dataesr/scientific-paragraphs-categorization huggingface dataset:
Extracting the parameters from the data We first fit the first and second wave (if reached) by use of independent solutions to the eRG framework. This exercise will allow us to compare the two waves, in particular the infection rates γ eRG , which are independent on the normalisation of the cumulative number of infected. We use open-source data from the online repository Ourworldindata. org. We first identify the first wave, within the dates indicated in Table  2 , and fit the data by use of a simple logistic function: I(t) = Ae γ eRG t b + e γ eRG t. (11) We then fit the data after the end date of the first wave (having subtracted the final number of cases) with a second independent logistic function plus a linearly growing term, which characterises the strolling period. If the second wave is absent, we simply fit the linear strolling.
We also noted that the value of the uniformity indicator reaches local minima at the peak of each wave, thus the values reported for starting waves are larger than the final one. Table  2. Parameters for the CeRG forecast for the third waves. To compute the values, we only used open-source data available on various online repositories. For Japan, we obtained the local data for the 46 prefectures from Toyokeizai. net. In the analysis we omitted Okinawa because of its distance from the mainland. For Germany (16 Landen), Italy (20 regions), Spain (17 regions) and England (9 regions), we obtained data collected in periods of about 4 weeks from Citypopulation. de. For France, as the local data on the new number of infected is not available before May 13, 2020, we used information for the number of hospitalisations in the 94 continental departments from Data.
gouv. fr. Finally, the data for each state of the US is obtained from Ourworldindata. org. For Japan and the US, the result for the third wave overestimates the one at the peak, which is not reached yet. The prediction corresponds to S t = 0. 01 for Canada, while the strolling parameter is fitted to the data for Bolivia, South Korea and Australia, and is compared to the data (adjourned to November 23) and the eRG fit from Table  1  (dashed).
Using a large-scale automated dataset, a multigene ochrophyte reference tree, and mathematical reconciliation of gene trees, we note a probable elevation of bacterial HGTs at foundational points in diatom evolution, following their divergence from other ochrophytes. Finally, we demonstrate that throughout ochrophyte evolutionary history, bacterial HGTs have been enriched in genes encoding secreted proteins. Our study provides insights into the sources and frequency of HGTs, and functional contributions that HGT has made to algal evolution. RNAseq | MMETSP | ornithine-urea cycle | phylogenomics | stramenopile S ince their origin, the eukaryotes have split into a multitude of different lineages  (1, 2). These comprise several "crown supergroups," some of which (e. g. , opisthokonts, including animals and fungi) are exclusively nonphotosynthetic, while others (e.
In the last decade, alongside improved genomic sampling  (17) , over 150 different transcriptome libraries have been sequenced from ochrophytes  (22, 23) , dramatically expanding our understanding of the functional biology of this lineage. Herein we harness a densely sampled, transcriptome-enriched reference sequence dataset, manual and automated phylogenetic annotations, and experimental characterization to assess the extent, timing, and functions of HGT across the ochrophytes. We manually assess all prokaryotic and eukaryotic HGTs during ochrophyte evolution that are detectable in the genome of P. tricornutum, and uncover a continuous flux of genes from bacteria as the predominant contributor of recent HGTs in diatom evolution. Through a larger-scale automated analysis of all genes likely to be derived from HGTs from bacteria across the ochrophytes, we identify large numbers of bacterial HGTs underpinning the evolution of diatoms, following their divergence from other ochrophytes.
Results Phylogenomic Profiling Reveals the Composite Eukaryotic and Bacterial History of the P. tricornutum Genome. We first wished to determine the most frequent evolutionary identities of the organisms that have donated genes into ochrophytes-and have received genes from ochrophytes-via HGT. To do this, we developed a custom pipeline to generate a global estimate of all HGTs associated with the genome of the model ochrophyte P. tricornutum, based on the manual inspection of single-gene trees with a densely sampled dataset of prokaryotic and eukaryotic genomes and transcriptomes (5, 24) (Dataset S1). We divided this dataset into 12 different lineages comprising 151 different taxonomic subcategories (shown in Dataset S1) based on phylogenetic affinity, and previously estimated contributions of different taxa to ochrophyte genome evolution  (5, 14).
This pipeline was used to trace all genes in the version 3 annotation (17) of the P. tricornutum genome that have undergone horizontal transfer since the ochrophyte common ancestor. Our dataset improves on previous analyses by considering HGTs between ochrophytes and other algae with chloroplasts of secondary origin (e. g. , haptophytes and dinoflagellates)  (5, 6) , and by considering the direction of transfer events, to explore the possibility that ochrophytes are donors as well as recipients of HGTs into other branches of the tree of life  (17, 21). We identified 1,979 genes (16. 3% of the total P. tricornutum genome) (Dataset S1) with potential histories of horizontal transfer during ochrophyte evolution. These included 1,347 genes (11. 0% total genome content) where the single gene tree implicated an HGT into ochrophytes at some point in their evolutionary history, and 1,771 HGTs, partitioned over 1,184 genes (9.
7% total genome content) from ochrophytes into another branch of the tree of life (Fig. 1A  and Dataset S1). Eighteen exemplar trees are provided in SI Appendix, Fig. S1. Reflecting the complex patterns of HGT likely to occur in ochrophytes, 547 (4. 4% total genome content) gene trees revealed an HGT into the ochrophytes, followed by one or more HGTs out from the ochrophytes into other lineages, while 397 (3. 3% total genome content) revealed transfers from ochrophytes into at least two different groups across the tree of life (Dataset S1). In 76 cases, the sister-group to the ochrophytes contained multiple nonstramenopile lineages, consistent with an HGT origin, but with no clear ancestral identity. Smaller numbers of HGTs were supported by >50% (727 HGTs in; 798 HGTs out), and >80% bootstrap support (415 HGTs in; 464 HGTs out), and phylogeneties with concordant sets of nonochrophyte BLAST top-hits (5, 17) (152 HGTs in; 240 HGTs out).
Broadly, these preserved the general dynamics and features discussed below (SI Appendix, Fig. S2  and Dataset S1). Complex Patterns of Horizontal Transfer between P. tricornutum and other Eukaryotic Algae. The majority of genes detectable in the P. tricornutum genome that could be inferred to be transferred into the ochrophytes (1,007 of 1,347 gene transfers in, 75%) are derived from eukaryotic algae with both primary and secondary chloroplasts (cryptomonads, haptophytes, dinoflagellates, red or green algae), with similar numbers of genes attributed to each (Fig. 1A  and Dataset S1). Transfers from eukaryotic algae comprised the majority of HGTs recovered with >50% (569 of 727 HGTs in, 78%) and >80% bootstrap support (326 of 415 HGTs in, 79%), and a plurality of HGTs into ochrophytes recovered by both phylogenetic and BLAST analysis (72 of 152 HGTs in, 47%) (SI Appendix, Fig.
S2 ). Exemplar trees for genes transferred from eukaryotic algae into ochrophytes are provided in SI Appendix, Fig. S1 A-H. The majority of transfers out from the ochrophytes likewise involved eukaryotic algae with secondary chloroplasts (1,747 of 1,771 total HGTs out, 99%), with the greatest number identified in haptophytes (817 of 1,771 inferred transfers out, 46%) (Fig. 1A  and Dataset S1). HGTs into haptophytes were recovered as the single largest category in trees filtered on 50% (448 of 898 HGTs out, 50%) and 80% bootstrap support (252 of 464 HGTs out, 54%), and in transfers recovered concordantly by phylogenetic and BLAST top-hit analysis (138 of 240 HGTs out, 58%) (SI Appendix, Fig. S2 ). Exemplar tree topologies for genes transferred from ochrophytes into other eukaryotic algae are provided in SI Appendix, Fig.
S1 A-K. The greatest number of transfers from ochrophytes into haptophytes (383 of 817 HGTs into haptophytes, 47%) were assigned to a common ancestor of Khakista (diatoms, bolidophytes) and Hypogyristea (pelagophytes and dictyochophytes) (Fig. 1B  and Dataset S1). This result was likewise recovered in trees filtered on 50% (249 of 448 HGTs into haptophytes, 56%) and 80% bootstrap support (145 of 252 HGTs into haptophytes, 58%); and in transfers recovered concordantly by phylogenetic and BLAST top-hit analysis (82 of 138 HGTs into haptophytes, 59%) (SI Appendix, Fig. S2 ). Analysis of the composition of the clades involved in each transfer (SI Appendix, Fig. S3 A, i ) furthermore showed a specific enrichment in pelagophytes and dictyochophytes in the ochrophyte sister-group to the haptophyte clade (making up >40% weighted sister-group presence).
Sequences from pelagophytes and dictyochophytes typically reciprocally retrieved haptophyte sequences in internal BLAST top-hit searches of each alignment (χ 2 enrichment P < 1E-05) (SI Appendix, Figs. S4 and S5 and Dataset S2). In contrast, this signal was evenly distributed across all haptophyte groups, including the early-diverging pavlovophytes (SI Appendix, Figs. S3 A , ii, S4, and S5 and Dataset S2). This association is specifically concordant with large amounts of HGT from a pelagophyte/dictyochophyte common ancestor into a haptophyte common ancestor, as has been previously proposed (e. g. , via an ancient chloroplast endosymbiosis)  (5, 21). Consideration of both clade compositions (SI Appendix, Fig. S3B ) and internal BLAST searches of each alignments (SI Appendix, Figs. S4  and S5 ) also revealed an association between pelagophytes and dictyochophytes with all dinoflagellates sampled, which may suggest a direct or indirect (e.
1B ). This result was also recovered when considering only HGTs with >50% bootstrap support (77 of 569 eukaryotic algal HGTs in, 14%; 69 of 896 eukaryotic algal HGTs out, 7%); >80% bootstrap support (51 of 326 eukaryotic algal HGTs in, 16%; 28 of 462 eukaryotic algal HGTs out, 6%); and transfers supported by BLAST top-hit analysis (11 of 72 eukaryotic algal HGTs in, 15%; 31 of 238 eukaryotic algal HGTs out, 13%) (SI Appendix, Fig. S2 ). Continuous Bacterial HGT Dominates Recent Arrivals in the P. tricornutum Genome. We identified a substantial number of genes (285, 2. 3% total genome content) that have been transferred into the P. tricornutum genome, since the ochrophyte common ancestor, from bacterial partners (Fig. 1A  and Dataset S1). The transfer events from bacteria are largely asymmetric, with only 18 plausible cases of genes across the P.
tricornutum genome (0. 1% total genome content) transferred into bacterial groups from ochrophyte donors (Fig. 1A  and Dataset S1). Smaller numbers of bacterial HGTs into ochrophytes could be detected with 50% bootstrap support (146 HGTs in), 80% bootstrap support (81 HGTs in), and concordant BLAST top-hit and phylogenetic annotations (76 HGTs in); effectively no HGTs out from ochrophytes to bacteria received more than minimal bootstrap support (SI Appendix, Fig. S2 ). The gene transfers inferred from bacteria into ochrophytes were attributed nearly equally to having occurred within diatoms (132 HGTs in) and earlier time points (153 HGTs) (Fig. 1  and Dataset S1). Exemplar trees showing HGTs from bacteria into early ancestors of the diatom lineage are provided in SI Appendix, Fig. S1 M-O , while trees documenting recent bacterial HGTs in the evolutionary history of P.
tricornutum are shown in SI Appendix, Fig. S1 P-R. Bacteria were responsible for nearly half of the gene transfers within diatoms detectable in P. tricornutum (49%, from 267 HGTs into diatoms) (Fig. 1A  and Dataset S1), and in trees with >50% bootstrap support (74 of 152 HGTs into diatoms, 48%); >80% bootstrap support (38 of 90 HGTs into diatoms, 42%), and a majority of transfers with concordant BLAST top-hit and phylogenetic annotations (59 of 71 HGTs into diatoms, 83%) (SI Appendix, Fig. S2 ). The bacterial HGTs were inferred to be derived from a wide range of taxa, considering BLAST top-hit assignation (Dataset S1). Notably, Phatr3_Jdraft542. p1 shows highest BLAST similarity with sequences from the nitrogen-fixing diatom endobiont Richelia intracellularis  (27) ; and Phatr3_J31257. p1 shows greatest similarity to the dinoflagellate epibiont Labrenzia aggregata (28) (Dataset S1), suggesting possible origins from bacterial symbionts.
Thousands of Bacterial Sequences Detectable in Ochrophyte Genomes and Transcriptomes. Given the overwhelmingly bacterial signature of HGTs in diatoms that can be detected in the P. tricornutum genome, we wished to quantify how prevalent bacterial HGT was EVOLUTION elsewhere in the ochrophyte tree. We identified genes that had phylogenetic histories compatible with prokaryotic HGTs based on 162 ochrophyte genomes and transcriptomes, including 109 diatom sequence libraries, of which 7 transcriptomes were generated for this study (Dataset S1), and a custom BLAST and phylogenetic pipeline (Materials and Methods and SI Appendix, Fig. S6 ). A total of 41,620 (1. 6%) ochrophyte sequences yielded exclusively noneukaryotic BLAST matches (outside of other ochrophytes), hence were considered prokaryote-derived sequences de facto, and a further 46,444 (1.
S9 ). To verify whether single-species HGT events in our dataset might be influenced by contamination, we compared GC content, as well as the distribution of unique 5mer patterns in bacterial sequences uniquely found in ochrophyte species, to species-specific models of nucleotide composition generated from a training dataset of 902,839 "vertically inherited" genes inferred from this library (SI Appendix, Fig. S10 ). The bacterial sequences identified in only one ochrophyte library frequently had different normalized GC contents and 5mer composition distributions than vertically inherited genes (SI Appendix, Fig. S7 ). In contrast, bacterial sequences found in more than one ochrophyte library had normalized GC contents and 5mer compositions that overlapped with those of vertically inherited genes (SI Appendix, Fig.
S10 ), suggesting that they correspond to bacterial HGTs that have drifted toward the sequence composition of their recipient ochrophyte genome. To test the effectiveness of the automated tree assignations, we compared the set of P. tricornutum genes inferred to be compatible with bacterial HGT through automated analysis with those detected in the previous manual assignation of P. tricornutum HGTs (SI Appendix, Fig. S11  and Dataset S3). A total of 37 genes identified in the automated analysis were independently confirmed manually to have undergone bacterial HGT; only 2 of the genes in the automated analysis were found to have vertical origins in manual assignations, and 5 were inferred to have originated through horizontal transfers from nonbacterial sources (Dataset S3). We identified concordant topologies for genes that either retrieved and for genes that did not retrieve eukaryotic homologs in the automatically reconciled gene tree, and for gene trees that were reconciled with >70% and <70% SH-aLRT branch support (SI Appendix, Fig.
S11 ). We note, moreover, that the number of HGTs per node predicted with low SH-aLRT branch supports (i. e. , <70%) is strongly correlated (R = 97. 6) with the number of HGTs predicted with higher branch supports (i. e. , >70%), demonstrating that the two HGT categories contained the same signal (SI Appendix, Fig. S12 ). We chose accordingly to work with the bacterial HGTs found in more than one ochrophyte library for downstream analysis, regardless of branch support or presence of eukaryotic homologs. As an explicit detection of genuine bacterial HGTs, we used a previously defined BLAST methodology  (32)  to search for genes that contain composite bacterial and ochrophyte domains, which arise through the recombination of bacterial and host sequences (SI Appendix, Fig. S13  and Dataset S5).
Bacterial HGTs Occur at Greater Frequency in Diatoms than Other Ochrophytes. Considering the large contribution of bacteria for HGTs into diatoms (Fig. 1B ), we wished to determine whether diatoms have undergone greater numbers of bacterial HGTs than other ochrophytes. We mapped the distribution of 2,796 sequence clusters compatible with HGTs from bacteria into ochrophytes and shared across at least 2 ochrophyte sequences to a 63-gene tree covering 213 species, including all 161 ochrophyte libraries referenced in this study (Fig. 2  and Dataset S4). This topology confirms phylogenetic relationships proposed by previously published phylogenies: placing Attheya as the sistergroup to all pennate diatoms and Striatella as the earliestdiverging pennate diatom genus  (33, 34) , and identifying two distinct early-branching ochrophyte clades, the first consisting of pinguiophytes, synchromophytes, and chrysophytes, and the second consisting of eustigmatophytes, phaeophytes, xanthophytes, and raphidophytes (35) (Fig.
2 ). Similar results were detected when only considering HGTs reconciled with >70% bootstrap support (Fig. 2 , SI Appendix, Fig. S18 , and Dataset S3). We then wished to determine whether HGTs were truly more frequent in diatoms than in other ochrophytes. We noted limited differences in the missing fraction of BUSCO libraries (36) across ochrophytes, with most libraries presenting >60% completeness (SI Appendix, Fig. S19A ), suggesting that library completeness does not account for the enrichment of HGTs detected in diatoms. Next, we used amalgamated likelihood estimation (ALE)  (37, 38) , a probabilistic gene reconciliation approach that can be used to infer HGT origins, to select, among the 675 HGT proteins present in at least 10 ochrophyte species, those that were inferred to be predominantly vertically inherited (and are therefore not contaminations or multiple independent acquisitions) (Fig.
3A ). This ALE-verified dataset contained 435 HGT protein clusters that originated up to 10 times more frequently within diatoms compared to other ochrophyte lineages (t test, t df = 327 = 3. 4, P = 0. 0008) (Fig. 3B , SI Appendix, Fig. S19B , and Dataset S4). We confirmed using randomizations that this diatom enrichment in bacterial HGTs was not due to random chance (Fig. 3C ). We also found that many of the bacterial HGT proteins have been subsequently lost in diatoms (SI Appendix, Fig. S19C ). Finally, we applied subsampling controls in which we compared the number of ALE-verified HGTs attributable to diatominclusive groups or nondiatom ochrophytes when randomly sampling 10 selected species, over 100 replicates. We noted elevated frequencies in diatom versus nondiatom groups, considering total HGTs identified (SI Appendix, Fig.
S20 ) and total HGTs assigned to the common ancestor of each group (SI Appendix, Fig. S21 ). Thus, even when sampling of diatoms and other groups are similar, our data indicate elevated frequencies of bacterial HGT into diatoms compared to other ochrophytes. Functional Insights into the Roles of Bacterial HGTs in Ochrophytes. Next, we considered what functional annotations might be associated with bacterial HGTs into ochrophytes. Using the P. tricornutum genome as a well-annotated model, we profiled biological functions, structural homology  (17) , and predicted localizations (39-42) of all genes of predicted bacterial origin extending to the ochrophyte ancestor (Dataset S6), considering genes identified in manual annotations of P. tricornutum trees (Dataset S1) and P. tricornutum genes identified in automated HGT analyses of all ochrophyte genomes and transcriptomes (Dataset S3).
The bacterial HGTs identified in P. tricornutum perform diverse functions. These included three vacuolar iron transport proteins (Phatr3_J37632. p1, Phatr3_J43313. p1, and Phatr3_J43314. p1)  (43) , most likely transferred into the diatom common ancestor from an actinobacterial donor (SI Appendix, Fig. S1M ). The inclusion of these proteins reflects the likely bacterial origin of iron-scavenging pathways unique to diatoms  (21). Our dataset also included cytoplasmic enzymes involved in putative siderophore (Phatr3_J46626. p1, isochorismatase), and menaquinone (Phatr3_J47199. p1/Phatr3_J48624. p1, demethylmenaquinone methyltransferase, Phatr3_J44670. p1, 1 4-dihydroxy-2naphthoate polyprenyltransferase) biosynthesis, reflecting the probable role of HGT for diversifying eukaryotic secondary metabolism  (44, 45).
Other pathways previously annotated as being bacterially derived in P. tricornutum were sparsely recovered in our dataset. For example, in the case of the diatom ornithine-urea cycle, which was originally proposed to contain multiple genes derived from bacterial HGT  (20, 46) , comparative analysis of our data (Dataset S6) and other published analyses  (17, 19, 47)  reveals a mosaic origin. These include enzymes likely to have arisen from bacterial HGT (Phatr3_J35643. p1, mitochondrial ornithine cyclodeaminase; Phatr3_J24238. p1, mitochondrial carbamate kinase; and Phatr3_J3969. p1, chloroplast acetylglutamate kinase), alongside others derived from within-eukaryotic HGT (e. g. , Phatr3_J29702. p1, mitochondrial urease, acquired from dinoflagellates; and Phatr3_ J50577. p1/ J54222. p1, chloroplast acetylornithine transaminase, acquired from haptophytes or green algae; SI Appendix, Fig.
Bacterial HGTs Frequently Encode Proteins with Secretory Localizations. We considered what localization patterns may be associated with ochrophyte proteins of bacterial HGT origin. Across our entire bacterial HGT dataset, we observed a strong enrichment in proteins with signal peptides, but nonchloroplastic localizations [assessed using signalP/ASAFind  (41, 49)  and HECTAR  (40) ], and secretory consensus predictions (either extracellular or plasma membrane) with WolfPSort  (42). We identified these enrichments among all genes inferred to originate from bacterial HGTs throughout ochrophyte evolution (Fig. 4A  and Dataset S3) and among bacterial HGTs detectable in manual annotations of the P. tricornutum genome (SI Appendix, Fig. S22 ). We tested the localization of proteins encoded by 10 genes of inferred bacterial origin detected in the P.
tricornutum genome, using full-length GFP C-terminal overexpression constructs (Dataset S6). Four of the proteins studied had clear secretory localizations. Phatr3_J33371. p1, a sialate O-acetylesterase manually annotated to have been acquired by a pennate diatom ancestor from bacteria; and Phatr3_J42871. p1, a protein of unknown function conserved across pennate and polar centric diatoms, as well as radial centric diatoms within the coscinodiscophytes, showed clear localization around the endoplasmic reticulum, verified using ER-Tracker staining (Fig. 4B  and SI Appendix, Fig. S22 ). Furthermore, Phatr3_J50959. p1, a homolog of the bacterial CoA-binding protein YccU conserved across all ochrophytes (SI Appendix, Fig. S7C ), as well as Phatr3_J8596. p1, a protein of unknown function shared across all ochrophytes except for chrysophytes, synurophytes, and pinguiophytes localized to the plasma membrane (Fig.