dataesr/scientific-paragraphs-categorization huggingface dataset:
In a second series of experiments, mice were bitten by RVFVexposed mosquitoes collected on D16 or on D19 after infected blood meal. Blood-fed mosquitoes were collected and their viral loads were determined. The weight curves for the mice bitten by mosquitoes at D16 after virus exposure were followed. Three out of five mice received 1 or 2 bites from RVFV-exposed mosquitoes. Only one mouse died 13 days after receiving four mosquito bites (for which two out of four mosquitoes were infected), while the other mice survived until day 14 (data not shown). The experiment was repeated with mice bitten by D19 RVFV-exposed mosquitoes (Figure  6 ). As before, the numbers of blood-fed mosquitoes were counted and their viral loads were determined. Mice received up to 9 bites and 3 to 6 of these bites were from infected mosquitoes.
VlincRNAs exist in very large numbers in a variety of cancerous and normal cell types In this work, we identify and characterize over 2000 vlincRNAs found in a number of published and unpublished datasets (Table  1 ). We generated a Single Molecule Sequencing (SMS) RNA-seq dataset from human blood (Materials and Methods) in order to profile a human primary tissue containing diverse cell types, free of cell culture or other in-vitro artifacts. In addition, we used the ENCODE/CSHL long nuclear polyA-RNAseq dataset  [5, 6]  consisting of several cell lines of cancerous or primary origin (Materials and Methods). First, we determined the reproducibility of our original vlincRNA observations  [12]  by verifying their detection on different sequencing platforms, by different research groups, and in different RNA isolations from the same cell line.
Of the 60 vlincRNAs previously identified by us on the Helicos SMS platform as specific to the K562 human cell line  [12]  (see below),  56  were expressed in the ENCODE K562 long RNAseq dataset generated with the Illumina platform. This result confirmed that vlincRNAs are bona fide RNAs present in a cell. Overall, 341 of the original 580 tumor vlincRNAs  [12]  (Table  1 ) overlap ENCODE vlincRNAs identified from mostly different cell lines, using a different sequencing platform (p-value 1. 54 × 10 -45 ). VlincRNAs were found in all cell lines tested, including non-cancerous cell lines and tissues (Table  1 ). Embryonic stem cell line H1-hEsc expressed 469 such regions, while non-cancerous normal human epidermal keratinocyte line (NHEK) and normal human umbilical vein endothelial cells (HUVEC) expressed 248 and 340 vlincRNAs, respectively (Table  1 ; Additional File 1, Table  S1 ).
82 × 10 -210 and 1. 0 × 10 -300 ) (see Table  1  and Materials and Methods for details). VlincRNAs segregate into three categories: totally standalone transcripts (Figure  2 ), adjacent to known genes, but transcribed bi-directionally (Figure  3  A&B), or antisense to known genes (Figure  3  C&D). Sometimes vlincRNAs correspond to spliced ESTs, but most of the RNAseq signal maps to intronic portions of these ESTs, indicating they probably exist in unspliced form (Figure  2A , Figure  3C ). To estimate the fraction of antisense vlincRNAs and those transcribed bi-directionally to known genes, we examined the 1,661 ENCODE vlincRNAs in our dataset with unambiguous strand assignments (Table  1 ). Of those, 550 (33. 1%) were antisense to known genes, and 83 (5. 0%) were transcribed bi-directionally.
Expression of vlinc_377 was restricted to K562, while ARL15 was constitutively expressed and the direction of vlinc_377 transcription was opposite from ARL15 as shown by the vlincRNA from the ENCODE/CSHL long RNAseq dataset  [56]  produced with a protocol that reduced spurious second strand formation  [57] (Materials and Methods). Consistent with this, a K562-specific promoter element could be identified at the boundary of vlincRNA_377, upstream of the constitutive promoter controlling the ARL15 expression. Vlinc_185 (C & D) represents an interesting example of a very long antisense transcript. Due to the original constraint of annotating vlincRNAs as intergenic regions, the vlincRNA bounds did not extend over the KCNJ16 gene even though the RNAseq signal clearly extends into that gene (C).
Furthermore, a spliced EST BE777672 connects vlinc_185 to an intron of KCNJ16 and the 5' end of this EST corresponds quite well with the end of the RNAseq signal and also with a K562-specific promoter (C & D). Consistent with this, BE777672 was also isolated from a CML source. The entire length of this vlincRNA would be ~130 kb. Finally, the ENCODE K562 vlincRNA shows the recapitulates the strand and the start site of the previously published vlincRNA. RNAseq data shows density of informative reads normalized by 10M informative reads. The Y-axis of the alignability track (Materials and Methods) is on the scale of 0 to 1. Coordinates: hg18. LTR-containing sequences from Active promoters associated with vlincRNAs can indeed function to initiate transcription, we selected 2 LTR-containing K562-specific Active promoters and performed reporter gene assays in two cell lines (K562 and Hep3b) (Figure  4 , Materials and Methods).
Interestingly, only LTR-type repeats appear to confer strong tissue-specific expression patterns on vlincRNAs. To examine this, we used the original 580 vlincRNAs for which we had highly quantitative SMS RNAseq data from total cellular RNA (Table  1 ). We split the Active and All promoters according to whether they contained an LTR, did not contain an LTR but contained another retroposon, or contained no retroposon repeats, and categorized the 580 vlincRNAs based on their promoter association into one of the three above classes. We defined vlincRNA tissue-specificity, for any tissue in our previous SMS RNAseq dataset  [12] , as the ratio of the highest expresser to the second highest expresser. The vlincRNAs associated with LTR promoters showed much higher tissue-specificity than either the nonrepeat or the non-LTR repeat-containing promoters (Figure  1C ).
Association between vlincRNAs and retroviral promoters is a function of transformed or pluripotent state in key cell lines and primary cells Using the ENCODE promoter data with normal cells as well as cell lines at different levels of transformation, we observed a direct relationship between the number of Active promoters that overlapped LTRs and the replicative state of the cell. The primary cell lines had the lowest number of such promoters (397-700), followed by the immortalized cell line (989), and finally the cancerous cell lines (1,165-1,199) as shown in Table  2. For each cell line, we then determined a set of cell-line specific Active promoters by removing any Active promoter that overlapped Active, Weak or Inactive/poised promoters in the other 8 cell lines. The same trend held true for the cell line-specific Active promoters: the respective numbers were: 6-24, 153 and 303-427 (Table  2 ).
We next wanted to close the logical loop and determine whether cancerous and pluripotent cells had a higher tendency to express LTR-driven vlincR-NAs. We compared vlincRNAs and annotated promoters from 6 cell lines common to the ENCODE/CSHL long RNAseq dataset and ENCODE annotated promoters (Materials and Methods). The malignant/pluripotent cell lines indeed expressed an order of magnitude higher absolute number and fraction of vlincRNAs driven by the LTR promoters than the primary cell lines (Table  3 ). The embryonic stem cell line expressed similar numbers to the cancerous cell lines, while the immortalized cell lines expressed numbers in between the ES cells and the primary cells (Table  3 ). To validate this intriguing observation in a larger number of cell types, we investigated expression of vlincRNAs in 16 cell lines using ENCODE total polyA-RNAseq data: the 6 ENCODE cell lines in Table  3  and 10 additional cell lines, including 3 cancerous and 7 primary  [24]  (Materials and Methods).
VlincRNAs represent functional RNAs There are many ways to determine the functional importance of a class of RNAs. Syntenic conservation between species often provides evidence of function, especially in non-coding RNA with low sequence conservation  [29]. To investigate the presence of vlincRNAs in the same syntenic locations in human and mice, we generated a vlincRNA dataset from normal mouse lung (Materials and Methods). In total, 225 mouse vlincRNAs were found and mapped to the human genome in intergenic space (Table  1 ). Similar to the human vlincRNAs, the mouse vlincRNAs overlap the ENCODE promoters (Table  1 ) and in addition, 79/225 mouse vlincRNAs overlapped human vlincRNAs (p-value 0. 03). This argues for conservation, and thus, functional importance of this class of RNAs. In addition to synteny, comparisons to other independent datasets of known functional importance can be informative.
The vlincRNA data is sorted by the K562-specificity index (see text) with the most K562specific vlincRNAs on the left (A). Additional details in text and Materials and Methods. The original data is shown in Additional File 3, Table  S3. As expected, all 4 of the siRNAs that resulted in the increased apoptosis phenotype showed approximately 2-fold depletion of the corresponding RNAs. Of the two siRNAs that showed no phenotype, one resulted in depletion of the vlincRNA and one did not (Figure  5B ). It is therefore possible that failure to observe phenotypes with some siRNAs could be due to inefficient depletion of the corresponding RNAs, or that a particular vlincRNA is not involved in the regulation of apoptosis. To confirm that the observed phenotype was not due to non-specific events, we have selected two additional siR-NAs per vlincRNA (Additional File 5, Table  S4 ) for 6 vlincRNAs for which phenotype could be observed, 3 of which were LTR-driven, and repeated the experiments.
Materials and methods Datasets used I. Publicly-available 1. The 580 K562 -Ewing Sarcoma VlincRNAs: the coordinates of the vlincRNAs are listed in the Supplementary Table  S3  [12]. 2. Promoters from 9 human cell lines annotated by the ENCODE consortium, Broad Institute, MIT and MGH  [5, 16, 17, 44]. The basis of this analysis was profile of 9 different chromatin marks and input controls in 9 human cell lines. A Hidden Markov Model was then used to define 15 different chromatin states based on the different marks, including 3 states that corresponded to Active, Weak and Poised promoters  [17]. 3. ENCODE Yale/UC-Davis/Harvard Transcription Factor Binding Sites  [5, 21, 45]. 4. ENCODE/CSHL long nuclear polyA-and total polyA-RNAseq dataset  [5, 6, 24, 46]. 5. LTR repeats were extracted from the RepeatMasker track tables chr[N]_rmsk.
txt, where N = 1,. , 22, X, Y, M  [47, 48]. 6. UCSC Genes annotations were from the known-Gene. txt file: HG19  [47]  (Last modified 05-Feb-2012) and HG18  [48]  (Last modified 10-May-2009). 7. Disease-associated SNPs from GWAS studies were downloaded from the corresponding track on the UCSC Genome browser [49]. 8. Alignability track (36mers, Guigo -CGR, Barcelona) was downloaded from the UCSC browser  [50]. II. Un-published 9. Human blood SMS RNAseq dataset. Prior to routine angiographic testing for coronary artery disease, adult volunteers were consented and peripheral blood was drawn under IRB-approved protocols. All human studies were conducted in accordance with the principles of the Helsinki Declaration. All patients provided informed consent under protocols approved by The George Washington University Institutional Review Board (#111051).
In total, ~120 million informative reads were produced. The latter were defined as reads uniquely aligning to the genome with a minimal normalized score  [12]  of 4. 3 and filtered for rRNA and chrM reads. 10. Mouse inflammation RNAseq dataset was produced by combining ~1 billion informative reads generated from rRNA-depleted total RNA isolated from control mouse lung tissue and also treated with lipopolysaccharide in different regimes using Helicos single molecule sequencing technology. The experimental details and other aspects of this dataset are described in St. Laurent et al  [52]. The informative reads were defined as reads uniquely aligning to the genome with a minimal normalized score  [12]  of 4. 3 and filtered for rRNA and chrM reads. The filtered relevant reads from the above datasets were posted in SRA [SRA:SRP021192].
Construction of vlincRNA regions from different RNAseq datasets The ENCODE/CSHL long RNAseq data from nuclear polyA-RNA subcompartment was downloaded in the form of "contigs" that represent blocks of overlapping mapped reads from the pooled biological replicates. We removed any contigs that overlapped exons or introns of UCSC Genes. Since the data is strand-specific, all downstream analysis was done in a strand-specific fashioncontigs that overlapped genes on the other strand were not removed. Contigs separated by 1000 bp or less were merged and only those merged contigs that were at least 50 kb in length were allowed. Those separated by 5 kb or less were merged together. The resulting vlincRNAs were strand-specific. For construction of vlincRNAs from blood and mouse, we have first created the read density for each genomic base in non-strand specific fashion, then removed positions corresponding to annotated genes.
We then applied to the following consecutive thresholds: density threshold corresponding to the 80 th %-ile of expression, followed by merging genomic bases separated by no more than 500 bp (blood) or 1000 bp (mouse), followed by selection of regions of 50 kb or longer. The resulting vlincRNAs were not strand-specific. For comparison with the human vlincRNAs, the coordinates of the mouse vlincRNAs were converted to human coordinates using the LiftOver tool from the UCSC Genome Browser  [53]. Overlap between different datasets I. Overlap and p-value calculation between the strandspecific vlincRNAs and promoters. 1) When appropriate, Active, Weak and Poised Promoters from each of the 6 cell lines (K562, GM12878, HepG2, HUVEC, NHEK and H1-hEsc) were overlapped with LTR repeats. In such cases, only promoters that overlap LTR repeats were selected.
2) 10 kb intervals one for each vlincRNA from each of the 6 cell lines were constructed (+/-5 kb from left border for the top strand vlincRNAs and +/-5 kb from right border for the bottom strand vlincRNAs). 3) The number n of 10 kb vlincRNA intervals that overlap promoters was calculated for each cell line and each strand. 4) Probability p i that 10 kb interval of i-th vlincRNA overlap a promoter was calculated by formula p i = Occupied space i /(|Space i | -V), for each i = 1,. , N, where N -number of vlincRNAs in a given dataset and given strand, |X| is the operator for taking the total length of the intervals X Space i = Genomic space minus Anti space intervals whose left boundaries for top stranded vlincRNAs (right boundaries for bottom stranded vlincRNAs) were extended by length of the given vlincRNA, Anti space = genomic intervals occupied by UCSC Known Genes or Encode blacklisted regions* minus parts that overlap tested vlincRNAs.
4) Expected number of vlincRNAs mwith at least one of the two 10 kb intervals overlapping a promoter from the tested class was calculated as: m = N i=1 p i. 5) P-value as a probability P(ξ ≥ n) was calculated under assumption that ξ distributed as binomial B(N, m N ). III. Calculation of p-value for how many vlincRNAs from set 1 overlap vlincRNAs from set 2. This procedure is applicable for any genomic interval data in set 2 including SNP. 1) Probability p i that i-th vlincRNA from set 1 overlap any vlincRNA from set 2 was calculated by formula p i = Occupied space i /(|Space i | -V), for each i = 1,. , N, where N -number of vlincRNAs in set 1, Space i = Genomic space minus Anti space intervals whose both boundaries were extended by half of length L i /2 of the given vlincRNA, Anti space = genomic intervals occupied by UCSC Known Genes or Encode blacklisted regions minus parts that overlap vlincRNAs from set 1.
Hep3b cells were trypsinized 24 hours after transfection, pooled, divided equally, and cultured in 12-well plates for luciferase assays. The pRL-CMV (0. 1 μg) was cotransfected to normalize the transfection efficiency. After 24 hours transfection, suspension K562 cells were pooled, divided equally, and cultured in 12-well plates for reporter assays. Luciferase and dual luciferase assays were performed in 6 replicas for Hep3b and 3 replicas for K562 with kits from Promega. Luminescence was measured in a TD20/20 luminometer (Turner Biosystems), and relative light units (RLU) were standardized to Renilla luciferase activity expressed from cotransfected pRL-CMV. Quantitation of vlincRNA expression in 16 ENCODE cell lines. The ENCODE/CSHL long RNAseq data from total polyA-RNA was downloaded in the form of "contigs" that represent blocks of overlapping mapped reads from the pooled biological replicates.
The 16 cell lines were: A549, AG04450, BJ, CD20+, GM12878, H1-hESC, HeLaS3, HepG2, HMEC, HSMM, HUVEC, K562, MCF7, Monocytes-CD14+, NHEK, NHLF and SK-N-SH (treated with retinoic acid). More information about the cell lines can be found on the UCSC browser at the link for this dataset above. For each vlincRNA, the counts based on total number of bases covered by reads from the contig data (column 9 of the BED files) were obtained and normalized to 20G bases and and 1MBp of vlincRNA length. Individual vlincRNAs built from the 6 ENCODE cell lines (K562, HepG2, GM12878, H1-hESC, NHEK and HUVEC) that could be assigned to a promoter in All category (see Additional File 1, Table  S1 ) were used in this analysis. These vlincRNAs were further stratified into 468 and 739 vlincRNAs that could be assigned to a promoter that overlapped or not an LTR sequence.
The counting was done in a strand-specific fashion and contigs with very high counts (> 1M) were removed as they could likely represent artifacts or alignments to highly expressed sequences such as snRNA or rRNA repeats. Maximal values for the cancerous and primary cell lines were calculated (the immortalized and ESC cell lines were represented only by a single cell line each) for each vlincRNA. The ratio of maximal values in cancerous cell lines vs that in primary was then calculated as well as the ratios of immortalized to max primary and ESC to max primary. Zero values were replaced by the minimal non-zero expression value in the dataset. The averages of these ratios are shown in the Table  4.
Expression of vlinc_377 was restricted to K562, while ARL15 was constitutively expressed and the direction of vlinc_377 transcription was opposite from ARL15 as shown by the vlincRNA from the ENCODE/CSHL long RNAseq dataset [56]  produced with a protocol that reduced spurious second strand formation [57] (Materials and Methods). Consistent with this, a K562-specific promoter element could be identified at the boundary of vlincRNA_377, upstream of the constitutive promoter controlling the ARL15 expression. Vlinc_185 (C & D) represents an interesting example of a very long antisense transcript. Due to the original constraint of annotating vlincRNAs as intergenic regions, the vlincRNA bounds did not extend over the KCNJ16 gene even though the RNAseq signal clearly extends into that gene (C). Furthermore, a spliced EST BE777672 connects vlinc_185 to an intron of KCNJ16 and the 5' end of this EST corresponds quite well with the end of the RNAseq signal and also with a K562-specific promoter (C & D).
Consistent with this, BE777672 was also isolated from a CML source. The entire length of this vlincRNA would be ~130 kb. Finally, the ENCODE K562 vlincRNA shows the recapitulates the strand and the start site of the previously published vlincRNA. RNAseq data shows density of informative reads normalized by 10M informative reads. The Y-axis of the alignability track (Materials and Methods) is on the scale of 0 to 1. Coordinates: hg18.
Acknowledgements We would like to acknowledge  Dr. Ian Toma  for help with human blood experiments,  Maxim Ri  and  Yuri Vyatkin  for help with statistical analysis. WX is supported by  National Institutes of Health  grants  HL080789  and  HL084381. Authors' details 1 St. Laurent Institute,  One Kendall Square , Cambridge, MA. 2  Department of Molecular Biology ,  Cell Biology , and  Biochemistry, Brown University, Providence, RI. 3 A. P. Ershov Institute of Informatics Systems SB RAS ,  6 ,  Acad. Lavrentjev ave. , Novosibirsk 630090, Russia. 4Department of  Microbiology and Immunology, Sol Sherry Thrombosis Research Center, Temple University, Philadelphia, PA. 5  Université de Toulouse ,  UPS , LBCMCP, F-31062 Toulouse, France. 6CNRS, LBCMCP, F-31062 Toulouse, France. 7Department of  Biology, Drexel University, 3245 Chestnut St, PISB 417, Philadelphia, PA.
Phylogenetic Analysis and Genotyping Contiguous sequences were assembled in Sequencher and sequences aligned by the Clustal Wallis method in Mega4. Three phylogenetic trees were created by neighbor-joining, minimum evolution and maximum parsimony methods from the alignment of each gene target with the bootstrap consensus tree being inferred from 500 replicates and the bat trypanosome T. cruzi marinkellei [593 (B3)] or T. brucei [TReu927] used as the outgroup  [29] [30] [31] [32]. A strict consensus tree was interpreted from the three methods based on topology with no observed bootstrap supported incongruencies. Evolutionary distances were computed using the Kimura 2-parameter method  [33]. Lineage typing of each isolate was performed with whole or partial sequences of the obtained gene sequence and a BLAST search was administered on GenBank to determine sequence identity with previously genotyped T.
TcI reference strain (P209) Tc52, DHFR-TS) were classified as TcIV by phylogenetic analysis of COII-NDI sequences. A single TcIV isolate, Griffin Dog, had an incongruent phylogenetic position. These nine isolates are highlighted in Figures  2  and 3. SNPs were not observed among the COII-ND1 US TcIV isolate sequences, but they only had 96% sequence identity to the CANIII cl1 reference strain with 36 SNPs (data not shown). Among the COII-ND1 US TcI isolate sequences, 88 SNPs were identified so that two TcI alleles were identified (data not shown). One allele corresponds to TcI strains proposed to exhibit evidence of genetic exchange based on the mitochondrial and nuclear incongruent phylogenies seen in Figures  2  and 3 , while the other consists of TcI strains that do not show evidence of such events.
Amino acid change VRM I RL T RR Genotype of each isolate precedes the isolate name. Nucleotide positions correspond to sites from SilvioX10 cl1 (Genbank AY540739). Dots represent nucleotide site identical to reference strain (either Silvio X10 cl1 for TcI or CANIII cl1 for TcIV). *The following 17 US TcI sequences were identical: Human isolates (TC CC, CA R, TC California), domestic dogs (USA Dog Y), Virginia opossums (92101601P cl2, 93041401P cl2, FH4, FL Opo 2, FL Opo 3, FL Opo 15, Opossum 1970), armadillos (Armadillo 1973, USA Armadillo), triatomine bugs (Florida C1F8, Florida), and raccoons (93053103R cl3, FL Rac 13). { The following 23 US TcIV sequences were identical: Raccoons (FL Rac 9, 92122102R, 93071502R cl2, 93040701R cl1, 93072805R cl3, FL Rac 15, FL Rac 46, FL Rac 5, GA Rac 134, GA Rac 143, GA Rac 69, Maryland Rac, STC 35R), domestic dogs (Samantha Dog, Caesar Dog, Dog Theis, OK Dog, Smokey), ring-tailed lemurs (Clarence, Meg), rhesus macaque (Texas Theis), striped skunk (GA Sk 1), and armadillo (GA Arm 20).