Volume 17. Article 1. Oceanography of Long Island Sound.

https://elischolar.library.yale.edu/bulletin_yale_bingham_oceanographic_collection/1157/thumbnail.jp

A Three-Stage Colonization Model for the Peopling of the Americas

Background: We evaluate the process by which the Americas were originally colonized and propose a three-stage model that integrates current genetic, archaeological, geological, and paleoecological data. Specifically, we analyze mitochondrial and nuclear genetic data by using complementary coalescent models of demographic history and incorporating nongenetic data to enhance the anthropological relevance of the analysis. Methodology/Findings: Bayesian skyline plots, which provide dynamic representations of population size changes over time, indicate that Amerinds went through two stages of growth <40,000 and <15,000 years ago separated by a long period of population stability. Isolation-with-migration coalescent analyses, which utilize data from sister populations to estimate a divergence date and founder population sizes, suggest an Amerind population expansion starting <15,000 years ago. Conclusions/Significance: These results support a model for the peopling of the New World in which Amerind ancestors diverged from the Asian gene pool prior to 40,000 years ago and experienced a gradual population expansion as they moved into Beringia. After a long period of little change in population size in greater Beringia, Amerinds rapidly expanded into the Americas <15,000 years ago either through an interior ice-free corridor or along the coast. This rapid colonization of the New World was achieved by a founder group with an effective population size of <1,000–5,400 individuals. Our model presents a detailed scenario for the timing and scale of the initial migration to the Americas, substantially refines th

Melanesian mtDNA Complexity

Melanesian populations are known for their diversity, but it has been hard to grasp the pattern of the variation or its underlying dynamic. Using 1,223 mitochondrial DNA (mtDNA) sequences from hypervariable regions 1 and 2 (HVR1 and HVR2) from 32 populations, we found the among-group variation is structured by island, island size, and also by language affiliation. The more isolated inland Papuan-speaking groups on the largest islands have the greatest distinctions, while shore dwelling populations are considerably less diverse (at the same time, within-group haplotype diversity is less in the most isolated groups). Persistent differences between shore and inland groups in effective population sizes and marital migration rates probably cause these differences. We also add 16 whole sequences to the Melanesian mtDNA phylogenies. We identify the likely origins of a number of the haplogroups and ancient branches in specific islands, point to some ancient mtDNA connections between Near Oceania and Australia, and show additional Holocene connections between Island Southeast Asia/Taiwan and Island Melanesia with branches of haplogroup E. Coalescence estimates based on synonymous transitions in the coding region suggest an initial settlement and expansion in the region at ∼30–50,000 years before present (YBP), and a second important expansion from Island Southeast Asia/Taiwan during the interval ∼3,500–8,000 YBP. However, there are some important variance components in molecular dating that have been overlooked, and the specific nature of ancestral (maternal) Austronesian influence in this region remains unresolved

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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 hospitalization2–4 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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Development of hydrocephalus and classical hypothesis of cerebrospinal fluid hydrodynamics: facts and illusions

According to the classical hypothesis of the cerebrospinal fluid (CSF) hydrodynamics, CSF is produced inside the brain ventricles, than it circulates like a slow river toward the cortical subarachnoid space, and finally it is absorbed into the venous sinuses. Some pathological conditions, primarily hydrocephalus, have also been interpreted based on this hypothesis. The development of hydrocephalus is explained as an imbalance between CSF formation and absorption, where more CSF is formed than is absorbed, which results in an abnormal increase in the CSF volume inside the cranial CSF spaces. It is believed that the reason for the imbalance is the obstruction of the CSF pathways between the site of CSF formation and the site of its absorption, which diminishes or prevents CSF outflow from the cranium. In spite of the general acceptance of the classical hypothesis, there are a considerable number of experimental results that do not support such a hypothesis and the generally accepted pathophysiology of hydrocephalus. A recently proposed new working hypothesis suggests that osmotic and hydrostatic forces at the central nervous system microvessels are crucial for the regulation of interstial fluid and CSF volume which constitute a functional unit. Based on that hypothesis, the generally accepted mechanisms of hydrocephalus development are not plausible. Therefore, the recent understanding of the correlation between CSF physiology and the development of hydrocephalus has been thoroughly presented, analyzed and evaluated, and new insights into hydrocephalus etiopathology have been proposed, which are in accordance with the experimental data and the new working hypothesis