dataesr/scientific-paragraphs-categorization huggingface dataset:
The exposure assessment model considers three stages: production, processing and distribution and preparation and consumption. It combines and modifies the USDA model mentioned above and an unpublished Health Canada risk assessment model developed in 2001 for S. Enteritidis, from which the structure and the shape/values given to distributions and parameters were derived. Generally, where input types were similar, the Health Canada model parameters were used. A comparative assessment of the existing dose-response models and their fit to the available epidemiological data led FAO-WHO to the choice of a single beta-Poisson dose-response function for all members of the population since it was concluded that there is insufficient evidence in the current outbreak database to conclude that some segments of the population have a higher probability of illness compared with others.
The prevalence of contaminated eggs in the original AECL model was determined from Australian and international surveys of egg contamination by non-S. Enteritidis serovars. This approach was modified by combining European data on the flock infection prevalence, the within-flock prevalence and the rate of contaminated eggs laid by infected hens. The Poisson distribution for the initial number of S. Enteritidis in the egg at the time of lay was truncated at one to avoid the possibility of no cells being present in a contaminated egg. The assumption that S. Enteritidis would grow in the first 24 hours after lay was removed after a reevaluation of scientific evidence for naturally contaminated eggs. Best, median and worst case scenarios were provided for practices on farm and during processing.
The process is repeated for any subsequent stages (Figure  9 ). The Microsoft Excel add-in software @Risk version 6. 2. 0 (Palisade Corporation) was used for all simulations 25. 25 Latin Hypercube sampling of distributions with a default setting of 100 000 iterations was used for all simulations. Convergence was monitored every 500 iterations and stopped when statistics changed by <1. 5 %.
Inputs for MAESM The prevalence of eggs contaminated with S. Enteritidis was estimated by combining the flock infection prevalence, the within flock prevalence and the rate of contaminated eggs laid by infected hens. Flock prevalence estimates were obtained from harmonised monitoring data from EU MSs in 2012  (EFSA and ECDC, 2014). The within-flock prevalence and the rate of contaminated eggs laid by infected hens were based on research carried out in the United Kingdom  (Arnold et al. , 2014a)  combined with expert opinion, as the data in the reference was considered not to fully reflect the variation in within-flock prevalence across the EU. The initial number of S. Enteritidis in a contaminated egg was defined using a Poisson distribution with a mean of 7 with lower bound truncated to one to account for the presence of at least one organism, to account for the variability in the numbers found in newly laid eggs and for the potential growth in the first 24 hours.
The growth of S. Enteritidis was capped at 10 10 CFU/egg in this model. Data on times and temperatures of storage during the different stages were collected by means of a questionnaire submitted to competent authorities and representatives of the egg industry in several MSs. In addition, expert opinion from the Working Group and Panel was used to fill some gaps in the available data. These data might therefore not be fully representative of the actual conditions of egg storage in all MSs. The information on storage time and temperature on the stages from the farm to transport to retail is displayed in Table  6. The information for the egg distribution chain for eggs used in catering can be found in Appendix B, Table  B1. For the retail stage, the temperature was modelled as a bimodal distribution to reflect the fact that, in some MSs, refrigeration is used in retail establishments, while in other MSs this is not the case.
ACKNOWLEDGEMENT OF OTHER DATA SOURCES The  Australian Egg Corporation Ltd  is acknowledged for granting permission for the model used in this assessment. Mark Williams  and colleagues from the  EUWEP  (the representative body in the EU for egg packers, egg traders and egg processors, and poultry and game) and the  European Egg Packers and Traders Association (EEPTA)  are acknowledged for kindly providing information on current egg storage practices along the egg distribution chain in the EU. David Cassin  is thanked for providing information on quality indicators in the manufacturing of egg products. In addition, the Panel would like to thank representatives from EU Member States that provided information on the rules affecting egg storage practices and  Klaus Kostenzer  of the  European Commission  for his assistance in collecting this information.
A quantitative analysis of high throughput sequencing datasets further shows that the underlying genetic properties of the germline DNA segments might act in concert with epigenetic signals to define germline specific sequences. Tetrahymena. As development proceeds, the number of these intensely labeled foci diminishes and the single remaining spot found in a DNA-poor region of the macronucleus eventually disappeared (Fig. 1B , Fig. S2-S3-S4 ).
DNA isolated from newly developed MACs at the same developmental stage from a cell culture grown without RNAi was also sequenced as a control (Table  S2 ). We compared the sequence complexity of different datasets by mapping the reads in each dataset to contigs previously assembled from new MACs after Pgm depletion  [2] , which is currently the best representation of the un-rearranged germline genome. As shown in Table  S3 , EZL1 reads have the same sequence complexity as the PGM reads, while the control dataset has about 13 Mb less sequence complexity. Of note, the total sequence complexity in the MIC is expected to be larger than the 89 Mb that we analyzed since our analysis only used PGM contigs larger than 1 kb. If we compare the complexity of regions not covered by the control sample, which correspond to the part of the MIC genome that is not collinear with MAC chromosomes, PGM and EZL1 datasets again show a similar complexity.
We also performed a qualitative evaluation of Sardine retention by mapping reads from each dataset to the known cloned copies of this transposable element  [2] (Fig. S9 ). Consistent with our Southern blot analysis (Fig. 5A ), we found that all characterized Sardine copies are retained after EZL1 silencing. This global analysis supports the conclusions made at the molecular level for two individual loci: EZL1, like PGM, is required for the imprecise elimination of germline-limited sequences.
Based on our PCR analyses, not all IESs are affected following EZL1 KD. To observe the effects of Ezl1p depletion genomewide, we used the EZL1 DNA-seq dataset. A retention score (RS) was calculated for each IES in the reference set  [2] : reads that map to IES ends were classified as IES-containing or as MAC junctioncontaining reads, representing retained and excised IESs respectively. The RS is the ratio of IES-containing to total classified reads, and RS values vary from 0 for no IES retention to 1 for complete IES retention. As expected (Fig. 6A ), the RS distribution of the control dataset is close to 0 (mean 0. 008), whereas a Gaussian distribution was observed for the PGM dataset  [2]  with a mean RS of 0. 77. Even if Pgm is responsible for complete excision of all IESs  [2, 3] , the mean RS never reaches 1 owing to the presence of rearranged DNA in the PGM sample coming from the fragments of the maternal MAC still present in the cytoplasm.
Histograms of IES retention scores, as defined in Materials and Methods, for control (grey), PGM (red), EZL1 (green) and DCL5 (blue) silencing and DCL2/3 co-silencing (yellow) datasets. B. EZL1 retention scores display a strong bias for IES size. IESs were grouped by size, each group corresponding to a peak in the genome-wide IES size distribution  [2]  Consistent with previous work  [2] , excision of all IESs appears to be affected in a similar manner following PGM KD. In the EZL1 dataset however, the mean RS is 0. 32 and the distribution is bimodal with 8,085 IESs that have an RS close to 0, the rest of the IESs displaying a wide distribution of retention scores (mean 0. 39) with a mode of 0. 5 (Fig. 6A ). We used a statistical test (see Materials and Methods) to compare the retention scores in the EZL1 or PGM datasets to the retention scores in the control dataset in order to identify significantly retained IESs.
In the PGM dataset, 44,028 IESs (97. 9%) are significantly retained compared to control and in the EZL1 dataset, 31,481 IESs (70. 1%) are significantly retained with a mean RS of 0. 42. A biological replicate from an independent EZL1 silencing experiment showed good correlation of retention scores (Spearman correlation coefficient: 0. 887, p, 2. 2 10 216 ). Based on these data, we can define two classes of IESs: those that are significantly retained after EZL1 KD and those that are not. Importantly, our PCR analyses are completely coherent with our genome-wide analysis (Table  S4 ). We then wondered what distinguishes the two classes of IESs. Our PCR analyses indicated that long IESs were retained in the new developing MAC following EZL1 KD (Fig. S10  and Table  S4 ). To confirm this observation genome-wide, IESs were grouped according to their size  [2]  and the distribution of retention scores for each group represented in a box plot (Fig.
9% are significantly retained after EZL1 KD, while only 40% of the IESs shorter than 52 bp in length are significantly retained. This robust correlation between IES size and retention score is not observed for the PGM dataset (Fig. S11 ), indicating that it is a property specific to Ezl1p depletion. We searched for features other than size that could be associated with EZL1 retained IESs. We compared IESs of the same size (26-32 bp) and did not find any meaningful correlation for a large number of criteria, including the consensus present at IES ends and the scnRNA density on IESs. We did observe that EZL1-retained IESs have: (i) a slightly higher GC content, (ii) a more frequent location within gene coding sequences (Fig. S12 ). It is intriguing that these two properties can also be important determinants in nucleosome positioning  [31] [32] [33].
The Dcl2 and Dcl3 proteins are required for the excision of a subset of IESs that are highly sensitive to Ezl1 depletion Since DCL2 and DCL3 genes, like EZL1, are required for establishing H3K27me3 and H3K9me3 in the developing MAC (Fig. 2  and 4 ), we hypothesized that depletion of Dcl2 and Dcl3 proteins would impair DNA elimination in a similar manner to that of Ezl1 depletion. To address this question, we sequenced DNA isolated from newly developed MACs following DCL2/3 cosilencing. When compared to the PGM and EZL1 datasets, the total sequence complexity was similar in the DCL2/3 dataset (Table  S3 ) and analysis of Sardine retention showed that all characterized Sardine copies are retained following DCL2/3 cosilencing (Fig. S9 ). This global analysis confirmed that the Dcl2 and Dcl3 proteins are required for the imprecise elimination of germline-limited sequences  [5].
Analysis of the effects of DCL2/3 KD on IES excision led to a surprising finding. Compared to PGM or EZL1 silencing, most IESs are weakly or not at all retained after DCL2/3 co-silencing (Fig. 6A ). Only 3,272 IESs (7. 3%) are significantly retained in the DCL2/3 dataset with a mean RS of 0. 24. The small number of significantly retained IESs and their low RS might be explained in part by incomplete silencing. Yet, the possibility that there are still low amounts of Dcl2 and Dcl3 proteins that would provide sufficient scnRNAs for IES excision is unlikely because very little if any scnRNAs can be detected in typical DCL2/3 KDs  [5, 6]. Moreover, we found 3,160 IESs significantly retained for a biological replicate  [6]  and a good correlation of RS was observed for the two biological replicates (Spearman correlation coefficient 0.
616, p, 2. 2 10 216 ) despite use of different silencing constructs. Furthermore, the RS measured for the DCL2/3 dataset are in agreement with our PCR analyses (Fig. S10  and Table  S4 ). Based on our PCR analyses, we noticed that all mcIESs are significantly retained in the DCL2/3 dataset and that all IESs retained after DCL2/3 KD are retained in the EZL1 dataset. The latter was confirmed genome-wide: almost all significantly retained IESs in the DCL2/3 dataset are significantly retained in the EZL1 dataset (3,269/3,272) (Fig. 6C ). Furthermore, IESs retained upon DCL2/3 KD are among the most retained IESs in the EZL1 dataset (Fig. S13 ). Only the largest IESs are retained in the DCL2/3 dataset; 50% of the IESs larger than 1 kb are significantly retained (Fig. S11 ). Among those, 19/28 Anchois IESs are significantly retained after DCL2/ 3 KD (Table  S5 ).
Altogether our data indicate that IESs retained upon DCL2/3 KD correspond to a small subset of EZL1 retained IESs (Fig. 6C ). The Dcl5 protein does not play a major role in the imprecise deletion of MIC-specific sequences and affects the excision of only a subset of IESs that are sensitive to Ezl1p depletion The Dicer-like protein Dcl5 was reported to be required for efficient excision of at least a fraction of IESs  [6]. We therefore compared the effects of Dcl5 depletion on DNA elimination, using the previously published DCL5 dataset  [6]  (Table  S2 ), to those observed after Ezl1 depletion. Compared to the PGM and EZL1 datasets, the total sequence complexity was much lower in the DCL5 dataset (Table  S3 ) and analysis of Sardine transposon retention showed that none of the characterized Sardine copies are retained following DCL5 silencing (Fig.
S9 ). This global analysis indicates that, in contrast to Pgm, Ezl1 or Dcl2/3 proteins, the Dcl5 protein is unlikely to play a major role in the imprecise elimination of germline-limited sequences. We then measured the retention score for each IES using our criteria for statistical significance (see Materials and Methods) and, consistent with previous work  [6] , most IESs are weakly or not at all retained after DCL5 silencing (Fig. 6A ). Only 3,024 IESs (6. 7%) are significantly retained in the DCL5 dataset with a mean RS of 0. 21. Almost all significantly retained IESs in the DCL5 dataset are strongly retained in the EZL1 dataset (Fig. 6C ). IESs retained upon DCL5 KD correspond to a small subset of EZL1 retained IESs, which is furthermore different than the subset of IESs retained upon DCL2/3 KD.
Consistent with the idea that the Ezl1 protein acts downstream of scnRNAs, analysis of small RNA sequencing datasets showed that scnRNA biogenesis is not affected upon Ezl1 depletion as compared to control RNAi or wild type (A. de Vanssay and O. Arnaiz, personal communication). Deposition of H3K27me3 and H3K9me3 would allow the recruitment, or activation of the excision machinery, followed by elimination of marked DNA segments (Fig. 7A ), consistent with our observations that the Ezl1 protein acts upstream of the Pgm endonuclease. Our study provides evidence that RNAi-mediated heterochromatin formation is necessary for elimination of germline DNA in Paramecium, as is the case in Tetrahymena  [1]. Ciliates use a similar, sRNA-dependent mechanisms for heterochromatin formation as other eukaryotes  [20, 21] , except that it goes a step further with the physical elimination of the targeted sequences during development of the somatic nucleus.
Lethality of post-autogamous cells after double silencing of DCL2 and DCL3 or silencing of PGM was 90-100% (30-60 cells were checked in each silencing experiment). As expected, Pgm depletion led to retention of all tested germline-limited elements in the developing MAC genome, while Dcl2/3 depletion led to retention of well-characterized IESs (Fig. S10 ) and Dcl5 depletion led to partial impairment of excision for IESs retained in the DCL5 dataset.
Images were acquired using a Zeiss LSM 710 laser-scanning confocal microscope and a Plan-Apochromat 63x/1. 40 oil DIC M27 objective. Z-series were performed with Z-steps of 0. 5 mm. To quantify the H3K27me3 and H3K9me3 signals, the Imaris 3D visualization software (Bitplane) was used. For each time point, the fluorescence intensities of H3K27me3/H3K9me3 in the developing MACs (signal) and in the corresponding volume of the cytoplasm (noise) were measured. The mean value and standard deviation of the signal to noise ratios were calculated using ten individual cells at each time point.
Reference genomes The following reference genomes  [2]  were used in the IES analyses and for read mapping. MAC reference (strain 51): http://paramecium. cgm. cnrs-gif. fr/download/fasta/ptetraurelia_ mac_51. fa MAC+IES reference (strain 51): http://paramecium. cgm. cnrs-gif. fr/download/fasta/ptetraurelia_ mac_51_with_ies. fa PGM contigs: http://paramecium. cgm. cnrs-gif. fr/download/fasta/assemblies/ ptetraurelia_PGM_k51_ctg. fa Macronuclear DNA reads for PiggyMac  [2]  and DCL5 depleted cells and for a biological replicate of the DCL2/3 cosilencing experiment  [6]  were obtained from the European Nucleotide Archive (Accession number ERA137420) (PGM) and the GenBank Sequence Read Archive (Accession numbers: SRX387766 (DCL2/3); SRX387766 (DCL5)).
The retention score (RS) of an IES is then given by the following equation: RS = (IES + ) / (IES + + IES 2 ) Since RS are based on read counts, appropriate statistical tests allowed us to discriminate IES retention as a result of gene silencing from IES retention as a result of biases in Illumina sequencing or errors in the IES identification pipeline (estimated false positive rate # 4%,  [2] ). First, we calculated the confidence interval (alpha = 0. 95) of the control retention score value, using the Pearson-Klopper exact method as implemented by the R binom package version 1. 0-5  [53]. Then we tested for higher retention in the experiment, thanks to a frequency comparison test (based on a binomial law of probability) between the experimental retention score and the upper bound of the confidence interval in the control.
Data accessibility The EZL1 KD, DCL2/3 KD and control DNA-seq datasets have been deposited in the European Nucleotide Archive (Accession number ERA309409). All IES retention scores may be obtained via ParameciumDB (http://paramecium. cgm. cnrsgif. fr/). trifallax. An unrooted Maximum-likelihood (ML) tree is shown. This tree has been constructed using the SET domains encoded by the genome of a large number of species. The full list of used sequences and studied species can be found in Table  S1  and Text S1. We identified 13 monophyletic groups that include sequences from several different species. We named most of these groups by using the name(s) of the Human and/or Drosophila proteins that are included in the group. We tried to use as much as possible the nomenclatures used in previous phylogenetic analyses of SET domain proteins  [58, 59].
This latter possibility is supported by the fact that the two groups are associated to the ASH/SET2/NSD group in the phylogenetic analyses made on the ciliates + Human + Drosophila + yeasts dataset. The inclusion of T. thermophila and O. trifallax proteins in the SMYD and SETD7 groups, as well as the belonging of a large number of ciliate proteins to the SETD6 group, has to be taken with caution, given the poor support of these groups, and may correspond to the artefactual grouping of highly divergent sequences. (EPS) Figure  S6  Alignment of SET domains from EZH-EZL proteins from P. tetraurelia, T. thermophila, O. trifallax and other organisms. Sequences were aligned using the Muscle v3. 8 software. The white text on a black background denotes invariant residues; white text on a gray background indicates conserved residues.
Highly conserved residues are highlighted with different colors according to  [60, 61] : catalytic site (red), adenosylmethionine (AdoMet) binding pocket (green), lysine substrate binding pocket (blue). EZL3a and EZL3b are gene duplicates from the last whole genome duplication  [25]. Note that Ptet_EZL3a, Pte-t_EZL3b and Ptet_EZL4 do not show all conserved residues. Accession numbers are given in Table  S1  and Text   S6 ) located on either side of the IES in mass autogamies after RNAi-mediated silencing of the indicated genes. Total DNA samples were prepared from starved post-autogamous cells at approximately 72 hrs. Because the maternal MAC is still present at this stage, the excised version is amplified in all cases; the IES-retaining fragment can be detected only if it accumulates in the zygotic developing MACs.
Supporting Information Figure  S11  IES retention score and size in control, EZL1, DCL2/3 or PGM datasets. IESs were grouped by size (cf. legend of Figure  6B ), and boxplots were determined to show the distribution of A) PGM dataset retention scores, B) control (KLEB) dataset retention scores, C) DCL2/3 dataset retention scores and D) EZL1 silencing sample retention scores (reproduced from Figure  6B  to facilitate comparison). E) The proportion of significantly retained IESs for PGM, DCL2/3 and EZL1 datasets are plotted as a function of IES size, using the same size groups as for parts A-D, corresponding to the peaks in the IES size distribution. This representation shows, for example, that 34% of the IESs in the smallest peak are significantly retained after EZL1 silencing. In the PGM dataset, essentially all IESs are significantly retained except in the last few groups of largest size, and that is because of the small number of IESs in those groups, introducing a lot of noise in the curve.
In the EZL1 dataset, the increase in significantly retained IESs is dramatic over the first 3 groups in the size distribution and then flattens out. The variation for the largest size groups is very similar to the variation found for the PGM dataset, in support of the hypothesis that this variation is noise that arises from the small number of IESs in those groups. For the DCL2/3 dataset, few IESs are significantly retained in any of the groups. However, there does appear to be an increase in significantly retained IESs for the largest IES sizes. As already noted, the largest groups include very few IESs introducing a lot of noise, however for the DCL2/3 dataset, the variations are different than for the other 2 samples, in support of a real increase in significant retention of IESs larger than , 500 bp.
S3  Sequence complexity of control, PGM, EZL1, DCL2/ 3 and DCL5 datasets. The previously published contigs assembled from a PGM dataset  [2]  were used as reference, representing the currently best available germline DNA assembly. However, only contigs larger than 1 kb were considered, representing 91 Mb of sequence complexity, of which 89 Mb are covered by read mapping above our cutoff (i. e. 2 reads per kb of contig per million mapped reads in the library). Reads from each sample were mapped to the PGM contigs using BWA with default parameters, to determine the complexity of the contigs covered by at least 2 reads per kilobase of contig per million reads in the library (RPKM), giving the first row of the table (''PGM'' Reference). In addition, a set of PGM contigs were selected that had control (KLEB) coverage below the cutoff of 2 RPKM (''PGM not KLEB'' Reference), representing pure germline DNA not collinear with MAC chromosomes.
Star(s) following a retention score indicate that the IES is significantly retained (cf. Materials and Methods and the legend to Figure  6B ). NA: not analyzed. No retention score can be calculated for (i) the mtA IES since it is retained in the MAC reference genome  [13]  and for (ii) IES51A1835, IES51A4404, IES51A2591 and IES51A4578 because the control strain carries a maternally inherited MAC deletion of the A gene. 1 : S. Duharcourt and E. Meyer, personal communication (DOCX) Table  S5  Anchois retention score. The 28 IESs that were used to identify the Anchois Tc1/mariner transposon  [2]  are provided with their ParameciumDB Accession Numbers, size and retention scores in the different RNAi datasets under consideration. Retention scores followed by a star are statistically significant.