dataesr/scientific-paragraphs-categorization huggingface dataset:
In marked contrast to her younger brother, F1:V-I is essentially clinically asymptomatic at the age of 10 years, although she has recently developed significant proteinuria and demonstrates a chronic elevation of ESR and interferon-induced gene transcripts. Using a new digital ELISA assay, we recorded increased levels of interferon alpha protein in serum and plasma from all three patients with mutations in DNase II, and showed that cells from these patients produce increased amounts of type I interferon and demonstrate enhanced STAT1 phosphorylation. Concordantly, we recorded a significant type I interferon signature by genomewide RNA-Seq analysis, similar to that observed in patients with other type I interferonopathies. Although mouse data emphasize the induction of both interferon and non-interferon-mediated inflammation in the absence of DNase II, the post-natal murine phenotype associated with DNase II deficiency in the context of functional type I interferon signaling has not been defined.
Methods Patient and study approval. The study was approved by the Comité de Protection des Personnes (ID-RCB/EUDRACT: 2014-A01017-40) in France, and the Comitato Indipendente di Bioetica, IRCCS Burlo Garofolo (19/2015; RC17/2014) in Italy. Investigations were undertaken with written informed parental consent, and the assent of the probands in both families. Whole-exome sequencing. DNA was extracted from whole blood samples using an in-house salting out method. Agilent SureSelect libraries were prepared from 3 µg of genomic DNA extracted from leukocytes, sheared with a Covaris S2 Ultrasonicator as recommended by the manufacturer. We used a 51 Mb SureSelect Human All Exon kit V5 (Agilent technologies) for exome capture, with multiplexed molecular barcodes for sample traceability. Pooled barcoded exome libraries were then sequenced on a HiSeq2500 (Illumina) machine, generating 76 + 76 bp paired-end reads, followed by processing using Genome Analysis Toolkit (GATK), SAMtools, and Picard (http://www.
broadinstitute. org/gatk/guide/topic?name = best-practices). Calls were made with the GATK HaplotypeCaller, and variants assessed using the in silico programs SIFT (http://sift. jcvi. org) and Polyphen2 (http://genetics. bwh. harvard. edu/pph2/), and population allele frequencies obtained from the ExAC (http://exac. broadinstitute. org) and gnomAD (http:// gnomad. broadinstitute. org) databases. We have screened close to 1000 probands for an interferon signature, and performed over 2500 interferon signatures in total (as outlined in Rice et al. 14  ). Not every patient has had genetic analysis, and it is possible that we are not comprehensively ascertaining DNASE2-mutated patients because, for example, they are dying due to the perinatal hematological phenotype. However, the clinical scenario that we describe in this manuscript is apparently rare in our cohort.
Using TaqMan probes for DNASE2 exon 4 (Hs00172391_m1) and DNASE2 exon5 (Hs00923081_m1), the relative abundance of each target transcript was normalized to the expression level of HPRT1 (Hs03929096_g1) and 18 S rRNA (Hs999999001_s1), and assessed with the Applied Biosystems StepOne Software v2. 1 and DataAssist Software v. 3. 01. JUP FMNL2 HESX1 GRB10 IL1R2 LHX4 LOXHD1 CRISP3 GYPA HOXA1 PDE9A SLC1A3 RHCE RP13-216E22. 4 ATF3 ATF2C2 RN7SL600P SLC14A1 FRMD4A SMIM24 KLC3 LINC00570 CTSE FAM225A DUSP13 TRIM10 RP11-476D10. 1 OSBP2 TMCC2 HIST2H2BF SNCA HIST1H2BF TMEM252 IL18R1 KIAA0825 CD274 FAM8A1 TMEM123 C2orf88 JAK2 RP11-85G21. 3 HEMGN TMEM92 ATP1B2 EMID1 CXCL11 RP11-305F5. 2 ABCC13 RPL5P4 RP11-20D14. 6 HIST1H2BD CEACAM1 RP1-221C16. 8 AP000662. 4 NKAIN1 BCL2L1 HBZ ALAS2 SELENBP1 EPB42 THEM5 CTD-2521M24.
We performed quantitative reverse transcription polymerase chain reaction (qPCR) analysis using the TaqMan Universal PCR Master Mix (Applied Biosystems), and cDNA derived from 40 ng total RNA. Using TaqMan probes for IFI27 (Hs01086370_m1), IFI44L (Hs00199115_m1), IFIT1 (Hs00356631_g1), ISG15 (Hs00192713_m1), RSAD2 (Hs01057264_m1), and SIGLEC1 (Hs00988063_m1), the relative abundance of each of 6 'interferon score' target transcripts was normalized to the expression level of HPRT1 (Hs03929096_g1), and 18 S rRNA (Hs999999001_s1), assessed using the Applied Biosystems StepOne Software v2. 1 and DataAssist Software v. 3. 01. Individual data were expressed relative to a single calibrator for each of the six probes. RQ (relative quantification) is equal to 2 -ΔΔCt , i. e. , the normalized fold change relative to the control data.
The median fold change of the 6 genes compared to the median of 29 previously collected healthy controls is used to create an interferon score for each individual, with an abnormal interferon score being defined as greater than +2 SD above the mean of the control group, i. e. , 2. 466. For the extended interferon analysis, the relative abundance of target transcripts, was measured using the additional TaqMan probes Ly6E (Hs00158942_m1), MX1 (Hs00895598_m1), USP18 (Hs00276441_m1), OAS1 (Hs00973637_m1), IFI44 (Hs00197427_m1), IFI6 (Hs00242571_m1), IFIT3 (Hs00155468_m1), IRF7 (Hs00185375_m1) and STAT1 (Hs01013989_m1), was normalized to the expression level of HPRT1 (Hs03929096_g1) and 18 s (Hs999999001_s1) and assessed with Applied Biosystems StepOne Software v2. 1. ISG RNA expression in PBMCs.
Messenger RNA from treated and non-treated cultured cells were quantified by qRT-PCR using TaqMan probes for IFI27 (Hs01086370_m1), IFI44L (Hs00199115_m1), ISG15 (Hs00192713_m1), and SIGLEC1 (Hs00988063_m1), the relative abundance of each target transcript normalized to the expression level of HPRT1 (Hs03929096_g1), and assessed with the Applied Biosystems StepOne Software v2. 1. ISG RNA expression analysis. 1 × 10 6 cells were lysed in 350 µL RLT-Buffer (Qiagen), frozen at -80 °C, thawed, supplemented with 1 volume 70% Ethanol and loaded onto a Zymo III column (Zymo). The column was then washed with RW1buffer (Qiagen) and then RNA wash buffer (Zymo) and eluted with DEPC water. Samples were then subjected to DNase I digestion and reverse transcription with OligodT primers and RevertAid (all from ThermoFischer, Waltham, MA, USA) according to the manufacturer's instructions.
We extracted total RNA from blood samples in PaxGene tubes (Qiagen, Valencia, CA), and analyzed RNA integrity with an Agilent 2100 Bioanalyzer. We used the Illumina TruSeq RNA Sample Preparation Kit (Illumina) for mRNA purification and fragmentation, complementary DNA synthesis and target amplification. cDNA libraries were then pooled and sequenced on a HiSeq 2000 Illumina platform (Illumina). The RNA-seq workflow was as follows: quality assessment by FastQC (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/), quality filtering with Trimmomatic (PMID: 24695404), read mapping with STAR (PMID: 23104886) to hg38, read counting into genes with HTSeq (PMID: 25260700) using annotation from GENCODE v24 (http://www. gencodegenes. org/), normalization and differential expression analysis with DESeq2 (PMID: 25516281).
Hierarchical clustering was conducted using the Partek software (version 6. 6). Patients and healthy controls were compared using ANOVA analysis, and a list of the 2-fold up or downregulated genes was generated. The statistical significance level adopted was p < 0. 05. Gene lists were uploaded into Ingenuity Pathway Analysis (http://www. ingenuity. com) in order to determine differentially regulated canonical pathways in the patients. Results for interferon-regulated genes are shown as a heat map, with shades of red denoting upregulated genes and shades of blue denoting downregulated genes. siRNA knockdown of DNASE2. siRNA knockdown was performed in primary fibroblasts via repetitive transient transfection using with 150 nM of SMARTpool ON-TARGETplus siRNA (Dharmacon) targeting DNASE2 (NCBI refseq: NM_001375) or a negative control.
Cells were stained with FITC-anti-STAT1 pY701 (BD Bioscience, cat: 612596, 4a, 1:5), PE-anti-STAT1 pY701 (BD Bioscience, cat: 612564, 4a, 1:5) or FITC-anti-STAT3 pY705 (BD Bioscience, cat: 612564, 4a, 1:5) and cell surface markers APC-CD3 (Miltenyi Biotec, cat: 160-109-462, REA613, 1:30) and APC-Alexa750-CD14 (Beckman Coulter, cat: B92421, RM052, 1:30)) for 1 h at room temperature protected from light. Flow cytometry analysis was performed on a Gallios Beckman Coulter flow cytometer. Results were analyzed using Kaluza software v1. Interferon alpha in serum and supernatant. As reported by Rodero et al. 26  , a Simoa interferon alpha (IFN-α) assay was developed using a Quanterix Homebrew Simoa assay and two autoantibodies specific for IFN-α isolated and cloned from two APS1/APECED patients recently described  24.
Acknowledgements Y. J. C. acknowledges the  European Research Council  ( GA 309449 ), and a state subsidy managed by the  National Research Agency (France)  under the  "Investments for the Future" program  bearing the reference  ANR-10-IAHU-01. We thank  ImmunoQure AG  for sharing of antibodies used to assess interferon alpha protein levels in the Simoa assay. M. -L. F. is supported by the  Institut National de la Santé et de la Recherche Médicale  (Grant number  000427993 ). A. T. and M. G. acknowledge the  Italian Telethon  (Grant no. GGP15241A ). A. T. acknowledges the Institute for Maternal and  Child Health-IRCCS "Burlo Garofolo " ( RC 17/2014  funded by  Italian Ministry of Health , art 12 and 12bis D. lgs  502/92 ), the " Associazione Azzurra Malattie Rare " and the " Beneficientia Stiftung in Vaduz ".
, 2014) , although the exact identity of this endosymbiotic acquisition remain unresolved. Characterising the ancestral ochrophyte plastid proteome might therefore help answer major questions about the ways in which plastids become established in the host cell, and provide valuable insights into the origins and diversification of other ecologically important algal lineages. In this study, we present an experimentally verified in silico reconstruction of the proteins targeted to the plastid of the last common ochrophyte ancestor. We show that this ancestral plastidtargeted proteome was an evolutionary mosaic, containing 770 proteins from a range of different sources. Our dataset indicates that the ochrophyte plastid was acquired late in stramenopile evolution, following the divergence of extant aplastidic relatives, that plastid-targeted proteins of green algal origin played a significant role in its origin, and that there has been bidirectional integration of the biology of the ochrophyte host and plastid proteomes, such as the ancient recruitment of proteins from both host and endosymbiont to dually support the biology of the plastid and mitochondria.
Each shaded cell corresponds to an identified orthologue in one sub-category of a particular ochrophyte lineage: orange cells indicate presence of chrysistan subcategories; light brown cells the presence of hypogyristean sub-categories; and dark brown cells the presence of diatom sub-categories. In each graph, black arrows label the conservation thresholds inferred to give the strongest separation (as inferred by chi-squared P-value) between positive and negative control sequences. The table (iii) tabulates the three conservation patterns identified as appropriate for distinguishing probable ancestral HPPGs from false positives. (Panel C) shows the complete HPPG assembly, alignment and phylogenetic pathway used to identify conserved plastidtargeted proteins. (Panel D) tabulates the number of HPPGs built using ASAFind and HECTAR predictions, and the number of non-redundant HPPGs identified in the final dataset.
The final total represents the pooled total of non-redundant HPPGs identified with both ASAFind and HECTAR. DOI: 10. 7554/eLife. 23717. 003 The following figure supplement is available for figure  1 : We next tested the level of conservation best able to identify truly ancestral HPPGs. We selected three patterns of conservation that identified the largest number of HPPGs from a positive control dataset of proteins with previously identified plastid-associated functions, and minimised the number identified from a negative control dataset of HPPGs generated using seed sequences from three other published CASH lineage genomes, for which no plastid-targeted orthologues were detected in any ochrophyte genome sequence (Materials and methods; Table  S2 -sheet 2, sections 1-2; Table  S3 -sheet 2, sections 1-2  [Dorrell et al.
, 2016] ). The selected conservation patterns were: the presence of the protein in a majority (!2/3) of chrysistan sub-categories and a majority of either diatom (!3/5) or hypogyristean (!2/3) sub-categories; or presence in at least one chrysistan sub-category and a majority of both diatoms and hypogyristea (Figure  1 , panel B). We extracted HPPGs matching the conservation patterns defined above and verified their monophyly within ochrophytes via alignment and single-gene trees (Figure  1 , panel C; Table  S4 -sheet 1  [Dorrell et al. , 2016] ). From this, we identified 770 proteins that were probably targeted to the ancestral ochrophyte plastid (Figure  1 , panel D; Table  S4 -sheet 2  [Dorrell et al. , 2016] ). This dataset is significantly enriched in proteins from within the positive control dataset and contains significantly fewer proteins from the negative control dataset than would be expected through random assortment (chi-squared test, p<1Â10 À10 ; Figure  1 ), confirming its specificity towards probable ancestral plastid-targeted proteins.
Experimental verification of ancestral ochrophyte HPPGs We wished to verify that the ancestral ochrophyte plastid-targeted proteins inferred from the in silico pipeline are genuinely plastid-targeted. 106 of our inferred ancestral HPPGs include a P. tricornutum protein with prior experimental plastid localization, or unambiguous plastid function (Figure  1 , panel D), but the remainder do not. We selected ten proteins for experimental localisation (Figure  2 , panel A; Table  S5   [Dorrell et al. , 2016] ). These were chosen on the basis of having only non-plastid annotations on the first 50 BLAST hits against the NCBI nr database excluding ochrophytes, hence lack specific a priori evidence for a plastid localization. In each case, all of the ochrophyte protein sequences within the alignment had a well conserved central domain, and a highly variable N-terminal domain of between 30 and 50 amino acids containing an ASAFAP motif, consistent with a conserved plastid targeting sequence  (Gruber et al.
Evolutionary origins of the ochrophyte plastid The ochrophyte plastid is an evolutionary mosaic We wished to identify the evolutionary affinity of each ancestral HPPG in our dataset. In particular, we assessed whether proteins that are of unconventional origin, such as the products of genes endogenous to the host, or genes that have been acquired from other sources such as prokaryotes and green algae, have significantly contributed to the origins of the ochrophyte plastid  (Dorrell and Smith, 2011; Moustafa et al. , 2009). We accordingly determined the closest relative of each ancestral HPPG (Materials and methods). Due to ongoing controversies regarding the evolutionary composition of ochrophyte genomes  (Woehle et al. , 2011; Deschamps and Moreira, 2012) , we utilised a combined phylogenetic and BLAST top hit approach to robustly infer the most probable origin of each HPPG (Materials and methods; Table  S4 -sheet 2  [Dorrell et al.
, 2016] ). For both the BLAST and phylogenetic analyses, stringent criteria were applied to avoid misidentification due to topological ambiguity, or contamination within individual sequence datasets  (Marron et al. , 2016; Dorrell et al. , 2017)  (Materials and methods). We took the union of these two analyses to produce a dataset of 263 HPPGs for which both phylogenetic and BLAST top hit analyses indicated the same clear evolutionary origin. These origins were grouped into six evolutionary categories, red algae, green algae, aplastidic stramenopiles, other eukaryotes, prokaryotes, and viruses (Figure  3 , panel A). Of the 263 HPPGs that were resolved from the combined analysis, 149 (57%) were of red algal, i. e. endosymbiont origin (Figure  3 , panel A; Table  S4 -sheet 3  [Dorrell et al.
First, we noted that the majority (20/26) of the ochrophyte HPPGs with aplastidic stramenopile origins specifically resolved as a sister-group to oomycetes, as opposed to the deeper-branching labyrinthulomycetes or slopalinids (Figure  3 , panel B; Table  S4 -sheet 3  [Dorrell et al. , 2016] ). Because oomycetes are the sister-group of ochrophytes  (Aleoshin et al. , 2016; Derelle et al. , 2016) , this suggests that our dataset retains useful phylogenetic signal. Next, from the 26 ancestral HPPGs of aplastidic stramenopile origin, we identified a clear sistergroup to the stramenopile clade for 16 HPPGs using BLAST, and for 18 HPPGs using single-gene trees (Figure  3 , panel B). However, only one BLAST top hit and four trees showed a deeper red algal affinity (Figure  3 , panel B). These proportions are significantly smaller than the proportions of ochrophyte proteins of red origin in the entire ancestral HPPG dataset (expected frequencies: 9.
, 2016] ). We therefore conclude that these green genes were not misidentified as the result of undersampling within red sequence libraries, or secondary gene loss events in the red algae  (Ku et al. , 2015; Qiu et al. , 2015). We then considered whether the green genes in our dataset originate from a specific source within the green algae. Phylogenetic analyses of the HPPGs of verified green origin exhibited a strong bias toward chlorophyte origins. Ochrophytes branched as sister-groups to individual or multiple chlorophyte lineages in 51 of the 67 trees (Figure  4  Similarly, we noted a strong predominance of chlorophyte lineages amongst BLAST top hits (56/67) despite the fact that these lineages only correspond to approximately 25% of the green sequences present in our libraries (Figure  4 -figure supplement 3; Table  S4 -sheet 3  [Dorrell et al.
We accordingly constructed a secondary dataset, consisting of 7140 non-redundant gene families that are broadly distributed across the ochrophytes, and tested the targeting preferences of proteins from each HPPG (Figure  4 , panel E; Figure  4 -figure supplement 5; Table  S8 -sheet 1  [Dorrell et al. , 2016] ). 871 gene families resolved with the green algae per BLAST top hit analysis (Figure  4 -figure supplement 5; Table  S8 -sheet 2  [Dorrell et al. , 2016] ). Using both ASAFind  (Gruber et al. , 2015)  and HECTAR  (Gschloessl et al. , 2008) , gene families of predicted green algal origin were significantly more likely to encode proteins with plastid-targeting predictions than the dataset as a whole (chi-squared, p<1E À03 ; Figure  4 , panel E; Figure  4 -figure supplement 5; Table  S8 -sheet 3  [Dorrell et al.
, 2016) ]. We also observed a similar, though stronger, bias towards   D ) lists the number of residues inferred from a dataset of 32 ochrophyte HPPGs of verified green origin, which have been subsequently entirely vertically inherited in all major photosynthetic eukaryotic lineages, to be uniquely shared between ochrophytes and some but not all green lineages, hence might represent specific synapomorphic residues. Residues are categorized by inferred origin point within the tree topology shown in panel A, i. e. , each of the five ancestral nodes labelled. A final category shows all of the residues inferred to be specifically shared with one green sub-category, and not with any other. The distribution of residues based on the earliest possible origin point (taking into account gapped and missing residues in each HPPG alignment) is shown in Figure  4 -figure supplement 4.
(Panel E) shows the number of the 7140 conserved gene families inferred to have been present in the last common ochrophyte ancestor that are predicted by ASAFind to encode proteins targeted to the plastid, subdivided by probable evolutionary origin, and the number expected to be present in each category assuming a random distribution of plastid-targeted proteins across the entire dataset, independent of evolutionary origin. Evolutionary categories of proteins found to be significantly more likely (chi-squared test, p=0. 05) to encode plastid-targeted proteins than would be expected are labelled with black arrows. An equivalent distribution of plastid-targeted proteins inferred using HECTAR is shown in   S8 -sheet 3  [Dorrell et al. , 2016] ). Collectively, our data support the presence of genes of chlorophyte origin in the last common ochrophyte ancestor, which are biased towards encoding proteins with predicted plastid localisations, consistent with an acquisition through a plastid endosymbiosis event.
Functional consequences of mosaic origins for the ochrophyte plastid Metabolic completeness of the ochrophyte plastid We identified effectively complete core plastid metabolism pathways within the ancestral HPPG dataset (  Figure 5, panel A;   [Dorrell et al. , 2016] ). The majority of the remaining proteins remain plastid-encoded in some ochrophyte lineages, or are dispensible for the metabolic pathway (Figure  5 -figure supplements 1 and 2)  (Ershov et al. , 2000; Rohdich et al. , 2002; Gutierrez-Marcos et al. , 1996). In four cases (isopropylmalate synthase, sedoheptulose bisphosphatase, 3-dehydroquinate synthase, and shikimate kinase) lateral gene transfer and replacement events have occurred into individual ochrophyte lineages since their radiation, preventing identification of a single HPPG within the ancestral dataset (Figure  5 , panel A; Figure  5 -figure supplements 2-6).
Consistent with this latter idea, we found very little evidence that individual categories of HPPG (i. e. , red algal, green algal, prokaryotic or host origin) are associated with particular KOG annotations, as inferred by chi-squared testing (p<0. 05) against a null hypothesis that all KOG families and classes are homogenously distributed across the ancestral HPPG dataset, independent of evolutionary origin (Figure  5   S9 -sheet 2  [Dorrell et al. , 2016] ). The notable exceptions are prokaryotic HPPGs being elevated in information storage and processing proteins, particularly those involved in translation, while HPPGs of host origin were enriched in proteins involved in cellular processes and signalling relative to the ancestral HPPG set as a whole (Figure  5   S9 -sheet 2  [Dorrell et al.
Ancient origins of chimeric plastid-targeted proteins We considered whether the mixing of proteins from different evolutionary sources might have more substantially changed the biology of the ochrophyte plastid. It has recently been reported  (Meheust et al. , 2016)  that proteins of chimeric evolutionary origin, generated by the fusion of  domains from different evolutionary sources, form a significant component of plastid proteomes. Thus, the chimeric origins of the ochrophyte plastid might have enabled the creation of syncretic proteins not found in the endosymbiont or host ancestors. We identified orthologues of seven chimeric proteins identified in this study within our dataset, underlining their importance for the establishment of the ochrophyte plastid (Figure  6 , panel A)  (Meheust et al.
Complex evolutionary origins of CASH lineage plastids A pelagophyte/dictyochophyte origin of the haptophyte plastid proteome We considered whether our dataset provides evidence for any of the other CASH lineage plastids (cryptomonads, haptophytes, or photosynthetic alveolates) originating within the ochrophytes  (Dorrell and Smith, 2011; Stiller et al. , 2014; S ˇevcˇı ´kovaet al. , 2015) , or evidence for gene transfer from ochrophytes into lineages with complex plastids of green algal origin (chlorarachniophytes and euglenids)  (Maruyama et al. , 2011; Archibald et al. , 2003). In a majority (243/437) of trees in which they could be assigned a clear origin, plastid-targeted proteins from haptophytes resolved at a position within the ochrophyte clade (Materials and methods; Figure  8 , panel A; Table  S4 -sheet  [Dorrell et al.