Whole genome survey of coding SNPs reveals a reproducible pathway determinant of Parkinson disease

It is quickly becoming apparent that situating human variation in a pathway context is crucial to understanding its phenotypic significance. Toward this end, we have developed a general method for finding pathways associated with traits that control for pathway size. We have applied this method to a new whole genome survey of coding SNP variation in 187 patients afflicted with Parkinson disease (PD) and 187 controls. We show that our dataset provides an independent replication of the axon guidance association recently reported by Lesnick et al. [PLoS Genet 2007;3:e98], and also indicates that variation in the ubiquitin-mediated proteolysis and T-cell receptor signaling pathways may predict PD susceptibility. Given this result, it is reasonable to hypothesize that pathway associations are more replicable than individual SNP associations in whole genome association studies. However, this hypothesis is complicated by a detailed comparison of our dataset to the second recent PD association study by Fung et al. [Lancet Neurol 2006;5:911–916]. Surprisingly, we find that the axon guidance pathway does not rank at the very top of the Fung dataset after controlling for pathway size. More generally, in comparing the studies, we find that SNP frequencies replicate well despite technologically different assays, but that both SNP and pathway associations are globally uncorrelated across studies. We thus have a situation in which an association between axon guidance pathway variation and PD has been found in 2 out of 3 studies. We conclude by relating this seeming inconsistency to the molecular heterogeneity of PD, and suggest future analyses that may resolve such discrepancies

High Throughput Automated Allele Frequency Estimation by Pyrosequencing

Pyrosequencing is a DNA sequencing method based on the principle of sequencing-by-synthesis and pyrophosphate detection through a series of enzymatic reactions. This bioluminometric, real-time DNA sequencing technique offers unique applications that are cost-effective and user-friendly. In this study, we have combined a number of methods to develop an accurate, robust and cost efficient method to determine allele frequencies in large populations for association studies. The assay offers the advantage of minimal systemic sampling errors, uses a general biotin amplification approach, and replaces dTTP for dATP-apha-thio to avoid non-uniform higher peaks in order to increase accuracy. We demonstrate that this newly developed assay is a robust, cost-effective, accurate and reproducible approach for large-scale genotyping of DNA pools. We also discuss potential improvements of the software for more accurate allele frequency analysis

Systematic Characterization of Donor Preference and Stress Response Mechanisms in Saccharomyces cerevisiae

Saccharomyces cerevisiae, or the baker's yeast, is an ideal model organism for biological studies, allowing for easy manipulation, and thus systematic characterization of different biological phenomena and their underlying genetic mechanisms. Here, I have leveraged such characteristic features of S. cerevisiae for developing experimental platforms which can be used towards understanding two fundamental biological processes: "DNA recombination" and "The cellular response to environmental cues". DNA damage is the major cause of cancer, and the target for many anticancer therapies. The DNA repair capability of a cell is essential for maintaining the integrity of its genome and influences the life span of the organism. Deficiency in DNA repair pathways leads to cell senescence, apoptosis, or formation of a cancerous tumor. Mating-type switching in S. cerevisiae, which arises from a similar double-strand break-induced gene conversion event, has traditionally been studied for understanding the mechanism of DNA repair and recombination. Here we have focused on donor preference, an aspect of mating type switching which is not fully understood and explored yet. In a separate endeavor towards system-level characterization of complex biological phenotypes in S. cerevisiae, we focused on yeast's response to environmental perturbations and signals. To that end, I picked two members of the signal transduction pathways involved in responding to environmental changes: Cdc19 and Msn2. Cdc19 is the main pyruvate kinase isozyme which is phosphorylated in response to glucose depletion. Msn2 transcription factor modulates cell's response to several types of stress at the transcriptome level. We found that while the phosphorylation state of yeast pyruvate kinase is modified in response to glucose availability, its activity is controlled by ultrasensitive allostery. Phosphorylation of Msn2 on the other hand has a more robust role in regulation of its activity. We found new phosphosites on Msn2 and showed that their level of phosphorylation changes upon environmental perturbations

Nucleotide degradation and ribose salvage in yeast

International audienceNucleotide degradation is a universal metabolic capability. Here we combine metabolomics, genetics and biochemistry to characterize the yeast pathway. Nutrient starvation, via PKA, AMPK/SNF1, and TOR, triggers autophagic breakdown of ribosomes into nucleotides. A protein not previously associated with nucleotide degradation, Phm8, converts nucleotide monophosphates into nucleosides. Downstream steps, which involve the purine nucleoside phosphorylase, Pnp1, and pyrimidine nucleoside hydrolase, Urh1, funnel ribose into the nonoxidative pentose phosphate pathway. During carbon starvation, the ribose-derived carbon accumulates as sedoheptulose-7-phosphate, whose consumption by transaldolase is impaired due to depletion of transaldolase's other substrate, glyceraldehyde-3-phosphate. Oxidative stress increases glyceraldehyde-3-phosphate, resulting in rapid consumption of sedoheptulose-7-phosphate to make NADPH for antioxidant defense. Ablation of Phm8 or double deletion of Pnp1 and Urh1 prevent effective nucleotide salvage, resulting in metabolite depletion and impaired survival of starving yeast. Thus, ribose salvage provides means of surviving nutrient starvation and oxidative stress

Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA

Early cancer detection could identify tumors at a time when outcomes are superior and treatment is less morbid. This prospective case-control sub-study (from NCT02889978 and NCT03085888) assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localize multiple cancer types across all stages at high specificity.The 6689 participants [2482 cancer (>50 cancer types), 4207 non-cancer] were divided into training and validation sets. Plasma cfDNA underwent bisulfite sequencing targeting a panel of >100 000 informative methylation regions. A classifier was developed and validated for cancer detection and tissue of origin (TOO) localization.Performance was consistent in training and validation sets. In validation, specificity was 99.3% [95% confidence interval (CI): 98.3% to 99.8%; 0.7% false-positive rate (FPR)]. Stage I–III sensitivity was 67.3% (CI: 60.7% to 73.3%) in a pre-specified set of 12 cancer types (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach), which account for ∼63% of US cancer deaths annually, and was 43.9% (CI: 39.4% to 48.5%) in all cancer types. Detection increased with increasing stage: in the pre-specified cancer types sensitivity was 39% (CI: 27% to 52%) in stage I, 69% (CI: 56% to 80%) in stage II, 83% (CI: 75% to 90%) in stage III, and 92% (CI: 86% to 96%) in stage IV. In all cancer types sensitivity was 18% (CI: 13% to 25%) in stage I, 43% (CI: 35% to 51%) in stage II, 81% (CI: 73% to 87%) in stage III, and 93% (CI: 87% to 96%) in stage IV. TOO was predicted in 96% of samples with cancer-like signal; of those, the TOO localization was accurate in 93%.cfDNA sequencing leveraging informative methylation patterns detected more than 50 cancer types across stages. Considering the potential value of early detection in deadly malignancies, further evaluation of this test is justified in prospective population-level studies.•Targeted methylation analysis of cfDNA simultaneously detected and localized >50 cancer types, including high-mortality cancers that lack screening paradigms.•Cancers were detected across all stages (stage I–III sensitivity: 43.9%; stage I–IV sensitivity: 54.9%) at a specificity of >99% and a single false positive rate of 90% accuracy, which will be critical for directing follow-up care.•This supports the continued investigation of this test with the goal of population-scale early multi-cancer detection