dataesr/scientific-paragraphs-categorization huggingface dataset:
These results are consistent with our investigations into nonacidified haloarchaeal proteins, in that both analyses identified nucleic acid binding and transmembrane proteins as potentially shielded from selective pressure to acidify and accumulate high G+ C content. However, the specific proteins identified by these analyses were not identical and previous work has indicated that G+C bias and acidification are not correlated for individual proteins  [35]. We speculate that many of the 138 unannotated protein families enriched in these regions of abnormal G+C content may be involved in DNA or RNA binding. We provide these regions in our Data Dryad package  [67] , as a rich source of data for identification of novel nucleic acid binding proteins and investigation of functionally important horizontal gene transfer events into the haloarchaea.
We examined the evolutionary history of haloarchaeal TBP and TFB homologs in order to understand their potential impact on environmental response. Phylogenetic distribution of paralog classes suggest that expansions of the TFB family are ancient, with several duplications occurring prior to haloarchaeal diversification (Figure  9 , Dataset S5, Figure  S9 , Dataset S6). Homologs of five of the seven TFB paralogs from the model haloarchaeon Halobacterium sp. NRC-1 were present in at least 79 of 80 sequenced isolates, while another (tfbA) was present in 74 isolates. The remaining paralog, tfbE, was found in only 39 of the 80 genomes sequenced, suggesting either that this paralog emerged from a relatively late gene duplication event, or has been lost from a large number of genomes. Evolutionary expansion of the TBP family appears to be a more recent phenomenon, with three haloarchaeal lineages showing distinct patterns of duplication and divergence (Figure  10 , Dataset S7, Figure  S10 , Dataset S8).
Bioinformatic applications of this dataset In addition to the applications we have already discussed (primarily focused on learning about osmoadaptation), our dataset has the power to address diverse problems in genomics, metagenomics, and other areas of bioinformatics. Here we illustrate some examples highlighting the diverse applicability of our dataset. Genera-level metagenomic profiling of saline environments. The first step in understanding a complex community is often determining what phylogenetic groups are present. This task may be facilitated by use of molecular markersgenes unique to and universal within a specific clade (following the example of  [20] ). We have developed a set of molecular markers for three deeply sequenced haloarchaeal genera (the Haloarcula, Halorubrum and Haloferax), and provide a list of these protein families as well as the protein sequences, alignments and hidden Markov models for each proposed molecular marker in our Data Dryad package  [67].
These markers may be integrated into metagenomics platforms such as Phylosift  [79] , for mining of metagenomic datasets from hypersaline environments. In addition, we provide a more extensive list of genera-specific protein families for 23 haloarchaeal genera (Dataset S9). This list includes any protein family for which members are found only within a specific genus, regardless of copy number or universality within the genus. Ranging from 1,456 unique protein families (Haloferax) to only two (Halopiger), this list provides a rich resource for exploring genera-specific haloarchaeal biology. Improvements to automated gene calling algorithms. Automated genome annotation programs inevitably result in both spurious and missed gene calls  [80]. The two annotation programs used in our analysis, NCBI's PGAAP  [14]  and the GLIMMER gene caller used in the RAST annotation pipeline  [13]  have been shown to exhibit this behavior  [80].
Improvements to automated gene annotation algorithms. Deep phylogenetic sampling also has the potential to improve gene annotation. By investigating patterns of protein family presence and absence across the haloarchaea, we were able to form testable hypotheses about the function of otherwise unannotated genes. We grouped protein families with similar phylogenetic distributions using hierarchical clustering. In cases where several protein families in a cluster were annotated as being involved in a particular process, unannotated members of that cluster were hypothesized to also be involved in this process. Two examples are discussed here, with additional examples in Dataset S10. First, a group of nine unannotated proteins were found to have similar phylogenetic distribution to six annotated redox proteins, including two menaquinol cytochrome-c reductases, two ferredoxins, a ubiquinol cytochrome-c reductase and a sulfite oxidase.
Additional examples can be found in Dataset S10 and Figures  S16-S22. In this section we have illustrated a few of the ways in which deep sequencing projects such as ours can benefit the genomics and metagenomics communities. These examples should not be taken as a complete set of problems to which our dataset may be applied, but rather as an indication of its broad utility and an invitation to the community to explore and utilize this data. To facilitate its widespread use, we have made the data available not only through the NCBI genome repository, but also through an SQL database and as a loadable ''popular genome set'' within the visualization tool JContextExplorer  [17]. We believe that lessons gleaned from explorations of this dataset will continue to enrich the genomics, halophile, archaeal, evolutionary and broader biology research communities for years to come.
Reads were assembled using the a5 pipeline  [18]. Following assembly, genomic DNA contamination arising from transpose-mediated library preparation was removed by searching assembled reads against a local BLAST database consisting of E. coli BL21 (DE3) genomic DNA and the cloning vector pWH1891. BLAST hits with an E-value # 10220 were considered to be significant matches and candidates for contamination. Contigs with matches covering $80% of the contig length and contigs #1 Kbp with matches covering any portion of the contig were treated as contamination and discarded from further analysis. Long contigs for which only a small portion of the contig matched to the local BLAST database were also discarded if there were either no annotated features, or if the annotated features were E. coli genes.
These criteria resulted in a total of 497 contigs equaling 265. 57 Kbp being removed from the final assemblies. A dual annotation pipeline was implemented in order to take advantage of the strengths of different existing automated annotation tools. Assembled genomes were first submitted to the Rapid Annotation using Subsystem Technology (RAST) server at the National Microbial Pathogen Data Resource. RAST-based gene calls and annotations were used for building of protein families, core genome and pan genome analyses, phylogenetic reconstruction, analysis of general transcription factor expansions, GC-bias analysis, building of molecular marker sets and phylogenetically informed re-annotation. These annotations can be accessed as a loadable ''popular genome set'' through the genome context viewer JContextExplorer  [17]  as well as a custom MySQL database (see Text S1 for instructions).
The RAST annotation system was particularly useful in enabling comparison of our genomes with previously sequenced haloarchaea, by allowing standardization via rapid reannotation of existing genomes. In addition, the newly sequenced genomes were annotated using NCBI's Prokaryotic Genome Annotation Pipeline (PGAAP)  [14]. PGAAP gene calls and annotations were used for COG analysis, proteome acidification calculations, and genera-based genomic feature comparisons. These annotations can be accessed through the NCBI website using the accession numbers listed in Table  S2  as well as through our custom MySQL database.
Phylogeny A phylogeny was constructed for all archaeal genomes available through the Integrated Microbial Genomes database along with our sequenced haloarchaea using a concatenated set of 40 conserved marker genes  [20]. Peptide sequences were downloaded for all archaeal genomes from the IMG 4. 0 database on January 4, 2013. HMM profiles of 40 bacterial and archaeal PhyEco markers were searched against these peptide sequences. We excluded genomes with less than 35 of these markers, as well as duplicate genomes which were included in both our analysis and the IMG database. A total of 151 IMG archaeal genomes and all 80 haloarchaeal genomes were included in the phylogenetic tree building. For each PhyEco marker family, only single-copy members from the genomes were included. Independent alignments were built using MUSCLE  [82]  for each gene families and then concatenated.
A phylogenetic tree was built from the concatenated alignment using PHYML 3. 0  [83]  with the LG substitution model. Tree topology and branch lengths were optimized by the program and aLRT SH-like statistics was used for branch support estimation. The R package ape was used to remove duplicate genomes  [84]  and the final tree was visualized using FigTree  [85]. The tree files are available as Dataset S3 (all archaea) and Dataset S11 (haloarchaea only).
Phylogenetic distribution of osmoadaptation genes A list of 74 genes involved in ion transport and compatible solute transport or synthesis compiled. Representative protein sequences for each of the selected genes were obtained by searching the NCBI protein database by annotation (Dataset S12). When available, sequences from the model organisms Escherichia coli and Bacillus subtilis were selected. Genes with ''MM'' prefix derive from Methanosarcina mazei Go1. BLASTp searches for these query sequences were conducted against a local BLAST database containing 80 haloarchaeal genomes. In order to obtain all potential homologs, the maximum target sequences parameter was set to 100,000 and an E-value cutoff of 1 was used. Resulting matches were then filtered using custom perl scripts to remove spurious domain-level matches by requiring a bidirectional querytarget coverage of $80%, and a bidirectional query-target length of $75%.
To reduce the number of non-specific family-level matches (for example, to differentiate between the closely related Trk H + /K + and Ktr Na + /K + symporters), sequences were also filtered to remove matches with an E-value of. 1e 220. A presence/ absence matrix was constructed from these filtered BLAST results using custom bash and R scripts, and visualized in iTOL  [91, 92]. Genes were grouped into functional categories based on substrate specificity and directionality for ion transporters, substrate imported for compatible solute transporters, or product for compatible solute biosynthesis proteins. As 20 of the query genes were not detected in the set of investigated species, only 54 columns appear in Figure  S5. Gene presence/absence data was scaffold on the multi-marker concatenated haloarchaeal phylogeny (Dataset S11).
Genera-based comparisons Whole-genome feature data for the 59 newly sequenced, PGAAP-annotated haloarchaea were retrieved from an in-house MySQL database using custom scripts  [67]. For each organism the genome size, number of contigs, percent G+C content, percent coding, number of coding regions, and number of insertion sequence elements were extracted. Genomes were organized into genera and box plots for each of the above traits were drawn for each genus using MATLAB's Statistics toolbox  [93]. Images were exported using the supplementary export_fig function  [94]. See Figure  S23.
Isoelectric point analysis All isoelectric point analyses were carried out exclusively on the PGAAP gene call set. The pI of every protein coding sequence was computationally predicted using the protein sequence isoelectric point prediction method included in the BioJava framework  [95]. pI histograms for each genome were computed using MATLAB's statistics toolbox  [93] , sorting proteins into 100 equally spaced bins ranging from a pI of 2. 0 to 13. 0. All proteins with a pI of 7. 5 or greater were collected and a list of all represented gene annotations was procured. For each gene annotation in this list, all instances were tabulated, including the number of instances with a pI greater than or equal to 7. 5. A table showing these results, sorted by frequency of instances with high pI can be found in Table  S5.
All proteins annotated as ribosomal subunits were collected, and all subunits which could confidently be mapped to experimentally characterized structures for the large (1QVG)  [96]  and small (1FKA)  [97]  ribosomal subunits were mapped. Subunits with a pI. 7. 5 in 60% or more of cases were colored red, and subunits with a pI,7. 5 in 60% or more of cases were colored blue. Any subunits which could not be confidently mapped or which had variable pI across species were left the default color of green. All mappings were done using the PyMOL protein visualization program  [98]. Comparative acidification visualizations of TBP and ribosome elongation factor a-1 proteins for haloarchaea and non-halophilic organisms were generated using the SWISS-MODEL web interface  [99]  and 1D3U  [100]  and 3VMF  [101]  as the structural templates, respectively.
General transcription factors A local BLAST database was constructed using RAST-derived gene calls for the 80 haloarchaea. This database, and the NCBI non-redundant protein database (as of October 30 th , 2012), were queried for homologs to the archaeal and eukaryotic general transcription factors TATA-binding protein (TBP) and transcription factor B/IIB (TFB) using a query set of 19 curated TBP homologs and 27 curated TFB homologs from six archaeal and one eukaryotic species (Datasets S18 & S19). A BLASTp search was conducted (BLAST+2. 2. 27) using a maximum expect value of 10 25 and maximum target sequence of 100,000. For each set of homologs, a multi-sequence alignment was constructed using MUSCLE v3. 8. 31  [82]  and manually curated to remove poorly aligning regions. Highly divergent and fragmentary sequences were manually removed.
One thousand bootstrapped alignments were created by resampling the curated alignment using Seqboot in the Phylip toolkit (v3. 69)  [103]. Phylogenetic trees were created for each bootstrapped alignment using FastTree v2. 1. 5 SSE3  [104]  and a consensus tree was produced by comparing these trees to a guide tree, also constructed using FastTree, using the tree comparison tool CompareToBootstrap. pl [105]. For all clades in the guide tree, the fraction of bootstrapped trees in which that clade appeared were tabulated and recorded as the bootstrap support values for that clade. Because this approach is limited in that only clades appearing in the initial guide tree are considered, we also constructed a consensus tree with the Consense program in the Phylip package  [105]  using the extended majority rule option.
Black line represents calculated G+C percent for each 100 bp window and vertical green lines represent points of inflection in the mean G+C percent which were selected as changepoints. Genomic regions between changepoints were taken as regions of abnormal G+C content, extracted and analyzed for enrichment of functional groups. The horizontal axis displays the number of 20 bp steps taken along the genome. Representative species selected correspond to those shown in Figure  7. (PDF) Figure  S9  Universal transcription factor B phylogeny. Unrooted phylogenetic tree of transcription factor B (TFB) homologs from NCBI's non-redundant protein database and recently sequenced haloarchaeal genomes. Red -haloarchaea, brown -other euryarchaeota, bright purple -crenarchaeota, yellow -thaumarchaeota, dark blue -other/unclassified archaea, salmon -metazoa, bright green -fungi, hot pink -viridiplantae, orange -other eukaryotes.
See Dataset S6 for tree file. (PDF) Figure  S10  Universal TATA-binding protein phylogeny. Unrooted phylogenetic tree of TATA-binding protein (TBP) homologs from NCBI's non-redundant protein database and recently sequenced haloarchaeal genomes. Red -haloarchaea, brown -other euryarchaeota, bright purple -crenarchaeota, yellow -thaumarchaeota, dark blue -other/unclassified archaea, dark green -chromalveolata, salmon -metazoa, dark purplecryptophyta, lavender -excavata, bright green -fungi, hot pinkviridiplantae, orange -other eukaryotes. See Dataset S7 for tree file. (PDF) Figure  S11  Genomic regions in Haloferax suggestive of a missed gene call. Analysis of genomic neighborhoods for 15 Haloferax species revealed a small hypothetical protein (Tribe4688, magenta) between a hypothetical protein (Tribe966, light blue) and a protein annotated as co-occurring with transport systems (Tribe458, dark blue), in most species.
Consense annotations and numbers corresponding to TRIBE-MCL protein families are shown on the right. (PDF) Figure  S23  Genera-level comparisons of genomic features (part II). Number of contigs (A), number of insertion elements (B) and percent coding DNA (C) were extracted from each genome, organized by genus, and boxplots calculated using MATLAB's Statistics toolbox  [93]. Boxplots were generated using 25 th and 75 th percentile as box edges, with median demarcated with horizontal line within box. Genera are ordered by descending number of species sequenced, with the number of species shown in parentheses. Genera with only a single sequenced member are shown as horizontal lines. (PDF)  Dataset S5 Haloarchaeal TFB CompareToBootstrap tree file. Manually curated alignment of haloarchaeal transcription factor B protein sequences was resampled 1000 times and trees constructed for each bootstrap replicate using FastTree  [104].
The consensus tree was produced by comparing these 1000 trees to a guide tree, also produced using FastTree, using the tree comparison tool CompareToBootstrap. pl [105]. Bootstrap support values for each clade represent the fraction of 1000 bootstrapped trees in which that clade appeared. Tree file is in Nexus format. (TXT) Dataset S6 Universal TFB CompareToBootstrap tree file. Manually curated alignment of archaeal and eukaryotic transcription factor B protein sequences was resampled 1000 times and trees constructed for each bootstrap replicate using FastTree  [104]. The consensus tree was produced by comparing these 1000 trees to a guide tree, also produced using FastTree, using the tree comparison tool CompareToBootstrap. pl [105]. Bootstrap support values for each clade represent the fraction of 1000 bootstrapped trees in which that clade appeared.
Tree file is in Nexus format. (TXT) Dataset S7 Haloarchaeal TBP CompareToBootstrap tree file. Manually curated alignment of haloarchaeal TATAbinding protein sequences was resampled 1000 times and trees constructed for each bootstrap replicate using FastTree  [104]. The consensus tree was produced by comparing these 1000 trees to a guide tree, also produced using FastTree, using the tree comparison tool CompareToBootstrap. pl [105]. Bootstrap support values for each clade represent the fraction of 1000 bootstrapped trees in which that clade appeared. Tree file is in Nexus format. (TXT) Dataset S8 Universal TBP CompareToBootstrap tree file. Manually curated alignment of archaeal and eukaryotic TATA-binding protein sequences was resampled 1000 times and trees constructed for each bootstrap replicate using FastTree  [104].
The consensus tree was produced by comparing these 1000 trees to a guide tree, also produced using FastTree, using the tree comparison tool CompareToBootstrap. pl [105]. Bootstrap support values for each clade represent the fraction of 1000 bootstrapped trees in which that clade appeared. Tree file is in Nexus format. (TXT) Dataset S9 Genera-specific protein families. A list of TRIBE-MCL protein families limited to, but not necessarily universal within, each haloarchaeal genus with sequenced members in this study. Manually curated alignment of haloarchaeal transcription factor B sequences was resampled 1000 times and trees constructed for each bootstrap replicate using FastTree  [104]. The consensus tree.
Figure2. Updated haloarchaeal phylogeny. Multi-marker concatenated phylogeny of the 80 genomes included in this study and other haloarchaeal genomes gathered from IMG. The unrooted tree was built from a concatenated alignment of 40 PhyEco markers using PHYML. Branch support values for top-level branches have been removed for ease of visualization. The full tree file can be accessed through Dataset S19. Grey boxes represent haloarchaeal clades as described in [19] , expanded as described in text. Tree roots in the Methanocella (not shown). doi:10. 1371/journal. pgen. 1004784. g002.
proteins dataframe. Analysis of predicted protein coding regions lacking annotations and belonging to a non-singleton protein family. From left to right, columns represent: protein ID (from RAST gene calls), protein family to which the protein belongs, and number of members, species and genera in that protein family. (TXT) Dataset S2 TRIBE-MCL clusters. Homologous protein families predicted by TRIBE-MCL clustering of all-vs-all BLAST results. Each line of this file represents one protein family, arranged in order of size. Tribe1 corresponds to first line of file and largest protein family. Families may include xenologs and paralogs as well as orthologs. Protein IDs are from the RAST gene call set. Protein families best explored via JContextExplorer (see Text S1 for detailed instructions). (TXT) Dataset S3 Multi-marker concatenated archaeal phylogeny tree file.
A phylogenetic tree was built from the concatenated alignment of 40 PhyEco markers using PHYML 3. 0 with the LG substitution model. Tree topology and branch lengths were optimized by the program and aLRT SH-like statistics was used for branch support estimation. Tree file is in Newick format. (TXT) Dataset S4 Osmoadaptation genes with annotations. A list of query proteins with functions related to osmoadaptation and their associated annotations. (TXT).
(TXT) Dataset S10 Reannotations based on phylogenetic profiling. A list of hypothesized gene functions for unannotated genes. Proposed reannotations are based on unannotated genes having similar phylogenetic distribution to a number of annotated genes in the same functional category as discovered via hierarchical clustering of protein presence and absence data across all 80 sequenced haloarchaeal genomes. (TXT) Dataset S11 Haloarchaeal phylogeny for use with JContextExplorer. A version of the multi-marker archaeal phylogeny (Dataset S3) where species not included in the set of 80 haloarchaea used in this study were removed using the R package ape. This tree file can be loaded into JContextExplorer for exploratory analyses of haloarchaeal genomic context evolution. Tree file is in Newick format.
(TXT) Dataset S12 Query sequences for osmoadaptation analysis. Fasta file containing all 74 query sequences used for BLASTp searches for genes potentially involved in osmoadaptation and other ion transport processes. (FASTA) Dataset S13 Query TBP sequences. Manually curated set of 19 archaeal and eukaryotic sequences used for detection of TATAbinding protein homologs via BLASTp searches. (FASTA) Dataset S14 Query TFB sequences. Manually curated set of 27 archaeal and eukaryotic sequences used for detection of transcription factor B homologs via BLASTp searches. (FASTA) Dataset S15 Haloarchaeal TFB consensus tree file.
The authors confirm that all data underlying the findings are fully available without restriction. All raw read files are available from the European Nucleotide Archive database. All assemblies and PGAAP annotations are available through the National Center for Biotechnology Information databases. Accession numbers for both databases are listed in Table  S2. Additional data files are available through the Data Dryad digital repository (doi: 10. 5061/ dryad. 1546n) as noted in the text.