Sex-Specific Embryonic Gene Expression in Species with Newly Evolved Sex Chromosomes

Sex chromosome dosage differences between females and males are a significant form of natural genetic variation in many species. Like many species with chromosomal sex determination, Drosophila females have two X chromosomes, while males have one X and one Y. Fusions of sex chromosomes with autosomes have occurred along the lineage leading to D. pseudoobscura and D. miranda. The resulting neo-sex chromosomes are gradually evolving the properties of sex chromosomes, and neo-X chromosomes are becoming targets for the molecular mechanisms that compensate for differences in X chromosome dose between sexes. We have previously shown that D. melanogaster possess at least two dosage compensation mechanisms: the well- characterized MSL-mediated dosage compensation active in most somatic tissues, and another system active during early embryogenesis prior to the onset of MSL-mediated dosage compensation. To better understand the developmental constraints on sex chromosome gene expression and evolution, we sequenced mRNA from individual male and female embryos of D. pseudoobscura and D. miranda, from ∼0.5 to 8 hours of development. Autosomal expression levels are highly conserved between these species. But, unlike D. melanogaster, we observe a general lack of dosage compensation in D. pseudoobscura and D. miranda prior to the onset of MSL-mediated dosage compensation. Thus, either there has been a lineage-specific gain or loss in early dosage compensation mechanism(s) or increasing X chromosome dose may strain dosage compensation systems and make them less effective. The extent of female bias on the X chromosomes decreases through developmental time with the establishment of MSL-mediated dosage compensation, but may do so more slowly in D. miranda than D. pseudoobscura. These results also prompt a number of questions about whether species with more sex-linked genes have more sex-specific phenotypes, and how much transcript level variance is tolerable during critical stages of development

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.status: publishe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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