dataesr/scientific-paragraphs-categorization huggingface dataset:
For in silico prioritization of variants, we integrated the following features: (a) gene/transcript annotations (downloaded from UCSC Genome Browser, hg19); (b) known sequence variants from the following data sources: dbSNP, 1000 Genomes project, 200 Danish exomes,  30  NHLBI Exome Sequencing Project (ESP6500, version without indels). Base exchanges were considered as 'known' (with exception of SNVs observed as only heterozygous in ESP6500 and 1000 Genomes project) if position and type of the nucleotide were identical to entries in the reference databases. We did not use a cutoff based on minor allele frequency. In case of short indels, a tolerance in positional matching was applied based on repetitiveness of the deleted/inserted sequence in the SNV flanking sequence; (c) variants detected in the screen performed by Tarpey et al.
3  were located in transcripts derived from ENSEMBL version 54. We defined the amino-acid coordinate shared by most transcripts of a gene as reference, which is sometimes different from the one annotated by Tarpey et al. 3  Conversion of coordinates was successful for 1647 variants; (d) evolutionary conservation across 44 vertebrate species; 31 (e) splice site detection for defining potential cryptic splice sites (software NNSplice; cutoff 0. 9 (ref. 32)); (f) potential functional impact: PolyPhen2,  33  SIFT 34 and (g) Human Gene Mutation Database (HGMD): known variants with Pubmed entries were treated as potentially disease causing if they were listed in HGMD Professional and annotated in maximally one reference SNV database. We thus defined a prioritization score (PS) based on basic, computationally tractable criteria like type of variant or evolutionary conservation.
Analysis of human CLCN4 SNVs in Xenopus oocytes CLCN4 SNVs were introduced into human CLCN4 (NM_001830. 3; Gene ID: 118) cDNA cloned into pTLN and pCIneo 36 by recombinant PCR. We assessed the expression level and stability of wild-type and mutants with p. Gly78Ser, p. Leu221Val, p. Val536Met or p. Gly731Arg substitutions by western blot analysis of lysates from transiently transfected cells using standard methods. Xenopus laevis oocytes were injected with 23 ng cRNA, which was transcribed with the mMessage Machine kit (Ambion, Thermo Fisher Scientific Inc. , Waltham, MA, USA) from pTLN. 37 After 3 days incubation at 17 °C, currents were measured at room temperature using standard two-electrode voltage clamp employing TurboTEC amplifiers (npi electronic, Tamm, Germany) and pClamp10. 2 software (Molecular Devices, Sunnyvale, CA, USA).
After filtering against variants from 47000 controls, present in publicly available databases as well as our in-house database, 28 recurrent and 765 non-recurrent exonic variants, as well as 16 potential splice site variants remained (Tables  1 2 3 , Supplementary Tables  1, 2, 3  and 4 ). As a follow-up study we investigated an additional cohort of 157 unresolved, similarly pre-screened XLID families. For this cohort, we present data on pathogenic variants identified in known XLID genes, likely or potentially pathogenic variants in novel and candidate XLID genes and truncating variants unlikely implicated in XLID. For validation and segregation analyses, we prioritized variants by defining a prioritization score (PS). This score incorporates several computationally tractable pieces of information including the type of variant, evolutionary conservation and (if available) evidence that the gene has a role in XLID.
77 Furthermore, variants in TAF2 have been associated with autosomal recessive ID. 78, 79  Although additional evidence for TAF1 being implicated in XLID is currently missing, these data indicate that loss of TAF1 function could affect cognition. Quantification of transfected neurons, for total length of neuritic branches, total number of branches (a branch is considered as the segment between two branching points) and for dendritic branching complexity (levels were quantified per neuron from 1 to 6, each time a branching point is met from nucleus toward the distal part of each dendrite). Detection of co-transfections of shRNA and cDNA encoding plasmids for rescue experiments is shown as overlap of GFP (green) and Halotag (red) signals. Clcn4 experiment is shown in (a) and Cnksr2 in (c). More than 15 representative cells of each type were analyzed per experiment, with three independent experiments conducted.
30 erview of sequence variants identified in 248 index patients with XLID Human Gene Mutation Database; XLID, X-linked intellectual disability. aVariantspresent in HGMD with PubMed entries (numbers shown in parentheses) were treated as potentially disease relevant and therefore were excluded from filtering against control populations (dbSNP 135, Exome Variant Server, NHLBI Exome Sequencing Project (ESP), Seattle, WA, 1000 Genomes Project, 200 Danish exomes3). Indels = insertions and deletions. b Three duplications were only detected by using a Hidden-Markov Model-based method. 30.
ACKNOWLEDGMENTS We thank all the families who participated in this research. We also thank  Susanne Freier ,  Ines Müller ,  Rien Blok ,  Carolien Oosterhoud ,  Roel Brandts ,  Demis Tserpelis ,  Evelyn Douglas ,  Lynne Hobson ,  Pia Winter  and  Sara Ekvall  for excellent technical assistance;  Dagmar Wieczorek ,  Vincent Desportes ,  Jean-Paul Bonnefont ,  Valerie Biancalana ,  Daniel Amram ,  Stanislas Lyonnet ,  Jacqueline Vigneron ,  Veronica Cusin ,  Philippe Jonveaux ,  Laurence-Olivier Faivre ,  Lydie Burglen ,  Yves Alembik ,  Sophie Scheidecker ,  Aurelia Jacquette ,  Delphine Heron ,  Cyril Goizet ,  Marie Ange Delrue ,  Didier Lacombe ,  Odile Boute ,  Andre Megarbane ,  Anne Moncla ,  Brigitte Gilbert Tiong Tan ,  Sharron Townshend ,  Michael Gabbett ,  Zornitza Stark ,  Mac Gardner ,  Joanne Dixon ,  Ian Glass ,  Martin Delatycki ,  Salim Aftimos ,  Felicity Collins ,  Paul James ,  George McGillivray ,  Kate Pope ,  Judith Allanson ,  Claude Moraine ,  Christine Francannet ,  Annick Toutain ,  James Lespinasse ,  Brigitte Gilbert ,  Isabelle Mortemousque ,  Anne Moncla ,  Etienne Mornet ,  Albert David ,  Connie Schrander-Stumpel ,  Christine de Die-Smulders ,  Yvonne Arens ,  Eric Smeets ,  Dominique Marcus-Soekarman ,  Ute Moog ,  Bert Smeets ,  Marzena Wiśniewska ,  Renata Glazar ,  Maciej Robert Krawczyński ,  Barbara Leube ,  Magdalena Nawara ,  Agnieszka Charzewska ,  Irma Järvelä ,  Barbara Oehl-Jaschkowitz ,  Marco Henneke ,  Peter Propping ,  Gholamali Tariverdian ,  Almuth Caliebe ,  Dorothea Wand ,  Jürgen Mücke ,  Eva Seemanova ,  Birgit Zirn ,  Jörg Müsebeck ,  Rudolf Mallmann ,  Christiane Zweier ,  Rami Abou Jamra  and  Anita Rauch  for contributing families with XLID.
html. SnpStore, http://www. seqan. de/projects/snpstore. html. Online Mendelian Inheritance in Man (OMIM), http://www. ncbi. nlm. nih. gov/omim. PolyPhen2, http://genetics. bwh. harvard. edu/pph2/. SIFT, http://sift. jcvi. org/. NHLBI Exome Variant Server  ( ESP6500 ), http://evs. gs. washington. edu/EVS/. dbSNP135, dbSNP138, http://www. ncbi. nlm. nih. gov/snp. Ingenuity tool, http://www. ingenuity. com. HOPE server, http://www. cmbi. ru. nl/hope/home. shRNA designer tools, http://france. promega. com/resources/tools/. Decipher, http://decipher. sanger. ac. uk/. RNAi Consortium  (TCR) shRNA Library, http://www. broadinstitute. org/rnai/trc/lib. MutationTaster, http://www. mutationtaster. org/. The Human Gene Mutation Database, http://www. hgmd. org/. Exome Aggregation Consortium (ExAC), Cambridge, MA , http://exac.
Arg415Trp 11 14 3/2/3, C MRX61/T11 RLIM p. Pro587Arg 11 13 3/1/3, encodes ring finger protein, LIM domain interacting, Non-specific mild to profound ID in two families with variable E3 ubiquitin-protein ligase, binds to transcription factors behavior problems, ID, microcephaly, micrognathia and that play important roles for the development of neuronal cryptorchidism in all affected of one family structures and cell types D72 RLIM p. Arg387Cys 12 12 1/2/8 AU31 RLIM p. Arg599Cys 14 18 2/3/3 D177 USP27X p. Ser342Argfs*14 20 10 3/0/2, encodes ubiquitin-specific peptidase 27, interacts with Borderline to moderate ID, variable absent or poor speech USP22 which deubiquitinates core histones H2A and H2B, and behavioral problems USP22 interacts with ARID gene KIF7 L75 USP27X p. Tyr381His 12 11 1/1/2, this residue is part of a domain (IPR001394) and using HOPE web server (see URLs) the variant is predicted to cause an empty space in the core of the protein or protein complex and to cause loss of hydrophobic interactions Potentially deleterious changes in novel candidate genes L56 CDK16 p.
Trp326Valfs*5 20 37 4/1/3, encodes cyclin-dependent kinase 16, also known as ID, spastic paraplegia PCTK1, PCTAIRE1, and PCT-1 N67 TAF1 p. Asn493Asp 13 19 2/0/2, encodes TATA box binding protein (TBP)-associated Mild to severe ID, facial features factor, 250 kDa, subunit of TAFIID which plays a key role transcription initiation. Drosophila homolog phosphorylates histone H2B, variants in TAF2 cause ARID 78,79 D185 TAF1 p. Arg1190Cys 14 27 2/4/7 Abbreviations: C, clinical evidence; F, functional evidence from this study; HGMD, Human Gene Mutation Database; ID, intellectual disability; PS, prioritization score, includes type of variant, evolutionary 35nservation and predictions from Polyphen2 and SIFT; C score obtained by using Combined Annotation-Dependent Depletion (CADD);35XLID, X-linked intellectual disability.
5-fold). All candidate regions were found to be due to local drop-offs in neighbouring regions rather than excess coverage in focal windows. For REL606-derived strains, candidate genomic differences compared with the ancestral genome were identified using the PALOMA  (Vallenet et al. , 2012)  and BRESEQ  (Barrick et al. , 2009)  pipelines. Sequencing data for the MG1655-derived strains and the 20k strain have been deposited in the European Nucleotide Archive (accession no. PRJEB7107). Sequencing data for the REL606-derived 40k clone was previously deposited in the National Center for Biotechnology Information Sequence Read Archive (accession no. SRR1536189).
Acknowledgements We thank  Heinz Himmelbauer  and the  CRG Genomics Unit  for sequencing the ΔmutH mutator strain and its laboratory ancestor;  Sanjay Khadayate  for input into mutation identification; and  Laurence Hurst ,  Ben Lehner ,  Fran Supek , and  Bojan Zagrovic  for comments. MR and AK are grateful to  Tea Copic  for technical support and to  Tobias Bergmiller  for the TB56 and TB62 strains and valuable advice. This work was funded by the  European Union  program  FP7-ICT-2013-10 project EvoEvo  grant  610427 , the  Universit é Grenoble Alpes  and the  CNRS  (to DS); MRC core funding (to TW);  Fondation Nelia et Amedeo Barletta  and the  Mediterranean Institute for Life Sciences  (to MR and AK).
Genetic and phenotypic data Leaf material was collected from 87 individual plants coming from two important ex situ collections, i. e. that of CATIE (Centro Agronómico Tropical de Investigación y Enseñanza), in Turrialba, Costa Rica and that of INIA (Instituto Nacional de Investigación Agraria) in Iquitos, Peru, as well as from collections in commercial farms in Colombia; samples were obtained/collected between 2009 and 2010. Material transfer agreements were signed with the genebanks of CATIE and INIA for their respective samples and permission was obtained by the owners of the farms from which the samples from Colombia were collected; only domesticated specimens were collected on-farm. A list of the material and passport information is given in S1 Table. The genebank samples (one tree per accession) were chosen in order to represent the broad phenotypic diversity available in both collections.
Based on measures of fruit weight, three accessions in the dataset appeared to be from wild populations (fruit weight < 10 g), possibly belonging to B. gasipaes var. chichagui. These individuals (marked with an asterisk in S1 Table ) all come from the Amazon basin, and were removed from the analyses. Collected leaf material was dried and conserved in zip-lock plastic bags with silica gel until DNA extraction (see S1 Text for details). Peach-palm specific microsatellite markers  [28]  (see S2 Table for primer sequences) were amplified on the samples. Population genetic parameters such as allele number, average allele frequency, heterozygosity (expected and observed), and the interindividual fixation index (Fis), were calculated and a Mantel test was conducted between the samples' geographical distances and their genetic distances  [29] , searching for evidence of genetic structuring and patterns of isolation by distance.
All analyses were performed in R  [30] , using packages Adegenet 1. 4-2  [31]  and Vegan 2. 0-8  [32]. Morphological and biochemical traits were measured (see S2 Text for details) on a subset of the molecular dataset, which includes the 67 cultivated accessions corresponding to those from CATIE and INIA Peru but excludes the samples collected on-farm in Colombia.
Suitability modeling We constructed a dataset containing 221 presence points of which 166 pertained to the cultivated form (B. gasipaes var. gasipaes) and 55 to the wild form (B. gasiapes var. chichagui). Additional presence points to those of the present study were collected from a variety of sources, including published papers  [6, 8] , members of the Latin American Forest Genetic Resources Network (Laforgen), and the Global Biodiversity Information Facility  [33]. The full dataset is shown in Fig  1 , with different colours and symbols distinguishing wild from cultivated samples, as well as samples used only for modelling from those on which genetic and/or phenotypic diversity analyses were carried out. We characterized the spatial distribution of favorable habitat conditions of peach palm under current, past, and future climatic conditions by means of suitability mapping based on ensembles of modelling algorithms, implemented in R package BiodiversityR  [35]  (see S3 Text for details on the modelling algorithms considered and calibration methods).
We tested three minumum sample sizes: 3 trees (the median value of all cells containing trees), 6 and 10 trees per cell. In each scenario all cells with fewer than the minimum number of trees were discarded from the analysis. For each of the retained grid cells, we averaged the values obtained for each of the genetic parameters as calculated for 1,000 bootstrapped samples  [43]. As the trends in genetic parameters obtained for the three sample sizes were highly correlated (S3 Table ), in what follows we will present the results obtained for a sample size of 3 trees per grid cell in order to maximize spatial coverage. To increase the geographical coverage of the genetic diversity patterns in peach palm, we performed a similar replication-bootstrapping exercise for allelic richness and locally common alleles based on the molecular marker dataset of Hernández et al  [37]  which included genetic data from four molecular markers (three in common with our study) measured on wild and cultivated individuals classified into 18 geographical populations (20 individuals per population for the cultivated samples, less in the case of the wild types, refer to  [37]  for further methodological details).
After discarding wild samples, we generated maps with the same resolution as described above and the same sample size of 3 trees per cell. To allow for comprehensive analyses of genetic diversity patterns of peach palm, we spatially combined the results from Hernández et al  [37]  with ours. Since both sample sets were genetically characterized in different laboratories and using a different number of markers, we first standardized the cell values of the rasters from each dataset to a common range of 0 to 1 and then merged both raster layers by assigning each cell containing a value from either one or both dataset the highest value among the two. We applied a similar replication-bootstrapping procedure to our dataset of morphological and biochemical characteristics of peach palm fruits and calculated the average coefficient of variation across all parameters (hereafter referred to as phenotypic variation, for the sake of brevity).
Prioritizing conservation areas We identified priority areas for on-farm conservation of peach palm based on the geographical intersect between areas for which the ensemble of distribution models returned high suitability scores during present and future (2050s) climate conditions, and areas holding the highest levels of allelic richness. Each of the layers here considered was restricted to the values above the third quartile of their density distributions. Similarly, we considered the geographical intersect between areas for which suitability scores under current and future (2050) climate conditions were high, and areas above the third quantile of the distribution of phenotypic variation (using the dataset resulting from the bootstrapping exercise described earlier), in order to look into priority areas for conservation of peach palm's morphological and biochemical diversity.
Genetic and phenotypic diversity After removing the three putatively wild samples from our dataset, only 80 of the samples submitted to genetic analyses and 66 of the samples submitted to morphological and biochemical analyses yielded meaningful results. All analysed loci were polymorphic with a total number of 68 alleles; level of polymorphisms per locus ranged from 4 (locus BG-24) to 12 alleles (locus BG-1 and BG-63) with an average of 7. 5 alleles per locus. Expected heterozygosity (He) varied between 0. 636 (locus BG-17) to 0. 881 (locus BG-3). The extent of reduction in observed heterozygosity was used to quantify the level of genetic differentiation between the individuals at each locus, through F statistics  (Wright 1951 (Wright , 1965)). The differentiation among individuals at different loci ranged from 0.
037 to 0. 455 (maximum at locus BG-17) (details on the results of population genetic parameters can be found in S4 Table ). Distribution patterns of genetic diversity show that both allelic richness and observed heterozygosity reach their highest values in the area covering the Ecuadorian Amazon (Fig  3A  and 3C , respectively). Lower but still notable allelic richness is observed among the samples from the Colombian Llanos (Vichada department; Fig  3A ). A map of allelic richness based on the dataset from Hernández et al  [37]  shows high richness in the Peruvian and western Brazilian Amazon. This data also highlights high allelic richness in Panama, close to the border with Colombia (Fig  4A ). Highest richness of locally common alleles according to the present study's dataset are found in the Ecuadorian and northern Peruvian Amazon, followed by the Cauca area and the Llanos in Colombia (Fig 3B ), while the dataset from Hernández et al  [37]  detects a hotspot in central Bolivia (Fig  4B ).
The fact that the values obtained for LCA and allelic richness did not always perfectly align at all sampling sites, both within our data and between our dataset and that of Hernández et al  [37] , is likely due to the fact that the different parameters focus on different aspects of genetic diversity, and possibly also to the small sample size we used, which exposes measures to a certain degree of stochasticity. The areas holding highest fruit morphological and biochemical diversity among those the present study covers are found in the northern Peruvian and Ecuadorian Amazon followed by southern Panama (Fig  3D ). Additional maps displaying the spatial distribution of the variation of phenotypic traits for the CATIE and INIA collections separately, as well as of single morphological and biochemical traits for each collection are shown in S1 to S3 Figs.
Another area of congruence is the northern Peruvian Amazon, where the highest levels of phenotypic diversity of our peach palm dataset was observed, confirming earlier observations  [17]. In this very same area the highest diversity of genetic clusters in cacao (which to some level are comparable to landraces in peach palm; see  [43] ) were found, which the authors related to the fact that the northern Peruvian Amazon region was an important center of crop genetic resources at the time of European conquest  [20, 49]. Such centers are known to have concentrated and created crop diversity through trade, cultivation and selection to guarantee their inhabitants' subsistence and survival. In peach palm, the legacy of such human-mediated processes might be manifested by the convergence of many different landraces in this region (Fig 2 ), such as the Pampa Hermosa, Yurimaguas, Tigre and Putumayo  [21].
The domestication of peach palm: a hypothesis Drawing on the present results, and building on previous findings reported in literature, in what follows we present a hypothesis of how peach palm may have evolved from a wild species Priorities for on-farm conservation of areas rich in genetic and phenotypic diversity and likely to remain suitable so in the future (in red and yellow, respectively). Dotted polygons represent areas likely to be occupied by indigenous peoples (based on language maps from the Ethnologue database  [47] ), suggesting sites where on-farm conservation may be already carried out by local communities or could be strengthened through their involvement. doi:10. 1371/journal. pone. 0144644. g008 into the cultivated landraces known today across Latin America. While acknowledging that our dataset is too small to unmistakingly validate this hypothesis, we hope that it can inspire future research aimed at furthering our understanding of the temporal and spatial dynamic of this important Amazonian crop.
In conclusion, our preliminary results highlight the usefulness of spatial analyses for making molecular data more explicit and meaningful within the broader context of geography, landscapes, climate dynamics, and human history and culture. Further validation of the initial hypotheses presented here for peach palm is needed, requiring the assemblage of larger genetic and phenotypic datasets at continental level (of both wild and cultivated populations), the use of standardized molecular markers (both nuclear and chloroplast) and protocols across different datasets and regions to facilitate aggregate analyses.
As the experiment progresses, mitochondria morphology appears to alter from tubular structures to round punctate or larger aggregations; (c) Primary neurons loaded with JC-1 were imaged every minute during OGD followed by analyses of mitochondrial length. Data shown are an average of 360 mitochondria per time point, and mitochondria from the first and last time points analyzed by student's t-test in the panel below, *** p < 0. 001; (d) Primary neurons were subjected to 90 min of OGD followed by up to 24 h incubation in normal growth medium. Lysates were assayed for citrate synthase activity at time points shown following the insult. Data is shown ± SD, n = 4-6 independent litters, determined by two-way ANOVA followed by a Bonferroni post-hoc test, ** p < 0. 01 for interaction and treatment.
, OPA1 ). There was a small but significant decrease in OPA1 expression in response to OGD exposure (a = 0. 0296). Mean data shown ± SD (n = 4-5 independent litters), significance determined by two way ANOVA; (b) Protein lysates were generated from primary neurons either immediately after 90 min OGD (0 h) or following 6 or 24 h recovery. Proteins were resolved by SDS-PAGE and OPA1 analyzed by western blot. Equal protein loading was determined by GAPDH expression. Size distribution of the OPA1 immunoreactivity is expressed as a proportion of total OPA1 (arrowheads). There was a significant increase in the expression of the OPA1 lower band at 0 and 6 h, significance determined by two-way ANOVA for treatment and band. If there was a significant interaction, a Bonferroni post-hoc was performed.