71 research outputs found
Phylotranscriptomics to Bring the Understudied into the Fold: Monophyletic Ostracoda, Fossil Placement, and Pancrustacean Phylogeny
An ambitious, yet fundamental goal for comparative biology is to understand the evolutionary relationships for all of life. However, many important taxonomic groups have remained recalcitrant to inclusion into broader scale studies. Here, we focus on collection of 9 new 454 transcriptome data sets from Ostracoda, an ancient and diverse group with a dense fossil record, which is often undersampled in broader studies. We combine the new transcriptomes with a new morphological matrix (including fossils) and existing expressed sequence tag, mitochondrial genome, nuclear genome, and ribosomal DNA data. Our analyses lead to new insights into ostracod and pancrustacean phylogeny. We obtained support for three epic pancrustacean clades that likely originated in the Cambrian: Oligostraca (Ostracoda, Mystacocarida, Branchiura, and Pentastomida); Multicrustacea (Copepoda, Malacostraca, and Thecostraca); and a clade we refer to as Allotriocarida (Hexapoda, Remipedia, Cephalocarida, and Branchiopoda). Within the Oligostraca clade, our results support the unresolved question of ostracod monophyly. Within Multicrustacea, we find support for Thecostraca plus Copepoda, for which we suggest the name Hexanauplia. Within Allotriocarida, some analyses support the hypothesis that Remipedia is the sister taxon to Hexapoda, but others support Branchiopoda + Cephalocarida as the sister group of hexapods. In multiple different analyses, we see better support for equivocal nodes using slow-evolving genes or when excluding distant outgroups, highlighting the increased importance of conditional data combination in this age of abundant, often anonymous data. However, when we analyze the same set of species and ignore rate of gene evolution, we find higher support when including all data, more in line with a “total evidence” philosophy. By concatenating molecular and morphological data, we place pancrustacean fossils in the phylogeny, which can be used for studies of divergence times in Pancrustacea, Arthropoda, or Metazoa. Our results and new data will allow for attributes of Ostracoda, such as its amazing fossil record and diverse biology, to be leveraged in broader scale comparative studies. Further, we illustrate how adding extensive next-generation sequence data from understudied groups can yield important new phylo- genetic insights into long-standing questions, especially when carefully analyzed in combination with other data
Diversity in genetic risk of recurrent stroke: a genome-wide association study meta-analysis
IntroductionStroke is a leading cause of death and disability worldwide. Recurrent strokes are seven times more lethal than initial ones, with 54% leading to long-term disability. Substantial recurrent stroke risk disparities exist among ancestral groups. Notably, Africans face double the risk and higher fatality rates compared to Europeans. Although genetic studies, particularly GWAS, hold promise for uncovering biological insights into recurrent stroke, they remain underexplored. Our study addresses this gap through meta-analyses of recurrent stroke GWAS, considering specific ancestral groups and a combined approach.MethodsWe utilized four independent study cohorts for African, European, and Combined ancestry recurrent stroke GWAS with genotyping, imputation, and strict quality control. We harmonized recurrent stroke phenotype and effect allele estimates across cohorts. The logistic regression GWAS model was adjusted for age, sex, and principal components. We assessed how well genetic risk of stroke informs recurrent stroke risk using Receiver Operating Characteristic (ROC) curve analysis with the GIGASTROKE Consortium's polygenic risk scores (PRS).ResultsHarmonization included 4,420 participants (818 African ancestry and 3,602 European ancestry) with a recurrent stroke rate of 16.8% [median age 66.9 (59.1, 73.6) years; 56.2% male]. We failed to find genome-wide significant variants (p < 5e−8). However, we found 18 distinct suggestive (p < 5e−6) genetic loci with high biological relevance consistent across African and European ancestries, including PPARGC1B, CCDC3, OPRL1, and MYH11 genes. These genes affect vascular stenosis through constriction and dilation. We also observed an association with SDK1 gene, which has been previous linked with hypertension in Nigerian and Japanese populations). ROC analysis showed poor performance of the ischemic stroke PRS in discriminating recurrent stroke status (area under the curve = 0.48).DiscussionOur study revealed genetic associations with recurrent stroke not previously associated with incident ischemic stroke. We found suggestive associations in genes previously linked with hypertension. We also determined that knowing the genetic risk of incident stroke does currently not inform recurrent stroke risk. We urgently need more studies to understand better the overlap or lack thereof between incident and recurrent stroke biology
Cephalopod genomics: a plan of strategies and organization
The Cephalopod Sequencing Consortium (CephSeq Consortium) was established at a NESCent Catalysis Group Meeting, "Paths to Cephalopod Genomics-Strategies, Choices, Organization," held in Durham, North Carolina, USA on May 24-27, 2012. Twenty-eight participants representing nine countries (Austria, Australia, China, Denmark, France, Italy, Japan, Spain and the USA) met to address the pressing need for genome sequencing of cephalopod mollusks. This group, drawn from cephalopod biologists, neuroscientists, developmental and evolutionary biologists, materials scientists, bioinformaticians and researchers active in sequencing, assembling and annotating genomes, agreed on a set of cephalopod species of particular importance for initial sequencing and developed strategies and an organization (CephSeq Consortium) to promote this sequencing. The conclusions and recommendations of this meeting are described in this white paper
Cephalopod genomics : a plan of strategies and organization
© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Standards in Genomic Sciences 7 (2012): 175-188, doi:10.4056/sigs.3136559.The Cephalopod Sequencing Consortium (CephSeq Consortium) was established at a NESCent Catalysis Group Meeting, “Paths to Cephalopod Genomics- Strategies, Choices, Organization,” held in Durham, North Carolina, USA on May 24-27, 2012. Twenty-eight participants representing nine countries (Austria, Australia, China, Denmark, France, Italy, Japan, Spain and the USA) met to address the pressing need for genome sequencing of cephalopod molluscs. This group, drawn from cephalopod biologists, neuroscientists, developmental and evolutionary biologists, materials scientists, bioinformaticians and researchers active in sequencing, assembling and annotating genomes, agreed on a set of cephalopod species of particular importance for initial sequencing and developed strategies and an organization (CephSeq Consortium) to promote this sequencing. The conclusions and recommendations of this meeting are described in this White Paper.The Catalysis Group Meeting was supported by the National Science Foundation through the National Evolutionary Synthesis Center (NESCent) under grant number NSF #EF-0905606
Mapping 123 million neonatal, infant and child deaths between 2000 and 2017
Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations
Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care
New genetic loci link adipose and insulin biology to body fat distribution.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p
Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes
AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p < 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p > 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec
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