dataesr/scientific-paragraphs-categorization huggingface dataset:
2 ), in support of the placement of the Yan-like clade near the base of Alsuviricetes (Fig. 3 ). The profileprofile comparisons also showed that the SJR-CP protein of Yan-like viruses has a two-domain organization, including the shell and projection domains, similar to the capsid proteins of certain nodaviruses and tombusviruses (Extended Data Fig. 3 ), solidifying the position of the Yan-like clade in the tree. Another major clade within the Yangshan assemblage (OV. 8, hereafter the Zhao-like clade) consists of 113 members (Fig. 3 ; Supplementary Datasets 1 and 2) and includes a previously orphan cluster of 9 Zhaoviruses identified in marine invertebrates  30  along with 'ciliovirus' and 'brinovirus' from a San Francisco wastewater virome  64. The Zhaoviruses, 'ciliovirus' and 'brinovirus' , together with 36 Yangshan virome viruses, form a separate group within the Zhao-like clade.
This group is distinguished by using ciliate and other protist genetic codes (see below) and by encoding a capping enzyme similar to the distinct capping enzyme of nodaviruses (Fig. 4  and Supplementary Dataset 2). The third major clade in the Yangshan assemblage, denoted 'Shanghai' , harbours 74 Yangshan RdRPs and the unclassified 'eunivirus' (KF412900), which was identified in a wastewater virome (Fig. 3 ; OV. 15). The signature of this clade is the domain permutation of the RdRP that apparently occurred at the base of this clade. Finally, the Wei-like clade with 57 Yangshan RdRPs (clusters OV. 46, OV. 49, OV. 53, OV. 58, OV. 192, OV. 233, OV. 250 and OV. 262) also includes 15 Weiviruses 30. The phylogenomic diversity within the Yangshan assemblage seems to justify the establishment of a virus class, subdivided into multiple orders and families.
The last large clade within Kitrinoviricota ('Brandma-like' viruses) combines 282 RdRPs (cluster OV. 4; Supplementary Datasets 1 and 2) with several previously reported orphan viruses from diverse sources (Fig. 2  and Supplementary Dataset 2). Most Brandma-like viruses have small, 4-5-kb genomes that encode only two recognizable domains, RdRp and SJR-CP (Supplementary Dataset 2). The Brandma-like viruses form a sister group to the Noda-like viruses (Fig. 2 ). Finally, two large clusters of the Yangshan RdRP belong to Lenarviricota, grouping with the +RNA bacteriophages of the Leviviridae and levi-like viruses (340 members), or with ourmia-like viruses (382 members), the eukaryote-infecting descendants of +RNA bacteriophages 2,30,37 (Fig. 2  and Supplementary Datasets 1 and 2). Such strong representation of the levi-like phages and ourmia-like viruses in an aquatic RNA virome is expected, and so is the absence of the other clades of Lenarviricota, namely, mito-and narnaviruses, common capsid-less +RNA agents of fungi  65.
Distinct domain architectures of virus proteins in the Yangshan virome. Analysis of the domain content of the longer Yangshan contigs indicates that the genome organizations are typically similar within clusters enriched in Yangshan viruses and closely resemble the genome organizations of the previously known viruses from the same clades. Nevertheless, we identified several domains that have not been previously observed in any RNA viruses (Fig. 4  and Supplementary Dataset 2), including small ubiquitin-like modifier (SUMO), PrsW-like protease and phospholipase A2 (Extended Data Fig. 5 ). In addition, many Yangshan virome clusters included viruses that appear to have relatively recently acquired other domains, in particular, Zn 2+ -binding and methyltransferase domains, as well as conserved domains of unknown function.
Collectively, these observations reveal dynamic acquisition of multiple functional domains that might be involved in distinct virushost interactions. Alternative genetic codes in RNA viruses. The RdRPs in the Yangshan virome were identified in end-to-end six-frame translations of the contigs. Mapping the RdRP core domain profile to the best-matching frame established the RdRP core boundaries for each contig. In 98. 7% of the contigs, the RdRP core translations obtained with the standard genetic code contained no stop codons. The remaining RdRP-coding regions, however, contained up to 26 stop codons (Supplementary Dataset 3), suggesting alternative genetic codes. These contigs were translated using all 26 known variants of the genetic code, and the code that yielded the longest protein including the RdRP core was selected for each contig.
Viruses using alternative codes were identified in the Yan-like and Zhao-like clades within the Yangshan assemblage where the use of alternative codes is mostly confined to two distinct, smaller lineages (Fig. 3 ). Outside the Yangshan assemblage, alternative genetic codes were detected among the Ourmia-like viruses in Lenarviricota, Aquatic picorna-like and Dicistro-like viruses in Pisuviricota and Tombus-like and Noda-like viruses in Kitrinoviricota (Supplementary Dataset 3). The viruses with alternative codes probably infect protists and particularly, ciliates. 2 ). b, Yan-like virus clade (as in Fig. 3 ). c, Noda-like virus clade (as in Figs. 2  and 3 ). d, Protopotyvirus clade (as in Fig. 2 ). e, Zhao-like virus clade (as in Fig. 3 ). f, Brandma-like virus clade (as in Fig. 2 ). Each panel contains a genome map(s) of a phylogenetically close reference virus(es ).
The Yangshan virome could also shed light on RNA virus ecology. Quantitative analysis of contig occurrence revealed several extremely abundant viruses that are likely to reflect virus blooms on the most abundant hosts (Extended Data Fig. 10 ; Supplementary Dataset 4). The ecological composition of the Yangshan biome could also be relevant to the dominance of non-enveloped +RNA viruses in the extracellular RNA virome, to the exclusion of (-)RNA viruses. According to RdRP phylogenetic tree, Negarnaviricota are nested within Duplornaviricota, which are themselves lodged within the +RNA virus radiation (Fig. 2 ), implying more recent origin of (-)RNA viruses. Given that the greatest diversity of Negarnaviricota is found in invertebrates  29  , it has been suggested that this virus phylum evolved during the explosive Cambrian diversification of invertebrates  2, 49.
The water samples were initially settled at 4 °C for 12 h, and viruses were isolated using tangential-flow-filtration procedures as previously described  68  (Extended Data Fig. 8 ). The concentrated viral particles were stored at -80 °C before use. The absence of bacterial or cellular contamination in the filtrate was confirmed by transmission electron microscopy. Virus nucleic acid extraction. One millilitre of concentrated virus (approximately 10 10 -10 11 virus particles isolated from 10 l of seawater) was used for extraction of either DNA using Purification Resin and Mini Column (Promega)  69  , or RNA by using TRIzol LS Reagent (Invitrogen) and the Fast Total RNA Kit (Generay Biotech) (Extended Data Fig. 8 ). The integrity and concentration of nucleic acids were measured with NanoDrop 2000 (Thermo) and Qubit 3 analyser (Invitrogen).
The TruSeq Nano DNA HT Library Prep Kit (Illumina) was used to generate a 150-bp paired-end DNA library from the virus DNA extracts (Extended Data Fig. 8 ). High-throughput sequencing was performed on the Illumina MiSeq platform with v3 chemistry, and subsequently on the Illumina HiSeq 2500 platform. Both the library preparation and high-throughput sequencing were performed by Biozeron (Shanghai). Sequencing parameters are shown in Extended Data Fig. 9.
Computational subtraction. Sequencing adapters were first removed, and nucleotides with quality scores lower than 20 were trimmed from the ends of reads using the cutadapt tool (https://cutadapt. readthedocs. io/en/stable/). To obtain a 'clean' RNA dataset, DNA-matching reads were computationally subtracted from the pool of RNA reads before virus genome assembly using a k-mer based approach. All unique 30-mers present in the DNA library were collected and RNA reads with an exact match to any 30-mer in the DNA library (on either read in the mate-pair for the paired-end datasets) were then excluded prior to contig assembly. Then, 20-and 25-mers were also tested to ensure that the subtraction was not sensitive to the k-mer length. As anticipated by a priori calculations, while subtraction using 20-mers resulted in gross overfiltering, 25-and 30-mers resulted in very similar numbers of removed reads.
We also repeated the subtraction separately for the RNA libraries with or without DNase I treatment using 30-mers from the DNA dataset, and found no substantial difference in the numbers of removed reads (about 50% in each case), thereby underscoring the importance of in silico DNA subtraction. Contig assembly. Contigs from the paired-end random-priming library were assembled using SPADES v. 3. 11. 1 in metagenomics mode, while contigs from the single-end template-switching library were assembled using SPADES v. 3. 7 in metagenomics mode (v. 3. 11. 1 only supports assembly of paired-end reads in metagenomics mode). After assembly, the two sets of contigs were unified into a single set of non-redundant contigs by excluding any contig from the template-switching dataset that shared more than 90% of its 15-mer sub-sequences with any contig in the random-priming dataset.
5. When the same position-specific scoring matrices were employed to search the protein sequences from GenBank, 5,481 full-length, non-redundant (<90% identity) RdRP sequences were identified that formed 2,021 clusters. After the addition of 4,593 full-length sequences from the Yangshan dataset, the combined set of 10,074 sequences produced 4,213 clusters under the same clustering procedure, increasing the number of clusters by a factor of 2. 08. Multiple alignments of sequences within clusters were generated using MUSCLE  71. Cluster-derived profiles were compared to existing profiles using the HHsearch program  72  to broadly assign the Yangshan sequences to the five major branches of RdRPs  42. Iterations of clustering using HHsearch and profileprofile alignments using HHalign were performed to refine the positions of the Yangshan sequences within the RdRP tree.
The clusters were delineated such as to include sufficiently diverse sequences and to be significantly enriched with sequences from the metaviromic sample. This procedure yielded 323 clusters (OV. 1 to OV. 323 in Supplementary Dataset 1) containing from 1 to 653 sequences. Phylogenetic trees for the cluster alignments were generated using FastTree  73  with the WAG evolutionary model and gamma-distributed site rates. Nearly monophyletic groups of Yangshan RdRPs (containing at least 90% of Yangshan metagenome sequences) or mixed, but shallow groups of Yangshan RdRPs (corresponding to the tree depth of less than 1. 0 substitution per site) were considered to be distinct Yangshan clusters. For further phylogenetic analysis, the full-length RdRPs of the Yangshan set were aligned with their previously identified homologues and subjected to additional clustering based on the resulting preliminary phylogenetic trees.
The resulting clusters were then fitted into the previously constructed RdRP tree  47  using a procedure that involved several iterations of aligning Yangshan RdRPs with those from GenBank, constructing preliminary trees, and extracting Yangshan RdRPs that grouped together. The overwhelming majority of the Yangshan sequences (4,348 of 4,593, or 95%) and all large clusters (31 clusters encompassing 22 or more sequences each) were affiliated with previously identified RdRP lineages (Fig. 2 ; Supplementary Dataset 1). The RdRp permutations make permuted sequences unalignable with those of the canonical configuration. To incorporate them into the phylogenetic analysis, the following de-permutation procedure was performed: first, permuted sequence were identified, clustered using MMSEQ2 with sequence similarity threshold of 0.
5 and aligned with each other. Profile-profile alignments between these clusters and their closest canonical configuration relatives were performed using the HHALIGN program; the boundaries of the permuted catalytic loop were determined by examining the alignment and the corresponding alignment fragment was transposed to the canonical location (typically the location of the gap against the canonically located loop). Then the de-permuted sequences were returned to the pool, replacing the permuted originals. This procedure was used to generate Extended Data Fig. 1. In addition to the RdRPs that could be assigned to previously identified clades at different depths of the phylogenetic tree, we attempted to detect putative highly divergent RdRPs. First, all long RNA contigs (>1,200 nucleotides; 10,813 contigs altogether) from the virome were translated stop-to-stop in 6 frames, and any which encoded open reading frames for more than 400 amino acids were selected and clustered by sequence similarity.
The 37 profiles constructed from the resulting cluster alignments of 10 or more sequences were used as queries to search sequence databases with HHPred search. No RdRPs were found among these clusters. Second, open reading frames derived from 33 of the longest contigs in our dataset were analysed one at a time using HHPred; this procedure resulted in the identification of 13 singleton RdRP sequences (this analysis is too time consuming to perform on all potential RdRP-bearing sequences). DNA viruses in the Yangshan virome. The nucleotide sequences of DNA viruses were identified by comparing position-specific scoring matrices for the respective capsid proteins to the 6-frame translated sequences of the DNA metagenomic contigs using PSI-BLAST. The set of scoring matrices consists of 200 profiles derived from multiple alignments of capsid and coat proteins of eukaryotic, bacterial and archaeal DNA viruses.
Of these, 98 alignments were taken from National Center for Biotechnology Information Conserved Domains Database  74  and 102 were developed in-house  [75] [76] [77]. PSI-BLAST searches initiated by these profiles were competed against other, unrelated PFAM profiles in the Conserved Domains Database. Significant (e-value < 0. 0001) hits were recorded; contigs containing these hits were tentatively assigned to the respective virus group. Sampled sequences were manually curated using HHPred to verify or correct assignments. For many of the Polinton-like virus contigs, the best hits in the NR database are (erroneously) annotated as bacteria assembled from marine metagenomes (for example MAO23883. 1/NZRF01000276. 1, matching NODE_13251 contig). These 'bacterial' assemblies probably contain numerous fragments derived from the marine virome.
All nucleo-cytoplasmic large DNA virus (NCDLV) contigs were found to be highly similar to Phycodnaviridae (for example YP_004062106. 1/ NC_014767. 1 matching NODE_1923356 contig). Many of these also have close matches in 'bacterial' assemblies from marine metagenomes (MAB60321. 1/ NYUE01000104. 1). All four parvovirus contigs showed only distant similarity (about 30% protein identity) to vertebrate parvoviruses (for example APQ44761. 1/ KY053092. 1 matching NODE_10537 contig), suggesting that these are viruses of unidentified hosts rather than vertebrate virus contaminants. Identification and annotation of protein domains. To identify protein domains, we performed sensitive profile-profile comparisons using HHsearch  72. The identification procedure was run iteratively. First, profiles for each in silico-translated protein sequence were generated by performing one iteration against uniclust30_2018_08 database  78  with HHblits  79.
The generated profiles were then compared against the previous generated RNA virus profile database  42. Protein regions longer than 100 residues that did not display significant hits were extracted and clustered with CLANS  80. Groups containing at least five members were identified using convex clustering algorithm implicated in CLANS, aligned with MUSCLE  71  , annotated when possible and added to the RNA virus profile database. In addition, extracted protein regions were searched against the European Bioinformatics Institute metagenomics database  81  , supplemented with the RNA virus protein sequences from the current study by performing one iteration of Jackhmmer  82. Profiles with statistically significant hits (probability >95%) were annotated and added to the RNA virus profile database.
Finally, domain identification procedure was repeated using the updated RNA virus profile database. CRISPR-spacer search. CRISPR spacers (363,468 unique spacers) were matched against the set of oceanic virus contigs; 90% identity, 90% coverage criteria were used for matches, as previously described  83. Virus abundance. The abundances of viruses present in each virus cluster were calculated by mapping DNA-subtracted RNA sequencing reads back to RdRP-bearing contigs using bowtie2  84. A bowtie2 index was generated from the combined non-redundant contigs assembled from all RNA libraries, and bowtie2 was then used to map reads from each experiment back to these contigs. All RdRP-bearing contigs were more than 95% covered by mapped reads. The abundance of each contig was calculated as mapped reads per kilobase per million (RPKM) total reads in the library.
The distribution of contig abundances covers several orders of magnitude, is unimodal with a peak at ~18 RPKM and a median of 21. 3 RPKM, and resembles a log-normal distribution (Extended Data Fig. 10a ). However, the distribution is skewed such that the highly abundant assemblies are more abundant than expected from the log-normal distribution (Extended Data Fig. 10b ). The top 20 contigs had at least 10× greater coverage than the median RPKM value (Supplementary Dataset 4). The most abundant virus, a member of OV. 89 in the Tombus-like clade, was more than 800-fold over-represented compared to the median. The next three most abundant viruses were those from the Picorna-like aquatic/Marnaviridae and Zhao-like clades, all probably hosted by eukaryotic phytoplankton. The contigs were then grouped by cluster or by clade to identify over-represented lineages (Supplementary Dataset 4).
Acknowledgements We thank  N. Yutin  for providing protein multiple-sequence analysis for DNA virus search. Y. I. W. and E. V. K. are supported through the  Intramural Research Program  of the  US National Institutes of Health (National Library of Medicine ). S. S. is a  Damon Runyon Fellow  supported by the  Damon Runyon Cancer Research Foundation  ( DRG-(2352-19 )). A. F. was supported by  National Institutes of Health  awards  R01GM37706  and  R35GM130366. M. K. was supported by l'  Agence Nationale de la Recherche  grant  ANR-17-CE15-0005-01  (ENVIRA). D. K. was funded by the  European Social Fund  under no. 09. 3. 3-LMT-K-712 ' Development of Competences of Scientists, other Researchers and Students through Practical Research Activities ' measure. Y. W. was supported by the  National Natural Science Foundation of China  (nos.
Data availability The sequence data analysed in this work are publicly available at the National Center for Biotechnology Information (NCBI) sequence databases under Bioproject PRJNA605028, accession JAAOEH000000000 (RNA virome) and Bioproject PRJNA610033, accession JAAOEI000000000 (DNA virome). Additional data (including alignments, trees and domain assignment) are available with no restrictions at ftp://ftp. ncbi. nih. gov/pub/wolf/_suppl/yangshan. Limited quantities of the remaining biological materials are available upon request. Source data are provided with this paper.
at the top and viruses discovered in this study, identified as 'NODE_NN'. NODE numbers correspond to contig gene IDs listed in Supplementary Datasets 3 and 5. Functional domains are colour coded and the colour key for the recurrent domains is shown at the bottom of the figure. HaRNAV, Heterosigma akashiwo RNA virus; PVY, potato virus Y; HAstV-1, human astrovirus 1; ShIV3, Shahe isopoda virus 3; BZhV1, Beihai zhaovirus-like virus 1; NoV, Nodamura virus; LeppyrTLV1, Leptomonas pyrrhocoris tombus-like virus 1; PrsW, PrsW-family protease; ZBD, zinc-binding domain; PLA2, phospholipase A2; vOTU, viral ovarian tumour protease; MTase, methyltransferase; Chy-Pro, chymotrypsin-like protease; S-Pro, serine protease; C-Pro, cysteine protease; VPg, viral genome-linked protein; CP, capsid protein; fCP, filamentous capsid protein; NSMP, non-structural mature protein; CapE, capping enzyme; S3H, superfamily 3 helicase; Como32K-like, comovirus 32K-like protease; r84.
The shape of the electron velocity distribution function plays an important role in the dynamics of the solar wind acceleration. Electrons are normally modelled with three components, the core, the halo, and the strahl. We investigate how well the fast strahl electrons in the inner heliosphere preserve the information about the coronal electron temperature at their origin. We analysed the data obtained by two missions, Helios spanning the distances between 65 and 215 R S , and Parker Solar Probe (PSP) reaching down to 35 R S during its first two orbits around the Sun. The electron strahl was characterised with two parameters, pitch-angle width (PAW), and the strahl parallel temperature (T s ). PSP observations confirm the already reported dependence of strahl PAW on core parallel plasma beta (β ec )  (Berčič et al.
Parker Solar Probe Launched in August 2018, PSP  (Fox et al. 2016 ) is a mission designed to study the solar wind in the vicinity of the Sun, eventually reaching as close as 8. 8 R S from its surface. We analyse the data gathered during the first two orbits of PSP with the perihelion of 34. 7 R S and the aphelion between the orbits of Venus and Earth. Electrons on-board PSP are measured with two SPAN Electron (SPAN-E) electrostatic analysers: SPAN-A and SPAN-B  (Whittlesey et al. 2020) , part of the SWEAP instrument suite  (Kasper et al. 2016 ). Positioned on the ram and on the anti-ram side of the spacecraft with their 120 o × 240 o field of views (FOV) 90 o tilted with respect to each other, they cover almost full 4π solid angle. The azimuth angle (φ) on each of the SPAN-Es is measured by 8 small (6 o ) and 8 large (24 o ) anodes, while the elevation (θ) angles are sampled by the electrostatic deflectors.
Helios 1 The predecessors of the PSP are the two Helios missions launched in the 70s  (Porsche 1981). For more than 6 years these two spacecraft were exploring the inner heliosphere down to 0. 3 au (64 R S ) and provided us with a big data set of various solar wind parameters, among others revealing radial and solar cycle related trends  (Feldman et al. 1975; Pilipp et al. 1987; Maksimovic et al. 2005; Marsch 2006; Štverák et al. 2009 ). These data were of great importance during the preparation for the PSP mission and stay important due to the large statistics and radial and time coverage. In this work we use the data from Helios 1 gathered between 1974 and 1980. Electron VDFs on-board Helios 1 mission are sampled by a single narrow 2 o × 19 o FOV aperture, which uses spacecraft spin to obtain a 2D measurement in the plane perpendicular to the spin axis.
The light grey areas represent the solid angles not sampled by the two instruments. ergy steps. The full 2D measurement (16 energies, 8 azimuths) is completed in 16 s with a cadence of 40 s. The proton on-board integrated densities and velocity vectors were taken from the original Helios files in Helios data archive 1. The magnetic field vector is a composite measurement of two fluxgate magnetometers: E2 for all instances where measured magnetic field was less than 50 nT, and E3 for the rest. More details about the Helios data set and instrumentation can be found in our previous work with Helios observations  (Berčič et al. 2019 ).