SNPPicker: High quality tag SNP selection across multiple populations

<p>Abstract</p> <p>Background</p> <p>Linkage Disequilibrium (LD) bin-tagging algorithms identify a reduced set of tag SNPs that can capture the genetic variation in a population without genotyping every single SNP. However, existing tag SNP selection algorithms for designing custom genotyping panels do not take into account all platform dependent factors affecting the likelihood of a tag SNP to be successfully genotyped and many of the constraints that can be imposed by the user.</p> <p>Results</p> <p>SNPPicker optimizes the selection of tag SNPs from common bin-tagging programs to design custom genotyping panels. The application uses a multi-step search strategy in combination with a statistical model to maximize the genotyping success of the selected tag SNPs. User preference toward functional SNPs can also be taken into account as secondary criteria. SNPPicker can also optimize tag SNP selection for a panel tagging multiple populations. SNPPicker can optimize custom genotyping panels including all the assay-specific constraints of Illumina's GoldenGate and Infinium assays.</p> <p>Conclusions</p> <p>A new application has been developed to maximize the success of custom multi-population genotyping panels. SNPPicker also takes into account user constraints including options for controlling runtime. Perl Scripts, Java source code and executables are available under an open source license for download at <url>http://mayoresearch.mayo.edu/mayo/research/biostat/software.cfm</url></p

Assessment of genotype imputation methods

Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods' imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease

Summary of the Fourth AIAA CFD Drag Prediction Workshop

Results from the Fourth AIAA Drag Prediction Workshop (DPW-IV) are summarized. The workshop focused on the prediction of both absolute and differential drag levels for wing-body and wing-body-horizontal-tail configurations that are representative of transonic transport air- craft. Numerical calculations are performed using industry-relevant test cases that include lift- specific flight conditions, trimmed drag polars, downwash variations, dragrises and Reynolds- number effects. Drag, lift and pitching moment predictions from numerous Reynolds-Averaged Navier-Stokes computational fluid dynamics methods are presented. Solutions are performed on structured, unstructured and hybrid grid systems. The structured-grid sets include point- matched multi-block meshes and over-set grid systems. The unstructured and hybrid grid sets are comprised of tetrahedral, pyramid, prismatic, and hexahedral elements. Effort is made to provide a high-quality and parametrically consistent family of grids for each grid type about each configuration under study. The wing-body-horizontal families are comprised of a coarse, medium and fine grid; an optional extra-fine grid augments several of the grid families. These mesh sequences are utilized to determine asymptotic grid-convergence characteristics of the solution sets, and to estimate grid-converged absolute drag levels of the wing-body-horizontal configuration using Richardson extrapolation

The Least Luminous Galaxy: Spectroscopy of the Milky Way Satellite Segue 1

We present Keck/DEIMOS spectroscopy of Segue 1, an ultra-low luminosity (M_V = -1.5) Milky Way satellite companion. While the combined size and luminosity of Segue 1 are consistent with either a globular cluster or a dwarf galaxy, we present spectroscopic evidence that this object is a dark matter-dominated dwarf galaxy. We identify 24 stars as members of Segue 1 with a mean heliocentric recession velocity of 206 +/- 1.3 kms. We measure an internal velocity dispersion of 4.3+/-1.2 kms. Under the assumption that these stars are in dynamical equilibrium, we infer a total mass of 4.5^{+4.7}_{-2.5} x 10^5 Msun in the case where mass-follow-light; using a two-component maximum likelihood model, we determine a similar mass within the stellar radius of 50 pc. This implies a mass-to-light ratio of ln(M/L_V) = 7.2^{+1.1}_{-1.2} or M/L_V = 1320^{+2680}_{-940}. The error distribution of the mass-to-light ratio is nearly log-normal, thus Segue 1 is dark matter-dominated at a high significance. Using spectral synthesis modeling, we derive a metallicity for the single red giant branch star in our sample of [Fe/H]=-3.3 +/- 0.2 dex. Finally, we discuss the prospects for detecting gamma-rays from annihilation of dark matter particles and show that Segue 1 is the most promising satellite for indirect dark matter detection. We conclude that Segue 1 is the least luminous of the ultra-faint galaxies recently discovered around the Milky Way, and is thus the least luminous known galaxy.Comment: 12 pages, 6 figures, ApJ accepte

Genetic variation in stromal proteins decorin and lumican with breast cancer: investigations in two case-control studies.

INTRODUCTION: The stroma is the supportive framework of biologic tissue in the breast, consisting of various proteins such as the proteoglycans, decorin and lumican. Altered expression of decorin and lumican is associated with breast tumors. We hypothesized that genetic variation in the decorin (DCN) and lumican (LUM) genes may contribute to breast cancer. METHODS: We investigated associations of 14 common polymorphisms in the DCN and LUM genes with 798 breast cancer cases and 843 controls from Mayo Clinic, MN, USA. One polymorphism per gene with the strongest risk association in the Mayo Clinic sample was genotyped in 4,470 breast cancer cases and 4,560 controls from East Anglia, England (Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH)). RESULTS: In the Mayo Clinic sample, six polymorphisms were associated with breast cancer risk (P trend <or= 0.05). The association with LUM rs2268578, evaluated further in SEARCH, was positive, although the odds ratios (OR) were weaker and not statistically significant. ORs were 1.4 (95% confidence interval [CI], 1.1 to 1.8) for heterozygotes and 2.2 (95% CI, 1.1 to 4.3; P2 df = 0.002) for homozygotes in the Mayo Clinic sample, and were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.4 (95% CI, 1.0 to 2.1; P2 df = 0.13) for homozygotes in the SEARCH sample. In combined analyses, the ORs were 1.1 (95% CI, 1.0 to 1.2) for heterozygotes and 1.6 (95% CI, 1.2 to 2.3; P2 df = 0.005) for homozygotes. Positive associations for this polymorphism were observed for estrogen receptor-positive tumors in both the Mayo Clinic sample (OR for heterozygotes = 1.5, 1.1 to 1.9 and OR for homozygotes = 2.5, 1.2 to 5.3;P2 df = 0.001) and the SEARCH sample (OR for heterozygotes = 1.0, 0.9 to 1.1 and OR for homozygotes = 1.6, 1.0 to 2.5; P2 df = 0.10). In combined analyses, the ORs were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.9 (95% CI, 1.3 to 2.8; P2 df = 0.001) for homozygotes. CONCLUSIONS: Although LUM rs2268578 was associated with breast cancer in the Mayo Clinic study, particularly estrogen receptor-positive breast cancer, weaker and modest associations were observed in the SEARCH sample. These modest associations will require larger samples to adequately assess the importance of this polymorphism in breast cancer

Risk of Ovarian Cancer and Inherited Variants in Relapse-Associated Genes

Background: We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. Methods and Findings: Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p = 0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p = 0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95 % CI 0.66–0.98; p = 0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p,0.05), and there was increased risk at HEXIM1 rs1053578 (p = 0.04, OR 1.40, 95 % CI 1.02–1.91). Conclusions: Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasiv

Polymorphisms in NF-κB Inhibitors and Risk of Epithelial Ovarian Cancer

<p>Abstract</p> <p>Background</p> <p>The nuclear factor-κB (NF-κB) family is a set of transcription factors with key roles in the induction of the inflammatory response and may be the link between inflammation and cancer development. This pathway has been shown to influence ovarian epithelial tissue repair. Inhibitors of κB (IκB) prevent NF-κB activation by sequestering NF-κB proteins in the cytoplasm until IκB proteins are phosphorylated and degraded.</p> <p>Methods</p> <p>We used a case-control study to evaluate the association between single nucleotide polymorphisms (SNPs) in <it>NFKBIA </it>and <it>NFKBIB </it>(the genes encoding IκBα and IκBβ, respectively) and risk of epithelial ovarian cancer. We queried 19 tagSNPs and putative-functional SNPs among 930 epithelial ovarian cancer cases and 1,037 controls from two studies.</p> <p>Results</p> <p>The minor allele for one synonymous SNP in <it>NFKBIA</it>, rs1957106, was associated with decreased risk (p = 0.03).</p> <p>Conclusion</p> <p>Considering the number of single-SNP tests performed and null gene-level results, we conclude that <it>NFKBIA </it>and <it>NFKBIB </it>are not likely to harbor ovarian cancer risk alleles. Due to its biological significance in ovarian cancer, additional genes encoding NF-κB subunits, activating and inhibiting molecules, and signaling molecules warrant interrogation.</p

Roles of neutrophils in the regulation of the extent of human inflammation through delivery of IL-1 and clearance of chemokines

This study examined the establishment of neutrophilic inflammation in humans. We tested the hypotheses that neutrophil recruitment was associated with local CXCL8 production and that neutrophils themselves might contribute to the regulation of the size of the inflammatory response. Humans were challenged i.d. with endotoxin. Biopsies of these sites were examined for cytokine production and leukocyte recruitment by qPCR and IHC. Additional in vitro models of inflammation examined the ability of neutrophils to produce and sequester cytokines relevant to neutrophilic inflammation. i.d. challenge with 15 ng of a TLR4-selective endotoxin caused a local inflammatory response, in which 1% of the total biopsy area stained positive for neutrophils at 6 h, correlating with 100-fold up-regulation in local CXCL8 mRNA generation. Neutrophils themselves were the major source of the early cytokine IL-1β. In vitro, neutrophils mediated CXCL8 but not IL-1β clearance (>90% clearance of ≤2 nM CXCL8 over 24 h). CXCL8 clearance was at least partially receptor-dependent and modified by inflammatory context, preserved in models of viral infection but reduced in models of bacterial infection. In conclusion, in a human inflammatory model, neutrophils are rapidly recruited and may regulate the size and outcome of the inflammatory response through the uptake and release of cytokines and chemokines in patterns dependent on the underlying inflammatory stimulus