovars are much more likely to cause severe disease than others  [84] [85] [86] [87]. The role of phages, plasmids, and horizontal transfer in the acquisition of virulence factors also remains to be determined. The molecular basis of host specificity is also largely unknown. Future dedicated studies will be needed to characterize the gene content of subclades, species and strains, and their association with the clinical presentation and outcome of Leptospira infections. For each profile (n = 359) belonging to a clonal group with at least 2 isolates, data were removed randomly so that the resulting profiles had from 25 to 525 missing alleles with a step size of 25; this was done 100 times for each profile and missing data point. The resulting profiles were then compared to all other (initial) isolates profiles, and all isolates that differed by less than the threshold (40 mismatches) were recorded.
There are three possibilities. (1) If all recorded isolates belonged to the same CG, and the CG was the one of the test isolate, this is counted as a match (reproducible clustering). (  2 ) If no isolate belonged to the CG of the test isolate, this is a mismatch. (3) If at least one isolate belonged to the cluster of the test isolate, and at least one other to another CG, this would lead through single-linkage clustering to the merging of initially separate CGs, and is counted as a fusion. We then computed the proportion of matches, mismatches and fusions in the simulation exercise. The figure presents the proportion of correct associations (matches) for each missing data level.
Distribution of the intra-and inter-subclade genetic distances. The distances were calculated from the concatenated alignment of the 545 cgMLST loci nucleotidic sequences of the 509 isolates used in this study, under the TN93 mode (https://doi. org/10. 1093/ oxfordjournals. molbev. a040023) and using the software goalign (https://github. com/ fredericlemoine/goalign). (TIFF) S4 Fig. Maximum-likelihood phylogenetic tree based on the concatenated alignment of the 545 cgMLST loci sequences of the isolates from the subclades S1 (panel 1) and P2 (panel B). Tip labels contain the name of the species when known. Species are grouped into subgroups within each subclade. (TIFF) S5 Fig. Maximum-likelihood phylogenetic tree of 152 L. interrogans strains. The tree was built from the concatenated alignment of the 545 cgMLST protein sequences, and includes all L.
Acknowledgments We thank the technicians of the National Reference Center for Leptospirosis, in particular Celine Lorioux, for cultures and typing of Leptospira strains, and  Evelyne Begaud and Chantal Bizet from Collection de l'Institut Pasteur (CIP)  for providing type and reference strains. We thank  Cyrille Goarant  ( Institut Pasteur de Noumea, New Caledonia ),  Anissa Amara Korba  ( Institut Pasteur d'Alger, Algeria ),  Fairuz Amran  ( Institute for Medical Research, Malaysia ),  Toshiyuki Masuzawa  ( Chiba Institute of Science, Japan ),  Vasantha Kumari Neela  ( Universiti Putra Malaysia, Malaysia ) and  Alejandro Buschiazzo ,  Leticia Zarantonelli  and the  consortium "Grupo de Trabajo Interinstitucional de Leptospirosis" (Institut Pasteur Montevideo/UdelaR/ INIA/MGAP, Uruguay)  for sharing Leptospira isolates.
In any case, acetylcholine was applied first to check for the presence of functional nAChRs and for current normalization in presence of lupanine or alkaloid extracts. Antagonist modulation of acetylcholine-elicited current was determined by pre-application of lupanine or alkaloid extracts for 10 seconds, followed by their co-application in the presence of acetylcholine. Data were collected and analysed using pCLAMP 10. 4 package (Molecular Devices, UK).
ܰ‬ ‫݀݁ݐܽ݁ݎݐ‬ ‫݀݁ݐܽݎ݃݅݉‬ ‫݁ܽݒݎ݈ܽ‬ ‫݁݃ܽݎ݁ݒܣ‬ ‫. ܰ‬ ‫݈ݎݐ݊ܿ‬ ‫݀݁ݐܽݎ݃݅݉‬ ‫݁ܽݒݎ݈ܽ‬ This proportion was subsequently regressed upon variety and parasitic isolate, simultaneously accounting for the migration plate effect fitted as a random effect with the lme function of the R software v3. 5  51. Model diagnostics was run to check for residual normality and detect putative outliers that were discarded accordingly. Post-hoc comparisons accounting for multiple comparisons between tested effect levels were performed using a Tukey's test implemented with the multcomp package v1. 4-8  52. Dose-response data were modelled as log-logistic regression with two, i. e. the curve slope and the associated median excitatory (EC50) or inhibitory (IC50) concentration using the drc package v3. 0-. CC-BY-NC-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
It is made available under The copyright holder for this preprint (which was not this version posted January 26, 2019. ; https://doi. org/10. 1101/530956 doi: bioRxiv preprint 1  53. A third parameter was added for electrophysiology data modelling to account for differences in maximal response values. Linear regression of FEC and haematocrit upon experimental group, day post infection and their interaction considered as fixed effects and individual as a random effect was implemented with the lme function of the R v3. 5 software 50. To account for group heterogeneity in haematocrit at the beginning of the 2 nd infection (FEC were 0 for every individual at 0 dpi), basal haematocrit level measured at 0 dpi was used as covariates. Average daily gain was computed for every ewe as the difference between weights at 30 and 0 dpi divided by the number of days, and recorded milk production volumes were summed for each goat as a proxy for their total volume.
Acknowledgements This project has received the grateful support of the  Centre-Val de Loire region (Lupinema project , grant number  2014-00091669 ). Alkaloid-rich seeds were provided by the  INRA CRB Protéagineux  and nematodes were maintained by the  BRC4Env Animal Parasitic Nematodes collection , the environmental resources pillar of the AgroBRC-RARe research infrastructure. Authors are grateful to  N. Harzic  for providing commercial lupin seeds.
Simulation program A FORTRAN program 'GenManSim'  (Windig and Oldenbroek, 2015)  was used and extended with the facility to simulate subpopulations  (Windig and Doekes, 2018). The specific functions needed in our study were added to the original simulation workflow of 'GenManSim', including generation of breeding values and phenotypes for individual animals and selection based on EBVs and/or phenotypes of HD. Because genetic evaluation across two countries with different HD scales was to be simulated, all animals had two sets of true breeding values (TBVs) and EBVs simulated: TBV1 and EBV1 for the scale used in country 1 (country 1 scale) and TBV2 and EBV2 used in country 2 (country 2 scale). The method about how TBVs and EBVs for HD were calculated is shown in Appendix (see Supplementary document 1).
Acknowledgement Shizhi Wang  benefited from a joint grant from the  Erasmus Mundus European Graduate School in Animal Breeding and Genetic (EGS-ABG). We are grateful to  EGS-ABG  for funding and grateful to the  Société Centrale Canine (SCC, France) ,  Svenska Kennelklubben (SKK, Sweden) , and  The Kennel Club (KC, UK)  for funding and data provision. Besides, we are also grateful to the valuable comments on the manuscript of  Freddy Fikse  and two anonymous reviewers.
The Hco-tbb-iso-1 locus is indicated by vertical dashed lines (GO:0046662, Kolmogorov-Smirnov test, P = 8. 6 × 10 -3 ) genes were enriched, both of which are phenotypes linked to ivermectin and its effect on parasite fecundity  29. Neurotransmission is the primary target of anthelmintics such as macrocyclic lactones  30  and levamisole  31  ; genes with GO terms related to neurotransmission (GO:0001505, Kolmogorov-Smirnov test, P = 9. 1 × 10 -3 ) were significantly enriched across comparisons. Anthelminticassociated GO terms including "response to drug", "regulation of neurotransmitter" and "neurotransmitter transporter activity" were significantly enriched in every comparison involving a South-African multi-resistant field isolates (STA. 1, Supplementary Data 4). Four candidate genes (HCOI00389600, HCOI00032800, HCOI00243900, HCOI00489500) were found overlapping XP-CLR signals of selection and thus seem candidates for drug resistance loci in H.
Methods Sample DNA extraction and sequencing. A total of 267 individual male H. contortus were obtained from a collection held at INRA  17  (metadata for all samples is presented in detail in Supplementary Data 1). The sampling regime was designed to delineate the contribution of major evolutionary forces, i. e. , migration and selection (drug and climate) but also constrained by the material available in the collection. Because migration was likely to match human history, isolates from western African countries and southern America were selected to address the contribution of slave trade history to the structuring of H. contortus populations; isolates from former colonies of the British Empire (South-Africa, Australia) were sampled to establish the connectivity between worm populations from Europe and these countries.
Ivermectin-resistant isolates (AUS. 1, STA. 1, STA. 3) were also retained to evaluate how anthelmintics had shaped H. contortus genomic variability (drug efficacy data have been provided in Supplementary Table  2 ). Isolates were selected based on available material to ensure minimal sample size (n = 9) per isolate and proper allele frequency estimation. Following these criteria, 19 isolates from 12 countries were available (Supplementary Data 1). Note that the second Australian population (AUS. 2) was obtained from an Italian laboratory (labelled ITA_NAP, Supplementary Data 1). Samples were gathered between 1995 and 2011 (Supplementary Data 1), and stored in liquid nitrogen upon collection. Four isolates were fenbendazole susceptible (Fig. 1  and Supplementary Table  2 ; triangles; FRA. 2, FRA.
4, STO, ZAI). DNA was extracted with the NucleoSpin Tissue XS kit (Macherey-Nagel GmbH&Co, France) following the manufacturer's instruction. Sequencing libraries were prepared using an amplification-free protocol  13  and were sequenced with 125 bp paired-end reads on an Illumina Hiseq2500 platform using V4 chemistry (Supplementary Data 1). A second round of sequencing was performed with 75 bp paired-end reads to increase the coverage of 43 samples (Supplementary Note 1). After sequencing, two samples were identified to be heavily contaminated by kraken-0. 10. 6-a2d113dc8f 59 and were discarded. In total, 18 sequencing lanes consisting of 4,152,170,256 reads were sequenced, the raw data of which are archived under the ENA study accession PRJEB9837. Sequencing data processing. Read mapping to both the mitochondrial and nuclear genomes (v3.
0, available at ftp://ngs. sanger. ac. uk/production/pathogens/ Haemonchus_contortus) was performed using SMALT (http://www. sanger. ac. uk/ science/tools/smalt-0) with a median insert size of 500 bp, k-mer length of 13 bp, and a stringency of 90%. For samples that had two or more BAM files (when split across multiple sequencing lanes), the BAM files were merged using samtools v. 0. 1. 19-44428  60 , and duplicated reads removed using Picard v. 2_14_0 (https:// github. com/broadinstitute/picard) before performing realignment around indels using Genome Analysis Toolkit (GATK v3. 6)  61  RealignerTargetCreator. Mean coverage of the mitochondrial and genomic genomes were estimated using GATK DepthOfCoverage, revealing coverage lower than the estimated target coverage (original 8×) for most samples.
To circumvent this issue, we applied the GATK Variant Quality Score Recalibration (https://gatkforums. broadinstitute. org/gatk/ discussion/39/variant-quality-score-recalibration-vqsr), which first uses a reference (truth) SNP set to estimate the covariance between called SNP quality score annotations and SNP probabilities, followed by application of these probabilities to the raw SNPs of interest (Supplementary Fig. 17 ). The reference "truth" SNP database was generated from the intersection of variants called from samples with at least a mean of 10× coverage (n = 13) using three independent SNP callers as described in the dedicated Supplementary Methods section. This procedure yielded 23,868,644 SNPs spanning the five autosomes. Called SNPs were used for particular analyses (Ne trajectory through time, cross-population composite likelihood-ratio) that could not be performed under the probabilistic framework that relied on GLs as implemented in ANGSD 62 v.
0. 919-20-gb988fab (Supplementary Note 1, Supplementary Fig. 18 ). These data were also used to estimate average differentiation between isolates (Supplementary Note 1). However, within-isolate diversity and admixture were analysed using ANGSD  62  (Supplementary Note 1). Mitochondrial DNA data processing. The mitochondrial genome exhibited an average coverage depth of 322× (ranging from 24× to 5,868×) per sample (Supplementary Data 1). Mitochondrial reads were extracted and filtered from poorly mapped reads using samtools view (-q 20 -f 0 × 0002 -F 0 × 0004 -F 0 × 0008) and from duplicated reads using Picard v. 2_14_0 MarkDuplicates (https://github. com/ broadinstitute/picard). Realignment around indels was applied with GATK  61  and SNP were subsequently called using samtools  60  mpileup using only reads that achieved a mapping quality of 30 and base quality of 30.
To exclude sites prone to heterozygous signals from further phylogenetic inference analysis, a SNP calling procedure was implemented with the HaplotypeCaller tool to apply hard filtering parameters on the raw SNP sets (QD ≥ 10, FS ≤ 35 MQ ≥ 30 MQRankSum ≥ -12. 5 and ReadPosRankSum ≥ -8) with a minimum depth of 20 reads. This procedure excluded 1354 putative heterozygous sites, and retained 72% of the putative SNP sites (3052 out of 4234 SNPs). Nucleotide diversity and Tajima's D were computed by sliding windows of 100 bp using vcftools v. 0. 1. 15  63. A PCA was performed on genotypes using the SNPrelate package 64 in R version 3. 5  65. A consensus fasta sequence was subsequently generated with GATK FastaAlternateReferenceMaker for each sample using the filtered variant set, which was used for the phylogenetic analyses.
05, P = 0. 55; Supplementary Fig. 21 ). The pairwise sequence divergence between individual samples was calculated using the Hamming distance, i. e. , 1-IBS, using PLINK  66  , considering the only individuals with a mean coverage above 2. 5× as failure to do so yielded biased estimates (Supplementary Note 1, Supplementary Fig. 22 ). A neighbour-joining tree of Hamming distances calculated from the nuclear DNA genotypes was built using the R package ape  67. PCA on genotypes inferred from GLs of the 223 samples was generated using ANGSD ngsCovar, filtering for sites with base and mapping quality phred scores < 30, minimum depth of five reads, and a SNP p value (as computed by ANGSD) below 10 -3. Clustering was robust to coverage variation and closely matched the PCA from the VQSR-called SNP genotypes (Supplementary Fig.
Mutation density along the sequence mirrors either recent (long tract of limited diversity) or older (enrichment in heterozygosity over short distances) events. MSMC2 was applied to individuals with a mean coverage above 10×, limiting the analysis to six isolates (FRA. 1, GUA, IND, MOR, NAM, STA. 1), and considering four haplotypes per isolate. Beagle v4. 1 was used to impute missing genotypes and to establish phase in VQSR SNP calls (Supplementary Note 2). Imputation accuracy analysis revealed a 7. 2% and 9. 0% discordance rates at the individual and site levels, respectively (Supplementary Fig. 25 ). Migration scenarios between populations were determined using the forward simulation framework implemented in δaδi  74  as outlined in the Supplementary Methods section. Under a given evolutionary scenario, this software models the expected joint site frequency spectrum between multiple populations using a diffusion equation.
1% of selection scores were deemed significant. Genetic analysis of benzimidazole-and ivermectin resistance. The genomic coordinates of Hco-btub-iso-1 were determined by blasting the gene coding sequence from WormBase Parasite 75 against current genome assembly (BLASTN, e value < 10 -50 ). The SNP positions associated with codons 167, 198 and 200 was determined to be at 7027535, 7027755 and 7027758 bp, respectively, along chromosome I after aligning the Hco-btub-iso-1 consensus sequence and published sequence (GenBank accession FJ981629. 1) using muscle v3. 8. 31  68. Genotype and GLs at these positions were determined with ANGSD  62. Genotypes were only considered for GL > 60% (n = 74), as coverage bias occurred otherwise (Supplementary Table  4  and Supplementary Fig. 12 ). For these samples, phased and imputed genotypes from VQSR SNPs spanning the Hco-btub-iso-1 locus were used to compute pairwise number of allele differences.
Selection in the vicinity of the Hco-btub-iso-1 locus was assessed by computing Tajima's D with ANGSD  62. For benzimidazole-resistant isolates, neutral state was built with ms 76 by simulating 10-Kbp wide isolate-specific sequences (n = 1000) following the same coalescent scenario as predicted by MSMC2 for chromosome I (considering a recombination rate of 1. 83 cM/Mbp 13 ). Suitable ms input parameters were derived from MSMC2 output files using the msmc2ms. py script from msmc-tools. This approach was implemented for isolates with sufficient mean depth of coverage, i. e. , three benzimidazole-resistant isolates. In case of susceptible isolates, the lack of significant departure in the Hco-btub-iso-1 vicinity relative to the rest of chromosome I was tested. The introduction of resistant haplotypes from France mainland into Guadeloupian worm isolates was tested by a topology weighting analysis implemented with TWISST  77.