dataesr/scientific-paragraphs-categorization huggingface dataset:
Interestingly, members of the pVOG9714 are most similar to the origin-binding protein (UL9) of eukaryotic herpesviruses (Pfam id: PF02399). We predict that pVOGs 1685 and 9714 represent a novel family of helicases specific to viruses and plasmids (Fig. S5 ). Finally, six proteins correspond to a unique fusion of the primase domain with the PriCT-1 and a domain homologous to the replication protein O of bacteriophage λ (Pfam id: PF04492). Protein O initiates replication of bacteriophage DNA by interacting with the replication origin  [46]. Conceivably, the C-terminal O-like domain recruits the primase to the replication origin, where it initiates the primer synthesis.
To further explore the provenance of the PriCT domains, we performed both sequence profile-based and structure-based analysis of PriCT domains. When the PriCT-2 sequence profile from Bacillus badius (WP_063441057) was used as a query, HHsearch found Fe-S domain of archaeal PriL (CDD: PRK02249) with high probability of 95% and aligned two of its four cysteine residues (Fig. S6 ). Structural modeling and structure similarity search using Dali server have further supported the PriCT-2 structural similarity to the larger domain of the PriL C-terminal region (Fig. 7 ; Tables  S2  and S4 ). Taken together these observations suggest that PriCT-1 and PriCT-2 are related to each other and to PriL Fe-S_N. Moreover, all three of them are structurally similar (Table  S4 , Fig. 7 ) to PriX, the recently identified non-catalytic subunit of the archaeal primases essential for efficient primer synthesis  [48].
Concluding Remarks and Evolutionary Considerations The diversity and abundance of AEP homologs in bacteria is rather astounding, especially considering that AEPs belong to the core DNA replication machinery of archaea and eukaryotes, but not bacteria, which instead use DnaG family primases. In this study, using an archaeal primase-polymerase PolpTN2 as a seed for sequence similarity searches, we recovered over 800 AEP homologs in bacteria from 12 highly diverse phyla, including not only those overrepresented in genomic databases, such as Proteobacteria, Firmicutes, and Actinobacteria, but also those from less sampled phyla, such as Deinococcus-Thermus, Fusobacteria, and Verrucomicrobia. Notably, for our searches, we used a protein database that was filtered to 70% identity (i. e. , all sequences that were more than 70% identical to any other sequence in the database were removed), suggesting that the actual number of PolpTN2-like bacterial AEP sequences is considerably greater.
Sequence searches and clustering Initially, the primase domain of PolpTN2 (YP_003603593. 1, 1-257 aa) was used as a query to search for homologs in the nr70 database with Jackhmmer  [54]. After seven Jackhmmer iterations, significantly (E-value ≤ 1e -03) matching sequences were extracted and grouped using CLANS  [24]. Major groups of PolpTN2 primase domain homologs were then identified using CLANS convex clustering algorithm at P-value = 1e-09. Next, sequences from the resulting groups were extracted and merged with homologs of well-characterized members of the AEP superfamily. The latter sequences were retrieved from uniref50 database using seven Jackhmmer iterations. All the merged sequences were then again grouped using CLANS. The list of PrimPol-PV1 sequences used for CLANS clustering is available for download (Supplementary data file 3).
Domain identification To identify the primase domain, sequences in each group of PolpTN2 homologs were aligned using MAFFT  [56]  optimized for accurate local alignment (option "L-INS-i"). Next, sequence regions longer than 50 residues on either side of the primase domain were extracted for domain identification. For every such region, we generated sequence profile by running two iterations of Jackhmmer  [54]  against the nr70 sequence database (the NCBI "nr" database filtered to 70% identity) using E-value = 1e -03 or a more stringent inclusion threshold. The resulting profiles were used to search against profile databases with HHsearch  [57].
Analysis of residue coevolution Covariation analysis was performed using PSICOV  [60]  and PLMC script from EVmutation package  [61]. Initial sequence alignment was generated by Jackhmmer after 10 iterations against nr70 database using PolPTN2 primase domain as a query. Sequences containing gaps in positions 179 or 231 were removed from the alignment. Final alignment used by PSICOV and PLMC had 1427 sequences. Covariation scores are available for download (Supplementary data file 2).
Identification and annotation of integrated MGEs The integrated MGEs were identified by thorough analysis of genomic neighborhoods of the AEPencoding genes. The precise borders of integration were defined based on the presence of direct repeats corresponding to attachment sites. The repeats were searched for using Unipro UGENE  [62]. Genes of integrated MGE were annotated based on the PSI-BLAST searches  [63]  against the non-redundant protein database at NCBI and HHpred searches  [57].
Acknowledgments This work was supported by the  bilateral Lithuanian-French program  " Gilibert. "D. K. was partly supported by an  EMBO  short-term fellowship ( ASTF 82-2016 ). P. F. is supported by a  European Research Council  grant from the  European Union 's  Seventh Framework Program  (FP/2007-2013)/Project EVOMOBIL- European Research Council  Grant Agreement No. 340440.
Statistical analyses Data were analysed using R statistical software (https:// cran. r-project. org). The relationships between HGP and other categorical variables were evaluated by the Chisquare test. The survival analyses included OS, 5-year survival, and disease-free (metastasis-free) survival (DFS). Patients were censored when alive at last follow-up or when lost to follow-up. OS was defined as the difference between time of metastasis (OS metastasis) and time of death or last follow-up or the difference between time of diagnosis of the primary UM (OS primary) and time of death or last follow-up. Differences in survival were calculated using log-rank test. Univariate and multivariate hazard ratios (HR) were calculated using Cox proportional hazards model. All statistical tests were considered significant with P value <0.
Acknowledgements This work was supported by the  French National Research Agency  through the  'Investments for the Future' program  ( France-BioImaging ,  ANR-10-INSB-04 ). We acknowledge the  PICT-IBiSA , member of the  France-BioImaging national research infrastructure , supported by the  CelTisPhyBio Labex  ( N ANR-10-LBX-0038 ) part of the  IDEX PSL  ( N ANR-10-IDEX-0001-02 PSL ).
Determination of gut volume. Raw 2D images of the guts were processed to erase the hindgut, stomach and any residual tissue around the axially-symmetric midgut (segment comprised between caecal appendix tip to duodenum-stomach junction). We then thresholded these images and extracted the midgut contour (Matlab routine). We next applied a Voronoi algorithm  42  to this contour to obtain the gut midline length and diameters along the midline. The volume is computed by integration of this data. We neglect the volume occupied by the lumen (<5% at E8 and E8+ 48 h culture, e. g. see Fig. 7a ). We also resorted to a second, different procedure (Olaf plugin)  43  which relies on manually fitting the gut contour with Bezier curves; the plugin automatically produces a 3D axisymmetric volume from the Bezier fit.
Acknowledgements This research was funded by  Agence Nationale de la Recherche (ANR)  through " Initiatives d'Excellence "  Idex  ( ANR-11-IDEX-0005-02 ), and " Labex Who Am I?"  ( ANR-11-LABX-0071 ). We thank  Olivier Cardoso  ("Olaf " plugin developer),  François Gallet  for proofreading,  Vincent Fleury  for proofreading and providing equipment and lab space to perform the experiments.
2015) , its routine use is hindered by the need for a more extensive characterization of spectral properties of existing fluorescent probes. Recent developments in far-red two-photon excitation make the need for an update of the spectral characteristics of fluorescent probes even more acute  (Herz et al. 2010; Mojzisova and Vermot 2011). While commercial and academic databases of one-photon absorption spectra are well documented, the two-photon specifications of most probes are only scarcely documented, despite a small number of helpful initiatives  (Bestvater et al. 2002; Cahalan et al. 2002; Drobizhev et al. 2011; Mütze et al. 2012; Romanelli et al. 2013; Lim and Cho 2013). In this review, we provide a comprehensive list of two-photon-related spectral and biological properties of more than 280 fluorescent probes, and discuss different routes of delivery of such probes into laboratory animals, as well as their actual or prospective relevance to in vivo multicolor TPM of cells, structures, and functions, in the healthy and diseased brain.
Tables  2 to 8 ), a description of different routes of in vivo delivery of these fluorophores (cf. Table  1 ), recommendations for the design of intravital multicolor TPM microscope setups, and a discussion about strategies of data post-processing. Taken together, this database and set of recommendations will help scientists design intravital TPM experiments focusing simultaneously on biological targets of diverse natures, ranging from cells (e. g. , neurons, astrocytes) and sub-cellular structures (e. g. , DNA, organelles) to functional processes -whose exploration greatly benefits from the optogenetics technology -(e. g. , ion transport, membrane potential), and through chemical or environmental parameters (e. g. , mechanical strains, pH) or even potentially connectomics  (Nemoto et al. 2015).
Funding: CH is supported by a  F30 Fellowship  ( NS093719  from  NIH NINDS) , as well as the  UCLA   Medical Scientist Training Program  ( NIH NIGMS  training grant  GM08042 ). CP-C is supported by  W81XWH-14-1-0433  ( USAMRMC, DOD ), a  Developmental Disabilities Translational Research Program grant  (# 20160969  from  John Merck ),  SFARI  Awards  295438  and  513155CP  ( Simons Foundation ) and  5R01HD054453  ( NICHD/NIH). GL is supported by the  Agence Nationale de la Recherche  ( ANR-15-CE37-0004  " SmellBrain " &  ANR-15-NEUC-0004  "Circuit_OPL").
For the analysis of the microtubule dynamics the plusT-ipTracker software  67  and the GFP-EB3 video time-lapse images were employed. We first adjusted the accuracy of the GFP-EB3 detection, and then analyzed the following parameters: growing and shrinking speed; growth and shrinking mean length; percentage of time in pause, growing and shrinking; distribution of microtubules based on their speed and length; catastrophe frequency and rescue frequency. These parameters were chosen based on previous studies  68, 69. To ensure the accuracy of the analysis, we compared the growing speed data obtained both automatically and manually. The microtubule curvature analysis was performed using the first image of each video time-lapse with m-cherry α-tubulin. Additionally, with the GFP-EB3 labeling experiment we obtained the maximum projection of the entire video time-lapse, allowing us to reconstruct the trajectories of the microtubules, whose curvature was also analyzed.
Thus, the curvature of microtubules was analyzed both in a static way and within their trajectory of movement. Curvature (k) was determined using the Mathematica software (Wolfram Research Europe, UK). After obtaining the equation of each microtubule with a spline cubic interpolation, the general formula of curvature  70  was employed to analyze each microtubule (equation 1): where (equations 2, 3, 4 and 5) = ′ ″ -′ ″ ′ + ′ k x y y x x y ( ) (1) ′ = x dx dt , (2) ″ = x d x dt , (3) 2 2 ′ = y dy dt , (4) ″ = y d y dt , (5) 2 2 i. e. , the first ( ′ ′ x y , ) and second ( ′′ ′ x y , ) derivatives at each point.
The final value for each animal used to compare was the mean of all Purkinje cells analyzed in these three sections. The morphological parameters studied were selected in basis to its meaning for PCs function  77, 78  : (1) the length and width of the main dendrite; (2) the length of the dendritic arbor of the PCs (measured indirectly through the molecular layer thickness); and (3) the soma size. Morphological analyses were carried out with the Neurolucida (MBF Bioscience, Williston, Vermont, USA) and ImageJ (NIH, USA) software, as previously described  77. Behavioral analyses. We characterized the effects of progressive cerebellar defects on motor, cognitive, and social processes. Behavioral analyses were performed at P15, P17, P22 and P30, encompassing both the pre-neurodegenerative (P15-P18) and neurodegenerative (P18-P30) stages.
Acknowledgements This work was supported by the  MINECO  ( SAF2016-79668-R ; to EW and  MTM2014-57129-C2-1-P  to JMMC), the  Regional Government of Castile and Leon  ( SA178U13  and  SA030P17  to EW and RMC), the  Centre for Regenerative Medicine and Cell Therapy of Castile and Leon (EW) , the  Samuel Solórzano Barruso Memorial Foundation  ( FS/3 2014  to DD), the  Foltra Foundation (DD) ,  INSERM ,  ARC  ( Association pour la Recherche sur le Cancer  grant  n°SFI20111204053  to MJM),  La Ligue contre le Cancer comités Savoie/Isère  ( MJM ),  ANR Blan07-2_187328 'TyrTIPs' (AA)  and  INCA   PLBIO10-030  ' TetraTips ' (AA). The authors express their gratitude to  E. J. Keck  for the English language editing.
Acknowledgements We thank  Denis Headon  for providing Edar DlJ mutant,  Irma Thesleff  for providing Edar probe. We acknowledge the contribution of  SFR Biosciences  ( UMS3444/CNRS ,  US8/Inserm ,  ENS de Lyon, UCBL)  facilities: PLATIM and PBES and warmly thank their respective staff for their constant help. We thank  Nicolas Gadot  and the  ANIPATH facility  for related work. We thank  Neal Anthwal  for helpful comments on the manuscript.
Discussion The new member of the PARP family, PARP3, was initially found when searching the expressed sequence tag library of the GenBank database using the sequence of the catalytic domain of hPARP1  14. Analysis of the human gene revealed the existence of two proteins as alternative splicing variants that differ by 7 aa at the N-terminus  15. The long splice variant was identified as a core component of the centrosome at all stages of the cell cycle, whereas the short isoform accumulates within the nucleus  15. During interphase in human somatic cells, PARP3 is primarily localised in cytoplasm and nuclear punctae  16. Interestingly, overexpression of PARP3 or its N-terminal domain leads to G1/S cell cycle arrest even in DNA-damaged human cells  15. At the same time, PARP3 is not essential for G2/M cell-cycle checkpoint after ionising radiation  17.
Materials and Methods Materials. The synthetic oligonucleotides were obtained from Biosset (Novosibirsk, Russia). The reagents for electrophoresis and the basic components of buffers were from Sigma (USA). γ-[ 32 P]-ATP and α-[ 32 P]-ATP (with specific activities of 5000 and 3000 Ci/mmol, respectively) were from the Laboratory of Biotechnology (Institute of Chemical Biology and Fundamental Medicine, Novosibirsk, Russia). T4 polynucleotide kinase was from Biosan (Novosibirsk, Russia). Ultrapure dNTPs/ddNTPs/NTPs/NAD + were from Promega (USA). SUMO fusion expression vector pETHSUL (GenBank: EF205333. 1) and pSUPER vector coding for the catalytic domain of the S. cerevisiae SUMO hydrolase dtUD1 were kindly provided by Dr. P. Loll (Drexel University, Philadelphia, USA). His 6 and Strep-II double-tagged dtUD1 hydrolase was expressed and purified as described in ref.
01, 0. 05, 0. 1, 0. 5 or 1 µM PARP3 and various concentrations of NAD + : 1-1000 µM. The reaction mixtures were incubated for 30 min at 37 °С then terminated by adding the 5x gel loading solution (90% formamide, 0. 1% xylenecyanole and 0. 1% bromophenol blue) and heating at 85 °C for 2 min. The mixtures were resolved on a 20% polyacrylamide gel containing 7 M urea and 10% formamide in 1x TBE buffer. The gels were dried and subjected to autoradiography and/or phosphorimaging for quantitation using the Typhoon imaging system from GE Healthcare Life Sciences and analysed using OriginPro7. 5, Microcal Software, USA. Purification of PARP3-modified oligonucleotides. The reaction was carried out in 400 µL HDB buffer with 2 mM MgCl 2. The mixture containing 1 µM [ 32 P]-DNA substrate gap1, 5 µM PARP3 and 1 mM NAD + was incubated at 37 °C for 45 min, then heated at 80 °C for 5 min and loaded onto a 20% polyacrylamide gel containing 7 M urea and 10% formamide in TBE buffer with 100 µL of 5x loading solution.
Acknowledgements The authors are grateful to  Dr. Murat Saparbaev  ( IGR, France ) for helpful discussions, to  Gabriela Zarkovich  ( CNRS; IGR, France ) for kindly providing PARP3 plasmid and helpful discussion, and to  Dr. Anne-Lise Haenni  ( IJM, France ) for editing the manuscript. This work was supported by grants from  Russian Science Foundation   14-24-0038  and  17-74-20075 (PARP2 purification ) to OIL and EAB, ERA. Net RUS Plus # 306  and  La Ligue Nationale Contre le Cancer "Equipe LNCC   2016 " to A. A. I. (protein purification).
After domestication 11 000 years ago in Asia Minor, the goat followed human migration to Europe and Asia. It was then introduced in Africa and is now raised all over the world. In this study, we exploited a dataset composed of 54 000 SNPs (Illumina goat DNA chip) to analyze the genetic diversity of 223 individuals belonging to eight French breeds (Alpine, Angora, Corse, Foss es, Poitevine, Provenc ßale, Pyr en ees and Saanen). Analyses carried out included individual-based approaches (principal component analysis and population structure) and population-based approaches (phylogenetic tree constructions). The results of the genetic diversity analyses revealed that French breeds are clearly differentiated, in particular, the Angora breed that originates from south west Asia. The Provenc ßale breed shows a very original genetic pattern that could be the result of ancient admixture.
Biological samples Based on pedigree records, 269 a priori minimally related individuals from eight French caprine breeds were selected and genotyped using the GoatSNP50 BeadChip (Illumina, Inc. ) developed by the International Goat Consortium  (Tosser-Klopp et al. 2014). Original marker positions were remapped on the recent goat reference sequence ARS1  (Bickhart et al. 2017). Quality control of the dataset was performed using PLINK v1. 90 beta  (Purcell et al. 2007; Yang et al. 2011; Chang et al. 2015). SNPs with a call rate greater than 0. 95 and a minor allele frequency (MAF) greater than 0. 05 were kept. Within each breed, we identified a set of unrelated individuals by pruning pairs of individuals that had a genomic kinship coefficient greater than 0. 2  (Rochus et al. 2018 ). After quality control, 46 065 SNPs and 223 animals from eight French caprine breeds were kept.
Genetic diversity analysis For each population, PLINK software was used to calculate two estimators of the inbreeding coefficient of each individual: F IS using the --het small-sample option and F ROH using the --homozyg command. PLINK was also used to perform a principal component analysis (PCA) using the --pca command. A model-based population structure analysis was performed using ADMIXTURE v1. 23  (Alexander et al. 2009 ). The optimal partitioning was evaluated by cross-validation with the number of hypothetical populations K ranging from 1 to 9 (Fig. S1 ). Reynolds' distances  (Reynolds et al. 1983)  were computed between all pairs of populations. The population tree was constructed by applying neighbor-joining (Saitou & Nei 1987) on the Reynolds distances as described by  Bonhomme et al.
(2010). These analyses were performed using HAPFLK v. 1. 3. 0  (Fariello et al. 2013). We also computed Weir and Cockerham F ST values  (Weir & Cockerham 1984)  between all pairs of populations using the HIERFSTAT R package  (Goudet 2005). To evaluate possible admixture events between populations, a maximum likelihood tree was estimated using TREEMIX v. 1. 12 (Pickrell & Pritchard 2012). The optimal number of admixture events inferred by the software was evaluated by measuring model fit as explained by  Pickrell & Pritchard (2012). The fraction of the variance in relatedness between populations that is accounted for by the models, f, was calculated for models with an added migration event number ranging from 0 to 10 (Fig. S2 ).
Selection signatures analysis Six breeds were used for the selection signatures analysis: Alpine, Corse, Foss es, Poitevine, Pyr en ees and Saanen. The Provenc ßale and Angora breeds were not included in the analysis for reasons explained in the Results section. We considered selection signatures leading to excess differentiation in allele or haplotype frequencies between populations. Specifically, the FLK (single SNP approach) and hapFLK (haplotypic approach) tests were performed using HAPFLK v. 1. 3. 0. The number of haplotype clusters used for the hapFLK genome scan was set at 40, as determined by the FASTPHASE cross-validation procedure  (Scheet & Stephens 2006). The P-values and significance of each statistic at each SNP were re-estimated following  Fariello et al. (2014)  and as indicated in the software documentation.
Tests were considered significant at the 10% false discovery rate level, estimated using the R BIOCONDUCTOR Q-VALUE package  (Storey et al. 2015). For each significant region, local trees were computed from the FLK and hapFLK statistics  (Fariello et al. 2013)  to highlight which population had most likely been selected on, using scripts provided on the HAPFLK web page. In parallel, allele frequencies of each population at each SNP were investigated using PLINK for each significant region. Candidate genes corresponding to protein-coding genes were extracted from the feature table of the reference caprine genome (ftp://ftp. ncbi. nlm. nih. gov/genomes/refseq/ vertebrate_mammalian/Capra_hircus/latest_assembly_ver sions/GCF_001704415. 1_ARS1) for each significant region. Some of these genes were considered selection candidates based on their physical proximity to the most significant SNP and on their referenced biological effects in the literature.
A representation of the first and second principal components of the PCA is provided in Fig. 1. The first component explained 36. 6% of the genetic variance in the dataset, corresponding to the divergence between Angora and the indigenous breeds (Alpine, Corse, Foss es, Poitevine, Provenc ßale, Pyr en ees and Saanen). The second component explained 13. 9% of the genetic variance and separated the Poitevine and Saanen. The other components (Fig. S4 ) explained less than 13% of the genetic variance and corresponded to the successive separations of the other breeds, which revealed a clear genetic structure in the dataset. The cross-validation procedure of ADMIXTURE software (Fig. S1 ) gave an optimal number of eight hypothetical populations, K, corresponding to the lowest cross-validation error (0.
Discussion In this study, we conducted an analysis of the genetic relationship among goat populations raised in France and identified five genomic regions that appear as selection signatures. For these two objectives, our results must be interpreted with caution for two main reasons. First, the individuals sampled were selected to ensure the representativeness of each breed, and we minimized the relationship between animals in the data by eliminating close relatives. However, the number of individuals within each breed remained rather small (about 28 individuals on average), although that is typical for such studies. In particular, due to the lack of knowledge of the pedigree for three breeds (Foss es, Provenc ßale and Pyr en ees), we eliminated several closely related individuals, leading to a reduced sample size (fewer than 20 animals).