Crykey: Comprehensive Identification of SARS-CoV-2 Cryptic Mutations in Wastewater (preprint)

We present Crykey, a computational tool for identifying SARS-CoV-2 cryptic mutations from wastewater. While previous exist for identifying cryptic mutations in specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of tracking cryptic mutations across the entire genome and at scale. Crykey fills this gap and leverages the co-occurrence of single nucleotide variants on the same read combined with variant frequency information. We evaluated Crykey on SARS-CoV-2 sequences from 3175 wastewater samples and more than 14000 clinical samples. Our results are threefold, we show: 1) Crykey can accurately identify cryptic lineages that are rare or missing in existing databases ; 2) the emergence of cryptic lineage can be related to increased transmission rates in the communities, and 3) some cryptic lineages in wastewater mirror intra-host low frequency co-occurring variants in individuals. In summary, Crykey facilitates rapid and comprehensive identification of SARS-CoV-2 cryptic mutations in wastewater samples.

Olivar: fully automated and variant aware primer design for multiplex tiled amplicon sequencing of pathogen genomes (preprint)

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of SARS-CoV-2 in real-time directly from environmental and clinical samples. Over 14 million SARS-CoV-2 genomes are now available on GISAID, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow, laborious, and costly. Here, we present Olivar, the first open-source computational tool capable of fully automating the design of tiled amplicons by integrating SNPs, non-specific amplification, etc. into a "risk score" for each single nucleotide of the target genome. Oli- var evaluates thousands sets of possible tiled amplicons and minimizes primer dimer in parallel. In a direct in-silico com- parison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used tiled amplicons for SARS-CoV-2 sequencing. We next tested Olivar on real wastewater samples and found that our automated approach had up to 3-fold higher map- ping rates compared to ARTIC v4.1 while retaining similar coverage. To the best of our knowledge, Olivar represents the first open-source, fully automated design tool that simultaneously evaluates and optimizes risks of known primer design issues for robust tiled amplicon sequencing. Olivar is available as a web application at https://olivar.rice.edu/. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https: //gitlab.com/treangenlab/olivar.

Patients with COVID-19 and HBV Coinfection are at Risk of Poor Prognosis (preprint)

Objective: Aim to study: 1. Whether there is a difference in the risk of death / critical illness between different stages of HBV (Resolved hepatitis B, HBeAg (-) CHB/infection, HBeAg (+) CHB/infection and HBV reactivation) coinfected with COVID-19; 2.If there is a difference, whether it is due to abnormal liver function and how much.Methods: This cohort study included all covid-19 inpatients of a single-center tertiary care academic hospital in Wuhan, Hubei, China, between February 4, 2020 and followed up to April 14, 2020. A total of 2899 COVID-19 patients were included as participants in this study and they were divided into five groups based on infection status of hepatitis B. Follow-up for mortality and ICU was carried out during hospitalization.Results: The median follow-up time was 39 (IQR,30-50) days with 66 deaths and 126 ICU. after adjustment, compared to patients without CHB, the hazard ratio (HR) for ICU was 8.02 (95% CI: 4.77-13.49) for patients with HBeAg (+) CHB/infection, and 5.15 (95% CI: 1.66-16.02) for those with HBV reactivation. And HR for death was 11.57 (95% CI: 6.30-21.26) for patients with HBeAg (+) CHB/infection. The results of mediating effect indicated the total effect of HBeAg (+) CHB/infection on death/ICU is partially mediated by abnormal liver function, accounted for 79.60% and 73.53%, respectively.Conclusion: COVID-19 patients coinfected with HBV at HBeAg (+) CHB/infection stage will increase the risk of poor prognosis, and abnormal liver function partially mediates the increased risk effect of poor prognosis caused by the coinfection.Funding: None to declare. Declaration of Interest: None to declare. Ethical Approval: This study was approved by the Medical Ethics Committee of the Chinese PLA General Hospital.

Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data (preprint)

Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost, exemplified by well over a half of million ONT SARS-COV-2 datasets. Tracking low frequency intra-host variants has provided important insights with respect to elucidating within host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluated Variabel on both within patient and across patient paired Illumina and ONT datasets; our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission (preprint)

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.