On the frequencies of circumbinary discs in protostellar systems

We report the analysis of circumbinary discs formed in a radiation hydrodynamical simulation of star cluster formation. We consider both pure binary stars and pairs within triple and quadruple systems. The protostellar systems are all young (ages < $10^5$ yrs). We find that the systems that host a circumbinary disc have a median separation of $\approx 11$ au, and the median characteristic radius of the discs is $\approx 64$ au. We find that $89$ per cent of pure binaries with semi-major axes $a<1$ au have a circumbinary disc, and the occurrence rate of circumbinary discs is bimodal with log-separation in pure binaries with a second peak at $a \approx 50$ au. Systems with $a>100$ au almost never have a circumbinary disc. The median size of a circumbinary disc is between $\approx 5-6\ a$ depending on the order of the system, with higher order systems having larger discs relative to binary separation. We find the underlying distribution of mutual inclinations between circumbinary discs and binary orbit of both observed and simulated discs to not differ statistically.Comment: 12 pages, 11 figures, 1 table, accepted for publication in MNRA

Comprehensive functional annotation of 77 prostate cancer risk loci.

Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process

Independent risk loci.

<p><b>Independent GWAS Loci.</b> Table of independent associations with prostate cancer. Index SNPs with are grouped together, and shown with source citations. A locus with a significant number of correlated SNPs at for two index SNPs that don't meet the cutoff are also considered the same locus. Also shown are the nearby genes (Gene) and population in which the associations were reported (Ethn).</p

Primer sequences.

<p><b>Primers used in cloning enhancers for reporter assays.</b> The underlined portion highlights the and sites used for site-directed cloning of the PCR product. The PSA control is described in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004102#pgen.1004102-Jia1" target="_blank">[7]</a>.</p

Androgen-regulated genes.

<p><b>Table of Index SNPs with AR regulated genes.</b> Genes within 1 Mb of functional SNPs. Genes are differentially expressed after exposure of LNCaP to androgen (see treatment in column header). Data are included from three different RNA-seq studies. Numbers represent fold change post-treatment. Genes identified by more than one study are indicated in bold typeface.</p

Missense variants in correlated SNPs.

<p><b>Non-synonymous substitutions.</b> Table of <i>Funci{SNP}</i>-identified single nucleotide missense variants in protein coding exons, showing the results of variant effect prediction software.</p

miR-target variants.

<p><b>SNPs in miR target sequences.</b> Table of SNPs affecting putative miR target sequences in untranslated coding regions, and the potentially affected target genes.</p

Transcription Factor Response Elements are not enriched in PCa GWAS SNPs.

<p> express number of observed response element disruptions as a proportion relative to the standard deviation from the background distribution. The regression line is shown in blue with 95% confidence interval. Transcription factors of interest are highlighted with blue text. The inner box (dotted line) demarcates the 95% C.I. of a bootstrapped distribution for each PWM. A bonferroni box is outside the bounds of the graphic.</p

Results of <i>Funci{SNP}</i> analysis of GWAS correlated SNPs.

<p>Index SNPs with biofeatures and correlated SNPs at are combined and summarized in A–D. A. SNP counts by value. B. SNP counts by biofeature. Some SNPs map to more than one biofeature, hence the total does not sum to 727. C. Classification of 727 SNPs by <i>putative</i> functional category. D. Supervised clustering of SNPs by biofeature.</p

Enrichment of Gene Ontology.

<p>Representative ontology clusters from DAVID <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004102#pgen.1004102-Huang1" target="_blank">[37]</a> enrichment analysis of nearby genes given in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004102#pgen-1004102-t001" target="_blank">Table 1</a>. Green boxes indicate membership of the genes (as columns) with the annotations (as rows). A. Transcription factor cluster. B. Male gonad development cluster.</p