dataesr/scientific-paragraphs-categorization huggingface dataset:
Remaining variants were filtered under an autosomal recessive (homozygous or compound heterozygous) and x-linked hypothesis. In addition, heterozygous variants called in both siblings and absent in the parents were selected under a parental mosaics for which the ExAC  10  filter was set at <2 calls. This analysis revealed only this one compound heterozygous UGDH variants. Family 4: Parent-proband trio exomes were prepared using the SureSelect Target Enrichment System (Agilent, Santa Clara CA) and sequenced on a HiSeq2000 System (Illumina, CA). Data processing, bioinformatics pipeline (for alignment, variant calling, annotation, and genetic model filtering), and analyses were previously described  45. The compound heterozygous rare missense alterations in the UGDH gene, c. 214T > C and c. 41A > G, were interpreted as the only candidate genetic etiology.
Family 5: The exome library was prepared on an ION OneTouch System and sequenced on an Ion Proton instrument (Life Technologies, Carlsbad, CA, USA) using one ION PI chip. Sequence reads were aligned to the human GRCh37/hg19. Variants were filtered for common SNPs using the NCBI's "common and no known medical impacts" database (ClinVar), ExAC 10 , as well as an in-house database of 406 sequenced samples. Additional filters were applied to retain proband's exonic variants that were homozygous while heterozygous in both parents. Out of 5 homozygous variants, only one missense variant c. 244G > A in the UGDH gene was found to segregate with the disease. Family 6: Exome sequencing was performed on a NextSeq 500 System (Illumina, CA USA), with a 2 × 150 bp high-output sequencing kit after enrichment with Seq Cap EZ MedExome kit (Roche, Basel Switzerland).
Sequence alignment, variant calling, and variant annotation was performed by Genosplice Technology (Paris France) with BWA 0. 7. 12, picard-tools-1. 121, GenomeAnalysisTK-2014. 3-17-g0583018 and SNPEff-4. 2 with additional annotations from ClinVar and HGMD. The compound heterozygous UGDH variants were selected to be the most promising candidates and were thus submitted to GeneMatcher. Families 7, 8, 16-25: Exome sequencing was performed essentially as described before  46  for families 7, 8, and 16-25. Target regions were enriched using the Agilent SureSelectXT Human All Exon 50 Mb Kit. Whole-exome sequencing was performed on the Illumina HiSeq platform (BGI, Copenhagen, Denmark) followed by data processing with BWA (read alignment,) and GATK (variant calling) software packages. Variants were annotated using an in-house developed pipeline.
Prioritization of variants was done by an in-house designed "variant interface" and manual curation. As four families with similar phenotype shared the homozygous p. R317Q as best candidate, a GeneMatcher entry was made and the in-house database was systematically screened for other potentially pathogenic UGDH variants. This allowed the identification of families 18 to 25. Family 11: The sequencing was performed at Claritas Genomics (Cambridge, USA). Extracted genomic DNA was amplified using the AmpliSeq system and sequenced using an IonTorrent Proton Instrument. Alignment and variant calling of the nuclear DNA was done on Proton data using Torrent Suite 4. 4 Software. Nuclear variants were filtered for quality using a custom filtering tool. In addition, extracted genomic and mitochondrial DNA was also run on an Agilent Clinical Research Exome capture sequence and then sequenced using an Illumina NextSeq instrument.
Alignment and variant calling on NextSeq data was performed by an implementation of GATK Best Practices Pipeline. Genomic DNA results from the two NGS runs on the proband were combined and annotated by a custom bioinformatics pipeline. Besides a heterozygous SLC6A5 missense variant inherited from the unaffected father, the compound heterozygous UGDH variants were the only candidates reported that had a minor allele frequency (MAF) of < or = 0. 01% that passed the laboratory's quality metrics and were not de novo, X-linked or had biallelic variants. Family 12: Isolated genomic DNA from peripheral blood leukocytes of proband and parents was captured with the Agilent Sure Select Clinical Research Exome (CRE) kit (v2). Sequencing was carried out with 150 bp paired-end reads on the Illumina HiSeq 4000.
Additional variants not included in this report are available upon request. Family 14: The patient F14-II:1 was enrolled in the ongoing "Undiagnosed Patients Program" at the Ospedale Pediatrico Bambino Gesù, Rome. Targeted enrichment (SureSelect All Exon V. 4, Agilent) used genomic DNA extracted from circulating leukocytes for the affected subject and both parents, and parallel sequencing was performed using an Illumina HiSeq2000 platform, obtaining about 70 million reads. The data analysis was performed using an in-house implemented pipeline, which mainly take advantage of the Genome Analysis Toolkit (GATK V. 3. 7)  47 framework, as previously reported  48, 49  ). 1] [52]. The functional impact of variants was analyzed by Combined Annotation Dependent Depletion (CADD) V. 1. 3, M-CAP V. 1.
0, and InterVar V. 0. 1. 6 algorithms  11, 53, 54. Two compound heterozygous private missense variants in the UGDH gene, c. 347T > C and c. 1328G > A, were interpreted as the only candidate genetic etiology. Family 15: genomic DNA from of the proband and parents were enriched for exonic sequences with the SureSelect Human All Exon 50 Mb V5 Kit (Agilent Technologies, Santa Clara, California, USA). The HiSeq2500 (Illumina, San Diego, California, USA) was used to generate 125-bp paired-end runs of sequences. Reads were aligned and variant called with DNAnexus (Palo Alto, California, USA) using the reference human genome assembly hg19 (GRCh37). A mean coverage of 104x was achieved for the proband. Data analysis was preformed using an in-house bioinformatics pipeline. The compound heterozygous UGDH variants were selected to be the most promising candidates and were thus submitted to GeneMatcher.
The total protein concentration of cell lysates was determined using the BCA Protein assay Kit (Thermo Fisher Scientific, USA). Sixty micrograms of total proteins were reduced in Laemeli loading buffer, denatured at 95 °C for 10 min, separated by 4-20% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (Invitrogen, Germany) electrophoresis and transferred onto Immun-Blot® Low Fluorescence PVDF Membranes (BIORAD). Protein detection was performed using anti-UGDH (1:500, Sigma-Aldrich, USA, HPA036657) and anti-GAPDH (1:2000, Santa Cruz Biotechnology Inc. , USA, SC 47724) antibodies. Secondary antibodies conjugated to peroxidase (1:4000, Santa Cruz Biotechnology Inc. , USA) were used and blots were developed using an enhanced chemiluminescence system, Pierce™ ECL Plus (Thermo Scientific), followed by detection on autoradiographic films.
Then, 500 µl of either egg water (negative control) or PTZ 30 mM (15 mM final concentration, Sigma, P6500) was added to the well. Three videos of 2 min each were acquired for a duration of 10 min for each condition tested. Fish locomotion was tracked online during video recording on a custom written software in LabView (www. critta. org). Analysis of locomotion was automated and performed blind offline after each experiment using custom written Python scripts (available on Github: https://github. com/mechunderlyingbehavior/24-Well-Larval-Locomotion. git). In this assay, low and high speed were defined as average speeds of 0 to 8 mm/s and >8 mm s -1 , respectively, based on a recent publication measuring convulsive-induced speed changes in zebrafish larvae  65. 57 SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore.
Acknowledgements We are grateful to the families of affected individuals whose cooperation made this study possible. We would like to thank  Dr. Mary-Claire King  from the  University of Washington (Seattle, USA ) and  Dr. Ephrat Levy-Lahad  ( Medical Genetics Institute Shaare Zedek Medical Center, Israel ) who independently investigated Family 1 and completed the segregation of the UGDH mutations in available family members. This study has been supported by the  German Research Foundation  (DFG, grant  SCHO754/5-2  to L. S. and H. M. M. ), by the  European Union  through funding for the NEUROMICS network ( F5-2012-305121  to L. S. ), by  A Strategic Positioning Fund on Genetic Orphan Diseases (GODAFIT)  and an  Industry Alignment Fund on Singapore Childhood Undiagnosed Diseases Program (SUREKids)  from the  Biomedical Research Council ,  A*STAR, Singapore.
L. received financial support obtained from the  Netherlands Organization for Scientific Research (ZONMW VIDI  grant  91713359  to D. J. L. ). S. S. J. is supported by  National Medical Research Council, Singapore  ( NMRC/CISSP/0003/2016 ). B. R. is a fellow of the  Branco Weiss Foundation , an A*STAR Investigator, a Young EMBO Investigator, a Senior NRF and AAA fellow. K. H. U was supported by the  FRAXA Foundation. Furthermore , we would like to thank the  EuroEPINOMICS-RES NLES Working Group  for their support by screening their database and matching Family 3. T. B. is supported by the  Netherlands Organisation for Scientific Research  ( ZonMW Veni , grant  91617021 ) and by an  NARSAD   Young Investigator Grant  from the  Brain & Behavior Research Foundation.
Data availability The data that support the findings of this study are available within the paper and its supplementary information files. All identified variants have been deposited in the ClinVar database (https://www. ncbi. nlm. nih. gov/clinvar/) under the name "UGDH001". Whole dataset from Family F3 was already published  66  and deposited in the European Genome-phenome Archive, accession numbers EGAS00001000190, EGAS00001000386, and EGAS00001000048. Whole datasets from Families F5 and F15 are available upon request from the corresponding authors. Consent restrictions preclude deposition of sequencing data of the other families, however, specific information (e. g. , secondary variants etc. , but not full datasets) can be obtained upon request from the corresponding authors. Lists of primers and antibodies are in Supplementary Tables  4  and 5 , respectively.
g. eyes, mouth) and uniformed by normalization of grey levels reducing the saturation to minimum and adjusting the exposure parameters in the software Preview. According to previous attempts  (Sackheim et al. 1978)  pictures were split on the midline of the full face and chimeric stimuli were constructed by mirroring each half of the face. This resulted in two chimeric facial stimuli, one made of the left side and one made up of the right side (Figure  1a, b ). This group also underwent diffusion MRI scans in order to reconstruct their white matter tracts. This material is available on demand to michel. thiebaut@gmail. com or ste. ioannucci@gmail. com A second group of 20 participants (referred to as judges, mean age 25. 65 ±4. 6, 10 males) judged the set of chimeric facial stimuli from the group of posers.
The diffusion weighting was equal to a b-value of 2000 s/mm -2. This sequence was fully repeated with reversed phase-encode blips. This provides us with two datasets with distortions going in opposite directions. From these pairs the susceptibility-induced offresonance field was estimated using a method similar to that described in  (Andersson et al. 2003 ) and corrected on the whole diffusion weighted dataset using the tool TOPUP and EDDY as implemented in FSL  (Smith et al. 2004 ). To exclude spurious local maxima, we applied both an absolute and a relative threshold on the FOD amplitude. A first "absolute" threshold was used to exclude intrinsically small local maxima due to noise or isotropic tissue. This threshold was set to 3 times the mean amplitude of a spherical FOD obtained from a grey matter isotropic voxel (and therefore also higher than an isotropic voxel in the cerebro-spinal fluid).
Tractography dissections Virtual dissections were made of the bilateral tracts on which we had a priori hypotheses, that is, the uncinate fasciculus, the three branches of the superior longitudinal fasciculi (SLF I, II and III) and the cingulum (Figure  2  a,b,c). We employed the software Trackvis (http://www. trackvis. org), which allows for visual inspection of the tracts and extracted a measure of their track count and hindrance modulated orientational anisotropy (HMOA)-a new index employed as a surrogate for tract microstructural organization (Dell'Acqua 2012). HMOA is preferable to fractional anisotropy (FA) in the case of algorithm solving fibre crossing. Indeed, HMOA is a true tract specific measurement, therefore HMOA values derived from dissections are not contaminated by other crossing tracts (i.
Statistics First, behavioural and anatomical asymmetries were analysed independently using SPSS software (SPSS, Inc. , Chicago, IL, United States of America) to perform one sample t-test against zero on the asymmetry indices of emotional expression and tract specific measurements. Subsequently the relationship between asymmetry indices of emotional expression and structural asymmetry indices was determined using two hierarchical linear regression analyses (i. e. happy and sad conditions). A maximum of 10 independent variables (i. e. asymmetry indices of streamlines and HMOA for uncinate, cingulum, SLF I, SLF II and SLF III) was introduced to a backward elimination analysis to identify significant regressors for predicting the asymmetry in the two conditions (i. e. happy or sad asymmetry indices).
Acknowledgments We thank  ERASMUS  for supporting SI. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 818521 ). The research leading to these results also received funding from the  "Agence Nationale de la Recherche " [grants number  ANR-13-JSV4-0001-01 ] and from the  Fondation pour la Recherche Médicale (FRM). Additional financial support comes from the program  " Investissements d'avenir "  ANR-10-IAIHU-06  and  ANR-11-INBS-0006. Funding from  ERC  (grant agreement No. 818521 ) and " Agence Nationale de la Recherche " [grants numbers  ANR-13-JSV4-0001-01 ,  ANR-10-IAIHU-06  and.
Bioinformatics Analysis Variants detected by targeted NGS and by WES were annotated using the Ion reporter and Annovar software, respectively. They were evaluated with Alamut Mutation Interpretation Software (Interactive Biosoftware, Rouen, France). Databases such as ExAC Genome browser (http: //exac. broadinstitute. org), dbSNP135 (National Center for Biotechnology Information (NCBI), Bethesda, Maryland, USA, (http://www. ncbi. nlm. nih. gov/projects/SNP/)), ClinVar (www. ncbi. nlm. nih. gov/clinvar) and HGMD professional (www. hgmd. cf. ac. uk) were also screened. Cov'Cop and CovCopCan, both interactive powerful software, were used to detect copy number variations (CNV)  [2, 3].
Array-Comparative Genomic Hybridization (aCGH) Array Comparative Genomic Hybridization (aCGH) was performed using G3 Human CGH microarrays 8 × 60K (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer's instructions. Agilent CytoGenomics software (Agilent Technologies) was used to visualize, detect, and analyze copy number changes.
Quantitative Real-Time PCR (Q-PCR) q-PCR reactions were carried out on genomic DNA extracted from blood samples. Primers were designed in exon 8 of the AARS1 gene and in exon 1 of the Albumin gene, chosen as a reference gene. A Rotor-Gene SYBR-Green PCR Kit (400) ( © QIAGEN, Hilden, Germany) was used following the standard protocol. Reactions were performed on the Corbett Rotor-Gene 6000 Machine ( © QIAGEN). The Ct values of each real-time reaction were normalized, using Albumin as the endogenous control gene, and then compared to the normalized Ct values of three control samples. The experiment was performed in triplicates. The normalized raw data of samples were analyzed by Student's t-test, comparing them with the normalized raw data of the controls. All results were statistically significant.
Results Targeted NGS strategy revealed a heterozygous c. 1403G > A mutation in the MFN2 gene (NM_014874. 3) on patient B only, resulting in the amino acidic substitution p. Arg468His. No other potentially pathological mutation was detected for patient B by targeted NGS. Sanger sequencing confirmed the presence of an MFN2 c. 1403G > A mutation in patient B, and excluded it in the other family members (Figure  1A ). Given the unclear role of MFN2 p. Arg468His in CMT pathophysiology and its absence in the affected subject A, we expanded our study looking for CNV with the bioinformatics tools Cov'Cop and CovCopCan  [2, 3]. We detected, among the 92 sequenced genes investigated, a complete duplication of the AARS1 gene (NM_001605. 2) in both patients (ClinVar accession number: SCV001167105). AARS1 duplication was confirmed by aCGH which allowed the identification of a 231 kb duplication, whose start and stop coordinates were identified in positions chr16:70185757 and chr16:70416579, respectively.
Other genes were included in the detected duplication and they are listed in Supplementary Table  S2. Although no neuropathic clinical cases caused by AARS1 duplication have been reported, we investigated the unaffected individuals of the same family by real-time qPCR. There was no AARS1 duplication in subject C, but it was present in unaffected subjects D and E, suggesting that AARS1 duplication by itself is not the major cause of CMT disease of patients A and B (Figure  1B ). investigated, a complete duplication of the AARS1 gene (NM_001605. 2) in both patients (ClinVar accession number: SCV001167105). AARS1 duplication was confirmed by aCGH which allowed the identification of a 231 kb duplication, whose start and stop coordinates were identified in positions chr16:70185757 and chr16:70416579, respectively.
Other genes were included in the detected duplication and they are listed in Supplementary Table  S2. Although no neuropathic clinical cases caused by AARS1 duplication have been reported, we investigated the unaffected individuals of the same family by real-time qPCR. There was no AARS1 duplication in subject C, but it was present in unaffected subjects D and E, suggesting that AARS1 duplication by itself is not the major cause of CMT disease of patients A and B (Figure  1B ). To elucidate the genetic cause of the disease, we performed WES on three different members of the family: subjects A, B, and E, who is the mother of six unaffected children, reinforcing the hypothesis that she does not carry a pathological mutation responsible for CMT disease in this family. Interestingly, WES data showed a heterozygous missense mutation c.
Arg468His is located between the transmembrane domain and the C-terminal coiled coil region of the MFN2 protein  [12]. It has already been described as the causative mutation of the axonal CMT2A, but its pathogenicity rests unclear and in the ClinVar database its interpretation is mentioned as conflicting. Engelfried et al. reported it in two patients, the first with muscular atrophy and sensory loss, the second with Parkinson's disease and distal neuropathy, but also in an asymptomatic individual  [12]. This MFN2 variation was also found in two members of a Spanish family with a mild CMT phenotype and discrete symptoms of neuropathy  [13]. Given the highly variability of the associated phenotype and its uncertain pathogenicity, functional studies were conducted on human fibroblasts carrying the p.
Arg468His mutation as modifier allele, in CMT, has already been suggested in a previous publication  [18]. Moreover, in our study family, we detected a third variation, the complete duplication of AARS1 gene, a SV never described before and not recorded in the GnomAD database. AARS1 encodes the alanyl-tRNA-synthetase, the enzyme that catalyzes proper attachment of Alanine to its tRNA. In 2010, Latour et al. showed for the first time that an AARS1 missense mutation was responsible for axonal Charcot-Marie-Tooth disease in a French family  [19]. Further AARS1 pathological mutations were then reported to be associated with CMT disease  [20, 21]. As well as AARS1, several other tRNA-synthases were shown to be involved in peripheral neuropathies. In these cases, dominant mutations resulted in pathological mutant proteins, and toxic gain-of-function effects, or in a protein's loss of function  [22].
Treatments were randomly assigned to the 25 m 2 plots and were replicated in three blocks at most sites (some sites had fewer/more blocks or were fully randomized). Sampling was done in 1 m 2 subplots and followed a standardized protocol at all sites  27. Site selection. Data were retrieved on 1 May 2020. To keep a constant number of communities per site and treatment, we used three blocks per site, excluding additional blocks from sites that had more than three (Supplementary Data 1). Sites spanned a broad envelope of seasonal variation in precipitation and temperature (Supplementary Fig. 1 ), and represent a wide range of grassland types, including alpine, desert and semiarid grasslands, prairies, old fields, pastures, savanna, tundra, and shrub-steppe (Supplementary Data 1). Stability and asynchrony measurements are sensitive to taxonomic inconsistencies.
For those sites, the maximum cover of each species and total biomass were used in the analyses. Diversity, asynchrony, and stability across spatial scales. We quantified local scale and larger-scale diversity indices across the three replicated 1-m 2 subplots for each site, treatment and duration period using cover data  37, 38. In our analysis, we treated each subplot as a "community" and the collective subplots as the "larger scale" sensu Whittaker  28. Local scale diversity indices (species richness, species evenness, Shannon, and Simpson) were measured for each community, and averaged across the three communities for each treatment at each site resulting in one single value per treatment and site. Species richness is the average number of plant species. Shannon is the average of Shannon-Weaver indices  39.
Following theoretical models  15, 16  , we quantified abundance-based gamma diversity as the inverse Simpson index over the three subplots for each treatment at each site and abundance-based beta diversity, as the multiplicative partitioning of abundance-based gamma diversity: abundance-based beta equals the abundance-based gamma over Simpson  28, 42  , resulting in one single beta diversity value per treatment and site. We used abundance-based beta diversity index because it is directly linked to ecosystem stability in theoretical models  15, 16  , and thus directly comparable to theories. We used the R functions "diversity", "specnumber", and "vegdist" from the vegan package  43  to calculate Shannon-Weaver, Simpson, and species richness indices within and across replicated plots. Stability at multiple scales was determined both without detrending and after detrending data.
We used the R function "var. partition" to calculate asynchrony and stability across spatial scales  14. Climate data. Precipitation and temperature seasonality were estimated for each site, using the long-term coefficient of variation of precipitation (MAP_VAR) and temperature (MAT_VAR), respectively, derived from the WorldClim Global Climate database (version 1. 4; http://www. worldclim. org/)  44. Analyses. All analyses were conducted in R 4. 0. 2 (ref. 45 ) with N = 42 for each analysis unless specified. First, we used analysis of variance to determine the effect of fertilization, and period of experimental duration on biodiversity and stability at the two scales investigated. Models including an autocorrelation structure with a first-order autoregressive model (AR(1)), where observations are expected to be correlated from 1 year to the next, gave substantial improvement in model fit when compared with models lacking autocorrelation structure.