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 reliable DNA barcode reference library for the identification of the North European shelf fish fauna

Valid fish species identification is an essential step both for fundamental science and fisheries management. The traditional identification is mainly based on external morphological diagnostic characters, leading to inconsistent results in many cases. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I (COI) for a valid identification of 93 North Atlantic fish species originating from the North Sea and adjacent waters, including many commercially exploited species. Neighbour-joining analysis based on K2P genetic distances formed nonoverlapping clusters for all species with a �99% bootstrap support each. Identification was successful for 100% of the species as the minimum genetic distance to the nearest neighbour always exceeded the maximum intraspecific distance. A barcoding gap was apparent for the whole data set. Within-species distances ranged from 0 to 2.35%, while interspecific distances varied between 3.15 and 28.09%. Distances between congeners were on average 51-fold higher than those within species. The validation of the sequence library by applying BOLDs barcode index number (BIN) analysis tool and a ranking system demonstrated high taxonomic reliability of the DNA barcodes for 85% of the investigated fish species. Thus, the sequence library presented here can be confidently used as a benchmark for identification of at least two-thirds of the typical fish species recorded for the North Sea