RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (Pecten maximus) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher Fst values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying population structure and phenotypic plasticity in natural populations

What is the Role of Community Capabilities for Maternal Health? An Exploration of Community Capabilities as Determinants to Institutional Deliveries in Bangladesh, India, and Uganda

Background: While community capabilities are recognized as important factors in developing resilient health systems and communities, appropriate metrics for these have not yet been developed. Furthermore, the role of community capabilities on access to maternal health services has been underexplored. In this paper, we summarize the development of a community capability score based on the Future Health System (FHS) project’s experience in Bangladesh, India, and Uganda, and, examine the role of community capabilities as determinants of institutional delivery in these three contexts. Methods: We developed a community capability score using a pooled dataset containing cross-sectional household survey data from Bangladesh, India, and Uganda. Our main outcome of interest was whether the woman delivered in an institution. Our predictor variables included the community capability score, as well as a series of previously identified determinants of maternal health. We calculate both population-averaged effects (using GEE logistic regression), as well as sub-national level effects (using a mixed effects model). Results: Our final sample for analysis included 2775 women, of which 1238 were from Bangladesh, 1199 from India, and 338 from Uganda. We found that individual-level determinants of institutional deliveries, such as maternal education, parity, and ante-natal care access were significant in our analysis and had a strong impact on a woman’s odds of delivering in an institution. We also found that, in addition to individual-level determinants, greater community capability was significantly associated with higher odds of institutional delivery. For every additional capability, the odds of institutional delivery would increase by up to almost 6 %. Conclusion: Individual-level characteristics are strong determinants of whether a woman delivered in an institution. However, we found that community capability also plays an important role, and should be taken into account when designing programs and interventions to support institutional deliveries. Consideration of individual factors and the capabilities of the communities in which people live would contribute to the vision of supporting people-centered approaches to health

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher

<p>Abstract</p> <p>Background</p> <p>Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and <it>complete </it>loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.</p> <p>Methods</p> <p>Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.</p> <p>We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.</p> <p>Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.</p> <p>Results</p> <p>The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.</p> <p>Conclusions</p> <p>Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.</p

Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

Peer reviewedPublisher PD

Thousands of Rab GTPases for the Cell Biologist

Rab proteins are small GTPases that act as essential regulators of vesicular trafficking. 44 subfamilies are known in humans, performing specific sets of functions at distinct subcellular localisations and tissues. Rab function is conserved even amongst distant orthologs. Hence, the annotation of Rabs yields functional predictions about the cell biology of trafficking. So far, annotating Rabs has been a laborious manual task not feasible for current and future genomic output of deep sequencing technologies. We developed, validated and benchmarked the Rabifier, an automated bioinformatic pipeline for the identification and classification of Rabs, which achieves up to 90% classification accuracy. We cataloged roughly 8.000 Rabs from 247 genomes covering the entire eukaryotic tree. The full Rab database and a web tool implementing the pipeline are publicly available at www.RabDB.org. For the first time, we describe and analyse the evolution of Rabs in a dataset covering the whole eukaryotic phylogeny. We found a highly dynamic family undergoing frequent taxon-specific expansions and losses. We dated the origin of human subfamilies using phylogenetic profiling, which enlarged the Rab repertoire of the Last Eukaryotic Common Ancestor with Rab14, 32 and RabL4. Furthermore, a detailed analysis of the Choanoflagellate Monosiga brevicollis Rab family pinpointed the changes that accompanied the emergence of Metazoan multicellularity, mainly an important expansion and specialisation of the secretory pathway. Lastly, we experimentally establish tissue specificity in expression of mouse Rabs and show that neo-functionalisation best explains the emergence of new human Rab subfamilies. With the Rabifier and RabDB, we provide tools that easily allows non-bioinformaticians to integrate thousands of Rabs in their analyses. RabDB is designed to enable the cell biology community to keep pace with the increasing number of fully-sequenced genomes and change the scale at which we perform comparative analysis in cell biology

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies

Measurement of the inclusive isolated-photon cross section in pp collisions at √s = 13 TeV using 36 fb−1 of ATLAS data

The differential cross section for isolated-photon production in pp collisions is measured at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC using an integrated luminosity of 36.1 fb. The differential cross section is presented as a function of the photon transverse energy in different regions of photon pseudorapidity. The differential cross section as a function of the absolute value of the photon pseudorapidity is also presented in different regions of photon transverse energy. Next-to-leading-order QCD calculations from Jetphox and Sherpa as well as next-to-next-to-leading-order QCD calculations from Nnlojet are compared with the measurement, using several parameterisations of the proton parton distribution functions. The predictions provide a good description of the data within the experimental and theoretical uncertainties. [Figure not available: see fulltext.