Next-generation sequencing and ‘omics’ platforms are used extensively in plant biology research to unravel new genomes and study their interactions with abiotic and biotic agents in the growth environment. Despite the availability of a large and growing number of genomic data sets, there are only limited resources providing highly-curated and up-to-date metabolic and regulatory networks for plant pathways.Oryza sativa) genes involved in the seed development process by curating interactions reported in the published literature. We then applied an InParanoid-based homology search to these genes and used the resulting gene clusters to identify 351 Arabidopsis thaliana genes. Using this list of homologous genes, we constructed a seed development network in Arabidopsis by processing the gene list and the rice network through a Perl utility software called Pathway GeneSWAPPER developed by us. In order to demonstrate the utility of these networks in generating testable hypotheses and preliminary analysis prior to more in-depth downstream analysis, we used the expression viewer and statistical analysis features of PathVisio to analyze publicly-available and published microarray gene expression data sets on diurnal photoperiod response and the seed development time course to discover patterns of coexpressed genes found in the rice and Arabidopsis seed development networks. These seed development networks described herein, along with other plant pathways and networks, are freely available on the plant pathways portal at WikiPathways (http://plants.wikipathways.org).Using PathVisio, a pathway editor tool associated with WikiPathways, we created a gene interaction network of 430 rice  application in saving valuable time and labor when a reference network in one species compiled in GPML format is used to project a similar network in another species based on gene homology.The online version of this article (doi:10.1186/1939-8433-6-14) contains supplementary material, which is available to authorized users. LEA) genes that are expressed during seed desiccation are also expressed in leaves undergoing dehydration , legumes  and oil crops , seed development is the major contributing factor towards quality and yield traits. The seed development process is dependent on growth environment conditions such as photoperiod, seasonal and diurnal rhythms, temperature fluctuations, water availability and mineral nutrition. The process is systematically coordinated by the gene products bearing functions involving metabolic enzyme activity, transport and gene expression regulation  for Arabidopsis, rice and maize, making it a powerful resource for the research community and providing a central platform for pathway curation.Plant databases like Gramene Jaiswal , Kyoto EOryza sativa) seed development network as an example to guide users in creating their own networks. We then show the functionality of the Pathway GeneSWAPPER (PGS) application developed by us to project a sequence homology-based seed development network for Arabidopsis  using rice seed development network as reference. We also present an interspecific comparison of the two networks by demonstrating the ease and functionality of visualizing gene expression data of a subset of homologous genes from the networks to compare expression at different time points during seed development while simultaneously visualizing their diurnal rhythmic expression during the seedling stage.In this report we introduce a collaborative work on the new Plants Portal at WikiPathways developed as a community curation and analysis tool for pathway networks in plants. We use the rice (http://www.wikipathways.org/index.php/Pathway:WP2199) that includes 430 rice genes (nodes)  which was then analyzed for gene loss and gain for inter- and intra-specific comparison  has one paralog, AtBHLH039 (AT3G56980) has two paralogs and AtNAS3 (AT1G09240) has three paralogs  were expressed in the seed, 28 genes had ‘absent’ call in the absolute analysis and 11 did not have a corresponding Affymetrix probe ID , glutelin  and prolamin  seed storage (nutrient reservoir) proteins were highly expressed in the seed dormancy and desiccation stage  and OsMADS57 (LOC_Os02g49840), which were absent in both early and late (21–29 DAP) stages or showed no change in expression in the late/desiccation stage  is very highly expressed in the early stage compared to the later stage (a fold change of −200) and the protein product is shown to interact directly with OsMADS57.MADS box transcription factors function throughout plant life cycle  was the only gene in the subgroup to fall in this category, showing a phase-9  with external environmental signals in promoting plant growth and development. Not surprisingly, more than one third of Arabidopsis genes are under circadian control  and AG (AT4G18960) but genes like rice MADS56 and its Arabidopsis ortholog AGL19 showed very high conservation in the diurnal expression, indicating a high functional conservation as previously reported  pathway. The maize pathways include the most up-to-date and well-known networks for the carbon assimilation C4 pathway and carotenoid, lycopene, anthocyanin and several B-vitamin biosynthesis pathways. These pathways are a community resource hosted on the Plants portal at WikiPathways (http://plants.wikipathways.org), an open and central curation platform, where registered users can make their own contributions to plant science by creating new networks of known and/or published pathways or editing the existing ones. Registered users are cited instantly for their contribution as and when a new pathway is added and released publicly, and they are credited for any additional edits made to the existing networks and/or annotations.In this work, we showcase the utility of PathVisio, a user-friendly, open-source software application adopted by the WikiPathways project, to build a network of genes involved in seed development in rice, an important food crop. By using publicly available microarray data sets for transcript profiles during different stages of seed development and diurnal time course we further demonstrate PathVisio’s efficacy in analysis and visualization of gene expression data sets by matching and overlaying the expression to the genes in the pathway. With the rice seed development pathway presented here, we aim to initiate and motivate community participation in the creation of pathways for many other processes in rice and other plant species. Currently, a small number of We also demonstrate the Pathway GeneSWAPPER (PGS) utility application which saves valuable time and labor when a reference network from one species in the GPML format can be used to project a similar network for another species based on gene homology. The PGS paralog map feature gives users the ability to instantly identify gene families that have expanded or shrunk with respect to the number of paralogs in comparison to the reference pathway. Curation is a continuous process and additions are made to a network upon newly published experimental evidence. In addition to new projections and paralog “density” mapping, the PGS paralog map feature can be used to add new interactions to an existing pathway. On the flip side, PGS has the limitation of projecting only those genes that are represented in a reference pathway. For example, an Arabidopsis gene that lacks a homolog in rice would not be represented in the new Arabidopsis network projected using the rice network as reference. However, any additions and corrections are enabled through manual editing. Building such networks in other plant species will enhance inter-species comparison and deeper analyses through integration of already available transcript, protein and metabolomics data.http://www.pathvisio.org and installed locally on the desktop. Following the instructions provided in the help documents and a set of tutorials , data nodes (genes and metabolites) and edges/connectors (interactions) between two nodes were drawn. The interaction arrows represent activation/up-regulation and T-bars represent inhibition/down-regulation. Groups of genes with same interactions and functional complexes were created where necessary. Each gene node is labeled with gene symbol; similarly, a metabolite node is labeled with the name of the metabolite. Subsequently, each node carries additional references to PubMed literature IDs and cites its corresponding reference database ID. For example, gene IDs refer to the Gramene Rice Ensembl/MSU6 Gene IDs and metabolites refer to either CAS numbers or ChEBI IDs depending on their availability. Any useful comments were added in free text format in the comments field. Nodes and edges/interactions were color-coded to reflect functional classification such as external stimulus, subcellular localization and self-interactions, etc.PathVisio  and extracted using Gramene Biomart . As an optional feature, PGS is able to render the frequency of paralog occurrence in the projected species on a blue-to-red ‘density’ gradient – blue boxes represent a lower number of paralogs, red boxes denote a higher frequency of paralogy for that projection. PGS retains all features of the original reference network in GPML format while projecting the network onto a new species. When compared to the hours of manual intervention required to modify hundreds of network nodes by hand, this software saves time by providing a projected network from a reference template. Pathway GeneSWAPPER is freely available for download at http://jaiswallab.cgrb.oregonstate.edu/software/PGS. This website also provides links to sample data files used in this study.Beyond the benefits of curating pathway diagrams for a given species, it is also helpful to construct and visualize a similar network for another species by analyzing homologs in a graphical context. To achieve this goal, we wrote Pathway GeneSWAPPER , a Perl software application that redraws the PathVisio pathway diagram of another species, given a reference network and gene homology  mappings. The application generates a new GPML network file containing differently colored boxes for the represented orthologs. The output of the program also includes summary information on the number of mapped and unmapped gene nodes and a compiled list of paralogs within the projected species. A configuration file allows some graphical customization  from the PathVisio website provided through the BridgeDb framework used for all ID mapping functions in PathVisio and WikiPathways. As required by PathVisio, the gene expression data (in CSV file format) included “Os” as system code for the Rice Ensembl Gene synonym database and “A” for the TAIR (Arabidopsis) synonym database. The expression data set was imported in PathVisio and visualization was enabled according to user-defined criteria. Statistical analysis was performed by following step-by-step instructions and criteria rules within PathVisio to pose simple but specific queries as defined in Additional files Oryza sativa ssp indica cv IR64 grown in a culture room at 28°C under 14 hour light and 10 hour dark cycles for 15 days prior to being transferred to greenhouse. Gene expression was analyzed by the authors using GCOS 1.2.1 calculated signal intensity values averaged over 3 replications. Additional file In order to investigate the seed specific gene co-expression profile of the 430 rice genes in the reference seed development network we used two gene expression data sets for rice seed development at 0–2 days and 21–29 days after pollination (DAP), available at Gene Expression Omnibus . The publicly available dataset includes 7-day-old japonica rice (cv Nipponbare) and Arabidopsis (Col-0) seedlings that were grown in 12 hour days under 100μE (micro-Einstein) of light at 22°C day and 12°C night temperatures . Normalized gcRMA values were used to visualize gene expression at 8 hours after lights-on to represent day and 8 hours before lights-on  to represent night. A phase corresponds to the respective hour after lights on.For analysis of the genes expressed and regulated during diurnal conditions, we analyzed the diurnal photoperiod response data set  List of rice genes and Arabidopsis homologs in the networks. (2) List of rice paralogs. (XLSX 86 KB)Additional file 1:Additional file 2: List of peer reviewed references used to curate the gene interaction data and build the rice seed development network in PathVisio. (DOC 61 KB)This file has three worksheets. (1) Rice expressed genes and their fold change in gene expression from early to late stage of seed development (2) Input data for analyzing rice gene expression in PathVisio. Fold Change in gene expression from early to late stage of seed development in rice. (3) List of rice genes expressed in seed. (XLS 126 KB)Additional file 3:Visualizing transcript expression in PathVisio. Full view of the rice seed development network showing up-regulation of rice genes in 0–2 days after pollination (DAP) (blue) and in 21–29 DAP (red). Expression data was not available for gene boxes colored in grey. (PPTX 509 KB)Additional file 4:This file has three worksheets. (1) Arabidopsis seed gene expression between 5 and 13 days after fertilization (DAF). (2) List of Arabidopsis genes and their tissue/growth stage specific profile. (3) List of seed expressed Arabidopsis genes reported by Ruuska et al., Additional file 5:Additional file 6: Rice and Arabidopsis gene subsets and expression values for visualization and statistical analysis. (XLS 38 KB)Comparison of gene expression during seed development and diurnal rhythm in rice and Arabidopsis seed development networks. Green-to-red color set represents expression fold changes (A) between 0–2 DAP and 21–29 DAP stages of rice seed development and (B) in Arabidopsis seed between 5–13 DAF. Blue-to-red color set represents diurnal phase of expression in (A) rice seedlings and (B) Arabidopsis seedlings. Nodes that are grey in both A and B denote genes that were not queried. Nodes that are colored in the rice network but are grey in the Arabidopsis network indicate genes that lack a homolog in Arabidopsis. Panels were colored in sea green when expression values were not available. A quick visual scan of the two networks identifies similarities and differences in diurnal gene expression in the two species. For example, contrasting diurnal expression pattern is displayed by rice MADS3 and its Arabidopsis homolog AG (circled in red), and rice MADS57 and its homolog AGL44 (circled in pink). However, rice SSA2 and its homolog AT1G47640 (circled in purple), and rice MADS56 and its homolog AGL19 (circled in blue) display conserved diurnal rhythmic expression. (PPTX 485 KB)Additional file 7:Diurnal expression of some rice genes. Arrows indicate (A) pre-dawn peak in bHLH60 (LOC_Os08g04390); (B) small crest at mid-day (phase9) in PROLM26 (LOC_Os07g10580); (C) pre-dawn peak in MADS57 (LOC_Os02g49840) and MADS14 (LOC_Os03g54160); (D) end-of-day spike in MADS5  and MADS15 . The images were downloaded from the DIURNAL website . (PPTX 158 KB)Additional file 8:Querying for the expression fold change between early and late seed developmental stages in a subset of rice genes using PathVisio. (A) Results obtained after statistical analysis with user-defined criteria to identify genes with very high expression in the desiccation stage of seed development in rice. (B) Combined table showing different criteria used to query rice seed gene expression data and the results obtained. (PPTX 127 KB)Additional file 9:Querying for the diurnal phase of expression in a subset of rice genes using PathVisio. (A) Number of genes that have a phase above 12 and display a diurnal crest in dark. (B) Number of genes up-regulated in the mid-day hours. (PPTX 112 KB)Additional file 10:Authors’ original file for figure 1Authors’ original file for figure 2Authors’ original file for figure 3Authors’ original file for figure 4Below are the links to the authors’ original submitted files for images.


We assayed genome-wide cis and trans regulatory differences between maize and its wild progenitor, teosinte, using deep RNA sequencing in F1 hybrid and parent inbred lines for three tissue types . Pervasive regulatory variation was observed with approximately 70% of ∼17,000 genes showing evidence of regulatory divergence between maize and teosinte. However, many fewer genes  show consistent cis differences with all sampled maize and teosinte lines. For ∼70% of these 1,079 genes, the cis differences are specific to a single tissue. The number of genes with cis regulatory differences is greatest for ear tissue, which underwent a drastic transformation in form during domestication. As expected from the domestication bottleneck, maize possesses less cis regulatory variation than teosinte with this deficit greatest for genes showing maize-teosinte cis regulatory divergence, suggesting selection on cis regulatory differences during domestication. Consistent with selection on cis regulatory elements, genes with cis effects correlated strongly with genes under positive selection during maize domestication and improvement, while genes with trans regulatory effects did not. We observed a directional bias such that genes with cis differences showed higher expression of the maize allele more often than the teosinte allele, suggesting domestication favored up-regulation of gene expression. Finally, this work documents the cis and trans regulatory changes between maize and teosinte in over 17,000 genes for three tissues.Gene expression differences between divergent lineages caused by modification of  cis regulatory elements to produce differences in gene expression level, localization, and timing is an important mechanism by which organisms evolve divergent adaptations. To examine gene regulatory change during the domestication of maize from its wild progenitor, teosinte, we assessed allele-specific expression in a collection of maize and teosinte inbreds and their F1 hybrids using three tissues from different developmental stages. Our use of F1 hybrids represents the first study in a domesticated crop and wild progenitor that dissects cis and trans regulatory effects to examine characteristics of genes under various cis and trans regulatory regimes. We find evidence for consistent cis regulatory divergence that differentiates maize from teosinte in approximately 4% of genes. These genes are significantly correlated with genes under selection during domestication and crop improvement, suggesting an important role for cis regulatory elements in maize evolution. This work provides valuable insight into the evolution of gene regulatory elements during the domestication of an important crop plant.Modification of  These studies have shown that hundreds or even thousands of genes have altered expression in crops as compared to their progenitors and that genes with altered expression often show evidence for selection cis or trans effects was not discernible Several transcriptional profiles contrasting crops and their ancestors have been performed, although the experimental designs used did not allow separation of Zea mays ssp. parviglumis), into cis and trans effects. Three tissue types were assayed: immature ear, seedling leaf, and seedling stem. Approximately 70% of the 17,000 genes assayed show evidence of regulatory divergence between maize and teosinte. Over 1,000 genes show cis divergence that is highly consistent across our sampled maize and teosinte lines. For ∼70% of genes with consistent cis effects, the cis effects are specific to a single tissue type. The number of genes with cis differences is greatest for the ear, which underwent a profound transformation in form during domestication. Genes with cis regulatory differences between maize and teosinte are correlated with genes that show evidence for positive selection during domestication while trans genes are not. Maize also possesses less cis regulatory variation than teosinte over all genes and this deficit in maize is greatest for genes with cis regulatory divergence from teosinte. We observed a directional bias in genes with cis differences such that maize alleles were more frequently up-regulated than teosinte. Finally, our data provide a catalog of cis and trans regulatory variation for over 17,000 genes in three tissue types for 15 maize and teosinte inbred lines.In this study, we used RNAseq to parse genome-wide expression differences between maize and its progenitor, teosinte , and immature ear from six maize inbreds, nine teosinte inbreds, and 29 of their F1 hybrid and 286 million, 283 million, and 276 million parent RNAseq reads were collected for ear, leaf, and stem tissue types, respectively  seen in all three tissues. Of the remaining genes, 1,467 are in two tissues and 1,691 are in only a single tissue  cis effects account for 45%, 42% and 47% of regulatory divergence for ear, leaf and stem tissue, respectively . This analysis shows that the proportion of divergence due to cis is greater with greater total divergence in expression (2 change of 5 or more), over 75% of divergence is due to cis. Thus, large expression differences appear to be caused primarily through difference in cis regulation as opposed to trans.We asked what proportion of regulatory divergence between maize and teosinte was due to ectively . We furtpression . At highcis regulatory differences between maize and teosinte. Such genes in the cis only or cis plus trans regulatory categories (CCT genes) are candidates for direct targets of selection during maize domestication or improvement for altered gene expression. We identified 5,618 ear, 5,398 leaf and 5,435 stem CCT genes in the overall analysis . Next, we asked if genes on the filtered CCT list consistently favor expression of maize or teosinte alleles in the individual F1 hybrids. The goal was to exclude CCT genes for which the significant overall cis effect was caused by a large expression bias in one or a few F1 crosses. We defined three levels of consistency: groups A, B and C for which 100%, 90% and 80% of F1s showed the same directionality, respectively. Groups A, B, and C genes combined across tissues contained 69, 1,042, and 2,326 genes respectively  with positive log2 hybrid expression ratios than with negative ratios, suggesting cis evolution during domestication more often favored alleles with increased expression in maize relative to teosinte. Consistent with this visual observation, the number of CCT (ABC list) genes with a positive (maize biased) versus negative (teosinte biased) log2 hybrid expression ratio are 947∶598, 844∶483 and 826∶545 for ear, leaf and stem, respectively  as compared to maize inbred lines. If such systematic error exists, the observed bias in directionality of cis evolution would be expected to be greatest for F1s involving the reference B73  and less extreme for crosses between teosinte and non-reference maize lines (moderate bias for non-reference maize and high bias for teosinte).The apparent bias in directionality of 2 hybrid expression ratios for F1s involving B73 and non-B73 maize parents separately. For ear tissue, there are 569 teosinte-biased and 975 maize-biased genes for B73 F1s and 606 teosinte-biased and 939 maize-biased genes for non-B73 F1s. A Fisher's exact test fails to reject the null hypothesis of equivalent ratios (p = 0.18). There was also no evidence for non-equivalent ratios with the other two tissue types  genes with positive versus negative logue types . Thus, w1 hybrids, a linear model was fitted on a gene-by-gene basis with maize and teosinte inbred parent as explanatory factors for hybrid expression ratio. Among ∼13,000 genes included in this analysis, the maize parent explains only 85% as much variation as the teosinte parent (Both the domestication bottleneck and selection during domestication are expected to reduce variation in maize as compared to teosinte. We asked if these reductions in variation are apparent in our gene expression data. To quantify whether variation in maize or teosinte was the source of the variation in expression ratios among Fe parent . The rede parent . This recis regulatory candidate genes (A group), the data indicate that maize explains only about half as much of the cis regulatory variation as teosinte.While the bottleneck predicts reduced expression variation in maize overall, genes that were targets of selection for regulatory differences should have an even greater reduction in expression variation. Consistent with this expectation, we observed a greater reduction in variation in maize as compared to teosinte for CCT genes than the full set of ∼13,000 genes . For the1 expression ratio  quantify the degree of support for positive selection on a genomic region. A comparison of the distributions of ln(XPCLR) scores at the transcriptional start site  for selection in 6 of 9 comparisons, while trans only genes are never enriched and are actually significantly underrepresented among selected genes in two cases  for which there is both microarray and RNAseq data  alleles at their trans regulators. In contrast, the effects of cis regulatory elements are expected to be purely additive in absence of transvection or similar mechanism Cis only genes classified as having dominant gene action may indicate error in classification due to trans effects below the level of statistical detection. Consistent with the expectation that dominance is more likely for trans only genes, the proportion of genes classified as dominant is higher for trans only genes in all three tissue types  groups. First, a list of maize transcription factors and their corresponding families were compiled from the transcription factor database CCT (AB list) genes were also compared with results from a recent QTL mapping experiment for a number of domestication and improvement traits trans only genes in 15 different metabolic pathways defined in the Kyoto Encyclopedia of Genes and Genomes (KEGG) was done using Fisher's exact test on 2×2 contingency tables. There was no compelling evidence for enrichment/depletion of either groups of genes in any of the 15 pathways tested  as CCT genes that show cis divergence between maize and teosinte. This is a remarkably high proportion that reflects the considerable statistical power to detect small differences, likely with minimal biological importance, and does not consider whether the expression difference is consistent across maize-teosinte F1 comparisons. Thus, we focused our analysis on CCT A, B, and C gene lists showing consistent directionality of expression bias in 100%, 90% and 80% (respectively) of maize-teosinte comparisons. This approach narrows the list to 1,079 genes (A and B lists) that we consider our most robust candidates for genes with cis regulatory differences between maize and teosinte.Our primary focus was on genes with cis regulatory divergence between taxa in multiple tissues CCT candidate genes from the three tissues were largely different. Among the 1,079 CCT genes on A and B lists, ∼73% were identified in only a single tissue. This includes 336 ear, 257 leaf, and 198 stem specific genes. In contrast, only 77 of the 1,079 CCT genes were classified as CCT candidates in all three tissues. These results are consistent with previous studies that examined 1 hybrids, 14,421 were expressed in all three tissues. This high proportion of genes (82%) expressed in all tissues creates a false impression that sampling one tissue type at one point in developmental time provides a reasonable assay of all tissues at all developmental times. The discordant observations that CCT genes are mostly tissue specific, while genes overall are expressed in all tissues can be explained by tissue specific enhancers or repressors.While CCT genes are mostly tissue-specific, genes overall are not. Of the 17,579 genes assayed with at least 100 read depth in both the parents and FArabidopsisAmong the sampled tissues, it is notable that ear has the largest number of overall (555) and tissue specific (336) CCT genes . The gre1 hybrid analysis, ∼55% of genes have higher maize expression than teosinte. Higher expression of the maize allele also occurs in the parent inbred lines, except for leaf, where an equal number of genes favor maize and teosinte alleles. This trend of up-regulated maize expression extends to the CCT gene lists, where ∼60% of genes favor the maize allele  for which the two studies disagree. Although much of this disagreement can likely be attributed to factors such as differences in sampling or other sources of error, it reminds us of the imprecision in these types of data.A recent study using microarrays is×trans . Anothercis regulatory variation. Overall, maize possesses only ∼85% of the cis regulatory variation seen in teosinte  responsible for the loss of seed shattering during maize domestication is not on the list of selection candidates Although greater than expected overlap was observed between selection candidates and CCT genes, the degree of correspondence is far from perfect. For example, 25 of 36 CCT A-list genes assessed in the genome selection scan from ear tissue do not show evidence for selection. The misalignment between the selection candidate and CCT lists is likely due to both biological factors and artifacts. Domestication genes such as It has been proposed that the allelic variants responsible for evolution during domestication are often recessive LOF alleles such that the wild progenitor allele would be dominant to the domesticated allele cis only genes, since dominance at cis only genes requires a mechanism such as transvection cis only gene produced 5 RNAseq reads and disruption of the CRE reduced expression to 1 read per allele in the crop, then the diploid progenitor would have 10 reads, the crop would have 2 reads, and their F1 hybrid would have 6 (5+1) reads. The gene would be classified as purely additive. However, for trans only genes, if haplo-sufficient, dominance of the maize or teosinte allele could be observed.Dominance is expected to be uncommon for gene expression of trans only genes versus cis only genes , a known maize single gene mutant that causes a defect in branch initiation for both the whole plant and tassel ba1 was one of our strongest candidates with all assayed crosses showing higher expression of the maize allele in the ear. The overall shift in expression was substantial (∼4-fold) and this shift was caused solely by cis regulatory differences. ba1 was also found to be under selection during maize domestication in two independent studies ba1 in the ear, perhaps resulting in a greater number of rows (branches) of kernels in the maize ear as compared to teosinte. Compelling evidence for this hypothesis could be obtained by fine-mapping and identifying the hypothesized CRE and demonstrating with expression assays that the maize and teosinte alleles of the CRE have the imagined effects on gene expression during ear development and on phenotype (kernel row number) in the adult ear. ba1 illustrates the power of genomic scans to identify strong candidates for future study that can inform us about the fine details of evolution under domestication.An example of the value in these supplemental datasets is 1 hybrids were used in this experiment  from each plant were pooled to obtain ∼50 milligrams of tissue. These three tissue types are referred to as the ear, leaf, and stem tissues.Six maize inbred lines, nine teosinte inbred lines, and 29 of their 54 possible maize-teosinte Fperiment . An aver1s) or 15 (parents), and the pooled libraries sequenced on one lane (parents) or two lanes (F1s) of an Illumina HiSeq2000 sequencer. The raw sequence data has been deposited in NCBI Sequence Read Archive with accessions SRX710894-711341 and the Gene Expression Omnibus (GEO) Series with accession number GSE61810 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61810).Total RNA was extracted from the plant tissues using a standard TRIzol protocol, quantified by spectrophotometer, and normalized to 1 µg/µL in nuclease free water. Starting with 5 µg total RNA, we generated polyA selected, strand specific, barcoded RNAseq libraries with a previously published protocol using a five minute fragmentation time and 12 PCR amplification cycles de novo transcriptome assemblies using Trinity et al.Mitigating mapping bias through use of multiple references or enhancing the reference with segregating sites is critical for allele specific studies Pseudo-transcriptomes were constructed using the B73 reference genome (version AGPv2) and transcriptome (version ZmB73_5a_WGS) plus ∼403.1 million (17.5× coverage) paired-end genomic sequencing reads from each of the other 14 inbred lines . For eacFor each of the 29 maize-teosinte pairs, a robust set of segregating sites was determined by comparing the pseudo-transcriptomes of the two parents and taking the sites where: the two parental alleles differed, coverage in genomic read alignment was at least four for both parents within the read length (88 bp) of the site, and no heterozygous polymorphisms were detected in genomic read alignments of the two parents within the read length of the site.1 hybrid and each corresponding pair of inbred parents were then aligned to the combined pseudo-transcriptomes of the two parents (B73 reference transcriptome used for the B73 parent) using the Bowtie aligner (version 0.12.7) RNAseq reads from each F1 hybrid and parent maize∶teosinte expression ratios for each gene of the 29 individual F1 hybrid comparisons. Total depth at segregating sites summed over genes was highly correlated between biological replicates  were then calculated by dividing total maize read depth by total teosinte read depth summed over all segregating sites in the gene. The parent expression ratios for individual maize-teosinte comparisons were calculated the same way from parental RNAseq reads, except total parental read depths at segregating sites were corrected for differences in total number of reads between the two parent lines  from the parent ratio (cis plus trans).The combination of Fcis and trans effects. Significant cis and trans effects were determined using binomial and Fisher's exact tests as described in McManus et al.1 hybrid and parent comparisons. Genes with an expression ratio significantly different from 1∶1 for the F1 hybrid and/or parent comparison were then subjected to a Fisher's exact test to determine if the parent and F1 hybrid maize∶teosinte expression ratios were different from one another. An FDR rate of 0.5% using Storey's q-value et al.Maize and teosinte gene expression as measured by the read depth counts at genes was used for statistical testing of cis expression ratio that is significantly different from 1∶1. These genes can fall into the cis only (C) or cis plus trans (CT) groups on Genes under selection for expression during maize domestication are expected to show a maize∶teosinte cis expression variation that is causal in maize domestication and improvement. Therefore, we applied filters to identify candidates with the strongest and most consistent regulatory differences.The list of CCT genes from the overall test was large  and reflects the considerable statistical power to detect slight overall expression biases for genes with thousands of reads aligning to segregating sites. We observed significant maize∶teosinte expression biases as small as 1.02-fold in the overall tests. Such small differences seem unlikely to have biological importance and genes showing these small differences are weak candidates for genes with cis regulation between maize and teosinte, we applied two filters. (1) Genes with the strongest evidence for cis differences will fall in the CCT group and have data from a majority of sampled maize and teosinte parents. Thus, we filtered the initial list of CCT genes for those with data from at least fifteen F1 hybrids that include at least three different maize inbreds and five different teosinte inbreds. (2) For genes with cis differences that contributed to maize domestication/improvement, the direction of the expression bias should be highly consistent among the individual F1 hybrids. Consequently, CCT genes were classified for consistency of directionality of expression bias among the F1s with several levels of candidate genes partitioned at 100%, 90% and 80% of F1s showing the same directionality. In calculating these percentages, we used read depth for each F1 at the gene to weight the contribution of the F1s to the overall percentage. We refer to the CCT genes with 100%, 90% and 80% consistent directionality among the F1s as the A-list, B-list and C-list, respectively. For comparative purposes, we made similar A, B and C lists of genes for the cis only or trans only classes. These CCT and cis only gene lists  were used in downstream analyses in comparison with conserved or trans only genes to explore the role of cis regulatory variation in maize domestication.To narrow down the CCT gene list to candidate genes that show the strongest evidence for differential 1 hybrid expression ratios. We asked whether cis expression variation among F1 hybrid ratios was more heavily influenced by maize or teosinte inbred parent. Since three teosinte inbreds  were involved in only a single F1 each, the three F1s involving these inbreds were removed in order to balance the number of maize and teosinte inbred parents for this analysis. Genes were tested for variation among the F1 expression ratios (cis variation) using a linear model on a gene-by-gene basis that fitted the log2(maize∶teosinte) F1 expression ratio to the maize and teosinte parents as independent variables. Significant maize and teosinte parent terms were identified with an F-test (p<0.05) using the R drop1 function. The data for each F1 was weighted by total depth at the gene to account for variable read depth in the F1 hybrids.CRE diversity within maize and teosinte is expected to display as variation in the F1 hybrid comparison. The overall maize-teosinte average D/A ratio was then calculated after exclusion of outlier D/A ratios  ratio for each gene and maize-teosinte FA ratios  by iteracis only and trans only) are over or under represented in several functional categories as compared to all genes or genes with conserved expression levels between maize and teosinte. Generally, we tested all CCT gene lists  with the most weight given to the CCT-AB gene lists, which we consider our best candidates genes. The categories we tested include transcription factors, several metabolic pathways, gene ontology (GO) categories, selection candidates, and domestication QTL. A list of maize transcription factors and their associated families was obtained from the plant transcription factor database We assessed whether genes in different expression classes  versus F1 hybrid (y-axis) allele-specific expression ratios are plotted against each other. Regulatory category in terms of the combination of significant statistical tests determined using the method described in methods is shown designated by color. Proportion and count of genes falling into the various regulatory categories are also shown in the lower right hand corner barplot. (A) The leaf tissue analysis included 15,931 genes and displayed a similar pattern to that seen in the ear tissue in Log(TIF)Click here for additional data file.Figure S2Cis versus estimated trans regulatory effect for CCT-ABC genes in the leaf and stem. CCT genes have a directional bias with more genes overall favoring the maize allele than teosinte. Genes with consistent cis regulatory differences tend to favor the domesticated maize allele. The (A) leaf tissue and (B) stem tissue display similar bias to that seen in the ear tissue in (TIF)Click here for additional data file.Figure S32 values grouped by regulatory category. In all three tissues, the proportion of maize to teosinte R2 varies between 80% and 90%, consistent with the average loss of nucleotide diversity seen during maize domestication. This suggests no single regulatory category captures more genes under selection than others.Ratio of the average maize to teosinte R(TIF)Click here for additional data file.Figure S410.Tissue specific density plots of the ln(XPCLR) score for conserved versus CCT candidate genes. CCT  gene lists have a significantly higher XPCLR score in the 10 kb window holding the transcriptional start site than conserved (Con) genes. The natural log transformed XPCLR scores for CCT genes are progressively statistically higher than genes identified as conserved in the initial analysis. The distributions of conserved and CCT genes are significantly different by both the shape sensitive Kolmogorov-Smirnov test (upper right of heatmap) and simple difference of the means t-test (lower right of heatmap). Heatmap scale is in log(TIF)Click here for additional data file.Figure S5cis effect caused by dropping read depth from a single F1. The average difference in cis effect for each assessed gene caused by dropping read depth from each F1 one by one was calculated. Density plots show a strong peak at zero with minimal variance, suggesting individual F1 read depths have minor effect on the overall expression ratio.Density plots of the average difference (by gene) in (TIF)Click here for additional data file.Figure S6Histogram of the number of outlier D/A ratios removed by the Dixon method. Cross specific D/A ratios were calculated for all genes and outlier D/A ratios were excluded by iteratively applying the Dixon method. The majority of cases removed two or fewer outliers.(TIF)Click here for additional data file.Table S1cis regulatory effect grouped by overall parental divergence calculated as described in McManus et al.Proportion of divergence due to (DOCX)Click here for additional data file.Table S2The number of genes for which the maize or teosinte allele is expressed at a higher level.(DOCX)Click here for additional data file.Table S3Bias for the maize allele grouped by inbred line for the three tissues in the CCT-ABC gene list.(DOCX)Click here for additional data file.Table S41 hybrids that is explained by maize and teosinte parents.Proportion of the variation among the maize∶teosinte expression ratios for the F(DOCX)Click here for additional data file.Table S5Number of genes for which the maize and/or teosinte parent contributed to the variance among the F1 hybrid gene expression ratios (heterogeneous) and genes for which there was no variance in expression attributable to the maize or teosinte parent (homogeneous). CCT genes in groups A, B, and C in the three tissue types are shown.(DOCX)Click here for additional data file.Table S6Comparison of observed and expected numbers of genes classified as differentially expressed (DE) or not differentially expressed (NDE) by RNAseq [this study] and microarray assays (DOCX)Click here for additional data file.Table S7RNAseq-based regulatory categories for genes identified as differentially expressed in the microarray study (DOCX)Click here for additional data file.Table S8Fisher's exact tests for the overlap between genes associated with regions that are differentially methylated in maize and teosinte (DMRs) (DOCX)Click here for additional data file.Table S9Number of candidate genes neighboring regions that are differentially methylated (DMRs) between maize and teosinte (DOCX)Click here for additional data file.Table S10cis and trans only candidate lists. Dominance cells contain the number of genes for which the maize∶teosinte allele was dominant. Fisher's exact tests (FET) interrogate whether the degree of dominance/additivity differs between the cis and trans classes. A binomial test (*) indicates significantly different maize∶teosinte count (p<0.005).Additive and dominant gene counts for the A, AB, and ABC (DOCX)Click here for additional data file.Table S11Degree of overlap between our CCT (AB list) genes and genes in different transcription factor families.(DOCX)Click here for additional data file.Table S12Degree of overlap between CCT (AB list) differentially expressed genes and genes in the 1.5 support intervals for QTL from a previous study.(DOCX)Click here for additional data file.Table S13trans only differentially expressed genes and genes in metabolic pathways defined in KEGG.Degree overlap between our CCT and (DOCX)Click here for additional data file.Table S14trans only gene lists including tissue, group, accession, description, counts, rate of occurrence, and FDR corrected p-values.Significantly enriched and depleted GO terms from CCT and (DOCX)Click here for additional data file.Table S151 hybrid and parent inbred lines for RNAseq expression study with hybrid replicates internal and parent around the perimeter (shaded gray).Numbers of biological replicates of F(DOCX)Click here for additional data file.Table S16Adapter name, barcode sequence, and barcode length for Illumina adapters used in RNAseq libraries.(DOCX)Click here for additional data file.Table S17Number of genomic paired end reads and coverage obtained for constructing pseudo-transcriptomes.(DOCX)Click here for additional data file.Table S181 and parent maize∶teosinte read depth ratios for the 29 maize-teosinte comparisons.F(DOCX)Click here for additional data file.Table S19Spearman correlation between all biological replicate pairs of the same genotype.(DOCX)Click here for additional data file.Table S20Comparison of RNAseq expression data with expectations identified in the literature.(DOCX)Click here for additional data file.Table S21Increase in size and percent of CCT A, B, and C gene lists when using 5% Storey's FDR for significant binomial and Fisher's exact tests.(DOCX)Click here for additional data file.Text S1Supplemental methods and results.(DOCX)Click here for additional data file.


Derivative structural polytypes coexisting with the rhombohedral A7 structure of elemental bismuth (Bi) have been discovered at ambient condition, based on microstructure analyses of pure Bi samples treated under high pressure and high temperature conditions. Three structures with atomic positions close to those of the A7 structure have been identified through first-principles calculations, showing these polytypes energetically comparable to the A7 structure under ambient condition. Simulated diffraction data are in excellent agreement with the experimental observations. We argue that previously reported some variations of physical properties  in bismuth could be due to the formation of these polytypes. The coexistence of metastable derivative structural polytypes may be a widely occurring phenomenon in other elemental materials. Bismuth as a typical semimetal has attracted extensive research interests. Numerous studies have been conducted on Bi to investigate the electrical properties1234678910111213141618192021Some long-standing unusual behaviors in physical properties have also been noted in Bi, possibly resulting from the structure uncertainty. In 1928, Kapitza reported inconsistent changes in specific resistance when Bi crystals were subjected to strong magnetic field27In this paper, we report structural polytypes of Bi evidenced by both experimental observations and first-principles calculations. We performed structural characterizations on pure Bi samples treated at the conditions of different pressure and temperature with XRD and high-resolution transmission electron microscopy (HRTEM) and discovered a remarkable structural diversity in Bi after the treatments. Using crystal structure prediction techniques, we identified three new structures of bismuth that are closely related to the well-known A7 structure and differ from each other only by minute lattice distortions. First principles calculations indicate these structures have very similar energies, explaining the observed coexistence of multiple metastable polytypes in Bi. Such a structural diversity is intrinsic, not due to extrinsic action from the impurities or deformation, and maybe leads to some property variations  in pure Bi under normal conditions. These polytypes provide a structural interpretation for the so-called “mosaic block” structure previously speculated.An HRTEM image of the Bi sample treated under the condition of high pressure of 2 GPa and temperature of 2273 K viewed along [010] zone axis is presented in The shifts of Bi atoms from the A7 structure are so small (less than 0.1 Å) that HRTEM images and the corresponding SAED patterns alone cannot offer solid proof of structural polytypes. To account for the subtle lattice distortions observed in HRTEM measurement, we theoretically investigated a number of possible structural variations, in which atoms were shifted slightly from the equilibrium sites of the A7 structure without significant energy increase. Three new structures based on CALYPSO searches along with the known A7 structure and phase II (structure of Bi at pressure higher than 2.7 GPa) are shown in ab plane of the lattice. The A7 structure is comprised of …ABCABC… stacked biatomic layers A, B, and C along the c axis, with each layer spanning one third of the lattice period. For M, T1, and phase II structures, each biatomic layer spans one lattice period along the c axis. T2 structure  and lengths (L1–L6) are thus introduced see , and lisDynamic stability of the new structures was verified by phonon spectrum calculations in The very small enthalpy differences among the A7, M, T1, and T2 structures suggest that very small energy perturbations, due to either phase transition from phase II on pressure release or magnetic treatment, may alter the structure of Bi and that these derivative polytypes can co-exist with the A7 structure. This may be the structural origin of the crystalline imperfections252627The structural polytypes can also be detected in XRD patterns , which fBased on the experimental and theoretical investigations, we establish the structural diversity as an essential property for element Bi, in particular for samples treated at high pressures and high temperatures. Such diversity leads to the formation of secondary structures, which may be considered as derivative structures of the A7 phase. In our samples, these phase have only be observed on the nanoscale basing on the HRTEM images. Coexisting derivative structural polytypes may be a general phenomenon. One example is the monoclinic diamond (M-diamond) recently reported in bulk nanotwinned diamond materialin situ with a type C thermocouple (W5/Re26). Pressure was estimated with previously obtained calibration curves based on the electrical resistance changeBi granules  were compressed into cylinders (6 mm in diameter and 6 mm in height) and each was placed into a BN capsule with 8 mm outer diameter. High-pressure and high-temperature (HP-HT) experiments were performed using a China-type large volume cubic press with a maximum of 1400 tons on every WC anvil26p3 electrons  was adopted. The energy cutoff was 300 eV, and appropriate Monkhorst-Pack k meshes were chosen to ensure that enthalpy calculations converged to better than 0.01 meV per atom for each structure. Phonon frequencies were generated using the Cambridge Serial Total Energy Package (CASTEP) with finite displacement theoryThe software package of the crystal structure analysis by particle swarm optimization (CALYPSO)How to cite this article: Shu, Y. et al. Coexistence of multiple metastable polytypes in rhombohedral bismuth. Sci. Rep.6, 20337; doi: 10.1038/srep20337 (2016).


MLL rearrangements and harbor very few somatic mutations, less is known about the genetics of the cases without MLL translocations. We performed the largest exome-sequencing study to date on matched non-cancer DNA from pairs of mothers and IL patients to characterize congenital variation that may contribute to early leukemogenesis. Using the COSMIC database to define acute leukemia-associated candidate genes, we find a significant enrichment of rare, potentially functional congenital variation in IL patients compared with randomly selected genes within the same patients and unaffected pediatric controls. IL acute myeloid leukemia (AML) patients had more overall variation than IL acute lymphocytic leukemia (ALL) patients, but less of that variation was inherited from mothers. Of our candidate genes, we found that MLL3 was a compound heterozygote in every infant who developed AML and 50% of infants who developed ALL. These data suggest a model by which known genetic mechanisms for leukemogenesis could be disrupted without an abundance of somatic mutation or chromosomal rearrangements. This model would be consistent with existing models for the establishment of leukemia clones in utero and the high rate of IL concordance in monozygotic twins.Infant leukemia (IL) is a rare sporadic cancer with a grim prognosis. Although most cases are accompanied by  Unlike leukemia in older children where survival rates for acute myeloid leukemia (AML) and acute lymphocytic leukemia (ALL) are approximately 60% and 85%, respectively, infants with leukemia have a 5-year event-free survival rate of about 50%.ETV6-RUNX1, E2A-PBX1) commonly seen in pediatric leukemia are very rarely observed in IL, MLL rearrangements (MLL+) are observed in approximately 50–80% of infant ALL cases and 34–50% of infant AML cases.4 In contrast, in older children the percentages of MLL rearrangements are 6% and 14% for ALL and AML, respectively.5 There is evidence from multiple in vitro systems that the presence of a MLL rearrangement is insufficient by itself to drive leukemogenesis,8 suggesting that additional factors are required in the presence (and absence) of MLL rearrangements to drive leukemogenesis. In contrast, very little is known about the role of congenital variation in MLL− IL. Infants without MLL rearrangements have superior outcomes9 and a unique expression profile compared with MLL+ IL and childhood B-precursor ALL.10 Finally, exome11 and genome sequencing12 of MLL+ cases have identified exceedingly few somatic mutations, supporting the hypothesis that somatic mutation alone is not the sole driver for IL. In comparison, no such large-scale sequencing effort has been reported on MLL− IL cases.Although other translocations  AE24: ‘Epidemiology of Infant Leukemia' case–control study to acquire information and DNA samples from mothers and their infants with acute leukemia. The AE24 study observed a statistically significant association with topoisomerase II inhibitor exposure during pregnancy only in mothers of infants with MLL+ AML, but this association was not observed for infants with MLL− disease or ALL.17In addition to genetic variation, epidemiological evidence suggests that maternal exposures during pregnancy, particularly to DNA topoisomerase II inhibitors,18 and that these rare variants have greater effect sizes19 and are more likely to act dominantly.20 Accordingly, some have proposed that rare, recently derived variants segregating in families may be critical for complex disease—and that the phenotypic consequences of these alleles may be critically shaped, and thus variable, by their genomic context .21 Motivated by this so-called ‘clan genomics' framework and the genetic architecture for carcinogenesis proposed by Vogelstein ,22 we set out to test whether or not IL arises within a genetic background enriched for functional variation in leukemia candidate genes—potentially mitigating the need for the expected burden of somatic mutation, but still resulting in the expected total amount of variation typically observed in cancer. We have completed exome sequencing of non-cancer DNA from mothers and infants with MLL− IL to characterize profiles of rare, congenital germline variation that may influence leukemogenesis and proliferation. Supporting our hypothesis, we observed a statistically significant enrichment of rare, non-synonymous and predicted functional sequence variants in genes previously known to harbor functional somatic mutations in pediatric and adult leukemia. Despite being uncommon, the study of the genetics driving rare cancers and their accompanying predisposition syndromes  has historically elucidated important biological insights into normal and pathological cellular mechanisms that can extend our understanding of additional complex diseases.In summary, IL is a distinct clinical entity with evidence for both genetic and environmental causes, but detailed studies have failed to account for overall disease incidence. Recently, large-scale genome sequencing projects have revealed that the spectrum of genetic variation in human populations is dominated by rare alleles,MLL gene rearrangements who were enrolled on the COG-AE24: ‘Epidemiology of Infant Leukemia' protocol. Briefly, infants (<12 months) with a confirmed diagnosis of ALL or AML during the period 1996–2006 at North American COG institutions were eligible for the parent AE24 study; cases with Down syndrome were excluded. None of the infants included in this study were reported to have birthmarks, birth defects, known chromosomal abnormalities or family histories of pediatric cancers. In addition to providing buccal cell samples for themselves (via mouthwash) and their infants in first remission (via cytobrushings) using Puregene Buccal Cell Kit , as well as consent for genetic research using the samples, mothers also released their child's diagnostic information, including results of Southern blot, reverse transcription-PCR, fluorescent in situ hybridization or other cytogenetics testing, to permit central review. Three independent reviewers evaluated submitted materials to confirm diagnoses and determine if there was evidence of MLL gene rearrangement (MLL+), no rearrangement (MLL−) or insufficient evidence to classify. Institutional Review Boards at the University of Minnesota Coordinating Center (#0309M52104) and participating COG institutions approved the parent AE24 study. Control pediatric exomes were obtained from Caucasian infants and their parents without cancer collected as part of an exome sequencing initiative conducted by the Newborn Medicine Division at St Louis Children's Hospital . Exome sequencing was approved by Washington University Human Research Protection Office ID# 201105062.DNA samples and demographic and clinical information were collected from 23 pairs of deidentified Caucasian mothers and their infants with acute leukemia without For all samples, 15–25 ng of germline DNA was whole-genome amplified using the Sigma GenomePlex kit according to the manufacturer's protocol . From each amplified product, 1 μg was used for sequencing library preparation according to the Illumina TruSeq DNA Sample Prep v2 kit followed by hybridization capture of each exome according to the Illumina TruSeq Exome Enrichment Kit . Libraries were sequenced three/lane on the Illumina HiSeq 2000 platform generating 101 bp paired-end reads by the Genome Technology Access Center at Washington University.23 with sensitivity of 96.9% and specificity of 99.8% with exome analysis for raw data alignment and variant calling. Raw sequence data in fastq format were aligned to the NCBI human genome build 37 (hg19) using a purchased, multi-threading version of Novoalign version 2.05 (www.novocraft.com) and published thresholds. An alignment threshold of 200 was used (-t 200), with adapter stripping (5′-a AGATCGGAAGAGCG-3′) and quality calibration enabled (-k). Reads with multiple alignments were discarded  and output was in SAM format (-o SAM). Variant calling from the aligned output for the individual exomes was then performed using SAMtools.24 The aligned data were converted to BAM format to allow the removal of duplicate reads using Picard ‘MarkDuplicates'. Variants were then called with the SAMtools version 0.1.18 mpileup command, using options -AB –ugf and bcftools ‘view' with settings -bvcg. Finally, variants were filtered with vcfutils ‘varFilter' using default settings except retaining all variants with under 99999 reads. This process ultimately yielded a comprehensive list of exomic variants for each subject, including single-nucleotide variants and short insertions and deletions. ‘Raw' variant calls from each sample were further filtered by retaining only variants with ⩾5-fold coverage/allele (>10-fold/base position), a genotype quality score of ⩾10 and a mapping quality score of ⩾60. Although ⩾5-fold coverage/allele was a bare minimum, it should be noted that our average coverage per variant per exome was 21.5-fold/allele (43-fold/base position). Each of the individual quality score thresholds will only retain a variant position with at least a 95% likelihood of being a true variant. When applied together, the probability of a variant miscall is significantly reduced. All remaining variants were used as input for the ‘variants_reduction.pl' tool provided with the ANNOVAR software package (http://www.openbioinformatics.org/annovar/).25 To enrich for high-confidence variants likely to confer a functional consequence, successive filters were applied, keeping only variants which were non-synonymous and coding or at splice junctions, and were rare  in either the 1000 Genomes Project (April 2012 release) or in the dbSNP130 Non-Flagged variants lists. Sequencing results are available at the NCBI Short Read Archive under accession number SRP024273.For all exome data from probands, mothers and controls, we used a published bioinformatic pipelinehttp://cancer.sanger.ac.uk/cancergenome/projects/cosmic/),26 we compiled lists of genes relevant in AML and ALL. To do this, we used the Tissue search feature, selecting samples from ‘hematopoietic and lymphoid' tissue followed by ‘NS' for Subtissue type. For AML, we further refined our gene list by selecting ‘hematopoietic' from the Histology menu and, from the subHistology menu, ‘Acute myeloid leukaemia', ‘Acute myeloid leukaemia associated with MDS', ‘Acute myeloid leukaemia myelodysplastic syndrome therapy related NOS' and ‘Acute myeloid leukaemia therapy related'. For ALL, we selected ‘Lymphoid Neoplasm' from the Histology menu followed by ‘Acute lymphoblastic leukaemia' and ‘Acute lymphoblastic B cell leukaemia' from the subHistology menu. Having filtered by tissue and histology, we selected all genes with sequence variation in our cohort, which yielded a list of 126 ALL-associated genes and 655 AML-associated genes. Thirty-four genes were shared between candidate gene sets. These genes are listed in Using version 63 (ALL) or version 64 (AML) of the COSMIC database (www.r-project.org). P-values (using an α=0.005 to increase stringency) were generated by comparing the aggregate number of rare, non-synonymous, predicted deleterious variation in each patient group against either the matched mothers, the unaffected control population, the opposite patient group or the opposite group of mothers. Unaffected controls consisted of 12 unaffected Caucasian pediatric exomes.Hypergeometric (Fisher's Exact) testing was performed using the ‘phyper' function in the R software statistics package .Permutation analysis was executed in the R software package using the ‘sample' function in the base package. Using this function, a distribution of the number of rare (not listed in dbSNP 135 or the 1000 Genomes Project), non-synonymous and predicted deleterious variants Confirmatory dideoxy sequencing was performed at Washington University's Protein and Nucleic Acid Chemistry Laboratory using primers listed in 11 To focus on variants more likely to impart a functional effect associated with acute leukemia, we identified 126 ALL-associated genes and 655 AML-associated genes within the COSMIC database. From these candidate genes, we tabulated the number of congenital variants that were rare, non-synonymous and predicted deleterious. We found an average of 12 variants per ALL patient in the 126 ALL-associated genes and 163 variants per AML patient in the 655 AML-associated genes, both values exceeded the averages of 6 and 132 observed in ALL and AML mothers, respectively, as well as the 2 and 28 observed in controls (R2=0.21 (ALL) and 0.15 (AML). Given the unexpectedly large numbers of variants identified in candidate genes, infants were tested for an enrichment of variation in candidate genes using a hypergeometric test , we performed a randomization test wherein the same total number of genes that were variant in our samples (7808 in ALL and 8422 in AML) was selected at random from each subgroup of IL patients and the number of genes per random sampling that were found on the COSMIC candidate gene lists was recorded . We repeall genes for compound heterozygotes, where a gene must show ⩾2 rare, non-synonymous and deleterious variants with ⩾1 seen in the matching mother and ⩾1 variant that was non-maternal. We found that every AML infant was a compound heterozygote for only two genes: MLL3 and ANKRD36. ANKRD36 (ankyrin repeat domain 36) was not a leukemia candidate gene and has not been previously associated to leukemia, albeit multiple carcinomas with somatic mutations have been identified in COSMIC. We focused on MLL3 because it was in our AML-candidate gene list and owing to its direct connection to leukemia. Interestingly, despite the fact that MLL3 was not on our ALL-candidate gene list, we found that 50% of infants with ALL were also compound heterozygotes. Within MLL3, we identified nine stop gain variants  compound heterozygous genes and (b) genes that were the most commonly variant across all patients. We surveyed variants . Six of  infants . We foun22 neither of these mechanisms appears sufficient to account for the incidence of IL, and genome-sequencing results from MLL+ infant ALL reported exceptionally few somatic mutations in these three classes of genes.12 One category of genetic variation that has not been deeply explored in these patients is rare germline variants. The aptly named model of ‘clan genomics' by Lupski and colleagues21 posits that combinations of rare and private alleles, in the right genomic context, can combine to exert profound, but variable, influence on complex phenotypes. Considering this model, we hypothesized that profiles of rare, coding germline variation may comprise some proportion of the expected functional variation typically observed in cancer, but as of yet, not observed in IL under a model of somatic mutation. Under this model, each parent possesses a partial profile of variation, individually insufficient to significantly increase cancer risk, but through random segregation these alleles align in an offspring and result in the right context to significantly increase that child's risk of early leukemogenesis. A recent genome-wide association study found support for an additive model of common variants influencing standard-risk pediatric ALL and proposed that additional low-risk and very rare variants are likely to be present and exerting substantial effects on ALL risk.27 The Rare Variant Hypothesis posits that a singular complex phenotype may demonstrate a wide variety of functionally significant genetic variants in critical genes or metabolic pathways.28 Support for this hypothesis is provided by recent studies asserting that genetic variance for complex traits is mostly additive in nature.29 These congenital profiles of variation may consist of very rare variants of strong effect that may be augmented or modulated by additional low-risk variants, which is consistent with reports describing how multiple functional variants are required for a normal cell to undergo malignant transformation.30Clearly, a critical component of IL etiology remains undiscovered. The search for these additional insults has been ongoing for decades and has mainly focused on the acquisition of additional somatic mutations within the pre-leukemic clones due either to (a) enhanced mechanisms of mutagenesis from the initial genetic defect or (b) environmental exposures to toxins that promote DNA mutation. Assuming that the typical cancer requires 2–8 mutation in genes regulating cell fate, cell survival and/or genome maintenance,MLL+ IL has been intensively studied, there are few studies of MLL− IL and none simultaneously characterizing large-scale maternal sequencing. To our knowledge, this is the largest sequencing survey of MLL− IL. In exome sequencing of non-cancer DNA from matched mothers and their infants who developed acute leukemia, we find a statistically significant excess of rare, non-synonymous and predicted deleterious sequence variants in genes already known to be mutated in hematologic malignancies in the COSMIC database. In addition, mothers demonstrated enrichment in candidate gene variation over the control population supporting the interpretation that the observed enrichment in infants is a chance occurrence resulting from the independent segregation of multiple rare variants inherited from each parent, who individually possess a lesser enrichment of variation in the genes in question. Therefore, consistent with existing models of carcinogenesis,29 leukemia can only arise after a discrete threshold of deleterious functional variation is surpassed, whether inherited or acquired. Because paternal, sibling and patient leukemia DNA were unavailable in the AE24 study, our ability to distinguish inherited variation versus de novo mutation, identify potentially more penetrant combinations of inherited variants and correlate these patterns with the presence of any somatic mutation is limited. However, the patients in our survey were part of an epidemiologic study that failed to identify significant in utero exposures accounting for their IL.17 A recent review of de novo mutation rates in autistic spectrum disorders reports that only one de novo mutation per exome is observed in cases that are significantly enriched for de novo mutations.31 Thus, although we cannot distinguish paternal variation from de novo mutations, elevated rates of de novo mutation are insufficient to account for the overall enrichment of variation in candidate genes we have identified in this survey. Despite these limitations, our results continue to support our hypothesis that these infants possess germline variability in leukemia-associated genes and pathways that may reduce the amount of functional somatic mutation typically observed in other cancers.Although 22 This model of germline variation influencing leukemogenesis could explain the short latency that has proven difficult to replicate in animal models given an entirely different profile of background variation. The model would not exclude potential leukemogenic effects of topoisomerase II inhibitor exposure, although this has only been associated with MLL+ IL, and would also be consistent with the lack of heritability observed within pedigrees if cosegregation of many alleles were necessary to predispose to malignancy. A recent Brazilian study of leukemia in children younger than 2 years found a statistically significant increase in adjusted odds ratios of 1.66 for infants with ALL and a near-significant increase of 1.54 for AML when any second-degree relative had cancer, supporting the conclusion of more subtle familial genetic susceptibility in IL.32 Interestingly, the odds ratios increased significantly when the children's father had any cancer (1.80 ALL and 2.34 AML), but no such significant increase was observed when mothers had cancer.Given the large number of variants observed, particularly in AML patients, we are not suggesting that every variant identified is involved in leukemogenesis nor that acquired chromosomal rearrangements or somatic mutations are irrelevant. We are providing evidence that these infants harbor an abundance of congenital and putatively functional variation that may drive or modulate early leukemogenesis. 33 is useful to describe the exceptionally high rate of leukemia concordance for monochorionic twins who share intra-placental anastomoses. The blood-borne nature of these hematologic malignancies would also explain why other pediatric cancer types do not show similarly high concordance in monozygotic, monochorionic twins.34 However, the majority of twins are dichorionic, and approximately 8% demonstrate blood group chimerism because of placental fusion allowing blood exchange.35 Despite this frequency and multiple reports of twin–twin transfusion syndrome in dichorionic twins,41 we found only one report of concordant IL in dichorionic twins because of the leukemia clone passing between infants, not through inter-placental anastomosis, but through the maternal circulation and not resulting in leukemia in the mother, only the other twin.42 Although discordant IL in monozygotic twins is rare, Brown and colleagues documented the apparent spontaneous resolution, potentially through an immune-mediated process, of a MLL-ENL+ clone from a co-twin of an affected twin.43 These observations further support the conclusion that these circulating leukemic clones require additional factors in order to proliferate.Additive germline variation could also explain the very high concordance observed in monochorionic twins as both would have the same profile of inherited genetic variation, as well as the relative lack of disease concordance between dichorionic twins despite an 8% incidence of shared placental circulation. The ‘intraplacental metastasis hypothesis'MLL3, a homolog of MLL, maps to 7q36, which is a chromosomal region often deleted in myeloid leukemias.44 Like its MLL family members, MLL3 is a H3K4 histone methyltransferase that regulates gene expression through the FYR and SET domains.45 We identified nine rare or novel germline frameshift insertions that introduces a premature stop codon truncating the C-terminal FYR-N, FYR-C and SET domains (HOX), critical for embryogenesis and development.46MLL3 has not been previously linked to IL, but has been associated with a variety of solid tumors and did show an enrichment of mutations in adult AML patients48 and germline MLL3 variation was recently reported in a pedigree with adult-onset AML and colorectal cancer.49 In addition to MLL3, TTN was frequently variable in these patients' germline and has been previously found to carry somatic mutation and germline variation in multiple cancer types.50 Although best studied during embyonal cardiac development during mesoderm differentiation between heart and blood, TTN has also been shown to be required for proper chromosome packaging and remodeling during cell division.51 It is reasonable to hypothesize that aberrant chromatin remodeling, either through dysfunctional MLL3 alone or in concert with dysfunctional TTN during embryonal mesodermal differentiation, may have a crucial role in the etiology of IL in these MLL− cases. domains  necessarMLL− IL. Future work will focus on additional sequencing of nuclear family pedigrees with an affected infant to further refine the candidate genes influencing leukemogenesis, as well as functional analyses in patient-derived myeloid precursors of profiles of additive variation in the context of MLL3 and TTN dysfunction within iPSC-based in vitro and in vivo model systems.These data raise interesting new insights into the genetic architecture of


Silent cerebral events (SCE) have been identified on magnetic resonance imaging (MRI) in asymptomatic patients after atrial fibrillation (AF) ablation. Procedural determinants influencing the risk for SCE still remain unclear.Comparing the risk for SCE depending on exchanges of catheters (ExCath) over a single transseptal sheath.88 Patients undergoing pulmonary vein isolation (PVI) only ablation using either single-tip or balloon-based technique underwent pre- and post-ablation cerebral MRI. Ablations were either performed with double transseptal access and without exchanging catheters over the transseptal sheaths (group 1: no ExCath) or after a single transseptal access and exchanges of therapeutic and diagnostic catheters (group 2: ExCath). Differences in regard to SCE rates were analyzed. Multivariate analysis was performed to identify factors related to the risk for SCE.Included patients underwent PVI using single tip irrigated radiofrequency in 41, endoscopic laser balloon in 27 and cryoballoon in 20 cases. Overall SCE were identified in 23 (26%) patients. In group 1  6 patients (13%) and in group 2 (N=42) 17 patients (40%) had documented SCE (p=0.007). The applied ablation technology did not affect SCE rate. In multivariate analysis age  and catheter exchanges over a single transseptal sheath  were the only independent predictors of a higher risk for SCE.Exchanging catheters over a single transseptal access to perform left atrial ablation is associated with a significantly higher incidence of SCE compared to an ablation technique using different transseptal accesses for therapeutic and diagnostic catheters. Cerebral infarction is a rare but devastating complication of ablation procedures to treat atrial fibrillation (AF). But symptomatic cerebral ischemia may only be the tip of the iceberg as recent studies have identified cerebral lesions in asymptomatic patients after pulmonary vein isolation (PVI) undergoing post-ablation brain magnetic resonance imaging (MRI) -4. IncidPatients were eligible if undergoing pulmonary vein isolation (PVI) alone for paroxysmal or short-lasting persistent AF (< 3 months sustained AF) using either single-tip radiofrequency ablation (RF) or balloon-based technologies  and if willing and able to undergo cerebral MRI. Patients were categorized as either having paroxysmal or persistent AF based on current guidelines. All patients underwent MRI scanning one day before and 1 to 4 days after PVI. Baseline and procedural patient data was collected including procedure duration (from puncture to sheaths out), total ablation duration, minimal and mean procedural activated clotting time (ACT), periprocedural anticoagulation management , echocardiographic evaluation , intraprocedural cardioversion or occurrence or persistence of AF.All patients were off anticoagulation at the day of the procedure and were bridged using low-molecular weight heparin . Warfarin medication or novel oral anticoagulants were administered on day 1 after the ablation procedure if access site was clinically blunt.All patients gave informed consent and procedures were performed after exclusion of intracardiac thrombus using transesophageal imaging. Procedures were performed under conscious sedation using propofol and via transseptal access to the left atrium in standard technique.In both groups ablations were started only after the ACT reached ≥ 300sec. Intraprocedurally, ACTs were controlled every 20 minutes for the course of the procedure. Minimum ACT was documented for each procedure. All transseptal sheaths were flushed continuously with a rate of 150ml/hr. In cases with exchanges of catheters over a single transseptal sheath blood was aspired after taking catheters out and high-volume flushed 999ml/hr) until the next catheter was introduced. Care was taken to avoid any introduction of air into the transseptal apparatus. Ablation procedures were performed using 3 different technologies as previously described ,9,11. Pa99ml/hr uA neurological evaluation by board-certified neurologists was performed the day of post-ablation MRI. In all cases only PVI was performed and no additional left atrial ablations were performed.1. Irrigated tip radiofrequency (irrRF) ablation was performed using CARTO3  or NavX  electroanatomic mapping system. Either single transseptal access  or double transseptal access  was performed. The circular diagnostic PV mapping catheter was used to create a 3-dimensional shell of the left atrium and prior computed tomography images were integrated by merging. In all cases a steerable transseptal sheath  was used for the ablation catheter and isolation of the ipsilateral PVs was performed en-block in a point-by-point fashion. Ablation was performed using a maximum of 35Watts with a target temperature of 43ºC and a maximum irrigation rate of 30ml/min.2. Ablation using the HeartLight™ Endoscopic Ablation system (EAS)  was performed after either a single or a double transseptal access. A CMC was used to confirm bidirectional PV block . Endoscopically assisted laser-balloon ablations for PVI were performed as previously described -13. Abla3. The ArcticFront™  cryo-balloon (CB) was used for PVI. A single or double transseptal access  was performed and either a CMC was used for pre- and post-ablation evaluation (as an exchange of catheters or over two distinct accesses) or the Achieve™  catheter was used as a guide-wire for the CB catheter and for diagnosis of PV-block (no exchange of catheters). At each PV at least two freezes lasting 300 seconds were carried out. In case of usage of the Achieve™ online monitoring of PV conduction was possible and further CB applications were performed directly if persistent PV conduction was found. If a single transseptal approach using a conventional circular mapping catheter was carried out, PV conduction was tested after performing 2 CB applications in each PV and the catheters had been exchanged. Further CB applications were performed if persistent PV conduction was found after exchanging the catheters again. No additional focal touch up ablations were performed.Group 1: No exchange of catheters (no ExCath) was defined as two transseptal accesses using two distinct transseptal sheaths for the CMC and the ablation device  or if the Achieve™ catheter was used through the inner lumen of the CB.Group 2: Exchange of catheters over a single transseptal sheath (ExCath) was defined as exchanging CMC and ablation device at least twice (CMC before and after ablation).In all patients the endpoint of PVI was confirmed as bidirectional PV block including entrance block  and exit block .MRI scans were independently evaluated by two board-certified radiologists experienced in the diagnosis of brain MRI scans blinded for the ablation technology used.3, flip angle 150º) and a transaxial diffusion-weighted echo-planar imaging (DWI) sequence . For each DWI sequence, the apparent diffusion coefficient (ADC) map was obtained. Additionally, a sagital T1-weighted spin-echo sequence  was acquired for assessing brain anatomy and for ruling out haemorrhaging conversion of the SCEs.Brain MRI was 1 to 3 days after ablation and during follow-up using a 1.5-T scanner . The imaging protocol for all images consisted of a transaxial T2-weighted, fluid-attenuated inversion recovery (FLAIR) sequence  for non-normally distributed data or percentages. Depending from the class of analyzed data and possible direction of causality, distributions were compared by means of multivariate logistic regression with forward selection, two sample t-test, Wilcoxons rank sum test or Pearson's Chi-squared test with Yates' continuity correction. For multivariate logistic regression variables were selected that differed with p<0.1 in a-priori Chi-squared test or Wilcoxons test and that did not correlate to procedure, respectively. A two-tailed p value of <0.05 was considered statistically significant in all tests.A total of 88 patients were included  during the study period. 46 patients were ablated without exchange of catheters over a single transseptal sheath  and 42 with  (baseline patient characteristics see Brain MRI was performed at a median of 1 day after the procedure (1 to 4 days). 2 (2%) patients had old lacunar infarction and 35 (40%) had unspecific white matter lesions and glial scarring identified as leucencephalopathy.No patient had new-onset neurological symptoms indicative of cerebral ischemia after the procedure. 23 patients (26%) had documented SCE (8 (20%) patients treated with IrrRF, 10 (37%) with EAS and 5 (25%) with CB). Overall 51 SCEs were identified , 41 (80%) were 3mm or less in diameter, 9 (18%) in between 4 to 10mm and 1 (2%) was larger than 10mm in diameter see .Baseline and procedural characteristics in relation to ExCath are displayed in Incidence of SCE was significantly higher in group 2 patients  compared to those group 1  (p=0.004) . Also, nComparative analysis of baseline characteristics is shown in Patients with SCE compared to those without were significantly older  and significantly more often ExCath was performed .No difference in any other tested variable was identified comparing patients with and without SCE .Comparing incidence of SCE and number of SCE/pt in between different ablation technologies did not reveal significant differences: The incidence of SCE was 20% in IrrRF (8 out of 41), 30% in CB (6 out of 20) and 37% in EAS (10/27) patients  .In the multivariate analysis  only ageIn multivariate analysis mode of ablation  did not affect SCE incidence.The presented data indicates that exchanging catheters over a single transseptal sheath during left atrial ablations significantly influence the risk for acute SCE identified on post-ablation MRI. In addition, age was also associated (but not as strong) with an increased risk for SCE.We identified a significantly higher incidence of SCE in patients with catheter exchanges over the transseptal sheath of 40% compared to 13% in the group of patients ablated without catheter exchanges. ExCath over a single transseptal sheath in our analysis was the strongest predictor for SCE associated with a 3.1-imes increased risk. Introducing and withdrawing a catheter over the transseptal sheath may lead to introduction of gas or thrombotic debris from within the transseptal sheath or the catheter. In addition, ExCath over a single transseptal sheath may influence the patency of the sheath's valve and may then lead to introduction of small air bubbles. In patients undergoing either single-tip irrRF ablation or balloon-based PVI the technique may include either having two transseptal sheaths (one for the ablation device and one for the circular mapping catheter) or only a single transseptal sheath with the need for exchanging diagnostic and therapeutic catheters. Further studies are needed to identify e.g. the number of exchanges that may be detrimental or may identify differences in between transsseptal sheath designs or size. In our study catheter exchanges were performed at least twice in group 2 patients. ExCath over a single transseptal sheath should be avoided in order to reduce the incidence of SCE.Predictors, so far identified to impact SCE rates, are intraprocedural ACT ,5,6, intRecently a study on phased RF ablation using the PVAC catheters indicated that subtle changes of the procedural steps lead to a dramatic reduction in FLAIR-positive silent cerebral lesions . FurtherSCE detected on cerebral MRI have been identified as a potential embolic complication of left atrial ablation procedures. Incidence of detected SCE depends upon MRI technique and definition used. In our study we used a more sensitive ("new") definition of SCE characterized only by a hyperintensity on DWI-MRI and corresponding hypointense lesion on ADC-map. In contrast to other (earlier) studies we have not included the FLAIR sequence, which may misclassify some DWI hyperintense lesions as negative due to the timeline of FLAIR becoming positive . This may lead to undertection of  silent cerebral events in up to 2/3 of lesions . SchmidtIn summary, using a more sensitive MRI definition more patients with SCE are detected (higher incidences) and differences between technologies appear to be less pronounced.So far, the exact mechanism of SCE generation remains unclear. Recent animal studies indicate that silent cerebral lesions usually dissolved on MRI within 4 days after occurrence although glial scar formation was detected on histopathology. Lesions detected on DWI and FLAIR in this study appear to present small asymptomatic strokes. The incidence of SCE may serve as a surrogate parameter for the embolic load of different left atrial ablation technologies and techniques. Whether different sizes of SCE represent different mechanisms (e.g. gaseous versus thrombotic embolism) and why and if lesions really remain asymptomatic using high precision neuropsychological testing needs to be further elucidated. So far no study has identified potential clinical sequel related to post-ablation SCE and their small number and size needs to be weighted against the high incidence and number of pre-existing white matter lesions related to the process of AF.The present study evaluates SCE rates related to intraprocedural exchanges of left atrial catheters over a single transseptal sheath using a sensitive methodology. Although many baseline and procedural characteristics have been evaluated, other - so far unknown - factors may also play a role or may only become visible in larger patient population.The number of exchanges of catheters over a single transseptal sheath and different sheath designs were not evaluated and further studies need to identify potential differences in regard to the sheath or technology used. It may be speculated that mismatches between catheter sizes and sheath diameter may also impact the risk for SCE.Furthermore, the effect of continued anticoagulation or novel oral anticoagulant during left atrial ablation was not studied in the present evaluation. Recent data indicates relevant differences in SCE incidences in between patients ablated on continued oral anticoagulation versus other protocols . This was not tested in the present study using a prespecified periprocedural anticoagulation protocol.Risk for SCE appears to be multifactorial: As a new but modifiable determinant we identified exchanges of catheters over a single transseptal sheath as a strong factor involving a higher risk for SCE. When using two different catheters for PVI diagnostics and ablation different accesses (sheaths) should be used to reduce SCE rates.SCE rates may serve as an indicator for the embolic risk of a left atrial ablation technology or procedure. Procedural and technological changes to minimize the incidence of SCE should be attempted.


Ebola virus (EBOV) is a highly pathogenic filovirus that causes hemorrhagic fever in humans and animals. Currently, how EBOV fuses its envelope membrane within an endosomal membrane to cause infection is poorly understood. We successfully measure cell-cell fusion mediated by the EBOV fusion protein, GP, assayed by the transfer of both cytoplasmic and membrane dyes. A small molecule fusion inhibitor, a neutralizing antibody, as well as mutations in EBOV GP known to reduce viral infection, all greatly reduce fusion. By monitoring redistribution of small aqueous dyes between cells and by electrical capacitance measurements, we discovered that EBOV GP-mediated fusion pores do not readily enlarge—a marked difference from the behavior of other viral fusion proteins. EBOV GP must be cleaved by late endosome-resident cathepsins B or L in order to become fusion-competent. Cleavage of cell surface-expressed GP appears to occur in endosomes, as evidenced by the fusion block imposed by cathepsin inhibitors, agents that raise endosomal pH, or an inhibitor of anterograde trafficking. Treating effector cells with a recombinant soluble cathepsin B or thermolysin, which cleaves GP into an active form, increases the extent of fusion, suggesting that a fraction of surface-expressed GP is not cleaved. Whereas the rate of fusion is increased by a brief exposure to acidic pH, fusion does occur at neutral pH. Importantly, the extent of fusion is independent of external pH in experiments in which cathepsin activity is blocked and EBOV GP is cleaved by thermolysin. These results imply that low pH promotes fusion through the well-known pH-dependent activity of cathepsins; fusion induced by cleaved EBOV GP is a process that is fundamentally independent of pH. The cell-cell fusion system has revealed some previously unappreciated features of EBOV entry, which could not be readily elucidated in the context of endosomal entry. The devastation and transmissibility of Ebola virus (EBOV) are well known. However, the manner in which EBOV enters host cells through endosomal membrane remains elusive. Here, we have developed a convenient experimental system to mimic EBOV fusion in endosomes: cells expressing the fusion protein of EBOV, GP, on their surface are fused to target cells. This system exhibits the known key properties of EBOV fusion. We show that the pH-dependence of EBOV fusion is caused by the pH-dependence of cathepsins, proteases known to cleave EBOV GP into a fusion-competent form. We demonstrate that the fusion activity of this cleaved form is independent of pH. We further show that the enlargement of the fusion pore created by EBOV GP is unusually slow in reaching sizes necessary to pass EBOV’s genome—this is atypical of virally created fusion pores. This cell-cell fusion system should provide a useful platform for developing drugs against EBOV infection. Ebola virus (EBOV) outbreaks continually occur and up to 90% of those infected die; currently there are no approved vaccines or antiviral therapeutics against the virus ,2. EBOV EBOV GP is a prototypic class I viral fusion protein . It is sAfter developing our system, we discovered that an EBOV GP-induced fusion pore that connects two plasma membranes does not readily enlarge over time, in contrast to the pores of other viral fusion proteins. This anomalous lack of growth may be the reason cell-cell fusion has not been successfully observed in many prior attempts that used less sensitive assays to detect fusion.On the question of low pH, we found that activation of cathepsins by acidity is the sole cause for augmentation of fusion: if EBOV GP on the cell surface is artificially cleaved by thermolysin in the presence of cathepsin inhibitors, the extent of fusion is independent of pH.We utilize fluorescent dye spread assays to monitor cell-cell fusion. Effector COS7 cells transfected to express EBOV GP were loaded with calcein-AM  and pretreated with thermolysin (Th) and. It has been shown that thermolysin treatment cleaves GP1 on the viral membrane into a fusion-competent 18–19 kDa subunit ,24. WithIt is often thought that EBOV fusion requires acidic pH ,25,27. BThe observed differences in extents of fusion between cells that were treated with thermolysin and those not were eliminated by long times of incubation after reneutralization . When EBNPC1 is an intracellular receptor for EBOV GP ,33. We cNPC1 is an endosomal protein , but a sfurin), the putative cleavage site for CatL in GP1 -10 mM HEPES (pH 7.2). To electrically characterize fusion pores created by IAV HA, ASLV Env, and HIV Env, we used cell lines that stably express the fusion protein and target cells that stably express the cognate receptor: HAb2 cells that express IAV HA as effectors and 293T cells as targets [Pore size over time was also quantified by using patch clamp time-resolved admittance measurements , often r targets ; NIH 3T3 targets ,67; and Pair-wise Student t-tests were used to compare the outcome of a manipulation on fusion as compared to the control. In figures, unless otherwise indicated, a single asterisk (*) denotes p < 0.05, two asterisks (**) denotes p < 0.01, and three asterisks (***) denotes p < 0.001.S1 TextConsequences of membrane trafficking of EBOV GP on cell-cell fusion.(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(A) The periods in which proteinase K  was present are marked in the schematic protocol, and numbers correspond to bar numbers below. Regardless of whether PK was present prior (bar 2) or subsequent (bar 3) to treating effector cells with thermolysin, the presence of PK virtually eliminated fusion. Similarly, adding and then maintaining PK to effector cells as they were bound with target cells led to greatly reduced fusion (bar 4). But adding PK immediately after the low pH pulse (bar 5) hardly affected fusion. (B) EBOV GP-mediated fusion recovered over time after proteinase K treatment: Left-hand bars of each pair denote that a pH pulse was not applied; a pH 5.7 pulse was applied for the right hand bars. Adding proteinase K and washing out immediately prior to thermolysin treatment virtually abolished fusion (first set of two bars). Allowing 2 hr between proteinase K removal and thermolysin treatment restored most of the fusion (second set of bars). Waiting 3 h completely restored fusion (third set of bars).(TIF)Click here for additional data file.S3 Fig(A) Immunostaining showed that mock-transfected cells did not react with the antibody. (B) Cells transfected with EBOV GP did show significant staining (upper right images). (C) The staining protocol was used without delay after treating cells with PK. (D) Maintaining the cells for 3 h in DMEM at 37°C before immunostaining. (E) The effect of PK treatment on EBOV GP expression was assessed using Volocity imaging software (Perkin Elmer). Integral fluorescence per field (3 image fields per datum point) was calculated after subtracting the fluorescence background determined from the mock-transfected images. This quantification shows that expression of EBOV GP was greatly reduced by the proteinase K treatment and significantly recovered after the protease was absent for 3 h. This demonstrates that the EBOV GP expression levels were steady over time.Left hand panels of each pair show confocal images of FITC fluorescence alone; right hand panels show fluorescence and cells in differential interference contrast. An anti-EBOV GP antibody (KZ52) was used for staining EBOV GP. A secondary FITC-labeled antibody was used to immunostain. (TIF)Click here for additional data file.S4 FigThe presence of Brefeldin A  at all points of the fusion protocol that utilizes thermolysin-treated effector cells and a pH 5.7 pulse reduced fusion greatly (bar 2) compared to the control . Washing out BFA and immediately treating effector cells with thermolysin led to greater fusion (bar 3). Waiting 30 min after the washout before thermolysin treatment led to fusion (bar 4) comparable to control. Adding and maintaining BFA after binding effector and target cells, but before applying a low pH pulse led to substantially reduced fusion (bar 5). Applying BFA after the low pH pulse led to less fusion than the control (bar 1), but to greater fusion than when the drug was added prior to the low pH pulse . Thermolysin was used to cleave EBOV GP just prior to measuring fusion for all conditions of, allowing meaningful comparisons.(TIF)Click here for additional data file.