Summary The emergence of the novel SARS coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19) 1 . The development of a vaccine is likely to require at least 12-18 months, and the typical timeline for approval of a novel antiviral therapeutic can exceed 10 years. Thus, repurposing of known drugs could significantly accelerate the deployment of novel therapies for COVID-19. Towards this end, we profiled a library of known drugs encompassing approximately 12,000 clinical-stage or FDA-approved small molecules. We report the identification of 100 molecules that inhibit viral replication, including 21 known drugs that exhibit dose response relationships. Of these, thirteen were found to harbor effective concentrations likely commensurate with achievable therapeutic doses in patients, including the PIKfyve kinase inhibitor apilimod 2 – 4 , and the cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825, and ONO 5334. Notably, MDL-28170, ONO 5334, and apilimod were found to antagonize viral replication in human iPSC-derived pneumocyte-like cells, and the PIKfyve inhibitor also demonstrated antiviral efficacy in a primary human lung explant model. Since most of the molecules identified in this study have already advanced into the clinic, the known pharmacological and human safety profiles of these compounds will enable accelerated preclinical and clinical evaluation of these drugs for the treatment of COVID-19.

CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.

Summary Two decades of research identified more than a dozen clock genes and defined a biochemical feedback mechanism of circadian oscillator function. To identify additional clock genes and modifiers, we conducted a genome-wide siRNA screen in a human cellular clock model. Knockdown of nearly a thousand genes reduced rhythm amplitude. Potent effects on period length or increased amplitude were less frequent; we found hundreds of these and confirmed them in secondary screens. Characterization of a subset of these genes demonstrated a dosage-dependent effect on oscillator function. Protein interaction network analysis showed that dozens of gene products directly or indirectly associate with known clock components. Pathway analysis revealed these genes are overrepresented for components of insulin and hedgehog signaling, the cell cycle, and the folate metabolism. Coupled with data showing many of these pathways are clock-regulated, we conclude the clock is interconnected with many aspects of cellular function.

BioGPS (http://biogps.org) is a centralized gene-annotation portal that enables researchers to access distributed gene annotation resources. This article focuses on the updates to BioGPS since our last paper (2013 database issue). The unique features of BioGPS, compared to those of other gene portals, are its community extensibility and user customizability. Users contribute the gene-specific resources accessible from BioGPS (‘plugins’), which helps ensure that the resource collection is always up-to-date and that it will continue expanding over time (since the 2013 paper, 162 resources have been added, for a 34% increase in the number of resources available). BioGPS users can create their own collections of relevant plugins and save them as customized gene-report pages or ‘layouts’ (since the 2013 paper, 488 user-created layouts have been added, for a 22% increase in the number of layouts). In addition, we recently updated the most popular plugin, the ‘Gene expression/activity chart’, to include ∼6000 datasets (from ∼2000 datasets) and we enhanced user interactivity. We also added a new ‘gene list’ feature that allows users to save query results for future reference.

We combined large-scale mRNA expression analysis and gene mapping to identify genes and loci that control hematopoietic stem cell (HSC) function. We measured mRNA expression levels in purified HSCs isolated from a panel of densely genotyped recombinant inbred mouse strains. We mapped quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts. By comparing the physical transcript position with the location of the controlling QTL, we identified polymorphic cis-acting stem cell genes. We also identified multiple trans-acting control loci that modify expression of large numbers of genes. These groups of coregulated transcripts identify pathways that specify variation in stem cells. We illustrate this concept with the identification of candidate genes involved with HSC turnover. We compared expression QTLs in HSCs and brain from the same mice and identified both shared and tissue-specific QTLs. Our data are accessible through WebQTL, a web-based interface that allows custom genetic linkage analysis and identification of coregulated transcripts.