Genome-wide algorithm for detecting CNV associations with diseases

<p>Abstract</p> <p>Background</p> <p>SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP data using the marker intensities. However, these algorithms lack specificity to detect small CNVs owing to the high false positive rate when calling CNVs based on the intensity values. Therefore, the resulting association tests lack power even if the CNVs affecting disease risk are common. An alternative procedure called PennCNV uses information from both the marker intensities as well as the genotypes and therefore has increased sensitivity.</p> <p>Results</p> <p>By using the hidden Markov model (HMM) implemented in PennCNV to derive the probabilities of different copy number states which we subsequently used in a logistic regression model, we developed a new genome-wide algorithm to detect CNV associations with diseases. We compared this new method with association test applied to the most probable copy number state for each individual that is provided by PennCNV after it performs an initial HMM analysis followed by application of the Viterbi algorithm, which removes information about copy number probabilities. In one of our simulation studies, we showed that for large CNVs (number of SNPs ≥ 10), the association tests based on PennCNV calls gave more significant results, but the new algorithm retained high power. For small CNVs (number of SNPs <it><</it>10), the logistic algorithm provided smaller average p-values (e.g., <it>p </it>= 7.54<it>e </it>- 17 when relative risk <it>RR </it>= 3.0) in all the scenarios and could capture signals that PennCNV did not (e.g., <it>p </it>= 0.020 when <it>RR </it>= 3.0). From a second set of simulations, we showed that the new algorithm is more powerful in detecting disease associations with small CNVs (number of SNPs ranging from 3 to 5) under different penetrance models (e.g., when <it>RR </it>= 3.0, for relatively weak signals, <it>power </it>= 0.8030 comparing to 0.2879 obtained from the association tests based on PennCNV calls). The new method was implemented in software GWCNV. It is freely available at <url>http://gwcnv.sourceforge.net</url>, distributed under a GPL license.</p> <p>Conclusions</p> <p>We conclude that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than the existing HMM algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.</p

An Efficient Estimator of the Mutation Parameter and Analysis of Polymorphism from the 1000 Genomes Project

The mutation parameter θ is fundamental and ubiquitous in the analysis of population samples of DNA sequences. This paper presents a new highly efficient estimator of θ by utilizing the phylogenetic information among distinct alleles in a sample of DNA sequences. The new estimator, called Allelic BLUE, is derived from a generalized linear model about the mutations in the allelic genealogy. This estimator is not only highly accurate, but also computational efficient, which makes it particularly useful for estimating θ for large samples, as well as for a large number of cases, such as the situation of analyzing sequence data from a large genome project, such as the 1000 Genomes Project. Simulation shows that Allelic BLUE is nearly unbiased, with variance nearly as small as the minimum achievable variance, and in many situations, it can be hundreds- or thousands-fold more efficient than a previous method, which was already quite efficient compared to other approaches. One useful feature of the new estimator is its applicability to collections of distinct alleles without detailed frequencies. The utility of the new estimator is demonstrated by analyzing the pattern of θ in the data from the 1000 Genomes Project

Chemical and structural characteristics of gas hydrates from the Haima cold seeps in the Qiongdongnan Basin of the South China Sea

Crystalline structure, cage occupancy, and gas composition are important gas hydrate characteristics, which can be used to calculate the gas hydrate's stability and to estimate the energy potential. In May and October of 2015, a Guangzhou Marine Geological Survey team investigated two sites in the Haima cold seeps in the Qiongdongnan Basin, northern South China Sea. They recovered massive gas hydrate samples by conventional gravity coring. After the Shenhu Sea area and Dongsha Sea area, the Qiongdongnan Basin became a new area on the northern slope of the South China Sea where gas hydrates have been found. In order to reveal the structural and geochemical characteristics of the natural gas hydrates, samples were analyzed by micro-Raman spectroscopy and X-ray diffraction under ambient pressure and low-temperature conditions. The results indicate that the gas hydrate samples from the Haima cold seeps are typical structure I hydrates with a hydration number of 6.12-6.19. In addition, trace amounts of H2S trapped in the hydrate were identified based on its characteristic vibrational signature. The gas composition and delta C-13-CH4 of the hydrate-bound gas samples were analyzed for gas-source correlation. All of the gas samples are dominated by methane with small amounts of ethane and propane and had relatively light 8 delta C-13-CH4 indicating that all of the hydrate-bound gases are mixtures of biogenic and thermogenic gas. The thermogenic gas is inferred to be mainly derived from the coal layers of the Late Miocene-Pliocene Yacheng Formation in the northern Lingshui sag

Genetic Association Analysis of Common Variants in <i>FOXO3</i> Related to Longevity in a Chinese Population

<div><p>Recent studies suggested that forkhead box class O3 (FOXO3) functions as a key regulator for the insulin/insulin-like growth factor-1signaling pathway that influence aging and longevity. This study aimed to comprehensively elucidate the association of common genetic variants in <i>FOXO3</i> with human longevity in a Chinese population. Eighteen single-nucleotide polymorphisms (SNPs) in <i>FOXO3</i> were successfully genotyped in 616 unrelated long-lived individuals and 846 younger controls. No nominally significant effects were found. However, when stratifying by gender, four SNPs (rs10499051, rs7762395, rs4946933 and rs3800230) previously reported to be associated with longevity and one novel SNP (rs4945815) showed significant association with male longevity (<i>P</i>-values: 0.007–0.032), but all SNPs were not associated with female longevity. Correspondingly, males carrying the <b><i>G</i></b>-G-<b><i>T</i></b>-<b><i>G</i></b> haplotype of rs10499051, rs7762395, rs4945815 and rs3800230 tended to have longer lifespan than those carrying the most common haplotype A-G-C-T (odds ratio = 2.36, 95% confidence interval = 1.20–4.63, <i>P</i> = 0.013). However, none of the associated SNPs and haplotype remained significant after Bonferroni correction. In conclusion, our findings revealed that the <i>FOXO3</i> variants we tested in our population of Chinese men and women were associated with longevity in men only. None of these associations passed Bonferroni correction. Bonferroni correction is very stringent for association studies. We therefore believe the effects of these nominally significant variants on human longevity will be confirmed by future studies.</p></div

Haplotype analysis of male-longevity-associated SNPs in <i>FOXO3</i>.

<p>Haplotype analysis of male-longevity-associated SNPs in <i>FOXO3</i>.</p

Linkage disequilibrium plot of the 18 <i>FOXO3</i> SNPs genotyped.

<p>Linkage disequilibrium was quantified as D' (A) and <i>r</i>² (B), calculated in all subjects with the web tool SHEsis. Note: the darker the color, the higher the values.</p

Genotype and allele frequencies of longevity-associated <i>FOXO3</i> polymorphisms in the long-lived individuals and controls.

<p>Genotype and allele frequencies of longevity-associated <i>FOXO3</i> polymorphisms in the long-lived individuals and controls.</p

Additional file 1: Table S1. of Common variants in SIRT1 and human longevity in a Chinese population

Details for single-nucleotide polymorphisms (SNPs) tagged by genotyped SNPs. Table S2. Genotype and allele frequencies of SIRT1 polymorphisms in the Chinese Han long-lived individuals and controls. Table S3. Association of SIRT1 haplotypes with human longevity in the Chinese Han long-lived individuals and controls. Table S4. Genotype and allele frequencies of SIRT1 polymorphisms in the long-lived individuals and controls when stratified by gender. Table S5. Association of SIRT1 haplotypes with human longevity when stratified by gender. Table S6. Association studies of SIRT1 with human longevity. (DOC 226 kb