SNP Miniplexes for Individual Identification of Random-Bred Domestic Cats.

Phenotypic and genotypic characteristics of the cat can be obtained from single nucleotide polymorphisms (SNPs) analyses of fur. This study developed miniplexes using SNPs with high discriminating power for random-bred domestic cats, focusing on individual and phenotypic identification. Seventy-eight SNPs were investigated using a multiplex PCR followed by a fluorescently labeled single base extension (SBE) technique (SNaPshot(®) ). The SNP miniplexes were evaluated for reliability, reproducibility, sensitivity, species specificity, detection limitations, and assignment accuracy. Six SNPplexes were developed containing 39 intergenic SNPs and 26 phenotypic SNPs, including a sex identification marker, ZFXY. The combined random match probability (cRMP) was 6.58 × 10(-19) across all Western cat populations and the likelihood ratio was 1.52 × 10(18) . These SNPplexes can distinguish individual cats and their phenotypic traits, which could provide insight into crime reconstructions. A SNP database of 237 cats from 13 worldwide populations is now available for forensic applications

A genome-wide association study demonstrates significant genetic variation for fracture risk in Thoroughbred racehorses

Background: Thoroughbred racehorses are subject to non-traumatic distal limb bone fractures that occur during racing and exercise. Susceptibility to fracture may be due to underlying disturbances in bone metabolism which have a genetic cause. Fracture risk has been shown to be heritable in several species but this study is the first genetic analysis of fracture risk in the horse. Results: Fracture cases (n = 269) were horses that sustained catastrophic distal limb fractures while racing on UK racecourses, necessitating euthanasia. Control horses (n = 253) were over 4 years of age, were racing during the same time period as the cases, and had no history of fracture at the time the study was carried out. The horses sampled were bred for both flat and National Hunt (NH) jump racing. 43,417 SNPs were employed to perform a genome-wide association analysis and to estimate the proportion of genetic variance attributable to the SNPs on each chromosome using restricted maximum likelihood (REML). Significant genetic variation associated with fracture risk was found on chromosomes 9, 18, 22 and 31. Three SNPs on chromosome 18 (62.05 Mb – 62.15 Mb) and one SNP on chromosome 1 (14.17 Mb) reached genome-wide significance (p <0.05) in a genome-wide association study (GWAS). Two of the SNPs on ECA 18 were located in a haplotype block containing the gene zinc finger protein 804A (ZNF804A). One haplotype within this block has a protective effect (controls at 1.95 times less risk of fracture than cases, p = 1 × 10-4), while a second haplotype increases fracture risk (cases at 3.39 times higher risk of fracture than controls, p = 0.042). Conclusions: Fracture risk in the Thoroughbred horse is a complex condition with an underlying genetic basis. Multiple genomic regions contribute to susceptibility to fracture risk. This suggests there is the potential to develop SNP-based estimators for genetic risk of fracture in the Thoroughbred racehorse, using methods pioneered in livestock genetics such as genomic selection. This information would be useful to racehorse breeders and owners, enabling them to reduce the risk of injury in their horses

Genome-Wide Association to Body Mass Index and Waist Circumference: The Framingham Heart Study 100K Project

BACKGROUND: Obesity is related to multiple cardiovascular disease (CVD) risk factors as well as CVD and has a strong familial component. We tested for association between SNPs on the Affymetrix 100K SNP GeneChip and measures of adiposity in the Framingham Heart Study. METHODS: A total of 1341 Framingham Heart Study participants in 310 families genotyped with the Affymetrix 100K SNP GeneChip had adiposity traits measured over 30 years of follow up. Body mass index (BMI), waist circumference (WC), weight change, height, and radiographic measures of adiposity (subcutaneous adipose tissue, visceral adipose tissue, waist circumference, sagittal height) were measured at multiple examination cycles. Multivariable-adjusted residuals, adjusting for age, age-squared, sex, smoking, and menopausal status, were evaluated in association with the genotype data using additive Generalized Estimating Equations (GEE) and Family Based Association Test (FBAT) models. We prioritized mean BMI over offspring examinations (1–7) and cohort examinations (10, 16, 18, 20, 22, 24, 26) and mean WC over offspring examinations (4–7) for presentation. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg equilibrium p ≥ 0.001, and call rates of at least 80%. RESULTS: The top SNPs to be associated with mean BMI and mean WC by GEE were rs110683 (p-value 1.22*10-7) and rs4471028 (p-values 1.96*10-7). Please see for the complete set of results. We were able to validate SNPs in known genes that have been related to BMI or other adiposity traits, including the ESR1 Xba1 SNP, PPARG, and ADIPOQ. CONCLUSION: Adiposity traits are associated with SNPs on the Affymetrix 100K SNP GeneChip. Replication of these initial findings is necessary. These data will serve as a resource for replication as more genes become identified with BMI and WC.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC-25195); Atwood (R01 DK066241); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1

Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this pa- per, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection

Interleukin-18 gene promoter polymorphisms and recurrent spontaneous abortion

Background: IL-18 is a multifunctional cytokine capable of inducing either Th1 or Th2 polarization depending on the immunologic milieu. IL-18 is detected at the materno-fetal interface very soon in early pregnancy. Two polymorphisms in the promoter region of the IL-18 gene at positions of -607 and -137 appear to have functional impacts. Objective: This study attempts to evaluate the frequency of these two polymorphisms in the IL-18 gene promoter in patients with recurrent spontaneous abortion (RSA) and normal pregnant women. Subjects and methods: One hundred and two RSA patients and 103 healthy pregnant women were enrolled in this study. Single nucleotide polymorphisms of the IL-18 gene at positions -607 (C/A) and -137 (G/C) were analyzed by the sequence-specific PCR method. Results: There was no significant association between the allele, genotype, and haplotype frequencies of the two single nucleotide polymorphisms (SNPs) in the IL-18 gene promoter and RSA. Conclusion: The results of this study showed that IL-18 gene promoter polymorphisms at positions -607 and -137 did not confer susceptibility to RSA in southern Iranian patients. © 2006 Elsevier Ireland Ltd. All rights reserved

Strong signature of natural selection within an FHIT intron implicated in prostate cancer risk

Previously, a candidate gene linkage approach on brother pairs affected with prostate cancer identified a locus of prostate cancer susceptibility at D3S1234 within the fragile histidine triad gene (FHIT), a tumor suppressor that induces apoptosis. Subsequent association tests on 16 SNPs spanning approximately 381 kb surrounding D3S1234 in Americans of European descent revealed significant evidence of association for a single SNP within intron 5 of FHIT. In the current study, resequencing and genotyping within a 28.5 kb region surrounding this SNP further delineated the association with prostate cancer risk to a 15 kb region. Multiple SNPs in sequences under evolutionary constraint within intron 5 of FHIT defined several related haplotypes with an increased risk of prostate cancer in European-Americans. Strong associations were detected for a risk haplotype defined by SNPs 138543, 142413, and 152494 in all cases (Pearson's χ2 = 12.34, df 1, P = 0.00045) and for the homozygous risk haplotype defined by SNPs 144716, 142413, and 148444 in cases that shared 2 alleles identical by descent with their affected brothers (Pearson's χ2 = 11.50, df 1, P = 0.00070). In addition to highly conserved sequences encompassing SNPs 148444 and 152413, population studies revealed strong signatures of natural selection for a 1 kb window covering the SNP 144716 in two human populations, the European American (π = 0.0072, Tajima's D= 3.31, 14 SNPs) and the Japanese (π = 0.0049, Fay & Wu's H = 8.05, 14 SNPs), as well as in chimpanzees (Fay & Wu's H = 8.62, 12 SNPs). These results strongly support the involvement of the FHIT intronic region in an increased risk of prostate cancer. © 2008 Ding et al

Unifying candidate gene and GWAS Approaches in Asthma.

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values <0.0035 (corrected for multiple testing). Combining genotyping and imputation, polymorphisms in DPP10, EDN1, IL12B, IL13, IL4, IL4R and TNF showed associations at a significance level between p = 0.05 and p = 0.0035. These data indicate that (a) GWAS coverage is insufficient for many asthma candidate genes, (b) imputation based on these data is reliable but incomplete, and (c) SNPs in three previously identified asthma candidate genes replicate in our GWAS population with significance after correction for multiple testing in 14 genes