Determination of quantitative and site-specific DNA methylation of perforin by pyrosequencing

<p>Abstract</p> <p>Background</p> <p>Differential expression of perforin (<it>PRF1</it>), a gene with a pivotal role in immune surveillance, can be attributed to differential methylation of CpG sites in its promoter region. A reproducible method for quantitative and CpG site-specific determination of perforin methylation is required for molecular epidemiologic studies of chronic diseases with immune dysfunction.</p> <p>Findings</p> <p>We developed a pyrosequencing based method to quantify site-specific methylation levels in 32 out of 34 CpG sites in the <it>PRF1 </it>promoter, and also compared methylation pattern in DNAs extracted from whole blood drawn into PAXgene blood DNA tubes (whole blood DNA) or DNA extracted from peripheral blood mononuclear cells (PBMC DNA) from the same normal subjects. Sodium bisulfite treatment of DNA and touchdown PCR were highly reproducible (coefficient of variation 1.63 to 2.18%) to preserve methylation information. Application of optimized pyrosequencing protocol to whole blood DNA revealed that methylation level varied along the promoter in normal subjects with extremely high methylation (mean 86%; range 82–92%) in the distal enhancer region (CpG sites 1–10), a variable methylation (range 49%–83%) in the methylation sensitive region (CpG sites 11–17), and a progressively declining methylation level (range 12%–80%) in the proximal promoter region (CpG sites 18–32) of <it>PRF1</it>. This pattern of methylation remained the same between whole blood and PBMC DNAs, but the absolute values of methylation in 30 out of 32 CpG sites differed significantly, with higher values for all CpG sites in the whole blood DNA.</p> <p>Conclusion</p> <p>This reproducible, site-specific and quantitative method for methylation determination of <it>PRF1 </it>based on pyrosequencing without cloning is well suited for large-scale molecular epidemiologic studies of diseases with immune dysfunction. PBMC DNA may be better suited than whole blood DNA for examining methylation levels in genes associated with immune function.</p

Gene expression profile of cervical tissue compared to exfoliated cells: Impact on biomarker discovery

BACKGROUND: Exfoliated cervical cells are used in cytology-based cancer screening and may also be a source for molecular biomarkers indicative of neoplastic changes in the underlying tissue. However, because of keratinization and terminal differentiation it is not clear that these cells have an mRNA profile representative of cervical tissue, and that the profile can distinguish the lesions targeted for early detection. RESULTS: We used whole genome microarrays (25,353 unique genes) to compare the transcription profiles from seven samples of normal exfoliated cells and one cervical tissue. We detected 10,158 genes in exfoliated cells, 14,544 in the tissue and 7320 genes in both samples. For both sample types the genes grouped into the same major gene ontology (GO) categories in the same order, with exfoliated cells, having on average 20% fewer genes in each category. We also compared microarray results of samples from women with cervical intraepithelial neoplasia grade 3 (CIN3, n = 15) to those from age and race matched women without significant abnormalities (CIN1, CIN0; n = 15). We used three microarray-adapted statistical packages to identify differential gene expression. The six genes identified in common were two to four fold upregulated in CIN3 samples. One of these genes, the ubiquitin-conjugating enzyme E2 variant 1, participates in the degradation of p53 through interaction with the oncogenic HPV E6 protein. CONCLUSION: The findings encourage further exploration of gene expression using exfoliated cells to identify and validate applicable biomarkers. We conclude that the gene expression profile of exfoliated cervical cells partially represents that of tissue and is complex enough to provide potential differentiation between disease and non-disease

Integrated Weighted Gene Co-expression Network Analysis with an Application to Chronic Fatigue Syndrome

<p>Abstract</p> <p>Background</p> <p>Systems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set.</p> <p>Results</p> <p>We combine WGCNA with genetic marker data to identify a disease-related pathway and its causal drivers, an analysis which we refer to as "Integrated WGCNA" or IWGCNA. Specifically, we present the following IWGCNA approach: 1) construct a co-expression network, 2) identify trait-related modules within the network, 3) use a trait-related genetic marker to prioritize genes within the module, 4) apply an integrated gene screening strategy to identify candidate genes and 5) carry out causality testing to verify and/or prioritize results. By applying this strategy to a CFS data set consisting of microarray, SNP and clinical trait data, we identify a module of 299 highly correlated genes that is associated with CFS severity. Our integrated gene screening strategy results in 20 candidate genes. We show that our approach yields biologically interesting genes that function in the same pathway and are causal drivers for their parent module. We use a separate data set to replicate findings and use Ingenuity Pathways Analysis software to functionally annotate the candidate gene pathways.</p> <p>Conclusion</p> <p>We show how WGCNA can be combined with genetic marker data to identify disease-related pathways and the causal drivers within them. The systems genetics approach described here can easily be used to generate testable genetic hypotheses in other complex disease studies.</p

Identification of Phosphoglycerate Kinase 1 (PGK1) as a reference gene for quantitative gene expression measurements in human blood RNA

<p>Abstract</p> <p>Background</p> <p>Blood is a convenient sample and increasingly used for quantitative gene expression measurements with a variety of diseases including chronic fatigue syndrome (CFS). Quantitative gene expression measurements require normalization of target genes to reference genes that are stable and independent from variables being tested in the experiment. Because there are no genes that are useful for all situations, reference gene selection is an essential step to any quantitative reverse transcription-PCR protocol. Many publications have described appropriate genes for a wide variety of tissues and experimental conditions, however, reference genes that may be suitable for the analysis of CFS, or human blood RNA derived from whole blood as well as isolated peripheral blood mononuclear cells (PBMCs), have not been described.</p> <p>Findings</p> <p>Literature review and analyses of our unpublished microarray data were used to narrow down the pool of candidate reference genes to six. We assayed whole blood RNA from Tempus tubes and cell preparation tube (CPT)-collected PBMC RNA from 46 subjects, and used the geNorm and NormFinder algorithms to select the most stable reference genes. <it>Phosphoglycerate kinase 1 (PGK1) </it>was one of the optimal normalization genes for both whole blood and PBMC RNA, however, additional genes differed for the two sample types; <it>Ribosomal protein large, P0 (RPLP0</it>) for PBMC RNA and <it>Peptidylprolyl isomerase B </it>(<it>PPIB) </it>for whole blood RNA. We also show that the use of a single reference gene is sufficient for normalization when the most stable candidates are used.</p> <p>Conclusions</p> <p>We have identified <it>PGK1 </it>as a stable reference gene for use with whole blood RNA and RNA derived from PBMC. When stable genes are selected it is possible to use a single gene for normalization rather than two or three. Optimal normalization will improve the ability of results from PBMC RNA to be compared with those from whole blood RNA and potentially allows comparison of gene expression results from blood RNA collected and processed by different methods with the intention of biomarker discovery. Results of this study should facilitate large-scale molecular epidemiologic studies using blood RNA as the target of quantitative gene expression measurements.</p

Broad-Spectrum Detection of HPV in Male Genital Samples Using Target-Enriched Whole-Genome Sequencing

Most human papillomavirus (HPV) surveillance studies target 30–50 of the more than 200 known types. We applied our recently described enriched whole-genome sequencing (eWGS) assay to demonstrate the impact of detecting all known and novel HPV types in male genital samples (n = 50). HPV was detected in nearly all (82%) samples, (mean number of types/samples 13.6; range 1–85), and nearly all HPV-positive samples included types in multiple genera (88%). A total of 560 HPV detections (237 unique HPV types: 46 alpha, 55 beta, 135 gamma, and 1 mu types) were made. The most frequently detected HPV types were alpha (HPV90, 43, and 74), beta (HPV115, 195, and 120), and gamma (HPV134, mSD2, and HPV50). High-risk alpha types (HPV16, 18, 31, 39, 52, and 58) were not common. A novel gamma type was identified (now officially HPV229) along with 90 unclassified types. This pilot study demonstrates the utility of the eWGS assay for broad-spectrum type detection and suggests a significantly higher type diversity in males compared to females that warrants further study

Simultaneous extraction of mRNA and microRNA from whole blood stabilized in tempus tubes

Abstract Objective Studies of mRNA and miRNA expression profiling increasingly use stabilized whole blood. Commercial RNA extraction kits do not provide information about the simultaneous recovery of both mRNA and miRNA. This study evaluated yield, quality, integrity and representation of mRNA and miRNA from whole blood stabilized in Tempus tubes using three RNA extraction kits; two filter-based (Tempus and Norgen) and one bead-based (MagMax; manual vs. semi-automated, and with and without DNase treatment). Results All RNA extraction kits and methods resulted in similar yields of mRNA (total RNA yield, quality, integrity and representation) whereas there were differences in yields of miRNA. MagMax, either manual or semi-automated, with or without DNase treatment, yielded 1.6–2.2-fold more miRNA than Tempus and Norgen kits. In addition, MagMax and Norgen methods gave greater than 12-fold more and 3.3-fold less enrichment of specific miRNA targets, respectively, in comparison to Tempus extraction reagents. This study identified MagMax kit for simultaneous recovery of both mRNA and miRNA from whole blood collected in Tempus tubes

NanoString Technology for Human Papillomavirus Typing

High-throughput HPV typing assays with increased automation, faster turnaround and type-specific digital readout would facilitate studies monitoring the impact of HPV vaccination. We evaluated the NanoString nCounter® platform for detection and digital readout of 48 HPV types in a single reaction. NanoString (NS) used proprietary software to design CodeSets: type-specific probe pairs targeting 48 HPV types and the globin gene. We tested residual DNA extracts from epidemiologic specimens and defined samples (HPV plasmids at 10 to 104 copies/reaction) directly (No-PCR) as well as after L1 consensus PCR of 45 (PCR-45) or 15 cycles (PCR-15). Assay and interpretation followed NS recommendations. We evaluated analytic performance by comparing NanoString results for types included in prior assays: Roche Linear Array (LA) or HPV TypeSeq assay. No-PCR results on 40 samples showed good type-specific agreement with LA (k = 0.621) but sensitivity was 65% with lower limit of detection (LOD) at 104 plasmid copies. PCR-45 results showed almost perfect type-specific agreement with LA (k = 0.862), 82% sensitivity and LOD at 10 copies. PCR-15 results on 75 samples showed substantial type-specific agreement with LA (k = 0.796, 92% sensitivity) and TypeSeq (k = 0.777, 87% sensitivity), and LOD at 10 copies of plasmids. This proof-of-principle study demonstrates the efficacy of the NS platform with HPV CodeSet for type-specific detection using a low number of PCR cycles (PCR-15). Studies are in progress to evaluate assay reproducibility and analytic validation with a larger number of samples