Croda, J. | bioRxiv Science

bioRxiv2020

Genomic surveillance of SARS-CoV-2 reveals community transmission of a major lineage during the early pandemic phase in Brazil

Despite all efforts to control the COVID-19 spread, the SARS-CoV-2 reached South America within three months after its first detection in China, and Brazil became one of the hotspots of COVID-19 in the world. Several SARS-CoV-2 lineages have been identified and some local clusters have been described in this early pandemic phase in Western countries. Here we investigated the genetic diversity of SARS-CoV-2 during the early phase (late February to late April) of the epidemic in Brazil. Phylogenetic analyses revealed multiple introductions of SARS-CoV-2 in Brazil and the community transmission of a major B.1.1 lineage defined by two amino acid substitutions in the Nucleocapsid and ORF6. This SARS-CoV-2 Brazilian lineage was probably established during February 2020 and rapidly spread through the country, reaching different Brazilian regions by the middle of March 2020. Our study also supports occasional exportations of this Brazilian B.1.1 lineage to neighboring South American countries and to more distant countries before the implementation of international air travels restrictions in Brazil.

evolutionary biology↗

bioRxiv2019

Genomic variant identification methods alter Mycobacterium tuberculosis transmission inference

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet there is no current consensus on how to measure genomic variation. We investigated the effects of variant identification approaches on transmission inferences for M. tuberculosis by comparing variants identified by five different groups in the same sequence data from a clonal outbreak. We then measured the performance of commonly used variant calling approaches in recovering variation in a simulated tuberculosis outbreak and tested the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant calling approaches used by different groups do not recover consistent sets of variants, often leading to conflicting transmission inferences. Further, performance in recovering true outbreak variation varied widely across approaches. Finally, stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. We conclude that measurements of genetic distance and phylogenetic structure are dependent on variant calling approach. Variant calling algorithms trained upon true sequence data outperform other approaches and enable inclusion of repetitive regions typically excluded from genomic epidemiology studies, maximizing the information gleaned from outbreak genomes.

genomics↗