NET-Seq

CirSeq

CirSeq accurately identifies ultra-rare and low-frequency genetic variants in RNA viruses. The method uses a unique step for circularization of fragmented viral RNAs, followed by rolling-circle RT. , CirSeq corrects for mutations introduced during its amplification steps by aligning the tandem-repeat sequences with each other and excluding those reads using informatics tools. First, single-stranded RNAs are fragmented using Zn²⁺ and size-selected to no more than one-third of the sequencing read length. Next, they are circularized and reverse-transcribed using random primers. Rolling-circle RT is used to generate tandem-repeat cDNA strands. The first-strand cDNAs are amplified, generating double-stranded cDNAs, followed by end repair, poly(A) tailing, and adapter ligation. The cDNA libraries are ready for sequencing.

Pros:

• Detects ultra-rare and low-frequency genetic variants in RNA viruses
• Rolling-circle RT creates tandem-repeat cDNAs that can be used to correct artificial mutations
• Error rates reported are far below those observed using standard RNA virus sequencing methods

Cons:

• Whole process takes ~5 days
• Unsuitable for sequencing clinical isolates, because it needs large quantities of purified viral RNAs
• Not applicable for de novo sequencing of viral RNAs

• CirSeq: Acevedo A., Brodsky L. and Andino R. Mutational and fitness landscapes of an RNA virus revealed through population sequencing. Nature. 2014;505:686-690
• CirSeq Protocol: Acevedo A. and Andino R. Library preparation for highly accurate population sequencing of RNA viruses. Nat Protoc. 2014;9:1760-1769

1. Posada-Cespedes S., Seifert D. and Beerenwinkel N. Recent advances in inferring viral diversity from high-throughput sequencing data. Virus Res. 2016;
2. Andino R. and Domingo E. Viral quasispecies. Virology. 2015;479-480C:46-51
3. Gordon A. J., Satory D., Halliday J. A. and Herman C. Lost in transcription: transient errors in information transfer. Curr Opin Microbiol. 2015;24C:80-87

1. Acevedo A., Brodsky L. and Andino R. Mutational and fitness landscapes of an RNA virus revealed through population sequencing. Nature. 2014;505:686-690
2. Wang K., Ma Q., Jiang L., et al. Ultra-precise detection of mutations by droplet-based amplification of circularized DNA. BMC Genomics. 2016;17:214