No abstract

Genome sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2,951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in non-essential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes, and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.

ARS-CoV-2 is the causal agent for COVID-19, and the World Health Organization classifies this virus as an airborne pathogen transmitted by asymptomatic, pre-symptomatic and symptomatic individuals through close contact via exposure to infected droplets and aerosols 1,2 . Although SARS-CoV-2 transmission can occur by activities involving the oral cavity, such as speaking, breathing, coughing, sneezing and even singing [3][4][5] , most attention has focused on the nasal-lung axis of infection 6 . Oral manifestations, such as taste loss, dry mouth and oral lesions, are evident in about half of COVID-19 cases [7][8][9] , although it remains unknown whether SARS-CoV-2 can directly infect and replicate in oral tissues, such as the salivary glands (SGs) or mucosa. This is critical because, if these are sites of early infection, they could play an important role in transmitting the virus to the lungs or the gastrointestinal tract via saliva, as has been suggested for other microbial-associated diseases, such as pneumonia 10 and inflammatory bowel diseases 11,12 (Extended Data Fig. 1a).SARS-CoV-2 uses host entry factors, such as ACE2 and TMPRSS family members (TMPRSS2 and TMPRSS4) 13,14 , and understanding the cell types that harbor these receptors is important for determining infection susceptibilities throughout the body [15][16][17] . ACE2 and TMPRSS2 expression has been reported in oral tissues 18,19 ; however, there are no comprehensive descriptions of viral entry factor expression nor direct confirmation of SARS-CoV-2 infection in oral tissues. We hypothesized that SGs and barrier epithelia of the oral cavity and oropharynx can be infected by SARS-CoV-2 and contribute to the transmission of SARS-CoV-2. To test this, we generated two human oral single-cell RNA sequencing (scRNA-seq) atlases to predict cell-specific susceptibilities to SARS-CoV-2 infection. We confirmed ACE2 and TMPRSS expression in SGs and oral mucosa epithelia. SARS-CoV-2 infection was confirmed using autopsy and outpatient samples. Saliva from asymptomatic individuals with COVID-19 demonstrated the potential for viral transmission. In a prospective clinical cohort, we found a positive correlation between salivary viral load and taste loss; we also demonstrated persistent salivary antibody responses to SARS-CoV-2 nucleocapsid and spike proteins. ResultsOral tissue atlases reveal resident immune cells and niche-specific epithelial diversity. The SGs and the barrier mucosa of the oral cavity and oropharynx are likely gateways for viral infection, replication SARS-CoV-2 infection of the oral cavity and saliva

Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules1. Although many editing sites have recently been discovered2–7, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood8–10. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.