Diagnostic value of exome and whole genome sequencing in craniosynostosis

Background Craniosynostosis, the premature fusion of one or more cranial sutures, occurs in ~1 in 2250 births, either in isolation or as part of a syndrome. Mutations in at least 57 genes have been associated with craniosynostosis, but only a minority of these are included in routine laboratory genetic testing. Methods We used exome or whole genome sequencing to seek a genetic cause in a cohort of 40 subjects with craniosynostosis, selected by clinical or molecular geneticists as being high-priority cases, and in whom prior clinically driven genetic testing had been negative. Results We identified likely associated mutations in 15 patients (37.5%), involving 14 different genes. All genes were mutated in single families, except for IL11RA (two families). We classified the other positive diagnoses as follows: commonly mutated craniosynostosis genes with atypical presentation (EFNB1, TWIST1); other core craniosynostosis genes (CDC45, MSX2, ZIC1); genes for which mutations are only rarely associated with craniosynostosis (FBN1, HUWE1, KRAS, STAT3); and known disease genes for which a causal relationship with craniosynostosis is currently unknown (AHDC1, NTRK2). In two further families, likely novel disease genes are currently undergoing functional validation. In 5 of the 15 positive cases, the (previously unanticipated) molecular diagnosis had immediate, actionable consequences for either genetic or medical management (mutations in EFNB1, FBN1, KRAS, NTRK2, STAT3). Conclusions This substantial genetic heterogeneity, and the multiple actionable mutations identified, emphasises the benefits of exome/whole genome sequencing to identify causal mutations in craniosynostosis cases for which routine clinical testing has yielded negative results

Developing a predictive modelling capacity for a climate change-vulnerable blanket bog habitat: Assessing 1961-1990 baseline relationships

Aim: Understanding the spatial distribution of high priority habitats and developing predictive models using climate and environmental variables to replicate these distributions are desirable conservation goals. The aim of this study was to model and elucidate the contributions of climate and topography to the distribution of a priority blanket bog habitat in Ireland, and to examine how this might inform the development of a climate change predictive capacity for peat-lands in Ireland. Methods: Ten climatic and two topographic variables were recorded for grid cells with a spatial resolution of 1010 km, covering 87% of the mainland land surface of Ireland. Presence-absence data were matched to these variables and generalised linear models (GLMs) fitted to identify the main climatic and terrain predictor variables for occurrence of the habitat. Candidate predictor variables were screened for collinearity, and the accuracy of the final fitted GLM was evaluated using fourfold cross-validation based on the area under the curve (AUC) derived from a receiver operating characteristic (ROC) plot. The GLM predicted habitat occurrence probability maps were mapped against the actual distributions using GIS techniques. Results: Despite the apparent parsimony of the initial GLM using only climatic variables, further testing indicated collinearity among temperature and precipitation variables for example. Subsequent elimination of the collinear variables and inclusion of elevation data produced an excellent performance based on the AUC scores of the final GLM. Mean annual temperature and total mean annual precipitation in combination with elevation range were the most powerful explanatory variable group among those explored for the presence of blanket bog habitat. Main conclusions: The results confirm that this habitat distribution in general can be modelled well using the non-collinear climatic and terrain variables tested at the grid resolution used. Mapping the GLM-predicted distribution to the observed distribution produced useful results in replicating the projected occurrence of the habitat distribution over an extensive area. The methods developed will usefully inform future climate change predictive modelling for Irelan

Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)-encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non-conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Proteinase K (EC 3.4.21.14)

The original publication is available at www.springerlink.com Copyright Humana Press [Full text of this article is not available in the UHRA]Proteinase K is a serine protease and the main proteolytic enzyme produced by the fungus Tritirachium album Limber (l). The enzyme has a broad specificity, cleaving peptide bonds C-terminal to a number of amino acids. The enzyme is produced, together with other proteases and an aminopeptidase, during stationary phase when the fungus is grown by submerged culture. The enzyme is so named because the organism can grow on native keratin as sole carbohydrate and nitrogen source owing to the enzyme’s ability to digest keratin. Because of its broad substrate specificity, high activity, and its ability to digest native proteins, proteinase K has found considerable use in procedures where the inactivation and degradation of proteins is required, particularly during the purification of nucleic acids.Peer reviewe

Condensation of a 50/50 Blend of R-32/R-125 in Horizontal Tubes with and Without Oil

This study examined local condensation heat transfer and pressure drop for a pure 50/50% mixture of R- 32/125 and for R-32/125 mixed with approximately 1%, 3%, and 5% concentrations of an ester oil. An apparatus was built to simulate conditions found in the condenser sections of domestic refrigerators/freezers. Experiments were performed to measure the internal heat transfer coefficients and pressure drops inside a 0.277 in. (7.0 mm) o.d. smooth, horizontal copper tube. It was observed from the oil samples that the oil concentration of the oil-refrigerant mixtures flowing through the test section changed for different mass fluxes and qualities. The data for the heat transfer coefficients were compared with existing correlations and the Dobson correlation demonstrated the best accuracy for the pure R-32/125 and predicted the performance of oil-refrigerant mixtures with less than 20% error when used with the Schlager enhancement factor. The experiments showed that oil addition degraded the heat transfer coefficient at vapor qualities greater than 50% and increased the pressure drop by as much as 25% at high mass fluxes