Complete genomic sequence analysis of infectious bronchitis virus Ark DPI strain and its evolution by recombination

An infectious bronchitis virus Arkansas DPI (Ark DPI) virulent strain was sequenced, analyzed and compared with many different IBV strains and coronaviruses. The genome of Ark DPI consists of 27,620 nucleotides, excluding poly (A) tail, and comprises ten open reading frames. Comparative sequence analysis of Ark DPI with other IBV strains shows striking similarity to the Conn, Gray, JMK, and Ark 99, which were circulating during that time period. Furthermore, comparison of the Ark genome with other coronaviruses demonstrates a close relationship to turkey coronavirus. Among non-structural genes, the 5'untranslated region (UTR), 3C-like proteinase (3CLpro) and the polymerase (RdRp) sequences are 100% identical to the Gray strain. Among structural genes, S1 has 97% identity with Ark 99; S2 has 100% identity with JMK and 96% to Conn; 3b 99%, and 3C to N is 100% identical to Conn strain. Possible recombination sites were found at the intergenic region of spike gene, 3'end of S1 and 3a gene. Independent recombination events may have occurred in the entire genome of Ark DPI, involving four different IBV strains, suggesting that genomic RNA recombination may occur in any part of the genome at number of sites. Hence, we speculate that the Ark DPI strain originated from the Conn strain, but diverged and evolved independently by point mutations and recombination between field strains

Sodium Selenide Toxicity Is Mediated by O2-Dependent DNA Breaks

Hydrogen selenide is a recurrent metabolite of selenium compounds. However, few experiments studied the direct link between this toxic agent and cell death. To address this question, we first screened a systematic collection of Saccharomyces cerevisiae haploid knockout strains for sensitivity to sodium selenide, a donor for hydrogen selenide (H2Se/HSe−/Se2−). Among the genes whose deletion caused hypresensitivity, homologous recombination and DNA damage checkpoint genes were over-represented, suggesting that DNA double-strand breaks are a dominant cause of hydrogen selenide toxicity. Consistent with this hypothesis, treatment of S. cerevisiae cells with sodium selenide triggered G2/M checkpoint activation and induced in vivo chromosome fragmentation. In vitro, sodium selenide directly induced DNA phosphodiester-bond breaks via an O2-dependent reaction. The reaction was inhibited by mannitol, a hydroxyl radical quencher, but not by superoxide dismutase or catalase, strongly suggesting the involvement of hydroxyl radicals and ruling out participations of superoxide anions or hydrogen peroxide. The •OH signature could indeed be detected by electron spin resonance upon exposure of a solution of sodium selenide to O2. Finally we showed that, in vivo, toxicity strictly depended on the presence of O2. Therefore, by combining genome-wide and biochemical approaches, we demonstrated that, in yeast cells, hydrogen selenide induces toxic DNA breaks through an O2-dependent radical-based mechanism

Fulvestrant: an oestrogen receptor antagonist with a novel mechanism of action

Due to their favourable tolerability profiles, endocrine therapies have long been considered the treatment of choice for hormone-sensitive metastatic breast cancer. However, the oestrogen agonist effects of the available selective oestrogen receptor modulators, such as tamoxifen, and the development of cross-resistance between endocrine therapies with similar modes of action have led to the need for new treatments that act through different mechanisms. Fulvestrant (‘Faslodex’) is the first of a new type of endocrine treatment – an oestrogen receptor (ER) antagonist that downregulates the ER and has no agonist effects. This article provides an overview of the current understanding of ER signalling and illustrates the unique mode of action of fulvestrant. Preclinical and clinical study data are presented in support of the novel mechanism of action of this new type of ER antagonist

Genetic and Non-Genetic Influences during Pregnancy on Infant Global and Site Specific DNA Methylation: Role for Folate Gene Variants and Vitamin B12

Inter-individual variation in patterns of DNA methylation at birth can be explained by the influence of environmental, genetic and stochastic factors. This study investigates the genetic and non-genetic determinants of variation in DNA methylation in human infants. Given its central role in provision of methyl groups for DNA methylation, this study focuses on aspects of folate metabolism. Global (LUMA) and gene specific (IGF2, ZNT5, IGFBP3) DNA methylation were quantified in 430 infants by Pyrosequencing®. Seven polymorphisms in 6 genes (MTHFR, MTRR, FOLH1, CβS, RFC1, SHMT) involved in folate absorption and metabolism were analysed in DNA from both infants and mothers. Red blood cell folate and serum vitamin B12 concentrations were measured as indices of vitamin status. Relationships between DNA methylation patterns and several covariates viz. sex, gestation length, maternal and infant red cell folate, maternal and infant serum vitamin B12, maternal age, smoking and genotype were tested. Length of gestation correlated positively with IGF2 methylation (rho = 0.11, p = 0.032) and inversely with ZNT5 methylation (rho = −0.13, p = 0.017). Methylation of the IGFBP3 locus correlated inversely with infant vitamin B12 concentration (rho = −0.16, p = 0.007), whilst global DNA methylation correlated inversely with maternal vitamin B12 concentrations (rho = 0.18, p = 0.044). Analysis of common genetic variants in folate pathway genes highlighted several associations including infant MTRR 66G>A genotype with DNA methylation (χ2 = 8.82, p = 0.003) and maternal MTHFR 677C>T genotype with IGF2 methylation (χ2 = 2.77, p = 0.006). These data support the hypothesis that both environmental and genetic factors involved in one-carbon metabolism influence DNA methylation in infants. Specifically, the findings highlight the importance of vitamin B12 status, infant MTRR genotype and maternal MTHFR genotype, all of which may influence the supply of methyl groups for DNA methylation. In addition, gestational length appears to be an important determinant of infant DNA methylation patterns

A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in non-coding regions, and causal genes underlying these associations remain largely unknown. Here we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian-tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P<2.2×10-6, we identified 35 genes including FZD4 at 11q14.2 (Z=5.08, P=3.83×10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly-associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and 3 genes remained (P<1.47 x 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis

Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression:Identification of a modifier of breast cancer risk at locus 11q22.3

Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of similar to 320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 x 10(-6)). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.</p

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

An essential role for the IL-2 receptor in Treg cell function

Regulatory T cells (Treg cells), which have abundant expression of the interleukin 2 receptor (IL-2R), are reliant on IL-2 produced by activated T cells. This feature indicates a key role for a simple network based on the consumption of IL-2 by Treg cells in their suppressor function. However, congenital deficiency in IL-2R results in reduced expression of the Treg cell lineage–specification factor Foxp3, which has confounded experimental efforts to understand the role of IL-2R expression and signaling in the suppressor function of Treg cells. Using genetic gain- and loss-of-function approaches, we found that capture of IL-2 was dispensable for the control of CD4+ T cells but was important for limiting the activation of CD8+ T cells, and that IL-2R-dependent activation of the transcription factor STAT5 had an essential role in the suppressor function of Treg cells separable from signaling via the T cell antigen receptor