Additional file 1 of Circlator: automated circularization of genome assemblies using long sequencing reads

Supplementary text and figures supporting the main text. (PDF 803 kb

Additional file 2 of Circlator: automated circularization of genome assemblies using long sequencing reads

An Excel spreadsheet containing Tables S1–5 and S7. Table S1. NCTC project IDs and accession numbers for the PacBio bacterial samples Table S2. A complete breakdown of results on the PacBio bacterial samples (an expanded version of Table 1) Table S3. QUAST results on the PacBio bacterial samples Table S4. Results of testing user-defined parameters for all NCTC data sets Table S5. Results of testing user-defined parameters for the MinION data set Table S7. Run time and memory usage for all data sets (excluding those in Tables S4 and S5). (XLS 305 kb

Additional file 3 of Circlator: automated circularization of genome assemblies using long sequencing reads

A gzipped archive containing all scripts, corrected reads, assemblies, and other data necessary to reproduce the results. (gzipped archive 11GB

N-acetyltransferase 1*10 genotype in bladder cancer patients

<p>In a large bladder cancer study in the greater Berlin area with 425 cases and 343 controls, the haplotype <i>N-acetyltransferase 1*10</i> (<i>NAT1*10</i>) was associated with a decreased bladder cancer risk. In a recently published meta-analysis, results of the studies were found to be inconclusive. Therefore, the aim of this study was to investigate the frequency of <i>NAT1*10</i> in bladder cancer patients and controls recruited in an area without industries reported to be associated with increased bladder cancer risk. Rs1057126 (1088 T > A) and rs15561 (1095 C > A) were determined in 412 bladder cancer patients and 415 controls without a known history of malignancies. With these two single-nucleotide polymorphisms (SNP), it was possible to distinguish between <i>NAT1*4</i> (wild type), <i>NAT1*3</i> (1095 C > A), and <i>NAT1*10</i> (1088 T > A, 1095C > A). The frequencies of the determined NAT1 haplotypes did not differ markedly between cases and controls: <i>NAT1*4</i>: 74%, <i>NAT1*3</i>: 6%, <i>NAT1*10</i>: 20%. Bladder cancer risk was not significantly modulated by <i>NAT1*10/*10</i> (OR 1.03, 95% CI 0.71–1.48) but was higher for <i>NAT1*3/*3</i> genotypes (OR 2.05, 95% CI 1.32–3.21). In contrast to the Berlin study from 2001, data in present study demonstrated that <i>NAT1*10</i> haplotype was not associated with a significantly decreased bladder cancer risk. This may be due to local effects in the greater Berlin area, particularly at the time of investigation. The findings of the present study are in agreement with observations of a recently published meta-analysis which also showed no relevant impact of <i>NAT1*10</i> haplotype on bladder cancer risk. The impact of the rare <i>NAT1*3/*3</i> genotype was significant but this may be attributed to rarity without major practical relevance.</p

CJ200528120617_2

Additional file 3. Additional figure S1–S8

Protocol for a Randomized Phase II Trial for Mesh Optimization by Autologous Plasma Coating in Prolapse Repair – IDEAL Stage 3

<p><strong>Article full text</strong></p> <p><br> The full text of this article can be found <a href="https://link.springer.com/article/10.1007/s12325-017-0493-z"><b>here</b>.</a><br> <br> <strong>Provide enhanced digital features for this article</strong><br> If you are an author of this publication and would like to provide additional enhanced digital features for your article then please contact <u>[email protected]</u>.<br> <br> The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content.<br> <br> Other enhanced features include, but are not limited to:<br> • Slide decks<br> • Videos and animations<br> • Audio abstracts<br> • Audio slides<u></u></p

Comparison of DNA Methylation with Gene Expression

<p>Amplicons generated from prostate (yellow), lung (blue), and liver (green) samples were divided into two categories: “upstream” and “intragenic”. The median methylation values for the amplicons were calculated as described in the text, and these were then classified as hypomethylated (median methylation less than 50%) or hypermethylated (median methylation greater than 50%), and plotted against the cDNA microarray expression data available at <a href="http://expression.gnf.org" target="_blank">http://expression.gnf.org</a> (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020405#pbio-0020405-Su1" target="_blank">Su et al. 2002</a>). The expression values are expressed as average difference values (ADVs) for each gene. The average difference value is computed using Affymetrix software and is proportional to mRNA content in the sample, with a value of 200 being a conservative cut-off below which a gene can be classified as being not expressed. The average difference values are the mean of 2 or 3 independent experiments. For prostate and liver, the expression levels associated with the hypermethylated upstream amplicons were significantly lower than the expression levels associated with the hypomethylated upstream amplicons (<i>p</i> < 0.0001 for prostate and <i>p</i> < 0.01 for liver). For lung, there was no significant difference between the expression levels associated with the hypermethylated upstream amplicons and those of the hypomethylated upstream amplicons (<i>p</i> > 0.3). There was no correlation between expression and methylation for the intragenic amplicons for any of the three tissues (<i>p</i> > 0.3). The width of the bars is indicative of the number of amplicons in each category: prostate upstream, hypermethylated (<i>n</i> = 9); prostate upstream, hypomethylated (<i>n</i> = 15); prostate intragenic, hypermethylated (<i>n</i> = 109); prostate intragenic, hypomethylated (<i>n</i> = 53); liver upstream, hypermethylated (<i>n</i> = 9); liver upstream, hypomethylated (<i>n</i> = 14); liver intragenic, hypermethylated (<i>n</i> = 115); liver intragenic, hypomethylated (<i>n</i> = 45); lung upstream, hypermethylated (<i>n</i> = 9); lung upstream, hypomethylated (<i>n</i> = 13); lung intragenic, hypermethylated (<i>n</i> = 112); and lung intragenic, hypomethylated (<i>n</i> = 57).</p

Comparison of Methylation Values Measured in Five Tissues and Eleven Amplicons Using MALDI-MS and ESME Analysis of Directly Sequenced PCR Products

<p>Each column is a tissue sample, each row a CpG site. Data are ordered in blocks by tissue type and amplicons. Positions of measurements for MALDI-MS (A) correspond to those for ESME analysis (B). The methylation values are colour coded from 0% methylation (yellow) to 100% methylation (blue), with intermediate methylation levels represented by shades of green. White indicates missing measurement values.</p

The HEP Database

<div><p>(A) We have created a Web-based, ENSEMBL-like genome browser for displaying HEP data that is publicly available at <a href="http://www.epigenome.org" target="_blank">http://www.epigenome.org</a>. The methylation levels calculated by the ESME software are displayed in the form of a matrix. Each matrix contains the data obtained from all the samples of one amplicon. Each colour-coded square (yellow represents 0% methylation, blue represents 100% methylation, and green represents intermediate levels) within the matrix represents one CpG site. Clicking on a square reveals the tissue source of the sample and the level of methylation observed at that particular CpG site. Grey squares indicate CpG sites for which methylation levels could not be determined. Each row of squares represents all the CpG sites for one sample of a particular amplicon, and the samples are grouped by tissue type. The red bar indicates the genomic region analysed. Also shown are chromosome coordinates, CpG islands, SNPs, and ENSEMBL and high-quality, manually curated VEGA transcript information. The HEP database links to the Ensembl genome browser, providing additional information about the region of interest. The example shows amplicons within the <i>SynGAP 1</i> gene that correspond to regions that were determined to be hypomethylated (second amplicon from the left), hypermethylated (first and fifth amplicons), and heterogeneously methylated (fourth amplicon). Insufficient data were obtained for the third amplicon.</p> <p>(B) By using the zoom function, the user can view the complete DNA sequence for the analysed amplicon.</p></div

Example of METHANE Output Showing Regions That Display Inter-Individual Variation of Methylation Profiles

<div><p>(A) Example of a region that displays significant inter-individual variation, especially in prostate. The matrix represents an amplicon that contains 27 CpG sites within a 527-bp region overlapping the last exon of the <i>CYP21A2</i> gene.</p> <p>(B) Another example of a region that displays significant inter-individual variation. The matrix represents an amplicon that contains 13 CpG sites within a 453-bp region overlapping the 5′ UTR and exon 1 of the <i>tumour necrosis factor</i> gene.</p></div