In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 -COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, but also in the design of accurate diagnostics.We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small-and large-scale intra-host variations in the viral genome. We identified tens of low-or higher-frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host but also strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene.Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements, reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Highlights SARS-CoV-2 exhibits intra-host small- and large-scale genomic variability. SNVs are collocalized with probes and primers used in molecular diagnostic assays. SARS-CoV-2 Spike (S) gene host a potential recombination hot-spot.

Hepatitis B Virus (HBV) is an Old World virus with a high mutation rate, which puts its origins in Africa alongside the origins of Homo sapiens, and is a member of the Hepadnaviridae family that is characterized by a unique viral replication cycle. It targets human hepatocytes and can lead to chronic HBV infection either after acute infection via horizontal transmission usually during infancy or childhood or via maternal–fetal transmission. HBV has been found in ~85% of HBV-related Hepatocellular Carcinomas (HCC), and it can integrate the whole or part of its genome into the host genomic DNA. The molecular mechanisms involved in the HBV DNA integration is not yet clear; thus, multiple models have been described with respect to either the relaxed-circular DNA (rcDNA) or the double-stranded linear DNA (dslDNA) of HBV. Various genes have been found to be affected by HBV DNA integration, including cell-proliferation-related genes, oncogenes and long non-coding RNA genes (lincRNAs). The present review summarizes the advances in the research of HBV DNA integration, focusing on the evolutionary and molecular side of the integration events along with the arising clinical aspects in the light of WHO’s commitment to eliminate HBV and viral hepatitis by 2030.

Background: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. Methods: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. Results: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50–100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0–19 y.o. decreased only in those regions where schools’ closure was combined with a lockdown. Conclusions: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.