A single nucleotide polymorphism in the p27Kip1 gene is associated with primary patency of lower extremity vein bypass grafts

ObjectiveFactors responsible for the variability in outcomes after lower extremity vein bypass grafting (LEVBG) are poorly understood. Recent evidence has suggested that a single nucleotide polymorphism (SNP) in the promoter region of the p27Kip1 gene, a cell-cycle regulator, is associated with coronary in-stent restenosis. We hypothesized an association with vein graft patency.MethodsThis was a retrospective genetic association study nested within a prospective cohort of 204 patients from three referral centers undergoing LEVBG for claudication or critical ischemia. The main outcome measure was primary vein graft patency.ResultsAll patients were followed up for a minimum of 1 year with duplex graft surveillance (median follow-up, 893 days; interquartile range, 539-1315). Genomic DNA was isolated and SNP analysis for the p27Kip1-838C>A variants was performed. Allele frequencies were correlated with graft outcome using survival analysis and Cox proportional hazards modeling. The p27Kip1-838C>A allele frequencies observed were CA, 53%; CC, 30%; and AA, 17%, satisfying Hardy-Weinberg equilibrium. Race (P = .025) and history of coronary artery disease (P = .027) were different across the genotypes; all other baseline variables were similar. Primary graft patency was greater among patients with the -838AA genotype (75% AA vs 55% CA/CC at 3 years; P = .029). In a Cox proportional hazards model including age, sex, race, diabetes, critical limb ischemia, redo (vs primary) bypass, vein type, and baseline C-reactive protein level, the p27Kip1-838AA genotype was significantly associated with higher graft patency (hazard ratio for failure, 0.4; 95% confidence interval, 0.17-0.93). Genotype was also associated with early (0-1 month) changes in graft lumen diameter by ultrasound imaging.ConclusionsThese data suggest that the p27Kip1-838C>A SNP is associated with LEVBG patency and, together with previous reports, underscore a central role for p27Kip1 in the generic response to vascular injury

The Reproducibility of 31-Phosphorus MRS Measures of Muscle Energetics at 3 Tesla in Trained Men

Magnetic resonance spectroscopy (MRS) provides an exceptional opportunity for the study of in vivo metabolism. MRS is widely used to measure phosphorus metabolites in trained muscle, although there are no published data regarding its reproducibility in this specialized cohort. Thus, the aim of this study was to assess the reproducibility of (31)P-MRS in trained skeletal muscle

Genome‑wide patterns of differentiation over spaceand time in the Queensland fruit fly

The Queensland fruit fly, Bactrocera tryoni, is a major pest of Australian horticulture which has expanded its range in association with the spread of horticulture over the last ~ 150 years. Its distribution in northern Australia overlaps that of another fruit fly pest to which some authors accord full species status, Bactrocera aquilonis. We have used reduced representation genome-wide sequencing to genotype 359 individuals taken from 35 populations from across the current range of the two taxa, plus a further 73 individuals from six of those populations collected 15-22 years earlier. We find significant population differentiation along an east-west transect across northern Australia which likely reflects limited but bidirectional gene flow between the two taxa. The southward expansion of B. tryoni has led to relatively little genetic differentiation, and most of it is associated with a move into previously marginal inland habitats. Two disjunct populations elsewhere in Australia and three on Melanesian islands are each clearly differentiated from all others, with data strongly supporting establishment from relatively few founders and significant isolation subsequently. Resequencing of historical samples from one of the disjunct Australian populations shows that its genetic profile has changed little over a 15-year period, while the Melanesian data suggest a succession of 'island hopping' events with progressive reductions in genetic diversity. We discuss our results in relation to the control of B. tryoni and as a model for understanding the genetics of invasion and hybridisation processes

The effect of artificial selection on phenotypic plasticity in maize

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0–5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets

Objectives: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F’s genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. Data description: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed

Substrate Type Determines Metagenomic Profiles from Diverse Chemical Habitats

Environmental parameters drive phenotypic and genotypic frequency variations in microbial communities and thus control the extent and structure of microbial diversity. We tested the extent to which microbial community composition changes are controlled by shifting physiochemical properties within a hypersaline lagoon. We sequenced four sediment metagenomes from the Coorong, South Australia from samples which varied in salinity by 99 Practical Salinity Units (PSU), an order of magnitude in ammonia concentration and two orders of magnitude in microbial abundance. Despite the marked divergence in environmental parameters observed between samples, hierarchical clustering of taxonomic and metabolic profiles of these metagenomes showed striking similarity between the samples (>89%). Comparison of these profiles to those derived from a wide variety of publically available datasets demonstrated that the Coorong sediment metagenomes were similar to other sediment, soil, biofilm and microbial mat samples regardless of salinity (>85% similarity). Overall, clustering of solid substrate and water metagenomes into discrete similarity groups based on functional potential indicated that the dichotomy between water and solid matrices is a fundamental determinant of community microbial metabolism that is not masked by salinity, nutrient concentration or microbial abundance

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P <7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.Peer reviewe

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

CMB-S4

We describe the stage 4 cosmic microwave background ground-based experiment CMB-S4