dataesr/scientific-paragraphs-categorization huggingface dataset:
946G>A (p. Val316Ile), and one with a de novo c. 236T>C (p. Met79Thr) variant. This latter individual was previously reported to have a de novo frameshift in CHAMP1 (c. 1876_1877delAG [p. Ser626Leufs] [GenBank: NM_032436. 2]), which also most likely contributes to the cognitive impairment of the subject (F3-II. 1 in Isidor et al. 42  ). All of these de novo missense variants are predicted to be damaging (PolyPhen-2, SIFT, and CADD). Their localization in GABRB2 is shown in Figure  1B. We were able to obtain detailed clinical information for all of these 11 individuals (Table  3  and Supplemental Note). They all displayed moderate to severe ID (or severe GDD), with the exception of the individual with the evolved into myoclonic status epilepticus or non-convulsive status epilepticus. Some individuals developed focal seizures with impaired awareness or autonomic seizures, tonic seizures, atonic seizures, and/or rarely generalized tonic-clonic seizures.
8] [49]  The amino acid residues affected by the latter two of these DNMs (p. Lys303Asn and p. Ala304Val) were also found to be mutated in our series. These four individuals appear to show ID or GDD and epilepsy, but no detailed clinical information was available. Out of the 13 GABRB2 DNMs previously reported or described herein, ten encode variants clustered within a stretch of 60 amino acids (positions 244-304) encompassing three transmembrane domains and/or their boundaries (p value ¼ 0. 000002, Denovonear) (Figure  1B ). These clustering variants appear to be mostly associated with severe GDD or ID and, with the exception of p. Arg293Pro, intractable generalized seizures and DEE. So far, only one of these de novo missense variants, p. Thr287Pro, has been functionally tested in transfected HEK293 cells and found to reduce cell-surface expression and peak current amplitudes of GABA A channels.
46 It is currently unknown whether the other de novo missense variants in GABRB2 behave similarly to p. Thr287Pro, especially the closely clustering or recurrent ones (p. Tyr244His, p. Leu277Ser, p. Lys303Leu, and p. Ala304Val), which might confer specific properties to the protein such as gain-of-function or dominant-negative effects. Collectively, the previously and presently reported individuals with DNMs in GABRB2 confirm that de novo missense mutations in GABRB2 can cause a DEE phenotype. CLTC Our WGS trio screen identified a de novo frameshift variant (c. 4575dupA [p. Glu1526fs*18]) in CLTC (GenBank: NM_004859. 3) in an individual with moderate ID associated with severe refractory seizures (absence, myoclonic, tonic, generalized tonic-clonic, and focal seizures). We obtained detailed clinical information on 11 additional individuals with DNMs in CLTC, four of whom were identified by the DDD study  10  and seven of whom we identified through clinical WES (Table  4  and Supplemental Note).
DHDDS WGS identified a de novo missense variant (c. 110G>A [p. Arg37His]) in DHDDS (GenBank: NM_024887. 3) in one of our DEE individuals (HSJ0762). We identified, by clinical WES, another DEE individual who carries the same de novo p. Arg37His. Interestingly, this missense variant lies adjacent to p. Arg38His, which was reported in a DEE subject from the Epi4K study. 7 Clustering analysis indicated that the presence of these two de novo variants in three individuals is statistically significant (p ¼ 0. 0005, Denovonear). In addition, we identified by clinical or research WES two other individuals with DEE and the de novo missense mutation c. 632G>A (p. Arg211Gln) in DHDDS and obtained detailed clinical information on a third subject, also with the same de novo p. Arg211Gln (indvNCJ herein), who was previously reported in a recent WES study of ID trios.
RAB11A We found a de novo predicted-damaging missense variant in RAB11A (c. 244C>T [p. Arg82Cys] [(GenBank: NM_004663. 3]) in a CENet individual with refractory epileptic spasms and erratic myoclonus with developmental regression. She subsequently developed focal seizures and severe ID. Using WES, we also identified another predicted-damaging de novo missense mutation in RAB11A (c. 71A>G [p. Lys24Arg]) in an individual with moderate GDD and abnormal EEG but with no seizures reported so far. Three additional individuals with DNMs in RAB11A, including two individuals with the same variant (c. 461C>T [p. Ser154Leu]) and another individual with a different variant (c. 39A>C [p. Lys13Asn]), were identified in the context of the DDD study. 10 We were able to obtain detailed clinical information on the individuals who had the p.
GABBR2 We identified from our WGS a de novo missense mutation in GABBR2 (c. 2077G>T [p. Gly693Trp] [GenBank: NM_005458. 7]) in one CENet subject who presented with focal seizures with impaired awareness and later developed epileptic spasms while on carbamazepine. He remains with refractory focal and generalized tonic-clonic seizures, severe ID, severe limb and axial hypotonia, and hyporeflexia (Table  7  and Supplemental Note). The Epi4K Consortium GABBR2 encodes a g-aminobutyric acid type B receptor that inhibits neuronal activity through G-protein-coupled second-messenger signaling at both the presynaptic and post-synaptic membranes, where it regulates neurotransmitter release and the activity of ion channels. 71 This receptor is the target of baclofen, a medication often used to treat spasticity.
SNAP25 We identified from our WGS a de novo missense mutation in SNAP25 (c. 496G>T [p. Asp166Tyr] [GenBank: NM_003081. 3 and NM_130811. 2]) in a male with DEE. He presented with apneas, GDD, nocturnal generalized tonic-clonic seizures, and focal seizures with impaired awareness and progressively developed moderate ID (Table  7  and Supplemental Note). SNAP25 is a member of the SNARE complex and is required for the exocytosis of neurotransmitters during synaptic transmission by mediating synaptic vesicle fusion. 72, 73 Developmentally regulated alternative splicing of two similar exon 5 sequences of SNAP25 generates two isoforms (a and b), which differ only by nine residues in this exon 5. Various mutant Snap25 mouse lines displayed cognitive deficit and seizures or susceptibility to seizures.
74, 75 8 Both mutations affect the N-terminal t-SNARE coiled-coil homology domain of SNAP25. The de novo missense variant identified in our cohort (p. Asp166Tyr) is predicted to be damaging (by SIFT, PolyPhen-2, and CADD) and alters a conserved residue in the second t-SNARE coiled-coil homology domain common to both isoforms (Figure  1H ). In addition, three DNMs in SNAP25 (c. 118A>G [p. Lys40Glu] [GenBank: NM_130811. 2], c. 127G>C [p. Gly43Arg], and c. 520C>T [p. Gln174*]) were recently reported in the DDD study, but no detailed clinical information was available on these. 10 Collectively, these findings support the involvement of SNAP25 mutations in DEE.
Four predicted-damaging missense variants absent from the ExAC Browser were identified, each in a single DEE subject, in NTRK2 (c. 1301A>G [p. Tyr434Cys] [GenBank: NM_006180. 4]), GABRB2 (c. 730T>C [p. Tyr244His] [GenBank: NM_021911. 2] and c. 911C>T [p. Ala304Val]), and HECW2 (c. 4484G>A [p. Arg1495Lys] [GenBank: NM_020760. 1].
27 mmary of the Clinical Features of Individuals with DNMs in RAB11A (GenBank: NM_004663. 4),GABBR2 (GenBank: NM_005458. 7),and SNAP25 (GenBank: NM_003081. 3)Lopes et al. recently reported a de novo missense mutation in GABBR2 (c. 1699G>A [p. Ala567Thr]) in an individual with severe ID and Rett-syndrome-like features but no seizures. 27.
Acknowledgments We thank the individuals participating in this study and their families for their contributions. This study was funded by grants from  Genome Canada and Genome Quebec , the  Jeanne and Jean-Louis Levesque Foundation  (to J. L. M. ), the  Michael Bahen Chair in Epilepsy Research  (to B. A. M. ), the  Ontario Brain Institute (EpLink) , the  McLaughlin Foundation  and the  University of Toronto  (to D. M. A. and B. A. M. ), and the  National Institute of Neurological Disorders and Stroke  ( RO1 NS069605  to H. C. M. ). We thank the members of the massive parallel sequencing and bioinformatics teams at the  McGill University and Genome Quebec Innovation Center  for their services. S. M. -M. was supported by the  University of Toronto   McLaughlin Accelerator Grant in Genomic Medicine  ( MC-2013-08 ).
We next evaluated the presence of 5hmCpGs at 20,287 MEIS1 binding sites in vivo by using single-CpG resolution data obtained by SCL-exo-seq in RA-treated P19 cells  (Sérandour et al. 2016). This method allows the genomewide identification of hydroxymethylated CpGs by a combination of chemical labeling (glucosylation followed by biotinylation), immobilization on streptavidin beads, and exonuclease digestion of the bead-trapped DNA molecules  (Sérandour et al. 2016). As shown in Figure  3B , 5hmCpGs were enriched at bulk MEIS1 binding sites (see also Supplemental Fig. S4A ). A cluster of 958 regions with centered 5hmCpGs was next recovered using the TMEV software  (Saeed et al. 2003)  in order to only consider regions with 5hmCpGs located within a few base pairs of MEIS1 binding sites. Sites from this cluster had, on average, a higher CpG density compared to bulk MEIS1 sites (Supplemental Fig.
S4B ). Heat maps, as well as profiles of MEIS1 ChIP-seq and SCL-exo signals (Fig. 3B-D ), showed that 5hmCpGs accumulated within -15/+15 bp of the MEIS1 ChIP-seq peak summits (defined as 0 in the heat maps and the average profiles). The 958 sequences were next analyzed and a consensus sequence was defined with the CLC Sequence Viewer 6 software (Fig. 3D ). Whereas 95 regions contained the TGACAG consensus MEIS1 site in close vicinity (within 2 to 20 bp) to 5hmCpGs, 29 regions did not include the consensus site but showed a TGACGG site, 24 of which had a hydroxymethylated CpG detected by SCL-exo (see examples in Supplemental Fig. S4C ). De novo motif discovery from the 958 sequences was then implemented with both SeqPos (Fig. 3E ; Supplemental Fig. S4D ) and SEME (Supplemental Fig. S4E ). SeqPos recovered a TGACG motif with a high probability, whereas the probability to find the MEIS1 motif was lower (Fig.
Notably, the chromatin features of this control enhancer were not affected by 5-azadC or DMOG treatments (Supplemental Fig. S7A, B ). Since DMOG could also inhibit histone demethylases of the Jumonji family  (Rose et al. 2011) , we controlled whether DMOG treatment increased H3K27 methylation, potentially leading to inhibition of enhancers, and found that H3K27me3 levels did not increase in DMOG-treated cells for any of the selected enhancers (Supplemental Fig. S7C ). These data indicate that, in our conditions, the observed effects of the DMOG treatment mainly reflected TET inhibition. The chromatin features of these 15 enhancers were then analyzed by (h)MeDIP-, ChIP-and FAIRE-qPCR experiments. Results of these experiments are depicted in the histograms of Supplemental Figures. S8 and   , S11 ).
wig file. A peak-calling algorithm  (Sérandour et al. 2012 ) was next used to identify peaks with a signal higher than τ in at least three consecutive positions. Called peaks were then extended by 100 bp on each side to include positions corresponding to the sides of the peaks even though they had an initial signal below τ. Finally, the original signal present within these extended regions was retrieved to generate normalized noise-free. wig files. Heat maps were generated by the Cistrome web-platform (http://cistrome. org/ap/; Liu et al. 2011). Motif search was run online through the SeqPos tool from Cistrome, and the analysis of motif distribution in genomic regions was done using CentDist (http://biogpu. ddns. comp. nus. edu. sg). TET1 ChIP-seq and SCL-exo data are from the NCBI GEO GSM941681 and GSE70635 data sets.
Pull-down assay Differentially modified 20-bp synthetic oligonucleotides (Sigma), biotinylated on the forward strand and containing either the PBX1/HOXA9 (TGATTTACG) or the PBX1/MEIS1 (TGATTGAC AG) recognition sites, were used as probes for pull-down assays. For each probe, cytosines from each CR dinucleotide (R = A or G) were unmodified (C), methylated (M), or hydroxymethylated (H). DNA/protein complexes were purified with streptavidin-coupled magnetic beads (Invitrogen) after incubation in binding buffer (Hepes 20 mM pH 7. 9, 50 mM KCl, 1 mM DTT, 2. 5 mM MgCl 2 , 5 µg/µL BSA, 10% glycerol) with 10, 20, or 40 µg of extracts from P19 cells treated for 48 h with RA. Protein binding was then analyzed by Western blot. Signals were quantified using the Quantity One 1-D Analysis Software from Bio-Rad.
Dot blot assay Genomic DNA was extracted using a DNA extraction kit (DNeasy Blood and Tissue kit; Qiagen) with a supplementary step of RNase digestion. Three hundred nanograms, 150 ng, and 75 ng of each sample DNA was spotted to a nylon membrane (Hybond N, GE Healthcare) previously soaked in 2× SSPE solution (0. 3 M NaCl, 20 mM sodium phosphate, 2 mM EDTA) and inserted in the dot blot apparatus (SCIE-PLAS). DNA was crosslinked to the membrane by 15 min exposure to UV light before blotting. After revelation, membranes were stained with methylene blue to control the amount of DNA spotted. Signals were quantified using the Quantity One 1-D Analysis Software from Bio-Rad.
Principal component analysis and clustering The R software (R Core Team 2013), with the FactoMineR package  (Lê et al. 2008) , was used to perform principal component analysis and hierarchical clustering. Briefly, chromatin mark variations across several genomic regions were investigated by PCA in which variables were genomic regions and individuals were chromatin marks. Data were sequentially scaled to unit variance and then projected onto orthogonal components. The resulting eigenvalues (based on both the covariance and correlation matrices) were used to retain the first components accounting for over 90% of the variance in the data. Finally, the coordinates of the individuals and variables on the selected principal components were used for the hierarchical classification.
Acknowledgments We thank  C. Le Péron  and  A. Laurent  for critical reading of the manuscript. We also thank the  "Human and Environmental Genomics" platform (Rennes)  for Illumina sequencing. We are thankful to  C. D'Santos  and  Chris Taylor  from the  Proteomics Core Facility  of the  Cambridge Institute (Cancer Research UK ) for running the MS experiments. This work was supported by the  CNRS , the  University of Rennes I , and the  Association de la Recherche contre le Cancer. E. A. M. was supported by a  PhD fellowship  from the  Ministère de l'Enseignement Supérieur et de la Recherche.
Data access All sequencing data from this study have been submitted to the NCBI Gene Expression Omnibus (GEO; http://www. ncbi. nlm. nih. gov/geo/) database under accession number GSE82314. PBX1 ChIP-MS data are accessible at the PRIDE Archive database from the European Bioinformatics Institute (https://www. ebi. ac. uk/pride/) under accession number PXD006158.
MAterIAls AnD MethODs study design and sampling This study complies with the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement. 23 Data used for this study was obtained from the Three-City study (3C). The 3C study is a French multisite prospective cohort study investigating the determinants of dementia, coronary heart disease and stroke. 24 Commencing from 1999 to 2001, the recruitment of a French population sample was sought for individuals who were 65 years or older at baseline, registered in the electoral rolls in the Dijon, Bordeaux and Montpelier catchment area, and able to provide written informed consent. Briefly, 9294 non-institutionalised community-dwelling adults aged ≥65 years were recruited and underwent extensive baseline examinations.
T2 acquisition consisted of 35, 3. 5 mm thick axial slices (with 0. 5 mm spacing between slices), having a matrix size of 256×256, and an in-plane resolution of 0. 98×0. 98 mm 2. T1 and T2 datasets were readily reconstructed, and visually checked for major artefacts before further analysis. Raw data were converted to the ACR-NEMA standard format and then transformed for analysis and storage at the Department of Neurofunctional Imaging, Caen.
Subjects were followed up to 12 years for incident stroke (fatal and non-fatal). For persons who reported the occurrence of vascular events during follow-up, further medical data were obtained from general practitioners, specialists and hospital records. The diagnosis and classification of strokes were made by a blinded expert panel that reviewed all existing medical information including, where available, cerebral imaging. Strokes subtypes included ischaemic and haemorrhagic strokes according to International Classification of Diseases 10th revision criteria. 30 atistical methods Potential predictors of extWML were selected based on published literature and study findings of 3C. 1 10-13  Other data definitions and additional statistical analyses are listed in the online supplementary file.
31  Thereafter age was eligible for elimination from the model. The optimal model for classifying extWML was computed with backward elimination to remove covariates not significantly associated with extWML at P<0. 05 level. The probabilistic model was evaluated based on overall performance, discriminatory power and calibration. Concordance was evaluated through the construction of a receiver operating characteristics curve and the C-statistic. Somer's D provides an estimate of the difference between concordant and discordant pairs on a scale of -1 to 0, in our case between the predictive model and the MRI quantification of extWML. Model fit and calibration was tested with the Hosmer and Lemeshow test Open Access (P>0. 05 implies a good fit, higher numbers signify a better fit). In the derivation cohort, missing data were handled with listwise deletion.
40 41 However, because of limited sample size and lack of precise diagnosis in the EVA study, it was not possible to take this heterogeneity into account. Another limitation to consider is that the backward deletion model may capitalise on chance variation within the dataset. However, the bootstrapping analysis showed consistency in the test score suggesting minimal optimism bias or overfitting to the 3C cohort. Another consideration for interpreting this model is the use of sex to derive the extWML thresholds based on previous findings of higher WML in women. 11 This may inadvertently reduce the predictive power of a risk score. Also,  as this study reports the development stage, the predictive ability of the scoring system requires further evaluation in an external implementation study.
Accession Numbers Sequence data from this article can be found in the Arabidopsis genome initiative database under the following accession numbers: NAC072 (AT4G27410), ABF3 (AT4G34000), ACT2 (AT3G18780), RD29A (AT5G52310), RD29B (AT5G52300), NAC055 (AT3G15500), and NAC019 (AT1G52890).
For comparison, ABF3-OX/072 plants were produced by crossing ABF3-OX with the nac072 mutant. All homozygotes were determined by hygromycin resistance screening and tri-primer PCR after F2 generation segregation (data not shown). Accumulations of NAC072 or ABF3 in these plants were shown by western blot using antibodies against a Flag or c-Myc protein tag (Figure  2C ). Thus, ABA sensitivities of these plants were examined during the development of green cotyledon and axial root growth. Overexpression of NAC072 or ABF3 (in the NAC072-OX or ABF3-OX plants) resulted in slight growth inhibition and enhanced ABA sensitivity (Figures  2C, D ; Supplementary Figures  S1, S2  and S5 ). However, overexpression of NAC072 in abf3 (NAC072-OX/abf3) resulted in less ABA sensitivity than in NAC072-OX or WT plants, and NAC072-OX/abf3 had less ABA sensitivity than abf3 (Figures  2C, D ; Supplementary Figures  S3,  S5,  and S7 ).
Lipid Extraction and Analysis The processes of lipid extraction, ESI-MS/MS analysis and quantification were performed in accordance with a protocol from  Welti et al. (2002). Data processing was performed as previously described. The lipids in each class were quantified by comparison with two internal standards of the class. Five replicates of each treatment for each genotype were analyzed. The Q test was performed on the total amount of lipid in each head-group class, and data from discordant samples was removed  (Devaiah et al. , 2006).
e. , minimizing the within group variance at different cut-offs. GO enrichments were estimated via the goseq Bioconductor package  (Young et al. , 2010)  (FDR ≤ 0. 05) on each detected cluster possessing similar expression profiles in all the stages. As goseq requires gene length data, median transcript length per gene was obtained by parsing with a custom R script cDNA fasta files, as obtained from Ensembl Plants repository. GO annotations for tomato genes were obtained via BLAST2GO  (Conesa and Götz, 2008)  against NR databases and default settings. Unless otherwise stated, further graphical outputs were obtained with R custom scripts.
Transcriptomic Perturbations in Response to Drought Stress and Rehydration To identify genes whose expression were altered by drought stress and rewatering in leaves, which could result in the observed physiological alterations, we carried out transcriptome sequencing. We used the Illumina platform on RNA samples extracted from leaves of M82 well-watered plants (WW) as well as in Dr1, RW, and Dr2 (Supplementary Table  S2 ). RNA sequencing derived data were then subjected to gene expression analyses followed by clustering of genes showing similar trends of expression by comparison of the four conditions, and by gene ontology (GO) enrichment analysis. By comparing the different treatments, we identified 966 genes that showed differential expression in at least one of the comparisons, which were therefore considered as Differentially Expressed Genes (DEGs) (Supplementary Table  S3 ).
, 1999; Cifre et al. , 2005). The efficiency of the electron transport in the photosystems also decreased as stress progressed (Figure  3 ). The low F v /F m ratio at Dr1 likely indicates that photoinactivation of PSII may have occurred  (Baker, 2008). Therefore, we conclude that photochemical limitations contributed to the decline in CO 2 assimilation along with the altered metabolic content under severe drought  (Cifre et al. , 2005; Chaves et al. , 2009). S6 ). (A) Expression value detected by RNA-seq method. (B) Expression analysis conducted by qRT-PCR. Data have been plotted on a log 2 scale. (C) Correlation between RNA-Sequencing and qRT-PCR data. The normalized expression value obtained with RNA sequencing (x axis) were compared to the log 2 of fold increase by qRT-PCR (y axis). RNA from well-watered control plants was used as calibrator sample.
Plant Materials, Growth Conditions, and Stress Treatments The rice (Oryza sativa) osgi mutant, osgi, was obtained from the Rice Tos17 insertion mutant database at the Rice Genome Resource Center, Japan. Osgi and its wild type control, cv. Nipponbare, were used for all physiological experiments. For complementation of the osgi mutant, the OsGI coding sequence was expressed in a modified pCAMBIA1300 vector under control of the Cauliflower Mosaic virus 35S promoter  (Wang et al. , 2009). The construct was introduced into osgi mutants using a Agrobacterium tumefaciens-mediated transformation method  (Wang et al. , 2009). A modified culture medium containing 1. 425 mM NH 4 NO 3 , 0. 323 mM NaH 2 PO 4 , 0. 513 mM K 2 SO 4 , 1. 643 mM MgSO 4 , 0. 998 mM CaCl 2 , 0. 125 mM EDTA-Fe(II), 0. 075 µM (NH 4 ) 6 Mo7O 24 , 0.