dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion The objective of this study is first to establish a Mediterranean-specific climatic classification for hydrology purposes based on a set of indices, mainly seasonality and aridity, and second to estimate the future evolution of this classification based on RCP scenarios. In this study, the climatic classification was applied and verified on three datasets of different resolutions; the gridbased, the station-based, and catchment-based classification using the same climatic indices. We can clearly notice that the grid-based classification yielded the best resolution; however, despite the variability of the class boundaries between classifications, where some regions shift from class to another, the continuous evolution of climate across the Mediterranean was demonstrated by the indices values uniformly increasing or decreasing from north to south in all classifications.
Acknowledgements. The authors would like to thank the editor  Giuseppe Tito Aronica , first reviewer  Christophe Cudennec , and anonymous second reviewer for their constructive comments. We would also like to thank the Med-CORDEX providers for making their Regional Climate Data available. Thanks to the HESS Executive Editor for granting the authors a full APC waiver for this paper. Review statement. This paper was edited by  Giuseppe Tito Aronica  and reviewed by  Christophe Cudennec  and one anonymous referee.
Data availability. All the climatic data are freely available online. The WorldClim-2 data are available from the WorldClim website at https://www. worldclim. org/data/worldclim21. html (last access: 8 September 2020, WorldClim, 2020). The ground weather station data are available from the Global Historical Climatology Network website at https://www. ncdc. noaa. gov/ghcn-daily-description (last access: 8 September 2020, NCEI, 2020). The ALADIN and CCLM simulations used in the current work can be downloaded from the Med-CORDEX database at https://www. medcordex. eu/ (last access: 8 September 2020).
We called variants using the following command: java -jar VarScan. v2. 3. 9. jar mpileup2snp input. pileup-min-coverage 100-min-avg-qual 30-min-var-freq 0. 01 -strand-filter 1-output-vcf 1 > output. vcf. VCF files were parsed and annotated with coding region changes using custom software available here (https://github. com/blab/h5n1-cambodia/ tree/master/scripts). All amino acid changes for HA are reported and plotted using native H5 numbering, including the signal peptide, which is 16 amino acids in length. For ease of comparison, some amino acid changes are also reported with mature H5 peptide numbering in the manuscript when indicated.
Phylogenetic reconstruction We downloaded all currently available H5N1 virus genomes from the EpiFlu Database of the Global Initiative for Sharing All Influenza Data  [32, 33]  (GISAID, https://www. gisaid. org/) and all currently available full H5N1 virus genomes from the Influenza Research Database (IRD, http://www. fludb. org) [34]  and added consensus genomes from our 5 duck samples and 8 human samples. Sequences and metadata were cleaned and organized using fauna (https:// github. com/nextstrain/fauna), a database system part of the Nextstrain platform. Sequences were then processed using Nextstrain's augur software  [35]  (https://github. com/nextstrain/ augur). Sequences were filtered by length to remove short sequences using the following length filters: PB2: 2100 bp, PB1: 2100 bp, PA: 2000 bp, HA: 1600 bp, NP: 1400 bp, NA: 1270 bp, MP: 900 bp, and NS: 800 bp.
We excluded sequences with sample collection dates prior to 1996, and those for which the host was annotated as laboratory derived, ferret, or unknown. We also excluded sequences for which the country or geographic region was unknown. Sequences for each gene were aligned using MAFFT  [36] , and then trimmed to the reference sequence. We chose the A/Goose/Guangdong/1/96(H5N1) genome (GenBank accession numbers: AF144300-AF144307) as the reference genome. IQTREE  [37, 38]  was then used to infer a maximum likelihood phylogeny, and TreeTime  [39]  was used to infer a molecular clock and temporally-resolved phylogeny. Tips which fell outside of 4 standard deviations away from the inferred molecular clock were removed. Finally, TreeTime  [39]  was used to infer ancestral sequence states at internal nodes and the geographic migration history across the phylogeny.
Diversity (π) calculation Within-host variants were called as described above, requiring a minimum coverage of 100x, a minimum frequency of 1%, a minimal base quality score of Q30, and detection on both forward and reverse reads. Variants were annotated as nonsynonymous or synonymous. For each sample and coding region, we computed the average number of pairwise nonsynonymous differences per nonsynonymous site (π N ) and the average number of pairwise synonymous differences per synonymous site and (π S ) with SNPGenie  [40, 41]  (https://github. com/ chasewnelson/SNPGenie). We used the same set of within-host variants as reported throughout the manuscript (minimum frequency of 1%) for these diversity calculations. In both.
Comparison to functional sites We used the Sequence Feature Variant Types tool from the Influenza Research Database  [34]  to download all currently available annotations for H5 hemagglutinins, N1 neuraminidases, and all subtypes for the remaining gene segments. We then annotated each within-host SNV identified in our dataset that fell within an annotated region or site. The complete results of this annotation are available in S1 Table. We next filtered our annotated SNVs to include only those located in sites involved in "host-specific" functions or interactions, i. e. , those that are distinct between human and avian hosts. We defined host-specific functions/interactions as receptor binding, interaction with host cellular machinery, nuclear import and export, immune antagonism, 5' cap binding, temperature sensitivity, and glycosylation.
We also included sites that have been phenotypically identified as determinants of transmissibility and virulence. Sites that participate in binding interactions with other viral subunits or vRNP, conserved active site domains, drug resistance mutations, and epitope sites were not categorized as host-specific for this analysis. We annotated both synonymous and nonsynonymous mutations in our dataset, but only highlight nonsynonymous changes in Fig 4  and Table 3. For each gene and sample, we computed nonsynonymous (π N ), and and synonymous (π S ) diversity as the average number of pairwise differences between a set of DNA sequences. Values of 0. 00 indicate that there were no SNPs identified in that gene for that host species and mutation type. We then combined values from each sample to generate a diversity estimate for each gene and host species.
All other branches were considered "to-avian" branches. We did not explicitly allow for human-to-avian branches in this analysis. Because avian sampling is poor relative to human sampling, and because H5N1 virus circulation is thought to be maintained by transmission in birds, we chose to only label branches explicitly leading to human infections as to-human branches. We also reasoned that for instances in which a human tip appears to be ancestral to an avian clade, this more likely results from poor avian sampling than from true human-toavian transmission. Using these criteria, we then gathered the inferred amino acid mutations that occurred along each branch in the phylogeny, and counted the number of times they were associated with each type of host transition. We then queried each SNV detected within-host in our dataset, in both human and duck samples, to determine the number of host transitions that they occurred on in the phylogeny, as shown in Fig 6B.
General availability of analysis software and data All code used to analyze data and generate figures for this manuscript are publicly available at https://github. com/blab/h5n1-cambodia. Raw FASTQ files with human reads removed are available under SRA accession number PRJNA547644, and accessions SRX5984186-SRX5984198. All reported variant calls and phylogenetic trees are available at https://github. com/blab/h5n1-cambodia/tree/master/data.
Sample selection and dataset information We analyzed full-genome sequence data from primary, influenza virus-confirmed samples from infected humans and domestic ducks from Cambodia (Table  1 ). Four domestic duck samples (pooled organs) were collected as part of poultry outbreak investigations, while one was collected during live bird market surveillance (pooled throat and cloacal swab)  [4]. All human samples (throat swabs) were collected via event-based surveillance upon admittance to various hospitals throughout Cambodia  [22]. Because of limited sample availability and long storage times, generating duplicate sequence data for each sample was not possible. We therefore focused on samples whose viral RNA copy numbers after viral RNA extraction were �10 3 copies/μl of buffer as assessed by RT-qPCR (Table  1 ), and whose mean coverage depth exceeded 100x (S1 Fig).
We analyzed full genome data for 7 human and 5 duck samples, and near complete genome data for A/Cambodia/X0128304/2013, for which we lack data from the PB1 gene. H5 viruses circulating in Cambodia were exclusively clade 1. 1. 2 [4]  until 2013, when a novel reassortant virus emerged  [42]. This reassortant virus expressed a hemagglutinin (HA) and neuraminidase (NA) from clade 1. 1. 2, with internal genes from clade 2. 3. 2. 1a  [22]. All 2013/ 2014 samples in our dataset come from this outbreak, while samples collected prior to 2013 are clade 1. 1. 2 (Table  1,   The 2013 reassortant viruses share 4 amino acid substitutions in HA, S123P, S133A, S155N, and K266R  [22]  (H5, mature peptide numbering). S133A and S155N have been linked to improved α-2,6 linked sialic acid binding, independently and in combination with S123P  [43] [44] [45].
All samples encode a polybasic cleavage site in HA (XRRKRR) between amino acids 325-330 (H5, mature peptide numbering), a virulence determinant for H5N1 AIVs  [46, 47] , and a 20 amino acid deletion in NA. This NA deletion is a well-documented host range determinant  [48] [49] [50] [51]. Duck samples are not immediately ancestral to the human samples in our dataset, and they therefore are unlikely to represent transmission pairs. We therefore treat these samples as examples of within-host diversity in naturally infected humans and ducks, rather than direct transmission pairs. With this caveat, we aimed to use this subset of 8 human and 5 duck samples to determine whether positive selection would promote adaptation in humans. Positive selection increases the frequency of beneficial variants, and is often identified by tracking mutations' frequencies over time.
While multiple time points were not available in our dataset, all human samples were collected 5-12 days after reported symptom onset  [22]. Animal infection studies have observed drastic changes in within-host variant frequencies in 3-7 days  [11, 13] , suggesting that 5-12 days post symptom onset may provide sufficient time for transmitted diversity to be altered within-host. We reasoned that while we expect positive selection to promote the emergence of human-adapting mutation in humans, H5N1 viruses should be well-adapted for replication in ducks, which are a natural host species. We therefore hypothesize to observe the following patterns: (1) During replication in humans, positive selection should increase the frequencies of human-adaptive mutations, resulting in elevated rates of nonsynonymous diversity and a higher proportion of high-frequency variants.
SNVs are identified in humans at functionally relevant sites Influenza phenotypes can be drastically altered by single amino acid changes. We took advantage of the Influenza Research Database 29 Sequence Feature Variant Types tool, a catalogue of amino acids that are critical to protein structure and function, and that have been experimentally linked to functional alteration. We downloaded all available annotations for H5 HAs, N1 NAs, and all subtypes for the remaining proteins, and annotated each mutation in our dataset that fell within an annotated region (S1 Table ). We then filtered these annotated amino acids to include only those located in sites involved in host-specific functions (see Methods for details). Of the 218 unique, polymorphic amino acid sites in our dataset (including both human and duck samples), we identified 34 nonsynonymous mutations at sites involved in viral replication, receptor binding, virulence, and interaction with host cell machinery (Fig  4 ).
All other human and avian samples in our dataset encoded the "avian-like" amino acids, glutamate at PB2 627, and aspartate at PB2 701. None of the adaptive polymerase mutations that were recently identified by Welkers et al. [17]  in H5N1 virus-infected humans in Indonesia were present in our samples, nor were any of the human-adaptive mutations identified in a recent deep mutational scan of PB2  [57]. We also identified HA mutations linked to human receptor binding. Two human samples encoded an HA A150V mutation (134 in mature, H5 peptide numbering, Fig 4 ). A valine at HA 150 improves α-2,6 linked sialic acid binding in H5N1 viruses  [58, 59] , and was also identified in H5N1 virus-infected humans in Vietnam  [16]. Finally, HA Q238L was detected in A/ Cambodia/V0417301/2011 and A/Cambodia/V0401301/2011.
Shared diversity is limited Each human H5N1 infection is thought to represent a unique avian spillover event. If selection is strong at a given site in the genome, then mutations may arise at that site independently across multiple patients. We identified 13 amino acid sites in our dataset that were polymorphic in at least 2 samples, 4 of which were detected in both species (PB1 371, PA 307, HA 265 and NP 201). Of the 34 unique polymorphic amino acid sites in ducks, 3 sites were shared by at least 2 duck samples; of the 188 unique polymorphic amino acid sites in humans, 9 were shared by at least 2 human samples (Fig  5A ). Two of these shared sites, HA 150 and HA 238, are linked to human-adapting phenotypes (Table  3 ). To determine whether the number of shared sites we observe is more or less than expected by chance, we performed a permutation test.
For each species, we simulated datasets with the same number of sequences and amino acid polymorphisms as our actual dataset, but assigned each polymorphism to a random amino acid site. For each iteration, we then counted the number of polymorphic sites that were shared by �2 samples. We ran this simulation for 100,000 iterations for each species, and used the number of shared sites per iteration to generate a null distribution (Fig  5B  Viral genomes are highly constrained  [61] , which could account for the convergence we observe. Experimental measurements of the distribution of fitness effects in influenza A virus have estimated that approximately 30% of genome mutations are lethal  [61] , while estimates from other RNA viruses suggest that lethal percentage ranges from 20-40%  [62]. We repeated our simulations to restrict the number of amino acid sites that could tolerate a mutation to 70% or 60%, representing a lethal fraction of 30% or 40%.
Within-host SNVs are not enriched on spillover branches If within-host mutations are human-adapting, then those mutations should be enriched among H5N1 viruses that have caused human infections in the past. To test this hypothesis, we inferred full genome phylogenies using all available full-genome H5N1 viruses from the EpiFlu  [32, 33]  and IRD  [34]   If a branch fell within a clade that included only human tips, that branch was labelled as a "tohuman" transition. If a branch led to a human-only clade but its ancestral branch included avian descendants, this was inferred to be an avian-to-human transition, and was also labelled as "to-human". All other transitions were labelled "to-avian" (Fig 6A, see Methods for more details). We then curated the mutations that occurred on each type of host transition, and compared these counts to the mutations identified within-host in our dataset.
Of the 120 nonsynonymous within-host SNVs we identified in our dataset, 60 (50%) were not detected on the phylogeny at all. This suggests that many of the mutations generated within-host are purged from the H5N1 viral population over time. Additionally, because humans are generally dead-end hosts for H5N1 viruses, even human-adapting variants arising within-host are likely to be lost due to lack of onward transmission. Of the within-host mutations that were detected on the phylogeny, most occurred on branches leading to avian infections (Fig 6B, blue bars). However, there were a few exceptions (Fig 6B, red bars). Across the phylogeny, we enumerated a total of 31,939 to-avian transitions, and 2,787 to-human transitions, so that we expect a 11. 46:1 ratio of to-avian transitions relative to to-human transitions.
Discussion Our study utilizes a unique dataset to quantify H5N1 virus diversity in natural spillover infections. We establish a set of hypotheses to interrogate whether H5N1 viruses adapt to humans during natural spillover, and find support for two of them. We detect putative human-adapting mutations (PB2 E627K, HA A150V, and HA Q238L) during human infection, two of which arose multiple times (supporting hypothesis 2). PB2 E627K and HA A150V are enriched along phylogenetic branches leading to human infections, supporting their potential role in human adaptation (supporting hypothesis 4). However, we also find that population growth, genetic drift, and weak purifying selection broadly shape viral diversity in both hosts (rejecting hypothesis 1), and that convergent evolution in human viruses can be explained by genomic constraint (rejecting hypothesis 3).
An important caveat of our study is that the human and duck samples described likely do not represent transmission pairs. Although the samples analyzed in this study descend from the same HA lineage (with the exception of A/duck/Cambodia/Y0224304/2014), the duck samples are not phylogenetically ancestral to the human samples in this dataset (Fig  1  and S2 Fig) , and most likely were not the source of the human infections. We therefore caution that each sample in this dataset merely represents an example of within-host diversity in a naturally infected host, rather than a before and after snapshot of individual cross-species transmission events. Assessing zoonotic risk is critical but challenging. By quantifying patterns of within-host diversity, identifying mutations at adaptive sites, measuring convergent evolution, and comparing within-host diversity to long-term evolution, we can assemble a nuanced understanding of AIV evolution.
S2 Fig. Full genome phylogenetic placement of H5N1 virus samples from Cambodia. All currently available H5N1 virus sequences were downloaded from the Influenza Research Database and the Global Initiative on Sharing All Influenza Data and used to generate full genome phylogenies using Nextstrain's augur pipeline. Colors represent the geographic region in which the sample was collected (for tips) or the inferred geographic location (for internal nodes). The x-axis position indicates the date of sample collection (for tips) or the inferred time to the most recent common ancestor (for internal nodes). In the full phylogenies (left), H5N1 viruses from Cambodia selected for within-host analysis are indicated by tan circles with black outlines. The subtrees containing the Cambodian samples selected for within-host analysis are shown to the right in the order that they appear in the full tree.
We divided the data into these categories by splitting on the mean days post symptom onset for human samples, which was 8 days. We then compared the proportion of host-specific variants during early and late infections with a Fisher's exact test. The proportion of variants that are host-specific is not different in early vs. late infections (p = 0. 72). (PDF) S1 Table. All within-host SNVs with annotations. Every SNV identified in humans and ducks within-host are displayed with their frequency, coding region change, and functional annotation. All annotations for H5 HAs, N1 NAs, and all subtypes for all other genes were downloaded from the Influenza Research Database Sequence Feature Variant Types tool. Each SNV was then annotated as shown in the "description" column. These descriptions are paraphrased from annotations presented in the Influenza Research Database.
We then manually curated annotated mutations to determine whether they were involved in "host-specific" functions or not, as shown in the "host-specific?" column. We defined host-specific functions/ interactions as receptor binding, interaction with host cellular machinery, nuclear import and export, immune antagonism, 5' cap binding, temperature sensitivity, and glycosylation. We also included sites that have been phenotypically identified as determinants of transmissibility and virulence. Sites that participate in binding interactions with other viral subunits or vRNP, conserved active site domains, drug resistance mutations, and epitope sites were not categorized as host-specific for this analysis. We annotated both synonymous and nonsynonymous mutations in our dataset. (DOCX).
S2 Fig. Our final trees are available at https://github. com/blab/ h5n1-cambodia/tree/master/data/tree-jsons, and include the following number of sequences: PB2: 4063, PB1: 3867, PA: 4082, HA: 6431, NP: 4070, NA: 5357, MP: 3940, NS: 3678. Plotting was performed using baltic (https://github. com/evogytis/baltic).
The subtrees containing the Cambodian samples selected for within-host analysis are shown to the right and are indicated with grey, dashed arrows. In these trees, human tips are marked with a tan circle with a black outline, while duck tips are denoted with a tan square with a black outline. All samples from our within-host dataset are labelled in the subtrees with their strain name. Internal genes from samples collected prior to 2013 belong to clade 1. 1. 2, while internal genes from samples collected in 2013 or later belong to clade 2. 3. 2. 1a. All HA and NA sequences in this dataset, besides A/duck/Cambodia/Y0224304/2014, belong to clade 1. 1. 2. https://doi. org/10. 1371/journal. ppat. 1008191. g001.
2, while internal genes from samples collected in 2013 or later belong to clade 2. 3. 2. 1a. All HA and NA sequences in this dataset, besides A/duck/Cambodia/Y0224304/2014, belong to clade 1. 1. 2. (PDF) S3 Fig. All within-host variants detected in our dataset. All within-host variants detected in our study are shown. Each row represents one sample and each column represents one gene. The x-axis shows the nucleotide site and the y-axis shows the frequency that the variant was detected within-host. Filled circles represent nonsynonymous changes, while open circles represent synonymous changes. Blue dots represent variants identified within duck samples, while red dots represent variants identified in human samples. Blank plots indicate that no variants were identified in that sample and gene.
[27]n reads were removed from raw FASTQ files by mapping to the human reference genome GRCH38 with bowtie2[27]version 2. 3. 2 (http://bowtie-bio. sourceforge. net/bowtie2/ index. shtml). Reads that did not map to human genome were output to separate FASTQ files and used for all subsequent analyses. Illumina data was analyzed using the pipeline described in detail at https://github. com/lmoncla/illumina_pipeline. Briefly, raw FASTQ files were.