An elevated level of viral diversity was found in some SARS-CoV-2 infected patients, indicating the risk of rapid evolution of the virus. Although no evidence for the transmission of intra-host variants was found, the risk should not be overlooked. Abstract:Background A novel coronavirus (SARS-CoV-2) has infected more than 75,000 individuals and spread to over 20 countries. It is still unclear how fast the virus evolved and how the virus interacts with other microorganisms in the lung. MethodsWe have conducted metatranscriptome sequencing for the bronchoalveolar lavage fluid of eight SARS-CoV-2 patients, 25 community-acquired pneumonia (CAP) patients, and 20 healthy controls. ResultsThe median number of intra-host variants was 1-4 in SARS-CoV-2 infected patients, which ranged between 0 and 51 in different samples. The distribution of variants on genes was similar to those observed in the population data (110 sequences).However, very few intra-host variants were observed in the population as polymorphism, implying either a bottleneck or purifying selection involved in the transmission of the virus, or a consequence of the limited diversity represented in the current polymorphism data. Although current evidence did not support the transmission of intra-host variants in a person-to-person spread, the risk should not be overlooked.The microbiota in SARS-CoV-2 infected patients was similar to those in CAP, either dominated by the pathogens or with elevated levels of oral and upper respiratory commensal bacteria.Conclusion SARS-CoV-2 evolves in vivo after infection, which may affect its virulence, infectivity, and transmissibility. Although how the intra-host variant spreads in the population is still elusive, it is necessary to strengthen the surveillance of the viral Downloaded from https://academic.oup.com/cid/advance-article-abstract/doi/10.1093/cid/ciaa203/5780800 by guest on 16 March 2020 4 evolution in the population and associated clinical changes.

With expanding applications of next-generation sequencing in medical genetics, increasing computational methods are being developed to predict the pathogenicity of missense variants. Selecting optimal methods can accelerate the identification of candidate genes. However, the performances of different computational methods under various conditions have not been completely evaluated. Here, we compared 12 performance measures of 23 methods based on three independent benchmark datasets: (i) clinical variants from the ClinVar database related to genetic diseases, (ii) somatic variants from the IARC TP53 and ICGC databases related to human cancers and (iii) experimentally evaluated PPARG variants. Some methods showed different performances under different conditions, suggesting that they were not always applicable for different conditions. Furthermore, the specificities were lower than the sensitivities for most methods (especially, for the experimentally evaluated benchmark datasets), suggesting that more rigorous cutoff values are necessary to distinguish pathogenic variants. Furthermore, REVEL, VEST3 and the combination of both methods (i.e. ReVe) showed the best overall performances with all the benchmark data. Finally, we evaluated the performances of these methods with de novo mutations, finding that ReVe consistently showed the best performance. We have summarized the performances of different methods under various conditions, providing tentative guidance for optimal tool selection.

A growing number of genomic tools and databases were developed to facilitate the interpretation of genomic variants, particularly in coding regions. However, these tools are separately available in different online websites or databases, making it challenging for general clinicians, geneticists and biologists to obtain the first-hand information regarding some particular variants and genes of interest. Starting with coding regions and splice sties, we artificially generated all possible single nucleotide variants (n = 110 154 363) and cataloged all reported insertion and deletions (n = 1 223 370). We then annotated these variants with respect to functional consequences from more than 60 genomic data sources to develop a database, named VarCards (http://varcards.biols.ac.cn/), by which users can conveniently search, browse and annotate the variant- and gene-level implications of given variants, including the following information: (i) functional effects; (ii) functional consequences through different in silico algorithms; (iii) allele frequencies in different populations; (iv) disease- and phenotype-related knowledge; (v) general meaningful gene-level information; and (vi) drug–gene interactions. As a case study, we successfully employed VarCards in interpretation of de novo mutations in autism spectrum disorders. In conclusion, VarCards provides an intuitive interface of necessary information for researchers to prioritize candidate variations and genes.

Synaptic cytoskeleton dysfunction represents a common pathogenesis in neurodevelopmental disorders, such as autism spectrum disorder (ASD). The serine/threonine kinase PAK2 is a critical regulator of cytoskeleton dynamics. However, its function within the central nervous system and its role in ASD pathogenesis remain undefined. Here, we found that Pak2 haploinsufficiency resulted in markedly decreased synapse densities, defective long-term potentiation, and autism-related behaviors in mice. Phosphorylation levels of key actin regulators LIMK1 and cofilin, together with their mediated actin polymerization, were reduced in Pak2mice. We identified one de novo PAK2 nonsense mutation that impaired PAK2 function in vitro and in vivo and four de novo copy-number deletions containing PAK2 in large cohorts of patients with ASD. PAK2 deficiency extensively perturbed functional networks associated with ASD by regulating actin cytoskeleton dynamics. Our genetic and functional results demonstrate a critical role of PAK2 in brain development and autism pathogenesis.

Autism spectrum disorder (ASD) represents a set of complex neurodevelopmental disorders with large degrees of heritability and heterogeneity. We sequenced 136 microcephaly or macrocephaly (Mic-Mac)-related genes and 158 possible ASD-risk genes in 536 Chinese ASD probands and detected 22 damaging de novo mutations (DNMs) in 20 genes, including CHD8 and SCN2A, with recurrent events. Nine of the 20 genes were previously reported to harbor DNMs in ASD patients from other populations, while 11 of them were first identified in present study. We combined genetic variations of the 294 sequenced genes from publicly available whole-exome or whole-genome sequencing studies (4167 probands plus 1786 controls) with our Chinese population (536 cases plus 1457 controls) to optimize the power of candidate-gene prioritization. As a result, we prioritized 67 ASD-candidate genes that exhibited significantly higher probabilities of haploinsufficiency and genic intolerance, and significantly interacted and co-expressed with each another, as well as other known ASD-risk genes. Probands with DNMs or rare inherited mutations in the 67 candidate genes exhibited significantly lower intelligence quotients, supporting their strong functional impact. In addition, we prioritized 39 ASD-related Mic-Mac-risk genes, and showed their interaction and co-expression in a functional network that converged on chromatin remodeling, synapse transmission and cell cycle progression. Genes within the three functional subnetworks exhibited distinct and recognizable spatiotemporal-expression patterns in human brains and laminar-expression profiles in the developing neocortex, highlighting their important roles in brain development. Our results indicate some of Mic-Mac-risk genes are involved in ASD.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a male-to-female prevalence of 4:1. However, the genetic mechanisms underlying this gender difference remain unclear. Mutation burden analysis, a TADA model, and co-expression and functional network analyses were performed on de novo mutations (DNMs) and corresponding candidate genes. We found that the prevalence of putative functional DNMs (loss-of-function and predicted deleterious missense mutations) in females was significantly higher than that in males, suggesting that a higher genetic load was required in females to reach the threshold for a diagnosis. We then prioritized 174 candidate genes, including 60 shared genes, 91 male-specific genes, and 23 female-specific genes. All of the three subclasses of candidate genes were significantly more frequently co-expressed in female brains than male brains, suggesting that compensation effects of the deficiency of ASD candidate genes may be more likely in females. Nevertheless, the three subclasses of candidate genes were co-expressed with each other, suggesting a convergent functional network of male and female-specific genes. Our analysis of different aspects of genetic components provides suggestive evidence supporting the female-protective effect in ASD. Moreover, further study is needed to integrate neuronal and hormonal data to elucidate the underlying gender difference in ASD.

Impact: This study demonstrates the association between the upper respiratory tract microbiota and the prognosis in COVID-19. A higher abundance of Streptococcus on admission predicts a lower mortality rate. The upper respiratory tract microbiota may reflect

Circadian rhythms govern various kinds of physiological and behavioral functions of the living organisms, and disruptions of the rhythms are highly detrimental to health. Although several databases have been built for circadian genes, a resource for comprehensive post-transcriptional regulatory information of circadian RNAs and expression patterns of disease-related circadian RNAs is still lacking. Here, we developed CirGRDB (http://cirgrdb.biols.ac.cn) by integrating more than 4936 genome-wide assays, with the aim of fulfilling the growing need to understand the rhythms of life. CirGRDB presents a friendly web interface that allows users to search and browse temporal expression patterns of interested genes in 37 human/mouse tissues or cell lines, and three clinical disorders including sleep disorder, aging and tumor. More importantly, eight kinds of potential transcriptional and post-transcriptional regulators involved in the rhythmic expression of the specific genes, including transcription factors, histone modifications, chromatin accessibility, enhancer RNAs, miRNAs, RNA-binding proteins, RNA editing and RNA methylation, can also be retrieved. Furthermore, a regulatory network could be generated based on the regulatory information. In summary, CirGRDB offers a useful repository for exploring disease-related circadian RNAs, and deciphering the transcriptional and post-transcriptional regulation of circadian rhythms.