Background With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Findings Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for high-performance computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA sequencing, chromatin immunoprecipitation sequencing, DNA sequencing, methylation sequencing, Hi-C, capture Hi-C, metagenomics, and Pacific Biosciences long-read assembly. The software is available under a GPLv3 open source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has already been configured on several servers, and a Docker image is also available to facilitate additional installations. Conclusions GenPipes offers genomics researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.

BackgroundMacrocyclic lactone (ML) anthelmintics are used for chemoprophylaxis for heartworm infection in dogs and cats. Cases of dogs becoming infected with heartworms, despite apparent compliance to recommended chemoprophylaxis with approved preventives, has led to such cases being considered as suspected lack of efficacy (LOE). Recently, microfilariae collected from a small number of LOE isolates were used as a source of infection of new host dogs and confirmed to have reduced susceptibility to ML in controlled efficacy studies using L3 challenge in dogs. A specific Dirofilaria immitis laboratory isolate named JYD-34 has also been confirmed to have less than 100% susceptibility to ML-based preventives. For preventive claims against heartworm disease, evidence of 100% efficacy is required by FDA-CVM. It was therefore of interest to determine whether JYD-34 has a genetic profile similar to other documented LOE and confirmed reduced susceptibility isolates or has a genetic profile similar to known ML-susceptible isolates.MethodsIn this study, the 90Mbp whole genome of the JYD-34 strain was sequenced. This genome was compared using bioinformatics tools to pooled whole genomes of four well-characterized susceptible D. immitis populations, one susceptible Missouri laboratory isolate, as well as the pooled whole genomes of four LOE D. immitis populations. Fixation indexes (FST), which allow the genetic structure of each population (isolate) to be compared at the level of single nucleotide polymorphisms (SNP) across the genome, have been calculated. Forty-one previously reported SNP, that appeared to differentiate between susceptible and LOE and confirmed reduced susceptibility isolates, were also investigated in the JYD-34 isolate.ResultsThe FST analysis, and the analysis of the 41 SNP that appeared to differentiate reduced susceptibility from fully susceptible isolates, confirmed that the JYD-34 isolate has a genome similar to previously investigated LOE isolates, and isolates confirmed to have reduced susceptibility, and to be dissimilar to the susceptible isolates.ConclusionsThese results provide additional evidence for the link between genotype and the reduced susceptibility phenotype observed in such isolates as JYD-34. Further work on other isolates showing reduced susceptibility to ML is required to demonstrate the value of genetic analysis in predicting the response to ML chemoprophylaxis. The authors suggest that genetic analysis may be useful in helping to interpret the results of in vivo efficacy testing of ML heartworm preventives against D. immitis isolates.Electronic supplementary materialThe online version of this article (10.1186/s13071-017-2437-5) contains supplementary material, which is available to authorized users.

We conducted a genome-wide association study of time to remission of COVID-19 symptoms in 1723 outpatients with at least one risk factor for disease severity from the COLCORONA clinical trial. We found a significant association at 5p13.3 (rs1173773; P = 4.94 × 10–8) near the natriuretic peptide receptor 3 gene (NPR3). By day 15 of the study, 44%, 54% and 59% of participants with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. In 851 participants not treated with colchicine (placebo), there was a significant association at 9q33.1 (rs62575331; P = 2.95 × 10–8) in interaction with colchicine (P = 1.19 × 10–5) without impact on risk of hospitalisations, highlighting a possibly shared mechanistic pathway. By day 15 of the study, 46%, 62% and 64% of those with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. The findings need to be replicated and could contribute to the biological understanding of COVID-19 symptom remission.

With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for High Performance Computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA-Seq, ChIP-Seq, DNA-Seq, Methyl-Seq, Hi-C, capture Hi-C, metagenomics and PacBio long read assembly. The software is available under a GPLv3 open source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has been already configured on several servers and a docker image is also available to facilitate additional installations. In summary, GenPipes offers genomic researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.

Blood pressure (BP) is a dynamic phenotype that varies rapidly to adjust to changing environmental conditions. Standing upright is a recent evolutionary trait, and genetic factors that influence postural adaptations may contribute to BP variability. We studied the effect of posture on the genetics of BP and intermediate BP phenotypes. We included 384 sib-pairs in 64 sib-ships from families ascertained by early-onset hypertension and dyslipidemia. Blood pressure, three hemodynamic and seven neuroendocrine intermediate BP phenotypes were measured with subjects lying supine and standing upright. The effect of posture on estimates of heritability and genetic covariance was investigated in full pedigrees. Linkage was conducted on 196 candidate genes by sib-pair analyses, and empirical estimates of significance were obtained. A permutation algorithm was implemented to study the postural effect on linkage. ADRA1A, APO, CAST, CORIN, CRHR1, EDNRB, FGF2, GC, GJA1, KCNB2, MMP3, NPY, NR3C2, PLN, TGFBR2, TNFRSF6, and TRHR showed evidence of linkage with any phenotype in the supine position and not upon standing, whereas AKR1B1, CD36, EDNRA, F5, MMP9, PKD2, PON1, PPARG, PPARGC1A, PRKCA, and RET were specifically linked to standing phenotypes. Genetic profiling was undertaken to show genetic interactions among intermediate BP phenotypes and genes specific to each posture. When investigators perform genetic studies exclusively on a single posture, important genetic components of BP are missed. Supine and standing BPs have distinct genetic signatures. Standardized maneuvers influence the results of genetic investigations into BP, thus reflecting its dynamic regulation. blood pressure; family studies; genetic linkage; postural adaptations HIGH BLOOD PRESSURE (BP) levels and variability are associated with a high risk of adverse outcomes (21, 32). It is estimated that up to 50% of BP variance is genetically determined, with the rest of it due to the effect of environment (24). However, individual quantitative trait loci (QTLs) contribute to only a small percentage of BP variation (7,28). In fact, genetic variants identified to date in genome-wide association studies (GWAS) may explain only 1-2% of BP variance in the population (9,19,29). The effect of a QTL on BP may be overridden by compensatory mechanisms (genetic modifiers and/or physiological adaptations) or obscured by the acute influence of environment at the time of BP measurement (random variation/acute hemodynamic adjustments) as well as by antihypertensive therapy (26).In contrast to stable or relatively stable quantitative traits, such as height or weight, BP is a highly dynamic phenotype designed to preserve tissue perfusion in continuously changing environmental conditions, such as emotional stress, time of the day, and posture. BP variability is clinically relevant since it is coupled with vascular complications, e.g., stroke (25, 32). Moreover, the genetic determinants of BP responses to the environment may contribute to BP levels (6, 13).BP regulation requires ...

Adsorption of hydrogen on graphdiyne (GDY) and boron-graphdiyne (BGDY) doped with palladium clusters has been investigated by performing density functional calculations. Pd6 fits well on the large holes of those porous layers, preserving its octahedral structure in GDY and changing it to a capped trigonal bipyramid structure in BGDY. Pd6GDY adsorbs up to five H2 molecules with sizable adsorption energies, two dissociated and three nondissociated. The dissociation barrier of H2 on the Pd6GDY cluster is 0.58 eV. Pd6BGDY can adsorb up to six molecules, three dissociated and three nondissociated, and the dissociation barrier of H2 on Pd6BGDY is 0.23 eV. In both cases, the dissociation barriers are substantially smaller than the corresponding dissociation barriers on undoped GDY and BGDY. The Pd clusters saturated with hydrogen can be viewed as nanohydrides. Spilling of the adsorbed hydrogen atoms toward the GDY and BGDY substrates is hindered by large activation barriers. We then propose using BGDY and GDY layers as support platforms for metal nanohydrides. The amount of stored hydrogen using Pd as the dopant is below the target of 6% of hydrogen in weight, but replacing Pd by a lighter metal with similar or higher affinity for hydrogen would substantially enhance the storage.

Gender captures social components beyond biological sex and can add valuable insight to health studies in populations. However, assessment of gender typically relies on questionnaires which may not be available. The aim of this study is to construct a gender metric using available variables in the UK Biobank and to apply it to the study of angina diagnosis. Proxy variables for femininity characteristics were identified in the UK Biobank and regressed on sex to construct a composite femininity score (FS) validated using tenfold cross-validation. The FS was assessed as a predictor of angina diagnosis before incident myocardial infarction (MI) events. The FS was derived for 315,937 UK Biobank participants. In 3059 individuals with no history of MI at study entry who had an incident MI event, the FS was a significant predictor of angina diagnosis prior to MI (OR 1.24, 95% CI 1.10–1.39, P < 0.001) with a significant sex-by-FS interaction effect (P = 0.003). The FS was positively associated with angina diagnosis prior to MI in men (OR 1.37, 95% CI 1.19–1.57, P < 0.001), but not in women. We have provided a new tool to conduct gender-sensitive analyses in observational studies, and applied it to study of angina diagnosis prior to MI.

We conducted a genome-wide association study of time to remission of COVID-19 symptoms in 1723 outpatients with at least one risk factor for disease severity from the COLCORONA clinical trial. We found a significant association at 5p13.3 (rs1173773; P = 4.94 × 10−8) near the natriuretic peptide receptor 3 gene (NPR3). By day 15 of the study, 44%, 54% and 59% of participants with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. In 851 participants not treated with colchicine (placebo), there was a significant association at 9q33.1 (rs62575331; P = 2.95 × 10−8) in interaction with colchicine (P = 1.19 × 10−5) without impact on risk of hospitalisations, highlighting a possibly shared mechanistic pathway. By day 15 of the study, 46%, 62% and 64% of those with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. The findings need to be replicated and could contribute to the biological understanding of COVID-19 symptom remission.