Prevalence of non-reversion and reversion mutations in complex biosynthetic metabolic pathways.

<p>Reversion (A) and non-reversion mutations (B) identified in protein sequences from all MRSA isolates exposed to drug treatment were mapped by homology to the <i>Staphylococcus aureus</i> metabolome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056466#pone.0056466-AubryDamon1" target="_blank">[31]</a> (mutations in compounds acting in Nucleoside/nucleotide Biosynthesis (A, orange) and Amino Acid Biosynthesis (B, red) are shown). Compounds accumulating mutations interact in complex pathway networks that involve highly conserved proteins (solid lines) as well as “pathway-holes” (light grey lines) where identified sequence or functional homologs have not yet been identified in the <i>Staphylococcus aureus</i> genomes. The propensity of different mutant types to accumulate in distinct biological pathways, and significant correlation of reversions arising in strains exposed to daptomycin, is suggestive of how exposure to different drugs likely presents evolutionary adaptation biases in metabolic regulation in order to minimize fitness cost while promoting the progression of antibiotic resistance.</p

Estimation of the accuracy of predicting RAMs using three methods.

<p>The accuracy statistics of three methods in predicting StaphRAMs (A–C) is compared to the known accuracy of the same methods for predicting Human DAMs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056466#pone.0056466-Lopes1" target="_blank">[21]</a> (D) Maximum likelihood estimation of a binormal ROC curve with an asymmetric 95% confidence interval using 3 methods of prediction (B), with CAROL predictions representing the strongest evidence of a damaging prediction (C). The area of the ROC curve is 0.63 with a standard deviation of 0.06. Accuracy, sensitivity, and specificity were estimated to be 62.6%, 94.0% and 38.5% respectively. Red and blue represent the fitted ROC curve (B). Grey lines denote the 95% confidence interval of the fitted ROC curve (B). A boxplot of the spread estimate for all three methods is shown and ROCR curves for each method are colorized according to the prediction cutoffs (C).</p

SupportingInformationS3

S3. Rooted maximum parsimony tree of C. burnetii MST genotypes (1-34 and Dugway) after Hornstra et al. (Hornstra, Priestley, et al. 2011). Whole genome sequences are mapped onto the tree and the major genomic groups of C. burnetii are identified

Supplementary Information S1

S1. SNP matrix of 11,286 orthologous SNPs discovered among ten C. burnetii genomes

A Multidisciplinary Biospecimen Bank of Renal Cell Carcinomas Compatible with Discovery Platforms at Mayo Clinic, Scottsdale, Arizona

<div><p>To address the need to study frozen clinical specimens using next-generation RNA, DNA, chromatin immunoprecipitation (ChIP) sequencing and protein analyses, we developed a biobank work flow to prospectively collect biospecimens from patients with renal cell carcinoma (RCC). We describe our standard operating procedures and work flow to annotate pathologic results and clinical outcomes. We report quality control outcomes and nucleic acid yields of our RCC submissions (N=16) to The Cancer Genome Atlas (TCGA) project, as well as newer discovery platforms, by describing mass spectrometry analysis of albumin oxidation in plasma and 6 ChIP sequencing libraries generated from nephrectomy specimens after histone H3 lysine 36 trimethylation (H3K36me3) immunoprecipitation. From June 1, 2010, through January 1, 2013, we enrolled 328 patients with RCC. Our mean (SD) TCGA RNA integrity numbers (RINs) were 8.1 (0.8) for papillary RCC, with a 12.5% overall rate of sample disqualification for RIN <7. Banked plasma had significantly less albumin oxidation (by mass spectrometry analysis) than plasma kept at 25°C (<i>P</i><.001). For ChIP sequencing, the FastQC score for average read quality was at least 30 for 91% to 95% of paired-end reads. In parallel, we analyzed frozen tissue by RNA sequencing; after genome alignment, only 0.2% to 0.4% of total reads failed the default quality check steps of Bowtie2, which was comparable to the disqualification ratio (0.1%) of the 786-O RCC cell line that was prepared under optimal RNA isolation conditions. The overall correlation coefficients for gene expression between Mayo Clinic vs TCGA tissues ranged from 0.75 to 0.82. These data support the generation of high-quality nucleic acids for genomic analyses from banked RCC. Importantly, the protocol does not interfere with routine clinical care. Collections over defined time points during disease treatment further enhance collaborative efforts to integrate genomic information with outcomes.</p></div

Whole Genome Analyses of a Well-Differentiated Liposarcoma Reveals Novel <i>SYT1</i> and <i>DDR2</i> Rearrangements

<div><p>Liposarcoma is the most common soft tissue sarcoma, but little is known about the genomic basis of this disease. Given the low cell content of this tumor type, we utilized flow cytometry to isolate the diploid normal and aneuploid tumor populations from a well-differentiated liposarcoma prior to array comparative genomic hybridization and whole genome sequencing. This work revealed massive highly focal amplifications throughout the aneuploid tumor genome including <i>MDM2</i>, a gene that has previously been found to be amplified in well-differentiated liposarcoma. Structural analysis revealed massive rearrangement of chromosome 12 and 11 gene fusions, some of which may be part of double minute chromosomes commonly present in well-differentiated liposarcoma. We identified a hotspot of genomic instability localized to a region of chromosome 12 that includes a highly conserved, putative L1 retrotransposon element, LOC100507498 which resides within a gene cluster (<i>NAV3</i>, <i>SYT1</i>, <i>PAWR</i>) where 6 of the 11 fusion events occurred. Interestingly, a potential gene fusion was also identified in amplified <i>DDR2</i>, which is a potential therapeutic target of kinase inhibitors such as dastinib, that are not routinely used in the treatment of patients with liposarcoma. Furthermore, 7 somatic, damaging single nucleotide variants have also been identified, including D125N in the PTPRQ protein. In conclusion, this work is the first to report the entire genome of a well-differentiated liposarcoma with novel chromosomal rearrangements associated with amplification of therapeutically targetable genes such as <i>MDM2</i> and <i>DDR2</i>.</p></div

Quality Assessment of Chromatin Immunoprecipitation Coupled With High-throughput Sequkencing.

<p>A, First end-read and, B, second end-read average quality score per base pair (bp) position assessment using FastQC. Higher scores correspond to better base calls. C, Box plots of enrichment of H3K36me3 immunoprecipitation (IP; red) over the matched control input library (Input; green). The human genome was split into 500-bp nonoverlapping windows, and the number of mapped pairs per window was calculated using BEDTools and normalized to a library size of 10 million uniquely mapped reads. The plots represent the top 5% of the 500-bp windows with the highe st counts in IP and the corresponding windows in input. D, Gene-body coverage by H3K36me3-binding sites. H3K36me3-binding sites identified by SICER (Spatial Clustering for Identification of ChIP-Enriched Regions) were intersected with gene coordinates to calculate the gene-body coverage (y-axis). On the x-axis, 1 to 22 represents chromosomes 1 to 22; 23 represents the X chromosome; and 24 represents the Y chromosome. ccRCC1 indicates clear cell renal cell carcinoma 1; ccRCC2, clear cell renal cell carcinoma 2; ccRCC3, clear cell renal cell carcinoma 3; Uninv., uninvolved.</p

Comparison of Mapped Reads Between the Mayo Clinic and TCGA Nephrectomy Samples.

<p>Abbreviation: TCGA, The Cancer Genome Atlas.</p><p>Comparison of Mapped Reads Between the Mayo Clinic and TCGA Nephrectomy Samples.</p

Depiction of genomic rearrangement hotspot on chromosome 12.

<p>We identified and further characterized a putative transposable element (LOC100507498) located on the (-) strand, within the PAWR-SYT1-NAV3 gene cluster (<b>3A</b>). The LOC100507498 and closely related sequences were characterized by comparing both nucleotide (<b>3B</b>,top) and translated (<b>3B</b>,bottom) sequences to known families of repetitive elements (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#s2" target="_blank">Methods</a>). Highly conserved sequence domains/motifs are color coded by known families of repetitive elements (Legend). Overall, these sequences exhibited the highest similarity to the L1 retrotransposon and Alu repeat elements (domain hit counts and similarity score). Sequence alignments of LOC100507498 (*) with known L1 elements <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#pone.0087113-Pickeral1" target="_blank">[32]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#pone.0087113-Goodier1" target="_blank">[33]</a> exhibited the highest overall homology to Class 3 L1 elements as described by Pickeral et al. (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#pone-0087113-t001" target="_blank">Table 1</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#pone.0087113-Pickeral1" target="_blank">[32]</a>) and in addition to the 5′-GGAG and 3′-AATA signature motifs, LOC100507498 carries several ‘AATGTTTA’ motifs that suggest multiple rounds of L1-mediated transduction <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087113#pone.0087113-Goodier1" target="_blank">[33]</a>. The LOC100507498 locus resides within a genomic region that is deleted in the Tumor (T) sample, but present in the Normal (N) genome (<b>3C</b>).</p

DNA validated fusion genes.

<p>DNA validated fusion genes.</p