Contrasting signals from multiple markers illuminate population connectivity in a marine fish

Recent advances in molecular biology and bioinformatics have helped to unveil striking and previously unrecognized patterns of geographic genetic structure in marine populations. Largely driven by the pressing needs of fisheries management and conservation, studies on marine fish populations have played a pivotal role in testing the efficiency of a range of approaches to explore connectivity and dispersal at sea. Here, we employed nuclear and mitochondrial DNA markers and parasitic infestations to examine the nature and patterns of population structure in a warm-temperate coastal marine teleost across major putative biogeographic barriers in the Mediterranean Sea and Eastern Atlantic Ocean. We detected deep genetic divergence between mitochondrial lineages, likely caused by dramatic climatic and geological transformations before and during the Pleistocene. Such long-diverged lineages later came into secondary contact and can now be found in sympatry. More importantly, microsatellite data revealed that these lineages, after millions of years of independent evolution, now interbreed extensively. By combining genetic and parasite data, we were able to identify at least five independent demographic units. While the different genetic and parasite-based methods produce notably contrasting signals and may complicate the reconstruction of connectivity dynamics, we show that by tailoring the correct interpretation to each of the descriptors used, it is possible to achieve a deeper understanding of the micro-evolutionary process and, consequently, resolve population structure

Vertebrate Vitellogenin Gene Duplication in Relation to the “3R Hypothesis”: Correlation to the Pelagic Egg and the Oceanic Radiation of Teleosts

The spiny ray-finned teleost fishes (Acanthomorpha) are the most successful group of vertebrates in terms of species diversity. Their meteoric radiation and speciation in the oceans during the late Cretaceous and Eocene epoch is unprecedented in vertebrate history, occurring in one third of the time for similar diversity to appear in the birds and mammals. The success of marine teleosts is even more remarkable considering their long freshwater ancestry, since it implies solving major physiological challenges when freely broadcasting their eggs in the hyper-osmotic conditions of seawater. Most extant marine teleosts spawn highly hydrated pelagic eggs, due to differential proteolysis of vitellogenin (Vtg)-derived yolk proteins. The maturational degradation of Vtg involves depolymerization of mainly the lipovitellin heavy chain (LvH) of one form of Vtg to generate a large pool of free amino acids (FAA 150–200 mM). This organic osmolyte pool drives hydration of the ooctye while still protected within the maternal ovary. In the present contribution, we have used Bayesian analysis to examine the evolution of vertebrate Vtg genes in relation to the “3R hypothesis” of whole genome duplication (WGD) and the functional end points of LvH degradation during oocyte maturation. We find that teleost Vtgs have experienced a post-R3 lineage-specific gene duplication to form paralogous clusters that correlate to the pelagic and benthic character of the eggs. Neo-functionalization allowed one paralogue to be proteolyzed to FAA driving hydration of the maturing oocytes, which pre-adapts them to the marine environment and causes them to float. The timing of these events matches the appearance of the Acanthomorpha in the fossil record. We discuss the significance of these adaptations in relation to ancestral physiological features, and propose that the neo-functionalization of duplicated Vtg genes was a key event in the evolution and success of the teleosts in the oceanic environment

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

Cluster headache genome-wide association study and meta-analysis identifies eight loci and implicates smoking as causal risk factor.

OBJECTIVE: Aggregating data for the first genome-wide association study meta-analysis of cluster headache, to identify genetic risk variants and gain biological insights. METHODS: A total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from ten European and one East Asian cohorts. We first performed an inverse-variance genome-wide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by five complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis and Mendelian randomization were part of the downstream analyses. RESULTS: The estimated SNP-based heritability of cluster headache was 14.5%. We identified nine independent signals in seven genome-wide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, ADHD, depression and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. INTERPRETATION: This first genome-wide association study meta-analysis gives clues to the biological basis of cluster headache and indicates that smoking is a causal risk factor. This article is protected by copyright. All rights reserved

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Alcohol, psychoactive substances and non-fatal road traffic accidents - a case-control study

<p>Abstract</p> <p>Background</p> <p>The prevalence of alcohol and other psychoactive substances is high in biological specimens from injured drivers, while the prevalence of these psychoactive substances in samples from drivers in normal traffic is low. The aim of this study was to compare the prevalence of alcohol and psychoactive substances in drivers admitted to hospital for treatment of injuries after road traffic accidents with that in drivers in normal traffic, and calculate risk estimates for the substances, and combinations of substances found in both groups.</p> <p>Methods</p> <p>Injured drivers were recruited in the hospital emergency department and drivers in normal conditions were taken from the hospital catchment area in roadside tests of moving traffic. Substances found in blood samples from injured drivers and oral fluid samples from drivers in moving traffic were compared using equivalent cut off concentrations, and risk estimates were calculated using logistic regression analyses.</p> <p>Results</p> <p>In 21.9% of the injured drivers, substances were found: most commonly alcohol (11.5%) and stimulants eg. cocaine or amphetamines (9.4%). This compares to 3.2% of drivers in normal traffic where the most commonly found substances were z-hypnotics (0.9%) and benzodiazepines (0.8%). The greatest increase in risk of being injured was for alcohol combined with any other substance (OR: 231.9, 95% CI: 33.3- 1615.4, p < 0.001), for more than three psychoactive substances (OR: 38.9, 95% CI: 8.2- 185.0, p < 0.001) and for alcohol alone (OR: 36.1, 95% CI: 13.2- 98.6, p < 0.001). Single use of non-alcohol substances was not associated with increased accident risk.</p> <p>Conclusion</p> <p>The prevalence of psychoactive substances was higher among injured drivers than drivers in normal moving traffic. The risk of accident is greatly increased among drivers who tested positive for alcohol, in particular, those who had also ingested one or more psychoactive substances. Various preventive measures should be considered to curb the prevalence of driving under the influence of psychoactive substances as these drivers constitute a significant risk for other road users as well as themselves.</p