dataesr/scientific-paragraphs-categorization huggingface dataset:
aegypti divergence scenario. All three topologies showed the Thai-American clade as a sister clade to the Cambodian clade, and only the relationships inside the American clade alternated. This analysis provides additional evidence of the unlikely phylogenetic congruence between CFAV and A. aegypti in Southeast Asia. Finally, we examined whether CFAV had recombined with other cISFs. We aligned all publicly available cISF full or nearly full ORF sequences (https://github. com/artembaidaliuk/CFAV-cISF-phy logeny-2019. git), by splitting them into individual genes and concatenating the amino-acid-guided nucleotide alignments into the full-ORF alignment. Recombination tests detected 10 putative recombination events (Supplementary Fig. S2B ), of which none could explain CFAV divergence in Southeast Asia.
Discussion In this study, we generated six novel full-genome CFAV sequences by sequencing three new virus isolates and subjecting two wild-caught mosquito samples and one recently colonized mosquito to untargeted viral metagenomics. In addition, we de novo assembled two full-genome CFAV sequences from deepsequencing datasets in which CFAV had been previously detected. We combined these newly obtained CFAV genome sequences with published ones to perform the first phylogenetic analysis of CFAV genetic diversity at a global scale. Overall, we found that despite some degree of geographical clustering among CFAV sequences, there were also notable discrepancies between geographical and phylogenetic distances. For instance, two CFAV sequences initially detected in Miami, Florida, USA within the same study  (Metsky et al.
2017)  fell into two distinct clades (Fig. 2 ; Supplementary Fig. S3 ). Likewise, two of the three CFAV sequences originating from the same city in Brazil clustered together with most other American sequences, whereas the third one was phylogenetically distant (Fig. 2 ; Supplementary Fig. S3 ), as was previously noticed  (Fernandes et al. 2018). CFAV sequences originating from the Americas, which were the most represented in our dataset, were divided into two major clades. One clade grouped with the only CFAV genome sequence from Uganda, and the other clade included sequences from Thailand, Indonesia, and Australia (Fig. 2 ; Supplementary Fig. S3 ). Such examples of high phylogenetic divergence observed for CFAV strains originating from the same locality indicate that the genetic structure of CFAV genetic diversity does not simply reflect geographical distance and point to a high degree of genetic mixing.
It is worth noting that several of the CFAV sequences that we used in our phylogenetic analysis were derived from untargeted viral metagenomics of wild-caught mosquitoes or an early-generation laboratory colony. We observed that these CFAV sequences were typically associated with larger amounts of minority variants than CFAV deep-sequencing datasets generated from cell-culture isolates (Supplementary Fig. S1 ). We cannot exclude that some of these sequences may reflect chimeric assemblies from mixed CFAV infections or pooled single infections. Moreover, the well-known presence of CFAV-derived endogenous viral elements in mosquito genomes  (Crochu 2004; Whitfield et al. 2017 ) may also contribute to produce chimeric sequences. Although such methodological issues are unlikely to explain all the phylogenetic discrepancies, the high phylogenetic divergence of some CFAV strains should be considered with caution.
$50% in nonstructural ORF regions). This could reflect the ancient nature of the recombination event, which would have occurred before the separation of the Culicini and Aedini tribes. Alternatively, the recombination event could be more recent but the true members of the recombination triplet would not have been present in the dataset tested. Recent CFAV detection in Culex mosquitoes  (Fernandes et al. 2018 ) provided circumstantial evidence that coinfection and potential recombination with Culex-associated flaviviruses is possible, but the likelihood of such event is yet to be investigated. Although the evolutionary history of CFAV in Southeast Asia remains obscure, our results revealed that the patterns of CFAV genetic diversity in Southeast Asia, and presumably in other parts of the world, do not merely reflect the population genetic structure of A.
aegypti. It is possible that CFAV was introduced multiple times in Southeast Asia through reintroductions of A. aegypti after it was already established in the region. The virus could have persisted by vertical transmission even if the introgression events did not leave a clear signal of admixed ancestry. Alternatively, the virus may have been horizontally transferred to A. aegypti from other mosquito species. Addressing these hypotheses will require further studies on CFAV host range, transmission routes, and genetic diversity. The rapid accumulation of full-genome sequences for cISFs in publicly available databases, such as the ones provided in this study, shed new light on the evolutionary history of cISFs and flaviviruses in general. For instance, we detected phylogenetic evidence of recombination between CFAV and Culex-associated cISFs with a breakpoint between structural and nonstructural parts of the polyprotein ORF.
Acknowledgements We thank  Catherine Lallemand  for assistance with mosquito rearing, and  Jeff Powell ,  Carla Saleh , and  Marie Flamand  for their insights. We are grateful to  Martin Mayanja  and  Julius Lutwama  for providing the original mosquito colony from  Uganda. We thank  Gordana Ra  si c,  Lı ´cia Natal Fernandes ,  Bronwyn MacInnis , and  Hayden Metsky  for providing CFAV sequences. We thank  Oliver Pybus ,  Peter Simmonds ,  Xavier de Lamballerie , and one anonymous reviewer for their insights and constructive suggestions on earlier versions of the manuscript. This work was supported by  Agence Nationale de la Recherche  (grant numbers  ANR-16-CE35-0004-01  and  ANR-17-ERC2-0016-01 ), the  French Government 's  Investissement d'Avenir program Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases  (grant number  ANR-10-LABX-62-IBEID ), the  INCEPTION program (Investissements d'Avenir  grant number  ANR-16-CONV-0005 ), the  City of Paris Emergence(s) program in Biomedical Research , and the  European Union Seventh Framework Programme  ( FP7/2007/ 2011 ) under Grant Agreement  282378.
Data availability All novel sequencing data are available from the SRA database under accession number PRJNA556544 and in the ENA database under accession numbers PRJEB33801 (LR694072, LR694073, LR694074, LR694075) and PRJEB33690 (LR694076, LR694077, LR694078, LR694079, LR694080, LR694081).
Tests were performed after euthanizing the mice in each group. All heads were scanned using the same parameters (pixel size 9 μm, 50 kV, 0. 5-mm Al filter, 15 min of scanning). The reconstructions were analyzed using NRecon and CTan software (Skyscan, Kontich, Belgium). Three-dimensional visualizations of the heads were obtained using ANT and CTvox softwares (Skyscan, Kontich, Belgium).
Micro-CT Analyses Analyses of bone microarchitecture were performed using a Skyscan 1076 in vivo micro-CT scanner (Skyscan, Kontich, Belgium). Tests were performed after euthanizing the mice in each group. All heads were scanned using the same parameters (pixel size 9 µm, 50 kV, 0. 5-mm Al filter, 15 min of scanning). The reconstructions were analyzed using NRecon (v1. 7. 04) and CTan (v2. 0) softwares (Skyscan, Kontich, Belgium). Three-dimensional visualizations of the heads were obtained using ANT (v1. 10. 7) and CTvox (v3. 0) softwares (Skyscan, Kontich, Belgium). The morphologies of the skull, and upper and lower jaws were evaluated on the basis of certain vertical, horizontal and sagittal cranial measurements (Figure  2b ). The choice of landmarks was based on a pre-existing analysis  [22].
Histology The heads were collected from the euthanized mice and fixed in 4% buffered paraformaldehyde (PFA) in phosphate buffered saline 0. 1M (PBS) for 48 hours (all chemical products from Sigma-Aldrich, Saint-Quentin Fallavier, France). The heads were decalcified in 4. 13% EDTA/0. 2% PFA pH 7. 4 in PBS for four days in a KOS sw10 (Milestone, Sorisole, Italy). The samples were dehydrated and embedded in paraffin or maintained in a PBS buffer solution at 4 • C before cryostat sectioning. Then, 5-µm-thick frontal sections were stained with Masson's trichrome and histological images were acquired using a Nano-Zoomer 2. 0-RS slide scanner (Hamamatsu Photonics, Hamamatsu, Japan) before being visualized and analyzed with the Nano-Zoomer software. Tartrate-resistant acid phosphatase staining was performed as previously described  [14]  to identify the multinucleated osteoclast cells (all chemical products from Sigma-Aldrich, Saint-Quentin Fallavier, France).
However, here we opted for a conservative approach in this complex group, to avoid inclusion of paralogs in our dataset. Analyses of the DNA degradation of the assembled MIGseq loci with mapDamage did not show the usual pattern of deamination at the 5' and 3' ends of fragments (e. g. [49] ), neither for each sample (S7 Fig) nor when considering herbarium and silica samples separately (S8 Fig). Indeed, MIGseq does not use the actual DNA fragments, but amplified ones through the two PCR steps, resulting in consensus sequences that are damage free  [49]. Although this could in theory lead to a bias in fragment representation, it is very unlikely for the SSR sequence (where the primers bind during amplification) is damaged in all DNA fragments in the DNA samples. Therefore, we do not expect a qualitative change in the loci pattern (i.
e. no change in the presence-absence of fragments), but cannot exclude the option that a few fragments were lost due to a lower level of amplification (and were thus removed from the results during the filtering steps). However, the overall absence of damage patterns in our results suggest that MIGseq could be a useful and elegant solution to avoid inclusion of DNA damage in phylogenetic datasets, although further investigation remains necessary to confirm this. The location of MIGseq loci. assessed by mapping them on the genome of the common oak, showed no specific pattern and a distribution of distances showed a global Poisson distribution corresponding to a random distribution (S9A Fig). Of the total 7,371 loci, only 19 could not be mapped on the common oak genome, reflecting the high level of conservation of the genomes in Fagaceae.
According to our expectations, the average number of loci retrieved from silica collections (mean = 695. 71) was slightly higher than those retrieved from herbarium collections (mean = 528. 48), but not significantly different. Difference detected in dataset characteristics (e. g. the number of both clusters and clusters retrieved with high depth, error level, the number of reads assembled in the consensus sequences, and the final number of loci assembled) between herbarium samples and silicadried samples were negligible. However, we retrieved a slightly higher number of raw reads, filtered reads (p = 0. 0169, Fig 4A  and 4B ) and heterozygosity level (p = 0. 0169, Fig  4E ) from herbarium material than from silica-dried samples. The ages of sample material did not strongly correlate with any of the properties of the assembled dataset (maximum r 2 = 0.
Conclusions Natural history collections are storehouses of evolutionary and biological information, constituting exceptional historical investments of time, money and human endeavor spanning centuries  [81]. The world's 3400 herbaria hold an estimated 350 million samples, collected over the last 400 years  [82]. With the rapid development of museomic and novel bioinformatic approaches to process large genomic datasets from a wide range of sources  [83] , the use of specimens that could not be collected nowadays for 'spatial' reasons  [84]  can address evolutionary questions (e. g. this study), resolve taxonomic placements of extinct taxa  [78] , or construct a biodiversity catalogue of an entire flora (e. g. the PhyloNorway project, which aims to build a reference database for all Norwegian vascular plants).
L. Helardot; vouchers lodged at BGT); 8) Vietnam-Dalat University (vouchers lodged at DLU), research and collecting permits issued). On a global scale, our sampling covers 11% of all species described. All vouchers of fresh materials were deposited at the Biodiversity Genomics Team (BGT) herbarium of Guangxi University. We used selected data from a previous study on Quercus to root the Lithocarpus ingroup  [43]. All voucher and collection data are available in S1 Table. DNA extraction and sequencing. Genomic DNA was purified from approximately 10 mg of leaf material using the Plant Genomic DNA kit (TIANGEN Biotech, Beijing, China), following the GP1 protocol. Following the MIGseq methodology and protocol  [54] , we amplified loci in a two-PCR step process. Our protocol followed standard conditions and described primer sequences, with the exception of a DNA starting amount of 50ng, and an increase in cycle number (increased to 27-30 cycles in the first PCR step, see below).
Sequencing was performed by Novogene (Beijing, PR China) on an Illumina HiSeq-Ten-X, according to the manufacturer instructions. Although MIGseq was designed to be highly multiplexed in order to reduce costs, we chose to generate approximately 1Gb of sequences per sample, representing a multiplexing of approximately 96-100 individuals per lane. Indeed, we expected herbarium samples to generate suboptimal DNA quality, thus decreasing the yield of loci at sufficient sequencing depths to be assembled. By generating more data than originally required by the MIGseq protocol, we maximized the potential retrieval of loci in these degraded samples. We performed two technical tests to assess the robustness of the MIGseq protocol, and applied our findings to adapt the protocol to suboptimal samples.
Loci were called only if found in more than 4 species. In the original MIGseq protocol, the authors assembled the loci dataset with STACKS  [56]. However, despite that ipyrad was designed for restriction-based methods, it is in fact more efficient for studies at larger taxonomic scales  [86]. All loci were used for divergence analyses, biogeographic and phylogenomic reconstruction. Because MIGseq loci are not based on direct sequencing of degraded DNA, but on the sequencing of PCR-enriched loci, we did not expect to observe degradation patterns often seen in ancient DNA studies. Indeed, the PCR steps imply that the primer regions are complete and the resulting amplicons have blunt-ends, making them less sensitive to deamination that would occur at both ends of the genomic DNA fragment. To verify our assumption, we used the MapDamage 2.
Phylogenomic analyses and molecular dating We reconstructed a Maximum Likelihood (ML) tree using PhyML 3. 1  [90] [91]  based on the concatenated SNPs found in the assembled loci from ipyrad. The GTR+I+G model was selected, with 4 gamma rate categories. Nodal support was estimated using the SH-like approach  [92] , for which values have been shown to be as conservative as the commonly used non-parametric bootstrap values  [93] , but much faster to compute in larger datasets (>7,000 loci, >73,000 SNPs herein)  [94]. We also reconstructed a NJ tree based on the presenceabsence of loci matrix using the package ape in R 3. 4 (R Core Team 2014) and estimated nodal support by generating 1000 bootstraps. Divergence of each locus was assessed by calculating the pairwise p-distance, then combining all comparisons and scoring them as "intra-zone" or "inter-zone" (see below).
We performed a two-way ANOVA, followed by a Tukey Honest Significant Difference test (Tukey HSD) to identify significantly different pairwise differences among 2 (I-II), 4 (I-IV) and 6 (I-VI) biogeographical zones. All statistical analyses were performed using R v3. 4  [95]. Divergence times were estimated using the Penalized-Likelihood method (PL) implemented in treePL v. 1. 0 [96]. To calibrate the divergence of Lithocarpus from Quercus, we used two Eocene macrofossils attributed to Lithocarpus, namely L. karasorianus and L. timensis from the Fossil Plants database (http://fossilplants. info/index. htm). These two fossils represent well conserved leaves, allowing us to determine they likely represent already derived morphs. In addition to this direct evidence, an Eocene divergence is coherent with previous date estimates in the family (e.
g. (  [62] ). Therefore, we set the minimum age of the divergence of Lithocarpus and Quercus to 33. 9 Ma, with an additional maximum age of 53 Ma, corresponding to the maximum age of the fossil calibration used elsewhere  [97]  for the entire Fagaceae family. To estimate the smoothing parameter, we used a cross-validation, ranging from 100,000 to 0. 001, and then set the value to 0. 01, according to the lowest Chi-square value (11562. 7). Raw reads were deposited to the ENA, under project number PRJEB34850. Alignments and trees were deposited in the Dryad repository (https://doi. org/10. 5061/dryad. xd2547dc8).
9-27. 82 Ma)  [103]  at which time the local conditions resembled a modern day warm monsoonal climate. To explore biogeographic patterns in Lithocarpus spp. , we divided our geographical and species datasets into "continent" and "island" groups and compared whether significant differences in genomic divergence exist between continental and island taxa. Secondly, using existing biogeographical units in the distribution range of Lithocarpus, we divided the area into a) a four zone configuration (Zone I (China, Japan), Zone II (Southeast Asia, India), Zone III (Malesia) and Zone IV (New Guinea)), and b) a 6 zone configuration (as in a) but with Zone III subdivided further according to the definition of the Malesian Floristic Subkingdoms [the Western, Southern and Eastern Divisions respectively, as identified in  [104]  (S3 and S4 Figs).
Patch-clamp Electrophysiology Recordings were made at room temperature using an Axopatch-200B amplifier equipped with a Digidata 1550A and pCLAMP 10. 6 software (Molecular Devices, Sunnyvale, CA, USA). Endothelium was in a standard bath solution containing (mM) 135 NaCl, 4 KCl, 2 CaCl 2 , 1 MgCl 2 , 10 glucose and 10 HEPES (titrated to pH 7. 4 using NaOH). For membrane potential recordings in zero current mode, heat-polished patch pipettes with tip resistances between 3 and 5 MU were used and contained amphotericin B (Sigma-Aldrich) as the perforating agent, added to a pipette solution containing (mM) 145 KCl, 1 MgCl 2 , 0. 5 EGTA and 10 HEPES (titrated to pH 7. 2 using KOH). Outside-out and cell-attached membrane patch recordings were made using the same equipment but in voltage-clamp mode.
Intracellular Ca 2+ Measurement Measurements were made at room temperature on a FlexStation 3 (Molecular Devices, California) bench-top fluorometer controlled by Softmax Pro software v5. 4. 5. Cells were plated in clear 96-well plates (Corning, NY, USA) at a confluence of 90% 24 hours before experimentation. Cells were incubated with fura-2AM (2 mM) (Molecular ProbesTM) in SBS containing 0. 01% pluronic acid (Thermo Fisher Scientific) for 60 min at 37 C. Cells were washed with SBS for 30 min at room temperature. Baseline fluorescence ratios were recorded before the addition of the compound solution to the cell plate after 60 s, with recording thereafter for a total of 300 s. The Standard Bath Solution (SBS) contained: NaCl 135 mM, KCl 5 mM, MgCl 2 1. 2 mM, CaCl 2 1. 5 mM, D-glucose 8 mM and HEPES 10 mM.
PIEZO1 Channel Modeling Structural data were obtained from the mouse cryo-EM structure PDB: 6B3R  (Guo and MacKinnon, 2017). A total of 58 missing residues (~2. 3% of the overall protein length) were added with MODELER (v 9. 19)  (Fiser and Sali, 2003; Sali and Blundell, 1993). These residues are  601-604, 876-879, 887-891, 1998-2014, 2066-2074, 2412-2423, 2457-2462  and 2547 (see Figure  S7 ). The loop refinement tool was used to remove a knot in one chain between residues 2066-2074. The loop was selected out of 10 candidates according to the discrete optimized protein energy method  (Shen and Sali, 2006). The final PIEZO1 mouse model does not comprises the first N-terminal 576 residues and residues  718-781, 1366-1492, 1579-1654, 1808-1951. Therefore, each chain is composed by five non-overlapping fragments: residues  577-717, 782-1365, 1493-1578, 1655-1807 and 1952-2547.
Trajectory Analyses and Molecular Graphics Root mean-square deviation (RMSD) and root mean-square fluctuation (RMSF) were performed using the g_rms and g_rmsf tools from the GROMACS package. The analysis suggested a stable structure (Figure  S7 ). Molecular graphics were generated with the VMD 1. 9. 3  (Humphrey et al. , 1996 ; http://www. ks. uiuc. edu/Research/vmd/) and data were plotted using Grace (https:// plasma-gate. weizmann. ac. il/Grace/). For the calculation of dome depth, the simulation trajectory was fitted to the protein coordinates (reference structure). The coordinates of the CG phosphate particles in each frame of the fitted trajectory were extracted by a Python script. The phosphate particles were then used to separate the bilayer leaflets using a branching network algorithm.
QUANTIFICATION AND STATISTICAL ANALYSIS Genotypes of mice were always blinded to the experimenter and mice were studied in random order determined by the genotype of litters. Data were generated in pairs (control mice and Smpd3 fro/fro mice) and datasets compared statistically by independent t test without assuming equal variance. Paired t tests were used when comparing data before and after application of flow or a substance to the same membrane patch or cell. One-way ANOVA followed by Tukey posthoc test was used for comparing multiple groups. Statistical significance was considered to exist at probability (P) < 0. 05 (* < 0. 05, ** < 0. 01, *** < 0. 001). Where data comparisons lack an asterisk, they were not significantly different. The number of independent recordings is indicated by n and the number of mice per dataset by N (in total, murine data are from n = 278 recordings and N = 105 mice).
All recordings were in the presence of 10 mM GW4869 and the absence (D) or presence of 10 mM ceramide (E), 10 mM 2-methacryloyloxyethyl PC (PC) (F), or 10 mM sphingomyelin (G). (H) Recording in vehicle-control conditions. (I) For experiments of the type exemplified in (D)-(H), mean ± SEM current amplitude normalized to the maximum at À40 mmHg plotted against the amplitude of the pressure step. Data are shown for vehicle control (black), in the presence of 10 mM GW4869 (red), in the presence of 10 mM GW4869 and 10 mM ceramide (green), in the presence of 10 mM GW4869 and 10 mM 2-methacryloyloxyethyl PC (PC; blue), and in the presence of 10 mM GW4869 and 10 mM sphingomyelin (cyan). Each dataset is for n = 6 recordings and N = 3 mice. (J) Generated from the data shown in (I); mean ± SEM pressure for half-maximal activation (P 1/2 ).
ACKNOWLEDGMENTS The research was supported by a  British Heart Foundation   Intermediate Research Fellowship  to J. S. ; Wellcome Trust Investigator and  British Heart Foundation  programme grants to D. J. B. ; an  Academy of Medical Sciences  and  Wellcome Trust   Springboard Award  to A. C. K. ; and INSERM funding to M. R. , A. N. S. , and N. A. A. J. H. was supported by a  BBSRC   PhD Studentship  and J. C. by a  MRC Clinical Research Training fellowship.