dataesr/scientific-paragraphs-categorization huggingface dataset:
bock@ign. fr At the beginning of the COST action, with updates in the course of the action, an inventory of available GNSS, VLBI and DORIS reprocessed ZTD and IWV datasets was carried out. For each dataset in the inventory the following information is reported: • Network coverage (global, Europe, other regions, national, campaigns) and number of stations, • Availability of RINEX data, • Availability of ZTD, horizontal gradients and IWV estimates, • Data file format, • Archive address (url, ftp) & type of access, WP3. 4 GNSS and climate research: aimed at conducting studies of IWV trends and variability using GNSS data as well as other observations, reanalyses and climate model simulations. WP3. 5 Database, formats, and dissemination: aimed at providing support to other WPs, develop a GNSS/climate database and update SINEX tropo format in cooperation with IAG, IGS, and EUREF.
It is worth noting that cooperation was established with experts from GRUAN, GEWEX, WMO, ECMWF, previous COST Action HOME, and results were communicated in climate meetings from EGU, AGU, EMS, GEWEX, IAMAS, among others. At the end of the Action, both a global reference GNSS IWV dataset (1995-2010) and a European reference ZTD dataset (1996-2014) were established. 5. 2 Available Reprocessed ZTD and IWV Datasets 5. 2. 1 Inventory of Available Reprocessed ZTD Datasets F. Ahmed Geodesy and Geospatial Engineering, Institute of Civil Engineering and Environment, University of Luxembourg, Luxembourg City, Luxembourg e-mail: furqan. ahmed@csr. utexas. edu.
five Analysis Centres homogenously reprocessed the EPN network for the period 1996-2014. Both individual and combined tropospheric products(Pacione et al. 2011)along with reference coordinates and other metadata, are stored in SINEX TRO format,Gendt (1997), and are available to the users at the EPN Regional Data Centres (RDC), located at BKG (Federal Agency for Cartography and Geodesy, Germany, https://igs. bkg. bund. de/root_ftp/EPNrepro2/products/). For each EPN station, plots on ZTD time series, ZTD monthly mean, comparison versus radiosonde data (if collocated), are publicly available at the EPN Central Bureau (Royal Observatory of Belgium, Brussels, Belgium, http://www. epncb. oma. be/_productsservices/analysiscentres/repro2. php). final IWV dataset is publicly available at: ftp://ftp.
, 2014b). To detect cilia, larvae were incubated with anti-acetylated α-tubulin primary antibody (clone 6-11B-1, Sigma) and AlexaFluor-488 secondary antibody (ThermoFisher) as previously described  (Pennati et al. , 2015). Cell outlines were counterstained with phalloidin AlexFluor-546 conjugate (ThermoFisher) incubated 1:50 for at least 2 hours prior to final washes, and nuclei were labeled with DAPI during the final wash. Embryos were imaged on upright and inverted epifluorescence microscopes (Leica), or TCS SP5 AOBS and TCS SP8 X scanning point confocal systems (Leica). Hybrid embryo allele-specific differential expression analyses M. occulta and M. oculata genomes  (Stolfi et al. , 2014b)  were improved using Redundans  (Pryszcz and Gabaldón, 2016) , reads from the initial assemblies (PRJNA253689) were used to improve scaffolding, which had been done to improve the M.
occidentalis genome and gene models we previously published  (Lowe and Stolfi, 2018). Additionally, the M. oculata genome was used as a reference to increase the scaffolding of the M. occulta genome. To build gene models, previously sequenced RNAseq reads  (Lowe et al. , 2014)  were mapped using hisat2 (v2. 1. 0) (Kim et al. , 2015) , converted to BAM and sorted using SAMTools (v1. 5)  (Li et al. , 2009)  and merged with picard tools (v2. 0. 1) (http://broadinstitute. github. io/picard/). Merged bam files were then assembled using Trinity genome-guide command (v2. 6. 6) (Grabherr et al. , 2011). Assembled transcripts were then translated and filtered using TransDecoder (https://github. com/TransDecoder/TransDecoder/wiki) removing any open-reading frames less than 100 amino acids. To improve on contiguity, transcripts were BLASTed against Ciona robusta predicted proteins from ANISEED  (Brozovic et al.
, 2018) , then scaffolded using TransPS  (Liu et al. , 2014). Default parameters were used for all steps and scripts can be found at https://github. com/elijahlowe/tailed. Genomes and transcriptomes used in this study can be found at https://osf. io/mj3r7/. For differential expression analysis, previously sequenced RNAseq reads from M. occulta, M. oculata and M. occulta × M. oculata hybrid embryos from three different stages  (Fodor et al. in preparation; Lowe et al. , in preparation)   (Lowe et al. , 2014)  were mapped to the M. occulta or M. oculata Ebf gene models using Salmon v0. 6. 0  (Patro et al. , 2015).
Acknowledgments We dedicate this manuscript to the memory of  Alexander "Zander" Fodor. We thank  C. Titus Brown  for his encouragement and continued support. We thank  Stéphane Hourdez ,  Sophie Booker , and  Xavier Bailly of the Station Biologique  for help in carrying out experiments at Roscoff. We thank  Susanne Gibboney  for assistance with cloning Molgula Ebf reporter plasmids. This work was supported by  NIH  award  R00 HD084814  to AS, by start-up package from the  College or Arts and Science at New York University  and  NIH  award  R01 GM096032  to LC, by  France BioImaging  infrastructure  ANR-10-INBS-04  to NP, and by a  University of Washington Royalty Research Fund  award ( A118261 ) to BJS. The collaborative MoEvoDevo network is supported by  ASSEMBLE (Association of European Marine Biological Laboratories) MARINE.
Since these limitations can conceal naturally occurring genomic diversity among Wolbachia populations, highly resolved analyses of individual mosquitoes may reveal additional insights into the Wolbachia 'mobilome', the pool of all mobile genetic elements associated with Wolbachia populations. Here we sequence ovary samples from four wild-caught C. pipiens individuals captured in Southern France from a single trap. Using genome-resolved metagenomic and pangenomic analysis strategies, we were able to reconstruct and compare nearcomplete Wolbachia genomes from each individual. Besides a diverse set of virus-associated genes that were missing or absent in the reference Wolbachia genome wPip Pel, our data reveal the first lines of evidence for an extrachromosomal circular element with genetic and functional hallmarks of a plasmid that we tentatively name pWCP.
Gene clusters unique to MAG O07 (n = 56) included a gene coding for an ankyrin and tetratricopeptide repeat protein previously identified in phage WO from Nasonia vitripennis wasps  27. Ankyrin and tetratricopeptide repeats mediate a broad range of protein-protein interactions (apoptosis, cell signaling, inflammatory response, etc. ) within eukaryotic cells and are commonly associated with effector proteins of certain intracellular pathogens  59, 60. There was also a Retron-type reverse transcriptase and genes coding for Transposases (COG3293 and a Transposase InsO and inactivated derivatives gene). Although most remaining unique O07 gene clusters had no functional annotation, about a third matched to eukaryotic viral genes based on homology searches in the NCBI's non-redundant protein sequence database (Supplementary Data 5).
To remove the least reliable data, we filtered the raw sequencing results using cluster intensity and chastity filter as described in ref. 68. Metagenomic assembly and binning. We used illumina-utils v1. 4. 4  69  to qualityfilter raw paired-end reads with the program 'iu-filter-quality-minoche' with default parameters, IDBA_UD v1. 1. 2  70 to assemble paired-end reads into contigs, and Bowtie2 v2. 2. 9  71  for all read recruitment analyses. We processed our contigs that are >1000 nts and read recruitment results with anvi'o v5  72  to recover MAGs from C. pipiens metagenomes. Briefly, we used the program 'anvi-gen-contigsdatabase' to generate anvi'o contigs databases for each four individual assemblies, during which anvi'o calculates and stores tetranucleotide frequency values and Prodigal v2.
6. 3  73  identifies ORFs in each contig. We ran default anvi'o HMM profiles on resulting contigs databases using the program 'anvi-run-hmms' and assigned functions to genes using the program 'anvi-run-ncbi-cogs', which searches gene amino acid sequences against the December 2014 release of the COG database 74 using blastp v2. 3. 0+  75. We profiled the short reads of our contigs recruited from each four individual metagenomes onto the four assemblies using the program 'anvi-profile', which generates anvi'o profile databases that store the coverage and detection statistics of each contig within each sample independently. We then merged resulting anvi'o profile databases for each sample using the program 'anvi-merge'. For an initial coarse binning, we used the CONCOCT  76  algorithm through the program 'anvi-cluster-with-concoct' and confined the number of clusters to five using the parameter '-num-clusters-requested 5'.
We then used the program 'anvi-script-get-collection-info' to identify bins with a bacterial population genome, manually refined them to identify bacterial genomes using the program 'anvi-refine', and assigned taxonomy to resulting MAGs using NCBI's non-redundant protein sequence database with amino acid sequences of core genes. The program 'anvi-refine' allows the identification and refinement of population genome bins through an interactive interface by offering a number of tools including (1) guiding hierarchical clustering dendrograms of contigs (including one based on tetranucleotide frequencies and differential coverage statistics across samples), (2) real-time completion and redundancy estimates of binned contigs based on bacterial single-copy core genes 77 , (3) interfaces that display nucleotide-level coverage statistics per gene and contig, (4) functional annotations and synteny of genes, and (5) online sequence homology search options for gene and contig sequences.
These tools collectively help minimize the inclusion of non-target contigs (such as eukaryotic contamination) in final bins, especially in complex metagenomes  78. Except for the manual refinement step, we automated the processing of our raw sequencing data with a snakemake  79  workflow anvi'o v5 implements (http://merenlab. org/2018/07/09/anvio-snakemakeworkflows/), and the Code availablility section reports necessary configuration files to fully reproduce this analysis. Sample preparation and long-read sequencing. To investigate the circularity of pWCP, we prepared for a long-read sequencing strategy. We extracted and pooled ARTICLE NATURE COMMUNICATIONS | https://doi. org/10. 1038/s41467-019-08973-w DNA from the ovaries of 7 C. pipiens and 15 C. quinquefasciatus mosquitoes. As the total DNA quantity from this step was only ng, we also extracted DNA from the abdomens of 15 C.
For downstream analyses, we only used reads with a minimum quality score of 7. Pangenomic analysis and the metapangenome. Our analysis of the Wolbachia pangenome followed the workflow outlined in ref. 80  and at http://merenlab. org/ 2016/11/08/pangenomics-v2/. Briefly, we first generated an anvi'o genomes storage database using the program 'anvi-gen-genomes-storage' for our four Wolbachia MAGs and the wPip reference genome wPip Pel 40 (NCBI Accession ID NC_010981. 1). We then used the program 'anvi-pan-genome' using the flag '-usencbi-blast', and parameters '-minbit 0. 5', and '-mcl-inflation 5'. This program (1) uses the blastp program all vs. all to create a graph of similarities between pairs of amino acid sequences, (2) removes bad hits using the 'minbit heuristic', (3) uses the Markov Cluster algorithm to determine gene clusters, (4) calculates the occurrence of gene clusters across genomes and the total number of genes they contain, (5) realizes a hierarchical clustering analysis for gene clusters (based on their distribution across genomes) and for genomes (based on shared gene clusters), and finally (6) generates an anvi'o pangenomic database that stores all results for downstream analyses.
We used the program 'anvi-display-pan' to visualize gene clusters and their distribution across the five genomes in anvi'o interactive interface and summarized our manual selection of gene clusters using the program 'anvisummarize'. To identify 'phage-like' gene clusters, we used blastn to search for genes homologous to the five phage regions  27  in the wPip Pel genome (hereafter referred to as WOPip1-5). We finally used a custom R script (see the Code availability section) to recover coverage values of each gene cluster using our four metagenomes. We visualized the metapangenome using the program 'anvidisplay-pan'. Computing the density of single-nucleotide variants per genome and metagenome. To infer the extent of heterogeneity in metagenomes for each Wolbachia MAG, we used the anvi'o program 'anvi-gen-variability-profile' to recover singlenucleotide variants from each merged profile without any filters (following the tutorial at http://merenlab.
org/2015/07/20/analyzing-variability/). We then kept only single-nucleotide variants that fall into the context of complete gene calls to minimize erroneous variants that often emerge from mappig artefacts around beginnings and ends of contigs and calculated the percentage of nucleotide positions in each genome that was not clonal in the metagenome. Computing the average nucleotide identity between genomes. To compute the level of similarity between the four Wolbachia MAGs and the wPip Pel reference genome, we used the program 'anvi-compute-ani', which called PyANI v0. 2. 7  81  in 'ANIb' mode to align 1 kbp long fragments of the input genome sequences with the NCBI's blastn program to summarize the average nucleotide identity and alignment coverage scores. PCR amplification of DNA. We used a set of specific primers on the four C.
To detect the circularity of the plasmid-like genome, we designed new primers (listed in Results) and used the following cycling parameters: 2 min at 95 °C, followed by 34 cycles of (94 °C for 30 s, 58 °C for 45 s, and 72 °C for 2 min) with a final elongation of 5 min at 72 °C. Finally, to confirm the presence of the IS110 TE, we used primers described in the Results section under the following PCR conditions: 2 min at 95 °C, followed by 34 cycles of (94 °C for 30 s, 55 °C for 45 s, and 72 °C for 30 s) and a final elongation of 5 min at 72 °C. Amplifications by PCR were performed using Platinium Taq DNA Polymerase High Fidelity (5 U/μL, Invitrogen). Plasmid characterization. We used the Glimmer software within Geneious v8. 1. 9 (Biomatters, Ltd) to identify ORFs and used the NCBI databases for nonredundant protein sequences and conserved domains  82  , SMART  83  , and HHpred 84 (including SCOPe, Pfam, and COG) to manually annotate putative functions based on amino acid sequence homology searches.
Acknowledgements We thank  Albane Marie ,  Gregory Lambert , and  Jean-Baptiste Panchau  from  EID (Entente Interdépartementale de Démoustication ) for field Culex pipiens samples;  Maria del Mar Fernandez de Marco  from  Animals Plant Health Agency  for antibiotic-treated Culex pipiens individuals;  Evan Kiefl ,  Richard Fox , and  Frederick Gavory  for their help with computational matters;  Phoebe Rice ,  Sean Crosson , and  Marie-Agnès Petit  for their insights into plasmid biology;  Nick Loman ,  Loïs Maignien ,  Manon Bonneau , and  Emmanuelle Jousselin  for their insights into sequencing. This research was funded by the  National Institute for Agronomical Research (INRA)   Young Researcher grant  ( 2017 ) to J. R. and  National Institutes of Health  awards  R01 AI132581  and  R21AI133522 ,  National Science Foundation  award  1456778 , and  Vanderbilt Microbiome Initiative  funding to  Seth R Bordenstein.
The  INRA Metaprogram (Microbial Ecology and Metagenomics) MEM  from  INRA  provided a USA mobility grant to J. R. , and A. M. E. was funded by the  University of Chicago  start-up funds and the  Keck Foundation. K. L. was supported by a  Gastrointestinal Research Foundation  grant. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Data availability The raw sequencing data for shotgun metagenomes are available in the European Nucleotide Archive via accession code PRJEB26028. Sequencing data for the MinION run is available at https://doi. org/10. 6084/m9. figshare. 7306784. We also made available FASTA files for individual metagenomic assemblies (https://doi. org/10. 6084/m9. figshare. 6263867), the four metagenome-assembled Wolbachia genomes (https://doi. org/ 10. 6084/m9. figshare. 6292040), artificially circularized individual plasmid sequences (https://doi. org/10. 6084/m9. figshare. 6380015), as well as anvi'o merged profile databases (https://doi. org/10. 6084/m9. figshare. 6263876) and anvi'o files for the Wolbachia pangenome (https://doi. org/10. 6084/m9. figshare. 6291650).
1 ). Based on these distributions, we excluded LGD mutations in genes with pLI score <0. 84 and RVIS percentiles >32. Under such restrictions, the proband (1902 SSC probands) burden for de novo LGD mutations became more significant (0. 040 vs. 0. 019; P = 2. 5 × 10 -4 , ANOVA) (Fig. 1a ). To prioritize ASD candidate genes, we combined de novo LGD mutations from two main ASD family-based WES studies: namely, the SSC WES study and the Autism Sequencing Consortium (ASC) WES study  4  (Methods). These two combined datasets represent 3953 families. Based on the SSC family analysis, we applied three criteria to prioritize the candidate genes: (i) mutation intolerance (pLI score > 0. 84 and RVIS% < 32); (ii) FMRP and RBFOX target enrichment; and (iii) variants in genes where genome-wide de novo significance had not been established in the recent meta-analysis  9.
These additional mutations included 14 LGD mutations and three intragenic microdeletions (Table  2 , Supplementary Data 4). The variants were detected by WES, targeted sequencing, or array comparative genomic hybridization (aCGH) (Methods) in the corresponding collaborating centers either as part of routine diagnosis or as part of research studies. In total, we identified and recruited 19 families (19 probands and 3 affected siblings) with potentially disruptive TANC2 variants, including 16 LGD mutations and three intragenic microdeletions (Table  2 , Fig. 2a, b ). Among the 16 LGD mutations, we determined that 11 are de novo, 4 are inherited, and in 2 one parent's DNA was not available. Two of the three microdeletions are de novo and one is transmitted from the mosaic father to two affected siblings (Fig.
2b, c , Supplementary Fig. 2 ). TANC2 is a highly conserved gene, in the top percentile of genes intolerant to truncating mutations (pLI score = 1, RVIS% = 0. 4). No LGD mutations in TANC2 are present in the 1000 Genomes Project 21 , ESP6500 (ref. 22 ), and 1911 SSC unaffected siblings. Only three LGD mutations in TANC2 are observed in 45,376 ExAC nonpsychiatric samples, and none of the specific truncated mutations observed in our patients are present in this database. Based on these data, we assessed significance of the genetic findings using two different tests. First, we assessed an enrichment of de novo LGD mutations among probands. Ten patients with confirmed TANC2 de novo LGD mutations were screened from nine cohorts from a total of 16,113 tested individuals (ACGC, Amsterdam, BCM, Leiden, Leipzig, Melbourne, Paris, SSC, Toronto; Table  2 ).
To guard against potential exon dropout, we assessed the mean coverage of TANC2 exons in ExAC. The average coverage is 49. 2 sequence reads per exon (Supplementary Fig. 3 ) with 24/25 of the exons showing on average more than 20-fold sequence read coverage. Disruption of TANC2 defines an NDD syndrome. Through patient recontact and review of the clinical information for all available patients/family members from the collaborating centers, we assembled phenotypic data for 19 probands and one affected sibling (13 males, 7 females, aged 4-40 years) carrying LGD mutations or intragenic microdeletions (Supplementary Data 4, Table  3 ). The most consistent phenotypes include ASD, ID, speech-language delay, and childhood motor delay (Table  3 ). In some cases, presentation of ASD was consistent with features reminiscent of the Rett-like spectrum.
In family GU, the carrier mother has ID and a history of seizures, motor delay, and learning difficulties during school years. Only the carrier father in family TI was thought to be unaffected; however, no clinical   LG. p1   Single cell RNA-sequencing dataset from developing human brain 0 1 2 3 4 eN1 eN2 eN3 eN4 eN5 eN6 eN7 eN8 eN9 iN1 iN2 iN3 iN4 iN5 IPC1 IPC2 IPC3 IPC4 IPC5 NiN1 NiN2 NiN3 NiN4 NiN5 Other1 Other2 Other3 Other5 Other7 Other8 RG1 RG2 RG3 RG4 RG5 RG6 RG7 VP1 VP2 VP3 VP4 VP5 VP6 2. 65E-17  De novo missense variants in TANC2. Although the most significant phenotypic findings were observed in patients with putative disruptive variants, we also identified five individuals with de novo TANC2 missense mutations from denovo-db v. 1. 5 (ref. 23 ) or by the targeted sequencing mentioned above (Table  2 , Fig.
2a , Supplementary Data 4). Three of these variants were identified in individuals with a primary diagnosis of ASD (p. R755H, p. R961Q, p. H1689R); one was found in an individual with a primary diagnosis of language disability and ID (p. R760C)  24  ; and the last was identified in a patient with schizophrenia (p. A794V)  25  , consistent with its role in psychiatric disorders. We note that three of the variants (p. R755H, p. R760C, p. A794V) cluster within the ATPase regulatory domain and one (p. R961Q) maps to one of the ANK domains (Fig. 2a ). Variants p. H1689R, p. R760C, and p. A794V have not been previously observed in ExAC nonpsychiatric samples while p. R755H and p. R961Q have both been reported four times in this database. Although the pathogenicity of these missense mutations is not yet established, p.
R755H, p. R760C, and p. R961Q are predicted to have a damaging or possibly damaging effect (Supplementary Table  2 ) by multiple prediction tools. In addition, the specific p. R760C variant was recently reported to impair the recruitment of KIF1A-transported vesicles in neurons  14  , making its pathogenicity more likely from a functional perspective. Expression pattern of TANC2 in the developing human brain. To further refine the expression pattern of TANC2 in the developing human cerebral cortex, we analyzed a single-cell RNA sequencing dataset generated across 48 individuals  26. Based on the transcriptomic profiles of 48 distinct clusters, we broadly classified six cell types: radial glia, intermediate progenitor cells, excitatory neurons, medial ganglionic eminence (MGE) progenitors, newborn MGE neurons, and inhibitory interneurons (Fig.
In brief, ACGC patients are diagnosed primarily according to DSM-IV/V criteria documenting additional comorbid conditions where possible. Peripheral-blood DNA of all probands, parents and siblings, where available, was collected with informed consent. Genomic DNA was extracted from the whole blood using a standard proteinase K digestion and phenol-chloroform method. The sequencing data have been deposited in the National Database for Autism Research (NDAR)  54. The study complied with all relevant ethical regulations for work with human participants and was approved by the Human Ethics Committee of Center for Medical Genetics, Central South University (institutional review board (IRB) #2014031113). Targeted sequencing was performed using smMIPs  19, 20. In summary, smMIPs were designed using MIPgen with an updated scoring algorithm.